2026-08-27T07:15:54Z https://ijeresm.com/oai-pmh.php

oai:ijeresm.com:11012022-03-31

A Study on the Association between Awareness of Investors and Demographic Factors towards Gold ETFs, Gold Bonds, and Gold DepositsSreenivasulu SunkaraM. Sreenivasa ReddyGold is one of the valuable metals and an important asset class for investors. People in India are emotionally attached to gold. Thousands of tonnes of idle gold are lying with Indian temples, trusts, and individuals. Investors consider capital appreciation; interest income and safety are major factors that influence buying of gold. India is one of the biggest importers of gold every year. The government of India has introduced a few gold-related schemes to reduce gold imports. Sovereign gold bond scheme and Re-vamped gold deposit scheme are introduced in the year 2015 under the Swarna Bharath initiative. The present study is an attempt to find the association between awareness of investors and demographic factors towards gold ETFs, gold bonds, and gold deposits. The results reveal that there is a significant association at a 5% significance level between awareness of investors and all demographic factors used in the study except the gender of the respondent.Gold ETFsGold BondsGold DepositsAwarenessSwarna BharatJPM Publishers2022-03-31International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/1101-2/https://ijeresm.com/wp-content/uploads/2022/04/ERESM11200301-1-4.pdfhttps://doi.org/10.58482/ijeresm.v1i1.110.58482/ijeresm.v1i1.1Vol. 1, Issue 1, pp. 01-04

oai:ijeresm.com:11022022-03-31

Design and Implementation of New Biorthogonal Wavelets and its Application to Image ProcessingE Sasikala ReddyTVV SathyanarayanaWavelet transformation has been an interesting field since its exposure with wavelet-based compression standard embedded zerotree wavelet. Though, the origin of wavelets back to many decades, the presence of research at the very beginning of wavelet bases is also being carried out in the research community. This is because of the wide presence of its applicability as well as its structure of adapting to the type of problem at hand. In this paper, an approach of designing biorthogonal wavelets is presented. This approach may be extended to design variety of wavelets. This paper mainly focus on the design steps and corresponding coding in MATLAB. By varying the length, type of the bases and other parameters, different wavelets may be devised.Biorthogonal waveletsSpline functionwavelet basewavelet designJPM Publishers2022-03-31International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/1102-2/https://ijeresm.com/wp-content/uploads/2022/04/ERESM11230301-5-10.pdfhttps://doi.org/10.58482/ijeresm.v1i1.210.58482/ijeresm.v1i1.2Vol. 1, Issue 1, pp. 05-10

oai:ijeresm.com:11032022-03-31

Design of Biorthogonal Wavelets based on Spline and Spline-like Functions for Image CompressionK SubramanyamT RamasriWavelet theory inspired from Fourier analysis is based on the basis function and its properties. Different wavelets use different basis functions which may better suit to some applications. The properties of basis functions along with their shape and magnification effects the performance of an application. The standard biorthogonal wavelets utilize spline functions for their construction. In this paper first the design procedure of biorthogonal wavelets is presented. Then a modified spline function is proposed. Based on the proposed spline function, three biorthogonal wavelets are designed with different length. The performance of proposed wavelets is analyzed by applying them on to images for SPIHT compression. The simulation results shown that the proposed wavelets have performed well compared to that of standard spline based biorthogonal wavelets.spline-like functionbiorthogonalitysymmetrynormalityJPM Publishers2022-03-31International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/1103-2/https://ijeresm.com/wp-content/uploads/2022/04/ERESM11230302-11-17.pdfhttps://doi.org/10.58482/ijeresm.v1i1.310.58482/ijeresm.v1i1.3Vol. 1, Issue 1, pp. 11-17

oai:ijeresm.com:11042022-03-31

Layer Decomposition based Local Tone Mapping OperatorZonnavada ChaithanyaG SreenivasuluDynamic range of an image directly defines the number of levels it can accommodate in an image. In general, a dynamic range of 256 is in use. Defining dynamic range of an image need to be done by considering the display unit on which the image will be displayed on. If the dynamic range extends over 256, the dynamic range is said to be high dynamic range. This range may extend up to 10,000. This kind of images can’t be displayed on display units which can’t differentiate that many pictorial information. This kind of pictorial information need to be converted so that the regular display units can adapt the format. This must be done without losing much information. This process is very crucial and is done by several tone mapping operators. Tone mapping operators are of two types, global and local. Global tone mapping operators apply same mapping function throughout the image while the local tone mapping operators use different mapping functions for local regions of the image. Though the quality of global TMOs is better, there are many halo effects in the converted image. In this paper, a global TMO based on decomposition is proposed intended to reduce these effects. Image is decomposed in to two layers, base, and detail. A hybrid decomposition and optimization are proposed to improve the quality of converted image.base layerdetail layerretinex decompositionTMQITone mappingJPM Publishers2022-03-31International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/1104-2/https://ijeresm.com/wp-content/uploads/2022/04/ERESM11250301-18-23.pdfhttps://doi.org/10.58482/ijeresm.v1i1.410.58482/ijeresm.v1i1.4Vol. 1, Issue 1, pp. 18-23

oai:ijeresm.com:11052022-03-31

Turbo Code with Hybrid Interleaver in the Presence of Impulsive NoiseY RavisankaraiahS VaradarajanIn this paper, a numerical density function of Impulsive symmetric α-stable (ISAS) noise was presented and simulated in the turbo coding environment. The ISAS noise has no closed-form expression, making it difficult to realize. The ISAS noise can be used to approximate many kinds of noise sources. In this paper, one of the parameters is used to set it as the Cauchy distribution. In addition, an improved interleaver structure is presented where the multiple interleavers of smaller capacity replace a single epic interleaver. Simulation results show that the hybrid interleaver outperforms the other interleavers presented in this paper.turbo codesinterleaverbit error rateCauchy distributionstable distributionJPM Publishers2022-03-31International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/1105-2/https://ijeresm.com/wp-content/uploads/2022/04/ERESM11270301-24-31.pdfhttps://doi.org/10.58482/ijeresm.v1i1.510.58482/ijeresm.v1i1.5Vol. 1, Issue 1, pp. 24-30

oai:ijeresm.com:12012022-06-30

Region Based Non-Uniform Scheme for Effective RetargetingEthireddy Sasikala ReddyY SwathiK ChandiniS SwethaCh SwapnaWith the invent of displays of varied features like bendable displays, twistable displays and slant displays the feed of these displays need to be adjusted so that useful objects of the scene are not destroyed. In general, if we want to project a particular scene of specified size after capturing on the display of other dimensions, image resizing is done. In image resizing, the whole image will be converted into dimension of the target display. In the process the whole image, including all the objects may be expanded or squeezed depending on the size of the target display. But, in image retargeting, in addition to changing the size of the image to suit the target display, some additional intelligence will be added there by preserving or retaining useful objects and removing unnecessary background information. In this paper, the global significance map will drive the retargeting which is formed by merging the local significance maps. The local significance maps are derived after forming regions by considering the average intensity levels locally. The simulation results clearly show the superiority of the scheme proposed.aspect ratioimage resizingimage retargetingimage wrappingresolutionJPM Publishers2022-06-30International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/1201-2/https://ijeresm.com/wp-content/uploads/2022/06/1.-ERESM12140501-1-6.pdfhttps://doi.org/10.58482/ijeresm.v1i2.110.58482/ijeresm.v1i2.1Vol. 1, Issue 2, pp. 01-06

oai:ijeresm.com:12022022-06-30

An Optimum Deraining Scheme using Sparse CodingA HazarathaiahDharani UdayabhanuAnukupalli AnjaliBiruduraju NymishaBorra PrathyushaRain streak removal is a challenging and interesting task of image processing where the rain streaks will be removed from an image with rain streaks. In the literature, a large number of proposals are made where rain streak removal is considered as image enhancement or denoising. In this paper, a model of rain streak removal was proposed using sparse coding. First the regularization terms of the rain streak removal are defined. Then, a suitable dictionary of sub- dictionary with respect to specific patch of input rainy image are prepared. Finally, the Sparse code is applied on the patches of input image individually. The simulation results prove that the proposed technique performs very well even if the raindrop size is above a certain threshold.derainingrain streak removalremote sensingsparse codingstripe removalJPM Publishers2022-06-30International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/1202-2/https://ijeresm.com/wp-content/uploads/2022/06/2.-ERESM12160501-7-11.pdfhttps://doi.org/10.58482/ijeresm.v1i2.210.58482/ijeresm.v1i2.2Vol. 1, Issue 2, pp. 07-11

oai:ijeresm.com:12032022-06-30

Light Attenuation Prior based Underwater Image EnhancementKaturi SravaniS.V. Padmavathi DeviImages captured underwater usually suffer from color distortion, detail blurring, low contrast, and a bluish or greenish tone due to light scattering and absorption in the underwater medium, which in turn affects the visibility adversely. Underwater image processing schemes are broadly categorized into two groups, restoration methods and enhancement methods. The approach of restoration methods is to assume the effects of underwater environment as degradation but in enhancement, this environment is assumed to be natural and tries to enhance the visual information to next extent. Restoration schemes are proved to give better performance than enhancement schemes. These restoration schemes are further classified as optical imaging methods, polarization methods and prior knowledge methods. The key problems faced by these schemes are excessive optimization parameters, difficulty of recognizing artificial lighting, adapting to multi-scatter scenario, red artifacts and over exposure. A large number of schemes are proposed in the literature under these categories and most of them suffer from one or more of the above-mentioned issues. In this paper, a rapid and effective scene depth estimation model will be proposed based on underwater light attenuation prior for underwater images and train the model coefficients with learning-based supervised linear regression. With the correct depth map, the background light and transmission maps for R-G-B light are easily estimated to recover the true scene radiance under the water.underwater imagesrestorationr-channelpriorlight attenuationJPM Publishers2022-06-30International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/1203-2/https://ijeresm.com/wp-content/uploads/2022/09/3.-ERESM12200601-12-17-.pdfhttps://doi.org/10.58482/ijeresm.v1i2.310.58482/ijeresm.v1i2.3Vol. 1, Issue 2, pp. 12-17

oai:ijeresm.com:12042022-06-30

Multi-exposure Image Fusion using Patch-based Component DecompositionDharmika AM GnanapriyaMulti exposure image fusion is always a challenge in task in image processing. The multiple images with the different image content, when mixed using a fusion formula generate different effects. One of the most prominent effects is ghosting effect. Ghost in effect occur even in capturing of images. The smallest ghosting effect may be treated as image blur. To handle ghosting effect as well as many other affects that are generated in the process of fusion are treated in the proposed technique. The proposal scheme introduces a completely new representation that may be explorer for the for many different applications. First the input images are decomposed into several patches. As the fusion involves multiple input images the special correlated patches are further grouped into a class. Individual patches of the class are decomposed into three logical components named strength structure and intensity. These components are calculated for all the patches of the class. Now using the rule of fusion these logical components are derived for the whole class. The decomposition of a patch into logical components is unique as well as invertible hence using the generated components patches restored. Simulation results prove the superiority of the scheme proposed.multi-exposure image fusionpatchimage decompositiondeghostingtone mappingJPM Publishers2022-06-30International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/1204-2/https://ijeresm.com/wp-content/uploads/2022/09/4.-ERESM12260601-18-25.pdfhttps://doi.org/10.58482/ijeresm.v1i2.410.58482/ijeresm.v1i2.4Vol. 1, Issue 2, pp. 18-25

oai:ijeresm.com:12052022-06-30

Multiscale Fusion for Underwater Image EnhancementKunisetty SivanihimajaE Sasikala ReddyIn this paper, an enhancement scheme on underwater images is proposed. Underwater images undergo efforts like scattering and attenuation. Many techniques are proposed for underwater image and enhancement that largely depends on the features and characteristics of light. The characterization of light signal is complex and the underlying system that depends on light will lead to additional complexities. In the proposed scheme, image fusion is done by blending two images that are generated from a single underwater image. The first image is pre-processed by white balancing and Gamma correction. The second image is pre-processed by white balancing and sharpening. White balancing by colour channels gives better enhancement both specially and temporally. The white balancing followed by Gama correction and sharpening highlights a regular underwater image in all geo-spatial locations. The multi-scale fusion of Gama corrected and sharpened image produces an enhanced underwater image. Simulations are carried on large number of underwater images and it was established that the proposed scheme out performs state-of-the-art techniques.multi-scale fusionenhancementGamma correctionsharpeningunderwater imagesJPM Publishers2022-06-30International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/1205-2/https://ijeresm.com/wp-content/uploads/2022/09/5.-ERESM12270601-26-33.pdfhttps://doi.org/10.58482/ijeresm.v1i2.510.58482/ijeresm.v1i2.5Vol. 1, Issue 2, pp. 26-33

oai:ijeresm.com:13022022-09-30

Hygiene Bio-Toilet Model for Energy GenerationSahane Sanchit J.Bhane Mayuri D.Pinjari Omika B.On August 15, 1947, British paramountcy had left India with many wonders including railway which also called ‘veins of our country’ spread across every length and breadth of country. Indian Railways (IR) were being constantly criticized, as the discharges from toilets was laid on the tracks and this leads to environmental hazard. The toilet system in Indian Railways works in such a manner that the human faces and urine gets directly flushed on railway tracks through the hole on the floor of IR coaches. In current scenario, to deal with this issue, different systems like Controlled Discharge Toilet System (CDTS), Bio-toilet developed by IR engineers and DRDO biotechnologists, and Zero Discharge Toilet System (ZDTS) are extensively used. In this paper, a model of flush to energy is presented. The Bio-toilet system focuses on conversion of the toilet waste and biodegradable waste from station into energy which can be used for different purposes.Alert indicatorbio-toiletflush to energy modelreservoirsanitation of platform.sanitation of platformJPM Publishers2022-09-30International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/1-1302/https://ijeresm.com/wp-content/uploads/2022/11/1.1302-1-6.pdfhttps://doi.org/10.58482/ijeresm.v1i3.110.58482/ijeresm.v1i3.1Vol. 1, Issue 3, pp. 01-06

oai:ijeresm.com:13032022-09-30

A Study of the Traditional Health Care Practices in Ancient Tamil Nadu – An AssessmentA. Abdul KareemDr. G. YoganandhamDr.G. YoganandhamIndia is known around the world for its diverse civilizations and mystical rituals. Scholars and philosophers of the time formed a century-old tradition in the depths of this culture. Despite a long history of being viewed as unscientific, scientists and doctors are now aware of the benefits of traditional Indian health care. Many investigations on traditional medicine and its apparently magical qualities in the treatment of terminal diseases are currently being done. Home remedies are used all around the world, but they are recognized as science in India only. Two traditional Indian medicinal traditions: Ayurveda and Siddha are progressively gaining traction in the global healthcare business. In this article, some of India’s most odd and effective medicinal practices, as well as the benefits of each therapy will be reviewed. Throughout history, traditional medicines were the only source of primary healthcare, and they made a substantial contribution. Knowledge of how to use medicinal plants to treat various ailments was highly valued by ancient cultures. Until the mid-nineteenth century, plants were the principal therapeutic agents used by humans, and they continue to play an important role in pharmaceutical formulations. Traditional medicine is used by around 80 percent of people in undeveloped countries for their primary health care needs because of its low prices, effectiveness, frequently restricted availability of modern medicine, and cultural and religious preferences. Plant research in the traditional system of medicine is becoming increasingly significant in the development of global healthcare and conservation efforts. Traditional medicine systems are being used to uncover biologically active chemicals that are useful to the pharmaceutical industry. To this end, as much information possible is presented about these areas in this article. There are a number of geographically specific traditional health behaviors and are well reviewed in this paper.Ayurveda and SiddhaHerbal MedicineHomeopathyTraditional Indian Health CareUnaniJPM Publishers2022-09-30International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/1-1303/https://ijeresm.com/wp-content/uploads/2022/11/2.-1303-7-10.pdfhttps://doi.org/10.58482/ijeresm.v1i3.210.58482/ijeresm.v1i3.2Vol. 1, Issue 3, pp. 07-10

oai:ijeresm.com:13072022-09-30

Influencer Marketing as Emerging Promotional Tool in Modern Era and Opportunities to Uprising SalesA. B. MishraKshirod ChandKapish KaithThe increasing impact of social media for big brands nowadays are preferring influencer marketing over the traditional marketing techniques. Influencer advertising is a methodology that recognizes influential individuals on social media who impact a brand’s industry or target crowd. In an influencer advertising technique, a brand shapes an association with the influencer wherein the influencer consents to open their crowd to the brand’s informing or substance. Influencer marketing has become dramatically throughout the long term and the objective gathering for this promoting procedure is expanding step by step. Digital ad campaigns and online sketches made by the influencers get viral in no span of time. With hashtags, makes reference & other keywords the name of the brand stays in limelight for a longer period of time & impacts deeper in the minds of the audience. The research paper is based on secondary data. In this paper, the researcher has studied influencer market for promotions and various opportunities for market expansion.advertisingbrandinginfluencer marketingmarket expansionsocial mediaJPM Publishers2022-09-30International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/1-1307/https://ijeresm.com/wp-content/uploads/2022/11/3.-1307-11-13.pdfhttps://doi.org/10.58482/ijeresm.v1i3.310.58482/ijeresm.v1i3.3Vol. 1, Issue 3, pp. 11-13

oai:ijeresm.com:13082022-09-30

An Evaluation of Indian Ayurvedic Medicinal PlantsA. Abdul KareemG. YoganandhamAyurveda, or conventional Indian medicine, emphasizes the importance of choosing a naturally comprehensive approach to maintaining one’s bodily and mental well-being. It’s not a diet for people looking for an escape or an excuse to keep abusing their bodies or minds. It is well known that Ayurvedic herbs are completely safe, have a unique flavor and aroma, and serve as the best mechanism for preserving a healthy balance between the mind and body. They are non-toxic and safe by nature because they are self-sufficient and nutritious. Antiseptics are frequently used and have excellent therapeutic benefits. Several herbs, including ginger, chamomile, cardamom, peppermint, coriander, and basil, help the body’s blood circulation in a healthy way. The interaction between a person’s personality, mental, emotional, and spiritual process determines whether they are ill or well. Ayurveda is a traditional medical system from India that promotes healthy food and active lifestyles. The tips in this article can help to adapt oneself to the surroundings. Aloe, ginger, tulsi, pepper, elaichi, and turmeric are all used in Ayurvedic natural remedies. The economic worth of Ayurvedic medicine is at an all-time high. The rise of a full-rate vital generation poses a serious challenge to contemporary life. According to the WHO, 36 million of the 57 million fatal cases reported globally in 2008 were caused by illnesses other than infections. This research has proved the value of therapeutic herbs to people in poor nations. The two biggest risks to therapeutic plants are the loss of Ayurveda and misuse of recognized species. Indigenous methods and expertise have been utilized to gather, utilize, and manage them for a very long time.ayurvedaayurvedic herbsIndian medicinetherapeutic herbs and health Caretraditional medical systemJPM Publishers2022-09-30International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/1-1308/https://ijeresm.com/wp-content/uploads/2022/11/4.-1308-14-18.pdfhttps://doi.org/10.58482/ijeresm.v1i3.410.58482/ijeresm.v1i3.4Vol. 1, Issue 3, pp. 14-18

oai:ijeresm.com:13052022-09-30

A Case Study of Air India - Maharajah Back to HomeA. B. MishraRuchi KarjodkarAir India, the prestige of Tatas has the history dates to 1930s. The Air India was founded about 90 years ago as Tata Airlines and first ride was taken by the founder himself, J. R. D. Tata from Karachi to Bombay. The journey of Air India is an emotional rather than commercial. The Air India was nationalized by Government of India decades ago, but its progress under national entity is limited only for few decades. When the private carriers came into the field, and because of maintenance with respect to operations and human resource, the Air India was treated to be not only a company with loss, but also as a burdened national entity. In the process of disinvestment by Government of India, the Air India has arrived back at the Tata’s group. In this paper, a case study of Air India was presented covering all major milestones and inferences are presented.Air Indiadisinvestmentnationalizationre-privatizationTata GroupJPM Publishers2022-09-30International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/5-1305/https://ijeresm.com/wp-content/uploads/2022/12/5.-1305-19-21.pdfhttps://doi.org/10.58482/ijeresm.v1i3.510.58482/ijeresm.v1i3.5Vol. 1, Issue 3, pp. 19-21

oai:ijeresm.com:14022022-12-31

Medicine Systems used by Indian People – An EvaluationA. Abdul KareemDr. G. YoganandhamMedicines are substances that are used to treat, identify, and prevent disease and illness. The ancient civilization of India fostered the growth of numerous medical systems. India offers both the allopathic medical system and the traditional Indian medical system. In addition to one type of allopathy, India has five distinct traditional medicinal systems in use: Siddha, Ayurveda, Unani, Homeopathy, and Naturopathy. In developing countries, traditional medicine is becoming increasingly popular, especially in rural areas. Ayurveda, which translates as “the science of life,” is a holistic medical strategy that emphasizes keeping one’s body, mind, and spirit in good shape. The three doshas (constitutional types) are the basis of ayurvedic doctrine, and the patient’s constitution is more heavily considered during diagnosis and treatment. Astrology and incantation are also used in Siddha medicine. Tamil Nadu, India’s most southern state, uses it the most commonly. In addition to mineral or metallic medications, adjuvants (like honey, ghee, milk, betel leaf juice, and hot water) are frequently administered. Clean air, food, water, physical movement and rest, psychological movement and rest, sleep and alertness, and the retention of beneficial materials and outflow of waste materials from the body are the six elements of illness prevention and health promotion. With origins in the Reformation, homoeopathy in Germany enjoyed a golden age in the 17th and 18th centuries. In 1995, the Department of Homeopathy and Indian Systems of Medicine was established. One of the objectives of the organization is to develop standards for Ayurvedic, Unani, Siddha, and homoeopathic medicines. Folk knowledge about the traditional application of herbal remedies is very prevalent in ethnic cultures. People become physically and psychologically weaker when they don’t take their medication, which makes them more susceptible to contracting new ailments. In addition to allopathy, India has five additional traditional medical systems. Among these are Siddha, Ayurveda, Unani, Homeopathy, and Naturopathy.allopathyayurvedahomeopathynaturopathy and ancient civilizationsiddhatraditional Indian medical systemUnaniJPM Publishers2022-12-31International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/1-1402/https://ijeresm.com/wp-content/uploads/2022/12/1-1402-1-5.pdfhttps://doi.org/10.58482/ijeresm.v1i4.110.58482/ijeresm.v1i4.1Vol. 1, Issue 4, pp. 01-05

oai:ijeresm.com:14012022-12-31

Crosstalk Analysis of On-chip VLSI InterconnectsManjula JayammaN. RamanjaneyuluAnchula SathishY. Mallikarjuna RaoIn this paper dynamic crosstalk is analyzed for coupled on-chip VLSI interconnects in different conditions. The proposed work has taken the MOS transistor analytical expressions. In this work, calculated the transition delays and different timings of the interconnect aggressor and interconnect victim drivers for in-phase switching and out-of-phase switching. All the calculated results are compared with simulations in SPICE. The average error in the transmission delay using SPICE is 2.02 and 3.274% for the interconnect aggressor and interconnect victim buffers for in phase switching, respectively. The average errors in the same are 2.3 and 1.87% for out phase switching event.CMOS inverterCrosstalkInterconnectPower dissipationJPM Publishers2022-12-31International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/2-1401/https://ijeresm.com/wp-content/uploads/2022/12/2-1401-6-11.pdfhttps://doi.org/10.58482/ijeresm.v1i4.210.58482/ijeresm.v1i4.2Vol. 1, Issue 4, pp. 06-11

oai:ijeresm.com:13062022-12-31

A Case Study of Amul: Implementation of Extension Strategy to Repositioning Brand During Covid-19 PeriodDr. A. B. MishraMs. Anmol GoelMs. Pooja JajooDuring lockdown and consequent pandemic, many organizations reduced their production, and few shut their operations. Some organizations continued their regular production. Apart from Pharma, very few organizations raised their production and raised their sales. Amul, a dairy products company is the one which in addition to raising production and sales, established an emotional and social connection with their clients. The advantage of essential commodity category and milk production aided its success during the pandemic. In this paper, the marketing strategy of Amul is review as backbone of their success being the advertising strategy.advertisingAmulbusiness during pandemicsocial media advertising.social media advertisingJPM Publishers2022-12-31International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/3-1306/https://ijeresm.com/wp-content/uploads/2022/12/3-1306-12-16.pdfhttps://doi.org/10.58482/ijeresm.v1i4.310.58482/ijeresm.v1i4.3Vol. 1, Issue 4, pp. 12-16

oai:ijeresm.com:14052022-12-31

Assessing the Organization Culture Influence in Employee Involvement and EmpowermentDr. Aabha SinghviMr. Yash C DoshiDr. Ravindra. R. KaikiniEmployee involvement and empowerment are two deep factors that affect the daily performance of the organization; however, both these aspects of involvement and empowerment are highly influenced by the organizational culture prevalent. The organizational culture thus, has a greater role in the level of involvement and empowerment. Organizational culture is the way the organization works its planning and strategizing, which further provides an impetus for the employees to stay. Culture does play a pivotal role in the organization. Employee involvement is the level of interest shown by the employee to accomplish the overall strategy of the organization whereas employee empowerment is the level of freedom towards the decision-making employees are allowed to make. This research paper is basically an assessment towards analyzing these factors in-depth. The outcome of the research shows tremendous influence of organization culture in employee empowerment and employee involvement.employee empowermentemployee effectivenessemployee involvementemployee performanceorganizational cultureJPM Publishers2022-12-31International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/4-1405/https://ijeresm.com/wp-content/uploads/2022/12/4-1405-17-31.pdfhttps://doi.org/10.58482/ijeresm.v1i4.410.58482/ijeresm.v1i4.4Vol. 1, Issue 4, pp. 17-31

oai:ijeresm.com:14082022-12-31

The Indian Medicine System and Homeopathy- An OverviewA. Abdul KareemDr. G. YoganandhamThe Indian Systems of Medicine and Homoeopathy include Ayurveda, Siddha, Unani, and Homoeopathy in addition to practices like Yoga and Naturopathy. While some of these systems are indigenous, others have over time assimilated into Indian society. The Indian system of medicine has established its value in treating several diseases that Allopathy is vying to treat. The Indian medical system has a long history that is significantly older than the current Allopathy, which begs the question of whether affection is necessary. The oldest and most effective kind of traditional Indian treatment is Ayurveda. India has one of the world’s oldest medical systems. The term for it is Ayurvedic medicine (Ayurveda). Ayurveda is the science of life since in Sanskrit, Ayur means “life” and Veda means “science” or “knowledge.” These include Homoeopathy, Natural Therapeutics, Yoga, Siddha, and Unani. Homoeopathy arrived in India in the 18th century, but it quickly got fully integrated into Indian culture and enriched like any other system, making it a part of Indian medical systems today. Homoeopathy and the Indian System of Treatment are preferred by most Indians for their healthcare practices over allopathic medicine because of cost-benefit analysis. The Indian System of Medicine and Homeopathy in India are hence the main topics of this research paper’s overview.ayurvedaailmentsallopathiccost-benefit analysishomoeopathyIndian culturesiddhaUnaniJPM Publishers2022-12-31International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/5-1408/https://ijeresm.com/wp-content/uploads/2022/12/5-1407-32-37.pdfhttps://doi.org/10.58482/ijeresm.v1i4.510.58482/ijeresm.v1i4.5Vol. 1, Issue 4, pp. 32-37

oai:ijeresm.com:21142023-03-31

Social Vices: Causes and Counselling RemediesSekh Nazimul IslamUmmi Sarki AbubakarMiswar BelloGlobal increase in social problems both reflect and contribute to national and international tensions. The social vices problem is a key concern in many developing countries, where many types of vices are not known. It has worsened into a current global issue which represents human undesirable side of social growth. This undesirable fact is an unfortunate and has developed many security encounters facing the modern society. In this paper, some contemporary social vices have been discussed in the light of their causes, consequences, and possible counselling remedies. This paper argues that examination malpractice, drug abuse, child abuse, domestic violence and political thuggery among other contemporary social vices have created havoc and have contributed greatly to the slow pace in Nigeria. The major causes which include unemployment, poverty, peer influence, students’ poor reading habit, quick success syndrome and lack of marital counselling with their effects were discussed. It has been established in the course of this study that the problem of social vices, is a symptom of society which is embroiled in moral decadence. Realizing the havoc which social vices have wrecked on individuals and the society at large, all hands must be on deck to combat the menace. However, to curb this menace, possible counselling remedies like Rational Emotive Therapy, Client-Centred therapy, Gestalt Therapy, Group Therapy, and family therapy were proffered to serve as a panacea which will stem the tide of social vices and foster rapid development. It was recommended that government and stakeholders should collaborate and ensure pre-marital counselling, marital counselling, drug abuse counselling, crisis counselling, sex counselling, counselling with families concerning children, vocational/career counselling, educational counselling as well as counselling delinquents are emphasized and recommended to curb the menace so as to promote individual, social, political, moral, educational and economic development.Child AbuseCounsellingDomestic ViolenceDrug AbuseSocial vicesJPM Publishers2023-03-31International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/2114-2/https://ijeresm.com/wp-content/uploads/2023/01/1.-2114-1-7.pdfhttps://doi.org/10.58482/ijeresm.v2i1.110.58482/ijeresm.v2i1.1Vol. 2, Issue 1, pp. 01-07

oai:ijeresm.com:21012023-03-31

Crosstalk Peak Overshoot Analysis of VLSI InterconnectsC. VenkataiahD. Rajesh SettyN. RamanjaneyuluY. Mallikarjuna RaoAs technology extended from deep sub-micron technology to nanometer regimes, the conventional copper (Cu) wire will not be able to continue. Now a substitute approaches such as Carbon Nano Tube (CNT) interconnects have been suggested to ignore the problems associated with global interconnects. Hence in this work, crosstalk analysis of Complementary metal oxide semiconductor (CMOS) buffer-driven of different interconnects have been analyzed for peak overshoot and overshoot width of Cu and CNTs for 16nm technology. For analyzing peak overshoot, the interconnect lengths are varied from 100um to 500um in 16 technology node for Cu, single walled carbon nanotube (SWCNT) and multi-walled carbon nanotube (MWCNT). The values of the peak overshoot and overshoot width changes, as the interconnect length increases, the peak overshoot and width is going to be increases. As Compared to Cu, SWCNT and MWCNT, the peak overshoot and width for SWCNT is lesser than copper and MWCNT. The MWCNT interconnect is less than that of conventional Copper interconnects.CMOS inverterCrosstalkInterconnectPower dissipationJPM Publishers2023-03-31International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/2101-2/https://ijeresm.com/wp-content/uploads/2023/01/2.-2101-8-12.pdfhttps://doi.org/10.58482/ijeresm.v2i1.210.58482/ijeresm.v2i1.2Vol. 2, Issue 1, pp. 08-12

oai:ijeresm.com:21062023-03-31

General Voting System for Democratic Countries Using Blockchain and Computer TechnologyVandanababu TalakayalaPrashant DahiwaleSanjay MateSecret voting in democratic countries using computational intelligence and Blockchain Technology, the vote is a fundamental right in democracy to elect people’s representatives at various levels. Manual voting is tedious and error prone. E-voting systems replaced the manual voting systems to overcome illegal voting and malpractices. Due to growing cybercrimes, the existing e-voting systems are not ideal and face many challenges like authentication, privacy, data integrity, etc. This paper presents computational intelligence and Blockchain technology in developing secret e-voting systems. This paper addresses various issues not addressed by traditional and e-voting systems and proposes new voting using computational intelligence techniques and blockchain technology.BlockchainEVMPaper BallotInformation SecurityJPM Publishers2023-03-31International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/2106-2/https://ijeresm.com/wp-content/uploads/2023/02/3.-2106-13-19.pdfhttps://doi.org/10.58482/ijeresm.v2i1.310.58482/ijeresm.v2i1.3Vol. 2, Issue 1, pp. 13-19

oai:ijeresm.com:21072023-03-31

Operational Plan for All Academic and Institutional LibrariesJogen SharmaDayawanti TarmaliThis article will help to understand the Operational Plan details related information and it will help people to make their knowledge grow. The Strategic Plan defines the idea and procedure of strategic planning and goes some way to explaining how it first appeared in the workplace in the 1960s before being adopted by library and information services in the 1970s with help from trade organizations and governmental organizations that supported the development of best practices. Will describe ground-breaking work on the subject, define basic planning stages, and list the advantages of strategic planning for libraries. With annotations, it enables us to understand scholarly works as well as read suggestions. The Annual Operational Plan of the Library of any educational institution corresponds to the current year. The strategic and operational objectives will be aimed at reinforcing the weak points and carrying out the necessary improvements to provide quality and excellent service. The Annual Operating Plan Development (AOPD) can carry out the following actions: take into account the strategic plan of the institute; select, analyze, and present proposals for actions for the current year, within the strategic lines; and general and operational objectives of the strategic plan. Institute offers excellent services that meet the needs of research and contribute to the dissemination of scientific production of the institute. People and organization: guarantee the professionalism of all library staff and propose an efficient training plan and permanent professional updating in an optimal working environment. The plan will be monitored by the Strategic Plan Group, which may propose the necessary adjustments.educational institutionlibrary management systemoperational objectivestrategic planJPM Publishers2023-03-31International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/2107-2/https://ijeresm.com/wp-content/uploads/2023/02/4.-2107-20-24.pdfhttps://doi.org/10.58482/ijeresm.v2i1.410.58482/ijeresm.v2i1.4Vol. 2, Issue 1, pp. 20-24

oai:ijeresm.com:21152023-03-31

A Differential Study of Compulsive Usage of WhatsAppAashish DhimanPooja VarmaThere are several kinds of compulsive usage of “a mobile phone” by youngsters around the world, which can be called mobile phone addiction/misuse. The more specific area of mobile usage is “WhatsApp’s addiction/misuse” which has prompted health officials around the world to consider this quickly expanding issue. The research study aimed to determine WhatsApp usage patterns among primary educators and students, as well as the influence of those patterns on their personal lives. From December 1, 2021, to May 1, 2022, A cross-sectional study was undertaken among primary educators and students of the Meerut region. The information was gathered using a standardized questionnaire. The sociodemographic profile, usage pattern, and impact are all included in the proforma. The overuse of WhatsApp has an adverse influence as well as an extreme effect on study time, educational achievement, and relaxation. Educators utilize WhatsApp groups for academic purposes, which disrupts and demolish their personal lives even after they have finished their professional work. WhatsApp users have enhanced their social lives in the virtual world. The findings of this research study are limited to the specific region and not generalized to other sectors and regions of the world. Further research can be carried out with more sample size considering different variables.impactpatternprimary educatorsstudentsWhatsApp usageJPM Publishers2023-03-31International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/2115-2/https://ijeresm.com/wp-content/uploads/2023/02/5.-2115-25-32.pdfhttps://doi.org/10.58482/ijeresm.v2i1.510.58482/ijeresm.v2i1.5Vol. 2, Issue 1, pp. 25-32

oai:ijeresm.com:21162023-03-31

Impact of Color on Human Behavior Case – Interior SpaceSavvy JainAvitesh Vaishnavi NayakColour is considered as the basic visual perception of any space. There are numerous developed theories and assumptions related to the aesthetic comfort offered by colours, and to their effect on human psyche. In this paper, it is inspected how the choice of colour changes with age and its impact on that age group of people. This investigation will focus all the factors those are predicted to be more influential in architecture, interior spaces and the psychological status of users. The research aim of this study is to increase the concern about the importance of the interaction between interior space and human behaviour responding to the colour of the interior space. Paper talks about the importance of colour in an interior space where the different user groups spend most of their time like- schools for kids, offices for adults and meditation centre, old age homes for senior citizens. This research would help others to understand the importance of colour in the interior space and how people of different age groups respond to it. Based on the analysis of the conducted surveys and interviews, conclusions are drawn about the effect colours have on human behaviour in an interior space.architecturecomfortemotionexperiencepsychologyJPM Publishers2023-03-31International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/2116-2/https://ijeresm.com/wp-content/uploads/2023/02/6.-2116-33-37.pdfhttps://doi.org/10.58482/ijeresm.v2i1.610.58482/ijeresm.v2i1.6Vol. 2, Issue 1, pp. 33-37

oai:ijeresm.com:21172023-03-31

Influence of Study Skills Training in Reducing Poor Study Habits among School StudentsSekh Nazimul IslamUmmi Sarki AbubakarMiswar BelloThis research looked at the outcome of Study Skill Training (SST) on senior secondary school students study habits. A Quasi-experimental design was employed for the study in form of pretest-posttest control group. The sample size were students identified with poor study habits students and were assigned to treatment and one control group. The treatment group was treated using Study Skills Training counselling technique. An instrument developed by Bakare was adapted and used in collecting the data from the respondents before and after treatment. The collected data was analyzed by simple frequency and percentage for answering the research question followed by t-test for independent samples for testing all the hypotheses. The findings revealed that the prevalence of study habit among secondary and senior secondary school students in Municipal Zonal Education Directorate, Kano State was poor at 85%, the finding also exposed that study skills training technique had significant effect in reducing poor study habits among the respondents (P 0.00 ≤ 0.05), the finding also revealed that there was insignificant difference in post-test mean score between male and female with school students (P .109 ≥ .0.05).high school studentspoor study habitsquasi-experimentalstudy skills trainingJPM Publishers2023-03-31International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/2117-2/https://ijeresm.com/wp-content/uploads/2023/02/7.-2117-38-43.pdfhttps://doi.org/10.58482/ijeresm.v2i1.710.58482/ijeresm.v2i1.7Vol. 2, Issue 1, pp. 38-43

oai:ijeresm.com:21192023-03-31

An Examination of the Implications of Transformative Leadership on the Perceptions Towards the WorkplaceAashish DhimanNeha VashisthaThe purpose of this research is to assess the role of transformative leadership on perceptions of faculty members towards the workplace. Workplace perceptions refer to how individuals feel, believe, and behave in various aspects of their work, environment, and colleagues. This study seeks to differentiate the perceptions of faculty members working in private and government institutions/colleges in the Ghaziabad District, Uttar Pradesh. Satisfaction at the workplace and commitment towards the workplace are the two variables considered for the study. This study is based on survey data from 160 faculty members using the Likert Scale. A chi-square test was used to test the effect of transformational leadership on workplace perceptions. The correlation coefficient is used to explore the association between perceptions of faculty members. Responses were collected through subjective sampling and analysis. In line with prior research, transformative leadership is found to have a significant impact on satisfaction and commitment toward the workplace. It is revealed in this study, that transformative leadership (TL) has a significant effect on the perception of the workplace of faculty members working in both Private and Government Institutes. The study also examined the correlation between the faculty members of private and government institutes and presented an adverse association between the two. The results cannot be generalized to other parts of the state/country and elsewhere as they are limited to a specific region only due to different policies and mindsets of the employees that differ from place to place.commitmentperceptionssatisfactiontransformative leadershipworkplaceJPM Publishers2023-03-31International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/2119-2/https://ijeresm.com/wp-content/uploads/2023/03/8.-2119-44-49.pdfhttps://doi.org/10.58482/ijeresm.v2i1.810.58482/ijeresm.v2i1.8Vol. 2, Issue 1, pp. 44-49

oai:ijeresm.com:22022023-06-30

Indian Livestock Farm Management Methodologies: A SurveySanjay MateVikas SomaniPrashant DahiwaleAgriculture has a good stake in the world’s GDP. In many countries, agriculture and allied sectors have a good stake in national GDP. This paper covers details related to livestock since 1960s. The workforce has managed livestock for many decades. The workforce increases as the number of animals increases; it is an energy, time-consuming, and economically costly approach. Apart from it, there is no assurance about animal welfare in case of diseases, breeding, and feed intake issues. In the 21st century of digitalization, technology has a key role in improving overall monitoring, controlling, and processing in livestock management. This paper has gone thoroughly into the manual and automated livestock farm management, aiming welfare of animals, livestock products, consumers’ benefit, and sustainable environmental approaches.Block chainFoot and Mouth Disease (FMD)GrazingMastitisVoluntarily CullingJPM Publishers2023-06-30International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/2202-2/https://ijeresm.com/wp-content/uploads/2023/05/1.-2202-1-9.pdfhttps://doi.org/10.58482/ijeresm.v2i2.110.58482/ijeresm.v2i2.1Vol. 2, Issue 2, pp. 01-09

oai:ijeresm.com:22042023-06-30

An Image Processing-Driven System for Fake Currency DetectionKunda HemalathaE Sasikala ReddyFake currency is a critical factor affecting economies worldwide, including India. In this paper, a novel and structurally efficient approach for detecting and identifying duplication in currency notes is presented using Discrete Wavelet Transform (DWT). The system employs image processing algorithms to extract essential features such as security thread, intaglio printing (RBI logo), and identification mark, which serve as security measures for Indian currency. To identify fake portions in the currency notes and make informed decisions about their authenticity, the matching scores from all fake detection modules are fused together. A crucial aspect of the work lies in comparing the extracted features from various currency notes, enabling us to differentiate between fake and genuine notes effectively. To assess the performance, mean square error is employed as a metric for comparison between two images. A database is build containing authentic Indian notes of different denominations, extract their features, convert them into binary equivalents, and then calculate their mean square error. The proposed Fake Note Detection System takes a test currency note image, performs preprocessing operations to eliminate noise and negative artifacts, and then proceeds with the detection process. The system offers a promising solution to combat counterfeit currency issues and safeguard the integrity of the Indian economy.Discrete Wavelet TransformFake currency detectionFeature extractionImage processingSecurity featuresJPM Publishers2023-06-30International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/2204-2/https://ijeresm.com/wp-content/uploads/2023/08/2.2204-10-15.pdfhttps://doi.org/10.58482/ijeresm.v2i2.210.58482/ijeresm.v2i2.2Vol. 2, Issue 2, pp. 10-15

oai:ijeresm.com:22052023-06-30

Machine Learning-Based Approach for Cardiovascular Disease Detection and ClassificationChenji KeerthipriyaMahammadi Nigar ShaikCardiovascular disease (CVD) remains the primary cause of mortality worldwide and continues to exhibit an alarming upward trend. Detecting CVD efficiently and accurately in large populations has become an urgent necessity. The proposed framework aims to detect and classify five major cardiovascular disorders in the heart, including Heart Attack, Heart Failure, Heart Valve disease, pericardial disease, and vascular disease (Blood Vessel Disease). Developed within the MATLAB environment, the system will undergo comprehensive simulation to ensure its effectiveness. To evaluate the system’s performance, a two-pronged approach will be employed: psycho-visual and parametric analysis. Through psycho-visual analysis, human experts will visually assess the system’s outputs, offering qualitative insights into its accuracy and reliability. Meanwhile, parametric analysis will utilize objective metrics to quantitatively measure the system’s efficiency in detecting and categorizing the cardiovascular conditions. The successful implementation of this proposed system holds promise for early and precise identification of cardiovascular disorders, facilitating timely medical interventions and improving patient outcomes. By incorporating both subjective and objective evaluations, this research seeks to develop a robust and efficient tool for cardiovascular disease screening, ultimately contributing to enhanced healthcare and reduced disease burden.Cardiovascular DiseaseDisease ScreeningHealthcareParametric analysisPsycho-visual analysisJPM Publishers2023-06-30International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/2205-2/https://ijeresm.com/wp-content/uploads/2023/08/3.2025-16-22.pdfhttps://doi.org/10.58482/ijeresm.v2i2.310.58482/ijeresm.v2i2.3Vol. 2, Issue 2, pp. 16-22

oai:ijeresm.com:22062023-06-30

Physical Layer Security in Interference-Limited Land Mobile Satellite Communication Systems: Safeguarding Data TransmissionMahesh NelavalliK SubrahmanyamThis paper focuses on evaluating the secrecy performance of a downlink land mobile satellite (LMS) system. The system faces the challenge of providing secure communication between a satellite and a legitimate user while an eavesdropper is present on the ground. Additionally, co-channel interference signals at the user’s destination are considered. To address these issues, the study proposes a novel approach that utilizes Shadowed-Rician fading channels for satellite links and Nakagami-m fading for interfering terrestrial links. The main objective is to enhance the physical layer security of Interference-Limited Land Mobile Satellite Communication Systems. The approach incorporates advanced signal processing, beamforming, and artificial noise techniques to effectively manage interference. Encryption, authentication mechanisms, and intelligent power control strategies are implemented to protect transmitted data and optimize signal strength while reducing the risk of interception by potential eavesdroppers. Through comprehensive simulations, the proposed approach is thoroughly evaluated, demonstrating its effectiveness in achieving improved secrecy performance and increased resilience against security threats. The findings highlight the potential for its application in secure satellite communication systems operating in interference-constrained environments.Co-channel InterferenceDownlinkEavesdropperInterference-LimitedLand Mobile Satellite CommunicationPhysical Layer SecuritySecrecy PerformanceShadowed-Rician FadingNakagami-m FadingJPM Publishers2023-06-30International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/2206-2/https://ijeresm.com/wp-content/uploads/2023/08/4.2026-23-27.pdfhttps://doi.org/10.58482/ijeresm.v2i2.410.58482/ijeresm.v2i2.4Vol. 2, Issue 2, pp. 23-27

oai:ijeresm.com:23012023-07-31

Brand Positioning in the Indian Smartphone Market: A Case Study of OnePlusA. B. MishraAbhishek SinghThis case study describes the glorious entry of OnePlus into the mobile industry which was already flooded with multiple smartphone players. OnePlus was established as a leading smartphone player by adopting technological and marketing strategies. To compete in the existing market, OnePlus must outperform the competition by exploring the gaps in the mobile industry. OnePlus came into existence at a time when it was widely agreed that no Android phone could compete with Apple phones in terms of quality. But OnePlus has achieved the most impetus in the Rs.30,000 to Rs.50,000 price range. In a very short time frame of four years, OnePlus became the number one smartphone brand in the Indian premium smartphone segment. This case study is based on secondary data which focuses on marketing strategies adopted by the company to enrichment of sales in the Indian smartphone market.Marketing StrategyMobile industryOnePlus IndiaSmartphoneJPM Publishers2023-07-31International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/2301-2/https://ijeresm.com/wp-content/uploads/2023/10/1.-2301-1-5.pdfhttps://doi.org/10.58482/ijeresm.v2i3.110.58482/ijeresm.v2i3.1Vol. 2, Issue 3, pp. 01-05

oai:ijeresm.com:23032023-07-31

IKEA - Phygital Transformation in Furniture Manufacturing IndustryA. B. MishraMithila SatarkarSanat JoshiIKEA was formed in a remote corner of Sweden, where it was difficult to contact potential clients in larger towns. Is currently serving over 775 million clients worldwide and has a presence in 35 countries IKEA is the best illustration of phygital transformation having the combination of Physical plus digital, i.e., merging digital experiences with physical ones. Technology is a requirement of the twenty-first century. IKEA has established a physical and digital presence using technology. IKEA mixes AR (Augmented Reality) and VR (Virtual Reality), which is a fundamental cause of the company’s success. This is the case study with a strong emphasis on sustainability development with the emerging phygital transmission of IKEA. The entire research is based on secondary data.Furniture ManufacturingIKEAPhygital TransmissionSustainability DevelopmentJPM Publishers2023-07-31International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/2303-2/https://ijeresm.com/wp-content/uploads/2023/10/2.-2303-6-9.pdfhttps://doi.org/10.58482/ijeresm.v2i3.210.58482/ijeresm.v2i3.2Vol. 2, Issue 3, pp. 06-09

oai:ijeresm.com:23052023-07-31

A Study on Business Use of Digital Platforms with Special Reference to Chennai CityM. M. ShanmugapriyaGlobal economic activity is driven by business. The significant transformation in how firms across industries, inside and outside the digital economy, develop, produce, and market their goods and services is a result of the expanding use of digital technology. The major goal of this article is to identify the various digital platforms used in business development in Chennai and to assess the challenges experienced by businesspeople in implementing these platforms. Numerous businesses in Chennai cater to both locals and tourists, including clothing stores, digital marketing agencies, IT service providers, and others. 200 businesspeople from those five firms are chosen as the sample unit and size of this study utilizing a practical random method. The entire focus of this study work is description. Primary data is gathered via a well-designed questionnaire that is divided into three sections: demographics of the respondents, use of digital platforms, and issues experienced by businesspeople in Chennai City with digital platforms. Annual reports, journals, periodicals, books, and newspapers are used to gather secondary data. The gathered data were analyzed using percentage analysis, the weighted average method, and the Kruskal-Wallis test. The study’s conclusions showed a strong correlation between businesspeople’s investments and the extent to which they use digital platforms for their operations.Business Use of Digital TechnologyDigital EconomyDigital PaymentsDigital PlatformsJPM Publishers2023-07-31International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/2305-2/https://ijeresm.com/wp-content/uploads/2023/10/3.-2305-10-15.pdfhttps://doi.org/10.58482/ijeresm.v2i3.310.58482/ijeresm.v2i3.3Vol. 2, Issue 3, pp. 10-15

oai:ijeresm.com:24252023-12-31

Optimizing Urban Mobility: Innovative Sloped Road Design for Fuel Efficiency and SafetyXing LieXing XieIn this paper, an urban road design concept is proposed that introduces gentle slopes along straight roads to optimize fuel efficiency between signalized intersections. These calculated inclines leverage gravitational forces, reducing vehicle fuel consumption. At signal crossings, a deliberate reversal of slope mitigates depth accumulation concerns, promoting safe intersection navigation. Smooth transition zones enhance road stability and drain depth adjustments accommodate stormwater management. Collaborative efforts with experts and public awareness initiatives are vital for successful implementation. This innovative concept combines technical precision, safety considerations, and environmental sustainability, offering a holistic approach to urban road design for enhanced efficiency and user experience.Urban Road DesignFuel EfficiencySloped RoadsSignalized IntersectionsSustainable TransportationJPM Publishers2023-12-31International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/2425-2/https://ijeresm.com/wp-content/uploads/2023/12/1.-2425-1-4.pdfhttps://doi.org/10.58482/ijeresm.v2i4.110.58482/ijeresm.v2i4.1Vol. 2, Issue 4, pp. 01-04

oai:ijeresm.com:24292023-12-31

Color Cast Correction Mechanisms: Techniques and Innovations for Image EnhancementNadia GargRavi JainRaksha SharmaThis paper presents an in-depth examination of color cast in digital images, elucidating its fundamental principles, generation mechanisms, and real-world implications influenced by light absorption and scattering. The study explores diverse color cast correction methods and provides a detailed analysis of their respective outcomes. Foundational knowledge of color cast, rooted in the principles of light interaction, serves as the basis for understanding its manifestation in various real-world contexts. The research systematically investigates the intricate dynamics of color cast across diverse scenarios, shedding light on its complexities and impact. The paper evaluates a range of color cast correction techniques, including classic approaches such as the Gray World Algorithm, Max–RGB, and White Balance Correction, as well as advanced methods like Gamma Correction, Histogram-Based Method, and the Gray Edge Algorithm. Notably, simulation results underscore the consistent superiority of the Gray Edge Algorithm in effectively correcting color cast, showcasing its robustness across diverse scenarios. This comprehensive exploration contributes to a holistic understanding of color cast, covering its generation, consequences in real-world scenarios, and an in-depth analysis of correction methodologies. The findings provide valuable insights for professionals in image processing and computer vision seeking efficient correction strategies.Color castImage processingColor correctionLight interactionReal-world scenariosJPM Publishers2023-12-31International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/2429-2/https://ijeresm.com/wp-content/uploads/2023/12/2.-2429-5-16.pdfhttps://doi.org/10.58482/ijeresm.v2i4.210.58482/ijeresm.v2i4.2Vol. 2, Issue 4, pp. 05-16

oai:ijeresm.com:31032024-03-31

Garlic Plant Characteristics and Medicinal Values: A ReviewDejene Tadesse BanjawHabtamu Gudisa MegersaGarlic is a versatile vegetable commonly grown in subtropical and highland agroecosystems, which is utilized for its culinary, medicinal, and spice properties. The use of garlic as a medicinal aid can be traced back to ancient times. The health benefits of garlic production are attributed to its antiviral, antibacterial, and antifungal properties. The use of garlic is prevalent in both traditional and modern healthcare systems, where it is used to treat a wide range of conditions. Numerous studies have reported the therapeutic properties of garlic, and its effectiveness has been demonstrated in clinical trials. The growing global interest in health and wellness, the widespread use of garlic as a spice, and its potential economic, social, and health benefits have contributed to a surge in its demand worldwide. This review aims to provide a comprehensive overview of the scientific literature on the morphological descriptions of garlic and its nutritional and health significance.allicinalliumgarlichealthmedicinal valuesJPM Publishers2024-03-31International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/3103-2/https://ijeresm.com/wp-content/uploads/2024/03/13103-Garlic-Plant-Characteristics-and-Medicinal-Values-A-Review.pdfhttps://doi.org/10.58482/ijeresm.v3i1.110.58482/ijeresm.v3i1.1Vol. 3, Issue 1, pp. 01-04

oai:ijeresm.com:31042024-03-31

Unveiling Experiential Learning: Saudi Female Undergraduates' Perceptions and Challenges in the Marshmallow Challenge within OB ClassTahreem Noor KhanThe Marshmallow Challenge, a popular activity in classrooms and team-building exercises in offices promotes teamwork, communication, and collaboration. Despite its widespread use, its application within the Saudi educational context remains underexplored. Therefore, this research delves into the experiences and perceptions of 43 Saudi female undergraduate students participating in the Marshmallow Challenge in Organizational Behaviour (OB) class at the University of Hail, Saudi Arabia. Utilizing semi-structured interviews, the study aims to understand the nuances of this experiential learning activity, focusing on teamwork, communication, leadership, collaboration, and related responses. The findings reveal a spectrum of reactions from initial apprehension and nervousness to subsequent collaborative problem-solving and reflection. Ultimately, this research paper contributes to the broader literature on experiential learning in OB education, offering educators actionable insights to optimize student engagement, collaboration, and skill learning.collaborative problem-solvingexperiential learningmarshmallow challengeorganizational behaviorJPM Publishers2024-03-31International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/3104-2/https://ijeresm.com/wp-content/uploads/2024/03/23104-Unveiling-Experiential-Learning-Saudi-Female-Undergraduates-Perceptions-and-Challenges-in-the-Marshmallow-Challenge-within-OB-Class.pdfhttps://doi.org/10.58482/ijeresm.v3i1.210.58482/ijeresm.v3i1.2Vol. 3, Issue 1, pp. 05-11

oai:ijeresm.com:31092024-03-31

Exploring the Landscape of Indian Traditional Medicine in Rural Tamil Nadu: Knowledge, Attitudes, Practices, and Safety ConcernsA. Abdul KareemG. YoganandhamIndian traditional medicine, encompassing systems such as Ayurveda, Siddha, and Unani, has been deeply rooted in the cultural heritage of the country for centuries. In rural Tamil Nadu, where these traditions have thrived, there exists a rich tapestry of knowledge, attitudes, and practices regarding traditional medicine. This study aims to delve into the landscape of traditional medicine in rural Tamil Nadu, shedding light on the depth of local knowledge, prevailing attitudes, prevalent practices, and pertinent safety concerns. Utilizing a mixed-methods approach, including qualitative interviews and quantitative assessments, data was collected from diverse rural communities across Tamil Nadu. Findings reveal a nuanced understanding of traditional medicine, deeply intertwined with cultural beliefs and socio-economic factors. Local communities demonstrate a profound knowledge of medicinal plants, formulations, and therapeutic practices passed down through generations. However, alongside this wealth of knowledge, concerns regarding safety, efficacy, and regulation persist. Attitudes toward traditional medicine are multifaceted, reflecting a blend of reverence, skepticism, and pragmatism. While many individuals continue to rely on traditional healers and remedies for primary healthcare needs, others express reservations, citing issues of standardization and scientific validation. Practices vary widely, from home remedies administered by family members to consultations with traditional practitioners and integration with modern healthcare systems. This study explores Indian traditional medicine in rural Tamil Nadu, highlighting safety concerns like adulteration and misidentification of plants. It suggests a comprehensive approach that integrates traditional and modern medicine, ensuring the safety and well-being of rural communities while addressing knowledge, attitudes, and practices. The approach places a strong emphasis on using data and statistics from secondary sources to discuss the article’s subject. It draws attention to how important the current social, political, and economic environment is in shaping the conversation.ayurvedamedicinal plantscare systems and human bodyIndian traditional medicinemedicinal plantssafety concernsSiddhaunaniJPM Publishers2024-03-31International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/3109-2/https://ijeresm.com/wp-content/uploads/2024/03/33109-Exploring-The-Landscape-Of-Indian-Traditional-Medicine-In-Rural-Tamil-Nadu-Knowledge-Attitudes-Practices-And-Safety-Concerns.pdfhttps://doi.org/10.58482/ijeresm.v3i1.310.58482/ijeresm.v3i1.3Vol. 3, Issue 1, pp. 12-19

oai:ijeresm.com:31082024-06-30

An Impact of Social Marketing on Smoking and Tobacco ConsumptionRuchi KansalMahtab AhmedRuchi Kansal, Mahtab AhmedThe paper discusses the role of social marketing in preventing health-related harmful habits such as tobacco consumption and smoking. These habits are the causes of deadly diseases such as lung cancer, tuberculosis, and other chronic infections which are detrimental to life of the people. Children fall prey to the wrong habits in the wrong company and become tobacco addicts. So many cases of teen drug addicts are reported in a large number. They have a lack of conscience at a tender age and negligence of their counselling and awareness increases the number of smokers, drunkards, and drug addicts. Once they are afflicted with the diseases they must run for medicines and treatment. Therefore, it should be prevented before suffering as the saying goes, “Prevention is better than cure “. They are unaware that they are prevented not only by clinical treatment and medicines but also by social awareness and education. Social mobilization of the people through awareness programs, education, camps, campaigns, etc. is known as social marketing. The significance of social marketing is its effects on the prevention of physically detrimental habits in the youth which contributed a lot to the reduction of cases of diseases. The role of government programs, educational and medical institutions, social workers, and NGOs is worth applauding in India which undertake and complete projects, organize awareness camps, and educate parents and youths to save themselves from the consumption of harmful substances. It has also produced good output in India that the cases of smoking and drug addiction have reduced to support the country’s development as India is advancing towards becoming the third largest economy and a developed country by 2030 and 2047 respectively.detrimental habitsdisease preventionhealth awarenesssmokingsocial marketingsocial mobilization.social mobilizationJPM Publishers2024-06-30International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/3108-2/https://ijeresm.com/wp-content/uploads/2024/04/13108-An-Impact-of-Social-Marketing-on-Smoking-and-Tobacco-Consumption.pdfhttps://doi.org/10.58482/ijeresm.v3i2.110.58482/ijeresm.v3i2.1Vol. 3, Issue 2, pp. 01-05

oai:ijeresm.com:32082024-06-30

A Study of Ancient Indian Astronomy through Architectural MarvelsKeerthi Krishnanath Prabhu ShirodkarAncient Indian astronomy has a rich legacy that spans millennia, encompassing intricate observations, advanced calculations, and skillful implementations. This review article explores the intersection of astronomy and architectural marvels in ancient India. By examining the architectural marvel, the profound astronomical knowledge embedded within its design and construction is inspected. The study aims to unveil the celestial alignments, geometric patterns, and symbolic representations reflecting the deep understanding of cosmic phenomena of ancient Indian astronomers and architects. With this review, through a comprehensive analysis of the temple’s architectural elements, it is expected to gain insights into the intricate methods employed by ancient Indians to encode astronomical principles into monumental structures and the cultural significance of these celestial pursuits.architectureastronomyequinoxKonark sun templeModhera sun templesolsticeJPM Publishers2024-06-30International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/3208-2/https://ijeresm.com/wp-content/uploads/2024/05/23208-A-Study-of-Ancient-Indian-Astronomy-through-Architectural-Marvels.pdfhttps://doi.org/10.58482/ijeresm.v3i2.210.58482/ijeresm.v3i2.2Vol. 3, Issue 2, pp. 06-10

oai:ijeresm.com:32542024-06-30

Phygital Transformation of Nilon’s: The Brand Building in Ready-to-eat SegmentA. B. MishraRitika SinghA. B. Mishra, Ritika SinghFast-Moving Consumer Goods (FMCG) is the fastest-growing sector globally. It is expanding at a healthy rate because of rising disposable income, youth population, and awareness about its products. Nilon’s is one of the leading FMCG players with deals in the ready-to-eat segment. It has recently completed 60 years of operations. Nilon’s products are available at six lakh stores throughout India. Significant in 20 countries including Japan, France, the USA, South Africa, Dubai, Saudi Arabia, Malaysia, Singapore, Australia, and Canada etc. It provides channel sales, including general trade, modern trade, direct-to-customer (D2C), defence, hotels, restaurants, and Catering. Nilon’s embarked on a phygital transformation journey to redefine its brand identity and strengthen its market position in the FMCG ready-to-eat segment. Secondary data was used as a framework for this research. This case study is based on Nailon’s transformational efforts to develop into a more prominent player in the ready-to-eat segment.D2CFMCGNilon’sphygital transformationready-to-eat segment.ready-to-eat segmentJPM Publishers2024-06-30International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/3254-2/https://ijeresm.com/wp-content/uploads/2024/08/33254-Phygital-Transformation-of-Nilons-The-Brand-Building-in-The-Ready-to-eat-Segment.pdfhttps://doi.org/10.58482/ijeresm.v3i2.310.58482/ijeresm.v3i2.3Vol. 3, Issue 2, pp. 11-14

oai:ijeresm.com:133042024-09-30

Defying Limits: A Study of Disability and Resilience in Preeti Monga's Novels The Other Senses and Flight Without SightMalavika M PV Tamil SelviDisability studies is an interdisciplinary field of studies based on the grounds of humanities and social sciences rather than viewing disability through the prism of medicine or psychology. It is an academic discipline that surfaced in the late 20th century, emanating from the disability rights movement and critical theory. This paper tries to examine Preeti Monga’s novels, The Other Senses: An Inspiring True Story of a Visually Impaired and Flight Without Sight, considering disability studies, marginalization, and oppression that disable the experience of people in private and public lives.BlindDisabilityInequalityInjusticeMarginalisationJPM Publishers2024-09-30International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/13304-2/https://ijeresm.com/wp-content/uploads/2024/09/13304-Defying-Limits-A-Study-of-Disability-and-Resilience-in-Preeti-Mongas-Novels-The-Other-Senses-An-Inspiring-True-Story-of-a-Visually-Impaired-and-Flight-Without-Sight.pdfhttps://doi.org/10.58482/ijeresm.v3i3.110.58482/ijeresm.v3i3.1Vol. 3, Issue 3, pp. 01-05

oai:ijeresm.com:233022024-09-30

Rethinking Man and Nature in The Old Man and The SeaGajalakshmi GMeenakshi SThis paper explores the intricate relationship between man and nature in Ernest Hemingway’s The Old Man and the Sea through the lens of deep ecology. It challenges the traditional anthropocentric interpretation of the novella, proposing that the protagonist Santiago’s struggle is not merely a tale of human triumph over nature but a journey towards understanding and coexisting with the natural world. By applying the principles of deep ecology, the study reveals how Santiago’s evolving relationship with the marlin and other sea elements reflects a broader ecological consciousness. The analysis also draws parallels between Santiago’s experience and the Biblical narrative of Jonah, suggesting that Santiago’s success is not solely due to his physical endurance but also the cosmic forces that aid him. This paper ultimately rethinks the themes of struggle and victory in the novella, emphasising the need for a harmonious relationship between humanity and the environment.Deep EcologyEcocriticismEnvironmental ConsciousnessMan and NatureThe Old Man and the SeaSantiagoJPM Publishers2024-09-30International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/23302-2/https://ijeresm.com/wp-content/uploads/2024/09/23302-Rethinking-Man-And-Nature-In-The-Old-Man-And-The-Sea.pdfhttps://doi.org/10.58482/ijeresm.v3i3.210.58482/ijeresm.v3i3.2Vol. 3, Issue 3, pp. 06-12

oai:ijeresm.com:333012024-09-30

Optimized Multiplier Architectures for Enhanced Performance and Efficiency in MAC UnitsG PriyankaN GireeshS HemachandraThis paper investigated the performance of Vedic multipliers in a 32-bit Multiplier-Accumulator Unit (MAC) by comparing Urdhva Tiryakbhyam and Nikhilam Sutras with various adder architectures. The goal was to identify the optimal combination of speed and resource efficiency. Urdhva Tiryakbhyam with CLA emerged as the fastest option, achieving a minimal delay of 0.709 ns. However, this came at the cost of higher resource utilization, measured in Logic Look-Up Tables (LUTs). Conversely, Nikhilam implementations generally required fewer LUTs, making them more resource-efficient, but they exhibited slightly slower performance. CLA consistently delivered the best delay for both Vedic multiplier types among the adder architectures. All the explored configurations are viable for practical implementation on Xilinx ISE 14.7. The key takeaway is that the choice between Urdhva Tiryakbhyam and Nikhilam and the specific adder architecture hinges on the application’s priorities.Deep Learning ModelMACVedic MultipliersWallace TreWallace TreeJPM Publishers2024-09-30International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/33301-2/https://ijeresm.com/wp-content/uploads/2024/09/33301-Optimized-Multiplier-Architectures-for-Enhanced-Performance-and-Efficiency-in-MAC-Units.pdfhttps://doi.org/10.58482/ijeresm.v3i3.310.58482/ijeresm.v3i3.3Vol. 3, Issue 3, pp. 13-19

oai:ijeresm.com:433062024-09-30

Early Detection of Alzheimer's Disease with Deep LearningSayyed NagulmeeraNagul Shareef ShaikG.MinniB Bhagya LakshmiAlzheimer’s disease (AD) is a progressive neurological disorder characterised by cognitive decline and memory loss. Early diagnosis is essential for effective treatment, although the complexity of the initial symptoms sometimes delays it. This review addresses the development of a deep learning-based model to aid in the early diagnosis of Alzheimer’s disease using neuroimaging data. Using MRI and PET scans from public datasets such as the Alzheimer’s Disease Neuroimaging Initiative, the proposed version makes use of convolutional neural networks (CNNs) to extract feature extraction and types by looking at brain structure in and on models associated with early Alzheimer’s ailment at the version that tries to decide the values ​​Performance is measured using key parameters along with sensitivity, specificity, accuracy, and area under the curve. The purpose is to develop a predictive tool which could help medical doctors diagnose Alzheimer’s disorder in advance and, in all likelihood, enhance the affected person’s effects via timely intervention.Alzheimer’s DiseaseBiomarkersConvolutional Neural NetworksDeep LearningMRINeuroimagingJPM Publishers2024-09-30International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/43306-2/https://ijeresm.com/wp-content/uploads/2024/09/43306-Early-Detection-of-Alzheimers-Disease-with-Deep-Learning.pdfhttps://doi.org/10.58482/ijeresm.v3i3.410.58482/ijeresm.v3i3.4Vol. 3, Issue 3, pp. 20-25

oai:ijeresm.com:533082024-09-30

Generative AI: Exploring the Applications of Generative Models in Creative IndustriesG.MinniSayyed NagulmeeraB Bhagya LakshmiNagul Shareef ShaikGenerative artificial intelligence, enabled through sophisticated machine learning frameworks, such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs), is disrupting the creative landscape within many of the creative industries, opening a new set of tools for content creation. Therefore, this article investigates the disruptions generative models present across multiple aspects of creative production, focusing on the influences of art, music, literature, and design. In the visual arts, generative AI produces original artworks that blend aesthetics and styles that extend conventional notions of creativity; in music, AI-composition tools allow musicians to compose original musical works and experiment with entirely new genres. In literature and storytelling, the same generative processes offer AI systems the ability to propose narrative frameworks and other textual elements that may instigate human writers to take these concepts further with a narrative or may stand on their own as original content. In design, generative algorithms support product development all the way down to quickly prototyping new products. The paper includes specific case studies or outlines of the application of generative AI tools to proposed projects, a discussion of effectiveness with the respective generative model, and the potential limitations generative models present for each creative area. The paper will also reflect on the threats generative AI may pose, the potential to redefine human creativity, originality, and ownership, implications for the potential decision-making capabilities of these systems, and if there may be consequences for society. In all these considerations, there are opportunities for and more significant implications of the potential of generative AI to assist and expand human creative possibilities throughout the entire creative process.Creative IndustryDecision MakingGenerative AIGenerative Adversarial NetworksGenerative AlgorithmsJPM Publishers2024-09-30International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/53308-2/https://ijeresm.com/wp-content/uploads/2024/09/53308-Generative-AI-Exploring-the-Applications-of-Generative-Models-in-Creative-Industries.pdfhttps://doi.org/10.58482/ijeresm.v3i3.510.58482/ijeresm.v3i3.5Vol. 3, Issue 3, pp. 26-33

oai:ijeresm.com:633132024-09-30

The Impact of Sustainable Trade Practices on Economic Transformation in Saudi Arabia: Lessons for Developing EconomiesSanjeevni GangwaniThe trade practices in Saudi Arabia include farming, date exports, and trade generated by pilgrims. There was less economic growth. However, the oil exports and earnings from the oil sector generated funds for economic development, which helped international trade to flourish in the Kingdom of Saudi Arabia (KSA). The present study sheds light on the economic transformation of the KSA due to its sustainable trade practices. A qualitative methodology approach of the resource-based view was carried out in the international context. The present study discussed KSA’s initiatives to boost international business, including the Future Investment Initiative and the creation of small and medium-sized enterprises (SMEs). The study will evaluate the international business practices and economic transformation in KSA. This study will present the Saudi business environment and the government’s contribution to the country’s economic transformation.Economic TransformationInternational Business PracticesSaudi Arabian governmentWorld Trade OrganizationJPM Publishers2024-09-30International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/63313-2/https://ijeresm.com/wp-content/uploads/2024/09/63313-The-Impact-of-Sustainable-Trade-Practices-on-Economic-Transformation-in-Saudi-Arabia-Lessons-for-Developing-Economies.pdfhttps://doi.org/10.58482/ijeresm.v3i3.610.58482/ijeresm.v3i3.6Vol. 3, Issue 3, pp. 34-39

oai:ijeresm.com:733142024-09-30

Millets for Prosperity: Enhancing Farmer Welfare and Reviving Crop Productivity in ChhattisgarhTapesh Chandra GuptaSushma TiwariThis comprehensive study thoroughly examines the current state of millet production in Chhattisgarh, India, with a multifaceted approach. It encompasses an in-depth analysis of various factors influencing millet production in the region, ranging from environmental conditions to agricultural practices and government initiatives. Millets, often called “smart food,” are resilient crops that can thrive in drought-prone areas while demanding significantly less water than other staple grains like wheat and rice. The research underscores millets’ remarkable nutritional value and health benefits, highlighting their significance in addressing the dual challenges of malnutrition and climate change. Millets have the potential to play a pivotal role in ensuring food security and mitigating the impact of climate change, making their resurgence a matter of global importance. This research underscores the growing importance of millets as a resilient and nutritious crop and a potential solution to pressing global challenges. By assessing their production, nutritional benefits, and consumer perceptions, this study provides insights that can drive policy and industry efforts to harness the full potential of millets in promoting food security, mitigating climate change, and advancing healthier dietary choices.ChhattisgarhCrop ProductivityFood SecurityInternational Year of MilletsNutrient-rich GrainsJPM Publishers2024-09-30International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/73314-2/https://ijeresm.com/wp-content/uploads/2024/09/63313-The-Impact-of-Sustainable-Trade-Practices-on-Economic-Transformation-in-Saudi-Arabia-Lessons-for-Developing-Economies.pdfhttps://doi.org/10.58482/ijeresm.v3i3.710.58482/ijeresm.v3i3.7Vol. 3, Issue 3, pp. 40-45

oai:ijeresm.com:833152024-09-30

Carbon Capture and Storage – Legal and Policy Considerations for Sustainable Energy SolutionsMohd Aqib AslamCarbon capture and storage (CCS) has become a vital technological advancement in the fight against climate change by lowering greenhouse gas emissions from energy generation and industrial operations. However, the development and application of CCS technologies confront formidable legal and policy obstacles despite their potential to help achieve global carbon reduction goals. This study examines the legislative and policy tools required to support the implementation of CCS as a sustainable energy choice. To solve these issues, it evaluates national, regional, and international legal methods and the regulatory gaps that prevent CCS projects from being widely implemented. The analysis focuses on identifying the factors that hinder and facilitate the deployment of CCS, including environmental regulations, intellectual property rights, liability concerns, and public participation. The research also examines how current international climate agreements, like the Paris Agreement, impact CCS’s regulatory environment. This paper identifies optimal methods for establishing a favorable legal environment by evaluating case studies from nations with advanced CCS efforts. Lastly, suggestions are made for coordinating legislative and regulatory frameworks so that CCS can significantly contribute to realizing sustainable energy transitions.Carbon Capture and StorageEnvironmental LawClimate PolicySustainable EnergyRegulatory FrameworksJPM Publishers2024-09-30International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/83315-2/https://ijeresm.com/wp-content/uploads/2024/09/83315-Carbon-Capture-and-Storage-Legal-and-Policy-Considerations-for-Sustainable-Energy-Solutions.pdfhttps://doi.org/10.58482/ijeresm.v3i3.810.58482/ijeresm.v3i3.8Vol. 3, Issue 3, pp. 46-50

oai:ijeresm.com:933102024-09-30

Evaluation of Mechanical Properties of Al6061 Composite by Stir Casting MethodAllu Venkata SatyanarayanaYerubandi Venkata Ramana MurthyMohd Aqib AslamChandra Mouli V.S.AAluminium alloy-based metallic matrix composites (MMC) have recently gained popularity in various aerospace and automotive applications. Aluminium has been utilized as a matrix material due to its high mechanical qualities, superior formability, and diverse industrial applications. The Al6061 alloy system becomes harder, stronger in tension, and more wear-resistant when TiB₂-SiC-Rh is added as reinforcement. Al6061–TiB₂-SiC-Rh composites were created in this study using a liquid metallurgical method, with TiB₂-SiC-Rh added in percentages ranging from 2% to 8% by weight in increments of 2%. The cast matrix alloy and its composites were treated with solutionizing at 500°C for 1 hour before being quenched in different media like air, water, and oil. After quenching, the samples were aged both artificially and naturally. Microstructural analysis was conducted to understand the relationship between structure and mechanical properties. Mechanical characteristics, including microhardness and abrasive wear experiments, were performed on matrix Al6061 and Al6061-TiB₂-SiC-Rh composites before and after heat treatment. Under the same heat treatment conditions, the Al6061-TiB₂-SiC-Rh composites exhibited improved microhardness, tensile strength, and reduced wear compared with the Al matrix alloy.Al6061Al6061–TiB2-SiC-RhHeat TreatmentMetallic Matrix CompositesStir CastingJPM Publishers2024-09-30International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/93310-2/https://ijeresm.com/wp-content/uploads/2024/10/93310-Evaluation-of-Mechanical-Properties-of-Al6061-Composite-by-Stir-Casting-Method.pdfhttps://doi.org/10.58482/ijeresm.v3i3.910.58482/ijeresm.v3i3.9Vol. 3, Issue 3, pp. 51-58

oai:ijeresm.com:1033112024-09-30

Performance Study of Plain Cement Concrete Containing Quartz Powder and Eggshell Powder as Partial Replacement of CementAllu Taraka Rama RaoRavi KumarChandra Mouli V.S.AConcrete remains a mainstay among construction materials despite ongoing improvements to enhance its environmental friendliness and effectiveness. This study explores the effects of adding quartz and eggshell powder to concrete. The experimental investigation measures concrete samples’ compressive strength, split tensile strength, and flexural strength at 7, 28, and 90 days. Concrete mixes with varying percentages of quartz powder and eggshell powder and their combinations were prepared and tested. The findings show that using quartz and eggshell powder improves the strength characteristics of concrete, with several mixtures performing better than conventional concrete. The examination of experimental data highlights the potential of these supplementary materials to enhance the sustainability and durability of concrete structures. It provides valuable insights into the mechanisms contributing to the strength improvement. These results advance the field of construction materials by contributing to ongoing efforts to create high-performance, environmentally friendly concrete compositionsConcreteEggshell PowderQuartz PowderSandJPM Publishers2024-09-30International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/103311-2/https://ijeresm.com/wp-content/uploads/2024/10/103311-Performance-study-of-plain-cement-concrete-containing-Quartz-powder-and-Eggshell-powder-as-partial-replacement-of-cement.pdfhttps://doi.org/10.58482/ijeresm.v3i3.1010.58482/ijeresm.v3i3.10Vol. 3, Issue 3, pp. 59-69

oai:ijeresm.com:134042024-12-31

Enhancing the Performance and Durability of M35 Grade Concrete with Alccofine 1203Vipparthi AnithaP. GnanamoorthyCh. SivanarayanaM DurgaThe construction industry faces pressures to reduce its environmental footprint, prompting the exploration of sustainable materials that maintain or enhance conventional concrete’s performance. This study investigates Alccofine 1203, a high-performance micro-fine material, as a partial replacement for cement at increments of 5%, 10%, and 15%. Multiple concrete cubes were prepared and tested for compressive strength, flexural strength, workability, and durability. Fresh properties were evaluated using slump and flow tests, ensuring adequate workability, while long-term performance was assessed through durability tests, including permeability and chloride ion penetration. The results indicate that a 10% replacement of cement with Alccofine 1203 enhances the compressive strength and durability of concrete without compromising workability. Higher replacement percentages showed varied results, necessitating further investigation to optimize the mix design. This study highlights the potential of Alccofine 1203 as a sustainable alternative to traditional cement, offering significant implications for eco-friendly construction practices. This research contributes to the field by providing empirical data on Alccofine 1203’s effects on concrete, supporting the development of more sustainable building materials. Future work will focus on refining mix proportions and exploring Alccofine’s impact on other concrete properties such as shrinkage and creep.Alccofine 1203DurabilityEnvironmental impact in constructionSustainable construction materialsWorkabilityEco-friendlyJPM Publishers2024-12-31International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/13404-2/https://ijeresm.com/wp-content/uploads/2024/10/13404-Enhancing-the-Performance-and-Durability-of-M35-Grade-Concrete-with-Alccofine-1203.pdfhttps://doi.org/10.58482/ijeresm.v3i4.110.58482/ijeresm.v3i4.1Vol. 3, Issue 4, pp. 01-10

oai:ijeresm.com:234012024-12-31

Impact of Ceramic Insulator Waste as Partial Replacement of Coarse Aggregate in Concrete: An Experimental Study and Evaluation of Mechanical PropertiesSeelam RajeshK. Sai AnithaCh. SivanarayanaThe construction industry faces pressures to reduce its environmental footprint, prompting the exploration of sustainable materials that maintain or enhance conventional concrete’s performance. This study investigates Alccofine 1203, a high-performance micro-fine material, as a partial replacement for cement at increments of 5%, 10%, and 15%. Multiple concrete cubes were prepared and tested for compressive strength, flexural strength, workability, and durability. Fresh properties were evaluated using slump and flow tests, ensuring adequate workability, while long-term performance was assessed through durability tests, including permeability and chloride ion penetration. The results indicate that a 10% replacement of cement with Alccofine 1203 enhances the compressive strength and durability of concrete without compromising workability. Higher replacement percentages showed varied results, necessitating further investigation to optimize the mix design. This study highlights the potential of Alccofine 1203 as a sustainable alternative to traditional cement, offering significant implications for eco-friendly construction practices. This research contributes to the field by providing empirical data on Alccofine 1203’s effects on concrete, supporting the development of more sustainable building materials. Future work will focus on refining mix proportions and exploring Alccofine’s impact on other concrete properties such as shrinkage and creep.Ceramic Insulator WasteConcreteEnvironmental benefitsMechanical propertiesStructural integritySustainable construction.ceramic Insulator Wasteconcreteenvironmental benefitsmechanical propertiesstructural integritysustainable constructionJPM Publishers2024-12-31International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/23401-2/https://ijeresm.com/wp-content/uploads/2024/10/23401-Impact-of-Ceramic-Insulator-Waste-as-Partial-Replacement-of-Coarse-Aggregate-in-Concrete-An-Experimental-Study-and-Evaluation-of-Mechanical-Properties.pdfhttps://doi.org/10.58482/ijeresm.v3i4.210.58482/ijeresm.v3i4.2Vol. 3, Issue 4, pp. 11-19

oai:ijeresm.com:334032024-12-31

An Experimental Investigation on Partial Replacement of Oil Palm Shell as Coarse Aggregate and M Sand as Fine Aggregate with Elevated TemperatureVakula Bharathi GeddamCh. SivanarayanaP. GnanamoorthyConcrete plays a pivotal role in construction, and the quest to enhance its performance and sustainability is ongoing. Aggregates, comprising 70-80% of concrete, are traditionally made of crushed rocks as coarse aggregates and river sand as fine aggregates. However, increasing demand for these natural resources due to growing construction activities has escalated costs and raised environmental concerns. This study investigates the potential of using Oil Palm Shell (OPS) as a partial replacement for coarse aggregates and Manufactured Sand (M Sand) as a substitute for fine aggregates in M30 grade concrete. Furthermore, the study examines how these replacements affect the concrete’s properties when exposed to elevated temperatures. Various tests were conducted to evaluate slump, split tensile strength, compressive strength, and flexural strength of concrete specimens after 7, 14, and 28 days of curing. Concrete samples were prepared with varying proportions of OPS (5%, 10%, and 15%) and M Sand (10%, 20%, and 30%), along with combinations of both. The results indicated that the inclusion of OPS and M Sand improved the concrete’s strength properties, with certain mixtures outperforming conventional concrete. The analysis of these outcomes underscores the factors contributing to the enhanced strength, demonstrating the potential of OPS and M Sand in boosting the durability and sustainability of concrete structures. Adopting these materials not only reduces construction costs but also promotes environmentally sustainable practices within the construction industry.Acid CuringFlexural StrengthM SandOil Palm ShellsSubstitution for Aggregates.Substitution for AggregatesJPM Publishers2024-12-31International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/33403-2/An Experimental Investigation on Partial Replacement of Oil Palm Shell as Coarse Aggregate and M Sand as Fine Aggregate with Elevated Temperaturehttps://doi.org/10.58482/ijeresm.v3i4.310.58482/ijeresm.v3i4.3Vol. 3, Issue 4, pp. 20-28

oai:ijeresm.com:434092024-12-31

Embedded System-based Restaurant AutomationM. Shanmuka Satya Sudheer NaiduA PravinI Rama Satya Nageswara RaoK SivaranjaniThe restaurant industry is evolving rapidly, with technology playing a crucial role in enhancing customer satisfaction and operational efficiency. This paper proposes an embedded system-based restaurant automation (ESRA) system to automate key tasks such as order management, table monitoring, inventory control, and customer service. The ESRA system’s functionality, components, architecture, and benefits for restaurant operations are outlined in detail. In today’s competitive and fast-paced restaurant environment, effective management and service delivery are essential to meet customer expectations. By automating operations, the ESRA system offers a solution that improves efficiency, accuracy, and customer satisfaction compared to traditional manual processes.ArduinoEmbedded systemInventory ControlRestaurant AutomationJPM Publishers2024-12-31International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/43409-2/https://ijeresm.com/wp-content/uploads/2024/10/43409-Embedded-System-based-Restaurant-Automation.pdfhttps://doi.org/10.58482/ijeresm.v3i4.410.58482/ijeresm.v3i4.4Vol. 3, Issue 4, pp. 29-32

oai:ijeresm.com:534112024-12-31

Design and Implementation of an Autonomous Wheelchair with Medical Kit Access Using Raspberry PiNarayana Murty YK. RajasekharGidla Sudheer BabuS. N. BhargaviThis paper presents an autonomous wheelchair system designed to enhance the mobility of elderly individuals and people with disabilities through advanced automation and artificial intelligence. Recognizing the importance of independent movement for promoting physical and psychological well-being, this system addresses the challenges faced by those with limited mobility. The wheelchair leverages various sensors to minimize the need for human intervention, thereby fostering autonomy and reducing reliance on caregivers. The system includes an Android interface connected via Bluetooth, allowing for intuitive user interaction and control. Utilizing Raspberry Pi technology, the research aims to create a reliable framework that can adapt to user needs through data processing and analysis. Additionally, the system enables effective communication through head-mounted support, allowing users to record and relay information. Ultimately, this autonomous wheelchair aims to improve mobility and confidence for individuals with disabilities while enhancing their overall independence and quality of life.Artificial IntelligenceAutonomous WheelchairMedical KitRaspberry PiJPM Publishers2024-12-31International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/53411-2/https://ijeresm.com/wp-content/uploads/2024/10/53411-Design-and-Implementation-of-an-Autonomous-Wheelchair-with-Medical-Kit-Access-Using-Raspberry-Pi.pdfhttps://doi.org/10.58482/ijeresm.v3i4.510.58482/ijeresm.v3i4.5Vol. 3, Issue 4, pp. 33-37

oai:ijeresm.com:634052024-12-31

Evaluation of the Performance of Plain Cement Concrete with Partial Replacement of Cement by Natural Pumice Powder and PolypropyleneDivya Mani PalnatiNageswara Rao PasupuletiV Pavan KumarConcrete is a fundamental construction material that is continually evolving to enhance its performance and sustainability. This research explores the potential of incorporating natural pumice powder and polypropylene as partial substitutes for cement in M20-grade concrete. The aim is to assess how these alternative materials influence concrete properties and sustainability. Through a comprehensive evaluation, the study provides valuable insights into improving the characteristics and environmental impact of concrete structures. This experimental study examines properties such as split tensile strength, compressive strength, and flexural strength of concrete specimens after curing periods of 7, 14, and 28 days. Concrete mixes with varying proportions of pumice powder (5%, 10%) and polypropylene (5%, 10%), as well as their combinations, are meticulously prepared and tested. The results indicate that adding pumice powder and polypropylene positively affects the strength properties of concrete, with some mixtures performing better than conventional concrete. The analysis reveals the underlying mechanisms contributing to enhanced strength, emphasizing the potential of these materials to boost the durability and long-term sustainability of concrete structures. These findings contribute to ongoing efforts to develop eco-friendly and highly durable concrete, promoting advancements in construction engineering.Compressive Strength, Flexural Strength, Natural Pumice Powder, Polypropylene, Tensile StrengthCompressive StrengthFlexural StrengthNatural Pumice PowderPolypropyleneTensile StrengthJPM Publishers2024-12-31International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/63405-2/https://ijeresm.com/wp-content/uploads/2024/10/63405-Evaluation-of-the-Performance-of-Plain-Cement-Concrete-with-Partial-Replacement-of-Cement-by-Natural-Pumice-Powder-and-Polypropylene.pdfhttps://doi.org/10.58482/ijeresm.v3i4.610.58482/ijeresm.v3i4.6Vol. 3, Issue 4, pp. 38-47

oai:ijeresm.com:734062024-12-31

Performance Study of Cement Concrete Containing Natural Zeolite Powder and Glass Powder as Partial Replacement of CementGopichand GattiRahul Kumar SinghV Pavan KumarConcrete, as a fundamental construction material, is constantly evolving to enhance its performance and sustainability. This study explores the effects of incorporating natural zeolite powder and glass powder as partial replacements for cement in M50 grade concrete. The experimental investigation evaluates the compressive, split tensile, and flexural strengths of concrete specimens at 7, 14, and 28 days. Concrete mixtures containing various proportions of zeolite powder (10%, 20%, 30%) and glass powder (10%, 20%, 30%), both individually and in combination, were prepared and tested. Results indicate that the inclusion of zeolite and glass powders positively influences the strength properties of concrete, with certain mixes outperforming conventional concrete. The analysis of experimental data provides insights into the strength enhancement mechanisms and underscores the potential of these supplementary materials to improve the durability and sustainability of concrete structures. These findings contribute to the development of eco-friendly and high-performance concrete, advancing the field of construction materials engineering.Durability Properties, Glass powder, Environmental benefits, Mechanical Properties, Zeolite PowderDurability PropertiesGlass powderEnvironmental benefitsMechanical PropertiesZeolite PowderJPM Publishers2024-12-31International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/73406-2/https://ijeresm.com/wp-content/uploads/2024/10/73406-Performance-Study-of-Cement-Concrete-Containing-Natural-Zeolite-Powder-and-Glass-Powder-as-Partial-Replacement-of-Cement.pdfhttps://doi.org/10.58482/ijeresm.v3i4.710.58482/ijeresm.v3i4.7Vol. 3, Issue 4, pp. 48-56

oai:ijeresm.com:833052024-12-31

Antimicrobial Activity of Selected Medicinal Plants from Around Ujjain City, IndiaNikita PathakAlok Kumar SrivastavAyurveda, an ancient Indian medical system, emphasizes the use of natural elements to treat diseases and promote a balanced, healthy life. Polyherbalism—the practice of combining multiple herbs—enhances therapeutic efficacy and reduces toxicity. In this study, three medicinal plants, Moringa oleifera, Withania somnifera, and Acorus calamus, were examined for their antimicrobial and antioxidant properties. Phytochemical screening of these plants identified active compounds like alkaloids, tannins, saponins, and flavonoids. Solvent extractions using methanol, chloroform, petroleum ether, and water were conducted, and antimicrobial activity was tested against Staphylococcus aureus, Escherichia coli, Bacillus subtilis, B. cereus, and Pseudomonas aeruginosa using the disc diffusion method. Additionally, antioxidant properties were measured with the DPPH radical scavenging assay. This research highlights the potential of these plants to combat microbial infections and oxidative stress-related disorders.Antimicrobial Activity, Antioxidant Activity, Phytochemical Screening, Polyherbal Formulation, Traditional Medicine.Antimicrobial ActivityAntioxidant ActivityPhytochemical ScreeningPolyherbal FormulationTraditional MedicineJPM Publishers2024-12-31International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/83305-2/https://ijeresm.com/wp-content/uploads/2024/10/83305-Antimicrobial-Activity-of-Selected-Medicinal-Plants-from-Around-Ujjain-City-India.pdfhttps://doi.org/10.58482/ijeresm.v3i4.810.58482/ijeresm.v3i4.8Vol. 3, Issue 4, pp. 57-61

oai:ijeresm.com:933092024-12-31

A Comprehensive Study on Blockchain Technology and its Prospects to Create an Effective Internal Control SystemSaji Vithal VernekarAman GuptaGanesh ChavanThis paper explores the revolutionary impact of blockchain technology on internal control systems in organizations. In today’s interconnected and rapidly changing corporate landscape, businesses must establish efficient administrative control systems to mitigate risks and meet legal obligations. Blockchain technology, with its decentralized record-keeping and cryptographic security features, addresses many contemporary issues related to transparency, security, and efficiency. This study delves into how blockchain affects internal control frameworks by ensuring immutable transaction trails, improving traceability, and enhancing security, all while automating processes through smart contracts. Additionally, challenges such as scalability, interoperability, and regulatory compliance are discussed. The conclusion emphasizes that while blockchain is not a replacement for internal control systems, it acts as a powerful complement, strengthening overall system efficiency and effectiveness.Blockchain Technology, Business Organizations, Internal Control, Risk Management, SecurityBlockchain TechnologyBusiness OrganizationsInternal ControlRisk ManagementSecurityJPM Publishers2024-12-31International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/93309-2/https://ijeresm.com/wp-content/uploads/2024/10/93309-A-Comprehensive-Study-on-Blockchain-Technology-and-its-Prospects-to-Create-an-Effective-Internal-Control-System.pdfhttps://doi.org/10.58482/ijeresm.v3i4.910.58482/ijeresm.v3i4.9Vol. 3, Issue 4, pp. 62-65

oai:ijeresm.com:34122024-12-31

Exploring the Role of Diet in Yogic Wellness: Bridging Physiological, Psychological, and Spiritual DimensionsA. RadhikaK. SatyamurthyFood plays a vital role in maintaining the body, enhancing mental capacity, boosting immunity, and extending longevity. This paper explores the multidimensional significance of food in yogic practice, drawing from classical texts such as the Upanishads, Bhagavad-Gita, and Hatha Yoga Pradipika. These texts emphasize the classification of food into sattvic, rajasik, and tamasik, highlighting their effects on physical, mental, and spiritual well-being. The discussion extends to the functional value of food in yoga, focusing on its role in achieving harmony across physical, astral, and magnetic planes. Food is presented as a bridge between terrestrial needs and spiritual aspirations, fostering a balance between physiological, psychological, and transcendental dimensions. The paper also examines how food supports yoga practice through its therapeutic qualities, aligning with seasonal and geographical factors, and enabling holistic wellness. By integrating ancient wisdom with modern perspectives, the paper underscores the transformative power of yogic food, not only as nourishment but also as a tool for achieving self-realization and spiritual harmony.Anna, Druda Bhumi, Sattvik Food, Yogic Wellness.AnnaDruda BhumiySattvik FoodYogic WellnessJPM Publishers2024-12-31International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/3412-2/https://ijeresm.com/wp-content/uploads/2024/11/103412-Exploring-the-Role-of-Diet-in-Yogic-Wellness-Bridging-Physiological-Psychological-and-Spiritual-Dimensions.pdfhttps://doi.org/10.58482/ijeresm.v3i4.1010.58482/ijeresm.v3i4.10Vol. 3, Issue 4, pp. 66-70

oai:ijeresm.com:141012025-03-31

Reducing Carbon Footprints with On-Grid Photovoltaic Systems: A Path to SustainabilityMustafa Faisal GhlaimAsmaa Miran HusseinMustafa Fakhir HusseinThe unrelenting effort to mitigate carbon emissions has gained crucial momentum in establishing a secure and sustainable environment. Significant emphasis is being placed on achieving environmental sustainability and enhancing carbon capture. This study highlights the critical importance of solar photovoltaic (PV) energy systems in addressing environmental concerns and strengthening energy sectors. It specifically focuses on the emergence of connected photovoltaic systems and their potential to supply the energy sector while reducing carbon dioxide emissions. Through the design of a connected photovoltaic system with a maximum operating power of 584 kW under conditions of 1000 W/m² and 50°C, consisting of 1,095 modules covering an area of 2,994 m², the study demonstrated the system’s ability to save between 13,636 and 23,117 tons of carbon dioxide. These results indicate that photovoltaic systems are a sustainable and transformative solution capable of maintaining the energy sector’s balance by 2050. Furthermore, they serve as a pivotal link in promoting environmental enhancement through renewable, inexhaustible energy sources.Carbon emissionsCarbon footprintEco-friendlyPhotovoltaic energyPVsystRenewable sourcesSustainabilityJPM Publishers2025-03-31International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/14101-2/https://ijeresm.com/wp-content/uploads/2025/01/14101-Reducing-Carbon-Footprints-with-On-Grid-Photovoltaic-Systems-A-Path-to-Sustainability.pdfhttps://doi.org/10.58482/ijeresm.v4i1.110.58482/ijeresm.v4i1.1Vol. 4, Issue 1, pp. 01-10

oai:ijeresm.com:241022025-03-31

Green Hydrogen in the Middle East: Challenges and Opportunities for Sustainability and ComplianceMustafa Faisal GhlaimAsmaa Miran HusseinMustafa Fakhir HusseinDeveloping new green energy technologies is one of the significant solutions to meet the growing energy demand worldwide. However, due to ongoing conflicts, the rapid growth of green hydrogen energy technologies encounters various technical barriers, such as the declining adoption of wind and solar energy in several Middle Eastern countries, including Iraq, Syria, Lebanon, and Yemen. This study elucidates the importance of green hydrogen energy globally. It highlights the shift toward sustainability based on insights from recent research conducted between 2024 and 2025 and global energy trends aimed at enhancing environmental and energy security by 2050.Arab GulfDecarbonizationGreen Hydrogen EnergySolar EnergySustainabilityWind EnergyJPM Publishers2025-03-31International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/24102-2/https://ijeresm.com/wp-content/uploads/2025/01/24102-Green-Hydrogen-in-the-Middle-East-Challenges-and-Opportunities-for-Sustainability-and-Compliance.pdfhttps://doi.org/10.58482/ijeresm.v4i1.210.58482/ijeresm.v4i1.2Vol. 4, Issue 1, pp. 11-21

oai:ijeresm.com:341062025-03-31

Brand Equity and Consumer Response in the Food and Beverage Industry (Cafés) in Saudi ArabiaDalia DiabTahreem Noor KhanRaya Saad AlmjnoniIn the competitive landscape of the food and beverage industry, brand equity and consumer response are crucial aspects influencing a café’s success. This study investigates the impact of brand equity dimensions (brand awareness, brand association, brand loyalty, and perceived quality) on consumer response (purchase intention and brand preference) in the Saudi Arabian café industry. Using a quantitative approach, data were collected from 300 university students in Hail City through an electronic survey. The hypotheses were tested using multiple linear regression analysis in SPSS version 25.0. The findings revealed that brand loyalty and brand association significantly and positively influence overall brand equity, while perceived quality and brand awareness did not demonstrate a significant impact. A positive and significant correlation was also observed between overall brand equity and consumer response.Brand AssociationBrand EquityBrand LoyaltyCaféConsumer ResponsePerceived QualitySaudi ArabiaJPM Publishers2025-03-31International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/34106-2/https://ijeresm.com/34106-2/https://doi.org/10.58482/ijeresm.v4i1.310.58482/ijeresm.v4i1.3Vol. 4, Issue 1, pp. 22-30

oai:ijeresm.com:441102025-03-31

An Analysis of the Variables Influencing Consumers' Purchasing Decisions for Organic Food Items in RajkotThakrar Pooja TulshibhaiN. D. ZalaThis study explores the key factors influencing consumer behavior in the organic food market of Rajkot City. Empirical research reveals that price is the most significant determinant across demographic groups, strongly influenced by age, education, occupation, and monthly income. Age and income moderately affect brand perception, suggesting its relevance for specific consumer segments. Taste plays a crucial role, particularly among different genders, and is slightly influenced by education, highlighting the importance of sensory appeal in purchase decisions. While health benefits, environmental concerns, and organic certifications show limited demographic influence, they remain universal motivators for organic food consumption. The study also identifies key barriers: gender influences perceptions of limited availability, while age and education significantly affect awareness levels. Additionally, education impacts perceptions of availability, and occupation plays a role in consumer awareness. Notably, monthly income does not significantly affect any of the identified barriers. These insights contribute to a better understanding of consumer preferences and challenges in the organic food sector, offering valuable implications for marketers, policymakers, and businesses aiming to promote sustainable and organic consumption in Rajkot City.Consumer BehaviorDemographic FactorsOrganic FoodPurchasing DecisionsRajkot CitySustainabilityJPM Publishers2025-03-31International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/44110-2/https://ijeresm.com/wp-content/uploads/2025/03/44110-An_Analysis_of_the_Variables_Influencing_Consumers_Purchasing_Decisions_for_Organic_Food_Items_in_Rajkot.pdfhttps://doi.org/10.58482/ijeresm.v4i1.410.58482/ijeresm.v4i1.4Vol. 4, Issue 1, pp. 31-36

oai:ijeresm.com:541122025-03-31

Foreign Portfolio Investment in India's Capital Market: A Comprehensive Analysis of Equity and Debt FlowsNishita ThakrarThis research analyzes Foreign Portfolio Investment (FPI) trends in India’s equity and debt markets from 2019 to 2024. It examines the macroeconomic and global factors influencing FPI flows and their impact on India’s financial landscape. The study highlights notable fluctuations in FPI inflows and outflows, driven by geopolitical tensions, monetary policy shifts, and global uncertainties, including the COVID-19 pandemic. Through statistical analysis, the research identifies key patterns and correlations between FPI movements and domestic economic indicators such as interest rates, exchange rates, and market capitalization.Capital MarketCovid-19Debt MarketFPIInflow and OutflowJPM Publishers2025-03-31International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/54112-2/https://ijeresm.com/wp-content/uploads/2025/03/54112-FPI_in_Indias_Capital_Market_A_Comprehensive_Analysis_of_Equity_and_Debt_Flows.pdfhttps://doi.org/10.58482/ijeresm.v4i1.510.58482/ijeresm.v4i1.5Vol. 4, Issue 1, pp. 37-40

oai:ijeresm.com:641152025-03-31

Digital Literacy and E-learning Adoption Among Commerce Students: Challenges and Opportunities in BhokardanSatish DhokeThe rapid advancement of digital technology has transformed education, making e-learning a vital instructional method. However, its adoption in rural areas, particularly among commerce students in Bhokardan, presents significant challenges. This study explores the level of digital literacy among students and identifies the barriers to e-learning adoption, focusing on factors such as resource limitations, digital infrastructure, and student readiness. A sample of 100 students was analyzed using the Chi-square test to examine the relationship between digital literacy, resource availability, and e-learning adoption. The findings indicate that low digital literacy serves as a significant barrier. At the same time, limited access to devices and unreliable internet connectivity also hinder adoption, though their impact is statistically less significant. Despite these obstacles, the study highlights opportunities to enhance e-learning through targeted digital literacy training and improved access to technological resources. The results emphasize the need for strategic interventions to strengthen digital literacy and infrastructure, which could significantly improve educational outcomes in rural areas.BhokardanDigital DivideDigital LiteracyE-learning AdoptionInfrastructure BarriersRural EducationJPM Publishers2025-03-31International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/64115-2/https://ijeresm.com/wp-content/uploads/2025/03/64115-Digital_Literacy_and_E-learning_Adoption_Among_Commerce_Students_Challenges_and_Opportunities_in_Bhokardan.pdfhttps://doi.org/10.58482/ijeresm.v4i1.610.58482/ijeresm.v4i1.6Vol. 4, Issue 1, pp. 41-48

oai:ijeresm.com:741202025-03-31

India's Global Trade: A Comprehensive Study of Imports and Exports with Leading Trading NationsSuyog AmrutraoThis study presents India’s import and export patterns with its top ten trading partners. It aims to identify the variables that impact India’s trade ties and their implications for its economic growth. The paper examines trade data, market trends, and monetary policies. The study highlights the advantages and disadvantages of India’s international trade framework, focusing on key commodities, trade volumes, and bilateral trade agreements. The outcome shows how strategically significant these top trading partners have been in shaping India’s trade environment and provides insight into possible areas of policy action to improve trade performance. This study contributes to the understanding of India’s role in the global trade landscape and provides recommendations for fostering more substantial and equitable trade relationships.Economic ImpactExportsImportsInternational TradeMarket TrendExports, ImportsJPM Publishers2025-03-31International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/74120-2/https://ijeresm.com/wp-content/uploads/2025/03/74120-Indias_Global_Trade_A_Comprehensive_Study_of_Imports_and_Exports_with_Leading_Trading_Nations.pdfhttps://doi.org/10.58482/ijeresm.v4i1.710.58482/ijeresm.v4i1.7Vol. 4, Issue 1, pp. 49-53

oai:ijeresm.com:841292025-03-31

Exploring the Diversity of Rice Grain Variegation: A ReviewM. NiranjanaF. Kurus Malai SelviChallenges persist in developing a suitable method to distinguish high-quality cultivated rice seeds, which can be estimated based on their characteristics. To prevent rice grain varieties from being incorrectly labeled, the quality and type of rice grains must be accurately identified. In this paper, the classification of rice grains is analyzed, and a study is conducted on various algorithms used at each stage. Generally, visual observations are made by specialists using specialized devices that measure various properties. The resultant data are processed through different stages using multiple algorithms, which are discussed in detail. This study reviews machine learning techniques for differentiating rice seeds based on various algorithms. Each stage is analyzed with distinct objectives, and necessary conclusions are drawn to inform the next stage of research.ClassificationDeep LearningEnsemble ModelMachine LearningRice GrainJPM Publishers2025-03-31International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/84129-2/https://ijeresm.com/wp-content/uploads/2025/04/84129-Exploring_the_Diversity_of_Rice_Grain_Variegation_A_Review.pdfhttps://doi.org/10.58482/ijeresm.v4i1.810.58482/ijeresm.v4i1.8Vol. 4, Issue 1, pp. 54-61

oai:ijeresm.com:941332025-03-31

Study of Awareness Towards Life Skill Education among Secondary-level StudentsSuman Lata YadavThe concept of life skills is related to the way of life that emphasises the mutual exchange of knowledge, attitudes, and interpersonal skills in education. Its objective is to develop diverse skills among students and prepare them to face life’s challenges with determination. The World Health Organization has defined life skills as “the positive behaviours and tendencies that enable a person to adapt in day-to-day life.” Life skills are the abilities that enable a person to adapt and exhibit positive behaviour, allowing them to deal effectively with the problems and challenges of daily life. Life is a unique gift. Therefore, by equipping life with various skills, happiness, peace, and prosperity are created. In this research, with the objectives of the study in mind, an analytical examination of life skills among secondary-level students has been conducted. This research study examines the effects of living conditions, gender, and social class on students’ life skills and presents the findings. Future researchers can build upon this, and other factors affecting the research can also be explored.Education SystemLife skillsSchool StudentsSecondary LevelJPM Publishers2025-03-31International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/94133-2/https://ijeresm.com/wp-content/uploads/2025/04/94133-Study_of_Awareness_Towards_Life_Skill_Education_among_Secondary-level_Students.pdfhttps://doi.org/10.58482/ijeresm.v4i1.910.58482/ijeresm.v4i1.9Vol. 4, Issue 1, pp. 62-66

oai:ijeresm.com:142142025-06-30

Assessment of Heavy Metal Levels in Water Samples Collected from Odugbo River, Benue State, NigeriaAlfa Unekwiu DicksonUmonye Eunice ElachiDrinking water is essential for life worldwide and is used daily. However, the quality of this drinking water varies from one source to another. In this research, analysis of five heavy metals: Pb, Zn, Cu, Mn, and Cd was carried out using the AAS technique in four water samples꞉: upper river water (L1), middle river water (L2), lower river water (L3), and Bottled water. The results of the study showed that Pb was found in the range of 0.411±0.001 mg/L to 0.852±0.021 mg/L in all the water samples analysed which is above the permissible limits of USEPA (0.015 mg/L), WHO (0.01 mg/L), SON (0.01 mg/L), and NAFDAC (0.01 mg/L) indicating health risk. Report from the four samples indicated the concentrations of Zn to be in the range 0.140±0,003 mg/L to 0.171±0.003 mg/L, which is below the permissible limits of USEPA (5.0 mg/L), WHO (5 mg/L), NAFDAC (5 mg/L), and SON (3.0 mg/L), and hence, no possible health risk. The results of the findings showed that the concentration of Cu is within the range of 0.212±0.027 mg/L to 0.761±0.012 mg/L and is found to be lower when compared to WHO (2.0 mg/L), NAFDAC (1.5 mg/L), USEPA (1.3 mg/L), and SON (1.0 mg/L). Mn ranged from 0.140±0.002 mg/L to 0.162±0.002 mg/L, below the standard that all the regulatory agencies set. Cd was found in the range of 0.200±0.001 mg/L to 0.231±0.231 mg/L and was found to be above all the regulatory agencies. Therefore, there is a need to take proactive action following the results of this research, which showed that concentrations of Pb and Cd in all the water samples analysed were detected above the permissible limits of the regulatory bodies, which is a potential health risk, either short-term or long-term, to the human body. The study further reviewed the fact that the bottled water analysed is of no significant quality compared to the river water.AASHealth ConsciousHeavy MetalWater ContaminationJPM Publishers2025-06-30International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/14214-2/https://doi.org/10.58482/ijeresm.v4i2.110.58482/ijeresm.v4i2.1Vol. 4, Issue 2, pp. 01-06

oai:ijeresm.com:241302025-06-30

Oral Lesions Classification using EfficientNet Transfer Learning ModelDevika GAsha Gowda KaregowdaDue to their wide variety of diseases, oral lesions present a substantial diagnostic problem. This research uses deep learning techniques, particularly the EfficientNetB7 model, to present an automated categorisation analysis of oral lesions. The study divides lesions into benign and malignant categories using the Oral Lesions: Cancer Detection Dataset, comprising 2270 high-resolution pictures. Known for its effectiveness in processing large-scale image collections, the EfficientNetB7 architecture is employed in this work. The model successfully distinguishes between benign and malignant tumors with an exceptional accuracy rate of 99.12%. The study highlights the diagnostic dependability of the model by analyzing its performance, including metrics for sensitivity, specificity, and accuracy. Moreover, the study investigates how interpretable the model’s predictions are, emphasizing essential aspects that support its decision-making process.BenignEfficientNet-B7MalignantOral LesionsTransfer LearningJPM Publishers2025-06-30International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/24130-2/https://doi.org/10.58482/ijeresm.v4i2.210.58482/ijeresm.v4i2.2Vol. 4, Issue 2, pp. 07-13

oai:ijeresm.com:342052025-06-30

Enhancing Biometric Security: A Robust Voice Frequency Detector with CNN-BiLSTM and Anti-Spoofing MechanismsMahfudz Ahnan Al FaruqMohammad Givi EfgiviaThis study introduces a Voice Frequency Detector (VFD) framework to enhance biometric password authentication by addressing key challenges such as spoofing attacks, environmental noise, and natural variations in speaker voice due to health, emotion, or aging. The system leverages dynamic vocal features including fundamental frequency (F0), Mel-Frequency Cepstral Coefficients (MFCCs), and formant structures, integrated with a hybrid CNN-BiLSTM deep learning model and attention mechanisms for robust spectral-temporal analysis. An anti-spoofing subsystem employs spectral flatness and phase distortion features to detect synthetic and replayed voices. The methodology involves signal preprocessing (Wiener filtering, voice activity detection), feature extraction, and score fusion by combining deep learning outputs with anti-spoofing results. Experiments on a dataset of 100 speakers and 1,000 spoofed samples demonstrate strong performance, achieving an EER of 2.8% in controlled conditions and 5.0% in noisy environments, with over 91% accuracy against replay, synthetic, and voice conversion attacks. Statistical analysis confirms that MFCCs are the most discriminative feature, contributing to 62% of the variance. The VFD framework offers a secure, adaptive, and practical voice authentication solution suitable for finance, IoT, and access control applications. Future enhancements may explore multi-modal integration and transformer-based architectures for broader applicability.Anti-SpoofingCNN-BiLSTMDeep LearningMFCCsVoice BiometricsJPM Publishers2025-06-30International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/34205-2/https://doi.org/10.58482/ijeresm.v4i2.310.58482/ijeresm.v4i2.3Vol. 4, Issue 2, pp. 14-22

oai:ijeresm.com:442072025-06-30

Integration of Artificial Intelligence in Network Technology: A Literature ReviewGusnul MahesaMuhammad RizalAhmad TajriDimas Arya BagaskaraEflan Ananda PujitoMohammad Givi EfgiviaIntegrating Artificial Intelligence (AI) and network technology represents a transformative advancement in modern networks’ protection, management, and optimisation. This literature review presents a comprehensive overview of current developments, existing challenges, and future directions for AI applications in computer networking. The primary aim is synthesising recent research to illustrate how AI-driven technologies reshape traditional network models and drive the shift toward more intelligent, autonomous, and resilient infrastructures, particularly in emerging 5G and forthcoming 6G networks. Network systems have evolved from simple analogue designs into complex digital ecosystems that support high-speed communication, intelligent devices, and data-intensive applications. However, this rapid growth has outpaced the capabilities of traditional rule-based network management approaches, highlighting the need for adaptive, real-time solutions. AI through machine learning (ML) and deep learning (DL) offers powerful data processing, pattern recognition, and autonomous decision-making capabilities, positioning it as a key enabler for managing growing complexity, enhancing security, and supporting autonomous operations. A systematic review was employed to ensure methodological rigour, focusing on peer-reviewed journal articles, leading conference papers, and expert analyses related to AI use in network security, administration, and optimisation. Thematic and comparative analyses were conducted to identify key trends, performance indicators, and innovative developments across various network layers, particularly emerging AI paradigms such as dynamic graph learning, federated learning, and explainable AI (XAI). The review finds that AI significantly improves network performance, including enhanced intrusion detection, advanced threat analysis, intelligent traffic routing, predictive maintenance, and autonomous resource allocation. Furthermore, AI is instrumental in enabling the full potential of 5G and future 6G technologies, supporting features like network slicing, ultra-low latency communication, and novel use cases such as real-time remote healthcare and immersive extended reality (XR) experiences. Despite these advancements, several research gaps remain. These include the lack of standardisation, challenges balancing model interpretability with accuracy, real-time explainability, developing lightweight AI models suited for constrained networking hardware, and concerns around privacy and ethical use. This review ultimately underscores the importance of continued interdisciplinary collaboration to ensure responsible, effective, and sustainable integration of AI into networking. As the digital landscape continues to grow, AI will be essential in driving the development of faster, more intelligent, and more secure network environments.Artificial IntelligenceDeep LearningMachine LearningNetwork AutomationNetwork OptimizationSmart NetworksJPM Publishers2025-06-30International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/44207-2/https://doi.org/10.58482/ijeresm.v4i2.410.58482/ijeresm.v4i2.4Vol. 4, Issue 2, pp. 23-31

oai:ijeresm.com:542162025-06-30

Axial Compression Behaviour of Steel Square Column Filled with Steel Fibre ConcretePrakash K.CN. Siva KumarKorakuti HanumanthuSteel Fibre Concrete-Filled Steel Square Tubes (SFCFSST) represent a modern and highly efficient structural system that combines steel’s strength and enhanced fibre-reinforced concrete performance. These columns exhibit improved compressive strength, ductility, and overall structural integrity by integrating steel fibres and expansive agents into the concrete mix. Although using such composite columns remains a relatively new concept, their potential to enhance seismic resistance, load-bearing capacity, and fire resilience positions them as a promising solution for future construction practices. In this study, axial compression tests were completed. According to the test results, the axial compression behaviour of columns increases with the proportion of steel fibres replaced. It has higher ductility than regular Concrete Filled Steel Tubes (CFST) columns. In this article, the strength attributes of CFST structures were investigated utilising Steel Fibre in various proportions, i.e., 0%, 0.5%, 1%, 2%, and 3% as partial replacements for Coarse Aggregate.Axial CompressionCompression StrengthConcrete-Filled Steel TubesSteel FibreJPM Publishers2025-06-30International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/54216-2/https://doi.org/10.58482/ijeresm.v4i2.510.58482/ijeresm.v4i2.5Vol. 4, Issue 2, pp. 32-39

oai:ijeresm.com:642032025-06-30

Assessment of LPG Safety Knowledge and Handling by Domestic UsersRichard AmorinEric Broni-BediakoEric StemnLiquefied Petroleum Gas (LPG) is gaining high usage as a domestic fuel worldwide. The Government of Ghana is determined to increase access to 50% by 2030. However, due to its high flammability, unsafe gas usage has resulted in various casualties nationwide. This work, therefore, assessed the safety knowledge and handling of LPG across three cities in the Western Region of Ghana. A total of 1144 LPG users participated in the research. Information gathered included the origin and material used for cylinder manufacturing, cylinder integrity test, refilling, transportation, storage, leakage detection and rectification, cylinder maintenance, safety valves, and other accessories such as LPG hoses and burners. The assessment showed that most users lacked basic safety knowledge regarding safe gas handling. It was evident that 99.2% had never examined and pressure-tested their cylinders for integrity purposes, with 98.0% not knowing when their cylinders would be due for either disposal or a mandatory pressure test. Further, the majority transported and stored their gas cylinders incorrectly. Also, 30.4% have been using their hoses for ≥ 5 years, with the majority replacing them not based on the recommended usage period but rather on damage. These practices are alarming, warranting an urgent need to intensify safety education on the safe use of this greener fuel. Several practical implications of the research that can improve the safe handling and use of LPG at the household level have been discussed.Domestic UsersLeakageLPGPressure TestStorageTransportationJPM Publishers2025-06-30International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/64203-2/https://doi.org/10.58482/ijeresm.v4i2.610.58482/ijeresm.v4i2.6Vol. 4, Issue 2, pp. 40-50

oai:ijeresm.com:742172025-06-30

Health Information Dissemination on Anti-Malarial Drug Resistance by Librarians and Its Use Among Post-Natal Mothers in Odugbo, Benue State, NigeriaAbubakar UsmanNura Mohammed MusaThe purpose of this paper was to investigate how librarians in the Federal College of Education Library, Odugbo, Benue State, have disseminated health information on anti-malarial drug resistance, and how post-natal mothers have utilised that information. The study adopted a survey research design. The study had a sample size of 192, comprising 187 post-natal mothers and five librarians. Due to the manageable population size, a total enumeration (census) method was employed. Separate questionnaires and an observation checklist were used as data collection instruments. A total of 187 copies of the questionnaire were administered to post-natal mothers, and 5 to librarians. Out of these, 184 (99.4%) and all 5 (100%) were correctly completed and returned, respectively. The data was analysed using descriptive statistics. The study findings indicated that the effects of librarians’ information dissemination on anti-malarial drug resistance among post-natal mothers are moderate. It further revealed that, according to the post-natal mothers, the actual use of the disseminated information had a relatively lower impact on addressing anti-malarial drug resistance. The perceptions of a subset of mothers (12 respondents) indicated that access to information helped them understand child delivery, gain general health and medical knowledge, recognise the consequences of drug misuse, and adhere strictly to malaria prescriptions and medications. Among other recommendations, the study suggests that the management of the Federal College of Education should collaborate with healthcare providers to offer timely and relevant information on the prevention and treatment of malaria.Anti-malarial drug resistanceHealth informationMalariaPost-natal mothersMalignantJPM Publishers2025-06-30International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/74217-2/https://doi.org/10.58482/ijeresm.v4i2.710.58482/ijeresm.v4i2.7Vol. 4, Issue 2, pp. 51-59

oai:ijeresm.com:842382025-06-30

An Assessment of the Potential Benefits of Refining Crude Oil in GhanaRichard AmorinCornelius B. BavohBayorbor YasmeenMohammed HamzahRefining is vital in the oil and gas industry, converting crude oil into products like gasoline, diesel, and LPG. Since discovering oil in 2007, Ghana’s petroleum sector has experienced significant growth; however, the country still relies on imports to meet its domestic demand, importing nearly four million metric tonnes of petroleum products in 2022, with gas oil (diesel) being the most significant component. This study, therefore, explored the potential benefits of refining Ghana’s crude oil, with a focus on its economic feasibility and the implications thereof. Considering the construction of a new refinery, a cost-benefit analysis was conducted using the Jubilee field crude oil, evaluating Net Present Value (NPV), Return on Investment (ROI), and Payback Period with the aid of Aspen HYSYS and an Excel Spreadsheet. The cost-benefit analysis indicated a positive NPV, a payback period of 3.5 years and an ROI of 29%. The predicted cost savings for local refining, with 2022 as a case, were estimated to be $1.4 billion (GH₵16.3 billion). By refining petroleum locally, an estimated net gain of $8.66 (GHS 96.99) per barrel was computed. A 2013 – 2033 forecast analysis projected increasing consumption volumes, rising import costs, and escalating ex-pump prices, further supporting the need for enhanced local refining capacity. The Government of Ghana should therefore prioritize refining crude oil locally as part of its industrialization strategy. This will help create jobs, generate foreign exchange savings, and enhance energy security.Crude oilEconomic AnalysisForecastRefiningJPM Publishers2025-06-30International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/84238-2/https://doi.org/10.58482/ijeresm.v4i2.810.58482/ijeresm.v4i2.8Vol. 4, Issue 2, pp. 60-67

oai:ijeresm.com:942332025-06-30

Assessing Computer Science Teachers' Competence in Constructing Essay Test Items: A Comparative Study of Lower and Higher Order Thinking Skills in Junior Secondary Schools in Benue StateAegiri Isaiah AgamaAkong Anthony AgboroThis study assessed the competence of junior secondary school Computer Science teachers in Benue State, Nigeria, in constructing essay test items based on Bloom’s Taxonomy, comparing the LOTS and HOTS. Adopting a descriptive survey design, the study was guided by two research questions and a hypothesis. The scope targeted junior secondary school Computer Science teachers in the state, and stratified disproportionate random sampling was used to select 105 teachers. Data was collected using the Computer Science Teachers’ Essay Test Item Construction Competency Test (CSTETICCT), a validated 30-item instrument covering all six cognitive levels of Bloom’s Taxonomy. Instrument reliability was confirmed through a pilot test involving 20 respondents, yielding a KR-20 coefficient of 0.85. Descriptive statistics (frequencies, percentages, means, and standard deviations) and visual aids (charts and graphs via Microsoft Excel) were used for data presentation. Inferential statistics, including t-test, ANOVA, and post hoc analysis, were conducted using SPSS Version 20. Findings, among others, revealed that teachers demonstrated high competence in constructing items for lower-order thinking skills (knowledge and comprehension), moderate ability at the application level, and low competence in higher-order thinking skills (analysis, synthesis, and evaluation), these different competency levels in constructing items that assess LOTS and HOTS were found to be significant. The study concludes that while teachers are proficient in evaluating lower-order cognitive skills, there is a notable gap in their ability to develop higher-order assessment items. It recommends continuous professional development, curriculum revision to include specialised Computer Science training, optional certification in assessment design, and mentorship programs to enhance teachers’ assessment competencies across all cognitive levels.AssessmentConstruction CompetencyEssay TestsTeachers’ CharacteristicsJPM Publishers2025-06-30International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/94233-2/https://doi.org/10.58482/ijeresm.v4i2.910.58482/ijeresm.v4i2.9Vol. 4, Issue 2, pp. 68-76

oai:ijeresm.com:143042025-09-30

Improving Concrete Strength using Jute Fiber Reinforcement with Surface TreatmentsSaniul Haque MahiMd. Sabbir AhmedMehedi HasanMd. Wahidur RahmanJamal HossainMd. Ariful Islam BelalMd. Razu AhmedThe significance of concrete in the construction sector may include strength and durability, but because of the low tensile strength and the cracking tendencies, its applicability is severely limited on many occasions. Fibers are also finding their way into concrete to counter such problems by enhancing their tensile strength, crack-bridging capacity, and general durability. This paper reflects on the effects of jute fiber reinforcement on the mechanical properties of concrete, in this case, compressive strength, split tensile strength, and workability. M20-grade concrete was mixed with jute fibers at 0.1%, 0.2%, and 0.4% volume fractions and treated with three different methods: alkali (6% NaOH), acidic (2% HCl), and hot water (80–100°C). Workability of the concrete was determined by carrying out a slump test, and the mechanical behavior of the concrete by the compressive and split tensile strength tests. It was found that by the addition of the jute fibers, there was a decrease in the workability of the mixture, such that an increase in fiber content resulted in a decrease in the slump. The alkali treatment enhanced workability and fiber dispersion, whereas the acidic treatment had the greatest impact on the reduction of workability since the fibers are degraded in the acidic treatment. As far as strength is concerned, alkali-treated jute fibers resulted in the best improvements on compressive and split tensile strength, especially for low fiber contents. Untreated and acidic-treated fibers, on the other hand, were weaker, especially at higher contents, because fibers did not disperse well and were weakly bonded to the matrix. It can be concluded that alkali treatment on jute fiber reinforced concrete improves strength and durability to a significant extent.Concrete StrengthFiber DispersionJute Fiber ReinforcementSurface TreatmentsSustainable ConstructionJPM Publishers2025-09-30International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/14304-2/https://ijeresm.com/wp-content/uploads/2025/08/14304-Improving_Concrete_Strength_using_Jute_Fiber_Reinforcement_with_Surface_Treatments.pdfhttps://doi.org/10.58482/ijeresm.v4i3.110.58482/ijeresm.v4i3.1Vol. 4, Issue 3, pp. 01-07

oai:ijeresm.com:243022025-09-30

Integrating COBIT and ISO Frameworks in IT Audits: A Literature ReviewMuhammad Fauzan HanifAhmad Rofik HarahapAde FakhrudinFadli Fatih MadinaDimas FebriawanThe accelerated evolution of information technology (IT) has compelled organizations to adopt structured governance frameworks to enhance audit efficacy and ensure robust information security. This study presents a systematic literature review examining the integration of COBIT and ISO/IEC 27001 within IT audit practices. Employing a qualitative descriptive methodology, the review synthesizes insights from seven primary scholarly sources, including case studies from both public and private sectors. The analysis delineates integration patterns, identifies best practices, and explores the synergistic potential of aligning COBIT’s strategic governance capabilities with the technical control rigour of ISO/IEC 27001. Findings demonstrate that such integration enhances audit capability maturity, facilitates structured risk mitigation, and fosters alignment between IT functions and organizational objectives. Nonetheless, notable research gaps persist, particularly the scarcity of quantitative assessments, limited cross-sector generalizability, and the absence of longitudinal evaluations of implementation outcomes. Additionally, practical challenges—including integration complexity, inadequate human resource competencies, and the lack of standardized implementation guidelines—impede broader adoption. The study concludes that integrating COBIT and ISO/IEC 27001 constitutes a viable foundation for advancing IT governance and audit maturity. However, further empirical investigation and development of pragmatic toolkits are essential. These insights aim to inform auditors, IT governance professionals, and policy makers in devising adaptive, standard-aligned audit strategies.COBITISO/IEC 27001IT AuditRisk ManagementJPM Publishers2025-09-30International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/24302-2/https://ijeresm.com/wp-content/uploads/2025/08/24302-Integrating_COBIT_and_ISO_Frameworks_in_IT_Audits_A_Literature_Review.pdfhttps://doi.org/10.58482/ijeresm.v4i3.210.58482/ijeresm.v4i3.2Vol. 4, Issue 3, pp. 08-14

oai:ijeresm.com:343052025-09-30

Effect of Surface Hardening by Gas Nitriding on the Fatigue Resistance of Low Alloy Steel EN 1.8509 (41CrAlMo7-10)Mahmood A. MohammedMohammed Z. HasanMohammed Salam TahaIn this research, the fatigue resistance of low alloy steel was improved by using surface hardening by gas nitridation at different temperatures, 475 to 610°C, and in a medium containing 70% nitrogen and 30% hydrogen. The results obtained showed a significant improvement in the fatigue resistance of the samples used after the nitridation process, where the highest fatigue resistance was obtained (580 MPa) at the temperature range 475 to 510°C. At the same time, there was a decrease in the fatigue resistance when using high temperatures in the gas nitridation process, which decreased to 400 MPa at 610 °C. In comparison, the value of the fatigue resistance before nitridation was 325 MPa. Through the results of the micro hardness and tensile test, it was found that there was an increase in the hardness tensile strength values on the surface and in general for all groups of samples treated by nitriding, It was also observed that the hardness gradually decreased smoothly as we moved away from the surface towards the depth, as the metal retains good hardness up to a depth of 300 microns. It helps to avoid the sudden and non-gradual transition from a rigid surface to a soft center. Thus, a structure of sufficient thickness is formed from the nitriding layer, coherent with the core. The results of the X-ray diffraction examination also showed the formation of nitrides of various alloying elements, Fe3N, Fe4N, Cr2N, Fe2Al5, Al2N, which have a significant role in increasing the hardness and improving the fatigue resistance.Fatigue ResistanceGas NitridingHardnessLow Alloy SteelSurface HardeningTensile StrengthJPM Publishers2025-09-30International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/34305-2/https://ijeresm.com/wp-content/uploads/2025/08/34305-Effect_of_Surface_Hardening_by_Gas_Nitriding_on_the_Fatigue_Resistance_of_Low_Alloy_Steel_EN_1.8509_41CrAlMo7-10.pdfhttps://doi.org/10.58482/ijeresm.v4i3.310.58482/ijeresm.v4i3.3Vol. 4, Issue 3, pp. 15-21

oai:ijeresm.com:443012025-09-30

Assessment of the Water Quality of the Odugbo River in Benue State, Nigeria for Irrigation FarmingAlfa Unekwu DicksonUmonye Eunice ElachiFood insecurity remains a pressing global issue, particularly in rapidly growing communities such as Odugbo, which may face challenges in sustaining food supply due to increasing population pressure. To mitigate this, the adoption of off-season irrigation farming becomes essential. In this study, water samples were collected during the dry season from three points along a river in the Odugbo area: the upper course (P1), middle course (P2), and lower course (P3). Physical parameters, heavy metal concentrations using Atomic Absorption Spectrophotometry (AAS), and anion levels via titration methods were analyzed.AnionsHeavy MetalsIrrigation WaterOff-season FarmingWater QualityJPM Publishers2025-09-30International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/44301-2/https://ijeresm.com/wp-content/uploads/2025/08/44301-Assessment_of_the_Water_Quality_of_the_Odugbo_River_in_Benue_State_Nigeria_for_Irrigation_Farming.pdfhttps://doi.org/10.58482/ijeresm.v4i3.410.58482/ijeresm.v4i3.4Vol. 4, Issue 3, pp. 22-28

oai:ijeresm.com:543082025-09-30

Re-Envisioning Talent Management in the 5th Industrial Revolution: A Conceptual Framework Integrating Systems and Design ThinkingKumar Aditendra Nath Shah DeoAnu PriyaThe 5th Industrial Revolution (5IR) is reshaping the global business landscape by integrating artificial intelligence, robotics, and the Internet of Things with a renewed focus on human-centered innovation. Talent management (TM), traditionally regarded as a human resources function, must re-envision itself within this paradigm. This paper develops a conceptual framework that applies systems thinking and design thinking to talent management in the context of the 5IR, enabling organizations to remain agile, innovative, and resilient. Systems thinking offers a holistic perspective on understanding the interconnections within the talent ecosystem, while design thinking promotes creative, empathetic, and human-centered solutions. Drawing on recent research on coopetition in SMEs, project-based talent development, global talent practices, and digital readiness in the public sector, the framework highlights the importance of upskilling, leadership support, and the responsible adoption of AI. The outcomes suggest that organizations should adopt holistic and adaptive talent management practices to address skills gaps, foster innovation, and maintain a competitive advantage in the rapidly evolving global environment.5th Industrial RevolutionDesign ThinkingHuman-Centered InnovationSystems ThinkingTalent ManagementJPM Publishers2025-09-30International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/54308-2/https://ijeresm.com/wp-content/uploads/2025/09/54308-Re-Envisioning_Talent_Management_in_the_5th_Industrial_Revolution.pdfhttps://doi.org/10.58482/ijeresm.v4i3.510.58482/ijeresm.v4i3.5Vol. 4, Issue 3, pp. 29-34

oai:ijeresm.com:643072025-09-30

Public Libraries in the Digital Age: An Indian PerspectiveJogen SharmaThis paper examines the state and challenges of public libraries in India amid the ongoing digital transformation. With over 75,000 rural and nearly 5,000 urban libraries, India’s public library network plays a crucial role in democratizing information access but faces significant issues, including funding disparities, staffing shortages, uneven ICT adoption, and limited digital resources, particularly in rural and underserved areas. The study examines staffing patterns, budgeting, collection development, ICT integration, and national policy frameworks, utilizing government reports and relevant literature. Findings highlight critical gaps in infrastructure, professional capacity, and policy implementation that hinder efforts to modernize. The paper recommends targeted investments in digital infrastructure, professional training, stable funding mechanisms, policy reform, and the development of multilingual resources to bridge the digital divide and enhance library services for inclusive lifelong learning.Public LibrariesICT IntegrationPolicy FrameworksLibrary StaffBudgetingCollection DevelopmentLibrary ManagementJPM Publishers2025-09-30International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/64307-2/https://ijeresm.com/wp-content/uploads/2025/10/64307-Public_Libraries_in_the_Digital_Age_An_Indian_Perspective.pdfhttps://doi.org/10.58482/ijeresm.v4i3.610.58482/ijeresm.v4i3.6Vol. 4, Issue 3, pp. 35-41

oai:ijeresm.com:743102025-09-30

AI-Driven Multimodal Emotion Recognition and Personalized Recommendations Using Power BIPooja Sithrubi GnanasambanthanM. Gnana PriyaMental health challenges demand innovative, non-invasive interventions to reduce stress and enhance emotional stability. Music has long served as a therapeutic medium; however, existing approaches often rely on generic playlists that lack personalization and adaptability to an individual’s psychological state. This paper presents a novel framework that combines webcam-based facial expression analysis with questionnaire-based self-reports to achieve robust emotion detection. The proposed system employs deep learning models to extract emotional cues from visual data, while structured self-assessments provide subjective validation of user states. A fusion mechanism integrates both modalities to enhance the accuracy and reliability of emotion recognition. Based on the detected emotional profile, personalized music recommendations are generated and visualized through interactive Power BI dashboards. This multimodal, AI-driven approach bridges traditional music therapy with modern data analytics, enabling adaptive, accessible, and user-centric mental health support. The experimental results highlight the potential of this method to enhance emotional well-being, alleviate stress, and increase access to personalized therapy.Mental healthMusic therapyArtificial Intelligence (AI)Multimodal Emotion recognitionPower BIJPM Publishers2025-09-30International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/74310-2/https://ijeresm.com/wp-content/uploads/2025/10/74310-AI-Driven_Multimodal_Emotion_Recognition_and_Personalized_Recommendations_Using_Power_BI.pdfhttps://doi.org/10.58482/ijeresm.v4i3.710.58482/ijeresm.v4i3.7Vol. 4, Issue 3, pp. 42-51

oai:ijeresm.com:843112025-09-30

Rationalization of Next-Generation GST Reforms: Enhancing Ease of Doing Business and Economic CompetitivenessSatish M DhokeIndia’s Goods and Services Tax, introduced in 2017, was envisioned as a transformative reform to unify indirect taxation and foster competitiveness. However, compliance burdens, multiple tax slabs, and frequent rule changes continue to limit efficiency. This study examines the impact of next-generation GST reform, including compliance simplification, slab rationalization, and digital automation, on the ease of doing business and competitiveness, with a focus on enterprises in the state of Maharashtra. A mixed-methods design combined survey data from 200 GST-registered businesses with expert interviews. Findings indicate that rationalization significantly improves operational efficiency, reduces transaction costs, and strengthens competitiveness, with digital automation emerging as the strongest predictor. The study concludes that GST rationalization is not merely an administrative adjustment but a strategic imperative for India’s economic growth.GST RationalizationEase of Doing BusinessDigital AutomationTax Slab ReformEconomic CompetitivenessMSMEsJPM Publishers2025-09-30International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/84311-2/https://ijeresm.com/wp-content/uploads/2025/10/84311-Rationalization_of_Next-Generation_GST_Reforms_Enhancing_Ease_of_Doing_Business_and_Economic_Competitiveness.pdfhttps://doi.org/10.58482/ijeresm.v4i3.810.58482/ijeresm.v4i3.8Vol. 4, Issue 3, pp. 52-59

oai:ijeresm.com:144052025-12-31

Ensemble Approach for Hypertension Risk Prediction Using Clinical and Demographic FeaturesOkebule ToyinOguntimilehin AbiodunAbiola O.BHypertension, also known as high blood pressure, is a major risk factor for cardiovascular diseases and stroke, and it often progresses silently until severe complications arise. Early detection is therefore essential for timely management and prevention. Traditional screening methods, however, do not always integrate multiple risk factors for accurate and early identification. This study develops a hypertension prediction system using deep learning and ensemble machine-learning techniques based on a dataset containing demographic, clinical, and lifestyle features. A Multi-Layer Perceptron (MLP), Random Forest, and XGBoost were trained and evaluated, with the Random Forest achieving an accuracy of 87.13%, XGBoost 84.50%, and the MLP 76.28%. An ensemble of the three models achieved 94% accuracy, indicating improved stability and predictive capability. While the system performs well, limitations such as possible overfitting and population-specific bias are noted. The study contributes to AI-driven healthcare by demonstrating a practical approach for early hypertension risk prediction. Future work may involve expanding the dataset, incorporating additional clinical indicators, and improving model robustness across diverse populations.Hypertension PredictionDeep LearningMachine LearningEnsemble ModelHealthcare AnalyticsJPM Publishers2025-12-31International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/14405-2/https://ijeresm.com/wp-content/uploads/2025/12/14405-Ensemble_Approach_for_Hypertension_Risk_Prediction_Using_Clinical_and_Demographic_Features.pdfhttps://doi.org/10.58482/ijeresm.v4i4.110.58482/ijeresm.v4i4.1Vol. 4, Issue 4, pp. 01-11

oai:ijeresm.com:244232025-12-22

Influence of Agricultural Waste and Ceramic Reinforcement on the Hardness of Aluminium 7075 Hybrid CompositesGururaj HattiRushikesh ShindeSandesh MindolkarSurendra GavadaRufiyat MulimaniMetal Matrix Composites offer superior mechanical properties compared to monolithic alloys, making them highly suitable for demanding engineering applications. This study investigates the mechanical behavior of an Aluminum 7075 alloy reinforced with Tungsten Carbide (WC) and Cow Dung Ash (CDA) fabricated via stir casting. The primary objective of this study was to evaluate the effect of hybrid reinforcement on the composite's hardness. The results indicated that the incorporation of WC and CDA significantly enhanced the hardness of the Al 7075 matrix. Specifically, the hybrid composite containing 3.5 wt.% WC and 1.5 wt.% CDA exhibited the highest hardness (35 HRB), representing a substantial improvement compared to the lower-WC compositions studied. These findings suggest that modifying Al 7075 with WC and CDA is a viable strategy for developing cost-effective high-strength composites.Cow Dung Ash (CDA)Hybrid Aluminum Metal Matrix Composite (HAMMC)HardnessStir CastingTungsten Carbide (WC)JPM Publishers2025-12-22International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/24423-2/https://ijeresm.com/wp-content/uploads/2025/12/24423-Influence_of_Agricultural_Waste_and_Ceramic_Reinforcement_on_the_Hardness_of_Aluminium_7075_Hybrid_Composites.pdfhttps://doi.org/10.58482/ijeresm.v4i4.210.58482/ijeresm.v4i4.2Vol. 4, Issue 4, pp. 12-17

oai:ijeresm.com:344202025-12-29

Forensic Accounting in Education: Empirical Evidence from Higher Education Institutions in KarnatakaUsha CForensic accounting has emerged as an important area of study in commerce education due to the increasing complexity of financial fraud and corporate malpractice. The present study examines the awareness, curriculum inclusion, resource availability, and overall effectiveness of forensic accounting education among academicians and students of higher education institutions in Karnataka. Primary data were collected using a structured questionnaire from 189 academicians and 180 students through a Google Form survey. A quantitative approach was adopted, and the data were analysed using reliability analysis, one-sample t-test, and multiple regression techniques. The findings of the study reveal that curriculum inclusion has the highest impact on the effectiveness of forensic accounting education, followed by awareness and resource availability. The regression model indicates a strong relationship among the variables, explaining 90 percent of the variation in effectiveness. The results highlight the need to strengthen forensic accounting education through structured curriculum integration, awareness programmes, and adequate institutional support. The study concludes that enhancing forensic accounting education can equip students with essential skills for fraud detection and financial investigation, thereby improving their professional readiness in commerce.Commerce EducationCurriculum InclusionForensic AccountingResource AvailabilityJPM Publishers2025-12-29International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/34420-2/https://ijeresm.com/wp-content/uploads/2025/12/34420-Forensic_Accounting_in_Education_Empirical_Evidence_from_Higher_Education_Institutions_in_Karnataka.pdfhttps://doi.org/10.58482/ijeresm.v4i4.310.58482/ijeresm.v4i4.3Vol. 4, Issue 4, pp. 18-24

oai:ijeresm.com:444312025-12-30

Machine Learning–Based Prediction of Organic Solar Cell Performance Using Molecular DescriptorsMohammed Saleh AlshaikhThe performance of Organic Solar Cells (OSCs) is intrinsically linked to the molecular, electronic, and structural properties of donor and acceptor materials. This study employs various machine learning techniques, namely the Generalized Regression Neural Network (GRNN), Support Vector Machine (SVM), and Tree Boost, to predict key performance metrics of OSCs, including power conversion efficiency (PCE), short-circuit current density (JSC), open-circuit voltage (VOC), and fill factor (FF). The models are trained and evaluated using an experimentally reported dataset compiled by Sahu et al. Correlation analysis demonstrates that material characteristics such as polarizability, bandgap, dipole moment, and charge transfer are statistically associated with OSC performance. The predictive performance of the GRNN model is compared with that of the SVM and Tree Boost models, showing consistently lower prediction errors within the considered dataset. In addition, sensitivity analysis is performed to assess the relative importance of the predictor variables and to examine the influence of kernel functions on GRNN performance. The results indicate that machine learning models, particularly GRNN, can serve as effective data-driven tools for predicting the performance of organic solar cells and for supporting computational screening studies.General Regression Neural NetworksOrganic Solar CellsPower Conversion EfficiencySensitivity AnalysisSupport Vector MachineTree BoostJPM Publishers2025-12-30International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/44431-2/https://ijeresm.com/wp-content/uploads/2025/12/44431-Machine-Learning–Based_Prediction_of_Organic_Solar_Cell_Performance_Using_Molecular_Descriptors.pdfhttps://doi.org/10.58482/ijeresm.v4i4.410.58482/ijeresm.v4i4.4Vol. 4, Issue 4, pp. 25-41

oai:ijeresm.com:544292025-12-31

Contractors’ Selection Criteria and Construction Project Outcome in Rivers StateReuben A. OkerekeKaanasor B. NwineThe building industry plays a leading role in the macroeconomic development of sovereign states, particularly in the provision of essential infrastructure such as bridges, motorways, and other structures that underpin commercial activity. However, the same sector in emerging economies often struggles to deliver projects that fully meet planned performance targets, largely due to inadequate contractor selection procedures. This paper examined the relationship between contractor selection standards and construction project performance outcomes. The survey tool consisted of 29 items on a five-point Likert scale and was administered to 132 officers of the Rivers State Universal Basic Education Board (RSUBEB). Data analysis was conducted using descriptive statistics and Pearson correlation analysis with SPSS V.23. The results revealed a strong positive relationship (r = 0.846; p = 0.000) between the rigor of contractor selection requirements and positive project results. Based on that, the research proposes that standardized evaluation metrics that emphasize financial soundness, technical skills, prior experience, and resource availability should be prioritized as key factors associated with improved construction project performance.Construction CostConstruction ProjectsContractorsEconomic DevelopmentSelection StrategiesJPM Publishers2025-12-31International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/54429-2/https://ijeresm.com/wp-content/uploads/2025/12/54429-Contractors_Selection_Criteria_and_Construction_Project_Outcome_in_Rivers_State.pdfhttps://doi.org/10.58482/ijeresm.v4i4.510.58482/ijeresm.v4i4.5Vol. 4, Issue 4, pp. 42-54

oai:ijeresm.com:05101009502026-02-08

A Hybrid VGG-ResNet Feature Fusion Network for Object Detection in Side-Scan Sonar ImagesVenkata Lakshmi Keerthi KVijayalakshmi PRajendran VSide-scan sonar images present significant challenges for object detection due to high noise levels, limited spatial resolution, and complex seabed structures. These factors, along with speckle noise and acoustic shadowing effects, further complicate reliable target detection. Nonetheless, object detection is extremely important in many areas, including marine archaeology, underwater search and rescue, mine countermeasures operations, and the inspection of critical national infrastructure, to improve safety and operational efficiency. In this work, a hybrid convolutional neural network (CNN) is presented for object detection in challenging side-scan sonar imagery. The proposed model combines the complementary feature-extraction capabilities of VGG-16 and ResNet-50 via feature fusion to improve target discrimination in sonar images. Transfer learning from ImageNet-pretrained backbones is employed to address data sparsity and improve model generalization on sonar datasets. Experimental evaluation demonstrates that the proposed model achieves an overall classification accuracy of 84.2% and a mean Average Precision (mAP) of 88.35%, outperforming several existing methods. The results pave the way to enhance the efficacy and accuracy of underwater surveys, search-and-rescue missions, and seabed mapping.feature fusionVGG-16ResNet-50hybrid CNNSide-scan sonarunderwater object detectionJPM Publishers2026-02-08International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/0510100950-3/https://ijeresm.com/wp-content/uploads/2026/02/0510100950.pdfhttps://doi.org/10.58482/ijeresm.v5i1.110.58482/ijeresm.v5i1.1Vol. 5, Issue 1, pp. 01-12

oai:ijeresm.com:05102009262026-02-19

Development and Evaluation of Automotive Lubricating Oil from Jatropha curcas OilIsaac NsorBennetta KoomsonPatrick BoakyeA Jatropha curcas-based bio-lubricant was developed and evaluated for automotive applications through acid esterification, base-catalyzed transesterification, in-situ peracetic acid epoxidation, and multi-additive blending. The molecular transformations were confirmed by GC–MS and FTIR, and physical properties were assessed using ASTM/ISO methods. Performance was further evaluated through a 12,000 km in-service motorcycle engine test and XRF wear analysis. Transesterification decreased kinematic viscosity at 40 °C from 36.6 to 16.7 cSt, and subsequent epoxidation and additive incorporation increased the viscosity to 47.2 cSt (40 °C) and 15.2 cSt (100 °C), meeting ISO VG-46 requirements. The resultant composition (JOA) showed density (888 kg m⁻³), viscosity index (227), pour point (−20 °C), flash point (230 °C), free fatty acid content (0.1%), and acid value < 0.5 mg KOH g⁻¹. The predominant components of JOA were determined by GC–MS, and ester and epoxide functionalities were confirmed by FTIR. During operation, the viscosity index decreased to 192.9, while maintaining acceptable viscosity retention and thermal stability. XRF analysis indicated controlled wear, with metal concentrations remaining within reported OEM guideline ranges. These results demonstrate the feasibility of using Jatropha curcas oil as a sustainable base stock for automotive lubricants.Bio-lubricantJatropha curcasTransesterificationEpoxidationISO VG-46Physicochemical propertiesJPM Publishers2026-02-19International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/0510200926-3/https://ijeresm.com/wp-content/uploads/2026/02/0510200926.pdfhttps://doi.org/10.58482/ijeresm.v5i1.210.58482/ijeresm.v5i1.2Vol. 5, Issue 1, pp. 13-31

oai:ijeresm.com:05103009172026-03-01

Substrate-Dependent Performance Evaluation of a DGS-Based Multiband Hexagonal Microstrip Patch Antenna for 5G FR2 ApplicationsYuvaraj KSanam Narayana ReddyThis paper presents a substrate-dependent performance evaluation of a defected ground structure (DGS)-integrated multiband hexagonal microstrip patch antenna operating in the 22–28 GHz millimetre-wave band for 5G FR2 applications. To examine the influence of dielectric properties on electromagnetic behaviour, the same antenna geometry is implemented on three commonly used substrates—Duroid (relative permittivity εr ≈ 2.2, loss tangent tanδ ≈ 0.0009), Rogers (εr ≈ 2.94, tanδ ≈ 0.0012), and FR4 (εr ≈ 4.4, tanδ ≈ 0.02). A controlled substrate-based comparison is conducted with respect to the reflection coefficient, impedance bandwidth, gain, and radiation efficiency. The results indicate that substrate characteristics significantly affect resonance depth, impedance stability, and radiation performance at millimetre-wave frequencies. The Duroid-based configuration achieves S₁₁ below −32 dB, peak gain of 8–8.5 dBi, and high radiation efficiency due to reduced dielectric loss. The Rogers substrate exhibits stable multiband behaviour with moderate gain, whereas the FR4-based design shows reduced resonance depth and lower gain due to increased dielectric dissipation. By maintaining identical geometry across all substrates, the study isolates the direct impact of dielectric constant and loss tangent on modal excitation and efficiency degradation in the 22–28 GHz band. The presented analysis supports informed substrate selection for compact multiband mmWave antenna designs in next-generation wireless systems.Millimetre-Wave AntennaHexagonal Microstrip AntennaDefected Ground Structure (DGS)Multiband OperationSubstrate-Dependent Analysis5G NR FR2JPM Publishers2026-03-01International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/0510300917-3/https://ijeresm.com/wp-content/uploads/2026/03/0510300917.pdfhttps://doi.org/10.58482/ijeresm.v5i1.310.58482/ijeresm.v5i1.3Vol. 5, Issue 1, pp. 32-41

oai:ijeresm.com:05104009392026-03-16

Atrous Convolutional Self-Attention-Based Capsule Network for Lung Disease ClassificationPraveena KakarlaVimala CLung diseases remain a major global health concern, affecting the supply of oxygen to other parts of the body. There are several types of lung diseases, including asthma, COPD, and pneumonia. Numerous methods have been developed to identify these lung diseases; however, they still have several shortcomings, including long processing times, complex structures, and poor classification accuracy. To address these issues, a lung disease classification system is developed using the proposed method. First, pre-processing techniques are applied to improve image quality by reducing noise and enhancing contrast using Modified Histogram Equalization and Cross-guided Bilateral Filtering. The images are collected from the NIH ChestX-ray dataset. Next, Extended Lyrebird Optimization is utilized to select the optimal features, and the Squeeze-Excited DenseNet201 (SE-DenseNet201) model is employed for feature extraction. Finally, an Atrous Convolutional Self-Attention-based Capsule Network model is utilized for classification, and the Kookaburra Optimization Algorithm is employed for hyperparameter tuning. The proposed approach is evaluated using the NIH ChestX-ray dataset and achieves an accuracy of 92.70%, with 92.13% precision and 92.99% recall.Lung disease classificationChest X-ray imagingDenseNet201Capsule networkFeature selectionMetaheuristic optimizationJPM Publishers2026-03-16International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/0510400939-3/https://ijeresm.com/wp-content/uploads/2026/03/0510400939.pdfhttps://doi.org/10.58482/ijeresm.v5i1.410.58482/ijeresm.v5i1.4Vol. 5, Issue 1, pp. 42-68

oai:ijeresm.com:05105009632026-03-18

Financial Literacy, Entrepreneurial Orientation, and Students’ Career Readiness in Dennis Osadebay UniversityEfemena Otejiri OlioguStephen Emeka ArinzeOghenekparobo Ernest AgbogunUdoka Bernard AlajekwuVincent N. EzeabasiliAs the global labour market becomes highly saturated, most Nigerian graduates are finding it difficult to start a sustainable career path. Hence, it is highly imperative for Nigerian graduates to be both financially literate and entrepreneurially oriented should they desire to forge a career path. This study investigated the effects of entrepreneurial orientation (EO) and financial literacy (FL) on career readiness among Accounting, Banking, and Finance students in Dennis Osadebay University (DOU), Asaba, Nigeria. A quantitative design was utilized. Questionnaires were distributed to 193 Accounting, Banking, and Finance students in the Faculty of Management Sciences. 25 students were surveyed to test the questionnaire’s reliability using Cronbach’s alpha. Regression analysis was the primary estimation technique used to test the relationships among financial literacy, entrepreneurial orientation, and career readiness. Cognitive factors (financial literacy) and behavioural factors (entrepreneurial orientations such as innovativeness, proactiveness, and risk-taking) are positively associated with students’ career readiness. These findings underscore that both financial literacy and entrepreneurial orientation are critical factors shaping students’ career readiness.Financial LiteracyEntrepreneurial OrientationCareer ReadinessUniversity StudentsDennis Osadebay UniversityJPM Publishers2026-03-18International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/0510500963-3/https://ijeresm.com/wp-content/uploads/2026/03/0510500963.pdfhttps://doi.org/10.58482/ijeresm.v5i1.510.58482/ijeresm.v5i1.5Vol. 5, Issue 1, pp. 69-76

oai:ijeresm.com:05106009592026-03-21

Stress-Enhanced MEMS Trapezoidal Microcantilever Sensor for Enhanced Detection of Respiratory Syncytial VirusM. Lakshmi PrasannaAnitha V REarly detection of disease-causing antigens plays a crucial role in preventive healthcare. Biosensors are devices that monitor and diagnose human health by converting biological interactions into measurable signals. In recent years, microcantilever-based biosensors have gained significant attention due to their high sensitivity, miniaturization capability, and rapid response characteristics. This paper focuses on detecting the RSV-G protein of Respiratory Syncytial Virus using a paddle-type trapezoidal microcantilever with different stress concentration regions. The cantilever is designed using SU-8 polymer material with a density of 1123 kg/m³, Young’s modulus of 5 GPa, and Poisson’s ratio of 0.22. The sensing mechanism is modeled in static mode, where antigen–antibody binding is represented as an equivalent surface-stress-induced loading condition in the finite element simulation. Comparative analysis of different SCR geometries shows that the rectangular SCR configuration yields a maximum displacement of 6.8 × 10⁻¹⁸ µm, demonstrating a nearly fourfold enhancement over the conventional design without an SCR. This improvement is attributed to localized stress concentration and reduction in effective structural stiffness under identical loading conditions. The results indicate that geometry-driven stress concentration significantly enhances the mechanical sensitivity of the microcantilever sensor and provides an effective approach to structural optimization for viral biosensing applications.Microcantilever biosensorStress concentration regionSurface stress modelingRSV-G protein detectionMEMS-based sensorJPM Publishers2026-03-21International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/0510600959-3/https://ijeresm.com/wp-content/uploads/2026/03/0510600959.pdfhttps://doi.org/10.58482/ijeresm.v5i1.610.58482/ijeresm.v5i1.6Vol. 5, Issue 1, pp. 77-85

oai:ijeresm.com:05107010162026-03-28

Long-Term Electricity Demand Forecasting for Thailand’s Small Business Sector: An LSTM-Based ApproachPuttiphong JaroonsiriphanKayun ChantarasathapornKhongdet PhasinamAccurate electricity demand forecasting is essential for Thailand’s energy system planning, particularly for the small business sector, whose consumption exhibits high variability (coefficient of variation: 26.34%). This study develops a Long Short-Term Memory (LSTM) model to forecast monthly electricity consumption of Thailand’s small business sector over a 12-month horizon from September 2025 to August 2026. The analysis is based on 284 months of historical consumption data (January 2002–August 2025) obtained from official national statistics. The forecasting framework employs Min–Max normalization and a supervised learning formulation with a 12-month lookback window. The dataset is chronologically divided into training (80%) and testing (20%) subsets, and model performance is evaluated using Root Mean Squared Error (RMSE) and Mean Absolute Percentage Error (MAPE). The optimized LSTM model achieves strong forecasting accuracy, with a training RMSE of 93.93 and MAPE of 5.45%, and a testing RMSE of 143.68 and MAPE of 6.25%. These results meet the criterion for highly accurate forecasting (MAPE < 10%), demonstrating the model’s ability to capture long-term trends and seasonal patterns while generalizing well to unseen data. The findings highlight the suitability of LSTM-based models for long-term electricity demand forecasting in high-volatility small-business sectors and underscore their practical relevance for energy planning and policy development in Thailand.Electricity ConsumptionDemand ForecastingLong Short-Term MemoryMean Absolute Percentage ErrorSmall Business SectorJPM Publishers2026-03-28International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/0510701016-3/https://ijeresm.com/wp-content/uploads/2026/03/0510701016.pdfhttps://doi.org/10.58482/ijeresm.v5i1.710.58482/ijeresm.v5i1.7Vol. 5, Issue 1, pp. 86-92

oai:ijeresm.com:05108009772026-03-30

Backward Token-Based Routing Framework for Hierarchical Tree Construction and Collision-Controlled Transmission in Wireless SenS NavaneethanA ArunWireless Sensor Networks (WSNs) require efficient routing mechanisms to ensure reliable data delivery while minimizing energy consumption and communication delay in resource-constrained environments. Conventional methods, including contention-based transmission schemes, often suffer from packet collisions, retransmissions, and increased latency as network density mounts. To combat these challenges, this paper proposes a Backward Token-Based Routing Framework (BTBRF) that allows a sink-initiated reverse-direction token propagation for hierarchical routing tree construction and controlled transmission scheduling in multi-hop WSN structures. In the proposed approach, backward tokens are generated at the sink node and establish parent–child relationships using hop count, path cost, and residual energy metrics. This ensures loop-free topology formation and regulated channel access. Hence, only authorized nodes participate in communication at a given time. The performance of the proposed framework was evaluated using the QualNet network simulator by varying node densities from 20 to 100 nodes. Simulation results demonstrate that the proposed method improves packet delivery ratio and throughput while reducing end-to-end delay and overall energy consumption compared with conventional single-token communication methods.Wireless Sensor NetworksToken-Based RoutingBackward Token PropagationEnergy-Efficient RoutingHierarchical Routing TreeCollision-Controlled TransmissionQualNet SimulationPacket Delivery RatioJPM Publishers2026-03-30International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/0510800977-3/https://ijeresm.com/wp-content/uploads/2026/03/0510800977.pdfhttps://doi.org/10.58482/ijeresm.v5i1.810.58482/ijeresm.v5i1.8Vol. 5, Issue 1, pp. 93-106

oai:ijeresm.com:05201009762026-04-26

Enhanced Prediction of Chronic Kidney Disease Based on an Integrated Framework of High-Dimensional Medical Image Data and DeepM. NareshM. V. Nageswara RaoD. Venkat ReddyKoiloth SRS JyothsnaNamburi Dhana LakshmiNanduri SrinivasChronic kidney disease (CKD) is characterized by progressive kidney damage and is a rapidly growing global health concern. CKD significantly increases morbidity and mortality risk. One way to lower the CKD mortality rate is to diagnose and treat patients early. Early detection of CKD remains challenging for medical practitioners. By integrating state-of-the-art deep-learning (DL) methods with high-dimensional medical image data, the proposed model enhances CKD prediction while addressing challenges related to data quality and scalability. Pre-processing, feature extraction, feature selection, and classification are the four stages of the proposed framework. The three models that extract the essential features are Inception-V3, ResNet-50, and VGG-16. In order to choose the best features and minimize problems caused by feature dimensionality, an upgraded version of the particle swarm optimization method (UPSO) is introduced during the feature selection step. Then, a deep capsule model combined with a depth-wise convolutional network is used for classification. The last step in improving CKD prediction is hyperparameter optimization, namely the Crayfish Optimization Algorithm (COA). Using performance metrics such as accuracy, precision, recall, F1-score, and specificity, the proposed technique is validated using benchmark CT kidney and retinal image datasets. The proposed model achieves an accuracy of 99.72% by integrating hybrid MMG–CLAHE preprocessing, multi-backbone transfer learning feature extraction (Inception-V3, ResNet-50, VGG-16), UPSO-based feature selection, and a depth-wise convolutional capsule classifier optimized using COA for CKD prediction.Chronic kidney diseaseDeep learningMedical image analysisTransfer learningCapsule networkCrayfish optimization algorithmJPM Publishers2026-04-26International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/0520100976-3/https://ijeresm.com/wp-content/uploads/2026/04/0520100976.pdfhttps://doi.org/10.58482/ijeresm.v5i2.110.58482/ijeresm.v5i2.1Vol. 5, Issue 2, pp. 01-22

oai:ijeresm.com:05202010192026-04-28

Feature Fusion Strategy Based on Concatenation of Histogram of Oriented Gradients and Pretrained CNN Features for Visual Object TrackingVillari Sreenatha SarmaP.M. Ashok KumarVadamala Purandhar ReddyThis paper presents a hybrid feature fusion approach for visual object tracking that combines hand-crafted gradient-based descriptors with semantic representations extracted from a pretrained convolutional neural network. The proposed tracker integrates Histogram of Oriented Gradients (HOG) features with ResNet-50-based deep features within a correlation filter framework to improve robustness against appearance variations, occlusion, and illumination changes. A concatenation-based fusion strategy with adaptive confidence-driven weighting is incorporated to dynamically balance the contribution of handcrafted and deep features during tracking. The architecture employs parallel feature extraction branches and multi-scale feature integration to enhance localization performance while maintaining computational efficiency. Experimental evaluation on standard benchmark datasets, including OTB-2015 and related tracking sequences, demonstrates that the proposed fusion strategy provides improved performance compared with individual feature-based tracking approaches and achieves competitive results relative to baseline correlation-filter trackers under challenging conditions. The study also outlines potential directions for further enhancement through online adaptation and attention-based feature fusion strategies.Visual Object TrackingFeature FusionHistogram of Oriented GradientsCorrelation Filter TrackingAdaptive Feature WeightingJPM Publishers2026-04-28International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/0520201019-3/https://ijeresm.com/wp-content/uploads/2026/04/0520201019.pdfhttps://doi.org/10.58482/ijeresm.v5i2.210.58482/ijeresm.v5i2.2Vol. 5, Issue 2, pp. 23-35

oai:ijeresm.com:05203010292026-05-21

A Systematic Review of Deep Learning Approaches for Information Disorder Detection on Social Media: The Context of Misinformation, Disinformation, and Mal-informationAndualem WoldegiorgisMohammed AbebeDurga Prasad SharmaWorku JimmaSocial media platforms have become powerful tools for communication, information exchange, networking, and community building. However, their widespread use has facilitated the proliferation of misinformation, disinformation, and mal-information, posing significant challenges to societal harmony and individual well-being. Attacks such as social pressure, bullying, extortion, manipulation, abuse, prejudice, and violence can deepen divisions and conflicts, demonize minorities, and undermine the integrity of public opinion and democratic elections. This study presents a systematic review with quantitative comparative analysis of machine learning and deep learning approaches for information disorder detection, with a unique emphasis on low-resource multilingual contexts, particularly Amharic and Afaan Oromo, while addressing critical challenges related to multimodality, data scarcity, and contextual linguistic complexity. Using the PRISMA framework, 963 studies were screened, resulting in the selection of 99 high-quality articles for in-depth analysis. This study provides a dataset-level synthesis, comparing benchmark and low-resource datasets across multiple dimensions such as data modalities (text, image, memes, audio) and learning models. The findings indicate an increasing adoption of transformer-based and deep learning models, which demonstrated strong performance, particularly on large benchmark and multimodal datasets. Importantly, the review identifies critical research gaps, including limited multimodal fusion techniques, insufficient multi-class classification approaches, and a lack of localized context-aware models for low-resource languages. Unlike global surveys, this study provides a localized Ethiopian-context analysis that addresses linguistic diversity, resource constraints, and real-world deployment challenges. The study contributes an integrated perspective encompassing multilingual, multimodal, and multiclass dimensions and outlines future directions for developing scalable, context-aware, and inclusive detection models.Social mediaDeep learningMachine learningDisinformationMisinformationMal-informationInformation Disorder DetectionJPM Publishers2026-05-21International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/0520301029-3/https://ijeresm.com/wp-content/uploads/2026/05/0520301029.pdfhttps://doi.org/10.58482/ijeresm.v5i2.310.58482/ijeresm.v5i2.3Vol. 5, Issue 2, pp. 36-66

oai:ijeresm.com:05204010612026-05-23

Reliability Assessment of a PV-Integrated 132 kV Power Network Using ETAPMohammed Jawad AbedSana BenrejebNadheer A ShalashAnis MhallaThis study presents a reliability assessment framework integrating ETAP simulations and probabilistic modeling to evaluate the reliability and operational impacts of photovoltaic (PV) integration on the Diyala 132 kV power network. The primary goal is to quantify the trade-off between improved reliability indices and operational shifts, such as altered power flows, loss reduction, and increased short-circuit fault currents. In this context, a reproducible methodology for assessing photovoltaic system reliability is presented, emphasizing probabilistic variations associated with photovoltaic power supplied through power electronic converter components. The study utilizes the Electrical Transient Analyzer Program (ETAP) for comprehensive network simulation, including load flow and short-circuit analysis. To model the stochastic nature of PV systems, a Capacity Outage Probability Table (COPT) based on the failure rates of power electronic components (e.g., DC converters, inverters) is linked to standard reliability indices. The integration of PV significantly alters network dynamics, notably reducing total apparent active power losses from 16.203 MW to 10.174 MW. However, PV penetration also increases short-circuit currents across the grid, necessitating adjustments to relay coordination to ensure protection. Furthermore, the results indicate that relay coordination adjustments may be required to mitigate increased fault currents while maintaining system efficiency. This research links component-level reliability analysis performed in MATLAB with system-level assessment conducted in ETAP, providing a reproducible methodology for evaluating PV-integrated grids. To enhance power system assessment, the proposed reliability framework provides information that may support relay coordination adjustment based on component failure characteristics.Reliability assessmentPhotovoltaic systemsPower system reliabilityETAPShort-circuit analysisCOPTJPM Publishers2026-05-23International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/0520401061-3/https://ijeresm.com/wp-content/uploads/2026/05/0520401061.pdfhttps://doi.org/10.58482/ijeresm.v5i2.410.58482/ijeresm.v5i2.4Vol. 5, Issue 2, pp. 67-81

oai:ijeresm.com:05205009462026-05-27

Design and RTL-Level FPGA Realization of a MIMO-GFDM Digital Baseband Modem for Underwater Optical Wireless CommunicationV TejovathiS SwarnalathaUnderwater Wireless Communication (UWC) has emerged as an important enabling technology for applications including ocean observation, offshore monitoring, underwater sensor networks, assisted navigation, and Internet of Underwater Things (IoUTs). Among the available communication techniques, Underwater Optical Wireless Communication (UOWC) offers high data rates, low transmission latency, and improved bandwidth utilization for short- to medium-range communication scenarios. However, underwater optical channels remain affected by attenuation, scattering, and signal degradation, requiring bandwidth efficient transmission techniques. This paper presents the design and RTL-level FPGA realization of a Multiple-Input Multiple-Output Generalized Frequency Division Multiplexing (MIMO-GFDM) digital baseband modem for underwater optical wireless communication. The proposed architecture combines GFDM-based multicarrier transmission with MIMO processing to support flexible time–frequency allocation and reduced interference effects in underwater communication environments. The complete modem architecture is developed and evaluated using MATLAB/Simulink under simulated underwater channel conditions. To demonstrate implementation feasibility, the designed communication blocks are translated into synthesizable VHDL through an HDL-based workflow and analysed through RTL-level realization for FPGA-oriented implementation. Simulation outputs including transmitted and received signal behaviour, error characteristics, spectral response, and implementation resource observations are presented for performance assessment. The obtained results indicate that the proposed architecture provides an effective framework for investigating spectrally efficient underwater optical communication systems and demonstrates the feasibility of RTL-level realization for future hardware deployment.Underwater Optical Wireless CommunicationMIMOGeneralized Frequency Division MultiplexingDigital Baseband ModemFPGARTL DesignMATLAB/SimulinkHDLJPM Publishers2026-05-27International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/0520500946-3/https://ijeresm.com/wp-content/uploads/2026/05/0520500946.pdfhttps://doi.org/10.58482/ijeresm.v5i2.510.58482/ijeresm.v5i2.5Vol. 5, Issue 2, pp. 82-95

oai:ijeresm.com:05206011252026-06-16

Feedback-Guided Parallel Transformer Framework for Remote Sensing Image Semantic SegmentationK. S. Raghavendra ReddyB. SudhakarK. Venkata RamanaiahAccurate semantic segmentation of remote sensing images is essential for applications such as urban planning, environmental monitoring, and land-use analysis. This study proposes a parallel-branch feedback-guided transformer framework for semantic segmentation of remote sensing images in complex scenes. Initially, images obtained from publicly available datasets are pre-processed using bilateral filtering to reduce noise while preserving important edge details. The pre-processed images are forwarded to a hierarchical transformer encoder, where feature representations are progressively extracted. Parallel processing is subsequently performed within the Atrous Spatial Pyramid Pooling-based Densely connected Residual (ASPP-DR) and Dual Attention Mechanism (DAM) modules to capture multi-scale contextual information together with spatial and channel-wise feature dependencies. A dual attention mechanism is incorporated to capture both spatial and channel-wise dependencies, improving contextual feature representation. The extracted multi-level feature maps are passed to a lightweight ASPP-DR module, which enhances contextual feature representation across multiple receptive fields. These enhanced features are subsequently forwarded to a multi-stage decoder that progressively reconstructs the spatial resolution. A feedback pyramid module is integrated within the decoding process to iteratively refine feature representations using previously generated outputs. In parallel, a multi-scale feature aggregation strategy combines features from different levels to produce a more discriminative representation. Finally, a cascaded upsampling decoder generates a high-resolution semantic segmentation map with accurate pixel-level classification. The proposed framework was evaluated on the LoveDA and WHU Building datasets. Experimental results achieved mIoU values of 95.4% and 96.1%, Dice scores of 97.7% and 98.0%, and precision values of 97.8% and 98.1% on the LoveDA and WHU datasets, respectively. The results indicate that the proposed framework effectively handles multi-scale variations while maintaining high segmentation accuracy.Remote sensing image segmentationVision transformerDual attention mechanismMulti-scale feature learningFeedback refinementSemantic segmentationJPM Publishers2026-06-16International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/0520601125-3/https://ijeresm.com/wp-content/uploads/2026/06/0520601125.pdfhttps://doi.org/10.58482/ijeresm.v5i2.610.58482/ijeresm.v5i2.6Vol. 5, Issue 2, pp. 96-118

oai:ijeresm.com:05207012042026-06-21

Deep Learning Models for Protein Structure Prediction: A Comprehensive SurveyC.S. SrushtiP.M. PrathibhavaniK.R. VenugopalA major challenge in computational biology is determining the 3D structure of proteins from their 1D amino acid sequence. Accurate prediction of protein structures improves the understanding of protein function and facilitates applications in drug discovery, protein engineering, and structural biology. Modeling proteins using template-based approaches is difficult when homologous structures are unavailable in the Protein Data Bank (PDB). Recent advances in deep learning (DL) have significantly improved the accuracy of protein structure prediction (PSP). The current approaches employ convolutional neural networks (CNNs), recurrent neural networks (RNNs), graph neural networks (GNNs), and Transformer architectures to learn complex sequence patterns, evolutionary relationships, and long-range residue interactions that govern protein folding. By predicting long-range residue contacts, inter-residue distances, and geometric constraints, these approaches enable the generation of highly accurate three-dimensional protein structures. DL has transformed PSP, with models such as AlphaFold2, AlphaFold3, Boltz-1, and other recent architectures achieving near-experimental accuracy on many CASP targets. The Critical Assessment of Protein Structure Prediction (CASP) is the standard biennial community-wide benchmark for evaluating PSP methods. One of the biggest challenges remaining in this area is modeling regions of proteins that are intrinsically disordered and capturing the full range of protein dynamics and the relationships of different protein domains that exist in different proteins. This survey provides a comprehensive review of recent DL-based PSP methods, analyzes their architectural evolution, compares their strengths and limitations, and discusses emerging research challenges and future directions.Template-based modellingTemplate-free modellingProtein language modelsAlphaFoldProtein structure predictionJPM Publishers2026-06-21International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/0520701204-3/https://ijeresm.com/wp-content/uploads/2026/06/0520701204.pdfhttps://doi.org/10.58482/ijeresm.v5i2.710.58482/ijeresm.v5i2.7Vol. 5, Issue 2, pp. 119-147

oai:ijeresm.com:05208011382026-06-26

Intrusion Mitigation-Based Adaptive Resource Allocation Using LSTM-RBF-FFO in Cloud EnvironmentsMudavath Yuvaraj NaikC. SivakumarCloud computing systems are becoming increasingly dynamic, requiring effective security mechanisms and efficient resource allocation strategies. As cyber threats become more sophisticated, cloud systems must not only detect and mitigate intrusions but also adaptively allocate resources to maintain system performance. Existing optimization-based approaches, such as the Radial Basis Function Firefly (RBF-FF) algorithm, have shown promise in balancing resource utilization and security in cloud environments. However, static RBF models do not adapt effectively to evolving intrusion patterns and workload variations in real time, resulting in delayed threat response and suboptimal resource utilization. Existing approaches generally address intrusion detection and resource allocation independently, limiting their ability to respond effectively to dynamic cloud environments. This paper proposes a Hybrid LSTM-RBF Firefly Optimization (HLR-FFO) framework that integrates Long Short-Term Memory (LSTM) networks, Radial Basis Function (RBF) neural networks, and an adaptive Firefly Optimization algorithm. The LSTM component learns temporal patterns from system logs and network traffic to improve intrusion prediction, while the RBF layer performs rapid and accurate classification. The Firefly Optimization algorithm employs an adaptive brightness decay factor to dynamically allocate cloud resources based on real-time user demand, VM capacity, and detected risk levels. Simulation results obtained over 1000 optimization iterations indicate that HLR-FFO achieves a detection accuracy of 99.1%, a false positive rate of 0.09%, and a false negative rate of 0.17%, demonstrating improved performance compared with GRU-PSO, CNN-LSTM-GA, and RBF-FF under the considered simulation settings. The proposed framework achieves an internal processing latency of 18.7 ms while reducing end-to-end response latency to 103 ms, demonstrating its ability to provide faster response while maintaining effective security and resource utilization.Cloud securityLSTM-RBF hybrid modelFirefly optimizationIntrusion detectionAdaptive resource allocationJPM Publishers2026-06-26International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/0520801138-3/https://ijeresm.com/wp-content/uploads/2026/06/0520801138.pdfhttps://doi.org/10.58482/ijeresm.v5i2.810.58482/ijeresm.v5i2.8Vol. 5, Issue 2, pp. 148-163

oai:ijeresm.com:05301011022026-07-19

Reliability Analysis of a Three-Unit Gas Lift System: A Comparative Study of Markov and Random Forest ModelsS Z TajS M RizwanMohamed Al IsmailiA gas lift is extensively used in the oil & gas industry to draw oil/gas from old wells. It comprises a compressor driven by an engine. This paper presents reliability analysis of a system consisting of three gas lifts operating in parallel. Reliability parameters such as availability of the system, busy period of the maintenance team, expected number of maintenance activities, and system profitability are estimated using real industrial maintenance data collected from the three-unit gas lift system. The dataset covers an observation period of four years during which 582 events of failure, inspections, and repairs were documented. The failures are classified into compressor and engine failures for each gas lift, enabling component-level parameter estimation. The data are used to develop a Markov model which is analyzed using regenerative processes. A detailed sensitivity analysis is also carried out to measure the effect of different parameters on the profitability of the system. Finally, a comparative analysis between the results of Markov model and Random Forest model is presented.Gas liftMarkov processesReliabilitySensitivityRandom ForestRegenerative processesJPM Publishers2026-07-19International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/0530101102-3/https://ijeresm.com/wp-content/uploads/2026/07/0530101102.pdfhttps://doi.org/10.58482/ijeresm.v5i3.110.58482/ijeresm.v5i3.1Vol. 5, Issue 3, pp. 1-13

oai:ijeresm.com:05302011692026-07-21

Improved Alzheimer's Disease Detection Using an Adaptive Spatial Attention-Based Twin Neural NetworkShaik Mahaboob BashaS. SwarnalathaB. Shoban BabuAlzheimer’s disease (AD) is one of the most prevalent forms of dementia, typically initiating with mild memory loss and progressively leading to severe cognitive decline. Early diagnosis is critical for effective intervention and improving patient outcomes. However, existing diagnostic approaches face challenges such as long prediction times, limited feature extraction capability, and the requirement for extensive training data, particularly in Machine Learning (ML)-based systems. To address these issues, this study proposes a novel computer-aided diagnostic framework called Adaptive Spatial Attention-based Twin Neural Network (ASTNet) for early AD detection using MRI data. Unlike traditional methods, ASTNet integrates several components: a biased fuzzy clustering-based segmentation technique that enhances tissue segmentation by emphasizing brain-relevant regions while suppressing skull and irrelevant tissues; Possibilistic C-Means (PCM) to improve segmentation robustness; a Convolutional Bidirectional LSTM (CBi-LSTM) network for context-aware feature extraction that captures temporal dependencies and reduces high-dimensional noise; and an adaptive spatial attention-based Twin Neural Network (TNN) for disease classification that improves spatial feature discrimination across cognitively normal (CN), mild cognitive impairment (MCI), and AD categories. The proposed approach was evaluated on the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset and achieved a classification accuracy of 0.9909, outperforming the compared Deep Learning (DL) models. Furthermore, the model demonstrates computational efficiency under the evaluated experimental setting and shows potential for computer-aided clinical decision support.Alzheimer’s disease diagnosisSkull strippingBiased fuzzy clusteringBidirectional Long Short-Term MemoryTwin Neural NetworkJPM Publishers2026-07-21International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/0530201169-3/https://ijeresm.com/wp-content/uploads/2026/07/0530201169.pdfhttps://doi.org/10.58482/ijeresm.v5i3.210.58482/ijeresm.v5i3.2Vol. 5, Issue 3, pp. 14-43

oai:ijeresm.com:05303010132026-07-22

Development of an Interactive Web-Based Hybrid E-Commerce Recommendation System Using Neural Collaborative Filtering and Content-Based FilteringMuhammad FaridTasyaul HusnaMuhammad Zia UlhaqTeuku Muhammad Faiz NuzullahTeuku Rizky NoviandyNovi Reandy SasmitaIn an increasingly digital era, technological advancements have transformed the way people shop and interact with e-commerce platforms. E-commerce offers a wide range of products and services online, but consumers often feel overwhelmed by the sheer number of choices. The importance of efficient and relevant services for consumers is a significant consideration in developing e-commerce systems. One effective solution is implementing a recommendation system that helps consumers find products that match their needs and preferences. This study develops an e-commerce recommendation system using neural collaborative filtering and content-based filtering methods, integrated with an interactive dashboard to improve user experience. With a learning rate of 0.01 and a batch size of 32, the developed neural collaborative filtering model shows a low testing error of 0.0705 and precision, recall, and F-measure of 0.9583, 0.8251, and 0.8867, respectively. The content-based filtering method uses the Cosine Similarity technique, achieving an Average Precision of 0.804 and an accuracy of 80%. The interactive dashboard was successfully developed to support system evaluation and user engagement. This study provides benefits for consumers who can find products according to their needs more quickly and for e-commerce business owners who can reach consumers more efficiently.Recommendation systemContent-based filteringHybrid recommendation systemNeural collaborative filteringE-commerceJPM Publishers2026-07-22International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/0530301013-3/https://ijeresm.com/wp-content/uploads/2026/07/0530301013.pdfhttps://doi.org/10.58482/ijeresm.v5i3.310.58482/ijeresm.v5i3.3Vol. 5, Issue 3, pp. 44-54

oai:ijeresm.com:05304012192026-07-25

Village-Level Assessment of Potential Surface Water Storage Using an Integrated Water Balance Approach in the Ippala Vagu Watershed, IndiaJ. RangaiahV. MallikarjunaP. Udaya BhaskarThe management of watersheds requires the planning of surface water resources. For hydrological analysis, runoff estimation is essential. This study aimed to estimate the village-level potential surface water storage by integrating the water balance components, including surface runoff, groundwater recharge, and effective rainfall. Surface runoff was estimated using the Soil Conservation Service Curve Number (SCS-CN), groundwater recharge was estimated by the Rainfall Infiltration Factor (RIF), and effective rainfall was estimated by Food and Agriculture Organization/ Agricultural Water Management Group (FAO/AGLW) approaches. Using rainfall data, water balance calculations were performed for the 18 villages within the Ippala Vagu Watershed to evaluate potential surface water storage. In total, 18 villages recorded an annual rainfall volume of 430.50 million cubic meters (MCM), of which 138.24 MCM (32.11%) was estimated as effective rainfall. Surface runoff constituted 71.57 MCM (16.62%), while groundwater recharge was estimated at 68.88 MCM (16.00%). The potential surface water storage amounted to 151.82 MCM, representing 35.27% of the annual precipitation volume. The current storage capacity was merely 73.67 MCM, constituting 48.52% of the potential surface water storage. These findings indicate considerable potential for improving the utilization of available surface water resources within the watershed. Accordingly, increasing water harvesting and storage facilities, especially in villages with high potential surface water storage, is recommended.Surface RunoffEffective RainfallPotential Surface Water StorageGeographic Information SystemSCS-CN MethodRainfall Infiltration FactorJPM Publishers2026-07-25International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/0530401219-3/https://ijeresm.com/wp-content/uploads/2026/07/0530401219.pdfhttps://doi.org/10.58482/ijeresm.v5i3.410.58482/ijeresm.v5i3.4Vol. 5, Issue 3, pp. 55-66

oai:ijeresm.com:05305012492026-08-07

Communication-Efficient Federated Learning for IIoT Bearing Fault Diagnosis Using Multi-Head Deep Q-Network-Based Intelligent Client SelectionBhupathirao LakinanaKalyana Chakravarthy ChilukuriFederated learning (FL), which allows distributed training across several industrial machines without exchanging raw vibration data, has emerged as a promising paradigm for privacy-preserving bearing fault diagnosis in Industrial Internet of Things (IIoT) scenarios. Nevertheless, current FL approaches for fault diagnosis face two significant limitations. First, uniform client participation in each communication round results in needless and prohibitive communication overhead. Second, static or random client selection strategies are indifferent to the informativeness of individual client updates under highly non-IID data distributions. This paper proposes a novel Multi-Head Deep Q-Network (Multi-Head DQN)-based client selection framework for communication-efficient federated learning applied to bearing fault diagnosis to overcome these limitations. In the proposed framework, the Multi-Head DQN agent jointly determines the optimal number of clients, k, to select in each round from a predefined range, and the identities of the most informative clients. To accurately replicate heterogeneous IIoT deployments in the real world, a stringent non-IID partitioning approach is implemented across 12 federated clients, each of which is allocated precisely two of four failure classes (Normal, Inner Race, Outer Race, and Ball). The Flower federated learning framework is used to compare six FL configurations: FedAvg, FedProx, FedAvg+FedRandom, FedProx+FedRandom, FedAvg+FedDQN, and FedProx+FedDQN. All experiments were conducted on the CWRU bearing fault dataset. Experimental results show that the proposed FedProx+FedDQN approach reduces cumulative communication costs by 19.15% compared with the all-client FedAvg baseline while achieving a global fault classification accuracy of 94.05%, which is comparable to the full-participation baselines (FedAvg and FedProx). The DQN-based selection prioritizes informative client updates, leading to faster convergence and lower communication overhead. These findings confirm that intelligent client selection is an effective strategy for improving communication efficiency in federated learning for industrial fault diagnosis applications.Federated learningbearing fault diagnosisIndustrial Internet of Thingsdeep Q-networkclient selectioncommunication efficiencynon-IID dataconvolutional neural networkreinforcement learningJPM Publishers2026-08-07International Journal of Emerging Research in Engineering, Science, and ManagementTextapplication/pdfenThis work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/4.0/https://ijeresm.com/0530501249-3/https://ijeresm.com/wp-content/uploads/2026/08/0530501249.pdfhttps://doi.org/10.58482/ijeresm.v5i3.510.58482/ijeresm.v5i3.5Vol. 5, Issue 3, pp. 67-80