IJSRET Volume 11 Issue 1, Jan-Feb-2025

Uncategorized

IoT Enabled Solutions for Women Safety and Health Monitring
Authors:-Sudeshna P, Vivekanandan K

Abstract-Women and children today deal with a number of problems, including sexual attacks. The victims’ life will undoubtedly be greatly impacted by such atrocities. It also has an impact on their psychological equilibrium and general wellbeing. The frequency of these acts of violence keeps rising daily. Even schoolchildren are victims of sexual abuse and abduction. In our society, a nine-month-old girl child is not protected; she was abducted, sexually assaulted, and ultimately killed. Seeing the abuses of women makes us want to take action to ensure the protection of women and children. Therefore, we intend to present a device in this project that will serve as a tool for security and guarantee the safety of women and children. GSM microcontroller.

DOI: 10.61137/ijsret.vol.10.issue5.224

A 19-Level Variable Frequency Switched DC-AC Converter fed Induction Motor Drive for Bench Grinding Applications
Authors:-MTech Scholar Umang Soni, Assistant Professor Shyam Kumar Barode, Assistant Professor Hari Mohan Soni, Assistant Professor Sachin Jain

Abstract-The development of inverters with more than two layers to reduce distortion from the fundamental sinusoidal waveform gave rise to the concept of a multilayer inverter. For bench grinder applications, the induction motor drive has to be powered by AC. Therefore, a multilayer inverter is used to boost the sine wave nature of the inverter output, and an asymmetrical H-bridge type inverter is used to decrease the bulkiness and cost of the system. The MATLAB platform is used to construct the concept, and analysis is then conducted to ascertain the end product’s value.

DOI: 10.61137/ijsret.vol.11.issue1.101

Review on PAPR Reduction and Improvement of OFDM System Performance Using Artificial Intelligence
Machine Learning Algorithm

Authors:-M.Tech Scholars Rahul Mishra, Assistant Professor Vijay Bisen

Abstract-The advancement of technology necessitates the development of more sophisticated modulation strategies for wideband digital communication systems. The requirements for high-speed data transmissions can be effectively met by utilizing orthogonal frequency division multiplexing, which is an effective technique. However, a high peak-to-average power ratio (PAPR) is one of the key limits that OFDM systems face, both in terms of their performance and their power efficiency. The evaluation of the PAPR reduction has become a topic of widespread interest in this present decade due to the relevance it holds in the industrial and scientific communities. The purpose of this study is to Review show the combination of the bat algorithm with the partial transmit sequence scheme as an effective way for reducing PAPR that also eases the burden of computing work. For the purpose of providing a comparative evaluation of the PAPR reduction performance, a number of simulations using various partial transmit sequence schemes have been carried out.

DOI: 10.61137/ijsret.vol.11.issue1.102

A Review on Nano Fluid Particles through a Rectangular Corrugated Channel
Authors:-Mayank Dwivedi, Dr. Sanjay Kumar Singh

Abstract-This review examines the thermal and hydraulic performance of nanofluids flowing through rectangular corrugated channels, focusing on their potential for enhancing heat transfer efficiency. Various nanofluids, including ZnO, CuO, Fe₂O₃, Al₂O₃, SiO₂, and TiO₂, are evaluated based on parameters such as heat transfer coefficient, pressure drop, and Nusselt number. The unique properties of nanofluids, coupled with the enhanced turbulence induced by corrugated geometries, result in significant improvements in thermal performance compared to conventional fluids. However, factors like pressure drop and flow resistance also vary widely depending on the type of nanoparticles used. This review highlights the critical role of nanoparticle selection and channel design in optimizing heat transfer while minimizing pressure losses, providing valuable insights for advanced thermal management systems.

An Algorithmic Implemetation on Big Data Approach Using Mapping Techniques
Authors:-Research Scholar Ms. Shilpa Sharma, Professor R. K. Bathla

Abstract-Research is an art of scientific examination. The advance learner’s vocabulary of current English lays down the meaning of research as “A careful exploration and enquiry especially through search for new facts in any branch of knowledge. Bradman and Morry define research as “A standardize efforts to increase new knowledge”. Research is, thus an original contribution to existing stock of knowledge making for its advancement. It is detection of truth with the help of study, observation, comparison, and experiments. The technologies that give support to the entire process of cost-effectively storing and processing data, and utilize internet technologies in a scattered way have arisen in the past few years. NoSQL and Cloud computing are the renowned ones that improve the potential offered by Big Data Technologies. Map Reduce is a software manufacture introduced by Google to act upon parallel processing on large datasets supercilious that large dataset storage is distributed over a large number of machines. Each machine computes data stored locally, which in turn contributes to distribute and parallel processing. This paper focuses on the Big data and Cloud services using impact of Map Reduce Algorithm and very advantageous for the researchers and corporate sectors who are using Map Reducing System technology.

DOI: 10.61137/ijsret.vol.11.issue1.103

The Impact of Digital Transformation on Warehouse Efficiency
Authors:-Tariq Ibrahim Al Barwani, Dr.Masengu Reason

Abstract-Digital transformation has emerged as a pivotal force reshaping the logistics and supply chain sectors, particularly in warehouse operations. This study explores the multifaceted impact of digital technologies on warehouse efficiency, highlighting key innovations such as automation, data analytics, and the Internet of Things (IoT). By integrating these technologies, warehouses can enhance operational performance, reduce costs, and improve inventory management. The research identifies how automation tools, such as robotics and automated guided vehicles (AGVs), streamline processes, reduce labour costs, and minimize human error. Furthermore, advanced data analytics enable real-time decision-making and predictive analytics, allowing for optimized inventory levels and enhanced demand forecasting. The IoT facilitates seamless communication between devices, improving visibility and traceability throughout the supply chain. Through case studies and empirical data, this paper demonstrates that warehouses adopting digital transformation strategies experience significant improvements in productivity, accuracy, and customer satisfaction. However, it also addresses the challenges faced during implementation, including workforce adaptation and cybersecurity concerns. Ultimately, this study emphasizes that embracing digital transformation is not merely a trend but necessary for warehouses aiming to thrive in an increasingly competitive market. The findings underscore the importance of strategic planning and investment in technology to achieve sustainable efficiency gains.

The Impact of Digital Transformation on Warehouse Efficiency
Authors:-Tariq Ibrahim Al Barwani, Dr.Masengu Reason

Abstract-Digital transformation has emerged as a pivotal force reshaping the logistics and supply chain sectors, particularly in warehouse operations. This study explores the multifaceted impact of digital technologies on warehouse efficiency, highlighting key innovations such as automation, data analytics, and the Internet of Things (IoT). By integrating these technologies, warehouses can enhance operational performance, reduce costs, and improve inventory management. The research identifies how automation tools, such as robotics and automated guided vehicles (AGVs), streamline processes, reduce labour costs, and minimize human error. Furthermore, advanced data analytics enable real-time decision-making and predictive analytics, allowing for optimized inventory levels and enhanced demand forecasting. The IoT facilitates seamless communication between devices, improving visibility and traceability throughout the supply chain. Through case studies and empirical data, this paper demonstrates that warehouses adopting digital transformation strategies experience significant improvements in productivity, accuracy, and customer satisfaction. However, it also addresses the challenges faced during implementation, including workforce adaptation and cybersecurity concerns. Ultimately, this study emphasizes that embracing digital transformation is not merely a trend but necessary for warehouses aiming to thrive in an increasingly competitive market. The findings underscore the importance of strategic planning and investment in technology to achieve sustainable efficiency gains.

Optimizing Deep Learning Models For Edge Devices: A Framework for Efficient Ai Deployment
Authors:-Preethi V, Associate Professor Dr S R Raja

Abstract-The proliferation of edge devices such as smartphones, IoT sensors, and embedded systems has driven the demand for deploying artificial intelligence (AI) models directly on these devices. However, the limited computational and energy resources of edge devices present significant challenges for deep learning (DL) models, which are typically resource-intensive. This paper proposes a novel framework for optimizing deep learning models for edge devices, focusing on techniques such as model compression, quantization, and knowledge distillation. By applying these techniques, the proposed framework ensures minimal loss of accuracy while significantly reducing model size and inference time. The effectiveness of the framework is demonstrated through experiments on image recognition and natural language processing tasks. The results highlight the potential for scalable AI solutions on edge devices without compromising user experience.

Automatic Pathole Detection System
Authors:-K .Kirti, W.Yash, C.Nihal, W. Nikhil, Professor Vairalkar, Professor T.Vivekanand

Abstract-Automatic Pothole Detection While Driving the main theme of the design is Smart Vehicles Electric vehicle/ Electric vehicle motor and battery technology. The arising need to help road accidents has ultimately came important aspect of moment’s developing world, the graph has taken a high rise in once 5 times. And numerous families being victims of this situation have suffered a lot. 60 of road accidents are passed due to uneven roads and interferers in the line. we came up with a an idea to descry potholes and humps in an automatic manner. and the person driving will be conceded about the pothole. An automatic pothole sensor using ultrasonic detector, which detects the potholes with the help of ultrasonic detector including longitude, latitude and depth of pothole and road humps. After seeing it sends the signal to GPS receiver through Arduino WiFi module which also displays the details in the TV and a android operation. This design can be used in the transport department as the importing and exporting is substantially done in night times and this sensor helps to warn the motorists. As this product has low manufacturing bring the price might not differ important and is surely affordable for a common man, due to its range of price the deals will rise to peaks and the manufacturer also has reasonable profit.

DOI: 10.61137/ijsret.vol.11.issue1.104

Review on Improvement of Shunt Active Filter Performance Using Artificial Intelligence Methods
Authors:-Manish Tomar, Raghunandan Singh Baghel

Abstract-In this review study, we looked at a variety of power filter approaches for high-power applications that frequently involve complicated digital control circuits and expensive batteries. An analog-based hysteresis current controller and capacitive energy storage are used to create a simple and low-cost active power filter circuit in this study. The filter is designed to be a low-power add-on item that reduces AC harmonic currents generated by existing electronic equipment (such as personal computers), which cause nonlinear loads on the AC mains. The suggested filter is addressed in terms of its operating concept, design requirements, and control method.

Kissan Buddy-An Android Application for Estimating The Nearest Mandi and Transaction Costs for Farmers
Authors:-KV Achyuth Reddy, Lochan S, Associate Professor Dr. M Swapna, Shrusthi, Ediga Purushotham Goud

Abstract-Kissan Buddy is an Android application developed to assist farmers in accessing real-time information about nearby mandis (agricultural markets) where they can sell their produce at optimal prices. The app utilizes Google Maps for accurate location services and Firebase for backend support, enabling farmers to input essential details such as their location, types of crops, and expected production costs. Based on this input, the application identifies the nearest mandis and estimates the transaction costs involved in selling the produce. This empowers The application uses advanced technologies such as Firebase, Google Maps, and cloud computing to offer farmers an intuitive platform where they can track their location, manage crops, and estimate nearby mandis (markets) where they can sell their produce, ensuring better price transparency and reducing reliance on middlemen. Key features of the app include location-based mandi search, real-time price estimation, and detailed transaction cost analysis. By improving market access, optimizing pricing transparency, and minimizing costs, Kissan Buddy aims to enhance profit margins for farmers and contribute to a more efficient and sustainable agricultural economy.

DOI: 10.61137/ijsret.vol.11.issue1.105

Teaching Identification of Fractions in Context Using the Three-tier Teaching Model’s Pedagogy
Authors:-Daniel Gbormittah, Christopher Yarkwah

Abstract-This paper aims to expand our understanding of culturally relevant pedagogy by utilizing the three-tier model for teaching mathematics in a context. The three-tier model is culturally relevant pedagogy (CRP). It is an innovative teaching approach that draws on learners’ sociocultural contexts to scaffold mathematics learning. The study investigated the effects of a culturally relevant pedagogy through the use of the three-tier model on pupils’ performance in fractions in Mfantsiman Municipality (MM). The study drew on ethnomathematics and the three-tier model as its main conceptual perspective. We administered a performance test to 426 participants in 12 primary schools in the MM. We analysed the quantitative data using frequency counts, mean, standard deviation, independent samples t-test, and paired samples t-test. We employed content analysis and narrative discussion to scrutinize the qualitative data. The results demonstrated that the culturally relevant pedagogy, specifically the three-tier model for teaching mathematics in a context approach, outperformed the conventional approach, reflecting the regular practices of primary school teachers in MM. The findings have implications for policy and the ongoing professional development of mathematics teachers.

DOI: 10.61137/ijsret.vol.11.issue1.106

Art without Borders: Exploring Transcultural Adaptations in Visual Creativity
Authors:-Sarika Tyagi

Abstract-This article delves into the concept of transcultural adaptations in visual arts, a practice that involves blending diverse cultural traditions, aesthetics, and ideas to create innovative and boundary-defying works. From historical exchanges along trade routes to the digital innovations of the contemporary era, transcultural art reflects the dynamic interplay of cultures across time. While celebrating creativity and hybridity, it also navigates critical ethical questions surrounding cultural sensitivity, power dynamics, and authenticity. By examining its historical roots, modern practices, and societal impact, this piece highlights the role of transcultural art in fostering dialogue, empathy, and inclusivity, ultimately enriching the global artistic landscape.

DOI: 10.61137/ijsret.vol.11.issue1.107

The Role of TiO2 Nanoparticles in Enhancing the Structural Properties and Thermal Stability of PVA Nanocomposites
Authors:-Assistant Professor R.Venugopal, Associate Professor Chandana.N, Assistant Professor S.Kiran, Assistant Professor B.Srinivas

Abstract-Polyvinyl alcohol (PVA) nanocomposites reinforced with titanium dioxide (TiO2) nanoparticles have garnered significant attention due to their unique properties and potential applications. In this study, we investigated the impact of TiO2 incorporation on the structural characteristics and thermal stability of PVA-matrix-based nanocomposites. The PVA polymer nanocomposite films were prepared using a solution casting method. The structural studies of the prepared films were characterized via X-ray diffraction (XRD), transmission electron microscopy (TEM). Moreover, the thermal properties of the prepared films were characterized by DSC, TGA and DTA. The addition of TiO2 nanoparticles induces structural changes in the PVA matrix. TEM studies showed that a PVA polymer surrounds TiO2 in its entirety. The PVA-TiO2 nanostructure is the same as the structure of a core-shell nanostructure. TiO2-doped PVA nanocomposites exhibited improved thermal stability. Thermogravimetric analysis of the nanocomposite films demonstrated enhanced resistance to thermal degradation. DSC analysis of the PVA-TiO2 nanocomposite films revealed that the glass transition temperature (Tg) and melting temperature (Tm) were 141°C and 265°C, respectively, for the 8 wt.% TiO2-incorporated PVA-TiO2 nanocomposites. The TGA and DTA studies of these nanocomposites revealed that their degradation behavior follows a four-step process. In comparison to those of pure PVA, these composites exhibit a sluggish decomposition rate, suggesting that the better thermal stability of these composites can be attributed to the better interaction among the -OH functional groups of PVA and TiO2 nanoparticles. These nanocomposites hold promise for various applications, including coatings, sensors, and optoelectronic devices. The combined effects of structural reinforcement and thermal stability make these materials attractive for engineering applications.

DOI: 10.61137/ijsret.vol.11.issue1.108

The Potential of Durian Husk, Durian Leaf-Litter and Banana Pseudo Stem as Bio-Leather
Authors:-Erika Grace Y. Sartagoda, Claire Joy Alicarte, Cyra Fathmah Cotin, Ruben Jr. Loren, Shecainah Lagaran, Cheerwina D. Puyales

Abstract-This study aimed to investigate the potential of durian husk, durian leaf litter, and banana pseudo stem as bio-leather. The bio leather was made from durian husk, durian leaf litter and banana pseudo stem. The bio leather made from these materials were tested in terms of its thickness, elongation and tensile strength. Also, as comparison the synthetic leather was tested according to its thickness, elongation and compression strength. The tests were performed at TERMS Concrete and Materials Testing Laboratory, Inc. Data were analyzed using mean and Mann Whitney U test. Results showed that, bio leather can be used to make light weight wallets since it only requires less thickness, low percentage of elongation and low tensile strength. For synthetic leather, can be used to make bags since the values of the indicators are high. The bio leather and synthetic leather do not significantly differ in terms of thickness, elongation and tensile strength; therefore, bio leather can be a good substitute for synthetic leather in making valuable items with high economic value.

DOI: 10.61137/ijsret.vol.11.issue1.109

The Reception Theory and the Value of Adaptation in Literature and Visual Arts
Authors:-Sarika Tyagi

Abstract-This article explores the intersection of reception theory and the value of adaptation in literature, visual arts, music, and theater. Reception theory, pioneered by Hans Robert Jauss, shifts the focus from the creator to the audience, emphasizing the evolving cultural and personal contexts that shape how stories are interpreted. Adaptations serve as transformative dialogues between the original work, its reimagining, and contemporary audiences, ensuring stories remain relevant across time and space. Examples such as Jean Rhys’s Wide Sargasso Sea, Alfred Hitchcock’s Rebecca, and Lin-Manuel Miranda’s Hamilton illustrate how adaptations reframe narratives to address new perspectives, cultural dynamics, and societal values. This article highlights how the reinterpretation of familiar tales enriches their meaning, engages diverse audiences, and underscores the timeless power of storytelling. By applying reception theory, the article demonstrates that the true value of adaptations lies in their ability to connect, challenge, and inspire audiences across generations.

DOI: 10.61137/ijsret.vol.11.issue1.110

Project Naiad: An Automated Smart Irrigation Revolution for Urban Home Gardens Using Arduino UNO R4 Wi-Fi
Authors:-Bernard Felipe B. Capalit, Client Teejay N. Jimenez, Anna Fatima P. Padao, Cairoden L. Usman Jr.

Abstract-This study aimed to develop a prototype of an automated smart plant watering system for urban home gardening, focusing on the reliability and functionality of its monitoring, notification, and water dispensing features. The system incorporated components such as the Arduino Uno R4 WiFi, DHT22 sensor, soil moisture and water level sensors, a raindrop sensor, and a submersible pump to address urban gardening challenges. The study evaluated the accuracy of the system’s sensors, the real- time data display, and SMS notifications, as well as the precision of water dispensing based on soil moisture levels. Results indicated high reliability, with most sensors achieving accuracy rates between 90% and 100%. The soil moisture sensor provided consistent readings, while the raindrop and water level sensors performed with near- perfect accuracy, enabling precise environmental monitoring. Notification features, including the LCD display and SMS alerts, were effective, with minimal delays in SMS reception. The water dispensing system demonstrated precision, adjusting water volume according to soil moisture levels, achieving an average water conservation effectiveness of 85% or higher. Additionally, a weak negative correlation between soil moisture and water dispensed highlighted the system’s responsiveness to environmental conditions. In conclusion, the prototype proved effective in monitoring and responding to soil conditions while minimizing water usage, making it a viable solution for urban home gardening. Future work could explore IoT-based enhancements for improved real-time monitoring, remote control, and data logging to further optimize system functionality.

DOI: 10.61137/ijsret.vol.11.issue1.111

Spammer Detection and Fake User Identification
Authors:-Assistant Professor Devi .S, Nived P J, Abhijith M, Boya Pavan Kumar, Spandau Gowda B C

Abstract-Social networking platforms attract millions of users globally. The interactions of these users with sites like Twitter and Facebook have a significant effect, often bringing about negative consequences in everyday life. Major social networking sites have become prime targets for spammers who disseminate vast amounts of irrelevant and harmful information. For instance, Twitter has emerged as one of the most extensively used platforms, leading to an overwhelming influx of spam. Fake accounts distribute unwanted tweets to promote services or websites, impacting genuine users and causing disruption in resource utilization. Additionally, the likelihood of spreading misinformation through counterfeit identities has grown, resulting in the circulation of harmful content. Lately, research has increasingly focused on detecting spammers and identifying fake accounts on Twitter within the realm of modern online social networks (OSNs). This paper examines various methods employed to identify spammers on Twitter.

Integrated Approach to Emotion Recognition Across Multiple Modalities
Authors:-Dr. Kavitha C, Jananisri K, Monisha B T, Prathibha G, Shanmitha P, Niranjani T

Abstract-Multimodal emotion recognition is essential for advancing human-computer interactions and enabling applications like mental health monitoring and social robotics. This study focuses on utilizing text, audio, and motion data from the IEMOCAP dataset to develop independent models that capture unique emotional cues from each modality. The audio model employs a hybrid architecture combining Convolutional Neural Networks (CNN), Multi-Head Attention, and Gated Recurrent Units (GRU), achieving an accuracy of 81%. The text model leverages a CNN-based approach inspired by Temporal Convolutional Networks (TCN), achieving 94% accuracy. For motion data, a Spatio-Temporal Graph Convolutional Network (ST-GCN) was implemented, achieving 63% accuracy. A score-level fusion strategy integrates these models, improving the overall recognition performance. Evaluations using metrics like accuracy, precision, and recall demonstrate how multimodal approaches can provide a more accurate and reliable emotion recognition system by combining complementary information from diverse data types.

DOI: 10.61137/ijsret.vol.11.issue1.112

Exploring How Globalization and Migration Have Impacted the Transformation of Religious Practices among the Youth in Singapore
Authors:-Margaret Pereira, Dr. Md Rosli Bin Ismail

Abstract-Youth expect religion to create meaning in life. These expectations play a significant role in practised religion and significant changes in the religious landscape. Participation in places of worship continues to decline. Organised religion might be facing a shifting landscape but this does not mean people are shunning religion. The interactions between religious institutions and an individuals’ perspectives of religion are investigated to reveal the transformation of religious practices in Singapore, from the lens of globalization and migration. Kierkegaard’s Theory of Existentialism is used along with non-probability purposive sampling with an objective to explore how globalisation has affected religious practices of Christian youth in Singapore and to investigate how migration has affected religious practices among Christian youth in Singapore. The key informants are six young Singaporean Christian adults between 25 and 30. Qualitative approach, semi-structured interviews, open-ended questions, in-depth interviews and thematic analysis is used.

DOI: 10.61137/ijsret.vol.11.issue1.113

Adaptive Reuse and Customization
Authors:-Harishanthana US

Abstract-Adaptive reuse is the best eco-friendly design strategy to repurpose existing building forms, stepping towards sustainability and a better environment. This type of revitalization is not restricted to buildings of historic significance but is also a smart strategy adopted in the case of archaic buildings. Customizing and reusing the existing built form not only saves money and profit but also a large amount of reduction in energy consumption and environmental impacts. Preservation, Rehabilitation, Restoration, and Reconstruction are major methods in bringing Adaptive reuse and Customization efficiently. Reusing the older vacant buildings for other purposes forms a very important outlook of any urban regeneration scheme and the adaptation process suggests opting for new technologies and design concepts that will support the older built to acclimate successfully to contemporary requirements without destroying the existing urban form. Adopting the adaptive reuse approach for the redevelopment of older vacant buildings provides added benefits to the regeneration of an urban area in a sustainable way, by transforming these buildings into usable and accessible units and providing a new sense of access to the public. While a large amount of historically built structures are being demolished and reconstructed. Adaptive reuse and customization could retain the built environment to the functions and needs and also maintain the historical facts and cultural factors.”

DOI: 10.61137/ijsret.vol.11.issue1.114

Fault Identification of Vibration-Based Condition Monitoring of Motor Using Minitab and Matlab: A Case Study on Francis Turbine
Authors:-Vishwas I, Bhagyaraj KS, Samiullah R, Ashok C, Professor Dr. Yadavalli Basavaraj, Professor Dr. V. Venkata Ramana, Assistant Professor Dr. Pavan Kumar.B. K

Abstract-This paper discusses the identification of faults in a Francis turbine using vibration-based condition monitoring with Minitab and MATLAB. The vibration signals are analyzed to detect faults in the motor components of the turbine. Statistical analysis uses Minitab to identify trends, while MATLAB carries out advanced signal processing, including Fast Fourier Transform (FFT) and wavelet analysis, to extract fault features. The combined approach effectively diagnoses issues like misalignment and bearing defects, showing its value in predictive maintenance for improved turbine performance.

DOI: 10.61137/ijsret.vol.11.issue1.115

Innovative Seed Sowing Machine for Improved Agricultural Productivity and Efficiency
Authors:-Mudgal Dipak Dinesh, V.D Dhanke

Abstract-This research focuses on the design and development of an innovative seed sowing machine aimed at improving agricultural productivity through precision and efficiency. Traditional sowing methods, which are either manual or use basic machinery, face challenges like inconsistent seed spacing, high labor requirements, and frequent blockages in seed dispensing tubes. These issues lead to reduced crop yields, increased operational costs, and significant seed wastage.The proposed seed sowing machine addresses these limitations by integrating automated seed dispensing, consistent depth control, and a blockage detection system using sensors. This machine is designed to place seeds uniformly at a specific depth and spacing, enhancing germination rates and ensuring even crop growth. Testing results demonstrate improved accuracy in seed placement and reduced downtime, showing a potential to save up to 40% of labor compared to traditional methods.Overall, this seed sowing machine offers a cost-effective and efficient solution for small to medium-scale farmers, enabling more sustainable and productive farming. This research lays the groundwork for future advancements in automated agricultural machinery, contributing to the broader goal of technological innovation in agriculture.

DOI: 10.61137/ijsret.vol.11.issue1.116

Flow Investigation over Oblique Wing Configuration
Authors:-Professor Dr. Prasanta Kumar Mohanta, Mysa Koushik, Borlakunta Praneeth, Y. Shanmukha Shambhavi

Abstract-This paper discusses the aerodynamic performance of oblique wing configuration in transonic and supersonic flight regimes. By using CFD tools within the ANSYS, the research has explored the function of oblique wing towards wave drag reduction and efficiency enhancement. Pivot angle variations of 0°, 30°, 45°, and 60° were used in asymmetrically designed wing and analysed at Mach 0.9 and 1.2. Some critical parameters include CL, CD, and pressure distribution, through which the design attains optimum operating characteristics. Some results reveal wave drag at specific pivot angles with the oblique wing. As the wave drags show least values for specific pivot angles (30°: Mach 0.9; 45°: Mach 1.2), these result in great applicability in improved aerodynamic efficiency and adaptability in varied conditions of flight towards the further developments of high-speed aircraft technology.

DOI: 10.61137/ijsret.vol.11.issue1.118

Performance and features of Amazon S3
Authors:-Fawaz Ali Syed, Mugdha Dharmadhikari

Abstract-This research paper investigates the multifaceted landscape of Amazon Simple Storage Service (Amazon S3), a pivotal component of cloud infrastructure provided by Amazon Web Services (AWS). By synthesizing findings from academic papers, industry reports, and case studies, it explores the fundamental features, security considerations, best practices, and real-world applications of Amazon S3. The analysis underscores the imperative of configuring S3 buckets meticulously to mitigate security risks, citing numerous instances of misconfigurations leading to data breaches. Through an in-depth examination of security best practices advocated by experts, including access control policies (ACPs), encryption mechanisms, and monitoring protocols. Additionally, it evaluates the scalability, reliability, and versatility of Amazon S3, positioning it as an indispensable asset for enterprises across various sectors. By leveraging insights from diverse sources, this research paper offers a comprehensive understanding of Amazon S3’s capabilities and advantages, providing actionable recommendations for optimizing its usage while safeguarding data integrity and confidentiality.

DOI: 10.61137/ijsret.vol.11.issue1.119

A Promising Breakthrough for Prostate Cancer Screening
Authors:-Jalene Jacob

Abstract-Prostate cancer is a major cause of morbidity and mortality among men worldwide. While traditional screening methods, such as Prostate Specific Antigen (PSA) testing and Digital Rectal Examiniations (DRE), have facilitated early detection, they face limitations, including false results and difficulty distinguishing aggressive from non-aggressive cancers. Recent advancements in urine-based testing offer a non-invasive, accurate alternative that improves diagnostic precision and reduces unnecessary biopsies. These tests analyze genetic and RNA biomarkers, providing personalized risk scores to guide biopsy decisions without requiring a DRE. They also address cultural barriers to screening and promote higher participation rates, particularly in underserved populations. Urine-based tests have the potential to optimize healthcare resources, reduce costs, and improve public health outcomes through early detection and intervention. However, equitable access, patient education, and data privacy protections remain critical considerations. As these tests become more widely available, they may transform prostate cancer screening and care.

From Irrelevant Utilisation to Excessive Dependence
Authors:-U. Sandhya Rani, S. Hemalatha, S. Mercy, T. Sushma Raj, Paila Bhanujirao

Abstract-The information relates to the use of substances that are harmful to one’s social, physical, mental, and emotional well-being, such as alcohol, opioids, tobacco, and some addictive medications like baclofen. This will have a complete impact on health. If used recreationally and developed into a habit of reliance. Substance misuse should be managed in its early stages since it cannot be stopped once it has developed into a habit. It can be challenging to stop using drugs if one has become habituated to doing so, and occasionally it can result in potentially fatal situations. When prescribed, some medications, such as opioids and non-opioid medications should be taken. However, longer periods of time should not be spent consuming them. And shouldn’t be stopped abruptly. Tapering the doses will help to progressively discontinue the consumption. In the event that consumption is abruptly stopped, coma or death may result. Substance abuse may influence vital organs over time, changing typical vital values over time. Because of reliance, each organ in the body will sustain harm through a variety of means.

DOI: 10.61137/ijsret.vol.11.issue1.120

Why a Flexible Workplace is Essential in a Modern Organization
Authors:-Anushka Gaikwad, Vaani Sharma, Anmol Rai

Abstract-The evolving dynamics of modern workplaces underscore the growing importance of flexible work arrangements in addressing the diverse needs of today’s workforce. This research delves into the necessity and impact of flexible workplaces, aiming to understand their prevalence, motivational drivers, and implications across various demographics, including students, professionals, and part-time employees. The study adopts a multi-faceted approach to examine patterns of flexibility, encompassing remote work, hybrid models, and flexible working hours, while evaluating their role in enhancing productivity and promoting a better work-life balance. A key focus is placed on identifying the motivational factors that lead individuals to prefer flexible arrangements, such as improved productivity, reduced commuting time, educational commitments, and family responsibilities. The study also assesses the challenges encountered, including time management difficulties, communication barriers, technical issues, and social isolation. By exploring these dimensions, it seeks to illuminate how flexible work environments can both empower individuals and pose unique obstacles that require organizational attention. In addition to individual experiences, the research evaluates organizational support systems and infrastructure, such as the provision of digital tools, internet allowances, structured guidelines, mental health initiatives, and workspace accommodations. These mechanisms are analyzed to understand their effectiveness in creating a conducive environment for flexible working. The study further examines how flexible work arrangements influence productivity across different contexts and demographic groups, offering valuable insights into their broader organizational and societal implications. The findings provide actionable recommendations for organizations aiming to implement or improve flexible work policies. These include fostering a culture of inclusivity, investing in digital infrastructure, offering targeted training programs, and creating clear guidelines to support employees effectively. Ultimately, the research highlights the transformative potential of flexible work arrangements in building resilient, adaptive, and employee-centric organizations capable of thriving in a rapidly changing work environment.

DOI: 10.61137/ijsret.vol.11.issue1.121

Telugu Voice Based Farmer Friendly Equipment Booking System
Authors:-Assistant Professor Durgunala Ranjith, Muskaan Thabassum, Kanraj Dhanush, B Bharath Kumar

Abstract-Agricultural equipment booking can be a challenging task for rural farmers due to language barriers and the complexity of existing digital platforms. This study is based on the concept of equipment rental. The E-commerce website has been improved as part of this project to bridge the gap between the farmer and the vendor on a lease basis. Only the user has access to the main programme after going through the login procedure; only the user may pick and book resources. This paper is jam-packed with information about the products. Farmers will benefit from this paper. The main goal of this website is to manage a variety of agricultural machinery, including Harvester, JCB, Tractor, Pickup, Rotor, and other agricultural machinery. End users will find the proposed system simple to use. As a result, we created a single website. We are attempting to provide the farmer or user with a solution that allows them to rent the goods by the hour.

DOI: 10.61137/ijsret.vol.11.issue1.122

Quantum Computing and its Effect on Sustainability
Authors:-Ravi Teja G, Associate Professor Dr. S. R. Raja

Abstract-Quantum computing is a new technology capable of solving problems that traditional/normal computers cannot handle. It is based on principles like superposition, entanglement, and interference to process information in ways that are not possible in classical computing. Unlike traditional computers that rely on bits as units of information, quantum computers use qubits, which can exist in multiple states simultaneously. This unique ability of qubits enables the quantum machines to perform computations at speeds that cannot be attainable by classical/normal systems. This new technology has the potential to transform all industries by addressing challenges in optimization, simulation, and data processing. For instance, quantum algorithms can simulate complex molecular interactions, leading to faster drug discovery in the pharmaceutical industry. Similarly, in logistics, quantum computers can optimize supply chains and reduce energy consumption, supporting more sustainable practices. Despite its promise, quantum computing also faces hurdles such as high costs, limited accessibility, and the need for stable operating environments.

The Role of Trolling in Mental Health and Creativity of Online Content Creators
Authors:-Tanisha Das, Assistant Professor Ms. Megha D. Prasad

Abstract-Trolling, defined as repeated and intentional online harassment, has become a significant issue for online content creators, affecting their mental health and creativity. This study aims to explore the role of trolling on psychological well-being and creative processes of content creators, addressing the gap in existing literature. Utilizing a qualitative exploratory design, semi-structured interviews were conducted with online content creators aged 18-45 who have experienced trolling. Participants were recruited through social media platforms using purposive and snowball sampling techniques. Data were analyzed thematically to identify patterns related to coping strategies, emotional impact, influence on content, long-term effects, and the role of platform support. The findings revealed that trolling contributes to heightened anxiety, self- censorship, and decreased motivation to produce creative content. Creators also reported dissatisfaction with the current support systems on social media platforms, highlighting a need for better moderation policies. This research underscores the importance of developing more effective support systems and mental health resources for content creators, along with stronger platform policies to combat trolling. The study contributes to a deeper understanding of the dual impact of trolling on mental health and creativity, paving the way for further research on supportive interventions in digital spaces.

Optimizing AI-Driven Decision Support Systems: Balancing Efficiency, Accuracy, and Ethical Considerations
Authors:-Yoga Srinivas B, Dr S R Raja

Abstract-Optimizing AI-driven decision support systems necessitates a careful balance between efficiency, accuracy, and ethical considerations. Efficiency involves ensuring that the system processes data swiftly and provides timely insights. Accuracy emphasizes the need for reliable and precise outputs to inform decision-making. Ethical considerations are paramount, addressing potential biases in data and algorithms to ensure fair and just outcomes. Transparency in the decision-making process fosters trust and accountability. By integrating these factors, AI-driven decision support systems can enhance decision-making processes while upholding ethical standards and maintaining user trust.

DOI: 10.61137/ijsret.vol.11.issue1.123

Green Revolution in Vector Management
Authors:-Stelson F. Quadros

Abstract-The primary vectors for the spread of diseases of concern like malaria, dengue, are mosquito species, particularly Aedes and Culex. There has been an exponential use and increased reliance by smaller groups, not specific to municipal and govt health bodies, but by housing societies and private pest control companies who rely on the acceptability of Thermal Fogging, as one of the key control or management factors of mosquito in urban setup. The professional pest control agencies are forced to adopt the use of Thermal Fogging even if there are ULV based options as there is fairly low awareness and poor visible changes at municipal level where adoption of ULV is not seen for more immediate adoption at social self help groups and with housing societies or with professional pest management companies. The urgent need to induct for a more less pollutant carrier, like BIODIESEL in thermal fogging and use of Plant Extract based Larvicides in water sources having significantly low toxicity will help build a more sustainable and low toxic mosquito management program, helping the human society at large to be truly living healthy through the means of Integrated Mosquito Management. In stark contrast where the use of polluting carriers like diesel leaves more lasting environmental damage affecting many more lives, than saving a few.

DOI: 10.61137/ijsret.vol.11.issue1.124

Implementing a Gamified Learning System for Enhancing Student Engagement and Motivation Using Reward-Based Mechanisms and Machine Learning
Authors:-Anand Sharma, Kunal Borage, Sujal Trivedi, Nikhil Neware, Professor Radhika Adki

Abstract-Student engagement would be one of the core elements that improve educational outcomes in the classroom. A gamification framework with machine learning would increase participation and personalize the experience of learning. The framework, through mechanics such as points, badges, leader boards, and challenges, encourages the participants to engage in the learning experience and enjoy it. However, machine learning facilitates adaptive learning by adapting the content based on the individual’s performance metrics. Student sentiment analysis helps to identify which students are in need of support, and predictive analytics would be used for identifying the students that may require more support. Real-time analytics allows teachers to keep track of student progression as well as classroom trends in real time. The system was designed to improve engagement and increase efficiency in the learning process. It considers the fact that competition can get unhealthy at times as well.

DOI: 10.61137/ijsret.vol.11.issue1.125

EMO Diary: Daily Diary with Sentiment Analysis
Authors:-Dr.Kavitha Soppari, Sk Hussain, Gvn Surya, M Pulla Rao

Abstract-The “Daily Diary Writer with Sentiment Analysis” project is a full-stack web application focused on enhancing personal well-being through sentiment analysis. Users can write daily diaries journals, and the system uses natural language processing to analyze the emotions expressed in their entries. This helps users reflect on their emotional patterns over time. Voice input allows for hands-free journaling, making the process more convenient and accessible. The project promotes self-reflection and emotional well-being through detailed sentiment insights.

DOI: 10.61137/ijsret.vol.11.issue1.126

Automation Bot for Data Extraction and Processing
Authors:-Assistant Professor Ms. Shristy Goswami, Aditya Singh, Anant Shukla, Anurag, Divanshu

Abstract-This paper presents the development and implementation of an automation bot designed for efficient data extraction and processing tasks. The bot automates the process of accessing a website, downloading an input Excel file, and extracting account numbers from the file. It then compares the last four digits of each account number with the digits in the names of zip files available on the website. Upon finding a match, the bot downloads the corresponding zip file, extracts its contents, and processes the required data from the unzipped text file, subsequently loading this data into the specific account number’s field. This automation bot significantly enhances data handling efficiency, reduces manual errors, and streamlines the data management process.

DOI: 10.61137/ijsret.vol.11.issue1.127

Thermal Insulating and Sound-Insulating Fiberboards Using Durian (Durio Zibethinus Murray) and Cogon Grass (Imperata Cylindrica)
Authors:-Denaga, Allona Devy P., Mamac, Leah O., Suguitan, Janine S., Sherwin S. Fortugaliza

Abstract-Global warming is impacting our communities, health, and wildlife, while noise pollution negatively affects both physical and mental well-being. This study examined durian husk and cogon grass fibers as sustainable materials for fiberboard production, focusing on their moisture resistance, thermal insulation, and soundproofing properties. These natural fibers outperformed traditional fiberboards. In sound absorption tests, durian fibers achieved 64.017 Hz, cogon fibers measured 67.600 Hz, and combined fibers recorded 62.617 Hz, compared to 83.033 Hz for the control group. Regarding thermal performance, durian fiberboards exhibited temperatures of 36.25°C and 36.95°C, while cogon fiberboards measured 37.90°C and 39.00°C. The commercial insulator consistently registered temperatures of 45.05°C and 46.05°C. Both durian and cogon fiberboards demonstrated 0% water absorption after 24 hours, in stark contrast to traditional fiberboard, which absorbed 200% more. This research underscores the potential of durian husk and cogon grass fibers as superior, eco-friendly alternatives for construction, effectively addressing noise and heat challenges in tropical regions.

Wireless Charging Platform for Drones Using WPT Technology
Authors:-Assistant Professor Ms. G. V. Swathi, S. Ronak Jain, S. Pushpa, K. Naga Sai

Abstract-Drones are becoming indispensable tools in various critical sectors of India, such as agriculture, disaster management, land surveys, mining, and infrastructure mapping. Their ability to access remote, hazardous, or hard-to-reach areas makes them invaluable for tasks, such as crop monitoring, search and rescue, and real-time data collection. However, the effectiveness of drones in these mission-critical applications is often limited by their battery life and the need for frequent recharging, particularly in environments where human access is difficult or impossible. This project addresses this challenge by developing a wireless power transfer (WPT) system for drone charging. The system converted a standard 230V supply into a low-voltage DC output, which was then wirelessly transferred via a high-frequency (100kHz) inverter and coil setup. This WPT system is particularly suited for use in remote or inaccessible locations, where minimizing downtime is critical.

DOI: 10.61137/ijsret.vol.11.issue1.128

Advancing Human-Centered Artificial Intelligence: Enhancing Explainability Real-World Applications
Authors:-Sriram R, Dr S R Raja

Abstract-Human-centered artificial intelligence (HCAI) emphasizes designing AI systems that prioritize human values, ethics, and usability, fostering trust and responsible adoption. This research explores the advancement of HCAI by addressing key challenges such as improving explainability, integrating ethical considerations, and optimizing real-world applications across diverse sectors. By investigating state-of- the-art methods for interpretable machine learning, the study aims to enhance user understanding and transparency in AI decision-making. It further examines frameworks for embedding ethical principles, including fairness, accountability, and privacy, into AI system design. Additionally, the research evaluates case studies from healthcare, education, and autonomous systems to illustrate the transformative potential of HCAI. This study underscores the need for interdisciplinary collaboration and innovation to ensure AI technologies align with human values and societal goals, paving the way for more inclusive and sustainable AI solutions.

DOI: 10.61137/ijsret.vol.11.issue1.129

Crop Disease Detection System
Authors:-Rupesh Gaikwad, Sarvesh Dharme, Vedant Zawar, Nachiket Kulkarni, Professor Prachi Tamhan

Abstract-One of the important and tedious tasks in agricultural practices is the detection of disease on crops. It requires time as well as skilled labor. This paper proposes a smart and efficient technique for the detection of crop disease which uses computer vision and machine learning techniques. Every year India loses a significant amount of annual crop yield due to unidentified plant diseases. The traditional method of disease detection is manual examination by either farmers or experts, which may be time-consuming and inaccurate. It is proving infeasible for many small and medium-sized farms around the world. To mitigate this issue, a computer-aided disease recognition model is proposed. It uses leaf image classification with the help of deep convolutional networks. In this paper, CNN was proposed to detect plant disease. It has three processing steps namely feature extraction, downsizing image, and classification. In CNN, the convolutional layer extracts the feature from the plant image. It helps to give personalized recommendations to farmers based on soil features, temperature, and humidity.

DOI: 10.61137/ijsret.vol.11.issue1.130

Design and Implementation of a Cost-Effective, Low-Latency IoT-Enabled Dental Chair: A Global Remote-Control Solution for Enhancing Clinical Efficiency and Pre-Operative Preparations
Authors:-Hiren Uthaiah M S, Khyati Priyesh, Manjunath K V, Samichi S Mathad, Siddhart Dhargi, Suhas S Rao

Abstract-This research introduces two innovative methods to convert a standard 16-control dental chair into an IoT-enabled dental chair at a minimal cost of under 2,000 INR. The first method involves directly interfacing the chair’s control wires with a 16-channel relay and an ESP32 microcontroller, enabling remote operation through the Blynk IoT platform. The second method leverages signal analysis by identifying the dental chair PCB’s communication lines, capturing control signals with a logic analyzer, and replicating them via the ESP32 for seamless functionality. Both approaches offer global control with minimal delay (<10ms) and enhance operational efficiency by enabling preemptive actions, such as heating water or cleaning the spit bowl remotely. This study provides a scalable, low-cost solution for modernizing dental chairs, ensuring ease of use and adaptability for dental clinics worldwide.

DOI: 10.61137/ijsret.vol.11.issue1.131

Facial Expression Detection Using Machine Learning Techniques
Authors:-Associate Professor Dr Sudhamani, Assistant Professor Kavya S N, Galal Ahmed Ghaleb Abdo Almaghrebi M, Mohammad Reza Sharifi, Research Scholar Jagadeesh M

Abstract-Facial expression detection has emerged as a transformative technology with applications in numerous fields such as healthcare, security, and entertainment. The proposed system aims to enhance user engagement by dynamically tailoring playlists based on the user’s emotional state. The proposed Emotion Recognition provides a foundation for further exploration and development of intelligent systems that adapt to users’ emotional states, fostering more immersive and personalized interactions in the realm of digital entertainment.

DOI: 10.61137/ijsret.vol.11.issue1.132

Understanding A.I.
Authors:-Kajal Nanda

Abstract-This paper aims to provide an in-depth understanding of A.I., its historical development, and its transformative influence on modern civilisation. We will discuss significant concepts, evolving technologies under influence, technological advancements, and ethical and unethical A.I..

DOI: 10.61137/ijsret.vol.11.issue1.133

Latest Trends and Techniques Developed in Mechanical Engineering
Authors:-Nimgaonkar S.S., Gadade R.A., Gaikwad Niti N Bhagwat, Tambe Laxman Tukaram

Abstract-Mechanical engineers dream up and design amazing machines and technologies that improve people’s lives in all kinds of ways. From airplanes and cars to robots and renewable energy systems, mechanical engineers have shaped our modern world. New technologies are opening up incredible opportunities for innovation. Read on to learn about the exciting changes & future trends in mechanical engineering and how you can prepare for it!

DOI: 10.61137/ijsret.vol.11.issue1.134

Detecting Unauthenticated Access Using Honeypot Sentinel
Authors:-Varshini J, Asvica J, Bharathi A K, Deepika P, Dharshana S, Yazhini K

Abstract-Unauthorized access remains a critical threat to network security, as attackers can exploit vulnerable systems to obtain sensitive data or disrupt services. This paper introduces Honeypot Sentinel, a proactive intrusion detection tool designed to flag unauthorized access attempts by monitoring and verifying usernames and IP addresses. Honeypot Sentinel uses a MongoDB database for logging, enabling the system to record details of unauthorized access attempts efficiently. Upon detecting any access attempts outside the predetermined criteria, Honeypot Sentinel triggers alerts, allowing system administrators to promptly address potential threats. This approach provides network security teams with real-time data, helping them respond effectively to unauthorized access incidents.

Exploring the Role of Microglia Activation in Alzheimer’s Disease and Parkinson’s Disease
Authors:-Tamaradoubrah Favour Melex, Akuroseokike G Babbo

Abstract-Microglia, the principal immune cells within the central nervous system (CNS), are essential for maintaining neuronal homeostasis. Nonetheless, the chronic activation of microglia has been associated with the development of neurodegenerative diseases, notably Alzheimer’s Disease (AD) and Parkinson’s Disease (PD). This review investigates the mechanisms underlying microglial activation, the dual functions of microglia in neuroprotection and neurotoxicity, and the implications for therapeutic strategies. By examining contemporary research, we aim to clarify the molecular pathways that link microglial activation to the progression of these diseases and identify potential approaches for modulating microglial responses to alleviate neurodegeneration.

Medicine Remiander Device Using ESP8266
Authors:-K. Likitha, M. Usha

Abstract-This journal discuss in detail on a suggested medication reminder device that will be made for senior citizens based on their problems. This study’s background is explained in the report, and its primary goal is to guarantee that the medication reminder device will be resolving issues that older people have. The problems that have been discovered are mostly focused at the elderly and are meant to address the problems that they encounter on a daily basis, particularly with regard to medication use. In order to design a better device, the study will also examine similar implemented devices and systems to determine the advantages and disadvantages of other pertinent devices and systems. This portable and economical system would be helpful to every age group also.

DOI: 10.61137/ijsret.vol.11.issue1.135

Assessment of Sustainable Building Material and the Benefits of Green-blue- grey Infrastructure for Feasible Urban Flood Risk Management
Authors:-Hambal Ahmad Khan

Abstract-The green infrastructure has some other benefits besides flood risk reduction. Those benefits mainly covers conservation of water, energy, and improvement in air quality and much more. The materials used are the essential components of the green infrastructure. The proper design accompanied by the material properties provides the accountability of the mechanical strength of the infrastructure. Hence, the eco-friendly materials are given more priority for green infrastructure. The price is considered primarily when either selected or r4elated material is compared for the similar purpose. Except the social and environmental costs, the cost of the building element conveys only the cost of transportation and manufacturing. Therefore, the sustainable development of the nation relies on the proper choice of the construction materials having least burden on the environment. Moreover, the result of mixture of blue, green and grey infrastructure is likely the best adaptation strategy as these comply with each other. The grey infrastructure reduces the flooding risk while the green infrastructure has its own multiple benefits which is not offered by the grey infrastructure. The paper focusses on the contribution of the sustainable building material in order to reduce the impact of environmental degradation which could help in identification of the strategies that are highly effective in improving the urban flood risk management.

Heart Attack Risk Assessment Using Deep Learning with Feature Optimization
Authors:-Ch. Rishitha, G. Poojitha, B. Sahith, Profeesor Shashank Tiwari

Abstract-Heart attacks remain a critical global health issue, necessitating accurate predictive models to identify at- risk individuals and support preventive care. This project, titled “Heart Attack Risk Assessment Using Deep Learning with Feature Optimization,” applies deep learning techniques to assess the likelihood of a heart attack. The study utilizes a Fully Connected Neural Network (FCNN) model enhanced by feature optimization methods, ensuring that the most relevant predictors are prioritized. Additionally, the project incorporates risk visualization, enabling clear and actionable insights for early detection and management of heart attack risks.

DOI: 10.61137/ijsret.vol.11.issue1.136

What Role Do Artificial Intelligence and Machine Learning Play in Enhancing Human Resource Decision-Making Processes by Method from 2015 to 2025 Using Bibliometric Method
Authors:-Muhammed Bah

Abstract-This research examines the impact of artificial intelligence (AI) and machine learning (ML) on improving human resource (HR) decision-making procedures, with an emphasis on the years from 2015 to 2025. Employing a bibliometric approach, the study uncovers trends, obstacles, and prospects related to artificial intelligence and machine learning usage in human resource management. The results depicted in Figure 1 (“Document by Year”) indicate a marked rise in research activity after 2020, emphasizing an increasing interest in the incorporation of AI and ML in HR practices. Figure 2 (“Document by Area”) illustrates that computer science (45%) and business studies (30%) lead in research contributions, highlighting the technical and strategic aspects of these technologies. The geographic analysis shown in Figure 5 (“Document by Country”) reveals that 40% of the studies come from the United States, while European and Asian nations account for 30% and 20%, respectively. Institutional contributions, shown in Figure 7 (“Document by Affiliation”), indicate that 60% of research originates from academic institutions, while corporate research centers account for 25%. Figures 3 and 4 underscore the variety of sources and funding, showing a balance between academic integrity and practical uses, with government funding representing 50%. The research highlights the revolutionary impact of Artificial intelligence and Machine learning in human resource management, especially concerning talent acquisition, employee engagement, and workforce management. Nevertheless, ethical issues, biases in algorithms, and privacy threats present significant challenges. By combining technological advancements with ethical guidance, as illustrated by the trends shown in the figures, organizations can develop adaptable, inclusive, and effective HR systems that meet the changing needs of the workforce.

DOI: 10.61137/ijsret.vol.11.issue1.137

Development of Robotic Arm Using Arduino
Authors:-Lingam Lakshmi Vagdevi, Edupuganti Harshitha

Abstract-Innovation in robotic arm control has been sparked by the development of Arduino-based technology, which provides both experts and enthusiasts with an affordable and user-friendly platform. The creation of robot arm control with an Arduino controller is presented in this work. The project entails integrating sensors and Arduino microcontrollers to provide dynamic and accurate control over a robotic arm. Four servo motors—which rotate left, right, front, and back—control the suggested robot. The study lays the groundwork for future developments in this emerging topic by discussing the difficulties faced during the development process and offering solutions. The demonstrated robotic arm control system has the potential to increase access to robotics education and promote automation innovation due to Arduino’s broad availability and low cost.

DOI: 10.61137/ijsret.vol.11.issue1.138

Object Detection Using Ultra Sonic Sensor
Authors:-Assistant Professor. D .Veeraswamy, Yagnasri Madhav, Lakkakula Lohith, Balla Kanth Naga Ayyappa

Abstract-Ultrasound is simply sound whose frequencies are too high to be heard by the mortal observance, that’s to say the frequencies are above c 20 kHz. At the top end of the scale, ultrasound is used at frequentness up to several GHz. The main end of this system is to descry object that will be ahead of ultrasonic transducer. Utmost ultrasonic detectors are grounded on the principle of measuring the propagation time of sound between send and admit (propinquity switch). The hedge principle determines the distance from the detector to the glass (retro-reflective detector) or to an object (through- ray detector) in the measuring range. Ultrasonic detectors are grounded on the measured propagation time of the ultrasonic signal. They emit high- frequency sound swells which reflect on an object. The objects to be detected may be solid, liquid, grainy or in greasepaint form. It sends an ultrasonic palpitation out at 40 kHz which travels through the air and if there is a handicap or object, it will bounce back to the detector. By calculating the trip time and the speed of sound, the distance can be calculated. Ultrasonic detectors are a great result for the discovery of clear objects.

DOI: 10.61137/ijsret.vol.11.issue1.139

Strategizing Digital Transformation with LangGen Cloud Computing
Authors:-Nikhil A Rawool, Dr. Tatiana Walsh, Professor John Lewis

Abstract-Cloud Computing with field of emergence with frameworks with intelligent platform based on cloud which is designed with “reliability , availability “ with key deliverables with a specific and specialized platforms which are designed on methods for computing technology and service streamlined with pattern – self based analysis for Multimedia Management with Enterprise on Digital Platforms for reviewing Data Agents for digital Background for computing level of architecture format with a self-developing ecosystem for pattern recognition and texture delivering format.

DOI: 10.61137/ijsret.vol.11.issue1.140

Data Transmission Using Li-Fi Technique
Authors:-A.Jeevan, P.N.Koushik, K.Murali

Abstract-Light fidelity (Li-Fi) technology is a wireless communication system that utilizes visible light spectrum to transmit data with high speed and secure manner compared to the traditional Wireless Fidelity (Wi-Fi) architecture. In this paper a smartphone is used in Li-Fi communication system. The aim of this proposed approach is to maximize the bit rate with high accuracy by using the flashlight of built-in smartphone camera as a source to send data and detect the effect of using a built-in smartphone ambient light sensor and external light detector sensors that is connected to Arduino UNO circuit to receive data. Four practical experiments were conducted to discover which light sensor accomplish higher data bit rate and tested the system performance under changing the distance between transmitter and receiver. The evaluation results demonstrated that the data bit rate is better with the proposed research than the others, where it reached more than 100 bps with accuracy 100%.

DOI: 10.61137/ijsret.vol.11.issue1.141

Cotton Detector and Collector Robot
Authors:-Professor Meenakshi Annamalai, Ashwini Rode, Archana Sonawane, Parigha Patil

Abstract-Robots that harvest cotton have become a viable way to alleviate labor shortages and boost production efficiency. In order to detect, navigate, and gather cotton bolls in the field, these robots use cutting-edge technologies. Cotton boll detection relies heavily on deep learning and machine vision methods. An innovative weed identification model that distinguished weeds from cotton seedlings with a map of 98.43% was developed using the CBAM module, the BiFPN structure, and the bilinear interpolation technique (Fan et al., 2023). The chromatic aberration approach showed great sensitivity and specificity with a 91.05% identification rate for cotton boll detection in natural lighting (Singh et al., 2021). GNSS and optical detection techniques are combined in cotton harvesting robot navigation systems. While boll position estimation demonstrated great precision with an R2 value of 99% when stationary and 95% when moving, a pixel-based method for cotton row detection obtained 92.3% accuracy (Fue, Li, et al., 2020). These developments in navigation and identification aid in the creation of accurate and productive cotton harvesting robots. In conclusion, there is a lot of promise for automating cotton harvesting through the combination of sophisticated detection algorithms, navigation systems, and robotic manipulation techniques. But there are also issues with adapting these technologies to different crop kinds and field conditions, which calls for more study and advancement in this subject.

Beta Blocker Management Post MI: Navigating Continuation and Interruption Strategies
Authors:-Bhupathi Sravani, Sirasani Tapaswi

Abstract-This study examines the effects of interrupting versus continuing beta-blocker therapy in post-myocardial infarction patients. The ABYSS trial, a multicenter noninferiority study, found that interrupting beta-blocker therapy did not offer any advantages over continuation in reducing major cardiovascular events or improving quality of life. The interruption group experienced a slight increase in hospitalizations for coronary-related conditions. These findings challenge existing guidelines recommending beta-blocker discontinuation after one year for certain patients. The trial highlights the necessity for additional research to clarify the role of beta-blockers in modern post-MI care, especially for patients with preserved left ventricular function.

DOI: 10.61137/ijsret.vol.11.issue1.142

School Management Committees’ Roles and Academic Performance of Pupils in Selected Government-Aided Primary Schools In Bulambuli Town Council, Bulambuli District
Authors:-Nambuya Mary, Dr. Ssendagi Muhamad, Wolukawu Ambrose

Abstract-This study investigated School Management Committee roles and the academic performance of pupils in selected government aided primary schools in Bulambuli Town Council, Bulambuli District. The study sought to; examine the relationship between the supervisory role of School Management Committees (SMCs) and academic Performance of pupils; examine the relationship between the supervisory role of School Management Committees (SMCs) and academic Performance of pupils; and examine the effect of the consultative role of School Management Committees (SMCs) on academic Performance of pupils. The study adopted a cross-sectional research design. Both simple random sampling and purposive sampling techniques were used to select the sample of respondents. The researcher studied a sample of 82 participants who included teachers, SMC members from selected government-aided primary schools, officials from DEO’s office and CCTs of selected schools in Bulambuli TC. Questionnaires and key informant interviews were used for data collection. Quantitative data from questionnaire was analyzed for both descriptive and inferential statistics using SPSS and Excel while qualitative data was analyzed thematically. The findings of this study were that; SMCs have significant influence on academic performance of pupils. The Pearson correlation coefficient shows that there is a significant positive relationship between the administrative role of SMCs and academic performance of pupils, r = 0.729, p = 0.000; supervisory role of SMCs influences the academic performance of pupils, r = 0.689, p = 0.000; and consultative role of SMCs has a significant positive relationship with academic performance of pupils, r = 0.648, p = 0.000. From the findings of this study, the researcher recommended that the SMCs should work with school administration to provide support such as academic intervention programs to struggling pupils so as to improve the academic performance of pupils; tighten regular monitoring and assessment of pupils’ progress to identify areas of improvement; and work closely with parents and other stake holders to support pupils’ learning. By involving the broader school community in academic initiatives, school will create a network of support that might help pupils thrive academically.

DOI: 10.61137/ijsret.vol.11.issue1.143

Simulation of Harmonics in Electric Locomotive Power Supply Device
Authors:-Assistant Professor Mr.J.Munichandra Sekhar, R .Prasad, P.Ganesh, K.Vijay Kumar, A. Tharun

Abstract-An electric locomotive power supply device is responsible for providing electrical power to the traction motors that drive the locomotive. These systems often use alternating current (AC) or direct current (DC) to power the motors, and they can operate using either overhead catenary systems or third-rail power supplies. Simulation of a locomotive power supply device involves analyzing its electrical and mechanical performance, power quality and efficiency. The power electric device which works under condition of high power and heavy load, suffer from faults frequently. The main circuit of the device is a kind of single-phase full bridge half controlled rectifier circuit. Harmonics are higher-frequency components that distort the waveform of current or voltage. In locomotive power supply systems, harmonics are typically introduced by non- linear loads, such as the power electronic devices (inverters, converters) used in these systems. Harmonics can cause several issues, including increased losses, power quality .

Blockchain Based Student Council Election Portal
Authors:-Professor Kusumlata Pawar, Asmi Santosh Wayare, Pooja Krishnakant Chavan

Abstract-The focus of this project is to make a secure and transparent voting system at college level. Even though paper based voting was a traditional approach and is being used for centuries, but still as we are facing the challenges during the overall voting process which includes, security risk, lack of transparency, human errors and privacy concerns. So, to overcome this limitations and vulnerabilities we came up with the idea of a blockchain based voting system. It is in high demand due to the immutability, transparency and decentralized solutions. The objective of this paper is to incorporate blockchain technology to construct a secure, tamper-proof elections at college level. It will also help developers to build and deploy smart contracts. The use of smart contracts guarantees the accuracy and provides fast voting result and makes counting procedures protected against fraudulent actions. This technology supports peer-to-peer decentralized network in which all the transactions are stored in blocks. To sum up, the proposed system will shorter the time for voting process while offering security and authentication and it also dwindles the expenses as there is no need to print ballots.

HSS and HCS Cutting Tool Material Influencing Surface Roughness in Machining of GFRP
Authors:-Dr. K N Lingaraju, Dhanushree M R, Prashanth Kumar N, Prashanth N, Vinayak Basavaraj Ganiger

Abstract-This work is concerned with the machining of Glass Fiber Reinforced Plastics (GFRP), with a primary interest in how surface roughness is affected by cutting tool materials. GFRP has found a niche in aerospace, automotive, and marine applications, and has obtained recognition for its ratio of strength to weight, resistance to corrosion, and thermal stability. Because of the peculiar structure of E-glass fibers in epoxy resin matrix systems, specific problems concerning the use of this material arise, such as delamination, fiber pull out, and wear of tools, thus requiring tailored machining techniques. The experiment compared performance between cut rods using high-speed steel (HSS) and high-carbon steel (HCS) while machining a GFRP rod (30 mm diameter, 240 mm length) using a lathe. Surface roughness parameters are Ra, Rz, Rt, Rpk, all measured by a Talysurf device. The results showed that HSS tools led to smoother surfaces and greater accuracy but that HCS tools were more economically viable for less rigorous jobs. These results touch upon the need for tool selection based on application and give some insight into further pros in terms of coatings, monitoring systems, and further sustainable machining approaches.

DOI: 10.61137/ijsret.vol.11.issue1.144

Design and Simulation of Fuzzy Logic-Based Maximum Power Point Tracking for Solar Pv Arrays
Authors:-Mr.D.Ramesh, M. Bharath Kumar, Sunkara Gyan Harsh, Shaik Sadik

Abstract-This paper presents a Fuzzy Logic-based Maximum Power Point Tracking (MPPT) algorithm for Solar Photovoltaic (PV) systems to enhance energy efficiency. The proposed approach adapts to fluctuating solar irradiance and temperature by utilizing rule-based logic, eliminating the need for precise mathematical models. Unlike traditional methods, the fuzzy logic controller provides fast and accurate responses, minimizing power loss and improving performance. It continuously adjusts the duty cycle of a DC-DC converter to maintain operation at the peak power point. MATLAB/Simulink simulations show faster tracking, reduced oscillations, and higher energy harvest compared to Perturb and Observe (P&O) and Incremental Conductance (IncCond) methods. This robust solution maximizes PV output, advancing the feasibility of solar energy as a renewable source.

Simulation and Performance Analysis of Solar PV System Using MATLAB
Authors:-Dr. M. Prasad, Ch.Srinitha, S.Srujan, N.Deva Raj

Abstract-Photovoltaic power generation system implements an effective utilization of solar energy, but has very low conversion efficiency. The major problem in solar photovoltaic system is to maintain the DC output power from the panel as constant. Irradiation and temperature are the two factors, which will change the output power of the panel. A boost converter is utilized as a DC-DC converter.The simulation includes the modeling of a solar panel, and a power conversion unit such as a DC-AC inverter. Key parameters such as irradiance, temperature, and shading effects are considered in the analysis to assess their impact on the power output and overall system efficiency. The results highlight the dynamic behavior of the system under different operating conditions. The MATLAB/Simulink environment is utilized to evaluate the system’s performance, and a comparison is made between the theoretical and simulated values. It is obtained by using MATLAB Simulink Model.The aim is to effectively track the maximum power points considering the fluctuations in solar irradiation and temperature.

Efficacy and Safety of an Oral Nutritional Supplement in Treating Nutritional Deficiencies and Related Conditions: A Phase 3 Randomized Controlled Trial
Authors:-Reedhika Puliani, Deepika Sharma, Priyanka Shetty

Abstract-Nutritional deficiencies are common worldwide and can also lead to weak immunity, weak stamina, metabolism and decreased bone health. To address these challenges, relying solely on diet may be insufficient, as most individuals do not consume nutritionally balanced diets. Nutritional supplements can help in achieving optimal, balanced nutrition while preventing nutritional deficiencies. This multicentre, double-blind, randomized, parallel-group phase 3 clinical trial evaluated the efficacy and safety of a nutritional supplement from British Life Sciences, Pvt. Ltd, BSURE Sugar-Free (Dutch Chocolate Flavour) against a multivitamin powder (Zooversandhaus Jung, Germany) in patients with nutritional deficiencies, weak immunity, low stamina, compromised bone health, and weak metabolism. Over three months, 231 participants were recruited, with 200 completing the study. Results demonstrated that BSURE achieved 97% and 98% efficacy in improving weak immunity and stamina, respectively, and showed comparable safety and tolerability to the control product. These findings support the use of the product for nutritional support in adults.

Magmla- Estate Agility
Authors:-Ritesh Kumar

Abstract-This is a presentation of the development of “Magma Estate Agility” web application. The application is designed with the use of HTML, CSS, and JavaScript for improving on estate management and aims at processes like property listing, tenant management, and sending in requests for maintenance. This paper describes the methodologies used, the technologies employed, and the results realized from the implementation of the project. From the findings, it shows that incorporating these technologies into the estate management process raises efficiency and user-friendliness in the processes.

Simulation of Harmonics in Electric Locomotive Power Supply Device
Authors:-Assistant Professor Mr.J.MunichandraSekhar, R .Prasad, P.Ganesh, K.Vijay Kumar, A. Tharun

Abstract-An electric locomotive power supply device is responsible for providing electrical power to the traction motors that drive the locomotive. These systems often use alternating current (AC) or direct current (DC) to power the motors, and they can operate using either overhead catenary systems or third-rail power supplies. Simulation of a locomotive power supply device involves analyzing its electrical and mechanical performance, power quality and efficiency. The power electric device which works under condition of high power and heavy load, suffer from faults frequently. The main circuit of the device is a kind of single-phase full bridge half controlled rectifier circuit. Harmonics are higher-frequency components that distort the waveform of current or voltage. In locomotive power supply systems, harmonics are typically introduced by non- linear loads, such as the power electronic devices (inverters, converters) used in these systems. Harmonics can cause several issues, including increased losses, power quality.

Simulation of Harmonics in Electric Locomotive Power Supply Device
Authors:-Assistant Professor Mr.J.MunichandraSekhar, R .Prasad, P.Ganesh, K.Vijay Kumar, A. Tharun

Abstract-An electric locomotive power supply device is responsible for providing electrical power to the traction motors that drive the locomotive. These systems often use alternating current (AC) or direct current (DC) to power the motors, and they can operate using either overhead catenary systems or third-rail power supplies. Simulation of a locomotive power supply device involves analyzing its electrical and mechanical performance, power quality and efficiency. The power electric device which works under condition of high power and heavy load, suffer from faults frequently. The main circuit of the device is a kind of single-phase full bridge half controlled rectifier circuit. Harmonics are higher-frequency components that distort the waveform of current or voltage. In locomotive power supply systems, harmonics are typically introduced by non- linear loads, such as the power electronic devices (inverters, converters) used in these systems. Harmonics can cause several issues, including increased losses, power quality.

MATLAB Implementation of Sine and Cosine Generator Using CORDIC Algorithm
Authors:-Assistant Professor Mr. Goutam Barma,K. Chakradhar,J. Appa Rao,S. Abhishek

Abstract-The CORDIC (Coordinate Rotation Digital Computer) algorithm is a versatile and efficient iterative method for computing a wide range of mathematical functions, including trigonometric, hyperbolic, exponential, logarithmic, and square root functions. Central to the CORDIC approach is its ability to perform vector rotations in a polar coordinate system, effectively transforming coordinates through a series of predefined angles. These methods eliminates the need for complex multiplications by utilizing simple shift and add operations, making it particularly well-suited for hardware implementations in resource-constrained environments, such as digital signal processors (DSPs) and field-programmable gate arrays (FPGAs).The algorithm operates in several modes, including rotation mode and vectoring mode, allowing it to adapt to various computational requirements. Each iteration reduces the angle by a fixed amount, using pre-computed arctangent values to guide the rotations. The convergence of the algorithm depends on the number of iterations, with higher iterations yielding greater accuracy. CORDIC’s unique architecture supports parallel processing, enabling simultaneous calculations of multiple functions, further enhancing its efficiency. Evaluation of trigonometric functions such as sine, cosine and tan has been obtained using MATLAB. This abstract encapsulates the fundamental principles, operational modes, computational advantages, and diverse applications of the CORDIC algorithm, underscoring its significance in modern digital computation and system design.

OpenCV- Based Intelligent Vehicle Surveillance and Time Stamping System
Authors:-Professor Dr.J.Preetha, Assisstant Professor Mr.R.Viswanathan, A Rasidha Begum, S Pooja, R Jona

Abstract-Automated traffic monitoring solutions have become necessary due to the difficulties of manual monitoring systems and the exponential growth in vehicular traffic. The new Advanced Vehicle Detection System described in this work uses sophisticated computer vision algorithms to identify, recognize, and log vehicle data in real time. Utilizing OpenCV, CNN (Convolutional Neural Network), YOLO (You Only Look Once), and OCR (Optical Character Recognition) technologies, the suggested system detects automobiles and records license plate information. In addition, the system gives law enforcement, traffic management, and institutional surveillance a reliable and scalable approach by automating the entry and exit timestamp logging process. Mostly we are developed for the college buses which has been include arrival and Departure time with an owner details and also the vehicle claim the insurance or not, These also updated the count of vehicle that are recognized by the entry and the exit time. Experimental results demonstrate the system’s high precision and efficiency, ensuring its practical applicability in real- world scenarios. This practical and efficient system is an excellent example of how technology can address real- world challenges in monitoring and managing vehicles.

DOI: 10.61137/ijsret.vol.11.issue1.145

PV Panel Drive 3-Phase Induction Motor Using Matlab Simulink
Authors:-Assistant Professor Mr.J.Munichandra Sekhar, K.Sudhakar, K.Pavan Kumar, K. Dheekshith

Abstract-This project presents a simulation-based study of a Photovoltaic (PV) panel driving a 3-phase induction motor using MATLAB Simulink. The model is developed to explore the feasibility of utilizing solar energy to power electric motors, which are essential in various industrial and agricultural applications. The PV panel generates DC power from sunlight, which is then converted into 3-phase AC power using a 3-phase inverter. The AC power is used to drive the induction motor, which converts electrical energy into mechanical energy to operate loads such as pumps and machinery. The MATLAB/Simulink environment is used to model and simulate the behavior of the entire system, including the PV panel, inverter, and induction motor. The simulation allows for real-time monitoring of key parameters such as power output, rotor speed, electromagnetic torque, and current in the motor’s stator and rotor. This enables performance optimization and ensures the system operates efficiently under varying irradiance and temperature conditions.

Impacts of Climate Change on the Himalayan Cryosphere: A Comprehensive Study of Snow Cover, Glacier Lakes, and Associated Geo-Hazards in Uttarakhand, India
Authors:-Samreen Azhar, Alishba, Anum Bibi, Meerab karamat, Maria, Hafiza Zoha Noor, Muhammad Arslan Aslam, Mazhar Ali, Talha, Dr Sumaira Abbas

Abstract-The Himalayas are referred to as the “Third Pole” and contain the largest concentration of glaciers outside of the Arctic and Antarctic. The glaciers are, therefore, an important source of water for these river systems including the Indus, Ganga, and Brahmaputra that support nearly 15% of India’s population. It has been observed during recent decades that the glaciers have retreated, and snow cover reduced significantly because of climate change, and this has resulted in the formation of lakes. In this study, the focus is on Uttarakhand in the Central Himalayas, assessing the relationship between climate change, snow cover, glacial lakes, and associated geo-hazards. There is a focus on key climate trends, snow cover dynamics, glacial lake expansion, and geo-hazards such as Glacier Lake Outburst Floods (GLOFs) using long-term satellite imagery, numerical models, and ground-based observations. The findings show that high-altitude areas are warming at 0.6 °C/decade, with declining rainfall trends, widespread reductions in the extent of snow cover, and deposition of potentially hazardous glacial lakes. Effective mitigation, long-term monitoring, and community-based approaches are necessary to minimize the risks to the environment and socio-economic sectors.

Unravelling the Dark Side: The Negative Impact of Social Media on Mental Health and Society
Authors:-Ishwarya B

Abstract-The Social media’s ubiquitous impact on contemporary life has unquestionably changed communication, connection, and information sharing, but underlying its glitzy exterior is a more sinister reality with significant ramifications for both societal well-being and personal mental well- being. This abstract examines how social media negatively impacts mental health, emphasizing problems like body dysmorphia, loneliness, anxiety, and depression that have become more prevalent as virtual platforms have grown in popularity. Feelings of inadequacy and loneliness are made worse by the continual push to produce idealized versions of oneself and the addictive nature of social media. Emotional well-being is further undermined by the culture of comparison, cyberbullying, and reality distortion promoted by algorithm- driven material. At the societal level, an over dependence on social media has led to a disintegration of interpersonal relationships, promoting divisiveness, echo chambers, and the dissemination of false information. Two of the main signs of this digital age are the decline in in-person interactions and people’s shortening attention spans. This abstract examines how social media is eroding the basis of genuine relationships and shared societal ideals while also enabling virtual interactions.

A Literature Survey on High Energy Physics
Authors:-Sanskriti Chanda, Dr. Subhash Chanda

Abstract-Research in modern science based on primordial particles those constitute the observable world. It is highly interesting to cover the vast field of materialistic world which lead to the scientists to investigate the building stone of the object that occurs naturally. Without proper knowledge of constituents of observable objects research on high energy physics will never yield satisfactory result. The aim of this paper is to intricate the right direction of investigation.

Implementation of NN Based MPPT Technic for Solar PV Module
Authors:-Associate Professor Mr. M. Raja Shekar, P. Narendar Reddy, K. Pramodh, Ch. Manoj Kumar

Abstract-Efficient power extraction from photovoltaic (PV) systems is critical in optimizing energy utilization for renewable applications. This project explores a Neural Network (NN)-based MPPT technique implemented in MATLAB/Simulink, designed to dynamically predict and track the maximum power point (MPP) of a solar PV system with battery storage. The NN-based MPPT is trained on a dataset encompassing various environmental conditions (irradiance, temperature, PV voltage, and current) to accurately predict the optimal duty cycle for the DC- DC converter, thereby maximizing power transfer from the PV system to the battery. A Simulink model incorporating a PV array, DC-DC converter, and the NN-based MPPT controller was developed, allowing for simulation and performance assessment under diverse scenarios. This work underscores the viability of intelligent MPPT solutions for advancing solar energy efficiency and sustainability.

Impact of Plastic on Environment
Authors:-Assistance Professor Naseem Husain, Assistance Professor Aqsa Almas Sheikh

Abstract-A serious environmental issue that has an impact on ecosystems, wildlife, and human health is plastic pollution. Since plastic production has increased to almost 368 million tons per year, plastics are found in both terrestrial and marine habitats. Although plastic materials are useful for many purposes, their durability also adds to their persistence in nature, which frequently harms the environment. Millions of marine species consume or become entangled in plastic waste, which can cause harm or even death, making marine life especially vulnerable. Microplastics, which are tiny plastic particles smaller than five millimeters, have also gotten into food chains, affected biodiversity, and endangered human health by contaminating water and shellfish. Plastic pollution has major socioeconomic repercussions since it impacts public health, tourism, and fisheries. Animal health and biodiversity are severely harmed by plastic pollution, which also poses a serious threat to ecosystems and animals. Ingestion, entanglement, or accumulation in food chains are all possible outcomes of the millions of tons of plastic waste that enter rivers, oceans, and terrestrial habitats every year. Fish, marine mammals, seabirds, and other marine species are especially at risk. Malnutrition, internal damage, and obstructions can result from consuming plastic waste, which significantly lowers survival rates. Several governmental efforts are being implemented to reduce plastic production and consumption, encourage recycling and biodegradable alternatives, and increase public knowledge of sustainable practices to reduce plastic pollution. To properly solve this complex issue, however, a comprehensive strategy including individuals, businesses, and governments is required.

DOI: 10.61137/ijsret.vol.11.issue1.146

Leveraging Data Science for Predictive Insights in Healthcare
Authors:-Maheshwar Pratap Roy, Associate Professor Dr S R Raja

Abstract-AThe rapid advancements in data science have revolutionized the healthcare industry, offering tools to enhance decision-making and optimize patient care. This paper focuses on the application of predictive analytics and machine learning models in healthcare, demonstrating how these technologies can forecast outcomes, identify patterns in patient data, and improve operational efficiency. By leveraging large-scale patient datasets, this research aligns with ethical practices and sustainability goals, ensuring equitable and impactful healthcare solutions. The results underscore the potential of data science in transforming healthcare delivery and promoting evidence-based decision-making.

Performance Analysis of Hybrid Solar Module and Wind Turbine Using Matlab
Authors:-Assistant Professor Ms. J. Malavika, Racharla Sri Harshini, Pinninti Sai Charan Reddy, Kandukuri Nithin

Abstract-The most popular renewable energy technology is Hybrid Power System consisting of wind and solar energy sources because the system is reliable and complimentary in nature. Wind / PV Hybrid system is commonly used in Distributed Generation (DG). This project proposes a new solution for improved voltage stability with quality power output. In this system voltage output from Wind Energy Conversion System(WECS) and Photo Voltaic Panels are given to separate DC-DC converters are independently controlled and connected to a common DC bus and from there it is inverted. In the proposed controller the voltage stability is obtained with a PI controller. The implementation of the proposed method is done by using MATLAB Simulink platform. The performance of the suggested coordinate control system is analyzed by comparing the computer simulation results with and with out using controllers and it shows that the proposed system is more efficient.

Simulation of Propulsion and Performance Analysis of Wap-7
Authors:-Assistant Professor Mr. D.Ramesh, D.Sai Kiran, T.S.Dinesh Karthik, E.Niharika

Abstract-This paper presents a comprehensive simulation and performance analysis of the WAP-7 electric locomotive, a cornerstone of Indian Railways’ passenger traffic. The WAP-7, with its robust design and advanced propulsion system, has been operational since its introduction in 2000, demonstrating remarkable versatility and efficiency in hauling heavy passenger trains. The WAP-7 electric locomotive has been the workhorse of Indian Railways’ passenger fleet for over two decades, with its robust design and propulsion system Utilizing MATLAB for simulation, we modeled the locomotive’s propulsion dynamics by incorporating critical parameters such as thrust, weight, drag coefficient, and braking forces.This also examines the evolution of the WAP-7’s propulsion system, the simulation provides insights into the impact of track conditions on WAP-7 performance.

Identification and Elimination of Hazards in Steel Industries by Hierarchy Control Method
Authors:-A. Tharanya, B. Balan

Abstract-The aim of this study is to Identification of hazards in various machineries in the steel industry and solution based on the hierarchy of controls. This will minimize the occupational health hazards of the workers. Hazard Identification and Risk Assessment (HIRA) is a process that involves examining what could cause harm to people in black bar to bright bar process workplace and evaluating whether the necessary precautions are in place. The goal is to ensure that no one becomes ill or gets hurt. Based on the risk assessment tool will Identify hazards, assess exposure, evaluate potential risks, and take precautions and to ensure that your workplace is safe and then decide what type of control measures shall be taken to control the employees are protected from harm by using the risk matrix to assist with the process.

DOI: 10.61137/ijsret.vol.11.issue1.147

A Study on the Effectiveness of Teaching Methods During Covid 19 in Secondary Schools of Lucknow
Authors:-Ravi Srivastava

Abstract-The COVID-19 pandemic dramatically accelerated the adoption of online learning methods in education. This abstract explores the various teaching methods employed during this period, including synchronous and asynchronous learning, flipped classrooms, and project-based learning. It also discusses the challenges and opportunities presented by these methods, such as the digital divide, student engagement, and assessment strategies. The abstract concludes by emphasizing the need for ongoing research and innovation in online teaching methods to ensure effective and equitable education for all students.

Conversational AI Chat Bot
Authors:-Mohamed Riyaz, Associate Professor Dr S R Raja

Abstract-This project aims to design and develop a conversational AI chat bot that can engage in basic conversations with users, providing helpful responses to frequently asked questions. Leveraging natural language processing (NLP) and machine learning algorithms, the chat bot will be integrated with a messaging platform to demonstrate its capabilities. The project’s objective is to create a functional chat bot that can understand user inputs, recognize intents, and generate appropriate responses.

Automated Canal Waste Collection System (ACWaCoS) for Canal Maintenance
Authors:-Nurina A. Lakian, Judy Norraine Banzon, John Arvin M. Bodlong, Gaezyll Lei C. Quong, George I. Salvador

Abstract-The study aimed to develop a prototype of an automated canal waste collection system. Specifically, it sought to determine the ultrasonic sensor’s capability to detect waste, servo motor’s spin to collect waste, system’s ability to update the serial monitor when the bin is full, average amount of time taken to complete a waste collection cycle, and average amount of waste detected and collected by the system for a certain period. The prototype used Arduino Uno R3, HC-SR04 ultrasonic sensors, MG995 servo motor, SG90 servo motor, jumper wires, breadboard, and a powerbank. The data were analyzed using frequency distribution, percentage, mean and Mann Whitney U-test. The results showed that the automated canal waste collection system prototype was 100% successful across three indicators; the prototype takes an average time of 14.6 seconds to complete a waste collection cycle; it detects an average amount of 7.50 wastes and collects an average amount of 7.20 wastes.  The amount of waste detected and collected does not significantly differ. This means that the prototype can collect a significant amount’ of detected wastes in the canal without human intervention. With these, the automated canal waste collection system has the potential in its functionality and consistency. Additionally, the device needs an IoT-based notification system for real-time monitoring.

Advancements in Plasma Physics for Space Propulsion [Core Reserach in Plasma Physics]
Authors:-Vishwanath. Barve, Pranav.D. Awate, Divyanshu.S. Yadav

Abstract-Plasma Physics, the study of charged particles and fluids interacting with electromagnetic fields, is increasingly gaining interest in the field of space propulsion. Traditional chemical rockets have limitations that restrict long-distance space travel, whereas plasma-based propulsion system promise higher efficiency and greater fuel academy. This paper explores the principles behind the plasma propulsion and examines the most recent advancement that bring this futuristic technology closer to practical applications. Additionally, it investigates the ongoing challenges, such as power requirements, fuel sources, and magnetic confinement, and how overcoming these challenges could open new frontiers for deep-space explorations.

DOI: 10.61137/ijsret.vol.11.issue1.148

Design of Battery Charging from Solar Using Buck Converters with MPPT Algorithm
Authors:-Professor Dr. S. Mani Kuchibhatla, K. Priyanka, V. Kavitha, M. Adithya

Abstract-Photovoltaic power generation system implements an effective utilization of solar energy, but has very low conversion efficiency. The major problem in solar photovoltaic system is to maintain the DC output power from the panel as constant. Irradiation and temperature are the two factors, which will change the output power of the panel. In this article it is shown that for charging lead acid batteries from solar panel, MPPT can be achieved by perturb and observe algorithm. MPPT is used in photovoltaic systems to regulate the photovoltaic array output. A buck converter is utilized as a DC-DC converter for the charge controller. It is used to match the impedance of solar panel and battery to deliver maximum power. Voltage and current from the solar panel is sensed and duty cycle of gating signal is varied accordingly by the algorithm to attain maximum power transfer. It is obtained by using MATLAB Simulink Model.

Smart Rides
Authors:-Anjali Dhunde, Srushti Anturkar, Vaishnavi Bhelkar, Vaishnavi Gudadhe

Abstract-The Smart rides is robotic car. The rise of smart transportation solutions is revolutionizing urban mobility, and the concept of “Smart Rides” is at the forefront of this transformation. Smart Rides integrate emerging technologies such as the Internet of Things (IoT), artificial intelligence (AI), and machine learning (ML) with transportation systems to provide efficient, safe, and sustainable travel experiences. This review paper explores the development, implementation, and challenges of Smart Rides, focusing on key components like real-time data processing, autonomous vehicles, ride-sharing services, and predictive analytics. We analyse various smart transportation initiatives across global cities, highlighting their impact on reducing congestion, enhancing energy efficiency, and improving accessibility for diverse populations. The paper also examines the role of smart infrastructure, including sensors and communication networks, in enabling seamless mobility. Additionally, the environmental and social implications of Smart Rides are discussed, with an emphasis on sustainability and equity. Challenges related to data privacy, cybersecurity, and regulatory frameworks are also addressed, proposing solutions for overcoming these barriers. By providing a comprehensive overview of the current state of Smart Rides and future trends, this review aims to guide policymakers, engineers, and researchers in shaping the next generation of intelligent transportation systems.

DOI: 10.61137/ijsret.vol.11.issue1.149

Implementation of AC to DC Converter in Wind Power Generation Using Matlab
Authors:-Professor Dr.S Mani.Kuchibhatla, A.Sony, B. Nishith, B. Ruthwik

Abstract-Wind power generation has emerged as a crucial component of renewable energy systems, offering a sustainable and environmentally friendly alternative to fossil fuels. However, the integration of wind energy into the grid requires efficient power conversion mechanisms due to the variable nature of wind speed and the need for compatibility with existing infrastructure. A typical wind power system involves the conversion of mechanical energy into alternating current (AC) power using a generator, which is driven by wind turbines. This project focuses on the design and implementation of an AC to DC converter in wind power generation systems. The AC to DC converter plays a vital role in transforming the variable frequency AC output of wind turbines into a stable DC voltage. In this process, the generated AC power is first converted into direct current (DC) using power electronics, which enables efficient integration with batteries or facilitates smooth conversion. This conversion process is essential for stabilizing power output, minimizing losses, and ensuring the efficient transmission of energy over long distances. Advanced AC to DC converters and control systems enhance the reliability, efficiency, and scalability of wind power systems, making them a vital component in modern renewable energy infrastructures. This is implemented in the MATLAB/SIMULINLK.

Development of Center Pivot Irrigation Systems to Revolutionized Modern Agriculture Irrigation
Authors:-M.Tech. Scholar Suchita Gangele, Associate Professor Dr. Vivek Soni

Abstract-A well-designed main line is the backbone of any center pivot irrigation system. Ensuring it’s optimally sized and configured helps in achieving uniform water distribution, preventing pressure variations that could affect sprinkler performance. By using analytical methods such as hydraulic modeling, and optimization techniques, one can fine-tune pipe sizes, pump capacities, and valve configurations to ensure maximum efficiency. As you mentioned, AI-driven modeling could play a crucial role in real-time monitoring, helping predict system behavior under varying conditions. With real-time data, adjustments could be made on-the-fly to optimize water usage and reduce waste, even accounting for changing weather patterns or soil moisture levels.

Mathematical Modeling of Population Growth: A Comparative Study of Exponential Model
Authors:-Sharif Shabir

Abstract-Population growth is a multifaceted and evolving issue that has captivated the attention of demographers, ecologists, and policymakers for many years. The swift increase in the global population carries significant consequences for resource management, environmental sustainability, and socioeconomic development. This study seeks to enhance the current body of knowledge on population growth by creating and comparing mathematical models that reflect the fundamental dynamics of this phenomenon. In particular, this research examines the exponential and logistic models of population growth, which are commonly utilized in the fields of demography and ecology. The exponential model posits that population growth is influenced by a constant birth rate and death rate, whereas the logistic model considers the environmental carrying capacity and the effects of resource constraints on population growth. Employing a mix of analytical and numerical techniques, this study evaluates the advantages and drawbacks of each model in forecasting population growth across various scenarios. The findings underscore the necessity of accounting for environmental carrying capacity and resource limitations when modeling population growth, and illustrate how mathematical models can guide policy and decision making in areas such as demography, ecology, and resource management. The implications of this study are significant for our comprehension of population growth and its effects on both the environment and society. The outcomes can be leveraged to create more precise and realistic population models, which can aid in policy and decision-making at local, national, and global scales. Additionally, this research showcases the potential of mathematical modeling to deepen our understanding of intricate social and environmental issues, emphasizing the need for further exploration in this area.

DOI: 10.61137/ijsret.vol.11.issue1.150

Design of Single Phase Grid Connected Solar PV Inverter Using MATLAB
Authors:-Assistant Professor Ms. A. Sunantha, M. Ashwini, K. Geetha, B. Ajay

Abstract-This project presents the design, simulation, and performance analysis of a single-phase grid-connected solar photovoltaic (PV) inverter using MATLAB /SIMULINK. The primary objective is to develop an efficient and reliable inverter system that ensures maximum power extraction from the solar PV array and seamless integration with the grid. The main elements of the PV control structure are: a maximum power point tracker (MPPT) algorithm using the incremental conductance method: a synchronization method using the phase-locked-loop (PLL), based on delay: the input power control using the DC voltage controller and power feed-forward and the grid current controller implemented in two different ways, using the classical proportional integral (PI) and the novel proportional resonant (PR) controllers. The control strategy was tested experimentally on 2kW PV inverter.

An Investigation of Cloud Computing Security Concerns
Authors:-Research Scholar Ms. Anshul, Professor & HOD Dr.Mukesh Singla

Abstract-Distributed computing is a flexible, savvy, and proven conveyance stage for conveying corporate or purchaser IT administrations by means of the Internet. Distributed computing, then again, represents an extra danger on the grounds that basic administrations are regularly moved to an outsider, making information security and protection more hard to ensure, help with information and administration accessibility, just as show consistence. Distributed computing utilizes an assortment of advancements (SOA, virtualization, Web 2.0), and it acquires their security concerns, which we inspect here by distinguishing the most widely recognized shortcomings in these frameworks and among the most regularly referred to risks in the Cloud Computing writing and its environmental factors, just as to identify and associate shortcomings and dangers to possible cures.

Automated Dog Feeder System Using Arduino Uno for Efficient and Timely Feeding
Authors:-James Dalisay Baranggan, Haire Ato, Isaiah Smile B. Halik, Jennie Jorimocha, John Renwel Mauro, Rexel Gold D. Emuy, Judie L. Velasco

Abstract-This project aims to develop a prototype that could potentially assist dog owners in managing feeding schedules more efficiently and inclusively. The functionality of the prototype was assessed based on the aptness of the object detection using an ultrasonic sensor, the accuracy of its real-time clock, the precision of its servo motor for kibble dispensing, the audibility of its voice recorder, the visibility of the neon signage for aging dogs, the braille integration for visually impaired owners, and its overall system reliability. The automated dog feeder was built using an Arduino Uno R3, an HC-SR04 ultrasonic sensor, RTC Module DS3231, PCB matrix, jumper wires, SG90 servo motor, LCD I2C screen, 12V AC adapter, MP3 player, speaker, acrylic, PVC elbow, and some recycled materials such as wood and PVC pipe. The data analysis was based on user feedback and system performance parameters. The results indicated that the prototype accurately dispensed kibble upon detection of the dog’s presence, tracked and scheduled feeding times, and got favorable feedback on its overall functionality, usability, and inclusivity. The given results imply that the automated dog feeder has strong potential to assist diverse dog owners in maintaining regular feeding schedules, making it a more practical solution for busy homes.

DOI: 10.61137/ijsret.vol.11.issue1.151

Online Payment Fraud Detection Using Python
Authors:-Manya Rajvaidya, Hresth Narayan Mishra, Professor Shilpa Tripathi

Abstract-Online payment fraud detection is a critical area of research and development in the realm of financial security. With the rise of e-commerce and digital transactions, ensuring the integrity and safety of online payments has become paramount, This abstract explores various methodologies and techniques employed in the detection and prevention of fraud in online payment systems. The detection of online payment fraud involves the use of advanced machine learning algorithms, anomaly detection techniques, and behavioral analytics. These methods analyze transactional data in real-time to identify suspicious patterns or anomalies that deviate from normal user behavior or transaction patterns. Additionally, the integration of artificial intelligence (Al) and deep learning models has enhanced the accuracy and efficiency of fraud detection systems by enabling them to adapt and learn from new fraud patterns continuously. Moreover, the abstract discusses the challenges associated with online payment fraud detection, including the balance between security and user experience, the need for real-time decision-making, and the evolving nature of fraudulent tactics employed by cybercriminals. Furthermore, it highlights the importance of collaboration between financial institutions, payment service providers, and cybersecurity experts in combating fraud effectively. In conclusion, effective online payment fraud detection is crucial for maintaining consumer trust, safeguarding financial transactions, and mitigating potential financial losses for businesses. Continued advancements in technology and methodologies will play a pivotal role in strengthening fraud prevention strategies and adapting to emerging threats in the digital payment landscape.

DOI: 10.61137/ijsret.vol.11.issue1.152

The Biomatrix Beat Sensor: Advancement in Mr Cardiac Imaging
Authors:-Assistant Professor Mr. Bibin Joseph

Abstract-The Biomatrix Beat Sensor, developed by Siemens Healthineers, represents a significant leap forward in cardiac and respiratory MRI. By eliminating the need for traditional electrocardiogram (ECG) electrodes and respiratory belts, this contactless technology leverages electromagnetic navigation (EMN) and the Pilot Tone (PT) concept to provide real-time, artifact-free synchronization of cardiac and respiratory motion. This review explores the limitations of conventional methods, the working principles of the Biomatrix Beat Sensor, its clinical applications, and its potential to transform patient care in MRI.

DOI: 10.61137/ijsret.vol.11.issue1.153

Vivaldi Antenna Design for Cognitive Radio Communication
Authors:-Assistant Professor Dr.K.Jayanthi, B.Loganayaki

Abstract-This project presents a versatile antenna design suitable for various wireless communication platforms, including cognitive radio (CR) communication, 5G, and Wireless Local Area Network (WLAN) applications. A two-port Vivaldi antenna is designed using an FR4 substrate material with a dielectric constant of 4.4 and dimensions of 45.12 mm × 57.94 mm × 1.6 mm. This design is suitable for communication within a cognitive radio architecture. The antenna operates across multiple frequency bands, including the n79 band (4.4 GHz to 5 GHz) for 5G networks via port 1, and the 2.4 GHz band for Wi-Fi and Bluetooth communication via port 2. It achieves a return loss below -10 dB and a VSWR below 1.5 across the n79 band for 5G communication, and the 2.4 GHz band for WLAN applications.

DOI: 10.61137/ijsret.vol.11.issue1.154

Strengthening Cybersecurity in Uganda’s Electoral Commission through Multi-Factor Authentication and Single Sign-on Solutions across Organizational Applications
Authors:-Carolyn Nasimolo, Associate Professor Dr.S.R.Raja

Abstract-The increasing reliance on digital platforms for electoral processes in Uganda has brought to light significant cybersecurity issues that the Uganda Electoral Commission faces and this has made it imperative for the UEC to prioritize the strengthening of its cybersecurity. The Uganda Electoral Commission relies solely on traditional password-based authentication but hacking technologies have become more advanced and diversified. As a result, for security and authentication organizations are unable to rely on user ID and password-based authentication. (Hong, 2011). This single- factor authentication has been found to be vulnerable to attacks like malware, brute force, dictionary attacks, shoulder surfing, replay and phishing attacks etc. Much as passwords can easily be memorized and users at no cost are able to use them in their daily lives, these can be forgotten especially if the users have to log into multiple systems. (Mohammadreza Hazhirpasand Barkadehi, 2018). The UEC users log in to each of the systems independently which could lead to password fatigue. Cyberattacks can lead to unauthorized access to sensitive data, and data breaches and can therefore undermine the entire electoral process if the integrity of electoral data is compromised. This can lead to public distrust which could pose a threat to national stability. Therefore, by integrating MFA the UEC protects its sensitive electoral data and ensure secure access to its applications. Single sign-on is the ability for a user to authenticate once and access other protected resources where he has permissionwithout logging re- authentication. This system not only secures sensitive data but streamlines user experience through Single Sign-on (SSO) enabling users to log on once and gain access to multiple applications seamlessly.

The Role of AI in Enhancing Safety Standards in Autonomous Shipping: A Review of Collision Avoidance Systems
Authors:-Mohammad Anas Ahmed Rizwan, Ayaan Ali Ahmed Siddiqui

Abstract-The rise of autonomous ships allows for great opportunities in the search for greater efficiency, cost-effectiveness, and environmental sustainability in maritime operations. Safety, though, has always been a major concern, particularly with the risks of collision within increasingly congested lanes. This paper reviews the literature on how artificial intelligence is being used to transform safety standards, including, in particular, autonomous shipping, for a collision avoidance system. We examined how AI-driven methodologies such as machine learning, path-planning algorithms, predictive analytics, and decision-support systems should be integrated to advance minimal human intervention in the development of navigational decision-making processes. Sensor technologies such as radar, LiDAR, sonar, and satellite imagery are analysed for situational awareness, real-time risk assessment, and dynamic adaptation to the maritime environment. The paper discusses the use of sensor technologies, for example, radar, LiDAR, sonar, and satellite imagery, in support of situational awareness, real-time risk assessment, and dynamic adaptation to the maritime environment. Further, it shows a number of regulatory challenges, ethical considerations, and urgent international standardization issues that the development and integration of AI technologies may have for maritime industries.

DOI: 10.61137/ijsret.vol.11.issue1.155

Fuzzy Logsic Controlled System for Utilization of Renewable Energy Sources of Industry and Home Appliances
Authors:-Dr. A. R. Wadekar, Miss. Rutuja Bharat Lomate

Abstract-The per capita of power in India is insufficient compared to other developed countries in the world. Hence, the only way is the optimal utilization of available energy sources but the difference between production and consumption of electrical energy, during summer is very high, due to large utilization of cooling machines like Air conditioner, Air coolers in such case a software industry, like BPO call center or any office with large server and many systems need to have a 24 hours working Air conditioner. This leads to huge power consumption. Conservative measures need to be initiated and implement to decrease this gap to restrain this situation the concert of DSM has begun in power system planning and management. Therefore this paper included Fuzzy logic applied to Ac which results to calculate the actual hourly turn off period and reduction in energy consumption. By the optimal consumption of electrical power results increase saving by reducing the electricity bill and reduce the over load on live grid during peak hours and also calculate the cost of savings and playback period for the return of investment. In this paper, solar energy is used to run air conditioner. The cost of saving and playback period is calculated by considering only photo voltaic (PV) and photo voltaic with fuzzy controller, Results proved that usage of PV with fuzzy controller has better annual savings and lower pay back period compared with only considering PV.

DOI: 10.61137/ijsret.vol.11.issue1.156

Preparation and Characterization of Al-Cu Composite by Using Stir Casting Technique
Authors:-Assistant Professor K. K. Kishore

Abstract-Composite materials have emerged as a critical area of research and development, rapidly gaining importance as structural materials. Among polymer applications, composite materials are poised for significant advancements. Aluminum matrix composites (AMCs) are particularly favored in automotive and aerospace industries due to their exceptional mechanical properties, such as a high strength-to-weight ratio, superior wear resistance, increased stiffness, enhanced fatigue resistance, controlled thermal expansion, and stability at elevated temperatures. Stir casting is widely recognized as an efficient and cost-effective method for AMC fabrication. This study investigates the mechanical behavior of composites made from pure aluminum reinforced with copper, fabricated using the stir casting method. The composites were produced with reinforcement levels of 0%, 2%, 4%, and 6%. Results indicate that the inclusion of copper particles significantly enhanced the hardness, tensile strength, and wear resistance of the composites, though an increase in copper content resulted in decreased density. These findings highlight the potential of copper as a reinforcement material for aluminum-based metal matrix composites, offering valuable insights for diverse engineering applications.

DOI: 10.61137/ijsret.vol.11.issue1.157

Arduino-Based Rainfall and Flood Monitoring System With Real-Time Alert Notification
Authors:-Janreign G. Zamarro, Kris Martin C. Paquibot, Cristian John L. Espares, John Rey Maltizo, Judie L. Velasco

Abstract-The objective of this research is to develop an Arduino-based rainfall and flood monitoring system with real-time alert notification to address the challenges faced by the affected residents of the outlying areas of the Davao region. It focuses on using Arduino technology for the areas affected by floods that can be easily monitored with an SMS alert notification and a buzzer system. This research employed an experimental approach, starting with the design and assembly of the prototype, followed by sensor accuracy testing and data collection over multiple trials. The findings revealed that the prototype accurately measured water level according to three categories: caution, warning, and danger; this category also achieves a 100% success rate in sending SMS alerts and providing timely warnings to the buzzer during moderate and critical rainfall events. The data logged on a microSD card confirmed the system’s consistent performance in tracking environmental conditions. In conclusion, the prototype reliably shows a rainfall and flood monitoring solution that ensures real-time alerts to the affected communities, significantly contributing to disaster preparedness and response of the local communities. Some of the suggestions for future upgrades are further testing under a variety of conditions, integrating the system with IoT platforms to manage data better, programs across the community to understand and develop the most effective response mechanisms, and system expansion for a greater spatial coverage by having multiple sensors along with a monitoring station network.

“Aum: The Primordial Sound and its Resonance in Science, Spirituality, and Artificial Intelligence and Data Science”
Authors:-Associate Professor Dr. Suneel Pappala, Professor Dr K Venkata Naganjaneyulu

Abstract-The sacred syllable “Aum” (or “Om”) holds profound significance in Hinduism, Buddhism, Jainism, and other spiritual traditions. It is revered as the primordial sound of the universe, symbolizing the essence of ultimate reality, consciousness, and the interconnectedness of all existence. Explores the multifaceted dimensions of Aum, bridging its spiritual symbolism with modern scientific and technological paradigms, particularly in the realm of Artificial Intelligence (AI). By examining Aum’s representation of creation, preservation, and destruction, as well as its vibrational resonance with Earth’s natural frequencies and cosmic phenomena, Highlights the potential for harmonizing AI development with ethical principles, sustainability, and human well-being. Furthermore, it delves into the applications of Aum-inspired concepts in data science, neural networks, quantum computing, and AI-driven meditation tools, offering a holistic perspective on the convergence of ancient wisdom and cutting-edge technology.

DOI: 10.61137/ijsret.vol.11.issue1.158

Optimizing Recycling Stream Sorting Systems Using Machine Learning to Minimize Contamination
Authors:-Assistant Professor Dr. Pankaj Malik, Yashee Verma, Yashi Harne, Yuvraj Bhatnagar, Shreya Joshi

Abstract-The efficiency of recycling systems is crucial for promoting sustainability and reducing environmental impact. However, contamination in recycling streams remains a significant challenge, often leading to decreased recycling effectiveness and increased operational costs. This paper investigates the potential of machine learning (ML) to optimize sorting systems in recycling plants, aiming to minimize contamination and improve material recovery rates. We explore the application of various ML algorithms, including Convolutional Neural Networks (CNNs), Support Vector Machines (SVM), and Random Forests, for automating the detection and classification of contaminants in waste streams. By leveraging sensor data, image recognition, and real-time decision-making, our approach enhances sorting accuracy, reduces human error, and supports the efficient separation of recyclable materials. Experimental results from simulations and real-world case studies demonstrate that ML-driven sorting systems can achieve higher contamination reduction and sorting efficiency compared to traditional methods. This study highlights the promising role of machine learning in transforming recycling processes and proposes future directions for integrating AI technologies in waste management to create more sustainable and effective recycling solutions.

DOI: 10.61137/ijsret.vol.11.issue1.159

Hypergraph Neural Networks for Robust Fingerprint Matching in Forensic Applications
Authors:-Assistant Professor Dr. Pankaj Malik, Lakshita Singh, Yashi Sethi, Dixika Verma, Dev Soni

Abstract-Fingerprint matching is a crucial task in forensic science, where the accurate and reliable identification of individuals is essential for criminal investigations. Traditional fingerprint matching algorithms often struggle with challenges such as occlusion, distortion, and partial prints. In this study, we propose a novel approach that leverages Hypergraph Neural Networks (HGNNs) to enhance the robustness and accuracy of fingerprint matching in forensic applications. By modeling fingerprint features as hypergraphs, we capture higher-order relationships between minutiae points and their spatial configurations, enabling more effective matching despite partial or degraded fingerprints. The HGNN framework integrates both local and global feature information, improving the system’s ability to recognize subtle and complex patterns in fingerprint data. Extensive experiments on benchmark fingerprint datasets demonstrate that our approach outperforms conventional methods in terms of matching accuracy and robustness to noise. The proposed HGNN-based model provides a promising solution for advancing forensic fingerprint identification systems, offering improved performance under challenging real-world conditions.

DOI: 10.61137/ijsret.vol.11.issue1.160

IoT and Computer Vision for Efficient Parking Management in Urban Areas: A Comprehensive Review
Authors:-Assistant Professor Mrs. Shikha Pachouly, Karan Solanki, Eeshaan Sawant, Aarya Rokade

Abstract-Urbanization and population growth have led to an exponential increase in vehicles, exacerbating parking-related challenges. Efficient parking management systems have become imperative to mitigate congestion, reduce fuel consumption, and minimize environmental impact. This paper reviews the integration of Internet of Things (IoT) technologies, computer vision, and Bluetooth Low Energy (BLE)-based indoor positioning systems for developing an efficient parking management system in urban areas. The proposed system is divided into three core modules: prediction of parking availability, real-time parking detection, and indoor navigation to guide users. This review evaluates existing approaches, highlights technological advancements, and discusses potential challenges in developing a proof of concept for the Indian context, emphasizing the cost- efficiency of the system.

DOI: 10.61137/ijsret.vol.11.issue1.161

Cyclooxygenases in Inflammatory Bowel Disease
Authors:-K. Anil Kumar

Abstract-Inflammatory Bowel Disease (IBD) is a long-term condition that presents as Ulcerative Colitis (UC), or Crohn’s Disease (CD) based on its manifestations. It is characterized by inflammation in the small intestine and colon, impacting millions of individuals globally. The development of IBD is influenced by genetic, environmental, and immunological factors. Various pro-inflammatory agents such as TNF-α, IL-1β, IL-6, IL-12, TGF-β, INF-γ, COX-2, and increased reactive oxygen species contribute to significant intestinal damage. Typical symptoms of IBD include fever, abdominal pain, vomiting, diarrhea, weight loss, blood in the stool, and an elevated risk of colon cancer. Changes in colonic motility linked to IBD can worsen discomfort and diarrhea. Prostaglandins, particularly elevated in IBD patients, may modulate these alterations. The enzyme Cyclooxygenase-2, responsible for producing prostaglandins, is targeted in IBD treatment. The role of PGE2 in the pathogenesis of IBD is intricate; while it can have anti-inflammatory effects by inhibiting pro-inflammatory cytokines, it can also act pro-inflammatory in IBD. Dysregulation of PGE2 production in IBD can lead to excess levels in inflamed gut tissue, perpetuating chronic inflammation by attracting immune cells, increasing blood vessel permeability, and causing tissue damage. The context-dependent role of PGE2 in IBD warrants further research for a comprehensive understanding. Modulating PGE2 levels or its signaling pathways may provide potential therapeutic options for managing IBD. This review specifically examines the involvement of Cyclooxygenases and coxibs in treating IBD.

DOI: 10.61137/ijsret.vol.11.issue1.162

Review on Accuracy Enhancement of Flower Classification Using Machine Learning
Authors:-Anshul Payasi, Assistant Professor Srashti Thakur

Abstract-The rapid evolution of Artificial Intelligence (AI) and Machine Learning (ML) technologies has led to the development of increasingly sophisticated algorithms and models. In particular, these advancements have been pivotal in the domain of flower classification and recognition, aiming to identify and categorize the vast array of species of flowers present on our planet. This review delves into the convergence of AI and ML within the realm of flower classification, a domain that greatly benefits from the advancements in computer vision. As a sub-field of AI, computer vision plays a crucial role in extracting intricate features from floral specimens and subsequently utilizing classification algorithms to accurately label and categorize them. This literature review offers a meticulous and comprehensive exploration of the existing body of knowledge, aiming to elucidate the various methodologies and approaches employed in the taxonomic categorization of floral specimens. It encompasses an extensive survey of scholarly works, research papers, and innovative techniques that contribute to the advancement of flower identification systems. The review addresses diverse strategies, including but not limited to deep learning architectures, neural networks, feature extraction methodologies, and optimization techniques used in the classification of flowers. By synthesizing and critically analyzing the existing literature, this review aims to provide insights into the state-of-the-art techniques and emerging trends in the field of flower classification and recognition using AI and ML. This paper holds several benefits to the society such as: agriculture, environment conservation, education and tourism.

Parental Involvement and Academic Performance of Bachelor of Technology and Livelihood Education Students of the University of Science and Technology of Southern Philippines
Authors:-Ruby Pearl A. Maghanoy, Abegail B. Gaid, Mhea A. Galera, Jomar P. Flores, Jorie May Elevado

Abstract-Parental involvement is crucial in the cognitive and socioemotional development of student, and during the pandemic, parents played a vital role in shaping their student’s educational success. This study examines the relationship between parental involvement and the academic performance of Bachelor of Technology and Livelihood Education (BTLED) students at the University of Science and Technology of Southern Philippines. The study aims to determine the level of parental involvement and its correlation with the academic performance (GPA) of the students, specifically exploring the relationship between these two variables. A quantitative correlational research design was employed to assess how parental involvement correlates with academic performance. The study was conducted at the University of Science and Technology of Southern Philippines, Cagayan de Oro City, with a sample of 133 third year BTLED students. A two-part questionnaire was used to gather demographic data, parental involvement levels, and students’ GPA. Data were analyzed using descriptive statistics (mean, frequency, percentage) and Spearman’s rank correlation to determine the relationship between parental involvement and academic performance. The findings revealed that while parental involvement was generally high, the relationship with academic performance was weak and negative. Despite a high level of parental engagement, there was no significant correlation between involvement and GPA. The conclusion of the study indicates that while parental involvement positively influences student motivation, it did not significantly impact academic performance. Other factors, such as student self-motivation and program structure, likely play a more influential role. The study recommends that parents maintain active communication and structure in their student’s academic progress and that teachers and policymakers focus on strategies to enhance student self-motivation and independent learning.

Electronic Devices and Circuits: The Foundation of Modern Technology and Innovation
Authors:-Jayakarthi S R

Abstract-Electronic devices and circuits form the backbone of modern technological advancements, driving innovation across a multitude of industries. From consumer electronics such as smartphones and wearables to complex systems in aerospace, telecommunications, and healthcare, the applications of electronic circuits are vast and diverse. These circuits enable functionality, automation, and communication, making them an integral part of everyday life. This article explores the fundamentals of electronic devices, including key components like semiconductors, diodes, transistors, and capacitors, and delves into the operation and application of essential circuits such as rectifiers, amplifiers, and oscillators. It also covers digital electronics, providing insights into logic gates, flip-flops, microprocessors, and the interface between analog and digital systems. Furthermore, the paper examines the role of power electronics in energy management, renewable energy solutions, and industrial automation. Communication circuits, including RF systems, modulation techniques, and wireless communication, are also discussed, along with their crucial role in enabling modern-day connectivity. Advanced topics such as integrated circuits, VLSI, embedded systems, and emerging trends like IoT, AI, and quantum electronics are presented to highlight the trajectory of innovation in the field. Finally, this article concludes with a reflection on the impact of electronic devices and circuits on contemporary life and their future potential in shaping technological progress.

A Deep Learning Approach to Tomato Disease Classification Using a CNN-LSTM Hybrid Network
Authors:-Youssef Laatiri, Mohamed Ali Mahjoub

Abstract-Our work proposes a classification architecture based on deep learning techniques, particularly convolutional and recurrent neural networks, for the classification of tomato diseases from digital images. More specifically, the objective is to classify leaves infected by a disease using supervised learning on a pre-labeled image dataset from PlantVillage. One of the main challenges of using deep learning, however, is the need for a very large amount of annotated data, which is not always available. Therefore, the objective of our study is to develop a specific hybrid architecture, CNN-LSTM (Convolutional Neural Networks – Long Short-Term Memory), capable of leveraging small (frugal) and relatively imbalanced datasets. To assess the relevance of this approach, we propose to compare it with deep learning algorithms frequently described in the literature. The proposed model achieved better classification performance in terms of validation Accuracy of 94,16%,

DOI: 10.61137/ijsret.vol.11.issue1.163

Slope Stability Analysis of Landslide at Fudale, Gamo Zone, Ethiopia
Authors:-Amanuel Abera, Bisrat Gissila, Democracy Dila, Vasudeva Rao

Abstract-Landslides are significant natural disasters that pose threats to human life and the environment, particularly in hilly regions. This study contributes to the understanding of landslide dynamics by providing localized geotechnical data and stability analyses. After the landslide in 2023, this study looks into the geotechnical conditions and stability factors that led to landslides in the Fudale, Gamo Zone, Southern Ethiopia. The research paper aims to analyze the soil characteristics contributing to landslide occurrences and to assess slope stability using the Finite Element Method (FEM) through Plaxis 2D software. Ten soil samples were collected from various depths, and laboratory tests were conducted to determine their index and engineering properties. Test results indicate that the predominant soil types are fine-grained, comprising significant percentages of clay and silt, which are particularly susceptible to saturation and subsequent landslides. The analysis identified rainfall, slope geometry, soil permeability, and groundwater conditions as critical factors influencing slope stability. The computed factor of safety (FOS) for natural conditions was found to be 0.972, indicating an unstable slope.

Reviewing Mental Health in Perinatology, a FOGSI “Manyata” Initiative
Authors:-Kranti Kulkarni, Amit Phadnis

Abstract-Mental illnesses are a serious concern in India where every seventh person suffers from mental health problems[1,5]—with women more affected than men. While the burden of perinatal mental illnesses grows, India lacks exclusive policies to address it. Although postpartum depression or blues are restricted to the period of six weeks post-delivery, the roots of this condition are traced right from pre-pregnancy through the antenatal period to the period of one year post-delivery. We took up a study amongst postpartum mothers about their self-assessment of this condition, their awareness and their strategies to combat postpartum anxiety and reinforce the importance of psychological well-being as a part of routine assessment during antenatal period, fortified in the postpartum phase.

DOI: 10.61137/ijsret.vol.11.issue1.164

Design and Development of Tablet Making Machine Using IoT
Authors:-Associate Professor Dr.T.Sengolrajan, V.Dharshini, M.Swathi, A.Thabuna

Abstract-The pharmaceutical industry, precision and efficiency of tablet manufacturing are required to meet quality standards. In this project, the production process is being modernized by incorporating information and communication technology (IoT) into the production line. The machine performs auto-loading of all important steps including material feeding, compression and ejection and also IoT-powered sensors track parameters such as compression force, tablet weight, and humidity. In real-time, data is data is sent to a cloud-based server, enabling remote monitoring and predictive maintenance. This system guarantees of quality tablet, reduces downtime, and improves efficiency. The resulting machine is scalable and intuitive to use, making it suitable for both small- and large-scale production and brings Smart Manufacturing into the pharmaceutical industry.

DOI: 10.61137/ijsret.vol.11.issue1.165

Application for Agriculture Management
Authors:-Jasmine Saranya. P, Sabareeshwaran. S, Priya. A, Sairam. K, Dhivakar. M

Abstract-The worldwide economy relies vigorously upon horticulture, yet ordinary cultivating rehearses remember disadvantages like flightiness for the climate, ineffectual asset the board, and an absence of ongoing independent direction. The information driven brilliant cultivating application introduced in this examination advances farming administration by joining Enormous Information, Computerized reasoning (man-made intelligence), and Web of Things (IoT) sensors. The framework involves OpenCV for plant illness finding, TensorFlow and K-Closest Neighbors (KNN) for crop observing, and Choice Tree calculations for crop suggestion. Besides, LLaMA-fueled “Vigro Bot,” a chatbot, offers ranchers constant exhortation. The proposed procedure supports practical cultivating techniques, increments efficiency, and lessens asset squander.

DOI: 10.61137/ijsret.vol.11.issue1.166

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