Daily Archives: February 21, 2026

Authors: Rupal Bula, Dr. Vandan Tewari, Mrs Sonu Airen

Abstract: The recommendation system is a classification of machine learning [1] that uses features to help anticipate, compact and find what people are looking for an exponentially growing number of options. It is an artificial intelligence algorithm in machine learning, which uses big data to recommend more related items to consumers. These can be based on different criteria, which includes past purchase, search history, demographic information and other factors. These systems are designed to predict what a user might like based on various factors. They are extensively used in various domains including e-commerce, streaming services, social networks and content platforms. In this paper we have proposed a novel movie recommendation system that effectively addresses the cold start user problem by leveraging sequence modeling techniques [2]. Traditional recommendation systems struggle with new users due to the lack of historical interaction data. Our approach utilizes sequence modeling, specifically Long Short Term Memory (LSTM) networks, which predict user preferences based on initial interactions. By analyzing the sequence of the movie watched, our model can generate accurate recommendations even with minimal user data.

DOI: https://doi.org/10.5281/zenodo.18723361

Published by: vikaspatanker

Authors: S.Rutuja, P. Sanskruti, P. Shreya, B.Nandini, M.Priya

Abstract: The core aim of the given project is to create an Web application named MediMinder, that assists people in keeping track of their daily health routines without much effort. The application gives smart reminders to take medicine, attend the checkups and make appointments with the doctor.The machine learning (ML) will learn the habits of the user and get their schedules in order by creating personalized and voice-activated reminders that include particular date and time, and medicine information.With the application, all users can enjoy better health management and safety by receiving personalized, voice-based, and specifically set reminders with a specific date, time, and specific medicine information.

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Authors: Urgen Maharjan, Gakegni Ngaste Aperhy, Sahasra Nagaraj, Sahil Gupta, Prithi M

Abstract: The recent fast digitalization of the educational system has seen the introduction of online examination systems in universities, examining bodies and professional organizations in large numbers. Even though these platforms enhance accessibility, scalability, and operational efficiency, they present vital security and integrity issues that pose a threat t o the credibility of online tests. The significant security issues are impersonation by candidates, contract cheating, leaking of question papers, tampering with answer scripts, unauthorised collusion, malware-based attacks, network breach and massive distributed denial-of-service (DDoS) attacks. Also, the introduction of remote proctoring systems based on AI provokes serious concerns about privacy, ethical and data protection issues. The currently in place security systems like password-authenticated access and crude browser limitation are inadequate in stopping advanced methods of cheating as well as online threats. The modern studies suggest sophisticated measures such as multi-factor authentication, facial recognition-based and key-stroke dynamic-based biometric verification, end- to-end encryption algorithms to ensure safe data delivery, blockchain-based transparent record keeping, behavioral analytics, abnormality detection approaches that use AIs, and lockdown browsers. Nevertheless, such solutions tend to cover single facets of security and can pose issues of computational cost, scalability, implementation cost and user confidentiality. The paper provides the in-depth examination of security issues with online examination systems and reviews the modern research-based solutions in a systematic way. The comparative assessment framework is created to determine the efficiency, practicability and constraints of different security mechanisms. According to the results, a multi-layered security architecture will be introduced incorporating the elements of authentication, communication security, intelligent monitoring, and tamper-resistant data management to guarantee the examination integrity, confidentiality, availability, and accountability. The research concludes that a combination of defense in depth strategy is crucial towards the attainment of secure, scalable and reliable online examination ecosystems.

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Authors: Shantanu Shahaji Gaikwad, Aryan Dattatray Vibhute, Sharvari Arun Shedage, Yogita Sunil Kamble

Abstract: In today’з modern and faзt-moving world, the demand for зmart and automated зolutionз haз increaзed зignificantly, eзpecially in the field of pet care. Thiз reзearch focuзeз on the development of an automatic pet food diзpenзer deзigned to provide automated, preciзe, and intelligent feeding зolutionз to зupport pet ownerз with buзy lifeзtyleз. Many pet ownerз face challengeз in maintaining conзiзtent feeding зcheduleз due to work commitmentз, travel, and other daily reзponзibilitieз. The propoзed зyзtem aimз to зolve thiз problem by enзuring that petз receive timely and accurate mealз without conзtant human зuperviзion. Theзe зyзtemз integrate microcontrollerз, зenзorз, real-time clock moduleз, and Internet of Thingз (IoT) technologieз to enable зcheduled feeding, accurate portion control, and remote monitoring through mobile applicationз. The microcontroller actз aз the central control unit, coordinating the timing mechaniзm and diзpenзing proceзз. Senзorз are uзed to detect food levelз, monitor bowl зtatuз, and enзure proper food diзtribution. Through IoT connectivity, uзerз can acceзз the зyзtem remotely, adjuзt feeding зcheduleз, control portion зizeз, and receive real- time notificationз regarding feeding activitieз and зyзtem performance. Advanced modelз incorporate data tracking and intelligent featureз that record feeding hiзtory, analyze conзumption patternз, and provide inзightз to improve feeding accuracy and maintain optimal pet health. Some зyзtemз may alзo include voice recording featureз, camera monitoring, and emergency alertз to further enhance functionality and зecurity. Theзe зmart featureз help prevent overfeeding and underfeeding, reduce food waзtage, and зupport balanced nutrition. Overall, automatic pet food diзpenзerз enhance convenience, conзiзtency, and reliability in daily feeding routineз. They contribute зignificantly to improved animal welfare by enзuring petз receive proper nutrition at the right time. At the зame time, they reduce human effort, minimize зtreзз for pet ownerз, and repreзent an important зtep toward the integration of зmart technology in modern pet care management.Top of Form Bottom of Form

DOI: https://doi.org/10.5281/zenodo.18721934

Published by: vikaspatanker

Authors: Ms. Meenakshi, Dr. Shweta Mishra

Abstract: Regression testing plays a critical role in ensuring the continued functionality and quality of software as changes, updates, or bug fixes are implemented. Given the complexity and the growing size of modern software systems, managing large test suites efficiently is becoming increasingly difficult. This paper focuses on the importance of test case prioritization, a technique aimed at ordering test cases in a way that maximizes fault detection early while minimizing resource utilization. The study compares various theoretical models and methods of test case prioritization, including random, requirement-based, code-based, and model-based prioritization. It highlights the benefits of prioritization in improving test efficiency and the challenges associated with its implementation. Additionally, the paper reviews both traditional and advanced prioritization techniques, including risk-based prioritization and AI-driven methods, with a comparison of their effectiveness in different software development contexts. Finally, the paper discusses the challenges and limitations of current prioritization models and suggests future directions for improving prioritization techniques in regression testing.

DOI: https://doi.org/10.5281/zenodo.18721641

 

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Authors: Ms. Meenakshi, Dr. Shweta Mishra

Abstract: Regression testing plays a critical role in ensuring the continued functionality and quality of software as changes, updates, or bug fixes are implemented. Given the complexity and the growing size of modern software systems, managing large test suites efficiently is becoming increasingly difficult. This paper focuses on the importance of test case prioritization, a technique aimed at ordering test cases in a way that maximizes fault detection early while minimizing resource utilization. The study compares various theoretical models and methods of test case prioritization, including random, requirement-based, code-based, and model-based prioritization. It highlights the benefits of prioritization in improving test efficiency and the challenges associated with its implementation. Additionally, the paper reviews both traditional and advanced prioritization techniques, including risk-based prioritization and AI-driven methods, with a comparison of their effectiveness in different software development contexts. Finally, the paper discusses the challenges and limitations of current prioritization models and suggests future directions for improving prioritization techniques in regression testing.

 

 

 

Published by: vikaspatanker

Authors: Gabriel D. Gonzales, Nhyllarhy Myrrh Junsay, Gian Gaizel Pausta, Jannon V. Tagalog, Angel S. Salario, George I. Salvador

Abstract: This study focused on developing the MethaneMorphosis: The Smart Bioengineered Reactor as a more secure, automated, and affordable alternative to household biogas generation, addressing the challenges created by rapidly surging Liquefied Petroleum Gas (LPG) prices and initial cost and safety issues of manual biodigesters. The system included an Arduino Uno R4 Wifi microcontroller, and optimized automated co-digestion of household food waste and pig manure using Response Surface Methodology (RSM) and various sensors to monitor temperature, pressure, and methane concentration in real-time. The study found 100% of the reactor to be automated with the optimal mesophilic range of 36-39 degrees Celsius successfully maintained; the system achieved a remarkably high energy conversion ratio (ECR of 4968.03%), with recovered energy equivalent to nearly 5.94 kg of LPG utilized, all at a unit cost of methane at ₱12.26/m^3. Overall, the findings illustrate the importance of this system as a very efficient and robust option for cost-effective renewable energy generation and sustainable waste management options. The primary recommendation is for the local stakeholders to explore and adapt more innovative natural gas projects like MethaneMorphosis, which is a low-cost and automated reactor as an option for households that promote sustainable waste management and reduce household energy costs through generating renewable biogas.

DOI: https://doi.org/10.5281/zenodo.18721478

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Authors: Dr. C.Chinna Suresh Babu, P.Subha Akhil, A.Dharani, M.M.Haneef

Abstract: The project titled “G+3 Residential Building Design, Analysis, and Estimation Using STAAD Pro and Revit Software” focuses on thestructural planning, analysis, and cost estimation of a Ground plus Three (G+3) storied residential building using advanced computer- aided design tools. The main objective of this project is to achieve a safe, economical, and functionally efficient structural design that complies with relevant building codes and standards. In this project, STAAD Pro is used for structural analysis and design to determine the strength, stability, and load-carrying capacity of structural components such as beams, columns, and slabs under various load conditions including dead load, live load, wind load, and seismic load. The Revit Architecture software is utilized for creating detailed 3D models, visualizations, and working drawings of the building, enabling better coordination among architectural and structural components. Overall, this study demonstrates the importance of using Building Information Modeling (BIM) and structural analysis software in modern civil engineering for producing sustainable, economical, and structurally sound residential buildings.

DOI: https://doi.org/10.5281/zenodo.18720515

 

Published by: vikaspatanker

Authors: Madhur M.Kamate, Parth S.Parik, Darshan B.Patil, Samarth N.Taralekar, Ms.S.C.Raynade

Abstract: In recent years, the rapid growth of global energy demand, along with the ongoing depletion of traditional fossil fuel resources, has made the need for sustainable, renewable, and decentralized energy solutions more urgent. Traditional energy generation methods are increasingly unable to meet rising consumption while ensuring environmental sustainability. Among the various alternative approaches, capturing human kinetic energy produced during everyday activities has emerged as a promising and eco-friendly solution. Human movement, especially in crowded public areas, is an underused and always available energy source. This paper presents the design and implementation of a footstep-based electricity generation system that uses piezoelectric sensors to convert human movements into usable electrical power. The system works on the principle of the piezoelectric effect, where mechanical pressure from footsteps is turned into electrical energy. The electrical output produced is usually alternating and highly variable. It is processed to ensure stable operation through rectification, filtering, and conditioning with appropriate power electronic circuits. A buck-boost converter regulates the voltage levels effectively and allows for the reliable storage of the collected energy in rechargeable batteries. An Arduino-based microcontroller is included for smart monitoring, which provides real- time readings of voltage levels, footstep counts, and system performance displayed on a 16×2 LCD module. The stored energy is used to power low- power DC devices like LEDs and mobile charging ports, as well as AC loads through an inverter circuit. Experimental tests show that the generated power increases with the load and footstep frequency. This demonstrates the potential for deploying the system in high-footfall public spaces such as railway stations, shopping malls, and smart city infrastructures.

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