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Energy Harvesting Poles: Harnessing Piezoelectric Power for Sustainable Infrastructure

The integration of piezoelectric poles in road infrastructure presents a promising avenue for sustainable energy generation and smart infrastructure development. Piezoelectric materials, which generate electrical energy when subjected to mechanical stress or pressure, can be embedded in road poles to harness the energy from vehicles passing by. These poles can convert the vibrations and pressure created by traffic into usable electrical energy, which can then be utilized to power streetlights, traffic signals or even be stored for future use. The potential for reducing dependency on traditional energy sources while improving the functionality and sustainability of roadways is substantial. Furthermore, piezoelectric poles can contribute to the development of smart roads, integrating sensors and communication systems that enhance traffic management and safety. This paper explores the feasibility, design, and applications of piezoelectric poles on roads, evaluating their potential environmental and economic benefits, as well as the challenges in scaling this technology for widespread use in modern transportation networks.

Published by: Ansh Mahadik, Aditi Gavand, Vivek Magar, Harashad Dhandar, Chaitali Bagul

Author: Ansh Mahadik

Paper ID: V11I2-1189

Paper Status: published

Published: April 12, 2025

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Research Paper

APPROCHE D’EFFICACITÉ ÉNERGÉTIQUE POUR OPTIMISER LES COÛTS DE PRODUCTION DES ENTREPRISES INDUSTRIELLES

Madagascar est une île de la côte orientale de l'Afrique qui possède de nombreuses ressources minières. Une société minière comme Ambatovy a décidé d'explorer le nickel et le cobalt dans ce pays et elle était confrontée à un problème de crise financière et de compétitivité sur le marché du nickel du LME. Le prix du nickel a diminué en raison du surstock de China Nickel. Pour éviter des mesures drastiques telles que des licenciements, l'entreprise a appliqué une nouvelle stratégie de réduction des coûts de production. Le secteur de l'énergie est l'un des secteurs les plus précieux qui peuvent bénéficier d'économies significatives s'il est bien optimisé. L'efficacité énergétique ou économie d'énergie a été mise en place afin d'optimiser la consommation et l'approvisionnement en énergie dans cette entreprise. Conformément à la norme AQME2011, Ambatovy utilise le modèle 3R de clés d'efficacité énergétique : -Réduction à la source : le comportement de l'utilisateur final doit s'aligner sur cette politique et mettre en place le FMS (Procédure de gestion du carburant), négocier le coût du contrat avec le fournisseur de carburant à Madagascar.-Récupération : continuez à utiliser ce que nous avons encore en moteur, stock bien optimisé et remplacement : Ambatovy a remplacé tous les bus à l'intérieur du site de l'usine par des bus et des véhicules électriques (tuctuc), cela peut économiser plus de 35 % des coûts quotidiennement car cela permet à l'entreprise arrêter le loyer, réduire les coûts de maintenance et récupérer la surproduction de la centrale électrique d'Ambatovy. Cette optimisation de la gestion de l'énergie permet à l'entreprise de réduire les coûts de production, d'éliminer les déchets et d'utiliser des véhicules solaires et électriques qui sont plus propres et respectueux de l'environnement.

Published by: Georges SOLOFOSON, Daudet Evariste ZELY, Herilalaina Fabien RANDRIANASOLO, Cyprien ZARALAHY, Holy Nivosoa RAKOTOMALALA

Author: Georges SOLOFOSON

Paper ID: V10I5-1296

Paper Status: published

Published: April 10, 2025

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Thesis

“A Study to Assess the Knowledge Regarding Isbar Handing and Taking Over Tool Among Staff Nurses Working at Selected Hospital in the City.”

Clinical handover is the transfer of professional responsibility and accountability for some or all aspects of care for a patient or group of patients to another person/family / legal guardian or professional group on a temporary or permanent basis. It is one of the most important skills that health professionals and students need to be taught. There are several structured formats available for clinical handover. e.g. IPASS3. I-SBAR is a mnemonic that aids in safe handover of patient information and improves communication and decision-making. This technique improves the efficiency and accuracy of Handing and Taking over the process by staff nurses4. PROBLEM STATEMENT: "A study to assess the knowledge regarding I-SBAR handing and taking over tool among staff nurses working in selected city hospitals." OBJECTIVES OF STUDY: • To assess the knowledge among staff nurses regarding the I-SBAR handing and taking over tool • To find an association of knowledge regarding the I-SBAR handing and to take over the tool with selected demographic variables. METHODS: The study was conducted at MGM of Chh. sambhajinagar city. The present study's sample size was 80 MGM hospital Chh staff nurses. sambhajinagar. A structured questionnaire regarding the ISBAR handing and taking over tool was used to assess the knowledge of staff nurses in MGM Hospital Chh. Sambhajinagar. 9 RESULTS:. The majority of samples, 57 (71.25%), have good knowledge regarding ISBAR handing and taking over the tools, 19 (23.75%) samples have average knowledge regarding ISBAR handing and taking over the tools, and 4 (5%) samples have poor knowledge regarding ISBAR handing and taking over a tool. CONCLUSION: This study assessed the knowledge regarding ISBAR handling and taking over tools. Based on the result, the investigator concluded that there was a significant association between religion and the knowledge of staff nurses regarding ISBAR handing and taking over tools.

Published by: Ms. Ashvini Chappekar, Ms. Bidyarani Yumnam

Author: Ms. Ashvini Chappekar

Paper ID: V11I1-1370

Paper Status: published

Published: April 10, 2025

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Research Paper

Encoding Digital Information in DNA: Advances, Techniques, and Applications

In 2020 approximately 64 zettabytes of Data were generated and it was predicted that by 2025 this number will be greater than twice that of it. This prediction is proving itself as every day approximately 402.74 million Terabytes of data is created and as of 2024 the number has risen to 147 Zettabytes already and it's assumed that this amount will be 181 Zettabytes by the end of 2025. This data primarily includes IoT data which is the fastest growing segment of data which is then followed by social media. The existing storage technologies cannot cater to the needs of the Zettabyte Era, as they have considerable issues like limited durability, high power consumption, and the environmental impact they cause. DNA is nature's best alternative to these problems and can store such high amounts of data for a longer period without very little decay. One gram of DNA can store up to 215 Petabytes of data. Its longevity of thousands of years and enormous information density without harming the environment by generating less e-waste makes it a promising archival storage medium.

Published by: Ananya Chandra, Mahesh Tiwari

Author: Ananya Chandra

Paper ID: V11I1-1285

Paper Status: published

Published: April 10, 2025

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Research Paper

Design and Development of V-Twin Stirling Engine

This project aims to address environmental issues like air pollution and noise generated by internal combustion (IC) engines through the development of a V-Twin Stirling engine. Stirling engines, which operate through cyclic expansion and contraction of gas via external heat sources, offer a more efficient and cleaner alternative to traditional IC engines. The design leverages a unique mechanism where one piston drives the motion of both pistons using a gear system, reducing fuel consumption and emissions. The project involves comprehensive analysis and design, with the engine components, such as flywheels, gears, and pistons, being meticulously crafted for optimized performance. The development process includes part drawings, weight and volume calculations, and precision manufacturing using aluminum. The Stirling engine’s potential to harness renewable energy, integrate into power generation systems, and recover waste heat positions it as a viable alternative for future sustainable automotive technologies. The total project budget is approximately INR 6000, covering materials, manufacturing, and necessary accessories.

Published by: Viraj Tambe, Ravi Singh, Rahul Mayekar, Tanish Tilak, Prof. Nikhil V.S.

Author: Viraj Tambe

Paper ID: V11I2-1166

Paper Status: published

Published: April 10, 2025

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Research Paper

Comparative Analysis of Machine Learning Models for Diabetes Prediction: A Performance Evaluation Study

Diabetes is a chronic disease affecting millions worldwide, necessitating early diagnosis and effective prediction models for improved healthcare outcomes. This study evaluates seven machine learning algorithms for diabetes prediction using healthcare data. We compared Logistic Regression, K-Nearest Neighbors (KNN), Random Forest, Decision Tree, AdaBoost, XGBoost, and Support Vector Machine (SVM) models. The analysis focused on key performance metrics: accuracy, precision, recall, F1-score, and Area Under the Curve (AUC). Results showed that logistic regression achieved the highest overall performance with 79% accuracy and 0.88 AUC, suggesting its potential utility in clinical diabetes prediction applications.

Published by: Taaha Ansari, Vaishali M. Bagade

Author: Taaha Ansari

Paper ID: V11I2-1170

Paper Status: published

Published: April 10, 2025

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