Life Cycle Assessment of Battery Energy Storage Technologies for Vehicular Applications
Battery technology; Charge-discharge; Cradle; Energy; Manufacturing; Recycling; Storage
The necessity of sustainable energy sources and storage technologies is emerging due to growing energy demands. Thus, it encourages the need to perform sustainability analysis in terms of energy efficiency. For battery technologies, energy production and recycling holds a significance. In this study, the direct and indirect requirements of various battery technologies including production to transportation. The five battery technologies taken into account for the analysis are Lithium ion, Nickel Metal Hydride, Lead acid, Valve Regulated lead Acid, and Nickel Cadmium. The characteristics analyzed here are cycle life, energy density and energy efficiency. The study also covers the life cycle assessment in an structured way from raw to evaluation of materials, energy flow, installation, usage to end of life. The Authors, published by EDP Sciences, 2024.
Sridevi J.; Ananthi S.; Gokilavani R.; Al-Farouni M.; Ameer S.A.
https://doi.org/10.1051/e3sconf/202456408004 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85203785443&doi=10.1051%2fe3sconf%2f202456408004&partnerID=40&md5=7ad4349201f445e19aec4031311142a0
Sridevi J., Department of EEE, GRIET, Bachupally, Telangana, Hyderabad, India; Ananthi S., New Prince Shri Bhavani College of Engineering and Technology, Chennai, India; Gokilavani R., Department of Commerce, CHRIST (Deemed to Be University), Bangalore, India; Al-Farouni M., Department of Computers Techniques Engineering, College of Technical Engineering, The Islamic University, Najaf, Iraq, Department of Computers Techniques Engineering, College of Technical Engineering, The Islamic University of Al Diwaniyah, Al Diwaniyah, Iraq, Department of Computers Techniques Engineering, College of Technical Engineering, The Islamic University of Babylon, Babylon, Iraq; Ameer S.A., Ahl Al Bayt University, Karbala, Iraq
Modernizing Electrical Grids with TCR-Based Flexible AC Transmission Systems
Current; Flexible AC Transmission Systems (FACTS); Thyristor-Controlled Reactors (TCRs)
Modernizing electrical grids is imperative to meet the growing demand for reliable, efficient, and sustainable energy. Thyristor-Controlled Reactors (TCRs) are integral components of modern Flexible AC Transmission Systems (FACTS). These systems offer a robust solution for enhancing grid stability, improving power quality, and optimizing transmission efficiency, ensuring that electric grids can support future energy needs. TCR-based FACTS are a collection of technologies designed to enhance the controllability, stability, and power transfer capability of AC electrical grid systems. In this paper, we will discuss the role of TCRs in modernizing AC transmission systems and their role in addressing grid challenges and improving performance, highlighting their critical role in future grid infrastructure. To discuss the future prospects and developments in TCR technology, with ongoing advancements and research efforts paving the way for more efficient, reliable, and flexible grid management solutions. The Authors, published by EDP Sciences, 2024.
Alabdeli H.; Obaid M.K.; Rekha M.; Sivasubramanian S.; Ashok J.; Tharmar S.
Alabdeli H., Department of Computers Techniques Engineering, College of Technical Engineering, The Islamic University, Najaf, Iraq, Department of Computers Techniques Engineering, College of Technical Engineering, The Islamic University of Al Diwaniyah, Al Diwaniyah, Iraq, Department of Computers Techniques Engineering, College of Technical Engineering, The Islamic University of Babylon, Babylon, Iraq; Obaid M.K., College of Arts, Ahl Al Bayt University, karbala, Iraq; Rekha M., Department of EEE, GRIET, Bachupally, Telangana, Hyderabad, India; Sivasubramanian S., New Prince Shri Bhavani College of Engineering and Technology, Chennai, India; Ashok J., School of Business and Management, CHRIST (Deemed to Be University), Karnataka, Bengaluru, India; Tharmar S., Mohamed Sathak Engineering College, Tamil Nadu, Kilakari, India
A PV-Powered Single Phase Seven-Level Invertera's Photocurrent and Injected Power
Harmonics; MPPT; Proportional Integral; PV inverter; Seven level inverter
The PV inverter in this study is linked to the grid and its performance analysis is evaluated using a PI controller. It is a single phase multi-level PV inverter. The major objective of this research is to increase efficiency and eliminate harmonics caused by DC link voltage fluctuations created by Maximum Power Point Tracking (MPPT) during foggy situations. PV inverters generate and inject actual power into the main grid. This study uses a transformer-less photovoltaic inverter to cut down on losses, cost, and size. A transformer-less multilayer inverter is described in this paper. There is no high-frequency leakage current since that inverter can distribute both actual and reactive electricity. MATLAB/Simulink software was used to analyze and assess the effects of various PV-based seven-level techniques on the devicea's Maximum Power Point Tracking (MPPT) performance. The Authors, published by EDP Sciences, 2024.
Alkhafaij M.A.; Davala K.; Edwin Prabhakar P.B.; Jeshurun S.B.; Ramy Riad A.-F.; Senthil Kumar R.
https://doi.org/10.1051/e3sconf/202456405009 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85203842044&doi=10.1051%2fe3sconf%2f202456405009&partnerID=40&md5=8214f998ba40f786a9c2e4b4b57eda38
Alkhafaij M.A., College of MLT, Ahl Al Bayt University, karbala, Iraq; Davala K., Department of EEE, GRIET, Bachupally, Telangana, Hyderabad, India; Edwin Prabhakar P.B., New Prince Shri Bhavani College of Engineering and Technology, Chennai, India; Jeshurun S.B., School of Business and Management, CHRIST University, Bangalore, India; Ramy Riad A.-F., Department of Computers Techniques Engineering, College of Technical Engineering, The Islamic University, Najaf, Iraq, Department of Computers Techniques Engineering, College of Technical Engineering, The Islamic University of Al Diwaniyah, Al Diwaniyah, Iraq, Department of Computers Techniques Engineering, College of Technical Engineering, The Islamic University of Babylon, Babylon, Iraq; Senthil Kumar R., AAA College of Engineering & Technology, tamil Nadu, Sivakasi, India
Energy Storage System Modelling for Hybrid Electric Vehicle
Characteristics; Charge; Curves; Discharge; Electrical; State of charge
The equivalent circuit model (ECM)-based traditional state-of-charge (SoC) estimate approaches combine all state variables into a single enhanced state vector. However, the stability and accuracy of the estimates are compromised by the correlations between RC voltages and SOC. In this article, the four battery chemistries have been discussed for their state variable characterization i.e. state of charge (SOC). The battery types considered are lead acid, nickel metal hydride, lithium ion. The manufacturera's battery discharge curves are used to determine the model parameters, and a method is also described for doing this. An improved battery model is suggested in this study that can be applied to HEV design and analysis. By incorporating the electrical characteristics of the battery, the model generates precise results. The Authors, published by EDP Sciences, 2024.
Mohammed G.; Srividya Devi P.; Durgadevi G.; Subramani R.; Husain S.O.
https://doi.org/10.1051/e3sconf/202456402012 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85203805758&doi=10.1051%2fe3sconf%2f202456402012&partnerID=40&md5=b73da57e214db6c6ce938ac664956bfc
Mohammed G., Ahl Al Bayt University, Karbala, Iraq; Srividya Devi P., Department of EEE, GRIET, Bachupally, Telangana, Hyderabad, India; Durgadevi G., New Prince Shri Bhavani College of Engineering and Technology, Chennai, India; Subramani R., Department of Mathematics, Christ University, Bangalore, India; Husain S.O., Department of Computers Techniques Engineering, College of Technical Engineering, The Islamic University, Najaf, Iraq, Department of Computers Techniques Engineering, College of Technical Engineering, The Islamic University of Al Diwaniyah, Al Diwaniyah, Iraq, Department of Computers Techniques Engineering, College of Technical Engineering, The Islamic University of Babylon, Babylon, Iraq
Fuzzy Logic Based Energy Storage Management for Parallel Hybrid Electric Vehicle
Energy management strategies; Forward facing; Fuel economy; Fuzzy logic; Optimizing; Power controller
For the parallel hybrid electric vehicle, the various control strategies for energy management are illustrated with the implementation of fuzzy logic. The controller is designed and simulated in two modes for the economy and fuel optimisation. In order to manage the energy in HEV with three separate energy sources - batteries, Fuel cell and a supercapacitor system, - this article intends to create a fuzzy logic controller. By considering a complete system, the operating efficiency of the components need to be optimized. the control strategy implementation will be performed by the forward-facing approach. The fuel economy is optimised by maximising the operating efficiency in this strategy while other strategies does not have this extra aspect. The ability controller for parallel hybrid vehicles is mentioned in this research to enhance fuel economy. Although the earlier installed power controllers optimise operation, they do not fully utilise the capabilities. Hybrid vehicles can be equipped with a variety of power and energy sources such as batteries, internal combustion engines, fuel cell systems, supercapacitor systems or flywheel systems. The Authors, published by EDP Sciences, 2024.
Hussein A.H.A.; Vijaya Rama Raju V.; Saritha G.; Subramani R.; Alsalami Z.
https://doi.org/10.1051/e3sconf/202456402011 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85203799028&doi=10.1051%2fe3sconf%2f202456402011&partnerID=40&md5=6d15ff90e3d07f080be6604f1d14408f
Hussein A.H.A., College of Pharmacy, Ahl Al Bayt University, Karbala, Iraq; Vijaya Rama Raju V., Department of EEE, GRIET, Bachupally, Telangana, Hyderabad, India; Saritha G., Sri Sai Ram Institute of Technology, Chennai, India; Subramani R., Department of Mathematics, Christ University, Bangalore, India; Alsalami Z., Department of Computers Techniques Engineering, College of Technical Engineering, The Islamic University, Najaf, Iraq, Department of Computers Techniques Engineering, College of Technical Engineering, The Islamic University of Al Diwaniyah, Al Diwaniyah, Iraq, Department of Computers Techniques Engineering, College of Technical Engineering, The Islamic University of Babylon, Babylon, Iraq
Efficiency Analysis of Modified Sepic Converter for Renewable Energy Applications
Converter; Efficiency continuous mode; Modified; Renewable; SEPIC; Voltage gain
A boosting module and a traditional SEPIC (single ended primary inductance converter) are combined to create the suggested circuit. As a result, the converter gains from the SEPIC convertera's many benefits. Also, the converter that is being presented is appropriate for renewable energy sources due to its high voltage gain and continuous input current. In comparison to a traditional SEPIC with a single-controlled switch, it offers a higher voltage gain. The voltage gains of the converter that has been suggested is closely related to that of the converter that was recently developed. This converter was constructed on the foundation of the conventional converter, as well as the conventional DC-to-DC converter. One of the most important characteristics of a projected converter is that it is equipped with a single controlled device and has the capability to increase voltage gain without the utilisation of a coupled inductor structure or transformer. The non-idealities of the semiconductor devices and passive components have been taken into consideration in the analysis of voltage gain in continuous current mode (CCM). The conventional SEPIC converter can be modified by incorporating capacitors and diodes. The experimental results indicate that this converter can amplify the output voltage by approximately 10 times and has an efficiency of around 97%. The Authors, published by EDP Sciences, 2024.
Rao D.S.N.M.; Jasmin M.; Pandey M.; Almusawi M.; Ramadan G.M.; Senthil Kumar R.
https://doi.org/10.1051/e3sconf/202456401007 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85203812459&doi=10.1051%2fe3sconf%2f202456401007&partnerID=40&md5=dedfc66e63f9763647c6824974304b44
Rao D.S.N.M., Department of EEE, GRIET, Bachupally, Telangana, Hyderabad, India; Jasmin M., New Prince Shri Bhavani College of Engineering and Technology, Chennai, India; Pandey M., School of Business and Management, CHRIST (Deemed to Be University), Bangalore, India; Almusawi M., Department of Computers Techniques Engineering, College of Technical Engineering, The Islamic University, Najaf, Iraq, Department of Computers Techniques Engineering, College of Technical Engineering, The Islamic University of Al Diwaniyah, Al Diwaniyah, Iraq, Department of Computers Techniques Engineering, College of Technical Engineering, The Islamic University of Babylon, Babylon, Iraq; Ramadan G.M., College of MLT, Ahl Al Bayt University, Karbala, Iraq; Senthil Kumar R., AAA College of Engineering & Technology, tamil Nadu, Sivakasi, India
Analyses of the Power Flow through Distributed Generator based on Unsynchronized Measurements
Distributed generator; Microgrid; Non-conventional energy sources; Power flow
Based on measurements taken from the main substation and the connections between distributed generators and micro-grids that are not in sync, this study suggests a new way to look at the load flow of distributed generation. The conclusions are based on data from a distribution generatora's Load Flow Analysis that was not in sync. Distributed generation is what this approach is based on. Creating a strong communication system and using measurement data from the past are two ways to make this happen. This objective may be achieved with the use of previously gathered measurements. The time-tested backward-forward sweep method is the method of choice for analyzing power flow using unsynchronized data. This is the preferred approach. The angles of synchronization are likely to be unknowns that must be estimated. On a smart grid system with a large number of distributed generation and microgrids, a range of mathematical computations are conducted to verify the correctness of performance predictions produced by the suggested theory. The classic backward-forward sweep was shown to be the most effective method for analyzing power flow based on data that was not synchronized in many instances. This is the strategy that is presently being recommended. Because the angles of synchronization are presumed to be unknown, a mathematical equation must be devised to determine them. The Authors, published by EDP Sciences, 2024.
Almoussawi Z.A.; Raju V.V.R.; Venkatasubramanian R.; Hariharan R.; Mundher Adnan M.
https://doi.org/10.1051/e3sconf/202456411019 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85203821737&doi=10.1051%2fe3sconf%2f202456411019&partnerID=40&md5=a6d3b4c7156bacde298e36dee73a1c0e
Almoussawi Z.A., College of Islamic Science, Ahl Al Bayt University, karbala, Iraq; Raju V.V.R., Department of EEE, GRIET, Bachupally, Telangana, Hyderabad, India; Venkatasubramanian R., New Prince Shri Bhavani College of Engineering and Technology, Chennai, India; Hariharan R., School of Business and Management, CHRIST(Deemed to Be University), Bangalore, India; Mundher Adnan M., Department of Computers Techniques Engineering, College of Technical Engineering, The Islamic University, Najaf, Iraq, Department of Computers Techniques Engineering, College of Technical Engineering, The Islamic University of Al Diwaniyah, Al Diwaniyah, Iraq, Department of Computers Techniques Engineering, College of Technical Engineering, The Islamic University of Babylon, Babylon, Iraq
Transference of Love-type Wave Through Cobalt Ferrite Cofe2O4 Layer Structure, Governed by an Imperfect Interface
An analytical discussion of the wave transmission in a piezomagnetic (Cobalt ferrite) thin plate resting on an elastic substrate is presented in the problem. It is presumed that the geometrys interface is not ideal. The flaw of the considered structure is used to describe by following the linear spring model. The calculative method of the upper material is Direct Sturm-Liouville. Dispersion relations are drived for each of the magnetically open and magnetically short cases. Love-type wave velocity profiles have been depicted on graphs for various influencing factors, such as heterogeneity in the substrate, layer thickness, and interface imperfections. It has been demonstrated that raising these parameters raises the Love waves phase velocity. Furthermore, it is found that compared to substrate heterogeneity, layer thickness has less of an impact on the waves velocity profile. Additionally, it has been shown how the aforementioned cases compare when imperfect parameters are varied. It is discovered that the velocity in the open case is greater than that in the short case. The results have potential applications in the design of piezomagnetic semiconductor devices controlled by electric fields and are of great significance for developing surface acoustic wave (SAW) gyroscopes. 2024 American Institute of Physics Inc.. All rights reserved.
AIP Conference Proceedings, Vol-3242, No. 1
https://doi.org/10.1063/5.0234299 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85206373677&doi=10.1063%2f5.0234299&partnerID=40&md5=a8923976a2d64de49895f2a90c19794e
Seema, Christ University, Karnataka, Bengaluru, 560029, India; Singhal A., Christ University, Karnataka, Bengaluru, 560029, India
Organizational Preparedness for Navigating Disruption Towards Sustainability: Strategies Analysis
Design thinking; Disruptive business; Disruptive innovation; Sustainability
The study explores how design thinking principles can be leveraged to enhance an organization's preparedness for disruptive innovation. To address this challenge, the authors sought to empathize with their clients, recognizing the need for a comprehensive evaluation. A framework guided by five fundamental principles - Scrutiny, Bravery, Resilience, Prosperous and Perseverance - was developed that integrates user-centred design methodologies to evaluate an organization's strengths and weaknesses in the face of disruption. We analysed and interpreted the intricacies of emerging market disruptions, providing organizations with the GroKalp Assessment Tool, an automated tool for self-evaluation and strategic adjustment leading towards a sustainable future. These principles were further broken down into fifteen distinct parameters, each thoughtfully designed to offer organizations a detailed and insightful method for evaluating their responses to the relentless waves of transformative innovation. By utilizing the GroKalp Assessment Tool, organizations can position themselves in one of three categories: Innovators, Adapters, or Resistance Fighters. Design thinking tools are vital in this process, as they encourage creative problem-solving, innovation, and adaptation in an era of rapid technological change. The Authors.
Pandey D.; Singh G.; Joshi L.; Polyakova O.; Sungatullina D.; Ashurov A.
https://doi.org/10.1051/e3sconf/202457407001 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85207308604&doi=10.1051%2fe3sconf%2f202457407001&partnerID=40&md5=c229bdf72e7be1bc7c551e6491f7d3cc
Pandey D., Christ University, Bengaluru, India; Singh G., Indian Institute of Technology, Delhi, India; Joshi L., GroKalp Limited, Rajasthan, Jodhpur, India; Polyakova O., Kazan Federal University, Kazan, Russian Federation; Sungatullina D., Kazan Federal University, Kazan, Russian Federation; Ashurov A., Termez University of Economics and Service, Termez, Uzbekistan, Tashkent Institute of Irrigation and Agricultural Mechanization Engineers, National Research University, Tashkent, Uzbekistan
AI and Machine Learning Applications in Predicting Energy Market Prices and Trends
AI; energy prices; forecasting; machine learning
The worldwide energy market is intricate and unstable, shaped by several aspects including geopolitical occurrences, supply-demand variations, and regulatory modifications. Precisely forecasting energy prices and trends is essential for stakeholders, such as energy producers, dealers, and policymakers. This study investigates the utilization of artificial intelligence (AI) and machine learning (ML) to improve energy price forecasting models. Conventional forecasting methods frequently fail to account for the dynamic and non-linear characteristics of energy markets; however, AI/ML techniques, including neural networks, decision trees, and reinforcement learning, provide enhanced prediction precision. By including external variables such as meteorological conditions and economic metrics, AI models can produce more accurate and useful insights. Case studies illustrate the effective implementation of AI in energy markets, showcasing its capacity to surpass traditional methods. This article addresses difficulties such as data quality and computing expenses while delineating potential developments in AI-driven energy market forecasts. The Authors, published by EDP Sciences.
Sharma G.; Dhore M.L.; Jansirani D.; Jeshurun S.B.; Sathi G.; Sherje N.; Vivek V.
https://doi.org/10.1051/e3sconf/202459101002 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85211823746&doi=10.1051%2fe3sconf%2f202459101002&partnerID=40&md5=4d1b251c6e717004c761bbc278ba6bda
Sharma G., Institute of Business Management, GLA University, Mathura, India; Dhore M.L., Department of Computer Engineering, Vishwakarma Institute of Technology, Pune, India; Jansirani D., Department of IT, New Prince Shri Bhavani College of Engineering and Technology, Tamil nadu, Chennai, 600073, India; Jeshurun S.B., School of Business and Management, CHRIST University, Bangaluru, India; Sathi G., Department of MECH, Prince Shri Venkateshwara Padmavathy Engineering College, Chennai, 127, India; Sherje N., Dr. D. Y. Patil Institute of Technology, Pimpri, Pune, India; Vivek V., Department of Computer Science and Engineering, AAA College of Engineering and Technology, Tamil Nadu, Sivakasi, 626005, India
Machine Learning Algorithms for Predictive Maintenance in Hybrid Renewable Energy Microgrid Systems
Energy Management; Hybrid Renewable Energy Systems; Machine Learning; Microgrid; Predictive Maintenance; Remaining Useful Life (RUL)
The rapid expansion of hybrid renewable energy microgrid systems presents new challenges in maintaining system reliability and performance. This paper explores the application of machine learning algorithms for predictive maintenance in such systems, focusing on the early detection of potential failures to optimize operational efficiency and reduce downtime. By integrating real-time data from solar, wind, and storage components, the proposed models predict the remaining useful life (RUL) of critical components. The results demonstrate significant improvements in predictive accuracy, offering a robust solution for enhancing the reliability and longevity of renewable energy microgrids. The Authors, published by EDP Sciences.
Edwin Prabhakar P.B.; Rajarajeswari S.; Antad S.; Jeshurun S.B.; Badhoutiya A.; Chandrika S.; Suresh Babu D.
https://doi.org/10.1051/e3sconf/202459105002 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85211764825&doi=10.1051%2fe3sconf%2f202459105002&partnerID=40&md5=f9f970983ec03a1283b410acacecd651
Edwin Prabhakar P.B., Department of CSE, New Prince Shri Bhavani College of Engineering and Technology, Tamil nadu, Chennai, 600073, India; Rajarajeswari S., Department of S&H, Prince Shri Venkateshwara Padmavathy Engineering College, Chennai, 127, India; Antad S., Department of Computer Engineering, Vishwakarma Institute of Technology, Pune, India; Jeshurun S.B., School of Business and Management, CHRIST University, Bangaluru, India; Badhoutiya A., Department of Electrical Engineering, GLA University, Mathura, India; Chandrika S., Department of Mechanical Engineering, Dr.D.Y.Patil Institute of Technology, Pimrpi, Pune, India; Suresh Babu D., Department of EEE, School of Engineering, Mohan Babu University, Andhra Pradesh, Tirupati, India
On near-perfect numbers with five prime factors
divisor sum function; Near-perfect numbers; perfect numbers
Let n be a positive integer and ?(n) the sum of all the positive divisors of n. We call n a near-perfect number with redundant divisor d if ?(n) = 2n + d. Let n be an odd near-perfect number of the form n = pa11 ? pa22 ? pa33 ? pa44 ? pa55 where pis are odd primes and ais (1 ? i ? 5) are positive integers. In this article, we prove that 3 | n and one of 5, 7, 11 | n. We also show that there exists no odd near-perfect number when n = 3a1 ? 7a2 ? pa33 ? pa44 ? pa55 with p3 ? {17, 19} and when n = 3a1 ? 11a2 ? pa33 ? pa44 ? pa55 Mathematical and Computational Sciences - Proceedings of the ICRTMPCS International Conference 2023.All rights reserved.
De Gruyter Proceedings in Mathematics, pp. 207-220.
https://doi.org/10.1515/9783111313634-016 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85216221756&doi=10.1515%2f9783111313634-016&partnerID=40&md5=5bde6ba289c8e745b5ffb27aeb9d9b1b
Jeba F.S., Department of Mathematics, CHRIST (Deemed to be University), Kanmanike, Kumbalgodu, Mysore Road, Karnataka, Bengaluru, 560074, India; Roy A., Department of Sciences and Humanities, CHRIST (Deemed to be University), Kanmanike, Kumbalgodu, Mysore Road, Karnataka, Bengaluru, 560074, India; Saikia M.P., Mathematical and Physical Sciences division, School of Arts and Sciences, Ahmedabad University, Commerce Six Roads, Navrangpura, Gujarat, Ahmedabad, 380009, India
Energy Management System for EV Charging Infrastructure
Demand-Supply Balancing; Electric Vehicle (EV) Charging; Energy Management Systems (EMS); Real-Time Power Allocation; Renewable Energy Integration; Smart Grid
The increasing adoption of electric vehicles (EVs) has led to a significant rise in the demand for efficient and sustainable charging infrastructure. Managing the energy supply to meet this growing demand while ensuring grid stability presents a critical challenge. This paper presents an energy management system designed for electric vehicle charging infrastructure that balances demand and supply in real time. The proposed system dynamically allocates available power to connected EVs based on their charging demands and the total power available, ensuring optimal utilization of energy resources. By simulating various scenarios, the system demonstrates its capability to prevent overloading, efficiently distribute power, and prioritize critical energy needs. The results of the simulation show that the system can effectively manage power distribution, reduce peak load impact, and enhance the reliability of EV charging networks. This approach offers a scalable and adaptable solution for integrating EVs into the existing power grid, contributing to the development of smart and sustainable transportation systems. The Authors, published by EDP Sciences.
Bhutkar G.; Kumar Y.; Subramani R.; Jothi E.; Valarmathy A.S.; Sherje N.; Tharmar S.
https://doi.org/10.1051/e3sconf/202459104004 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85211798420&doi=10.1051%2fe3sconf%2f202459104004&partnerID=40&md5=aef97eea211aa5b0b909ab931d3ac168
Bhutkar G., Department of Computer Engineering, Vishwakarma Institute of Technology, Pune, India; Kumar Y., Institute of Business Management, GLA University, Mathura, India; Subramani R., Department of Mathematics, Christ University, Bengaluru, India; Jothi E., Department of IT, New Prince Shri Bhavani College of Engineering and Technology, Tamil nadu, Chennai, 600073, India; Valarmathy A.S., Department of EEE, Prince Shri Venkateshwara Padmavathy Engineering College, Chennai, 127, India; Sherje N., Mechanical Engineering, Dr. D. Y. Patil Institute of Technology, Pimpri, Pune, India; Tharmar S., Mohamed Sathak Engineering College, Kilakarai, India
Financial analytical usage of cloud and appropriateness of cloud computing for certain small and medium-sized enterprises
adoption; Cloud computing; ICT; India; MSME; SMEs
The term "cloud computing"refers to a novel approach of providing useful ICTs to consumers over the internet on an as-needed and pay-per-usage basis. Businesses may streamline internal processes, increase contact with customers, and expand their market reach with the aid of cloud computing, which provides convenient and inexpensive access to cutting-edge information and communication technologies. Developing economies like India's present unique problems for small and medium-sized businesses (SMEs), such as a lack of funding, an inadequate workforce, and inadequate information and communication technology (ICT) use. Various advantages offered by current information and communication technology solutions are unavailable to SMEs because of these limitations. If small and medium-sized enterprises (SMEs) are seeking to enhance their internal operations, communication with customers and business partners, and market reach using current information and communication technology (ICT) solutions, cloud computing might be a good fit for them. Therefore, SMEs are particularly well-served by cloud computing. Companies with a lack of capital, personnel, or other resources to deploy and use appropriate ICTs may greatly benefit from cloud computing, and the public cloud in particular. 2024 Author(s).
Kavitha S.; Srinivasan S.; Manasa N.; Band G.; Kanetkar M.; Patnayak D.
AIP Conference Proceedings, Vol-3214, No. 1
https://doi.org/10.1063/5.0239684 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85210436931&doi=10.1063%2f5.0239684&partnerID=40&md5=027903c9baec58d6a7e5a098333ee108
Kavitha S., Department of MBA, Dr. Ambedkar Institute of Technology, Mallathalli, Bangalore, India; Srinivasan S., Department of MBA, Nagarjuna College of Engineering and Technology, Bangalore, India; Manasa N., Department of Business and Management, CHRIST (Deemed to Be University) Yeshwantpur Campus, Bangalore, India; Band G., Department of Management Technology, Shri Ramdeobaba College of Engineering and Management, Nagpur, India; Kanetkar M., Department of Studies in Business Administration, C.P. & Berar E.S. College Ravinagar, Nagpur, India; Patnayak D., Department of Computer Science and Engineering, M. S. Engineering College, Bengaluru, India
Evaluation of machine and deep learning models for utility mining-based stock market price predictions
Deep Learning; LSTM; Neural Networks; Non-Linearity; RNNM; Stock Market Prediction
Considering the extreme volatility of stock market returns and hazards, accurate price prediction has attracted the attention of both financial institutions and regulatory bodies. Stocks, due to their historically strong returns, have long been considered by investors to be an excellent asset allocation strategy. Predicting stock prices has never ceased being a hot topic of study. Many early-day economists sought to foretell future stock values. In subsequent years, as computer technology has advanced rapidly and mathematical theory has been extensively studied, it has been shown that mathematical models, like the time series model, may be very effective in predicting due to their simplicity and superiority. Over time, the time series model is put into practice. Over time, the horizon widened. Support vector machines and other ML techniques have challenges when applied to stock data because of its non-linearity. In subsequent years, thanks to advancements in deep learning, models like RNN and LSTM Neural Networks were able to analyze non-linear input, remember the sequence, and remember valuable information,Stock data forecasting cannot be done without it. 2024 Author(s).
Rajeshwari G.M.; Manasa N.; Rajimol K.P.; Naidu K.; Samal A.; Garg N.
https://doi.org/10.1063/5.0239965 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85210417925&doi=10.1063%2f5.0239965&partnerID=40&md5=eb3f7aad795f2c42f826bea2451b579d
Rajeshwari G.M., Department of Studies in Business Administration, Pooja Bhagavat Memorial Mahajana Education Centre, Mysuru, India; Manasa N., Department of Business and Management, CHRIST (Deemed to Be University) Yeshwantpur Campus, Bangalore, India; Rajimol K.P., Department of MBA, Atria Institute of Technology, Karnataka, Bangalore, India; Naidu K., Department of Management Technology, Shri Ramdeobaba College of Engineering and Management, Nagpur, India; Samal A., Dept of MBA, Sri Venkateshwara College of Engineering, Karnataka, Bangalore, India; Garg N., Department of Studies in Business Administration, RIMS, Maharashtra, India
Advanced Materials for Next-Generation Energy Storage Devices: A Focus on Efficiency and Cost Reduction
Advanced materials; cost reduction; efficiency optimization; energy storage; nanomaterials
The increasing demand for efficient and cost-effective energy storage systems has pushed extensive research into improved materials for next-generation energy storage devices. This study discusses the crucial significance of material advances in boosting the performance and reducing the costs of storage technologies such as batteries and supercapacitors. Conventional energy storage systems face limits in energy density, charge or discharge rates, and scalability, which impede their broad implementation. Advanced materials, including nanomaterials, solid-state electrolytes, and innovative electrode compounds, offer solutions to these difficulties by enhancing energy efficiency, power output, and overall longevity. Additionally, the use of plentiful and low-cost materials, such as sodium-ion and aluminium-based compounds, presents prospects for significant cost savings. This research analyzes current trends, issues in material manufacturing, and future perspectives for energy storage systems, concentrating on balancing efficiency improvements with cost-effectiveness to enable the rising integration of renewable energy sources. The development of these materials is important to creating sustainable, scalable, and economical energy storage systems for the future. The Authors, published by EDP Sciences.
Chandrakala P.; Liz A.S.; Mane V.; Jeshurun S.B.; Sharma G.; Pardeshi P.R.; Senthil kumar R.
https://doi.org/10.1051/e3sconf/202459101001 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85211801054&doi=10.1051%2fe3sconf%2f202459101001&partnerID=40&md5=6a6055616267c09ddd036f1ce952ef45
Chandrakala P., Department of EEE, Prince Shri Venkateshwara Padmavathy Engineering College, Chennai, 127, India; Liz A.S., Department of CSE, New Prince Shri Bhavani College of Engineering and Technology, Tamil nadu, Chennai, 600073, India; Mane V., Vishwakarma Institute of Technology, Pune, India; Jeshurun S.B., School of Business and Management, CHRIST University, Bangaluru, India; Sharma G., Institute of Business Management, GLA University, Mathura, India; Pardeshi P.R., Department of Mechanical Engineering, Dr. D. Y. Patil Institute of Techology, Pimrpi, Pune, India; Senthil kumar R., AAA College of Engineering and Technology, Sivakasi, India
Quantitative Structure-Activity Relationship Modeling for the Prediction of Fish Toxicity Lethal Concentration on Fathead Minnow
Aquatic Toxicity; Fathead Minnow; LC50; Lethal Concentrations; Pimephales promelas; QSAR
As there has been a rise in the usage of in silico approaches, for assessing the risks of harmful chemicals upon animals, more researchers focus on the utilization of Quantitative Structure Activity Relationship models. A number of machine learning algorithms link molecular descriptors that can infer chemical structural properties associated with their corresponding biological activity. Efficient and comprehensive computational methods which can process huge set of heterogeneous chemical datasets are in demand. In this context, this study establishes the usage of various machine learning algorithms in predicting the acute aquatic toxicity of diverse chemicals on Fathead Minnow (Pimephales promelas). Sample drive approach is employed on the train set for binning the data so that they can be located in a domain space having more similar chemicals, instead of using the dataset that covers a wide range of chemicals at the entirety. Here, bin wise best learning model and subset of features that are minimally required for the classification are found for further ease. Several regression methods are employed to find the estimation of toxicity LC50 value by adopting several statistical measures and hence bin wise strategies are determined. Through experimentation, it is evident that the proposed model surpasses the other existing models by providing an R2 of 0.8473 with RMSE 0.3035 which is comparable. Hence, the proposed model is competent for estimating the toxicity in new and unseen chemical. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) , Vol-15310 LNCS, pp. 34-46.
Springer Science and Business Media Deutschland GmbH
Kavitha R., Department of Data Science, CHRIST (Deemed to Be University), Karnataka, Bangalore, 560 029, India; Guru D.S., Department of Studies in Computer Science, University of Mysore, Karnataka, Mysuru, 570 006, India
Digitization of Monuments An Impact on the Tourist Experience with Special Reference to Hampi
Accessible Tourism; Cultural Heritage; Digitization; Enhanced Tourist Experience; Monument Optimization
The cultural heritage of India offers a deep examination of the country's political and historical evolution. Historical structures and monuments are among a nation's most valuable assets and a source of pride for Indian civilization. Monuments hold significant historical importance and exert a profound emotional influence on the community. Given the deterioration of culturally significant heritage monuments caused by factors such as weather, climate change, and human activity, as well as the threats these elements pose to numerous heritage sites of national and international significance, it is imperative to prioritize the recording, preservation, and conservation of these monuments. Events of cultural significance require comprehensive digital documentation and proper recording. As demonstrated by various programs and initiatives led by Prime Minister Narendra Modi, the government is committed to enhancing the visitor experience at monuments and museums. The primary aim of the current study is to better understand how cultural heritage sites are digitized and to assess the implications of this process for enhancing the tourist experience. To address the research objectives, a survey was conducted to analyze digital requirements. The digitization of significant cultural heritage sites is vital for the long-term sustainability of the tourism industry. Many methods will be adapted as resources permit, ensuring the industry's steady growth over time. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
Lecture Notes in Electrical Engineering, Vol-1273 LNEE, pp. 31-36.
Ashok M.B., Christ (Deemed to be University), Karnataka, Bangalore, 560076, India; Thomas J., Christ (Deemed to be University), Karnataka, Bangalore, 560073, India
Impact of Homophily on Patient Empowerment: A Study of Online Patient Support Groups
Homophily; Online health communities; Online patient support groups; Patient empowerment
Internet facility has led to emergence of patient support groups. These have gained prominence as these fulfils important benefits to patients. One such benefit is patient empowerment. These online groups provide opportunity to patients to interact with similar ailments and predicaments and who can understand the pain and discomfort felt by the patient. This provides validation for the patient and patients experiences. How does this homophily impacts patient empowerment? This question has been explored in this study. The methodology is based on an online survey of patients visiting such online platforms. In all 701 patients provided the data. Independent variable (homophily) and dependent variable (patient empowerment) have been measured using a 7-point Likert scale. Findings provide that both are weakly correlated, but this correlation is significant. Regression analysis led to a regression model that is fit statistically. This provides basis to encourage patients to visit online support groups. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
Pandey V.; Mukherjee S.K.; Singh A.; Saha S.K.; Jha A.
Lecture Notes in Electrical Engineering, Vol-1243 LNEE, pp. 201-209.
Pandey V., Sikkim Manipal Institute of Technology, Sikkim, Majitar, Rangpo, India; Mukherjee S.K., Sikkim Manipal Institute of Technology, Sikkim, Majitar, Rangpo, India; Singh A., Symbiosis Institute of Health Sciences, A Constituent of Symbiosis International (Deemed University), Maharashtra, Lavale, Pune, 412115, India; Saha S.K., Christ University, Bengaluru, India; Jha A., Sikkim Manipal Institute of Technology, Sikkim, Majitar, Rangpo, India
Linking the Path to Zero Hunger: Analysing Sustainable Development Goals Within the Context of Global Sustainability
Policy measures; SDG 2 Zero Hunger; Sustainability; Sustainable agriculture; Sustainable Development Goals
A global framework, the Sustainable Development Goals of the United Nations, are designed to tackle the most urgent global issues. SDG 2, which stands for Zero Hunger, demonstrates a robust interconnection with the remaining seventeen goals since achieving food security and improved nutrition requires an all-encompassing approach that addresses the interconnected challenges presented by poverty, health, education, gender equality, climate change, and sustainable resource management. Within this framework, the research endeavors to ascertain the interrelationships among SDG 2 and other goals and analyze the critical goals that drive the achievement of SDG 2. Furthermore, the study provides an exhaustive analysis of the positions adopted by different nations concerning SDG 2. The results indicate that the SDGs are interconnected; while SDG 2 is closely linked to several other SDGs, their respective impacts differ. Furthermore, it has been determined that policies are crucial to attaining the SDGs. Without a transformation in agri-food systems that enhances resilience and facilitates the provision of affordable, nutritious foods and healthy diets, the current state of affairs will persist. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
Lecture Notes in Civil Engineering, Vol-557 LNCE, pp. 362-369.
Sharma S., Indian Institute of Technology, Uttar Pradesh, Kanpur, India; Sahni J., Prince Sultan University, NJ, Riyadh, 08544, Saudi Arabia; Joy R., Christ University, Karnataka, Bengaluru, India