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                <text>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.</text>
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                <text>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</text>
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                <text>Modernizing Electrical Grids with TCR-Based Flexible AC Transmission Systems</text>
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                <text>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.</text>
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                <text>Alabdeli H.; Obaid M.K.; Rekha M.; Sivasubramanian S.; Ashok J.; Tharmar S.</text>
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                <text>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</text>
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                <text>Harmonics; MPPT; Proportional Integral; PV inverter; Seven level inverter</text>
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                <text>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.</text>
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                <text>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 &amp;amp; Technology, tamil Nadu, Sivakasi, India</text>
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                <text>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.</text>
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                <text>Mohammed G.; Srividya Devi P.; Durgadevi G.; Subramani R.; Husain S.O.</text>
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                <text>E3S Web of Conferences, Vol-564</text>
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                <text>EDP Sciences</text>
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                <text>&lt;a href="https://doi.org/10.1051/e3sconf/202456402012" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1051/e3sconf/202456402012&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85203805758&amp;amp;doi=10.1051%2Fe3sconf%2F202456402012&amp;amp;partnerID=40&amp;amp;md5=b73da57e214db6c6ce938ac664956bfc" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85203805758&amp;amp;doi=10.1051%2fe3sconf%2f202456402012&amp;amp;partnerID=40&amp;amp;md5=b73da57e214db6c6ce938ac664956bfc&lt;/a&gt;</text>
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                <text>All Open Access; Gold Open Access</text>
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                <text>ISSN: 25550403</text>
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                <text>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</text>
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          <element elementId="50">
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              <elementText elementTextId="160857">
                <text>Fuzzy Logic Based Energy Storage Management for Parallel Hybrid Electric Vehicle</text>
              </elementText>
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            <name>Subject</name>
            <description>The topic of the resource</description>
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              <elementText elementTextId="160858">
                <text>Energy management strategies; Forward facing; Fuel economy; Fuzzy logic; Optimizing; Power controller</text>
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            <name>Description</name>
            <description>An account of the resource</description>
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                <text>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.</text>
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              <elementText elementTextId="160860">
                <text>Hussein A.H.A.; Vijaya Rama Raju V.; Saritha G.; Subramani R.; Alsalami Z.</text>
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                <text>E3S Web of Conferences, Vol-564</text>
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              <elementText elementTextId="160862">
                <text>EDP Sciences</text>
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            <description>A point or period of time associated with an event in the lifecycle of the resource</description>
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              <elementText elementTextId="160863">
                <text>2024-01-01</text>
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                <text>&lt;a href="https://doi.org/10.1051/e3sconf/202456402011" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1051/e3sconf/202456402011&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85203799028&amp;amp;doi=10.1051%2Fe3sconf%2F202456402011&amp;amp;partnerID=40&amp;amp;md5=6d15ff90e3d07f080be6604f1d14408f" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85203799028&amp;amp;doi=10.1051%2fe3sconf%2f202456402011&amp;amp;partnerID=40&amp;amp;md5=6d15ff90e3d07f080be6604f1d14408f&lt;/a&gt;</text>
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            <name>Rights</name>
            <description>Information about rights held in and over the resource</description>
            <elementTextContainer>
              <elementText elementTextId="160865">
                <text>All Open Access; Gold Open Access</text>
              </elementText>
            </elementTextContainer>
          </element>
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            <description>A related resource</description>
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              <elementText elementTextId="160866">
                <text>ISSN: 25550403</text>
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            <name>Format</name>
            <description>The file format, physical medium, or dimensions of the resource</description>
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              <elementText elementTextId="160867">
                <text>Online</text>
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            <name>Language</name>
            <description>A language of the resource</description>
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              <elementText elementTextId="160868">
                <text>English</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="51">
            <name>Type</name>
            <description>The nature or genre of the resource</description>
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              <elementText elementTextId="160869">
                <text>Conference paper</text>
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            </elementTextContainer>
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            <description>The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant</description>
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              <elementText elementTextId="160870">
                <text>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</text>
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  <item itemId="18942" public="1" featured="0">
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          <elementContainer>
            <element elementId="50">
              <name>Title</name>
              <description>A name given to the resource</description>
              <elementTextContainer>
                <elementText elementTextId="51377">
                  <text>Conference Papers</text>
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      </elementSetContainer>
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    <itemType itemTypeId="28">
      <name>Conference Paper</name>
      <description>Faculty Publications- Conference Papers</description>
    </itemType>
    <elementSetContainer>
      <elementSet elementSetId="1">
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        <description>The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.</description>
        <elementContainer>
          <element elementId="50">
            <name>Title</name>
            <description>A name given to the resource</description>
            <elementTextContainer>
              <elementText elementTextId="160843">
                <text>Efficiency Analysis of Modified Sepic Converter for Renewable Energy Applications</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="49">
            <name>Subject</name>
            <description>The topic of the resource</description>
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              <elementText elementTextId="160844">
                <text>Converter; Efficiency continuous mode; Modified; Renewable; SEPIC; Voltage gain</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="41">
            <name>Description</name>
            <description>An account of the resource</description>
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              <elementText elementTextId="160845">
                <text>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.</text>
              </elementText>
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            <name>Creator</name>
            <description>An entity primarily responsible for making the resource</description>
            <elementTextContainer>
              <elementText elementTextId="160846">
                <text>Rao D.S.N.M.; Jasmin M.; Pandey M.; Almusawi M.; Ramadan G.M.; Senthil Kumar R.</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="48">
            <name>Source</name>
            <description>A related resource from which the described resource is derived</description>
            <elementTextContainer>
              <elementText elementTextId="160847">
                <text>E3S Web of Conferences, Vol-564</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="45">
            <name>Publisher</name>
            <description>An entity responsible for making the resource available</description>
            <elementTextContainer>
              <elementText elementTextId="160848">
                <text>EDP Sciences</text>
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            </elementTextContainer>
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          <element elementId="40">
            <name>Date</name>
            <description>A point or period of time associated with an event in the lifecycle of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="160849">
                <text>2024-01-01</text>
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            <name>Identifier</name>
            <description>An unambiguous reference to the resource within a given context</description>
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              <elementText elementTextId="160850">
                <text>&lt;a href="https://doi.org/10.1051/e3sconf/202456401007" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1051/e3sconf/202456401007&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85203812459&amp;amp;doi=10.1051%2Fe3sconf%2F202456401007&amp;amp;partnerID=40&amp;amp;md5=dedfc66e63f9763647c6824974304b44" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85203812459&amp;amp;doi=10.1051%2fe3sconf%2f202456401007&amp;amp;partnerID=40&amp;amp;md5=dedfc66e63f9763647c6824974304b44&lt;/a&gt;</text>
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          <element elementId="47">
            <name>Rights</name>
            <description>Information about rights held in and over the resource</description>
            <elementTextContainer>
              <elementText elementTextId="160851">
                <text>All Open Access; Gold Open Access</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="46">
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            <description>A related resource</description>
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              <elementText elementTextId="160852">
                <text>ISSN: 25550403</text>
              </elementText>
            </elementTextContainer>
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            <name>Format</name>
            <description>The file format, physical medium, or dimensions of the resource</description>
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            <description>A language of the resource</description>
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              <elementText elementTextId="160854">
                <text>English</text>
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              <elementText elementTextId="160856">
                <text>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 &amp;amp; Technology, tamil Nadu, Sivakasi, India</text>
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  <item itemId="18941" public="1" featured="0">
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          <description>The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/.</description>
          <elementContainer>
            <element elementId="50">
              <name>Title</name>
              <description>A name given to the resource</description>
              <elementTextContainer>
                <elementText elementTextId="51377">
                  <text>Conference Papers</text>
                </elementText>
              </elementTextContainer>
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      <name>Conference Paper</name>
      <description>Faculty Publications- Conference Papers</description>
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        <elementContainer>
          <element elementId="50">
            <name>Title</name>
            <description>A name given to the resource</description>
            <elementTextContainer>
              <elementText elementTextId="160829">
                <text>Analyses of the Power Flow through Distributed Generator based on Unsynchronized Measurements</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="49">
            <name>Subject</name>
            <description>The topic of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="160830">
                <text>Distributed generator; Microgrid; Non-conventional energy sources; Power flow</text>
              </elementText>
            </elementTextContainer>
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            <name>Description</name>
            <description>An account of the resource</description>
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              <elementText elementTextId="160831">
                <text>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.</text>
              </elementText>
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            <name>Creator</name>
            <description>An entity primarily responsible for making the resource</description>
            <elementTextContainer>
              <elementText elementTextId="160832">
                <text>Almoussawi Z.A.; Raju V.V.R.; Venkatasubramanian R.; Hariharan R.; Mundher Adnan M.</text>
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            <elementTextContainer>
              <elementText elementTextId="160833">
                <text>E3S Web of Conferences, Vol-564</text>
              </elementText>
            </elementTextContainer>
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            <name>Publisher</name>
            <description>An entity responsible for making the resource available</description>
            <elementTextContainer>
              <elementText elementTextId="160834">
                <text>EDP Sciences</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="40">
            <name>Date</name>
            <description>A point or period of time associated with an event in the lifecycle of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="160835">
                <text>2024-01-01</text>
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                <text>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</text>
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                <text>Seema, Christ University, Karnataka, Bengaluru, 560029, India; Singhal A., Christ University, Karnataka, Bengaluru, 560029, India</text>
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                <text>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</text>
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                <text>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.</text>
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                <text>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</text>
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                <text>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.</text>
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                <text>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&amp;amp;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</text>
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                <text>On near-perfect numbers with five prime factors</text>
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                <text>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.</text>
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                <text>Jeba F.S.; Roy A.; Saikia M.P.</text>
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                <text>De Gruyter Proceedings in Mathematics, pp. 207-220.</text>
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                <text>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</text>
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                <text>Energy Management System for EV Charging Infrastructure</text>
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          <element elementId="49">
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              <elementText elementTextId="160747">
                <text>Demand-Supply Balancing; Electric Vehicle (EV) Charging; Energy Management Systems (EMS); Real-Time Power Allocation; Renewable Energy Integration; Smart Grid</text>
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                <text>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.</text>
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                <text>Bhutkar G.; Kumar Y.; Subramani R.; Jothi E.; Valarmathy A.S.; Sherje N.; Tharmar S.</text>
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                <text>E3S Web of Conferences, Vol-591</text>
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                <text>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</text>
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                <text>Financial analytical usage of cloud and appropriateness of cloud computing for certain small and medium-sized enterprises</text>
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              <elementText elementTextId="160733">
                <text>adoption; Cloud computing; ICT; India; MSME; SMEs</text>
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                <text>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. &amp;amp; Berar E.S. College Ravinagar, Nagpur, India; Patnayak D., Department of Computer Science and Engineering, M. S. Engineering College, Bengaluru, India</text>
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                <text>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).</text>
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                <text>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</text>
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                <text>Advanced Materials for Next-Generation Energy Storage Devices: A Focus on Efficiency and Cost Reduction</text>
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                <text>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.</text>
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                <text>Chandrakala P.; Liz A.S.; Mane V.; Jeshurun S.B.; Sharma G.; Pardeshi P.R.; Senthil kumar R.</text>
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                <text>E3S Web of Conferences, Vol-591</text>
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                <text>ISSN: 25550403</text>
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                <text>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</text>
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                <text>Quantitative Structure-Activity Relationship Modeling for the Prediction of Fish Toxicity Lethal Concentration on Fathead Minnow</text>
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                <text>Aquatic Toxicity; Fathead Minnow; LC50; Lethal Concentrations; Pimephales promelas; QSAR</text>
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                <text>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.</text>
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                <text>Kavitha R.; Guru D.S.</text>
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                <text>Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) , Vol-15310 LNCS, pp. 34-46.</text>
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                <text>Springer Science and Business Media Deutschland GmbH</text>
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                <text>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</text>
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                <text>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.</text>
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                <text>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</text>
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