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Decision-Aid Applied to Rank Diverse Energy Storage Systems Technologies: A Methodology Using Information Fusion Concepts 1

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4th international conference on Optimization learning Algorithms and Applications

作者： Acioly Filho, Leonardo Veiga Cardoso Leite, Gabriel Matos Jimenez-Fernandez, Silvia Salcedo-Sanz, Sancho Divino Moreira Delgado, Carla Amor Gil Marcelino, Carolina Fed Univ Rio Janeiro UFRJ Inst Comp Rio De Janeiro Brazil Fed Univ Rio Janeiro UFRJ Syst & Comp Dept Rio De Janeiro Brazil Alcala Univ UAH Dept Signal Proc & Commun Madrid Spain

ISBN: (数字)9783031774324

ISBN: (纸本)9783031774317;9783031774324

the demand for electricity from renewable sources is increasingly becoming a necessity. Climate change and self-purchasing power demand is a greater nominal power from the public grid. In this way, hybrid microgrid systems (HMGS) - a type of smart grid - have become an alternative to meet power demand. One of the pieces of equipment that has become more essential in these systems is the energy storage system (ESS). Defining which technology is most suitable for a given microgrid is a hard task. this work presents the study and application of fourteen ESSs for a specific industrial electrical dispatch scenario maintained by an HMGS connected to the public grid network. the proposed mathematical modeling is solved by a swarm-evolutionary algorithm. the optimized values of cost, losses, and renewable factors are used as decision-making criteria to rank the ESS using the TOPSIS multi-criteria decision method. the results show that ESSs based on Vanadium Redox Flow can be a good alternative to recent Lithium-based technologies.

关键词： Electric Dispatch smart Grids Swarm evolutionary algorithms

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Proceedings of the 2022 IEEE Nigeria 4th international conference on Disruptive Technologies for Sustainable development, NIGERCON 2022

Proceedings of the 2022 IEEE Nigeria 4th International Confe...

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4th IEEE Nigeria international conference on Disruptive Technologies for Sustainable development, NIGERCON 2022

ISBN: (纸本)9781665479783

the proceedings contain 140 papers. the topics discussed include: machine learning models for predicting bank loan eligibility;semantic relation evaluation of data science articles using network of mention;effect of training algorithms and network architecture on the performance of multi-band ANN-based path loss prediction model;digital transformation in Nigeria: the prospects and challenges of the gig economy;assessing the vulnerabilities of internet users to cyber-attacks using their password login patterns;benefits of smart devices and grid-tied minigrids on the Nigerian electricity supply industry;development of Bluetooth enabled switching device for handoff selection in multiple operators enabled sim card system;a spatio-temporal non-concurrent data gathering and energy replenishment in wireless rechargeable sensor networks (ST-NCDR);tech mining analysis: renewable energy forecasting using artificial intelligence technologies;and proactive fuzzy-based backup channel selection scheme for spectrum handoff in cognitive radio networks.

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4th international Congress on Blockchain and Applications, BLOCKCHAIN 2022

4th International Congress on Blockchain and Applications, B...

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4th international Congress on Blockchain and Applications, BLOCKCHAIN 2022

ISBN: (纸本)9783031212284

the proceedings contain 42 papers. the special focus in this conference is on Blockchain and Applications. the topics include: Mitigation of Scaling Effects in NTF-Based Ticketing Systems;Digital Content Verification Using Hyperledger BESU;prototyping a smart Contract Application for Fair Reward Distribution in Software development Projects;blockchain in the Public Sector: An Umbrella Review of Literature;digital Identity Using Hyperledger Fabric as a Private Blockchain-Based System;cryptocurrencies, Systematic Literature Review on their Current Context and Challenges;blockchain Assisted Voting in Academic Councils;scalable and Transparent Blockchain Multi-layer Approach for smart Energy Communities;blockchain Consensus Algorithms: A Survey;assessing Blockchain Challenges in the Maritime Sector;decentralised Argumentation for Data Vetting in Blockchains;designing the Chain of Custody Process for Blockchain-Based Digital Evidences;the Devil Hides in the Model: Reviewing Blockchain and BFT Protocols;Blockchain-Based Business Process Management (BPM) for Finance: the Case of Loan-Application;objective-Aware Reputation-Enabled Blockchain-Based Federated learning;enhancing smart Contract Quality by Introducing a Continuous Integration Pipeline for Solidity Based smart Contracts;"Are You What You Claim to Be?" Attribute Validation with IOTA for Multi Authority CP-ABE;privacy-Preserving Energy Trade Using Double Auction in Blockchain Offline Channels;interoperable Industry 4.0 Plant Blockchain and Data Homogenization via Decentralized Oracles;towards Cost-Efficient Management for Power Purchase Agreements Using Blockchain Technology;a Model of Decentralised Distribution Line Using Layer 2 Blockchains;tokenizing the Portuguese Accounting Standards System;bibliometric Analysis on the Convergence of Artificial Intelligence and Blockchain;towards an Infrastructure Cost Model for Blockchain-Based Applications;a Benchmarking Study of Blockchain-Based Technology Implementation Co

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High-speed train automatic stopping control method based on deep reinforcement learning 4

High-speed train automatic stopping control method based on ...

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4th international conference on smart City Engineering and Public Transportation, SCEPT 2024

作者： Ma, Shengquan Shan, Wei Deng, Hai Xie, Xianyi Zhu, Wentao Jin, Lisheng Engineering Research Center CEEC Changchun Railway Vehicles Co. Ltd Jilin Changchun130062 China Locomotive and Vehicle Department China State Railway Group Co. Ltd. Beijing100000 China School of Vehicle and Energy Yanshan University Hebei Qinhuangdao066004 China

ISBN: (数字)9781510679825

ISBN: (纸本)9781510679818

Train Automatic Stop Control (TASC) system based on reinforcement learning(RL) is a crucial technology to improve self-driving performance for automatic train operation(ATO). Although significant progress has been achieved, existing RL-TASC systems still face challenges related to sparse rewards and lower control precision. In this paper, we design a train automatic stop strategy based on the Deep Q-Network (DQN) algorithm with both global rewards and single-step rewards to enhance the precision and training stability of RL-TASC systems. Initially, a single-point motion equation for the train was established and the state-action space was defined. Subsequently, a global reward function was designed based on stopping error. To address the challenges posed by sparse global rewards, which led to poor training effects, and imprecise stopping performance, a method for setting a single-step reward function based on expected velocity was proposed. Finally, through simulation experiments, the results showed that the improved control method could maintain the train stopping error within 0.05 meters. Comparing to the pre-improved model, the average value of stopping error decreased by 76.56% and the standard deviation of stopping error decreased by 67.74%, confirming the effectiveness of the improved method. this paper provides a high-precision and highly robust method for automatic stopping control in high-speed train ATO systems. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Errors

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Intrusion Detection in Wireless Sensor Networks using Machine learning 4

Intrusion Detection in Wireless Sensor Networks using Machin...

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4th international conference on Evolutionary Computing and Mobile Sustainable Networks, ICECMSN 2024

作者： Fares, Hajar Vibhute, Amol D. Mouniane, Yassine Bouijij, Habiba Equipe of Telecommunication and Detection Faculty of Science Abdelmalek Essaadi University Tetouan Morocco MH Pune411016 India Natural Resources and Sustainable Development Laboratory Faculty of Sciences Ibn Tofail University B.P 242 Kenitra Morocco ENSIAS SSLAB Mohammed v University in Rabat Rabat Morocco

Attackers are continuously enhancing their techniques to attack confidential data. thus, the classical security solutions based on cryptography and older detection systems must be revised, especially for a network dataset. Wireless sensor networks (WSN) consist of several smart devices distributed randomly in hostile areas with many restrictions, such as low operational time, short memory and minimal energy resources, and are susceptible to numerous attacks, such as Denial-of-Service (DoS). Recently, intrusion detection based on artificial intelligence models has provided an alternative and efficient solution with low computational resources. therefore, the present study provides an innovative approach for detecting DoS attacks in the network using machine learning. three machine learning methods, such as Support Vector Machine (SVM), K-Nearest Neighbor (KNN) and decision tree, were implemented with a well-known WSN-DS data specialized for DoS attacks. the performance of the models has been evaluated using standard metrics like accuracy, precision, F1-score and recall. the experimental results demonstrated the effectiveness of the KNN model after achieving the highest accuracy of 99.76% in DoS detection. thus, the present study's approach can be used in real-time intrusion detection. © 2025 the Authors. Published by Elsevier B.V.

关键词： Network intrusion

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Design of Hybrid Energy Storage and Management System in Hybrid Electric Vehicle Using Machine learning Approach 4

Design of Hybrid Energy Storage and Management System in Hyb...

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4th international conference on smart Electronics and Communication, ICOSEC 2023

作者： Kamalakannan, J. Reddy, K. Rajasekhara Kumar, N.M.G. Shafee, S.M. Dewangan, Kunal Kannan, V. Sri Sai Ram Institute of Technology Department of Mechanical Engineering Tamil Nadu Chennai600044 India Santhiram Engineering College Department of Electrical and Electronic Engineering Andhra Pradesh Nandyala518501 India Mohan Babu University Sree Vidyanikethan Engineering College Department of Electrical and Electronic Engineering Andhra pradesh 517102 India Sree Venkateswara College of Engineering Department of Mechanical Engineering Andhra pradesh 524316 India Kalinga University Department of Mechanical Engineering Chhattisgarh 492101 India K. Ramakrishnan College of Engineering Department of Physics Tamil Nadu Tiruchirapalli621112 India

ISBN: (纸本)9798350300888

the growing concern for reducing carbon emissions and the depletion Using fossil fuels has led to a considerable increase in the development of hybrid electric vehicles (HEVs) and their associated Controlling and storing energy systems. the blueprint of an efficient and effective System for storing and managing energy is crucial for the optimal performance of HEVs. In this context, this study proposes a novel strategies for designing mixed-source power storage and management system for HEVs using recurrent neural network (RNN)-based machine learning. the proposed approach involves the integration of RNN-based predictive models with the energy storage and management system of the HEV. the RNN-based predictive model is developed using historical driving data to predict the future driving pattern of the vehicle. the predicted driving pattern is then used to optimize the energy management system, which includes the control of the battery charging and discharging operations as well as the allocation of power between the battery and other power sources. Specifically, the suggested approach, simulations are carried out using a high-fidelity HEV model the actual world driving numbers. the end outcome of the simulations show that the proposed RNN-based energy storage and management system outperforms traditional rule-based control strategies in terms of energy efficiency, battery lifespan, and vehicle performance. In conclusion, the proposed approach of using RNN-based predictive models for designing hybrid energy storage and management systems in HEVs provides a promising avenue for the creation of more efficient and effective energy management systems for HEVs. this could lead to significant improvements in the fuel economy, reduced emissions, and extended battery lifespan of HEVs, thereby contributing to a greener and more sustainable future. © 2023 IEEE.

关键词： Recurrent neural networks

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Capacity Building Across Higher Education and Rural Youth in WINnovators Space 13th

Capacity Building Across Higher Education and Rural Youth in...

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13th international conference on Methodologies and Intelligent Systems for Technology Enhanced learning, mis4TEL 2023

作者： Pata, Kai Jüristo, Kristi Zapušek, Matej Leiba, Nathalie Pantic, Sanja Popovic Devedzić, Vladan Radenkovic, Sonja Devedzić, Mirjana Blagojević, Marija Milošević, Danijela School of Education Tallinn University Tallinn Estonia Ljubljana University Ljubljana Slovenia VITECO Catania Italy Institute Mihajlo Pupin Science and Technology Policy Research Center Belgrade Serbia University of Belgrade Belgrade Serbia Serbian Academy of Sciences and Arts Belgrade Serbia Faculty of Technical Sciences University of Kragujevac Kragujevac Serbia

ISBN: (纸本)9783031421334

this paper demonstrates the Design as a Hypothesis Framework for developing cross-university students and mentors, and rural youth (aged 18–30) and regional business ecosystems capacity building practice approaches to support sustainable development goals. We describe how a gamified learning and co-working WINnovators Space (https://***/ ) with e-learning materials for self-learning and mentored group work problem based challenges was developed to support university students’, mentors and the business partners’ engagement and building agency and capacity with regional rural young women. the Pilot study with the capacity building practice application validates the Design Hypothesis in three countries – Estonia (N = 35), Slovenia (N28), Serbia (N22) – involving young rural women, higher education students, academic and business mentors. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Sustainable development

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thematic Clustering of Green Banking Research Using Topic Modelling and Text Mining: A Machine learning Approach 4

Thematic Clustering of Green Banking Research Using Topic Mo...

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4th IEEE international conference on smart Technologies in Computing, Electrical and Electronics, ICSTCEE 2023

作者： Olasiuk, Hanna Kumar, Sanjeev Singh, Sudhanshu Nagpal, Gaurav Ganushchak, Tetiana Op Jindal Global University Jindal Global Business School Haryana Sonipat India Galgotias University School Of Business Uttar Pradesh Gautam Buddh Nagar India Birla Institute Of Technology And Science Pilani Department Of Management Pilani Campus Rajasthan India State University Of Trade And Economics Economic And Finance Enterprise Department 19 Kyoto st. Kyiv Ukraine

ISBN: (纸本)9798350384628

Green banking is pivotal in aligning the financial sector with sustainability objectives. It plays a crucial role in mitigating environmental risks and fostering responsible banking practices with the potential for long-term economic benefits. In the last decade, there has been substantial growth in research on green banking. However, a notable gap exists in comprehensive reviews that consolidate and clarify the core themes in this field. To bridge this gap, the study combines bibliometric analysis and structural topic modelling, delving into a dataset of 169 articles from Elsevier's Scopus database, covering 2012 to 2023. this study focuses on green banking, identifying key themes, scrutinising publication trends, and recognising influential journals. Notably, "Sustainability (Switzerland)"stands out as the leading source, contributing 9 articles, equivalent to around 5.3% of the total articles. these research findings offer valuable insights into the evolving landscape of green banking research. the outcomes of structural topic modelling reveal three distinct thematic clusters: i) Green banking and sustainability, ii) the role of technology and customer perceptions in green banking, and iii) Financial performance and regulations in green banking. Future green banking research will centre on assessing economic effects, enhancing transparency, and promoting sustainability through new financial tools and technology like blockchain and AI. the emphasis will be on policy frameworks, standardised metrics, and interdisciplinary research to encourage eco-friendly banking practices. these results enrich the comprehension of green banking by highlighting vital themes and crucial keywords. they hold significant relevance for diverse audiences, encompassing scholars, policymakers, financial institutions, and professionals in the industry. © 2023 IEEE.

关键词： Sustainable development

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Digital Making and Entrepreneurship. Imagine the Future 5th

Digital Making and Entrepreneurship. Imagine the Future

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5th international conference on smart learning ecosystems and regional development (SLERD)

作者： Buffardi, Annalisa Indire Naples Italy

ISBN: (纸本)9789811573835;9789811573828

the contemporary dynamics of cultural, social, and economic change address us toward a global recall to a new educational design, which should be able to enhance and create new competencies for the worker and the citizen of the future. this paper proposes a reflexion on the innovations that characterize the ongoing transformation and on the challenges that educative institutions have to face. In particular, we will focus on some twists among possible educative scenarios, based on the digital making and focused on the entrepreneurship competence framework, always with a sight to the connections between technological innovation and education. the paper recalls the laboratories of digital fabrication as expression of a dynamic that put together the cultural technological characteristics and the technical development that take shape on the new social and instances. Within this frame, the paper presents some results of the research carried out by the National Institute for Documentation, Innovation and Educational Research (INDIRE) within the 2014-2020 National Operational Programme Focusing on the development of the competencies to participate in the twenty-first century, the research analyzed ten case studies in the upper secondary school. this practice of teaching and learning is based on the increasing affordances of educational technologies combined with traditional science labs, and maximises the value and potential of digital culture by encouraging participation and creativity.

关键词： Digital making Entrepreneurship Work-based learning

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2022 4th international conference on Cybernetics and Intelligent System, ICORIS 2022

2022 4th International Conference on Cybernetics and Intelli...

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4th international conference on Cybernetics and Intelligent System, ICORIS 2022

ISBN: (纸本)9781665453950

the proceedings contain 116 papers. the topics discussed include: the evaluation model of the travel application as the impact of the covid-19 pandemic and its adaptation simulation;banyan: generating micro, small, and medium enterprises through augmented reality;systematic literature review on machine learning predictive models for indoor climate in smart solar dryer dome;web development of direct-to-consumer genetics testing;digitizing farmers' land data collection systems in Indonesia with the use of Tani Millenial apps;a diversity inventory monitoring system of riparian vegetation;systematic literature review: machine learning prediction model for covid-19 spreading;the technology behind genomic database;web-based application for searching the event organizers with provided audiences by using recommender system method;generalization of public key cryptosystem based on singular matrix using ring of integer modulo;air quality monitor in hospital based on fog and cloud computing;and elevating thematic branding through social media content: a visual concept of Kayutangan heritage's Instagram feed.

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