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Sustainable energy management in the AI era: a comprehensive analysis of ML and DL approaches

Computing 2025年第6期107卷 1-64页

作者： Javed, Haseeb Eid, Fatma El-Sappagh, Shaker Abuhmed, Tamer Department of Computer Science and Engineering College of Computing and Informatics Sungkyunkwan University Suwon Korea Republic of Technology Management Stony Brook University NY11794 United States Applied Artificial Intelligence College of Computing and Informatics Sungkyunkwan University Suwon Korea Republic of Faculty of Computer Science and Engineering Galala University Suez435611 Egypt Information Systems Department Faculty of Computers and Artificial Intelligence Benha University Banha13518 Egypt

This study comprehensively analyzes the application of innovative deep learning (DL) and machine learning (ML) techniques in smart energy management systems (EMSs), with an emphasis on load forecasting, demand response, and the development of smart energy sectors. The application of various ML and DL models were examined in over 200 studies from 2014 to 2024 in an electrical network's EMS to highlight the key benefits and advances made by each technology for the sustainable management systems in energy sector. The findings emphasize DL and ML models’ enhanced precision and predictive capabilities in load forecasting, their efficacy in enabling efficient demand response mechanisms, and their significance in supporting the development of smart energy sectors. Furthermore, recommendations are made based on the survey results to assist in incorporating these techniques into EMS frameworks, such as investment in data infrastructure, model training and validation, and collaboration between researchers, industry experts, and policymakers. The study also discusses the limitations identified in the literature, such as limited real-world implementations, challenges regarding quality and data availability, and the need for enhanced ML and DL model interpretability. Addressing these limitations can assist in increasing the application and efficacy of ML and DL techniques in EMSs, enabling a more efficient and sustainable energy landscape. Finally, this study facilitates researchers' exploration of ML and DL in energy management, highlighting relevant limitations, strengths, and alternative approaches associated with sustainable energy management. It also indicates potential future research directions for further investigation. © The Author(s) 2025.

关键词： Power management (telecommunication)

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Optimizing task scheduling in cloud environments: a hybrid golden search whale optimization algorithm approach

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Neural Computing and Applications 2025年第17期37卷 10851-10873页

作者： Acharya, Biswaranjan Panda, Sucheta Das, Satyabrata Majhi, Santosh Kumar Gerogiannis, Vassilis C. Kanavos, Andreas Department of Computer Science and Engineering Veer Surendra Sai University of Technology Odisha Burla India Bilaspur India Department of Digital Systems University of Thessaly Larissa Greece Department of Informatics Ionian University Corfu Greece

Managing fluctuating workloads and optimizing resource utilization in cloud environments pose significant challenges, particularly in fields requiring real-time data processing, such as healthcare. This paper introduces a novel hybrid metaheuristic technique, the Golden Search Whale Optimization Algorithm (GSWOA), specifically designed for scheduling independent dynamic biomedical data. GSWOA merges the strengths of Golden Search Optimization (GSO) and Whale Optimization Algorithm (WOA), optimizing numerical function optimization and achieving a balance between exploration and exploitation. The algorithm’s effectiveness was assessed using MATLAB by applying standard benchmark functions and further evaluated on a real-world biomedical dataset within the CloudSim environment. The performance evaluations demonstrate that GSWOA significantly outperforms existing metaheuristic and traditional scheduling techniques, achieving a 42.71% increase in resource utilization and a 14.17% reduction in makespan compared to conventional methods. These results highlight GSWOA’s potential to enhance scheduling efficiency substantially in cloud computing infrastructures, suggesting it is a powerful tool for complex task allocations. Future research will explore the scalability of GSWOA and its applicability across other data-intensive sectors. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

关键词： Scheduling algorithms

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IoT-Integrated Machine Learning for Real-Time Soil Nutrient Monitoring and Horticultural Crop Recommendations 10

IoT-Integrated Machine Learning for Real-Time Soil Nutrient ...

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10th IEEE Information technology International Seminar, ITIS 2024

作者： Wahid, Abdul Parenreng, Jumadi Mabe Aswandi Alwi, Ananta Dwi Prayoga Zain, Satria Gunawan Setialeksana, Wirawan Universitas Negeri Makassar Informatics and Computer Engineering Department Makassar Indonesia Politeknik Negeri Lhokseumawe Network Engineering Technology Study Program Lhokseumawe Indonesia

ISBN: (纸本)9798331521295

Farmers and agricultural newcomers often rely on intuition for plant nutrient management, leading to inaccuracies. This study presents a real-time soil nutrient monitoring and plant recommendation system using IoT and machine learning. The prototype integrates an ESP32 microcontroller, NPK sensor, soil pH sensor, and DHT11 with an application and a machine learning model. The model employs a hard voting method combining random forest, LightGBM, and support vector machine algorithms, deployed via Flask API and hosted on Vercel. Testing showed the system effectively monitors soil nutrients in real-time, with a pH sensor error margin of ±0.51 and NPK sensor readings displaying a non-linear increase in levels. The hard voting method achieved 98.5% accuracy, with recommendation processing taking less than one second (371.17ms) and CPU usage at 7%. System performance depends on internet speed, while recommendation accuracy is influenced by temperature and humidity. This system offers a practical solution for precision agriculture by optimizing nutrient application and plant recommendations. © 2024 IEEE.

关键词： pH sensors

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Addressing the Skills Gap in Microelectronics-Development and Validation of Reactive Response in the Project European Chips Skills Academy 30

Addressing the Skills Gap in Microelectronics-Development an...

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30th IEEE International Symposium for Design and technology in Electronic Packaging, SIITME 2024

作者： Gharaibeh, Ali Krammer, Oliver Cummings, Victoria Budapest University of Technology and Economics Faculty of Electrical Engineering and Informatics Department of Electronics Technology Budapest Hungary Brussels Office SEMI Europe Brussels Belgium

ISBN: (纸本)9798331539511

The European Chips Skills Academy (ECSA), funded by the European Union, began in October 2023 to address the skills and workforce gap in the microelectronics sector. Work Package 5 (WP5) focuses on creating specialised training content for the ECSA, targeting the current and future workforce in Europe's electronics and microelectronics industries. Initially, WP5 is producing training materials on soft skills, such as agile management and digital competences, to support remote workforce development in response to COVID19. Later, the project will expand to include curricula on digital skills, entrepreneurship, green initiatives, and specific microelectronics topics. The developed content will be tested and validated through a Test and Validation Plan, which details activities, timelines, and feedback tools. This plan ensures standardised training and visiting activities, along with uniform reporting by partners, facilitating the final Validation Report and recommendations for improving ECSA training. © 2024 IEEE.

关键词： Microelectronics

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Hand Sign Detection and Voice Conversion for the Hearing and Speech Impaired Using Convolutional Neural Networks 4th

Hand Sign Detection and Voice Conversion for the Hearing and...

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4th International Conference on Recent Trends in Machine Learning, IoT, Smart Cities, and Applications, ICMISC 2023

作者： Belgaum, Mohammad Riyaz Sowmya, Kurni Sireesha, Kuruva Priyanka, Tatagari Tony Vyshnavi, Uppara Uravakonda Department of Computer Science and Engineering G. Pullaiah College of Engineering and Technology Kurnool India Faculty of Computing and Informatics Multimedia University Cyberjaya Malaysia

ISBN: (纸本)9789819994410

Sign Language Recognition (SLR) tries to convert sign language into written or spoken form to enable communication between a deaf-mute person and a normal person. The task of communicating with disabled and impaired persons is extremely challenging, owing to its complexity and variety of hand motions that have a major societal impact. In order to depict sign language motions, SLR approaches are increasingly being used. These classification models are based on hand-crafted characteristics. Building reliable features that can adapt to the diverse range of hand signs is nonetheless challenging. To address this issue, the authors proposed a special 3D convolutional neural network (CNN) to ease the communication between normal and mute communities. Our proposed model eliminates the requirement to create features by automatically extracting discriminative spatial–temporal features from the actual livestream without any prior information. To improve performance, the 3D CNN is fed with multiple channels of video feeds that include colour, depth, trajectory information, joint body locations, and depth clues. We illustrate the proposed model's superiority to the conventional methods based on hand-crafted characteristics by testing them against a real dataset collected using a depth camera. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Audition

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A Novel Framework for Preserving Patient Health Record in IoT Healthcare 3

A Novel Framework for Preserving Patient Health Record in Io...

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3rd International Conference on Smart Technologies and Systems for Next Generation Computing, ICSTSN 2024

作者： Belgaum, Mohammad Riyaz Pothureddy, Priyanka Patnam, Sai Suraksha Gadda, Parimala Deepthi G. Pullaiah College of Engineering and Technology Department of Computer Science and Engineering Kurnool India Multimedia University Faculty of Computing and Informatics Cyberjaya Malaysia

ISBN: (纸本)9798350391565

As artificial intelligence, the Internet of Things (IoT), and next-generation mobile communication continue to evolve at a rapid pace, an increasingly popular application called the Internet of Medical Things (IoT) has arisen to provide ease and practicality in healthcare. Nonetheless, privacy preservation issues are brought up by accessing patient medical information inside the IoT framework, which calls for the creation of safe and private-preserving solutions. To address these issues, we provide in this study an IoT-Framework for preserving patient health record (FFPPHR) based on ELGamal blind signatures. We provide an enhanced privacy protection medical record searching technique (FFPPHR) based on the elliptic curve discrete logarithm problem (ECDLP) and point out security vulnerabilities in the current FFPPHR. Our security research shows that by utilizing the hard problem assumption of ECDLP, the FPMR guarantees identity privacy and accuracy. Furthermore, the use of Blind ECDSA Signatures improves data security. Performance assessments confirm the FFPPHR efficiency, and theoretical findings agree with simulations. The suggested FFPPHR approach yields lower time costs when compared to state-of-the-art techniques, which makes it a potential option for safe and effective medical record searches in IoT contexts. © 2024 IEEE.

关键词： Electronic health record

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Analysis of YouTube Video Comments with NLP Methods 16

Analysis of YouTube Video Comments with NLP Methods

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16th International Conference on Electronics, Computers and Artificial Intelligence, ECAI 2024

作者： Mironela, Pirnau Iustin, Priescu Mihaela, Priescu Catalina Claudiu, Pirnau Daniel, Ghiculescu Liviu 'Titu Maiorescu' University Faculty of Informatics Department of Informatics Bucharest Romania National University of Science and Technology Politehnica Bucharest Faculty of Automatic Control and Computer Science Bucharest Romania National University of Science and Technology Politehnica Bucharest Faculty of Industrial Engineering and Robotics Manufacturing Engineering Department Bucharest Romania

ISBN: (纸本)9798350371154

This study proposes methods that can be used to examine and interpret comments that users have made after watching videos on YouTube on a particular topic. YouTube tutorials are very popular among young people. They have become an important pillar in informal education, thus contributing to the rapid acquisition of skills and knowledge. Under these circumstances, we were interested in analysing the YouTube videos comments, knowing that the platform has a continuous increase in popularity, which is also due to the opportunities of sharing them. Since ChatGPT-themed YouTube videos have seen a significant surge in popularity since 2022, we were interested to analyse some videos that approach the topics of 'ChatGPT, AI clone, AI robot and Deep Learning.' © 2024 IEEE.

关键词： Deep learning

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Analysis of selected dielectric parameters of insulating liquids 23

Analysis of selected dielectric parameters of insulating liq...

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23rd International Scientific Conference on Electric Power engineering, EPE 2023

作者： Pluzek, Aleksandra Nagi, Lukasz Koziol, Michal Zygarlicka, Malgorzata Opole University of Technology Faculty of Electrical Engineering Automatic Control and Informatics Department of Electrical Power and Renewable Energy Opole Poland Opole University of Technology Faculty of Electrical Engineering Automatic Control and Informatics Department of Computer Science Opole Poland

ISBN: (纸本)9798350335934

During the last few years, there has been a growing interest in the topic of using natural or synthetic esters as an alternative to mineral oils in oil transformers due to the easier way to obtain them and their ability to exhibit better electrical properties. In addition, more and more researchers are describing in their work that doping esters with nanoparticles is capable of further improving these properties. Therefore, in the current work, it was decided to see what effect the addition of a hydrophobic carbon shell iron nanoparticle to ORLEN mineral oil and Midel 7131 synthetic ester would have on selected electrical parameters of the insulating fluid, i.e. breakdown voltage and electrical strength. © 2023 IEEE.

关键词： Nanoparticles

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Enhanced sensitivity via non-Hermitian topology

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Light(Science & Applications) 2025年第1期14卷 86-92页

作者： Midya Parto Christian Leefmans James Williams Robert M.Gray Alireza Marandi Department of Electrical Engineering California Institute of TechnologyPasadenaCA91125USA Physics and Informatics Laboratories NTT ResearchInc.SunnyvaleCA94085USA CREOL The College of Optics and PhotonicsUniversity of Central FloridaOrlandoFLUSA Department of Applied Physics California Institute of TechnologyPasadenaCA91125USA

Sensors are indispensable tools of modern life that are ubiquitously used in diverse settings ranging from smartphones and autonomous vehicles to the healthcare industry and space *** interfacing multiple sensors that collectively interact with the signal to be measured,one can go beyond the signal-to-noise ratios(SNR)attainable by the individual constituting *** techniques have also been implemented in the quantum regime,where a linear increase in the SNR has been achieved via using entangled *** similar lines,coupled non-Hermitian systems have provided yet additional degrees of freedom to obtain better sensors via higher-order exceptional *** recently,a new class of non-Hermitian systems,known as non-Hermitian topological sensors(NTOS)has been theoretically ***,the synergistic interplay between non-Hermiticity and topology is expected to bestow such sensors with an enhanced sensitivity that grows exponentially with the size of the sensor ***,we experimentally demonstrate NTOS using a network of photonic time-multiplexed resonators in the synthetic dimension represented by optical *** judiciously programming the delay lines in such a network,we realize the archetypal Hatano-Nelson model for our non-Hermitian topological sensing *** experimentally measured sensitivities for different lattice sizes confirm the characteristic exponential enhancement of *** show that this peculiar response arises due to the combined synergy between non-Hermiticity and topology,something that is absent in Hermitian topological *** demonstration of NTOS paves the way for realizing sensors with unprecedented sensitivities.

关键词： topology topological collective

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Piano Soundboard Analysis at Radiated Sound

Periodica polytechnica Electrical engineering and computer s...

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Periodica polytechnica Electrical engineering and computer science 2023年第3期67卷 291-299页

作者： Jenei-Kulcsár, Dóra Fiala, Péter Department of Networked Systems and Services Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Muegyetem rkp. 3. BudapestH-1111 Hungary

The piano is a complex musical instrument consisting of several components influencing vibration and sound production. By understanding the sound production mechanism virtual instruments can be created (physics-based sound synthesis) and the design and manufacturing of soundboards can be supported (virtual prototyping). Based on previous results published in the literature, a piano model was built and extended by a near field sound radiation model capable for physics-based sound synthesis. In this paper a simplified piano model is presented, including hammer strike and hysteretic felt models, coupled lossy string model and a 2D FEM based stiffened plate model for soundboard. This paper contains a parametric study where the soundboard parameters, such as its material characteristics and boundary conditions, are modified and their effect on the soundboard's modal behavior and the radiated sound is analyzed. Instead of using only musical (qualitative) descriptors, e.g. brightness or coloring, the piano sounds are characterized based on standard quantitative descriptors (e.g. harmonic ratio, spectral centroid). It is shown that these descriptors are determined by soundboard admittance, string characteristics and position on the soundboard;radiated sound from wooden soundboards can be characterized as harmonic for wide range of initial material descriptors;the string position is essential, and the perceived sound can differ significantly for different listening positions, even for the same harmonic decay pattern. © 2023 Budapest University of technology and Economics. All rights reserved.

关键词： Musical instruments

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