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6th IEEE International Conference and Workshop Obuda on Electrical and Power engineering, CANDO-EPE 2023

作者： Misljenovic, Nemanja Fekete, Kresimir Knezevic, Goran Pleskalt, Martin Josip Juraj Strossmayer University of Osijek Computer Science and Information Technology Osijek Faculty of Electrical Engineering Osijek Croatia

ISBN: (纸本)9798350328752

This paper strives to investigate the impact of integrating charging stations in the parking lot of the faculty building with an installed photovoltaic power plant (PV) and battery energy storage system (BESS) to maximize social welfare. The integration of charging stations in the parking lot of business buildings would enable savings for owners of electric vehicles (EVs) who live in residential buildings and have to charge their EVs at public charging stations. On the other hand, by integrating charging stations into the parking lot, business buildings could reduce their electricity costs because they use EVs as BESS. Accordingly, the optimization model was developed in the GAMS environment by applying MILP formulation. The research was conducted according to the current market conditions and for a newly proposed market model for charging and discharging batteries of EVs in the parking lot of business buildings. The results show the need to find the optimal prices for charging and discharging batteries of EVs by applying multi-level optimization. © 2023 IEEE.

关键词： Energy management systems

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A Unified Decision-Making Technique for Analysing Treatments in Pandemic Context

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computers, Materials & Continua 2022年第11期73卷 2591-2618页

作者： Fawaz Alsolami Abdullah Saad Al-Malaise Alghamdi Asif Irshad Khan Yoosef B.Abushark Abdulmohsen Almalawi Farrukh Saleem Alka Agrawal Rajeev Kumar Raees Ahmad Khan Department of Computer Science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Information Technology Babasaheb Bhimrao Ambedkar UniversityLucknow226025Uttar PradeshIndia Department of Computer Science and Engineering Babu Banarasi Das UniversityLucknow226028India

The COVID-19 pandemic has triggered a global humanitarian disaster that has never been seen *** experts,on the other hand,are undecided on the most valuable treatments of therapy because people ill with this infection exhibit a wide range of illness indications at different phases of ***,this project aims to undertake an experimental investigation to determine which treatments for COVID-19 disease is the most effective and *** research analysis is based on vast data gathered from professionals and research journals,making this study a comprehensive *** solve this challenging task,the researchers used the HF AHPTOPSIS Methodology,which is a well-known and highly effective MultiCriteria Decision Making(MCDM)*** technique assesses the many treatment options identified through various research papers and guidelines proposed by various countries,based on the recommendations of medical practitioners and *** review process begins with a ranking of different treatments based on their effectiveness using the HF-AHP approach and then evaluates the results in five different hospitals chosen by the authors as *** also perform robustness analysis to validate the conclusions of our *** a result,we obtained highly corroborative results that can be used as a *** results suggest that convalescent plasma has the greatest rank and priority in terms of effectiveness and demand,implying that convalescent plasma is the most effective treatment for SARS-CoV-2 in our *** also has the lowest priority in the estimation.

关键词： AHP-TOPSIS hesitant fuzzy sets SARS-CoV-2 healthcare sector preventive drugs

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FireBot - An Autonomous Surveillance Robot for Fire Prevention, Early Detection and Extinguishing 15

FireBot - An Autonomous Surveillance Robot for Fire Preventi...

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15th International Conference on computer and Automation engineering, ICCAE 2023

作者： Balen, Josip Damjanovic, Davor Maric, Petar Vdovjak, Kresimir Arlovic, Matej Martinovic, Goran Josip Juraj Strossmayer University of Osijek Faculty of Electrical Engineering Computer Science and Information Technology Osijek Osijek Croatia

ISBN: (纸本)9798350396225

Every year, fire is responsible for numerous deaths, as well as huge material losses. Therefore, prevention and early detection of fire have become a priority for society, as well as the main research and development issue for many scientists and various industries. This paper describes our work in the development of FireBot, an autonomous surveillance robot. The Firebot is equipped with modern technologies and state-of-the-art navigational and computer vision methods that enable autonomous navigation, obstacle avoidance, video surveillance, fire prevention and detection, and fire extinguishing. It utilizes both infrared thermal (IRT) and RGB cameras paired with a modern convolutional neural network (CNN) for fault and fire detection, as well as various other sensors for analyzing air composition, processing of surrounding sounds, and detecting irregularities in its environment in general. The best performing CNN was implemented and tested in real-world environments for fire detection purposes, the results of which are presented in this paper. A state-of-the-art SLAM algorithm paired with LiDAR and a depth camera is used for mapping and navigation. The architecture presented in this paper, along with all functionalities planned for future work, represents an innovative autonomous surveillance system that will make a great contribution in the field of fire prevention and detection. © 2023 IEEE.

关键词： Fires

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Utilization of HEVC ChaCha20-Based Selective Encryption for Secure Telehealth Video Conferencing

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computers, Materials & Continua 2022年第1期70卷 831-845页

作者： Osama S.Faragallah Ahmed I.Sallam Hala S.El-sayed Department of Information Technology College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Computer Science and Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Electrical Engineering Faculty of EngineeringMenoufia UniversityShebin El-Kom32511Egypt

Coronavirus(COVID-19)is a contagious disease that causes exceptional effect on healthcare organizationsworldwide with dangerous impact on medical services within the *** of the fast spread of COVID-19,the healthcare facilities could be a big source of disease ***,healthcare video consultations should be used to decrease face-to-face communication between clinician and *** video consultations may be beneficial for some COVID-19 conditions and reduce the need for faceto-face contact with a potentially positive patient without *** conditions are like top clinicians who provide remote consultations to develop treatment methodology and follow-up remotely,patients who consult about COVID-19,and those who have mild symptoms suggestive of the COVID-19 *** consultations are a supplement to,and not a substitute for,telephone *** may also form part of a broader COVID-19 distance care strategy that contains computerized screening,separation of possibly infectious patients within medical services,and computerized video-intensive observing of their intensive care that helps reduce ***,the spread of the COVID-19 virus helps to expand the use of video healthcare consultations because it helps to exchange experiences and remote medical consultations,save costs and health procedures used to cope with the pandemic of the COVID-19 virus,and monitor the progress of treatment plans,moment by moment from a distance with precision,clarity and *** this perspective,this paper introduces a high-efficiency video coding(HEVC)ChaCha20-based selective encryption(SE)scheme for secure healthcare video *** proposed HEVC ChaCha20-based SE scheme uses the ChaCha20 for encrypting the sign bits of the Discrete Cosine Transform(DCT)and Motion Vector Difference(MVD)in the HEVC entropy *** main achievement of HEVC ChaCha20-based SE scheme is encrypting the most sensitive video bits with keeping low

关键词： Telehealth HEVC cahcha20 video conferencing

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Inferring Global Exponential Stability Properties using Lie-bracket Approximations 63

Inferring Global Exponential Stability Properties using Lie-...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Weber, Marc Gharesifard, Bahman Ebenbauer, Christian Rwth Aachen University Faculty of Electrical Engineering and Information Technology AachenD-52074 Germany University of California Electrical & Computer Engineering Department Los Angeles United States

ISBN: (纸本)9798350316339

In the present paper, a novel result for inferring uniform global, not semi-global, exponential stability in the sense of Lyapunov with respect to input-affine systems from global uniform exponential stability properties with respect to their associated Lie-bracket systems is shown. The result is applied to adapt dither frequencies to find a sufficiently high gain in adaptive control of linear unknown systems, and a simple numerical example is provided to support the theoretical findings. © 2024 IEEE.

关键词： Adaptive control systems

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Towards Content-Optimized Selection of Video Spatiotemporal Resolution for HTTP Adaptive Video Streaming 66

Towards Content-Optimized Selection of Video Spatiotemporal ...

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66th International Symposium ELMAR, ELMAR 2024

作者： Kuna, Renato Suljug, Jelena Rimac-Drlje, Snjezana Computer Sciences and Information Technology Osijek J. J. Strossmayer University of Osijek Faculty of Electrical Engineering OsijekHR-31000 Croatia

ISBN: (纸本)9798350375411

In adaptive video streaming systems, selecting optimal spatial and temporal resolutions for a given bitrate is crucial when encoding various video representations on the server side. Previous research has primarily focused on adjusting spatial resolution, leaving optimization in the time-space domain as an open research question. The research aims to identify the optimal spatiotemporal resolution for a given bitrate, contingent on the complexity of the video sequence. Given the extensive requirements of such research, this paper presents preliminary findings based on five sequences of differing complexity. For low-complexity sequences, the optimal approach is to first reduce the temporal resolution from 120 fps to 25 fps, followed by a reduction in spatial resolution. Conversely, for sequences with medium and high complexity, it is preferable to decrease the spatial resolution first and then the temporal resolution. The appropriate bitrates for these resolution adjustments are also influenced by the complexity of the video signal. The encoded sequences, along with their objective and subjective quality evaluations will serve as a foundation for future AI-based modeling efforts. © 2024 IEEE.

关键词： HTTP

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Validation of Machine Learning-Based Lane Lines Detection Methods Using Different Datasets

Validation of Machine Learning-Based Lane Lines Detection Me...

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2023 IEEE Zooming Innovation in Consumer Technologies Conference, ZINC 2023

作者： Jukic, Grgur Vranjes, Mario Vajak, Denis Vranjes, Denis TTTech Auto CEE Osijek Croatia Faculty of Electrical Engineering Computer Science and Information Technology Osijek Osijek Croatia

ISBN: (纸本)9798350347722

Advanced Driver Assistance System (ADAS) uses various sensors that exist in the vehicle to collect information about the vehicle and its surroundings. One of the most commonly used ADASs is the one designed to recognize driving lane lines. In this paper, analysis, and validation of freely available state-of-The-Art deep learning-based lane lines detection (LLD) methods are done using three different well-known datasets: CULane, TuSimple, and LLAMAS. To perform the validation, as part of this research, two converters of lane line label formats were made. Converters allow testing models that have been previously trained on a dataset that uses different lane line label formats so that their performances can be verified on other datasets with different lane line format types. The experimental results show that the adaptability of the model to the change of the dataset depends on the architecture used as the basis of the model for the LLD, and the similarity of the training set of the initially used dataset and the new, *** dataset. All tested models showed shortcomings when tested on images from datasets on which they were not trained, which confirms that there is still no model that we can confidently say achieves high performance in all possible scenarios. © 2023 IEEE.

关键词： Advanced driver assistance systems

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A Multi - Aspect Evaluation of DL-based SQLi Attack Detection Models 22

A Multi - Aspect Evaluation of DL-based SQLi Attack Detectio...

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22nd IEEE/ACIS International Conference on Software engineering Research, Management and Applications, SERA 2024

作者： Leelaprute, Pattara Kase, Yuki Amasaki, Sousuke Aman, Hirohisa Yokogawa, Tomoyuki Kasetsart University Department of Computer Engineering Faculty of Engineering Bangkok Thailand Okayama Prefectural University Department of Systems Engineering Soja Japan Center for Information Technology Ehime University Matsuyama Japan

ISBN: (纸本)9798350391343

CONTEXT: Web applications are exposed to malicious accesses through the Internet. SQL injection (SQLi) attacks are still a typical threat to web application providers. Although recent studies proposed deep learning-based SQLi attack detection models with high performance, those studies were not evaluated under the same conditions. Crucial aspects other than the predictive performance were also overlooked. OBJECTIVE: To evaluate SQLi attack detection models from multi-aspects related to its operation. METHOD: Three aspects, namely, predictive performance, detection speed, and operation costs, were applied to deep learning-based SQLi attack detection models. RESULTS: No DL-based model beaten a conventional machine learning-based model, Random Forests. CONCLUSION: Researchers must evaluate DL-based SQLi attack detection models with conventional ones with hyper-parameter tuning. © 2024 IEEE.

关键词： Contrastive Learning

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A fatigue assessment method based on attention mechanism and surface electromyography

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Internet of Things and Cyber-Physical Systems 2023年第1期3卷 112-120页

作者： Dang, Yukun Liu, Zitong Yang, Xixin Ge, Linqiang Miao, Sheng College of Computer Science & Technology Qingdao University Qingdao266071 China School of Information and Control Engineering Qingdao University of Technology Qingdao266520 China School of Computer Science Columbus State University GA31907 United States Faculty of Environmental Engineering The University of Kitakyushu Kitakyushu808-0135 Japan

Surface electromyography (sEMG) signals can be used to quantitatively assess muscle fatigue, thereby directly and objectively reflecting the functional state of neuromuscular activity. Effective fatigue diagnosis can prevent muscle damage, thereby improving the safety of rehabilitation exercise. Traditional fatigue diagnosis has certain limitations, including strong subjectivity and poor accuracy. This paper designs a sEMG signals acquisition circuit and collects the sEMG signals of the upper limb biceps brachii and triceps brachii in the force-relaxation state in a dual-channel form. Muscle fatigue classification assessment using Dynamic Time Warping-K Nearest Neighbor (DTW-KNN) and three deep learning algorithms. The experimental results show that compared with traditional machine learning algorithms, deep learning algorithm can achieve higher accuracy and time efficiency. In addition, this study introduces an attention mechanism to dynamically and reasonably assign network weights to achieve high level feature learning. The Attention-Long Short-Term Memory (Attention Based LSTM) neural network achieves 93.5% assessment accuracy with a time overhead of only 3.73s, allowing for real-time assessment of muscle fatigue. © 2023 The Authors

关键词： Long short-term memory

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Analysis of Bio-Inspired approaches and Social Media Analytics in Twitter datasets for Misinformation Detection 1

Analysis of Bio-Inspired approaches and Social Media Analyti...

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1st International Conference on Advances in Electrical, Electronics and Computational Intelligence, ICAEECI 2023

作者： Nicholas, Neomi Nelin Nirmalrani, V. Sathyabama Institute of Science and Technology Faculty of Computer Science and Engineering Chennai India Sathyabama Institute of Science and Technology Department of Information Technology Chennai India

ISBN: (纸本)9798350342796

Bio-inspired algorithms, such as those with regard to collective intelligence and evolutionary algorithms have been increasingly used in social media analytics in recent years. These algorithms have been shown to be effective in many areas, such as sentiment analysis, community identification, and misinformation detection. This paper explains the underlying principles and features of the most recent bio-inspired techniques. The effectiveness of bio-inspired algorithms for the sentiment analysis categorization on Twitter datasets is studied. In this paper, several social media spam detection techniques that are currently in use are tabulated, and detailed study on the use of social media analytics and bio-inspired algorithms to detect misinformation in social media datasets is performed. The findings of the proposed analysis throws light into the efficiency of these algorithms and gaps for more research, which is inevitable to further improve their performance and robustness for misinformation detection. © 2023 IEEE.

关键词： bio inspired algorithms misinformation detection optimization social media analytics twitter datasets

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