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Electrical, Electronic and Information sciences (eStream), Open Conference of

作者： Saloua Lagnaoui Khaoula Boumais Saad El Fallah Zakariae En-Naimani Khalid Haddouch Dalius Matuzevičius Laboratory Engineering Systems and Applications ENSA Sidi Mohamed Ben Abdellah University Fez Morocco Laboratory AI Data Science and Emerging Systems Sidi Mohammed ben Abdallah University ENSA Fez Morocco Systems and Sustainable Environment Laboratory Faculty of Engineering Sciences Private University of Fez Fez Morocco Laboratory Computer Science AI and Cyber Security ENSET University of Hassan II Casablanca Mohammedia Morocco Department of Electronic Systems Faculty of Electronics Vilnius Gediminas Technical University Vilnius Lithuania

ISBN: (数字)9798350352412

ISBN: (纸本)9798350352429

Convolutional Neural Networks are instrumental in artificial intelligence, especially in image processing, where their ability to autonomously learn hierarchical features has led to significant breakthroughs. However, the success of these models is intricately tied to the judicious choice of hyperparameters, which include the configuration of convolutional layers, activation functions, and kernel initialization methods. This research explores kernel initialization methods in Convolutional Neural Network models, seven diverse initialization methods (Glorot Uniform, Ones initialization, Zero initialization, Constant initialization, Random initialization, HeNormal initialization, and Orthogonal initialization) are comprehensively compared. The primary objective is to showcase the sensitivity of Convolutional Neural Networks to these various initialization techniques. The study not only aims to reveal the nuanced impact of kernel initialization but also introduces an adaptive method to enhance model performance. By delving into the intricacies of initialization methods, this research contributes to the improvement of Convolutional Neural Networks effectiveness, especially in critical applications like Plant Disease classification.

关键词： Training Plant diseases Adaptation models Sensitivity Neural networks Convolutional neural networks Kernel

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Applying Deep Learning to Autonomous Vehicles: A Survey 4

Applying Deep Learning to Autonomous Vehicles: A Survey

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4th International Conference on Artificial Intelligence and Big Data, ICAIBD 2021

作者： Ren, Jing Gaber, Hossam Al Jabar, Sk Sami Ontario Tech University Dept. of Electrical and Computer Engineering OshawaON Canada Ontario Tech University Faculty of Energy Systems and Nuclear Science OshawaON Canada

ISBN: (纸本)9780738131702

Autonomous vehicles will revolutionize the future automotive industry by reducing or eliminating human errors and increasing vehicle safety. The design of autonomous vehicles will bring together many modern technologies such as control, computer vision, path planning, sensor fusion and fault diagnosis. Although traditional algorithms can be used to implement these technologies, in the last decade, deep learning has been proposed to challenge traditional algorithms and excels in many applications and research areas. Deep learning has shown its significant use in the design and operation of autonomous vehicles. In this paper, we will review the application of deep learning in five major research areas of autonomous vehicles i.e. path planning, control, computer vision, sensor fusion and fault diagnosis. Recent advances of the deep learning in autonomous vehicles will be reviewed and discussed. © 2021 IEEE.

关键词： Failure analysis

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Protecting Image-classifiers from Adversarial Attacks using an Adaptive Clustering Buffer-based Detection

Protecting Image-classifiers from Adversarial Attacks using ...

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Artificial Intelligence and Internet of Things (GCAIoT), IEEE Global Conference

作者： Abdullah Alshanqiti Ali Ismail Dumlu Abdullah Ahmed Aeshah Alsughayyir Faculty of Computer and Information Systems Islamic University (IU) Madinah KSA College of Computer Science and Engineering Taibah University (TU) Madinah KSA

ISBN: (纸本)9798350309850

Endeavoring to defend image classifier models from query-based adversarial attacks, in this paper, we present a novel buffer-based defender that is adaptively optimized using an unsupervised neural network clustering technique. The proposed defender can be considered as a complementary and independent firewall protector that is integrable with almost all available defense methods. We empirically evaluate the detection accuracy besides the performance of the buffer on three image classifier models (MLP, VGG19, and ResNet50) against various white/black-box attack methods. Results revealed that our buffer-based detection method could relatively improve the protection rate without sacrificing the overall performance.

关键词： Self-organizing feature maps Adaptation models Firewalls (computing) Perturbation methods Gaussian noise Semantics Neural networks

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The performance of circularly polarized phased sub-array antennas for 5G laptop devices investigating the radiation effects

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Progress in Electromagnetics Research C 2021年 110卷 267-283页

作者： Mahmoud, Korany R. Baz, Abdullah Alhakami, Wajdi Alhakami, Hosam Montaser, Ahmed M. Department of Electronics and Communications Faculty of Engineering Helwan University Cairo Egypt National Telecommunications Regulatory Authority Ministry of Communication and Information Technology Giza Egypt Computer Engineering Department College of Computer and Information Systems Umm Al-Qura University Makkah Saudi Arabia Department of Computer Science College of Computer and Information Technology Taif University P. O. Box 11099 Taif21944 Saudi Arabia Department of Computer Science College of Computer and Information Techonogy Umm Al-Qura University Makkah21955 Saudi Arabia Electrical Engineering Department Sohag University Sohag Egypt

In this paper, the performance of circularly polarized (CP) adaptive sub-arrays integrated into 5G laptop device is investigated in the presence of a whole-body human phantom model. In addition, the radiation effect of the steered beam patterns has been analyzed by calculating the specific absorption rate distribution and temperature rise. In this target, a single-feed CP antenna element has been firstly designed to resonate at 28GHz with high realized gain and radiation efficiency. Then, 4 subarrays have been constructed in a rectangular configuration with four-elements for each sub-array. To let the study more realistic, a complete human model is considered to investigate the radiation effects. The measured reflection coefficient and realized gain results of the designed antenna element are found to be -30 dB and 7.82 dB, respectively, in the assigned frequency band. Likewise, the antennas sub-arrays have approximately kept the same impedance matching attitude with high insertion loss of -22 dB and a realized gain and radiation efficiency of 16.85 dB and 86%, respectively, on average. Furthermore, the sub-arrays scan patterns and coverage efficiency have been studied considering the existence of the human body in different scenarios. Regarding the RF exposure, the results show that the resultant maximum values of specific absorption rate and power density do not exceed 1.52 W/kg and 3.5W/m2, respectively, whereas the maximum exposure temperature in such a case is less than 2.8°C after 30 minutes and decreases to 0.5°C after a penetration depth of 3mm which reflects the possibility of safe use. © 2021, Electromagnetics Academy. All rights reserved.

关键词： Radiation efficiency

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Examining the Use of Non-fungible Tokens (NFTs) as a Trading Mechanism for the Metaverse 1

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29th European systems, Software and Services Process Improvement, EuroSPI 2022

作者： Yilmaz, Murat Hacaloğlu, Tuna Clarke, Paul Department of Computer Engineering Engineering Faculty Gazi University Ankara Turkey Metaverse Research and Development Laboratory Gazi University Ankara Turkey Department of Information Systems Engineering Atilim University Ankara Turkey School of Computing Dublin City University Dublin Ireland Lero the Science Foundation Ireland Research Centre for Software Limerick Ireland

ISBN: (数字)9783031155598

ISBN: (纸本)9783031155581

The notion of a metaverse seems hard to define but encourages the impression that it can be considered as a new virtual metaphysical landscape that somehow goes beyond our geographical locations and understanding (i.e., independent of time and space). Based on virtual reality, augmented reality, and blockchain, it is envisioned as an independent but extended world that is planned to be a digital virtuality entrenched not only in our old habits such as gaming and entertainment but also in virtual asset trade. In particular, trading is a pillar of the virtual economy, and auction houses will be crucial for Metaverse trading. This exploratory study examines the possibility of using an auction environment to improve the trading capabilities in a virtual universe. We investigate the cases of creating a virtual auction house with the potential of social trading of virtual assets with crypto coins and bartering. To this end, we built a virtual auction house and tested it initially using a set of scenarios. Our preliminary findings suggest that creating a virtual trading environment would be beneficial as an environment for buying and selling virtual assets and exploring their consequences. © 2022, Springer Nature Switzerland AG.

关键词： Augmented reality

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Optimal Participation of Virtual Power Plants in the Electricity Market Considering Multi-Energy systems

Optimal Participation of Virtual Power Plants in the Electri...

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International Conference on Smart Energy systems and Technologies (SEST)

作者： Mohammad Sadegh Javadi Gerardo J. Osório André S. Parente João P.S. Catalão Institute for Systems and Computer Engineering Technology and Science (INESC TEC) Porto Portugal Portucalense University Infante D. Henrique (UPT) / REMIT Porto Portugal Faculty of Engineering University of Porto Porto Portugal Research Center for Systems and Technologies (SYSTEC) Advanced Production and Intelligent Systems Associate Laboratory (ARISE) Faculty of Engineering University of Porto Porto Portugal

The growth and modernization of the power system are the keys to enabling economic progress. The deregulation, added to the new emerging production technologies, conversion, and storage, triggered a change in the way of managing the power system worldwide. This work analyses the optimal dispatch of a virtual power plant (VPP) with active participation in the electricity market, considering multi-energy systems. The objective is to minimize the total operating cost of the power plant. The power plant is fed by two external networks: electrical and natural gas. The VPP is composed of energy production, conversion, and storage technologies, also considering the integration of a wind turbine and a set of electric vehicles (EVs). In addition to the Grid-to-Vehicle (G2V) charging, the advantage of Vehicle-to-Grid (V2G) technology is also verified, which allows the injection of power into the grid through the vehicles and Vehicle-to-Load (V2L) technology, enabling EVs to contribute to the satisfaction of the electrical load, reducing the costs, showing the advantages as well of EVs' integration in the VPP under analysis.

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Generation of High-Quality Relevant Judgments through Document Similarity and Document Pooling for the Evaluation of Information Retrieval systems

Generation of High-Quality Relevant Judgments through Docume...

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International Conference on Software, Knowledge Information, Industrial Management and Applications (SKIMA)

作者： Minnu Helen Joseph Sri Devi Ravana Department of Information Systems Faculty of Computer Science & Information Technology University of Malaya Malaysia Faculty of Computer Science Engineering & Technology School of Computing Asia Pacific University of Technology and Innovation (APU) Malaysia

ISBN: (纸本)9781665493352

The Information Retrieval System Evaluation have carried out through Cranfield-paradigm in which the test collections provide the foundation of the evaluation process. The test collections consist of document corpus, topics, and a set of relevance judgements. The relevant judgements are the documents which retrieved from the test collections based on the topics. The precision of the evaluation process is based on the number of relevant documents in the relevant judgement list called qrels. This paper presents a study on how methodologies like pooling and document similarity helps to generate more relevant documents into the relevance judgments set in order to increase the accuracy of the evaluation process. The initial results have shown that combination of pooling with document similarity performs better compared to base clustering or classification.

关键词： Information retrieval Software Information management

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Efficient and High-quality Recommendations via Momentum-incorporated Parallel Stochastic Gradient Descent-Based Learning

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IEEE/CAA Journal of Automatica Sinica 2021年第2期8卷 402-411页

作者： Xin Luo Wen Qin Ani Dong Khaled Sedraoui MengChu Zhou the School of Computer Science and Technology Dongguan University of TechnologyDongguan 523808 Hengrui(Chongqing)Artificial Intelligence Research Center Department of Big Data Analyses TechniquesCloudwalkChongqing 401331China the School of Computer Science and Technology Chongqing University of Posts and TelecommunicationsChongqing 400065 Chongqing Engineering Research Center of Big Data Application for Smart Cities Chongqing Institute of Green and Intelligent TechnologyChinese Academy of SciencesChongqing 400714China the Department of Computer and Information Science City College of Dongguan University of TechnologyDongguan 523419China the Department of Electrical and Computer Engineering Faculty of Engineeringand Center of Research Excellence in Renewable Energy and Power SystemsKing Abdulaziz UniversityJeddah 21481Saudi Arabia the Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewarkNJ 07102 USA the Center of Research Excellence in Renewable Energy and Power Systems King Abdulaziz UniversityJeddah 21481Saudi Arabia

A recommender system(RS)relying on latent factor analysis usually adopts stochastic gradient descent(SGD)as its learning ***,owing to its serial mechanism,an SGD algorithm suffers from low efficiency and scalability when handling large-scale industrial *** at addressing this issue,this study proposes a momentum-incorporated parallel stochastic gradient descent(MPSGD)algorithm,whose main idea is two-fold:a)implementing parallelization via a novel datasplitting strategy,and b)accelerating convergence rate by integrating momentum effects into its training *** it,an MPSGD-based latent factor(MLF)model is achieved,which is capable of performing efficient and high-quality *** results on four high-dimensional and sparse matrices generated by industrial RS indicate that owing to an MPSGD algorithm,an MLF model outperforms the existing state-of-the-art ones in both computational efficiency and scalability.

关键词： Big data industrial application industrial data latent factor analysis machine learning parallel algorithm recommender system(RS) stochastic gradient descent(SGD)

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Cryptocurrency-Enabled Energy Trading in Micro-Grid Using Blockchain Technology

Cryptocurrency-Enabled Energy Trading in Micro-Grid Using Bl...

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Cyber Resilience (ICCR), International Conference on

作者： Ahsan Waseem Mohd Bilal Abhishek Bhardwaj M Saad Bin Arif Taher M. Ghazal Department of Electrical Engineering Aligarh Muslim University Aligarh India Computer Science Department Faculty of Information Science and Technology Centre for Cyber Physical Systems Khalifa University Center for Cyber Security Universiti Kebangsaan Malaysia (UKM) Bangi Selangor Malaysia

ISBN: (数字)9798350394962

ISBN: (纸本)9798350394979

This article explores energy trading in grid-connected microgrids powered by renewable sources, utilizing cryptocurrency and blockchain technology. Through net metering, it emphasizes the proactive roles of prosumers and consumers in managing excess energy. The study investigates peer-to-peer energy transfers with blockchain-based cryptocurrencies, high-lighting their advantages in affordability, trade efficiency, and openness. Real-world case like LO3 Energy and Power Ledger are examined to address regulation, scalability, and cybersecurity concerns. The paper explores blockchain-enabled energy trade revolutionizing the industry, enhancing community resilience, accelerating renewable energy adoption, and reducing reliance on outdated technologies.

关键词： Renewable energy sources Shape Scalability Smart contracts Regulation Blockchains Cryptocurrency

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Role of 5G and 6G Technologies in Metaverse, Quality of Service Challenges and Future Research Directions

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IEEE Network 2024年

作者： Adil, Muhammad Abulkasim, Hussein A., Ali H., Song A., Farouk Z., Jin University at Buffalo The State University of New York Department of Computer Science and Engineering BuffaloNY14260 United States University of Science and Technology of Fujairah College of Engineering and Technology Fujairah United Arab Emirates New Valley University Faculty of Science El-Kharga72511 Egypt Asia Pacific University School of Technology Malaysia University of Maryland Department of Information Systems Baltimore County BaltimoreMD21250 United States Hurghada University Faculty of Computers and Artificial Intelligence Department of Computer Science Hurghada83523 Egypt South China University of Technology School of Future Technology Guangdong Guangzhou511442 China University at Buffalo Department of Computer Science and Engineering BuffaloNY14260 United States

The popularity of Metaverse technology has grown in recent years due to its ability to connect real-world and virtual-world objects to establish a social ecology paradigm, in which various applications collaborate towards a common objective, such as the digital transformation of the world. However, this emerging technology faces significant challenges in terms of security, scalability, interoperability, and communication, which can impact Quality of Service (QoS) metrics like latency, throughput, handover with mobility, communication cost, platform integration, and data privacy, etc. The literature contains several survey papers to familiarize readers, students, researchers, and enterprise stakeholders with these challenges. However, we did not find a single comprehensive review paper that discusses how security, scalability, interoperability, and communication affect the QoS metrics in the Metaverse, especially in the context of 5G and 6G technologies. Therefore, our aim is to provide an overview of the latest literature by considering the requirements of Metaverse technology in the era of futuristic communication technologies such as 5G and 6G technologies. Moreover, we identified and analyzed the contributions and limitations of current literature to highlight the key research challenges that require the attention of the research community to ensure their redressal. Furthermore, we acknowledge that this is the first survey paper that provides an overview of the QoS metrics of future 5G and 6G-enabled Metaverse technology under one umbrella. © 1986-2012 IEEE.

关键词： 5G mobile communication systems

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