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Condition Monitoring and Maintenance Management with Grid-Connected Renewable Energy Systems

computers, Materials & Continua 2022年第8期72卷 3999-4017页

作者： Md.Mottahir Alam Ahteshamul Haque Mohammed Ali Khan Nebras M.Sobahi Ibrahim Mustafa Mehedi Asif Irshad Khan Department of Electrical and Computer Engineering(ECE) King Abdulaziz UniversityJeddah 21589Saudi Arabia Advance Power Electronics Research Lab Department of Electrical EngineeringJamia Millia IslamiaNew Delhi 110025India Department of Electrical Power Engineering Faculty of Electrical Engineering and CommunicationBrno University of TechnologyBrno 61600Czech Republic Center of Excellence in Intelligent Engineering Systems(CEIES) King Abdulaziz UniversityJeddah 21589Saudi Arabia Computer Science Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah 21589Saudi Arabia

The shift towards the renewable energy market for carbon-neutral power generation has encouraged different governments to come up with a plan of *** with the endorsement of renewable energy for harsh environmental conditions like sand dust and snow,monitoring and maintenance are a few of the prime *** problems were addressed widely in the literature,but most of the research has drawbacks due to long detection time,and high misclassification *** to overcome these drawbacks,and to develop an accurate monitoring approach,this paper is motivated toward the understanding of primary failure concerning a grid-connected photovoltaic(PV)system and highlighted along with a brief overview on existing fault detection *** on the drawback a data-driven machine learning approach has been used for the identification of fault and indicating the maintenance unit regarding the operation and maintenance ***,the system was tested with a 4 kWp grid-connected PV system,and a decision tree-based algorithm was developed for the identification of a *** results identified 94.7%training accuracy and 14000 observations/sec prediction speed for the trained classifier and improved the reliability of fault detection nature of the grid-connected PV operation.

关键词： Fault detection machine learning fault ride through

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Exact Statistics and Tight Approximations for RIS-Assisted Communications in Generalized Fading Environments 100

Exact Statistics and Tight Approximations for RIS-Assisted C...

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100th IEEE Vehicular technology Conference, VTC 2024-Fall

作者： Luna Alvarado, Maria Cecilia Rafael Nogueira Da Silva, Carlos Simmons, Nidhi Sofotasios, Paschalis C. Cotton, Simon L. Yacoub, Michel Daoud University of Campinas Wireless Technology Laboratory School of Electrical and Computer Engineering Campinas Brazil Federal University of Triângulo Mineiro Department of Electrical Engineering Uberaba Brazil Belfast United Kingdom Khalifa University C2PS and 6G Center Department of Computer and Information Engineering Abu Dhabi United Arab Emirates

ISBN: (纸本)9798331517786

Reconfigurable Intelligent Surfaces (RISs) are considered a key candidate technology for next-generation 6G wireless systems, promising to extend network coverage, enhance spectral efficiency, and effectively mitigate interference. RISs will achieve this by controlling the propagation environment, enabled by carefully altering the reflective properties of their elements. In this context, this work presents a general framework for deriving the exact probability density function (PDF) and higher-order moments of the signal-to-ratio (SNR) in a RIS system, considering the direct transmission and RIS-assisted links from source to destination. Recognizing the analytical challenges associated with obtaining exact statistics for RIS-assisted systems, which persist in both common and more generalized fading models, the proposed contribution is realized with the aid of the suitable α-μ fading model. To that end, we derive accurate approximations for the κ-μ and the extended η-μ distributions, which constitute effective and versatile multipath fading models. Based on this, the achieved results are virtually indistinguishable from those obtained through simulations for various environmental settings. This renders the proposed framework a valuable tool for evaluating the performance of RIS systems, particularly in terms of the corresponding average symbol error rate (ASER). Tractable closed-form asymptotic expressions are also derived and utilized to provide a deeper understanding of the system's behavior. © 2024 IEEE.

关键词： Multipath fading

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Evaluating the Effectiveness of Multi-Factor Authentication for Preventing Cyber Attacks 15

Evaluating the Effectiveness of Multi-Factor Authentication ...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Venkatasubramanian, D. Goyal, Saumya Ezhilarasan, G. Sharma, Yogesh K. Vijayalakshmi, V.J. Garg, Prateek Prince Shri Venkateshwara Padmavathy Engineering College Department of Information Technology Chennai127 India Quantum University Research Center Quantum University India School of Engineering and Technology Electrical and Electronics Engineering Karnataka Bangalore India Vishwakarma Institute of Technology Department of Computer Engineering Pune India Karpagam Academy of Higher Education Department of Electrical and Electronics Engineering Coimbatore641021 India Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura140417 India

ISBN: (纸本)9798350370249

this article affords an outline of the effectiveness of multi-thing authentication (MFA) for stopping cyber attacks. MFA is an authentication procedure that combines or greater elements or traits to verify the identification of a character or user earlier than granting them access. This sort of authentication is increasingly being used to protect non-public data and to prevent unauthorized get admission to systems and services. Diverse studies have been carried out to evaluate the effectiveness of MFA as compared to traditional authentication methods, like passwords. The outcomes of these studies show that after properly implemented, MFA may be a powerful method to shield towards cyber-assaults. This article also presents satisfactory practices for implementing MFA to maximize its effectiveness and discusses risks related to using MFA. © 2024 IEEE.

关键词： Authentication Character Diverse Effectiveness Elements Identification Presents Protect

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Novel intelligent predictive networks for analysis of chaos in stochastic differential SIS epidemic model with vaccination impact

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Mathematics and computers in Simulation 2024年 219卷 251-283页

作者： Anwar, Nabeela Ahmad, Iftikhar Kiani, Adiqa Kausar Shoaib, Muhammad Raja, Muhammad Asif Zahoor Department of Mathematics University of Narowal 51600 Pakistan Department of Mathematics University of Gujrat 50700 Pakistan Future Technology Research Center National Yunlin University of Science and Technology 123 University Road Section 3 Yunlin Douliou64002 Taiwan Yuan Ze University AI Center Taoyuan320 Taiwan Department of Electrical and Computer Engineering COMSATS University Islamabad Attock Campus Attock43600 Pakistan

In this paper, stochastic predictive computing networks are exploited to investigate the dynamics of the SIS with vaccination impact based epidemic model (SISV-EM) represented by nonlinear systems of stochastic differential equations (SDEs) by exploitation of artificial neural networks (ANNs) with the backpropagated Levenberg-Marquardt technique (BLMT) i.e., (ANNs-BLMT) to approximate the solution behavior. The stochastic nonlinear SISV-EM is governed with three classes: susceptible, infectious, and vaccinated populations. The referenced or target datasets for ANNs-BLMT are constructed by employing Euler-Maruyama (EM) scheme for solving stochastic differential systems in case of sufficiently various nonlinear SISV-EM scenarios by varying the percentage of vaccination for newly born, the coefficient of transmission, the natural mortality rates, the infectious rates of recovery, the rate at which vaccinated people lose their immunity, the rate of death caused by disease, the proportion of vaccinated against susceptible and the white noise in the environment. Based on arbitrary training, testing, and validation samples from the referenced dataset, the ANNs-BLMT provides an approximate solution for the stochastic nonlinear SISV-EM, with significant correlations to the referenced results. Exhaustive simulation-based results using error histograms, mean square errors, and regression analyses further demonstrate that the proposed ANNs-BLMT is efficient, consistent, and accurate for solving SISV-EM. © 2023 International Association for Mathematics and computers in Simulation (IMACS)

关键词： Mean square error

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Smart Home Connectivity: Identifying the Best IoT Application Layer Protocols 14

Smart Home Connectivity: Identifying the Best IoT Applicatio...

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14th International Conference on computer and Knowledge engineering, ICCKE 2024

作者： Shahinzadeh, Hossein Azani, Zohreh Al-Hameedawi, Sundus F. Mohammadali Zanjani, S. Mehrabani-Najafabadi, Saiedeh Hemmati, Mohammadreza Department of Electrical Engineering Amirkabir University of Technology Tehran Iran Department of Electrical Engineering University of Shahrekord Shahrekord Iran Smart Microgrid Research Center Najafabad Branch Islamic Azad University Najafabad Iran Faculty of Computer Engineering Najafabad Branch Islamic Azad University Najafabad Iran

ISBN: (纸本)9798331511272

The Internet of Things (IoT) bridges the physical and digital worlds by utilizing sensors, actuators, communication technologies, computing power, and data analytics to enable precise monitoring and control of the surrounding environment. Leveraging the data derived from IoT can lead to optimal decision-making for system management. In smart homes, IoT has ushered in a new generation known as connected homes. Given the diverse range of protocols available for the IoT application layer, selecting the appropriate protocol to connect smart home devices (based on their specific requirements) to the internet gateway is a critical issue. This paper first identifies the key factors influencing the choice of application layer protocols in smart homes. Then, it examines and analyzes some of the most commonly used IoT application layer protocols, including HTTP, MQTT, CoAP, WebSocket, DDS, XMPP, AMQP, STOMP, LwM2M, Zigbee, Z-Wave, BLE, and 6LoWPAN, based on these factors. Finally, recommendations for protocol selection in various sections of a smart home are provided based on the analysis conducted. ©2024 IEEE.

关键词： Smart homes

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Evolutional Codes: Novel Efficient Graph Data Representation for Mobile Edge Computing

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IEEE Transactions on Network Science and engineering 2024年第1期11卷 1387-1397页

作者： Sun, Elaine Y.-N. Wu, Hsiao-Chun Huang, Scott C.-H. Kuan, Yen-Cheng Yung, Chi National Tsing Hua University Department of Electrical Engineering Hsinchu30013 Taiwan Louisiana State University School of Electrical Engineering and Computer Science Baton RougeLA70803 United States Yuan Ze University Innovation Center for Ai Applications Chungli32003 Taiwan International College of Semiconductor Technology Hsinchu30010 Taiwan

To transmit big graph data emerging from prevalent social networks and biological networks over mobile devices has become challenging nowadays. Since graphs are usually represented by the associated adjacency matrices or graph data structures, dynamic node (vertex) re-ordering to reflect the nodes' real relations (for example, spatial or structural relations) is desirable in practice but impossible for these two existing graph-representation methods. Lately, we proposed a novel evolutional coding technique, which can restructure graph data dynamically, flexibly, and efficiently for transmission among mobile devices. Memory efficiency, in terms of number of memory storage units, is a crucial performance measure for mobile edge computing. To select the optimal graph-representation strategy for arbitrary graph data, we define a new graph-taxonomy metric dependent on the edge density (edges per node) in this work. According to our newly defined graph-taxonomy metric, one can choose the optimal graph-representation solution among the three aforementioned methods in terms of required memory-storage space for any application. Pertinent theorems and proofs for the underlying comparative studies on graph representation are presented in this article. © 2013 IEEE.

关键词： Digital storage

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Research on the quantum photonic convolutional neural network for artificial intelligence-based healthcare system security

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Optical and Quantum Electronics 2024年第2期56卷 1-18页

作者： Sita Kumari, K. Shivaprakash, G. Arslan, Farrukh Alsafarini, Maram Y. Ziyadullayevich, Avlokulov Anvar Haleem, Sulaima Lebbe Abdul Arumugam, Mahendran Velagapudi Ramakrishna Siddhartha Engineering College Andhra Pradesh Vijayawada India Department of Electronics and Instrumentation Engineering Ramaiah Institute of Technology Bengaluru India School of Electrical and Computer Engineering Purdue University West Lafayette United States Department of Electrical Engineering University of Engineering and Technology Lahore Lahore Pakistan Computer Science Department Zarqa University Zarqa Jordan The Department of Audit Tashkent Institute of Finance Tashkent Uzbekistan Department of Information and Communication Technology Faculty of Technology South Eastern University of Sri Lanka Oluvil Sri Lanka Center for Transdisciplinary Research Saveetha Dental College Saveetha Institute of Medical and Technical Science Chennai India

Artificial intelligence (AI) has quickly integrated into contemporary healthcare organizations, providing a variety of purposes, including identifying diseases, individualized therapy suggestions, and healthcare picture analytics. However, substantial security concerns are raised by the extensive use of AI in Healthcare, particularly regarding the reliability and confidentiality of private patient information. In this paper, we offer quantum photonic convolutional neural network (QP-CNN) to strengthen AI-based healthcare systems' security to overcome this crucial issue. To create an innovative convolutional neural network (CNN) architecture capable of handling the quantum computations that can endanger the safety of patient data, we analyze the special aspects of quantum photonics in this study. We explore the basic ideas behind quantum photonic computation and show how they can be used to develop strong cryptography methods for securing healthcare information during transport and preservation. Initially, we gather the dataset and preprocess the collected data using min–max normalization to remove duplicates and guarantee homogeneity. The subsequent stage involves utilizing principal component analysis (PCA) to extract pertinent features from the preprocessed data. We simulate trials with Python 3.11 software to assess the efficiency of the suggested algorithm. In terms of accuracy (82.67%), precision (82%), recall (75.84%), and F1-score (85%), specificity (95.67%), AUC (93.15%). Our results show that the QP-CNN technique outperforms other methods in effectiveness. Our suggested QP-CNN technique provides exciting outcomes for the security of an artificial intelligence-based healthcare system. © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

关键词： Healthcare Patient evaluation Prediction Quantum photonic convolutional neural network (QP-CNN) Security

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Information Centric Networking Based Cooperative Caching Framework for 5G Communication Systems

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computers, Materials & Continua 2024年第9期80卷 3945-3966页

作者： R.Mahaveerakannan Thanarajan Tamilvizhi Sonia Jenifer Rayen Osamah Ibrahim Khalaf Habib Hamam Department of Computer Science and Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical SciencesChennai602105India Department of Computer Science and Engineering Panimalar Engineering CollegeChennai600123India Department of Computer Science and Engineering Sathyabama Institute of Science and TechnologyChennai600119India Department of Solar Energy Al-Nahrain Research Center for Renewable EnergyAl-Nahrain UniversityJadriyaBaghdad64074Iraq Faculty of Engineering Universitéde MonctonNew BrunswickE1A3E9Canada Hodmas University College Mogadishu521376Somalia Bridges for Academic Excellence Tunis1002Tunisia School of Electrical Engineering University of JohannesburgAuckland ParkJohannesburg2006South Africa

The demands on conventional communication networks are increasing rapidly because of the exponential expansion of connected multimedia *** light of the data-centric aspect of contemporary communication,the information-centric network(ICN)paradigm offers hope for a solution by emphasizing content retrieval by name instead of *** 5G networks are to meet the expected data demand surge from expanded connectivity and Internet of Things(IoT)devices,then effective caching solutions will be required tomaximize network throughput andminimize the use of ***,an ICN-based Cooperative Caching(ICN-CoC)technique has been used to select a cache by considering cache position,content attractiveness,and rate *** findings show that utilizing our suggested approach improves caching regarding the Cache Hit Ratio(CHR)of 84.3%,Average Hop Minimization Ratio(AHMR)of 89.5%,and Mean Access Latency(MAL)of 0.4 *** a framework,it suggests improved caching strategies to handle the difficulty of effectively controlling data consumption in 5G *** improvements aim to make the network run more smoothly by enhancing content delivery,decreasing latency,and relieving *** improving 5G communication systems’capacity tomanage the demands faced by modern data-centric applications,the research ultimately aids in advancement.

关键词： Information-centric networking caching schemes 5G communication non-negative matrix factorization(NMF) weighted clustering algorithm

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Harris Hawks Optimizer with Graph Convolutional Network Based Weed Detection in Precision Agriculture

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computer Systems Science & engineering 2023年第8期46卷 1533-1547页

作者： Saud Yonbawi Sultan Alahmari T.Satyanarayana Murthy Padmakar Maddala E.Laxmi Lydia Seifedine Kadry Jungeun Kim Department of Software Engineering College of Computer Science and EngineeringUniversity of JeddahJeddahSaudi Arabia King Abdul Aziz City for Science and Technology RiyadhKingdom of Saudi Arabia Chaitanya Bharathi Institute of Technology HyderabadTelanganaIndia Department of Civil Engineering Vignan’s Institute of Information and Technology(A)DuvvadaVisakhapatnamAP530049India Department of Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India Department of Applied Data Science Noroff University CollegeKristiansandNorway Artificial Intelligence Research Center(AIRC) College of Engineering and Information TechnologyAjman UniversityAjmanUnited Arab Emirates Department of Electrical and Computer Engineering Lebanese American UniversityByblosLebanon Department of Software Kongju National UniversityCheonan31080Korea

Precision agriculture includes the optimum and adequate use of resources depending on several variables that govern crop *** agriculture offers a novel solution utilizing a systematic technique for current agricultural problems like balancing production and environmental *** control has become one of the significant problems in the agricultural *** traditional weed control,the entire field is treated uniformly by spraying the soil,a single herbicide dose,weed,and crops in the same *** more precise farming,robots could accomplish targeted weed treatment if they could specifically find the location of the dispensable plant and identify the weed *** may lessen by large margin utilization of agrochemicals on agricultural fields and favour sustainable *** study presents a Harris Hawks Optimizer with Graph Convolutional Network based Weed Detection(HHOGCN-WD)technique for Precision *** HHOGCN-WD technique mainly focuses on identifying and classifying weeds for precision *** image pre-processing,the HHOGCN-WD model utilizes a bilateral normal filter(BNF)for noise *** addition,coupled convolutional neural network(CCNet)model is utilized to derive a set of feature *** detect and classify weed,the GCN model is utilized with the HHO algorithm as a hyperparameter optimizer to improve the detection *** experimental results of the HHOGCN-WD technique are investigated under the benchmark *** results indicate the promising performance of the presented HHOGCN-WD model over other recent approaches,with increased accuracy of 99.13%.

关键词： Weed detection precision agriculture graph convolutional network harris hawks optimizer hyperparameter tuning

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A Survey of Artificial Hummingbird Algorithm and Its Variants: Statistical Analysis, Performance Evaluation, and Structural Reviewing

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Archives of computational Methods in engineering 2025年第1期32卷 269-310页

作者： Hosseinzadeh, Mehdi Rahmani, Amir Masoud Husari, Fatimatelbatoul Mahmoud Alsalami, Omar Mutab Marzougui, Mehrez Nguyen, Gia Nhu Lee, Sang-Woong Institute of Research and Development Duy Tan University Da Nang Viet Nam School of Medicine and Pharmacy Duy Tan University Da Nang Viet Nam Future Technology Research Center National Yunlin University of Science and Technology Yunlin Taiwan Department of Communication and Computer Engineering Faculty of Engineering Cihan University-Erbil Kurdistan Region Iraq Department of Electrical Engineering College of Engineering Taif University Taif21944 Saudi Arabia Department of Computer Engineering College of Computer Science King Khalid University Abha61413 Saudi Arabia School of Computer Science Duy Tan University Da Nang Viet Nam Pattern Recognition and Machine Learning Lab Gachon University 1342 Seongnamdaero Sujeonggu Seongnam13120 Korea Republic of

In the last few decades, metaheuristic algorithms that use the laws of nature have been used dramatically in numerous and complex optimization problems. The artificial hummingbird algorithm (AHA) is one of the metaheuristic algorithms that was invented in 2022 based on the foraging and migration behavior of the hummingbird for modeling and solving optimization problems. The algorithm initially starts with an initial random population of solutions. It then uses iterative processes and hummingbird position updates to balance exploration and exploitation toward the most optimal solutions. This paper has a detailed and extensive review of the AHA algorithm considering the aspects of hybrid, improved, binary, multi-objective, and optimization problems. In addition, a wide range of applications of AHA in various fields such as feature selection, image processing, scheduling, Internet of Things, classification, clustering, financial and economic issues, forecasting, wireless sensor networks, and many engineering challenges are explored. The statistical and numerical results showed that the AHA algorithm with deep learning methods, Levy flight, and opposition-based learning had the best performance. Also, the AHA algorithm is most widely used in solving multimodal optimization problems and continuous functions. © The Author(s) under exclusive licence to International center for Numerical Methods in engineering (CIMNE) 2024.

关键词： Optimization

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