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1st IEEE International Interdisciplinary Humanitarian Conference for Sustainability, IIHC 2022

作者： Shaheen, H. MohanRaj, A. Shobha Rani, Meesala Sreeraj, S. Amutha, M. Kannadhasan, S. UWL-RAK Faculty of Computing and Engineering United Arab Emirates Sri Eshwar College of Engineering Department of Computer Science and Engineering Coimbatore India MVJ College of Engineering Department of Computer Science and Engineering Bangalore India Sri Krishna College of Engineering and Technology Department of Computer Science and Engineering Coimbatore India Hindusthan College of Engineering Technical Campus Department of Computer Science and Engineering Coimbatore India Study World Collge of Engineering Department of Electronics and Communication Engineering Coimbatore India

ISBN: (纸本)9781665456876

The motto behind the keenness of urban areas has become unmistakable in current cities because of the rise of installed and associated shrewd gadgets, frameworks, and innovations. It is possible to connect every object to the Internet. As a result, in the impending Internet of Things era, the 'Internet of Vehicles-IoV' will play a critical role in newly developed dazzling urban communities. The IoV can possibly address different traffic and street wellbeing issues successfully to forestall deadly crashes. In any case, a specific test of IoV, particularly in 'Vehicle-to-Vehicle' as well as 'Vehicle-to-Infrastructure' communications, guarantees quick, in order to transmit securely and exact performance of the information. The above effort is modifying Blockchain innovation for continuous application called RTA to meet 'Vehicle-to-Every thing-V2x' communications problems in order to overcome these challenges. As a result, the main goal of the study is to develop a Blockchain-based IoT framework for establishing communication security and creating a completely decentralized computing platform. Research methodology used here is divided into two major sections. In the part 1 presented below, authors discuss the traceability and optimization over Merkle trees. The second section deals with implementing an actual blockchain with our optimized Merkle tree as the underlying technology to represent a distributed trust based ledger. © 2022 IEEE.

关键词： Blockchain

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Virtual Twin Analytics: Advancing IoT Security through AI-Powered Software Informatics

Virtual Twin Analytics: Advancing IoT Security through AI-Po...

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Software, Systems and Information technology (SSITCON), International Conference on

作者： S. Nanthini Upma Jain Renuka Arora Rishu Bhatia Kruti Sutaria Harshal Patil Department of Computer Science and Engineering Saveetha School of Engineering Chennai India Department of Computer Science and Engineering Graphic Era Deemed to be University Dehradun India Department of Computer Science and Engineering Jagannath University Haryana India Department of Electronics and Communication Engineering Ganga Institute of Technology and Management Haryana India Faculty of Engineering and Technology Parul institute of Engineering and Technology Gujarat India School of Computer Science and Engineering Uttar Pradesh India

ISBN: (数字)9798350352931

ISBN: (纸本)9798350352948

The Internet has grown in importance and impact over the years, causing people to become more reliant on it. The Internet has evolved into a major vector for cybercrime because to its ever-increasing user base. Over the last decade, the number of these computing systems—including desktops, laptops, smartphones, and the Internet of Things (IoT)—has skyrocketed. Among them, cell phones are practically integral to modern life. The popularity of web-based assaults has skyrocketed with the exponential growth in the number of individuals using the Internet. These web-based assaults are increasingly being combatted by security corporations. Unfortunately, new forms of these assaults are appearing all the time, making it hard for older security measures to stay up. Artificial intelligence (AI) is a source of optimism in the current cybersecurity landscape, offering a potential solution to the ever-changing digital dangers. The fast development of AI over the last decade has given rise to this optimism, because it is now impacting the expansion of every industry. With AI bringing so many advantages in every field, online security is one sector that just cannot afford to ignore it. This planned effort’s work represents an advance in that direction. Critical online security issues have been the focus of this proposed work’s study, which aims to address these issues using AI. Web security issues for desktop and mobile devices have been addressed in the proposed work. The planned work’s contributions to online security are as follows: The ‘MalCrawler’ web crawler is a targeted tool for finding and exploring the web. This crawler makes it easy to gather websites, particularly ones that are harmful. It does a better job of collecting dangerous websites than a typical crawler. Additionally, it is built to circumvent the evasion strategies used by rogue websites. The crawler’s ability to gather webpages—particularly dangerous ones—in order to provide datasets for ML-based analysis a

关键词： Analytical models Computational modeling Crawlers Vectors Digital twins Internet of Things Security Artificial intelligence Informatics Context modeling

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High Gain and Efficiency Triple U-shaped Slots Microstrip Patch Antenna for 5G Applications 3

High Gain and Efficiency Triple U-shaped Slots Microstrip Pa...

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3rd International Conference on Computing and Information technology, ICCIT 2023

作者： Almohammedi, Akram A. Raad, Ahmad Darshi, Sam Shepelev, Vladimir Mohd Yusof, Mohammad Hafiz Balfaqih, Mohammed Karabük University Electrical & Electronics Department Karabük Turkey South Ural State University Automobile Transportation Department Chelyabinsk Russia Karabük University Electrical & Electronics Engineering Department Karabük Turkey Indian Institute of Technology Ropar Department of Electrical Engineering Punjab India Universiti Teknologi Mara Faculty of Computer and Mathematical Sciences Perak Malaysia University of Jeddah Department of Computer and Network Engineering Jeddah23218 Saudi Arabia

ISBN: (纸本)9798350321487

The 28 GHz band is a frequency band that has been allocated for use in 5G mobile communication networks. It is part of the millimeter wave spectrum, which is a range of frequencies between 30 GHz and 300 GHz. This study proposes and investigates the 28 GHz 5G networks. A modified single element patch antenna with three grooved U-shaped holes is shown and is used to indicate a high gain and Efficiency for 28 GHz 5G antenna. The proposed antenna consists of the radiation element on a RTRogers 5880 laminate and is actuated by a microstrip feedline. The proposed work includes the most desirable characteristics, such as small size, light weight, low-cost fabrication and wide operation up to 1.4 GHz (27.1 - 28.5 GHz). The proposed antenna design also offers a high efficiency up to 89.73 %, high gain up to 8.14 dBi, and return loss up to -30 dB, resulting in attractive performance. The results obtained show that the antenna is a viable candidate for 5G applications at 28 GHz. © 2023 IEEE.

关键词： 5G mobile communication systems

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Input Impedance and Performance Analysis of Series-Fed Microstrip Patch Array Antenna

Input Impedance and Performance Analysis of Series-Fed Micro...

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2022 International Conference on Power, Energy and Innovations, ICPEI 2022

作者： Phakaew, Thipamas Pongthavornkamol, Tiwat Thaiwirot, Wanwisa Chalermwisutkul, Suramate The Sirindhorn International Thai-German Graduate School of Engineering King Mongkut's U. of Technology North Bangkok Bangkok Thailand National Electronics and Computer Technology Center National Science and Technology Development Agency Pathum Thani Thailand King Mongkut's U. of Technology North Bangkok Faculty of Engineering Department of Electrical and Computer Engineering Bangkok Thailand

ISBN: (数字)9781665460194

ISBN: (纸本)9781665460194

This paper presents input impedance and performance analysis of a series-fed 2×1 patch array antenna operating at 9.55 GHz. Effects of substrate's dielectric constant and height are discussed. Input impedance is optimized step by step from a single patch to a 2×1 array. Low impedance patches provide higher gain at the cost of increased capacitive coupling between the elements. Consequently, input impedance at the operating frequency is affected by the higher resonant mode. Finally, a technique to mitigate the coupling between the patches is proposed. With the proposed technique, the higher resonant mode can be eliminated so that the 2×1 array can easily be matched and operates with the correct patch array mode. © 2022 IEEE.

关键词： Microstrip antennas

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Lag Synchronization and Lag H∞ Synchronization for Multiweighted Coupled Reaction-Diffusion Neural Networks Suffering Topology Attacks

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IEEE Transactions on Control of Network Systems 2025年

作者： Wang, Jin-Liang Zhao, Xin-Yu Ren, Shun-Yan Huang, Tingwen Tiangong University Tianjin Key Laboratory of Autonomous Intelligence Technology and Systems School of Computer Science and Technology Tianjin300387 China Tiangong University School of Electronics & Information Engineering Tianjin300387 China University of Electronic Science and Technology of China School of Mechanical and Electrical Engineering Chengdu611731 China Shenzhen University of Advanced Technology Faculty of Computer Science and Control Engineering Shenzhen518055 China

This paper mainly discusses two kinds of coupled reaction-diffusion neural networks (CRNN) under topology attacks, that is, the cases with multistate couplings and with multiple spatial-diffusion couplings. On one hand, by adopting state feedback control scheme, the problem of the lag synchronization for the multistate coupled CRNN is addressed. Moreover, the influences of external disturbances for the lag synchronization of the CRNN with multistate couplings are also taken into consideration. On the other hand, several lag and lag H∞ synchronization conditions for CRNN with multiple spatial-diffusion couplings are derived under the help of the Kronecker product and the state feedback control method. Finally, two numerical examples are provided to verify the correctness of the derived criteria. © 2014 IEEE.

关键词： State feedback

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A Study on 1D-Point Cloud Using Through-Wall mm Wave Radar for Human Pose Estimation

A Study on 1D-Point Cloud Using Through-Wall mm Wave Radar f...

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International Electrical engineering Congress (iEECON)

作者： Kritthee Phaisiri Chainarong Kittiyanpunya Nattakarn Shutimarrungson Akkarat Boonpoonga Prayoot Akkaraekthalin Kamol Kaemarungsi Department of Electrical and Computer Engineering Faculty of Engineering King Mongkut's University of Technology North Bangkok Bangkok Thailand Department of Mechatronics Engineering Faculty of Engineering Rajamangala University of Technology Rattanakosin Nakhon Pathom Thailand Department of Business Computer Mahasarakham Business School Mahasarakham University Maha Sarakham Thailand Department of Electrical and Computer Engineering Research Center of Innovation Digital and Electromagnetic Technology (iDEMT) Faculty of Engineering King Mongkut's University of Technology North Bangkok Bangkok Thailand National Electronics and Computer Technology Center National Science and Technology Development Agency Pathum Thani Thailand

ISBN: (数字)9798350383591

ISBN: (纸本)9798350383607

This paper presents human pose estimation using millimeter-wave (mmWave) radar technology capable of penetrating obstacles. Operating within the frequency modulated continuous wave (FMCW) at 60 - 64 GHz, our radar system generates signals conducive to accurate human pose representation. Our data processing framework focuses on producing point cloud data, effectively capturing each human movement. Results are visualized through a 2D graph, with the z-axis representing time. Experimental data, collected from various activities conducted behind different walls, underwent thorough analysis, comparing point cloud positions with actual human postures. The outcomes affirm the effectiveness of mmWave radar systems, positioned behind obstacles, in accurately extracting human postures.

关键词： Point cloud compression Electrical engineering Frequency modulation Pose estimation Data visualization Millimeter wave radar Data processing

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Analysis and Optimization of Neural Networks for Image and Speech Recognition

Analysis and Optimization of Neural Networks for Image and S...

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2023 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems, ICSES 2023

作者： Komala, C.R. Purushothaman, R. Ande, Pavan Kumar Dinesh, P.M. Anitha Rani, K.S. Yamuna, P. HKBK College of Engineering Department of Information Science and Engineering Karnataka Bengaluru560045 India Sri Ramachandra Institute of Higher Education and Research Faculty of Engineering and Technology Tamil Nadu Chennai600116 India KoneruLakshmaiah Education Foundation Department of Computer Science and Engineering Andhra Pradesh Guntur522502 India Sona College of Technology Department of Electronics and Communication Engineering Tamil Nadu Salem636005 India REVA University School of Computer Science and Applications Karnataka Bengaluru560064 India Acharya Institute of Graduate Studies Department of Computer Applications Karnataka Soladevanahalli 560107 India

ISBN: (纸本)9798350319200

The strategy of transforming vocal discourse signals into text using records is known as programmed discourse acknowledgment (ASR). In the ongoing time of the PC unrest, the ASR has a huge impact in further developing the client experience while communicating with the PCs in a characteristic manner. Conventional instruments like a console and mouse can't be utilized, and the client might do a limitless number of undertakings like controlling of contraptions and correspondence with client care. This study presents an air terminal enquiry framework in view of ASR. The program was made solely for the Telugu language. In view of the most generally posed inquiries about air terminals, a data set was created. Convolutional Brain Organization (CNN) has been utilized for preparing and testing the information base in view of its extraordinary exhibition. Convolution brain organizations (CNNs) have as of late been demonstrated to perform better on the telephone discovery test than regular completely associated profound brain networks when utilized in a half and half profound brain organization/stowed away Markov model (DNN/Gee) design. © 2023 IEEE.

关键词： Image Networks Neural Optimization Speech Recognition

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Stock Market Trading Based on Market Sentiments and Reinforcement Learning

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computers, Materials & Continua 2022年第1期70卷 935-950页

作者： K.M.Ameen Suhail Syam Sankar Ashok S.Kumar Tsafack Nestor Naglaa F.Soliman Abeer D.Algarni Walid El-Shafai Fathi E.Abd El-Samie Department of Computer Science&Engineering NSS College of EngineeringPalakkad678008KeralaIndia Department of Electronics and Communication Engineering NSS College of EngineeringPalakkad678008KeralaIndia Unitéde Recherche de Matière Condensée D’Electronique et de Traitement du Signal(URAMACETS)Department of PhysicsUniversity of DschangP.O.Box 67DschangCameroon Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia Department Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt

Stock market is a place,where shares of different companies are *** is a collection of buyers’and sellers’*** this digital era,analysis and prediction in the stock market have gained an essential role in shaping today’s *** market analysis can be either fundamental or *** analysis can be performed either with technical indicators or through machine learning *** this paper,we report a system that uses a Reinforcement Learning(RL)network and market sentiments to make decisions about stock market *** system uses sentiment analysis on daily market news to spot trends in stock *** sentiment analysis module generates a unified score as a measure of the daily news about *** score is then fed into the RL module as one of its *** RL section gives decisions in the form of three actions:buy,sell,or *** objective is to maximize long-term future *** have used stock data of Apple from 2006 to 2016 to interpret how sentiments affect *** stock price of any company rises,when significant positive news become available in the public *** results reveal the influence of market sentiments on forecasting of stock prices.

关键词： Deep learning machine learning daily market news reinforcement learning stock market

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Chaotic RIME optimization algorithm with adaptive mutualism for feature selection problems

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computers in Biology and Medicine 2024年 179卷 108803-108803页

作者： Abdel-Salam, Mahmoud Hu, Gang Çelik, Emre Gharehchopogh, Farhad Soleimanian EL-Hasnony, Ibrahim M. Faculty of Computer and Information Science Mansoura University Mansoura35516 Egypt Department of Applied Mathematics Xi'an University of Technology Xi'an710054 China Department of Electrical and Electronics Engineering Faculty of Engineering Düzce University Düzce Turkey Department of Computer Engineering Urmia Branch Islamic Azad University Urmia Iran

The RIME optimization algorithm is a newly developed physics-based optimization algorithm used for solving optimization problems. The RIME algorithm proved high-performing in various fields and domains, providing a high-performance solution. Nevertheless, like many swarm-based optimization algorithms, RIME suffers from many limitations, including the exploration-exploitation balance not being well balanced. In addition, the likelihood of falling into local optimal solutions is high, and the convergence speed still needs some work. Hence, there is room for enhancement in the search mechanism so that various search agents can discover new solutions. The authors suggest an adaptive chaotic version of the RIME algorithm named ACRIME, which incorporates four main improvements, including an intelligent population initialization using chaotic maps, a novel adaptive modified Symbiotic Organism Search (SOS) mutualism phase, a novel mixed mutation strategy, and the utilization of restart strategy. The main goal of these improvements is to improve the variety of the population, achieve a better balance between exploration and exploitation, and improve RIME's local and global search abilities. The study assesses the effectiveness of ACRIME by using the standard benchmark functions of the CEC2005 and CEC2019 benchmarks. The proposed ACRIME is also applied as a feature selection to fourteen various datasets to test its applicability to real-world problems. Besides, the ACRIME algorithm is applied to the COVID-19 classification real problem to test its applicability and performance further. The suggested algorithm is compared to other sophisticated classical and advanced metaheuristics, and its performance is assessed using statistical tests such as Wilcoxon rank-sum and Friedman rank tests. The study demonstrates that ACRIME exhibits a high level of competitiveness and often outperforms competing algorithms. It discovers the optimal subset of features, enhancing the accuracy of c

关键词： Feature Selection

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ShieldSMS Sentinel: Guardian of Your Digital Communication Bastion

ShieldSMS Sentinel: Guardian of Your Digital Communication B...

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Artificial Intelligence in Education and Industry 4.0 (IDICAIEI), DMIHER International Conference on

作者： Palash Gourshettiwar Rajesh D Thakare Prapti Duddalwar Rushikesh Shete Swapnil Gundewar Prateek Verma Department of Computer Science and Medical Engineering Faculty of Engineering and Technology DMIHER(DU) Wardha Maharashtra India Department of Electronics Engineering Yashavantrao Chavan College of Engineering Nagpur Maharashtra India Department of Electronics Engineering Vishwakarma Institute of Technology Pune Maharashtra India Department of Computer Science and Business Systems St. Vincent Pallotti College of Engineering and Technology Nagpur Maharashtra India Department of Artificial Intelligence and Machine Learning Faculty of Engineering and Technology DMIHER(DU) Wardha Maharashtra India

ISBN: (数字)9798331528713

ISBN: (纸本)9798331528720

The SMS spam detection Project provides a comprehensive framework for reliably identifying and classifying spam messages sent over SMS communication channels by fusing ML algorithms with NLP techniques. Using EDA, a dataset of labelled SMS messages identified as spam or ham is thoroughly studied to reveal patterns in the word count, sentence count, and message length distributions. Then, unstructured text is transformed into structured data that may be utilized with ML models through tokenization, punctuation and stop word removal, stemming, and other text preprocessing techniques. Feature engineering, which numerically represents text data using vectorization techniques like BoW and TF-IDF, plays a significant role. Various ML algorithms, including Gaussian Naive Bayes, Multinomial Naive Bayes, SVM, and ensemble approaches, are trained and evaluated. Performance metrics, including accuracy and precision, serve as standards for model selection.

关键词： Support vector machines Measurement Industries Medical services Message services Tokenization Numerical models Bayes methods Reliability Standards

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