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

作者： Khan, Mohammad Ahmar Verma, Pushpendra Kumar Ghaldiyal, Shivangi Balaji, N.V. Francis, G. Arun Patil, Swati Bula Department of Management Information System College of Commerce & Business Administration Dhofar University Country Sultanate of Oman Oman School of Computer Science and Applications IIMT University Meerut India Department of Computer Applications Invertis University Uttar Pradesh Bareilly India Department of Computer Science Karpagam Academy of Higher Education Tamil Nadu Coimbatore India Department of Electronics and Communication Engineering Karpagam College of Engineering Tamil Nadu Coimbatore India IT Vishwakarma Institute of Technology Pune India

ISBN: (纸本)9798350370249

Research on fake news has gained significant traction in a number of fields, We describe how the issue is tackled from a natural language processing standpoint in this research with the aim of developing identify false material in news. Collecting high-quality data, such as examples of false and actual news stories on a diverse range of subjects, is the key obstacle in this field of study. We examine the available before introducing the site as our lab's gift to the . We provide the whole text of the news that have already been applied based on human evaluation of the articles' authenticity. In order to clarify the gaps and causes of imbalance in the datasets that are now accessible and to direct ongoing attempts, we also conduct an appearance-based experiment. We urge the public to gather more information and make it accessible for study. ©2024 IEEE.

关键词： Data collection

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Text Recognition on Curved Metal Surface: An Enhanced Approach using EasyOCR and OpenCV

Text Recognition on Curved Metal Surface: An Enhanced Approa...

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Pervasive Computing and Social Networking (ICPCSN), International Conference on

作者： Vijayalakshmi. R A.T.N Charany S. Niresh Kumar Somu C. S Sajan. D Deepika. N Department of Computer Science and Business System Rajalakshmi Institute of Technology Chennai India Department of Information Technology Chennai Institute of Technology Chennai India Department of Computer Science and Engineering St. Joseph’s College of Engineering Chennai India Department of Computer Science and Engineering Sri Sairam Institute of Technology Chennai India Department of Computer Science and Engineering Sri Venkateswara College of Engineering Chennai India

ISBN: (数字)9798331535193

ISBN: (纸本)9798331535209

Text is a fundamental system of symbolic representation, and it plays a major role in human culture and communication. Its ability to convey the rich semantic information has become very essential in vision-based applications. With the advancement of deep learning, computer vision techniques particularly in text detection and recognition has undergone significant evolution. This paper investigates the transformative impact of deep learning on scene text detection and recognition, specifically on curved metal surfaces. By leveraging Easy Optical Character Recognition (EasyOCR) and OpenCV, the proposed approach achieves an impressive accuracy of 90% for text recognition in challenging curved surfaces. Additionally, this study explores to optimization techniques designed to enhance detection precision and examines the scalability of deep learning models in real-world applications.

关键词： Deep learning Codes Accuracy Text recognition Social networking (online) Scalability Computational modeling Text detection Metals Containers

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Coil Optimization using Metaheuristic Techniques for Wireless Charging of Electric Vehicles - A Comparative Analysis. 5

Coil Optimization using Metaheuristic Techniques for Wireles...

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5th International Conference on Power and Energy technology, ICPET 2023

作者： Imtiaz, Tabish Elsanabary, Ahmed Mekhilef, Saad Mubin, Marizan Binti Soon, Tey Kok Aziz, Nur Fadilah Ab Universiti Malaya Department of Electrical Engineering Kuala Lumpur Malaysia Universiti Tenaga Nasional Institute of Power Engineering Selangor Kajang Malaysia Swinburne University of Technology School of Science Computing and Engineering Technologies Melbourne Australia Universiti Malaya Department of Computer System & Technology Kuala Lumpur Malaysia Universiti Tenaga Nasional Department of Electrical & Electronic Engineering Selangor Malaysia

ISBN: (纸本)9798350339673

Wireless Power Transfer (WPT) used for charging of electric vehicles (EVs), suffers from the problem of misalignment. In this paper metaheuristic optimizing techniques are used to increase the misalignment tolerance of the receiver coil. This is done by optimizing the length of each turn of the transmitter coil such that a uniform magnetic field density is produced over the charging area, which is kept 26% higher than the transmitting coil area which further aids to accommodate misalignment of the receiver coil. Differential Evolution (DE), Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) optimization algorithms are used to obtain the lengths of all the turns of the transmitter coil. These algorithms are also compared by varying the number of turns while keeping the number of iterations to a fixed value. © 2023 IEEE.

关键词： ABC Coil DE Misalignment Opti-mization PSO Wireless Power Transfer

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Compressed VGGNet for Automatic COVID-19 Disease Detection from CT Scan Images 8th

Compressed VGGNet for Automatic COVID-19 Disease Detection f...

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8th IFIP TC 12 International Conference on computer, Communication and Signal Processing, ICCCSP 2024

作者： Vinothini, R. Niranjana, G. Dhamanti, Inge Lailiyah, Syifa’ul Yakub, Fitri Department of Computer Science and Engineering SRM Institute of Science and Technology Kattankulathur 603203 India Department of Computing Technologies School of Computing SRM Institute of Science and Technology Kattankulathur 603203 India Department of Health Policy and Administration Faculty of Public Health Universitas Airlangga Surabaya Indonesia Faculty of Health Medicine and Life Sciences Universitas Airlangga East Java Indonesia Electronic System Engineering Department Malaysia-Japan International Institute of Technology Kuala Lumpur Malaysia

ISBN: (纸本)9783031736162

Millions of people across the globe were affected by this rapidly spreading disease by the year 2020. Contamination of the respiratory system results from contracting COVID-19. Nonetheless, establishing a conclusive diagnosis of COVID-19 may prove difficult due to the subtle differences it shares with conventional pneumonia and the complexities involved in identifying areas of infection. A growing number of approaches based on deep learning (DL) are being proposed for the automated detection of COVID-19 from CT scan images. By employing the data pretreatment methodology, unprocessed image data becomes prepared for further analysis. The proposed framework utilised transfer learning to construct VGGNet, which is capable of discerning the Covid-19 disease. The model was subsequently assessed in comparison to the most sophisticated models, VGG16 and VGG19, using the SARS-COV2 CT scan dataset. This dataset contains 1230 CT scans of non-infected images and 1252 CT scans of Covid-19-infected images. The model has achieved 99% accuracy, 98% precision, 97% recall, and 98% F1-score, among other performance metrics. © IFIP International Federation for Information Processing 2025.

关键词： COVID-19

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A 180-Degree Phase Difference Output of Wilkinson Power Divider Using Microstrip Parallel Coupled Lines 6

A 180-Degree Phase Difference Output of Wilkinson Power Divi...

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6th International Conference on Power, Energy and Innovations, ICPEI 2024

作者： Phanomupatum, Pratya Phromloungsri, Ravee Tama, Rachata Pongthavornkamol, Tiwat Wongpatsa, Decha Sonasang, Somchat Nakhon Phanom University Faculty Industrial Technology Department of Electronics Nakhon Phanom Thailand Udon Thani Rajabhat University Computer and Communication Engineering Faculty of Technology Udon Thani Thailand National Electronic and Computer Technology Center National Science and Technology Development Agency Location and Automatic Identification System Research Team Communication and Network Research Group Pathumthani Thailand Faculty Industrial Technology Nakhon Phanom Thailand

ISBN: (纸本)9798350356779

The design of a 180° output phase difference Wilkinson power divider for L-band applications is detailed in this article. The Wilkinson power is generated through the utilization of the parallel coupler's phase shifter. To showcase the potential of the suggested power divider, an FR4 microwave substrate is fabricated with a narrow band of 1.6 GHz to accommodate radio astronomy systems. The insertion loss, return loss, and isolation loss for the power divider's difference phase are accurately simulated at the operational frequency. © 2024 IEEE.

关键词： Radio astronomy

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Prediction of piRNA-mRNA interactions based on an interactive inference network

Prediction of piRNA-mRNA interactions based on an interactiv...

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Liu, Yajun Li, Ru Li, Aimin Fei, Rong Guo, Xie Wu, Fang-Xiang Xi'an University of Technology Shaanxi Key Laboratory for Network Computing and Security Technology Xi'an China Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an China University of Saskatchewan Division of Biomedical Engineering Department of Computer Science Department of Mechanical Engineering Saskatoon Canada

ISBN: (纸本)9798350337488

As the largest class of small non-coding RNAs, piRNAs primarily present in the reproductive cells of mammals, which influence post-transcriptional processes of mRNAs in multiple ways. Effective methods for predicting piRNA and mRNA target relationships can help identify piRNA functions, investigate the possibility of piRNAs as biomarkers and therapeutic targets. In this study, we propose a computational approach for classifying the relationships of piRNA-mRNA pairs based on an interactive inference network (IIN). First, we gather piRNA-mRNA target data, collect sequence data by position alignment, and construct a benchmark dataset. Furthermore, a reliable negative set is constructed by positive-unlabeled learning. Finally, we view a piRNA and a mRNA sequence as a premise and hypothesis sentence, respectively, and IIN model is used to predict the relationship between them. The experiments demonstrate that our method effectively characterizes piRNA-mRNA interaction and could be beneficial for researchers to investigate piRNA functions. © 2023 IEEE.

关键词： interactive inference network noncoding RNA piRNA-mRNA interactions positive-unlabeled learning

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Discounted Iterative Adaptive Critic Designs With Novel Stability Analysis for Tracking Control

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IEEE/CAA Journal of Automatica Sinica 2022年第7期9卷 1262-1272页

作者： Mingming Ha Ding Wang Derong Liu School of Automation and Electrical Engineering University of Science and Technology BeijingBeijing 100083China Faculty of Information Technology the Beijing Key Laboratory of Computational Intelligence and Intelligent Systemthe Beijing Laboratory of Smart Environmental Protectionand the Beijing Institute of Artificial IntelligenceBeijing University of TechnologyBeijing 100124China Department of Electrical and Computer Engineering University of Illinois at ChicagoChicago IL 60607 USA IEEE

The core task of tracking control is to make the controlled plant track a desired *** traditional performance index used in previous studies cannot eliminate completely the tracking error as the number of time steps *** this paper,a new cost function is introduced to develop the value-iteration-based adaptive critic framework to solve the tracking control *** the regulator problem,the iterative value function of tracking control problem cannot be regarded as a Lyapunov function.A novel stability analysis method is developed to guarantee that the tracking error converges to *** discounted iterative scheme under the new cost function for the special case of linear systems is ***,the tracking performance of the present scheme is demonstrated by numerical results and compared with those of the traditional approaches.

关键词： Adaptive critic design adaptive dynamic programming(ADP) approximate dynamic programming discrete-time nonlinear systems reinforcement learning stability analysis tracking control value iteration(VI)

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Perimeter-Search-Based Semi-Join Query Optimization Algorithm in Data-Sharing Environment

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Chinese Journal of Electronics 2023年第4期18卷 593-598页

作者： Xiaoqing Wang Youyuan Fang Yanxing Zheng Jianjian Zong Tianyang Gu Department of Computer Science and Technology Tsinghua University Beijing China Beijing Institute of System Engineering Beijing China

The problem of SQO (Semi-join query optimization) in data-sharing environment is addressed and a Perimeter-search-based semi-join query optimization algorithm (PSSJA) is presented. The algorithm can determine optimal sequence of semi-join operations, minimize the data transmission cost, saves storage space, and reduce the search complexity in a costeffective manner. Experiment shows the efficiency of our algorithm.

关键词： Costs Query processing Soft sensors Distributed databases Aerospace electronics Complexity theory Data communication

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Detecting and Mitigating Distributed Denial of Service Attacks in Software-Defined Networking

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computers, Materials & Continua 2025年第6期83卷 4515-4535页

作者： Abdullah M.Alnajim Faisal Mohammed Alotaibi Sheroz Khan Department of Information Technology College of ComputerQassim UniversityBuraydah51452Saudi Arabia College of Computer Engineering and Sciences Department of information systemPrince Sattam bin Abdulaziz UniversityAl-Kharj16273Saudi Arabia Department of Electrical Engineering College of Engineering and Information TechnologyOnaizah CollegesQassim56447Saudi Arabia

Distributed denial of service(DDoS)attacks are common network attacks that primarily target Internet of Things(IoT)*** are critical for emerging wireless services,especially for applications with limited *** attacks pose significant risks to entrepreneurial businesses,preventing legitimate customers from accessing their *** attacks require intelligent analytics before processing service *** denial of service(DDoS)attacks exploit vulnerabilities in IoT devices by launchingmulti-point distributed *** attacks generate massive traffic that overwhelms the victim’s network,disrupting normal *** consequences of distributed denial of service(DDoS)attacks are typically more severe in software-defined networks(SDNs)than in traditional *** centralised architecture of these networks can exacerbate existing vulnerabilities,as these weaknesses may not be effectively addressed in this *** preliminary objective for detecting and mitigating distributed denial of service(DDoS)attacks in software-defined networks(SDN)is to monitor traffic patterns and identify anomalies that indicate distributed denial of service(DDoS)*** implements measures to counter the effects ofDDoS attacks,and ensure network reliability and availability by leveraging the flexibility and programmability of SDN to adaptively respond to *** authors present a mechanism that leverages the OpenFlow and sFlow protocols to counter the threats posed by DDoS *** results indicate that the proposed model effectively mitigates the negative effects of DDoS attacks in an SDN environment.

关键词： Software-defined networking(SDN) distributed denial of service(DDoS)attack sampling Flow(sFlow) OpenFlow OpenDaylight controller

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The Spreading Prediction and Severity Analysis of Blood Cancer Using Scale-Invariant Feature Transform

The Spreading Prediction and Severity Analysis of Blood Canc...

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2023 IEEE International Conference on Network, Multimedia and Information technology, NMITCON 2023

作者： Mohammed, Vazeer Ali Mohammed, Mehmood Ali Mohammed, Murtuza Ali Ramakrishnan, Rakesh Logeshwaran, J. Lewis University Department of Computer & Information System IL United States University of the Cumberlands Department of Information Technology WilliamsburgKY United States University of the Cumberlands Department of Information Technology Union CityCA United States Sri Eshwar College of Engineering Department of Electronics and Communication Engineering Tamil Nadu Coimbatore641202 India

ISBN: (纸本)9798350300826

Blood cancer is an ever-growing global health concern. Early detection and accurate diagnosis are key to successful treatment and long-term prognosis of the disease. Despite various advances in medical technologies, current methods for blood cancer detection are far from perfect and often suffer from a lack of accuracy. This paper proposes the use of Scale-Invariant Feature Transform (SIFT) based approaches for predicting the spreading of blood cancer and assessing its severity. SIFT is a computer vision technique that extracts meaningful features from an image. Through SIFT, meaningful patterns in medical imaging datasets, such as those used for blood cancer detection, can be identified. The output from SIFT can then be used to build predictive models which can accurately predict the spread of the disease and its severity. Additionally, this paper explains how machine-learning algorithms and artificial neural networks can be used to further enhance the accuracy of these predictions. Finally, the proposed approach is validated using benchmark datasets and its accuracy is compared with existing methods for blood cancer prediction. The proposed model reached 89.71% accuracy, 89.25% precision, 90.71% recall and 89.40% f1-score results. The results show that prediction accuracy increases significantly when SIFT is used. It is concluded that SIFT can be a powerful tool for predicting blood cancer and estimating its severity. © 2023 IEEE.

关键词： Diseases

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