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3rd International Conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Junnarkar, Aparna A. Jakhar, Sunil Kumar Nagpal, Manish Yadav, Rakesh Kumar Moger, Vinod Sindhu, M. Vishwakarma Institute of Information Technology Department of Information Technology Pune India Vivekananda Global University Department of Mechanical Engineering Jaipur India Chitkara University Institute of Engineering and Technology Chitkara University Centre of Interdisciplinary Research in Business and Technology Punjab India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Faculty of Engineering and Technology Department of Mechanical Engineering Karnataka Ramnagar562112 India Prince Shri Venkateshwara Padmavathy Engineering College Department of Computer Science and Engineering Chennai127 India

ISBN: (纸本)9798350319125

The text type is a vital undertaking within the realm of gadget-gaining knowledge of algorithms and can contain classifying text files into predefined classes. Text category is used in many herbal language processing obligations, sentiment evaluation, topic modeling, and record summarization. Design techniques for device mastering algorithms for textual content categories contain information preprocessing, feature engineering, model choice, and evaluation. Records preprocessing requires expertise in text information and includes the stairs of tokenizing the text records, removing stopwords, acting stemming and lemmatization, part-of-speech tagging, and vectorization. Feature engineering, which is a step that requires domain expertise, applies strategies consisting of feature selection, function extraction, and feature transformation. Version choice and optimization techniques, including hyperparameter tuning and version choice, are used to choose the most appropriate studying algorithm for the task. Lastly, assessment metrics evaluate the model's effectiveness, including accuracy, precision, remembering, and f-ratings. On average, these layout techniques are critical components while growing a successful text-type model. © 2023 IEEE.

关键词： Classification (of information)

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Tensile Testing Based on the Polarization-maintaining Fiber Powered by an SM Optical Fibre 4

Tensile Testing Based on the Polarization-maintaining Fiber ...

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4th International Conference on Electrical, computer, Communications and Mechatronics engineering, ICECCME 2024

作者： Kyselak, Martin Vavra, Jiri Vylezich, Zdenek Grenar, David Slavicek, Karel University of Defense Faculty of Military Technology Department of Electrical Engineering Brno Czech Republic University of Technology Faculty of Electrical Eng. and Communication Dept. of Telecommunications Brno Czech Republic Institute of Computer Science Masaryk University IT Infrastructure Division Brno Czech Republic

ISBN: (纸本)9798350391183

Optical fibre sensors are currently used to detect many non-electrical phenomena. The latest sensors analyze the polarization properties of light inside an optical fiber. Unlike interferometric methods, this method uses the interference of two planes of polarization at the output of the optical fibre. The sensors are divided into linear polarizer sensors or multi-fibre interference sensors based on different ways of converting the polarization state into a change in the intensity of the optical radiation. These sensors are particularly suitable for low frequency vibration measurements due to the transformation of beats into the longitudinal deformation of the optical fibre. The aim of the presented measurements was to demonstrate that these polarization vibration sensors have excellent sensitivity and are thus suitable for vibration detection. This paper demonstrates that polarization sensors have excellent sensitivity, are convenient and inexpensive to install, and, due to their non-electric nature, are suitable for hazardous environments. In addition, it is possible to employ these sensors as intrusion detection and prevention systems and remotely power them at a distance of tens of kilometers. The motivation for this research was the lack of information and equipment for vibration testing of optical fibres and the associated polarization changes. © 2024 IEEE.

关键词： Tensile testing

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Deep learning-based Soft word embedding approach for sentiment analysis 28th

Deep learning-based Soft word embedding approach for sentime...

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28th International Conference on Knowledge Based and Intelligent information and engineering Systems, KES 2024

作者： Ouni, Chafika Benmohamed, Emna Ltifi, Hela REGIM-Lab.: Research Groups in Intelligent Machines LR11ES48 3038 Faculty of Sciences Economics and Management of Sfax University of Sfax Tunisia Department of Computer Science College of Engineering and Information Technology Onaizah Colleges P.O. Box 5371 Onaizah Saudi Arabia Computer Science and Mathematics Department Faculty of Sciences and techniques of Sidi Bouzid University of Kairouan Tunisia

Word Embeddings (WE) play a crucial role in capturing the meanings of words. They provide continuous vector representations that encode semantic and syntactic information. To accurately convert words into meaningful vectors, in this paper, we propose a novel approach called Soft EMBedding method (SoftEMB). SoftEMB combines the strengths of the Glove and Word2Vec methods through a Soft-Voting algorithm. The SoftEMD approach aims to improve the performance of word embedding, particularly in the context of Sentiment Analysis (SA) hybrid models. To evaluate the SoftEMD performance, we test it on various SA models based on CNN-LSTM, CNN-GRU, CNN-biLSTM, and CNN-bi-GRU. Our results demonstrate a substantial enhancement in accuracy when evaluating movie reviews, with scores of 88.29%, 88.33%, 88.27%, and 88.27%. Similarly, for Sentiment140 dataset, our proposal shows improved results, achieving accuracy rates of 83.27%, 82.78%, 82.76%, and 82.51%. These results highlight the significant progress made in accurately analyzing both movie reviews and the Sentiment140 dataset. © 2024 The Authors.

关键词： Semantics

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FedNIA: Noise-Induced Activation Analysis for Mitigating Data Poisoning in Federated Learning

arXiv

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arXiv 2025年

作者： Hallaji, Ehsan Razavi-Far, Roozbeh Saif, Mehrdad Department of Electrical and Computer Engineering University of Windsor WindsorON Canada Faculty of Computer Science University of New Brunswick FrederictonNB Canada

Federated learning systems are increasingly threatened by data poisoning attacks, where malicious clients compromise global models by contributing tampered updates. Existing defenses often rely on impractical assumptions, such as access to a central test dataset, or fail to generalize across diverse attack types, particularly those involving multiple malicious clients working collaboratively. To address this, we propose Federated Noise-Induced Activation Analysis (FedNIA), a novel defense framework to identify and exclude adversarial clients without relying on any central test dataset. FedNIA injects random noise inputs to analyze the layerwise activation patterns in client models leveraging an autoencoder that detects abnormal behaviors indicative of data poisoning. FedNIA can defend against diverse attack types, including sample poisoning, label flipping, and backdoors, even in scenarios with multiple attacking nodes. Experimental results on non-iid federated datasets demonstrate its effectiveness and robustness, underscoring its potential as a foundational approach for enhancing the security of federated learning systems. © 2025, CC BY-NC-ND.

关键词： Federated learning

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A Compact Rhombus Shaped Antenna with Extended Stubs for Ultra-Wideband Applications

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computers, Materials & Continua 2022年第11期73卷 2637-2650页

作者： Syed Misbah un Noor Muhammad Amir Khan Shahid Khan NZ Jhanjhi Mamoona Humayun Hesham A.Alhumyan Department of Electrical Engineering IIC University of TechnologyPhnom PenhCambodia Department of Computer Science COMSATS University IslamabadAbbottabad Campus22060Pakistan Department of Electrical and Computer Engineering COMSATS University IslamabadAbbottabad Campus22060Pakistan School of Computer Science SCSTaylor’s UniversitySubang Jaya47500SelangorMalaysia 5Center for Smart Society 0 CSS5 Faculty of Innovation and TechnologyTaylor’s UniversitySubang Jaya47500Malaysia Department of Information Systems College of Computer and Information SciencesJouf UniversityAl-JoufKSA

Ultra-wideband(UWB)is highly preferred for short distance *** a result of this significance,this project targets the design of a compact UWB *** paper describes a printed UWB rhombusshaped antenna with a partial ground *** achieve wideband response,two stubs and a notch are incorporated at both sides of the rhombus design and ground plane *** excite the antenna,a simple microstrip feed line is *** suggested antenna is built on a 1.6 mm thick FR4 *** proposed design is very compact with overall electrical size of 0.18λ×0.25λ(14×18 mm2).The rhombus shaped antenna covers frequency ranging from 3.5 to 11 GHz with 7.5 GHz impedance *** proposed design simulated and measured bandwidths are 83.33%and 80%,*** pattern in terms of E-field and H-field are discussed at 4,5.5 and 10 GHz *** proposed design has 65%radiation efficiency and 1.5 dBi peak *** proposed design is simulated in CST(computer Simulation Technology)simulator and the simulated design is fabricated for the measured *** simulated and measured findings are in close *** obtained results confirm the application of the proposed design for the ultra-wide band applications.

关键词： Ultra-wideband impedance bandwidth radiation pattern CST electrical size

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End-to-End Quality of Service Provisioning in High Speed Networks 3

End-to-End Quality of Service Provisioning in High Speed Net...

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3rd International Conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Rao, Srikrishna B. Sathya, T. Bagade, Jayashree V. Sharma, Vishal Dhingra, Lovish Kumar, Ritesh Faculty of Engineering and Technology Department of Mechanical Engineering Karnataka Ramnagar562112 India Prince Shri Venkateshwara Padmavathy Engineering College Department of Computer Science and Engineering Chennai127 India Vishwakarma Institute of Information Technology Department of Information Technology Pune India Vivekananda Global University Department of Mechanical Engineering Jaipur India Centre of Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (纸本)9798350319125

End-to-give a fine of service (quality of service) provisioning is essential for improving the person's experience in excessive velocity networks. Quality of service provisioning is a set of strategies, methods, and strategies designed to ensure ok transport and performance of community visitors. It does so by way of deliberating first-rate-effort services, which include routing, forwarding, and mistakes-correction and using also introducing better layer services, including waft manipulation, precedence schemes, link layer offerings, and numerous exemplary carrier models like Voice over IP (VoIP), traffic engineering (TE), valuable resource Reservation Protocol (RSVP) among *** the network layer, quality of service techniques provides a manner to allocate bandwidth, regulate packet forwarding, shape site visitors, and reserve assets in excessive-speed networks. The packages of quality of service provisioning in excessive speed networks include but are not limited to assuring the non-stop shipping of bandwidth extensive real-time packages consisting of Voice over IP (VoIP) and Video streaming, granting high availability to sure assignment-essential applications, making certain a minimum fine of service (quality of service) to specific applications and supplying differentiated bandwidth for positive lessons of site visitors. Quit-to-end quality of service in high-speed networks may be done by using techniques along with weighted packet scheduling, multi-level priority queues, admission management algorithms, selectable sign and coding schemes, dual buffers, Etc. By ensuring service provisioning quality in excessive-pace networks, telecommunication service providers can offer a more significant consumer enjoy and make sure that the services they offer are up to customer expectation. © 2023 IEEE.

关键词： admission availability provisioning techniques telecommunication

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Classification of Football Player Actions Using Sensing Data

Classification of Football Player Actions Using Sensing Data

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Image Processing and Robotics (ICIP), International Conference on

作者： Yukito Hirasawa Yuichiro Kinoshita Latifah Munirah Kamarudin Ammar Zakaria Department of Computer Science and Engineering University of Yamanashi Yamanashi Japan Faculty of Electronic Engineering and Technology Universiti Malaysia Perlis Perlis Malaysia

ISBN: (数字)9798350374766

ISBN: (纸本)9798350374773

This study classifies the actions of football players using sensing data acquired from wearable sensors attached to players and the ball. More than 800 sensing data with the labels of five types of player actions were created as a dataset. The neural networks were trained using 19 input items created by considering time-series variations in player and ball locations. The trained neural network model demonstrated a classification accuracy of $84.0 \%$. The model successfully obtained sufficient accuracy for all types of *** results demonstrate that the sensing data and created input items can be effectively utilized for classifying the actions of football player.

关键词： Robot kinematics Image processing Neural networks Detectors Robot sensing systems Sensors Recording

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A Data Mining Approach for Analysis of Telco Customer Churn

A Data Mining Approach for Analysis of Telco Customer Churn

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2023 Al-Sadiq International Conference on Communication and Information Technology, AICCIT 2023

作者： Al-Shakarchi, Ali H. Mostafa, Salama A. Saringat, Mohd Zainuri Mohammed, Dheyaa Abdulameer Khaleefah, Shihab Hamad Jaber, Mustafa Musa Ninevah University College of Information Technology Mosul Iraq Universiti Tun Hussein Onn Malaysia Faculty of Computer Science and Information Technology Johor Malaysia Imam Ja'afar Al-Sadiq University College of Information Technology Department of Computer Technical Engineering Al-Muthanna Iraq Al Maarif University College Department of Computer Science Anbar Iraq Al-turath University Department of Medical Instruments Engineering Techniques Baghdad Iraq Al-farahidi University Department of Medical Instruments Engineering Techniques Baghdad Iraq

ISBN: (纸本)9798350341881

Telco is a telephone service provider that gives data communications access. Information technology and the capability to stay connected and communicate all day are becoming the modern living trend. Telco company offers different promotions and services to attract consumers to select their telco company. The current service is inexpensive, and the quality of most telco companies is the same. Understanding the customer churn rate is crucial as it is highly associated with customer retention. This paper classified customer churn based on various attributes and utilized four different machine learning algorithms: Averaged Perceptron (AP), Bayes Point Machine (BPM), Decision Forest (DF), and Logistic Regression (LR). Microsoft Machine Learning Studio is used for Implementing and Testing Classification Models. The models are evaluated on Telco Customer Churn (TCC) dataset in terms of accuracy, precision, recall, and error. The experimental results show that the LR model has an average accuracy of 80.1% compared to the other three models, in which AP scores 79.92%, BPM scores 80.04%, and DF scores 77.04%. The obtained results can provide significant insights for telecommunications companies to recognize market demands and develop appropriate strategies to enhance customer retention. © 2023 IEEE.

关键词： Logistic regression

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Research on the 'Electric Vehicles and Automotive Electronics' Curriculum Aimed at Modernization within the DIGITRANS Project 65

Research on the 'Electric Vehicles and Automotive Electronic...

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65th IEEE Annual International Scientific Conference on Power and Electrical engineering of Riga Technical University, RTUCON 2024

作者： Arhun, Shchasiana Hnatov, Andrii Kunicina, Nadezhda Kharkiv National Automobile and Highway University Automobile Faculty Vehicle Electronics Department Kharkiv Ukraine Riga Technical University Riga Latvia Institute of Industrial Electronics Electrical Engineering and Energy Riga Technical University Faculty of Computer Science Information Technology and Energy Riga Latvia

ISBN: (纸本)9798350365771

The rapid evolution of the automotive industry, driven by technological innovations and the shift towards sustainability, necessitates a corresponding transformation in educational curricula. This paper presents a detailed examination of the 'Electric Vehicles and Automotive Electronics' curriculum at Kharkiv National Automobile and Highway University, which has been targeted for modernization under the DIGITRANS project. The project's primary objective is to align the curriculum with the latest industry demands and technological advances, particularly focusing on electric vehicles (EVs) and automotive electronics. This research utilizes a mixed-methods approach, combining quantitative data from industry surveys with qualitative feedback from academic experts and industry stakeholders. The findings highlight significant gaps in the current educational offerings, particularly in areas such as advanced diagnostics, battery management systems, and integration of smart automotive technologies. The paper discusses the development and integration of new course materials that include hands-on laboratory exercises, industry placements, and enhanced e-learning modules. The modernized curriculum aims to equip students with the skills necessary to excel in the fast-evolving automotive sector, emphasizing critical thinking, technical expertise, and practical experience. The outcomes of this research underscore the importance of continuous industry-academia collaboration to keep educational programs relevant and forward-thinking. This initiative not only enhances the employability of graduates but also contributes to the broader goal of advancing electric vehicle technology and sustainability in automotive engineering. © 2024 IEEE.

关键词： Automotive industry

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A New AI System for Precise Grading of HCC Based on Analyzing DW-MRI Radiomics and Alpha-fetoprotein as Liver Cancer Clinical Marker 27th

A New AI System for Precise Grading of HCC Based on Analyzin...

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27th International Conference on Pattern Recognition, ICPR 2024

作者： Elkhouly, Abdelrhman Alksas, Ahmed Saleh, Gehad A. Shehata, Mohamed Karawia, Abdelrahman Ghazal, Mohammed Contractor, Sohail El-Baz, Ayman Mathematics Department Faculty of Science Mansoura University Mansoura Egypt Department of Bioengineering University of Louisville LouisvilleKY United States Diagnostic and Interventional Radiology Department Faculty of Medicine Mansoura University Mansoura Egypt Electrical Computer Biomedical Engineering Department Abu Dhabi University Abu Dhabi United Arab Emirates Department of Radiology University of Louisville LouisvilleKY United States

ISBN: (纸本)9783031783975

Hepatocellular carcinoma (HCC), – the main form of liver cancer –, is the second global leading cause of cancer-related mortality. LI-RADS is considered the worldwide non-invasive standard method for imaging interpretation and reporting in patients with HCC eliminating the need for biopsy. However, it might be prone to interpretation subjectivity. Therefore, we develop an objective non-invasive AI-based grading system for HCC for appropriate etiology treatment plans. The developed system integrates potential image-based markers that represent the tumor’s morphology, functionality, and appearance/texture with the associated clinical biomarkers. The study encompasses 117 patients diagnosed with HCC and was divided into three different groups (group 1: benign low-grade (LR 1,2), N = 41;group 2: malignant high-grade (LR 4,5), N = 39;and group 3: malignant not HCC (LR-M), N = 37). Diffusion-weighted magnetic resonance imaging (DWI) was acquired for imaging-based markers identification. The developed grading system pipeline includes: i) estimation of morphological markers using a new parametric spherical harmonic model, ii) estimation of appearance/textural markers using a novel rotation invariant circular binary pattern model, iii) calculation of the functional markers by constructing the representative cumulative distribution functions of the estimated apparent diffusion coefficients, and iv) integrating the aforementioned imaging-based markers with the associated clinical biomarkers, known as Alpha-fetoprotein. The integrated markers were optimized to train and test multiple machine learning (ML) classifiers and a hyper-tuned custom CNN. On a randomly stratified train (80%) test (20%) split scheme, the developed obtained an overall accuracy of 88% in differentiating between the three groups using the integrated markers along with the CatBoost classifier, surpassing the diagnostic performance of individual marker sets, other ML classifiers, and the CNN as well. The obta

关键词： Noninvasive medical procedures

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