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Text Augmentation-Based Model for Emotion Recognition Using Transformers

computers, Materials & Continua 2023年第9期76卷 3523-3547页

作者： Fida Mohammad Mukhtaj Khan Safdar Nawaz Khan Marwat Naveed Jan Neelam Gohar Muhammad Bilal Amal Al-Rasheed Department of Computer Science The University of HaripurHaripur22620Pakistan Department of Computer Systems Engineering Faculty of Electrical and Computer EngineeringUniversity of Engineering and Technology PeshawarPeshawar25120Pakistan Department of Electronics Engineering Technology University of TechnologyNowshera24100Pakistan Department of Computer Science Shaheed Benazir BhuttoWomen UniversityPeshawar25000Pakistan Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia

Emotion Recognition in Conversations(ERC)is fundamental in creating emotionally ***-BasedNetwork(GBN)models have gained popularity in detecting conversational contexts for ERC ***,their limited ability to collect and acquire contextual information hinders their *** propose a Text Augmentation-based computational model for recognizing emotions using transformers(TA-MERT)to address *** proposed model uses the Multimodal Emotion Lines Dataset(MELD),which ensures a balanced representation for recognizing human *** used text augmentation techniques to producemore training data,improving the proposed model’s *** encoders train the deep neural network(DNN)model,especially Bidirectional Encoder(BE)representations that capture both forward and backward contextual *** integration improves the accuracy and robustness of the proposed ***,we present a method for balancing the training dataset by creating enhanced samples from the original *** balancing the dataset across all emotion categories,we can lessen the adverse effects of data imbalance on the accuracy of the proposed *** results on the MELD dataset show that TA-MERT outperforms earlier methods,achieving a weighted F1 score of 62.60%and an accuracy of 64.36%.Overall,the proposed TA-MERT model solves the GBN models’weaknesses in obtaining contextual data for ***-MERT model recognizes human emotions more accurately by employing text augmentation and transformer-based *** balanced dataset and the additional training samples also enhance its *** findings highlight the significance of transformer-based approaches for special emotion recognition in conversations.

关键词： Emotion recognition in conversation graph-based network text augmentation-basedmodel multimodal emotion lines dataset bidirectional encoder representation for transformer

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A Study on 1D-Point Cloud Using Through-Wall mm Wave Radar for Human Pose Estimation 12

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

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12th International electrical engineering Congress, iEECON 2024

作者： Phaisiri, Kritthee Kittiyanpunya, Chainarong Shutimarrungson, Nattakarn Boonpoonga, Akkarat Akkaraekthalin, Prayoot Kaemarungsi, Kamol King Mongkut's University Of Technology North Bangkok Faculty Of Engineering Department Of Electrical And Computer Engineering Bangkok Thailand Rajamangala University Of Technology Rattanakosin Faculty Of Engineering Department Of Mechatronics Engineering Nakhon Pathom Thailand Mahasarakham Business School Mahasarakham University Department Of Business Computer Maha Sarakham Thailand Faculty Of Engineering Department Of Electrical And Computer Engineering Bangkok Thailand National Electronics And Computer Technology Center National Science And Technology Development Agency Pathum Thani Thailand

ISBN: (纸本)9798350383591

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. © 2024 IEEE.

关键词： Frequency modulation

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Single-Phase Direct PWM Bipolar Buck–Boost AC–AC Converter Without Commutation Problem

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IEEE Journal of Emerging and Selected Topics in Power Electronics 2023年第6期11卷 5940-5953页

作者： Ahmed, Hafiz Furqan Ali Khan, Ashraf Abdoli, Iman Zaabi, Omar Al the Department of Electrical Engineering National Sun Yat-sen University Kaohsiung80424 Taiwan the Department of Electrical and Computer Engineering Faculty of Engineering and Applied Science Memorial University of Newfoundland St. John’sNLA1B 3X7 Canada the Department of Electrical Engineering Shahid Beheshti University Tehran19839-69411 Iran Department of Electrical Engineering and Computer Science Khalifa University Abu Dhabi United Arab Emirates

— The direct pulsewidth modulation (PWM) ac–ac converters are seeing rapid development due to their single-stage power conversion with reduced footprints, due to the elimination of intermediate dc-link capacitor. However, they only provide unipolar voltage gain and fixed frequency operation and use the bidirectional voltage-blocking devices without natural inductor current free-wheeling path, restricting their practical applications. This article proposes a direct PWM bipolar and step-variable frequency buck–boost ac–ac converter. The proposed converter is fabricated by connecting input–output LC filters and a small value film capacitor to six unidirectional voltage-blocking devices, which are arranged as a three-leg inverter module. It can provide noninverting and inverting buck–boost voltage operations with a symmetric bipolar voltage gain of ±d/(1 − d) and can also change the frequency of output voltage in discrete steps, same as that of single-phase matrix converters (MCs). It has no open-circuit risk of inductor due to the presence of natural current free-wheeling path during PWM dead time. Therefore, it is unaffected by the commutation problem of conventional direct ac–ac converters. The proposed converter can realize high-quality input and output due to the presence of second-order input–output filters with continuous input–output currents. A detailed analysis is provided based on proposed switch modulation strategies and confirmed through extensive experimental tests on a laboratory-fabricated hardware. © 2023 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission.

关键词： Matrix converters

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A New ZVS Interleaved Flyback Converter 12

A New ZVS Interleaved Flyback Converter

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12th Iranian Conference on Renewable Energies and Distributed Generation, ICREDG 2025

作者： Mojaveri, Shokouh Shabani Delshad, Majid Heydarian-Forushani, Ehsan Branch Islamic Azad University Faculty of Engineering Isfahan Iran Qom University of Technology Department of Electrical and Computer Engineering Qom Iran

ISBN: (纸本)9798331525132

This paper presents a new auxiliary circuit for interleaved flyback converters to create soft switching conditions in the element in addition the semiconductor in the converter structure prevents the voltage spike across the switches. Also, due to the use of the ripple cancellation technique, the input current has decreased. The proposed interleaved flyback converter has been completely analyzed, a 100W laboratory sample has been developed to confirm its performance, and practical results have been provided to verify the proper performance of the circuit. © 2025 IEEE.

关键词： Flyback converter Interleaved Ripple cancellation Zero voltage switching

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Access Management in IoT: Implementing a Secure Access Control System 15

Access Management in IoT: Implementing a Secure Access Contr...

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15th International Conference on Communications, COMM 2024

作者： Neculai, Razvan-Sebastian Bogdan, Ioana-Corina Alexandru, Marian Robu, Dan-Nicolae Transilvania University of Brasov & Eviden Faculty of Electrical Engineering and Computer Science Department of Cybersecurity Braşov Romania Transilvania University of Brasov Faculty of Electrical Engineering and Computer Science Department of Electronics and Computers Braşov Romania

ISBN: (纸本)9798350355956

This paper aims to implement and use the Spring Security framework to secure and authenticate the connection between a web application and the ESP32 device. In the context of a web application, by analyzing the integration of the Spring Security framework, it investigates the ways in which it manages the complex process of authentication and authorization, thus providing a secure and protected connection to an IoT device. Additionally, this study investigates the integration and use of the RTOS operating system to manage physical access in an IoT environment, in particular by implementing the opening of a door using tags. The mechanism described above leads to an additional level of security and control over physical access in an IoT ecosystem. © 2024 IEEE.

关键词： Radio frequency identification (RFID)

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A Testing Platform for Airborne Wind Energy: Modelling, Sensoring, and Actuation 16th

A Testing Platform for Airborne Wind Energy: Modelling, Sen...

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16th APCA International Conference on Automatic Control and Soft Computing, CONTROLO 2024

作者： Fernandes, Gabriel M. Costa, Conrado Guimarães da Vinha, Sérgio Fontes, Fernando A. C. C. Department of Electrical and Computer Engineering Faculty of Engineering University of Porto Rua Dr. Roberto Frias Porto4200-465 Portugal

ISBN: (纸本)9783031817236

This article addresses the development and control of a tethered support car designed to facilitate the take-off and landing maneuvers of an Airborne Wind Energy System (AWES) during its circular motion. To improve kite flight performance, minimizing weight is essential. This requires a support structure that allows the kite to accelerate while aligning with its operational needs. Given this, the work begins with an overview of system models, including an analysis of the aircraft aerodynamic characteristics and the development of the support car model. Subsequently, the specifications for designing and assembling the aircraft prototype are presented. A system testing platform is described to validate the small-scale prototype, incorporating a set of sensors and actuators that meet the requirements and constraints of the take-off and landing phases. Finally, a low-level controller for the system velocity is developed and validated through real tests. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Airborne Wind Energy Systems Automatic Take-off and Landing Circular Take-off and Landing Low-Level Control Tethered Aircraft

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A Yet Powerful Routing Protocol for Vehicular Ad-hoc Networks (VANETs) Utilizing Software Defined Network (SDN) and Fog Computing 8

A Yet Powerful Routing Protocol for Vehicular Ad-hoc Network...

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8th International Conference on Information Technology, Information Systems and electrical engineering, ICITISEE 2024

作者： Darabkh, Khalid A. Al-Mistarihi, Mamoun F. Al-Maaitah, Mera Ismail School of Engineering The University of Jordan Computer Engineering Department Amman11942 Jordan Jordan University of Science and Technology Faculty of Engineering Electrical Engineering Department Irbid22110 Jordan

ISBN: (纸本)9798350368970

In this article, we propose a novel protocol that employs different technologies together, such as Software Defined Network (SDN) for the purpose of offering scalability, programmability, and global network information, and Fog computing for the reason of providing location services that meet V ANET standards. Additionally, we propose a novel cluster head selection algorithm for the purpose of enhancing the efficiency of the protocol by considering three different dimensions, namely, lifetime, average distance, and signal-to-interference noise ratio. The novelty of this proposed algorithm comes from reducing the number of control overheads, reducing long-distance communications, and reducing packet loss due to collisions and contentions inside each cluster, respectively. The proposed protocol has been assessed using N s3 simulator whereas its results are so promising and worth publishing. © 2024 IEEE.

关键词： Vehicular ad hoc networks

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A two-stage progressive deep segmentation network for tumor detection in breast ultrasound images

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Multimedia Tools and Applications 2024年 1-23页

作者： Zaidkilani, Nadeem Abdel-Nasser, Mohamed Garcia, Miguel Angel Puig, Domenec Department of Computer Engineering and Mathematics University Rovira i Virgili Tarragona43007 Spain Electrical Engineering Department Faculty of Engineering Aswan University Aswan81542 Egypt Department of Electronic and Communications Technology Autonomous University of Madrid Madrid Spain

Segmenting tumorous regions in breast ultrasound images is a challenging problem due to several factors, including the relatively low contrast of the available images, the presence of speckle noise, and the considerable variations in breast mass sizes and shapes. Current methods are not precise enough and prone to misdetections. An efficient deep neural model is proposed for automatically segmenting tumorous regions in breast ultrasound images. The model is constituted by two consecutive encoder-decoder (autoencoder) networks. The first autoencoder extracts a preliminary binary mask from the given image. The second autoencoder refines that mask after concatenating it with the original image. The encoders within each autoencoder can be defined by applying any state-of-the-art network. In addition, cost-sensitive learning has been used in order to focalize training on the segmentation errors of the minority class (tumor). Semantic segmentation based on advanced deep learning methods is thus applied in order to enhance tumor segmentation in breast ultrasound images. The proposed model offers advanced capabilities for automated segmentation with the aim of helping physicians identify and diagnose tumors using state-of-the-art techniques. This model outperforms recent tumor segmentation methods in the experiments conducted on two public datasets of breast ultrasound images (UDIAT and BUSI). The largest improvement for both datasets was achieved by using CoAtNet as baseline model (Dice index equal to 84.49% and 78.94%, respectively). © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Ultrasonic imaging

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Knowledge‐based deep learning system for classifying Alzheimer's disease for multi‐task learning

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CAAI Transactions on Intelligence Technology 2024年第4期9卷 805-820页

作者： Amol Dattatray Dhaygude Gaurav Kumar Ameta Ihtiram Raza Khan Pavitar Parkash Singh Renato R.Maaliw III Natrayan Lakshmaiya Mohammad Shabaz Muhammad Attique Khan Hany S.Hussein Hammam Alshazly Department of Data Science University of WashingtonSeattleWashingtonUSA Department of Computer Science&Engineering Parul Institute of TechnologyParul UniversityVadodaraGujaratIndia Department of Computer Science Jamia HamdardDelhiIndia Department of Management Lovely Professional UniversityPhagwaraIndia 5 College of Engineering Southern Luzon State UniversityLucbanQuezonPhilippines Department of Mechanical Engineering Saveetha School of EngineeringSIMATSChennaiTamil NaduIndia Model Institute of Engineering and Technology JammuJ&KIndia Department of Computer Science HITEC UniversityTaxilaPakistan Department of Computer Science and Mathematics Lebanese American UniversityBeirutLebanon Electrical Engineering Department College of EngineeringKing Khalid UniversityAbhaSaudi Arabia Electrical Engineering Department Aswan UniversityAswanEgypt Faculty of Computers and Information South Valley UniversityQenaEgypt

Deep learning has recently become a viable approach for classifying Alzheimer's disease(AD)in medical ***,existing models struggle to efficiently extract features from medical images and may squander additional information resources for illness *** address these issues,a deep three‐dimensional convolutional neural network incorporating multi‐task learning and attention mechanisms is *** upgraded primary C3D network is utilised to create rougher low‐level feature *** introduces a new convolution block that focuses on the structural aspects of the magnetORCID:ic resonance imaging image and another block that extracts attention weights unique to certain pixel positions in the feature map and multiplies them with the feature map ***,several fully connected layers are used to achieve multi‐task learning,generating three outputs,including the primary classification *** other two outputs employ backpropagation during training to improve the primary classification *** findings show that the authors’proposed method outperforms current approaches for classifying AD,achieving enhanced classification accuracy and other in-dicators on the Alzheimer's disease Neuroimaging Initiative *** authors demonstrate promise for future disease classification studies.

关键词： classification deep learning

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Solving non-cyclic dynamic multi-objective optimization problems via GRU prediction and multi-information hybrid exploration

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Journal of Supercomputing 2025年第8期81卷 1-34页

作者： Sun, Hao Bai, Xiaochuang Wang, Cong Yang, He Hu, Ziyu School of Electrical and Engineering Yanshan University Hebei Qinhuangdao066004 China Key Laboratory of Industrial Computer Control Engineering of Hebei Province Yanshan University Hebei Qinhuangdao066004 China Electrical automation department Tianjin Research Institute of Electric Science Co. Ltd. Tianjin China

In non-cyclic dynamic multi-objective optimization problems, the non-cyclic nature of environmental changes may cause the Pareto optimal front (PF) to be different from historical times. In addition, changes may also occur on the Pareto optimal solutions set (PS). However, predictions based solely on a single space show lower accuracy due to insufficient information. Therefore, solving non-cyclic dynamic multi-objective optimization problems via gate recurrent unit (GRU) prediction and multi-information hybrid exploration (GPMHE) is designed to overcome the above challenges. In the objective space, the GRU-based prediction strategy (GP) captures patterns of population change, predicts its distribution in new environments, and subsequently maps the results to the decision space;The multi-information hybrid exploration strategy (MHE) takes the feature individual as the representative individual, adaptively guides the population evolution direction in the decision space, thereby enhancing the algorithm’s adaptability. Compared with five advanced algorithms on the non-cyclic dynamic benchmark test set (NCD), the proposed algorithm GPMHE has shown robust adaptation to dynamic environmental changes. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Multiobjective optimization

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