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Dual-Buck Bipolar Buck-Boost AC-AC Converter With Reduced Semiconductor Devices

IEEE Transactions on Industrial Electronics 2024年第9期71卷 10495-10511页

作者： Ahmed, Hafiz Furqan Chien, Howard Khan, Ashraf Ali Islam, Shirazul Akbar, Fazal Alzaabi, Omar National Sun Yat-sen University Department of Electrical Engineering Kaohsiung80424 Taiwan Memorial University of Newfoundland Faculty of Engineering And Applied Science Department of Electrical And Computer Engineering St. John'sNLA1B 3X9 Canada Qatar University Department of Electrical Engineering Doha2713 Qatar University of Edinburgh EdinburghEH9 3JL United Kingdom Khalifa University Department of Electrical Engineering And Computer Science Advanced Power And Energy Center Abu Dhabi127788 United Arab Emirates

Dual-buck (DB) structured ac-ac converters are becoming advanced due to their inherent protection from open- and short-circuit risks, and elimination of commutation issue. However, the existing DB ac-ac converters provide restricted bipolar voltage operations with a large semiconductor device count and underutilized inductors. This article proposed a new reduced switch DB ac-ac converter without commutation issue. The propose converter provides multiple buck-boost voltage operations with noninverting and inverting outputs, making it a flexible topology for various ac voltage applications. The propose converter exhibits the continuous input and output currents irrespective of operation mode, and performs well with nonunity power factor loads. The positive and negative voltage gains of the proposed converter can address the grid voltage sag and swell issues, respectively, making it right candidate for application as dynamic voltage restorer. A detailed comparative evaluation is carried out with existing DB converters, which validated the effectiveness of the proposed converter, including;reduced semiconductor device count and their power ratings, reduced inductor sizes with improved magnetic utilization, enhanced voltage compensation ranges, and better efficiency. A laboratory scale hardware prototype of the proposed converter is built and thoroughly tested to validate its operation. © 1982-2012 IEEE.

关键词： Semiconductor devices

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Watch You under Low-Resolution and Low-Illumination: Face Enhancement via Bi-Factor Degradation Decoupling

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IEEE Transactions on Circuits and Systems for Video Technology 2024年第5期34卷 3481-3495页

作者： Ding, Xin Wang, Zheng Fang, Jing Shu, Zhenyu Hu, Ruimin Lin, Chia-Wen NingboTech University School of Computer and Data Engineering Ningbo315100 China Wuhan University National Engineering Research Center for Multimedia Software School of Computer Wuhan430072 China National Tsing Hua University Department of Electrical Engineering The Institute of Communications Engineering Hsinchu300044 Taiwan

Face enhancement aims to improve low-quality face images to a higher-quality level. However, in real-world nighttime scenes, complex degradation factors often affect these images, making it challenging to preserve important facial details. Existing image enhancement algorithms typically focus on independently conducting image super-resolution and brightness enhancement, assuming a fixed degradation level based on simulated training datasets. Nonetheless, real nighttime scenes involve complex degradation processes, where degradation factors dynamically and variably manifest. Therefore, achieving effective face enhancement in such scenarios is particularly daunting. This work analyzes and unveils the multiple factors of low resolution and low illumination during degradation. Based on this analysis, we propose a Bi-factor Degradation Decoupling network. Our method leverages a decoupling network to generate qualitative and quantitative features corresponding to each factor's degradation degree in the low-quality environment. These features are then combined with robust facial feature constraints to recover the details of low-quality faces. Extensive experiments demonstrate that our method surpasses state-of-the-art approaches in both enhancement and face super-resolution. © 1991-2012 IEEE.

关键词： Image reconstruction

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Enhancing AI-Supported Channel Estimation in MIMO Systems with Open Set Recognition

Enhancing AI-Supported Channel Estimation in MIMO Systems wi...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Zhang, Huiwen Kumar, Venkataramani Ye, Feng Hu, Rose Qingyang Qian, Yi University of Wisconsin-Madison Department of Electrical and Computer Engineering MadisonWI United States University of Puerto Rico Department of Computer Science and Engineering Mayaguez Puerto Rico Utah State University Department of Electrical and Computer Engineering LoganUT United States University of Nebraska-Lincoln Department of Electrical and Computer Engineering OmahaNE United States

ISBN: (纸本)9798350351255

Accurate channel estimation is required for various multiple input multiple output (MIMO) implementations in the next-generation wireless communication systems. Recently, Artificial Intelligence (AI) techniques have been introduced for channel state information (CSI) processing in channel estimation because of their accuracy and relatively low complexity compared to the traditional approaches. However, these AI-supported CSI processing models are usually developed with a fixed training dataset. Therefore, the performance of such approaches cannot be guaranteed in new environments. This paper focuses on enhancing AI-supported channel estimation methods with a 2-stage open set recognition scheme. New environments are detected in the first stage by identifying different characteristics between testing and training data. In the second stage, new data is filtered and further categorized to each individual environment. Simulation results using four different environment settings demonstrate that the proposed method can greatly enhance the usability of AI-supported channel estimation. © 2024 IEEE.

关键词： Channel state information

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Optimizing Crisis Management with Advanced UAV Imaging Technology 4

Optimizing Crisis Management with Advanced UAV Imaging Techn...

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4th International Conference on Sustainable Expert Systems, ICSES 2024

作者： Reddy, Jambula Snehith Mathi, Sri Chaithanya Reddy, Polu Sai Nadh Mateti, Vedha Pranava Yadav, Sudha Amrita School of Engineering Department of Electrical and Electronics Engineering Bengaluru India Amrita School of Engineering Department of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798331540364

The UAV systems that are fitted with current technology have helped in boosting the crisis management activities such as disaster relief operations, search and rescues, and policing. This paper integrates the developmental function of advanced detective UAVs into episodes of crises. These UAVs are capable of quickly and effectively assessing the damage, find people and observe post-disaster occurrences through with the help of complicated image analysis. It incorporates cameras with HD resolutions, thermal imagery systems, and numerous ML algorithms that allow entities and people to be identified besides detecting heat through barriers and thus increase the operational effectiveness during response operations. Indeed, the social implication as noticed with detective UAVs is highly useful in that it provides support services in disaster, bringing relief directly to the affected groups and guaranteeing the security of the rescue squads. Therefore, these UAVs enhance crisis consequence management, reducing death rates, the number of casualties and the extent of property damage. They do also help in safety and security to the public through assisting the police in surveillance and the fight against crime. Analyzing UAV's physical and virtual units, the challenges describe the UAV's use cases in different kinds of crises, such as natural ones, industrial failures, and criminal events. It also deals with issues such as restrictive policies, data security, and the requirement of professional personnel. From case studies and more personal accounts, detective UAVs' potential of crisis management is revolutionary: loss of life is avoided, damage to property is limited, and order is maintained. If further developed and properly integrated into the emergency management systems, UAVs will be the part of the equipment of the future for enhancing the efficiency of response to critical situations. © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Blockchain-Based Lightweight Certificateless Authenticated Key Agreement Protocol for V2V Communications in IoV

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IEEE Internet of Things Journal 2024年第16期11卷 27744-27759页

作者： Lin, Hui-Tang Jhuang, Wei-Li National Cheng Kung University Institute of Computer and Communication Engineering The Department of Electrical Engineering Tainan City701 Taiwan Silicon Motion Technology Corporation Zhubei Taiwan

With the emergence of the Internet of Things, traditional vehicular ad hoc networks have evolved into the more sophisticated Internet of Vehicles (IoV). IoV is expected to play a key role in the development of future smart cities and intelligent transportation systems. However, like most information technology systems, IoV is vulnerable to the cyberattack. A hacker may gain control over a vehicle, thereby posing serious danger to the vehicle occupants, surrounding vehicles and pedestrians. Consequently, improving the security of IoV is essential in ensuring its future success. Among the various security concerns surrounding IoV, secure communications and authentication are two of the most critical. Currently, most proposed works suffers the single-point-of-failure (SPOF) problem and the trusted third party (TTP) compromise issue. To address these issues, the present study proposes a secure key generation mechanism which leverages the advantages of blockchain technology and certificateless public-key cryptography. In the proposed method, the distributed architecture of blockchain is exploited to realize a decentralized TTP service to prevent the SPOF problem and the TTP compromise issue. In addition, an authenticated key agreement (AKA) protocol based on the legal key pairs is proposed to facilitate efficient mutual authentication and session key agreement between the vehicles. The security analysis results show that the proposed schemes have excellent resistance to the typical TTP issues. Moreover, the feasibility of the proposed AKA protocol is demonstrated through the extended Canetti-Krawczyk model. Finally, the performance analysis results show that the proposed scheme yields a significant reduction in the computational cost compared to the existing AKA protocols. © 2014 IEEE.

关键词： Smart contract

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SEF:A Smart and Energy-Aware Forwarding Strategy for NDN-Based Internet of Healthcare

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computers, Materials & Continua 2024年第12期81卷 4625-4658页

作者： Naeem Ali Askar Adib Habbal Hassen Hamouda Abdullah Mohammad Alnajim Sheroz Khan Department of Computer Engineering Faculty of EngineeringKarabük UniversityKarabük78050Türkiye Department ofManagement Information Systems College of Business AdministrationMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Information Technology College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Electrical Engineering College of Engineering and Information TechnologyOnaizah CollegesQassim51911Saudi Arabia

Named Data Networking(NDN)has emerged as a promising communication paradigm,emphasizing content-centric access rather than location-based *** model offers several advantages for Internet of Healthcare Things(IoHT)environments,including efficient content distribution,built-in security,and natural support for mobility and ***,existing NDN-based IoHT systems face inefficiencies in their forwarding strategy,where identical Interest packets are forwarded across multiple nodes,causing broadcast storms,increased collisions,higher energy consumption,and *** issues negatively impact healthcare system performance,particularly for individuals with disabilities and chronic diseases requiring continuous *** address these challenges,we propose a Smart and Energy-Aware Forwarding(SEF)strategy based on reinforcement learning for NDN-based *** SEF strategy leverages the geographical distance and energy levels of neighboring nodes,enabling devices to make more informed forwarding decisions and optimize next-hop *** approach reduces broadcast storms,optimizes overall energy consumption,and extends network *** system model,which targets smart hospitals and monitoring systems for individuals with disabilities,was examined in relation to the proposed *** SEF strategy was then implemented in the NS-3 simulation environment to assess its performance in healthcare *** demonstrated that SEF significantly enhanced NDN-based IoHT ***,it reduced energy consumption by up to 27.11%,82.23%,and 84.44%,decreased retrieval time by 20.23%,48.12%,and 51.65%,and achieved satisfaction rates that were approximately 0.69 higher than those of other strategies,even in more densely populated *** forwarding strategy is anticipated to substantially improve the quality and efficiency of NDN-based IoHT systems.

关键词： Energy efficient forwarding strategy health information system internet technologies IoHT people with disabilities reinforcement learning Q-learning

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A Promising Approach for Next-Generation Mobile Communications 3

A Promising Approach for Next-Generation Mobile Communicatio...

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3rd International Conference on electrical, Electronics, Information and Communication Technologies, ICEEICT 2024

作者： Abdulhussien, Saif A. Hamza, Noor Aldeen Ibrahim, Sarmad K. Mustansiriyah University College of Engineering Electrical Engineering Department Baghdad Iraq Mustansiriyah University College of Engineering Computer Engineering Department Baghdad Iraq

ISBN: (纸本)9798350369083

The introduction of 5G technology has intensified the demand for higher throughput in mobile communications. This study identifies and addresses key obstacles to optimal 5G throughput, focusing on spectrum allocation, interference mitigation, and resource management. We propose an innovative approach utilizing advanced algorithms and resource management strategies to enhance throughput efficiency. Simulations and real-world experiments demonstrate a 27% improvement in throughput performance over traditional 5G systems. This research contributes to ongoing 5G advancements by providing practical solutions to current throughput challenges, highlighting the potential of our technology to significantly enhance the performance and efficiency of future wireless communication systems. © 2024 IEEE.

关键词： 5G mobile communication systems

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Evolutionary Approach to GAN Hyperparameter Tuning: Minimizing Discriminator and Generator Loss Functions 14

Evolutionary Approach to GAN Hyperparameter Tuning: Minimizi...

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

作者： Klidbary, Sajad Haghzad Babaei, Anahita Ghorbani, Ramin Department of Computer Engineering Faculty of Engineering University of Zanjan Zanjan Iran Department of Electrical Engineering Faculty of Engineering University of Zanjan Zanjan Iran

ISBN: (纸本)9798331511272

Image Reconstruction has always been among machine vision’s challenging topics. One of image restoration’s most challenging is to fill the damaged area after deleting, it in a visually acceptable way. The beginning of image reconstruction goes back to the last five decades, but due to the ineffectiveness of the basic methods, new methods have been offered. In the field of image restoration, GAN or Generative Adversarial Networks can be very useful due to the high similarity between the generated data and the training data. In this paper, by presenting an algorithm based on these networks, we try to increase the accuracy of the image restoration process. The GAN's accuracy is related to the correct selection of parameters. Using trial and error methods to find parameters is time-consuming. In this paper, the optimal parameters of the GANs have been used by providing suitable coding for the genetic algorithm. The simulation results represent that the proposed GA has notable performance. The best results give a minimum value of about 0.16 for the discriminator loss function and 0 for the generator loss function. ©2024 IEEE.

关键词： Generative adversarial networks

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An Improved Vision Transformer Architecture-Based computer Recognition Platform for Lilium Classification

An Improved Vision Transformer Architecture-Based Computer R...

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2025 IEEE International Conference on Consumer Electronics, ICCE 2025

作者： Huang, Xiang-Rui Ke, Huai-Jhan Kuo, Szu-Yu Chen, Liang-Bi Master Program in Electrical Engineering and Computer Science Department of Electrical Engineering National Penghu University of Science and Technology Penghu Taiwan Department of Shipping and Transportation Management National Kaohsiung University of Science and Technology Kaohsiung Taiwan Department of Computer Science and Information Engineering National Penghu University of Science and Technology Penghu Taiwan

ISBN: (纸本)9798331521165

Lilies are popular in the global flower market, but consumers often lack information about specific varieties. To address this issue, this paper proposes a computer recognition platform based on the Vision Transformer (ViT) architecture. The proposed platform uses an improved vision transformer (ViT) architecture to classify different types of lilies, allowing consumers to access information and names of various Lilium species. The experimental results show that the proposed lily classification model achieved a 96.4% accuracy rate in classifying six lily species. © 2025 IEEE.

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Bi-LSTM-Based Deep Stacked Sequence-to-Sequence Autoencoder for Forecasting Solar Irradiation and Wind Speed

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computers, Materials & Continua 2023年第6期75卷 6375-6393页

作者： Neelam Mughees Mujtaba Hussain Jaffery Abdullah Mughees Anam Mughees Krzysztof Ejsmont Department of Electrical and Computer Engineering COMSATS University IslamabadLahore Campus45550Pakistan School of Engineering and Technology National Textile UniversityFaisalabad37610Pakistan Department of Electrical Engineering Information Technology UniversityLahore54000Pakistan Department of Electrical Engineering GC UniversityFaisalabad38000Pakistan Faculty of Mechanical and Industrial Engineering Warsaw University of Technology02-524WarsawPoland

Wind and solar energy are two popular forms of renewable energy used in microgrids and facilitating the transition towards net-zero carbon emissions by ***,they are exceedingly unpredictable since they rely highly on weather and atmospheric *** microgrids,smart energy management systems,such as integrated demand response programs,are permanently established on a step-ahead basis,which means that accu-rate forecasting of wind speed and solar irradiance intervals is becoming increasingly crucial to the optimal operation and planning of *** this in mind,a novel“bidirectional long short-term memory network”(Bi-LSTM)-based,deep stacked,sequence-to-sequence autoencoder(S2SAE)forecasting model for predicting short-term solar irradiation and wind speed was developed and evaluated in *** create a deep stacked S2SAE prediction model,a deep Bi-LSTM-based encoder and decoder are stacked on top of one another to reduce the dimension of the input sequence,extract its features,and then reconstruct it to produce the *** of the proposed deep stacked S2SAE forecasting model were optimized using the Bayesian optimization ***,the forecasting performance of the proposed Bi-LSTM-based deep stacked S2SAE model was compared to three other deep,and shallow stacked S2SAEs,i.e.,the LSTM-based deep stacked S2SAE model,gated recurrent unit-based deep stacked S2SAE model,and Bi-LSTM-based shallow stacked S2SAE *** these models were also optimized and modeled in *** results simulated based on actual data confirmed that the proposed model outperformed the alternatives by achieving an accuracy of up to 99.7%,which evidenced the high reliability of the proposed forecasting.

关键词： Deep stacked autoencoder sequence to sequence autoencoder bidirectional long short-term memory network wind speed forecasting solar irradiation forecasting

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