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Resource Allocation in a RIS-Assisted TDMA Wireless Powered Sensor Network Using UAV

IEEE Communications Letters 2025年第6期29卷 1375-1379页

作者： Ghasemi, Omid Abachian Chehel Amirani, Mehdi Urmia University Electrical and Computer Engineering Department Urmia57179-44514 Iran

Integrating reconfigurable intelligent surfaces (RISs) with energy harvesting technology offers a promising solution to enhance the performance of wireless networks. This letter investigates an RIS-assisted wireless powered sensor network (WPSN) where sensors distributed in an area harvest energy from an unmanned aerial vehicle (UAV) and subsequently transmit their data to the fusion center (FC) using the Time Division Multiple Access (TDMA) protocol, aided by an RIS mounted on the UAV. In the proposed model, the wireless power transfer (WPT) time is predetermined as a fraction of the total data transmission time and is excluded from the optimization variables. The objective is to maximize the sum throughput by optimally allocating time to the sensors and adjusting the phase shifts of the RIS elements. The resulting non-convex optimization problem is solved by decomposing it into two subproblems: first, determining the optimal phase shifts;and second, developing an algorithm for optimal time allocation using the Lagrange dual method and Karush-Kuhn-Tucker (KKT) conditions. Excluding the WPT time from the optimization variables enables us to develop an efficient algorithm for time allocation with significantly reduced execution time compared to scenarios where WPT time is also an optimization variable, while maintaining comparable performance. Numerical results demonstrate that the proposed method significantly improves the network's performance. © 2025 IEEE.

关键词： Convex optimization

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Utilization of Two Cross Two Switch for Bitonic Sorting Circuit

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Micro and Nanosystems 2025年第1期17卷 45-57页

作者： Bhattacharjee, Subhasree Sarkar, Soumyadip Das, Kunal Sadhu, Arindam Sarkar, Bikramjit Department of Computer Application Narula Institute of Technology Kolkata India Department of Computer Science Acharya Prafulla Chandra College Kolkata India Department of Electronics & Communication Engineering Greater Kolkata College of Engineering and Management West Bengal India Department of Computer Science & Engineering JIS College of Engineering West Bengal India

Background: The synthesis of reversible logic has gained prominence as a crucial research area, particularly in the context of post-CMOS computing devices, notably quantum computing. Objective: To implement the bitonic sorting circuit, 2x2 switch, is used. The overarching objective of implementing a reversible sorting circuit is to mitigate power consumption while promising secure communication. The successful implementation of the bitonic sorting circuit utilizing the proposed 2x2 switch is validated through simulations conducted in IBM Qiskit. Methods: This study begins by employing the control swap gate to implement a 2x2 switch, aimed at enabling concurrent computing operations within multiprocessor systems to enhance throughput. Subsequently, following the successful implementation of the 2x2 switch, the study proceeds to design a bitonic sorting circuit. Results: Bitonic sort using a 2x2 switch on the IBM Quantum Experience (IBMQ) platform via the QISKit SDK in Python 3.6. Specifically, Qiskit v0.29.0 is utilized, with OpenQASM. OpenQASM serves as the quantum assembly and instruction language. Conclusion: This work presents a methodology for constructing a 2x2 switch, utilizing a reversible control swap gate as its core component. Additionally, it demonstrates the intricate development and implementation of a bitonic sorting circuit, capitalizing on this innovative switch architecture. © 2025 Bentham science Publishers.

关键词： Quantum computers

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AGG: attention-based gated convolutional GAN with prior guidance for image inpainting

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Neural Computing and Applications 2024年第20期36卷 12589-12604页

作者： Yu, Xiankang Dai, Lei Chen, Zhihua Sheng, Bin Department of Computer Science and Engineering East China University of Science and Technology Shanghai200237 China Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai200240 China

Image inpainting has made great achievements recently, but it is often tough to generate a semantically consistent image when faced with large missing areas in complex scenes. To address semantic and structural alignment in existing methods for image inpainting, this paper proposes an end-to-end attention-based gated convolution GAN with prior guidance named AGG, which designs the spatial and channel attention mechanisms for full extraction of semantic and structural features. Moreover, AGG constructs the attention-based upsampling module based on the channel attention to refine the feature map and capture more details from features of up-level low sizes. AGG uses the image contour as prior, allowing the gated convolution and attention mechanism may fill the image efficiently by focusing on the contour information. The attention-based gated convolution can effectively capture the global features and compensate for the limitations of the restricted receptive field of the naive convolution. Compared to other models, AGG generates images with finer outline features and no common problems such as the watermark and blur, which shows the best overall performance on the Paris StreetView, CelebA-HQ, and Places2 datasets. The best FID, LPIPS, PSNR, and SSIM values achieved by AGG are 2.18, 0.046, 30.82, and 0.951 on the CelebA-HQ dataset, with at least 3.21% and 6.52% performance improvement on FID and LPIPS compared to state-of-the-art methods, respectively. The source code will be available at https://***/Shawn-Yu-1/AGGNet. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024. corrected publication 2024.

关键词： Convolution

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How Does a Swarm Exhibit Emergent Behavior Through Synchronization?

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Journal of Institute of Control, Robotics and Systems 2024年第4期30卷 352-362页

作者： Shim, Hyungbo ASRI Electrical and Computer Engineering Department Seoul National University Korea Republic of

A swarm of individuals often exhibits behaviors that are not possible for each individual. This phenomenon is called emergence, and this paper mathematically demonstrates that new dynamics can arise in swarm behavior that cannot be explained by the dynamics of individuals. In particular, we argue that emergence occurs when heterogeneity is coupled with synchronization. These two concepts may seem conflicting, as heterogeneity is the tendency to differ whereas synchronization is the tendency toward sameness. However, we show that emergent behavior arises from the interplay between the two. © ICROS 2024.

关键词： Multi agent systems

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Comprehensive Design, Modeling and Analysis of Grid-Forming Type IV Wind Turbine Generators using State-Space Methods

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IEEE Access 2025年 13卷 91089-91112页

作者： Udawatte, Harith E. Ravanji, Mohammad H. Bahrani, Behrooz Monash University Department of Electrical & Computer Systems Engineering ClaytonVIC3800 Australia Sharif University of Technology Department of Electrical Engineering Tehran Iran

Grid-forming (GFM) control has emerged as a promising solution to the challenges posed by the increasing reliance on inverter-based resources (IBRs). However, unlike in a battery-based IBR, the implementation of GFM in wind turbine generators (WTGs) introduces challenges due to multiple machine-side converter (MSC) and grid-side converter (GSC) interactions. In this work, a GFM-WTG control structure is adopted in which the MSC primarily regulates the DC-link voltage, while the GSC emulates grid-forming behavior using virtual synchronous generator principles. Accordingly, this paper presents a practical control implementation scheme and a systematic small-signal modeling framework for GFM WTGs using the component connection method, enabling a unified state-space representation that captures key electromechanical, aerodynamic and control interactions inside the GFM-WTG system. The proposed model is validated through electromagnetic transient simulations, and eigenvalue and participation factor analyses reveal strong MSC-GSC inter-dependencies. Sensitivity analysis further confirms model accuracy across varying operating conditions. Additionally, a reduced-order model is derived to balance computational efficiency with dynamic fidelity. The findings provide a robust foundation for stability analysis and control tuning of GFM WTGs, supporting their reliable integration into future power grids. © 2013 IEEE.

关键词： Electric power transmission networks

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Transient Characteristics and Accommodative Current Limiting Strategy for Bidirectional Interlinking Converters in Hybrid AC/DC Microgrids

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CSEE Journal of Power and Energy Systems 2024年第4期10卷 1575-1588页

作者： Xia Shen Zhikang Shuai Wen Huang Chao Shen Yang Shen Z.John Shen College of Electrical and Information Engineering Hunan UniversityChangsha 410082China Department of Electrical and Computer Engineering Illinois Institute of TechnologyChicagoIL 60616 USA

Bidirectional interlinking converter(BIC)is the core equipment in a hybrid AC/DC microgrid connected between AC and DC ***,the variety of control modes and flexible bidirectional power flow complicate the influence of AC faults on BIC itself and on DC sub-grid,which potentially threaten both converter safety and system *** study first investigates AC fault influence on the BIC and DC bus voltage under different BIC control modes and different pre-fault operation states,by developing a mathematical model and equivalent sequence ***,based on the analysis results,a general accommodative current limiting strategy is proposed for BIC without limitations to specific mode or operation *** amplitude is predicted and constrained according to the critical requirements to protect the BIC and relieving the AC fault influence on the DC bus *** with conventional methods,potential current limit failure and distortions under asymmetric faults can also be ***,experiments verify feasibility of the proposed method.

关键词： Bidirectional interlinking converter current limiting fault characteristic hybrid AC/DC microgrid variation/oscillation of DC bus voltage

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Aggregated DER_A Model Parameterization Via Online Moving Horizon Estimation

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IEEE Transactions on Smart Grid 2025年第4期16卷 3030-3044页

作者： Vasquez-Plaza, Jesus D. Subedi, Sunil Bhujel, Niranjan Hansen, Timothy M. Tonkoski, Reinaldo Andrade, Fabio Department of Electrical and Computer Engineering University of Puerto Rico Mayaguez Mayagüez PR USA Electrification and Infrastructures Division Oak Ridge National Laboratory Knoxville TN USA Electrical Engineering and Computer Science Department The University of Maine Orono ME USA Electrical Engineering and Computer Science Department South Dakota State University Brookings SD USA Chair of Electric Power Transmission and Distribution School of Engineering and Design Technical University of Munich Munich Germany

This paper introduces a methodology for parameterizing the DER A model using a novel smooth mathematical representation, simplifying the process and preserving accuracy in modeling inverter-based generator (IBG). The methodology employs an online parameterization process that can operate in real-time. The model parameterization process is structured into five sequential steps, each targeting a specific aspect of the DER A model through moving horizon estimation. This approach adapts to systems with varying voltage and frequency support requirements by selectively applying each step. Simulation results on systems with both known and unknown parameters validate the methodologys effectiveness. The online moving horizon estimation technique accurately captures the dynamics of the overall system and ensures that the parameterized DER A model closely mirrors the real systems voltage, current, and power dynamics. The findings highlight the potential of this methodology to substantially improve and simplify the dynamic modeling of power systems, paving the way for more reliable and robust IBG and grid integration. © 2010-2012 IEEE.

关键词： Parameterization

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A Versatile Converter and Consolidated Energy Management Scheme for Modern AAVs

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IEEE Transactions on Aerospace and Electronic Systems 2025年第3期61卷 7264-7278页

作者： Mishra, Anjanee Kumar Singh, Ankit Kumar Kim, Taehyung Netaji Subhas University of Technology Department of Electrical Engineering Delhi India University of Michigan – Dearborn Electrical and Computer Engineering Department Dearborn United States

This article presents a versatile power converter and a hybrid energy source propulsion system for reliable, lightweight, and extended flight endurance autonomous aerial vehicles. The proposed converter is designed to operate in various configurations to meet different flight mission requirements. It efficiently harvests power from solar panels, fuel cells, and a battery without requiring an additional converter in multiple working conditions. Furthermore, when the aircraft is in rest mode, the converter can act in power factor correction converter mode. The proposed converter can minimize the number of components by integrating step-up and step-down operation capabilities as required for the objective. A brushless dc motor is used as the propulsion motor in the system because of its distinct benefits and unique features. Moreover, this work also discusses a unique technique to emulate the avionic load subsystem. The system is initially simulated using MATLAB/Simulink, and then it is verified on a real-time test bench. © 1965-2011 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Fast sampling from constrained spaces using the Metropolis-adjusted Mirror Langevin algorithm 37

Fast sampling from constrained spaces using the Metropolis-a...

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37th Annual Conference on Learning Theory, COLT 2024

作者： Srinivasan, Vishwak Wibisono, Andre Wilson, Ashia Department of Electrical Engineering and Computer Science MIT United States Department of Computer Science Yale University United States

We propose a new method called the Metropolis-adjusted Mirror Langevin algorithm for approximate sampling from distributions whose support is a compact and convex set. This algorithm adds an accept-reject filter to the Markov chain induced by a single step of the Mirror Langevin algorithm (Zhang et al., 2020), which is a basic discretisation of the Mirror Langevin dynamics. Due to the inclusion of this filter, our method is unbiased relative to the target, while known discretisations of the Mirror Langevin dynamics including the Mirror Langevin algorithm have an asymptotic bias. For this algorithm, we also give upper bounds for the number of iterations taken to mix to a constrained distribution whose potential is relatively smooth, convex, and Lipschitz continuous with respect to a self-concordant mirror function. As a consequence of the reversibility of the Markov chain induced by the inclusion of the Metropolis-Hastings filter, we obtain an exponentially better dependence on the error tolerance for approximate constrained sampling. © 2024 V. Srinivasan, A. Wibisono & A. Wilson.

关键词： Markov chains

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Pneumonia Net: Pneumonia Detection and Categorization in Chest X-ray Images

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Recent Advances in computer science and Communications 2024年第3期17卷 20-31页

作者： Srivastava, Somya Verma, Seema Das, Nripendra Narayan Sharma, Shraddha Dubey, Gaurav Department of Computer Science ABES Engineering College Ghaziabad India Department of Computer Science and Engineering Guru Gobind Singh Indraprastha University Delhi India Department of Information Technology Manipal University Jaipur Rajasthan Jaipur India Department of Computer Science Pandit Deendayal Energy University Gujarat India Department of Computer Science KIET Group of Institutions Ghaziabad India

Background: Pneumonia is one of the leading causes of death and disability due to respiratory infections. The key to successful treatment of pneumonia is in its early diagnosis and correct classification. PneumoniaNet is a unique deep-learning model based on CNN for identifying pneumonia on chest X-rays. Objective: A deep learning model that combines convolutional, pooling, and fully connected layers is presented in this study. Methods: In order to learn how to identify cases of pneumonia and healthy controls on chest X-ray pictures, PneumoniaNet was trained on a large labeled library of such images. A robust data augmentation technique was adopted to enhance the model generalization and training set diversity. Standard measures like as accuracy, precision, recall, and F1-score were applied to PneumoniaNet's performance evaluation. Results: The suggested model performed effectively in detecting pneumonia cases with an accuracy of 93.88%. Conclusion: The model was evaluated against the current state-of-art methods and showed that PneumoniaNet outperformed the other models. © 2024 Bentham science Publishers.

关键词： Deep learning

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