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2023 IEEE Conference on Control Technology and Applications, CCTA 2023

作者： Tully, Zachary Starke, Genevieve Johnson, Kathryn King, Jennifer Colorado School of Mines Advanced Energy Systems Graduate Program GoldenCO80401 United States National Renewable Energy Laboratory GoldenCO80401 United States Colorado School of Mines Electrical Engineering Department GoldenCO80401 United States

ISBN: (纸本)9798350335446

With the growing demand for renewable-energy-powered hydrogen generation and the corresponding increase in plant capacity, individually controlling many electrolyzer stacks will be critical for increasing the plant's lifetime and efficiency. This paper introduces a rule-based controller framework targeting electrolyzer degradation to explore the opportunity space in multi-stack hydrogen plant control. A novel control-oriented degradation model is also presented in this work, which quantifies the impact of steady power input, fluctuating power input, and the number of startup/shutdown cycles on electrolyzer degradation. Using a wind power input signal, 13 controller configurations are tested on 5 MW hydrogen plants consisting of 2, 5, 10, and 25 stacks. These configurations are evaluated on their capability to mitigate electrolyzer degradation and efficiently produce hydrogen from the time-varying input power. The results show that multi-stack control for degradation can extend the plant's lifetime by more than a factor of 3 with minimal impact on instantaneous hydrogen production. © 2023 IEEE.

关键词： Controllers

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Energy-aware Model Predictive Control with Obstacle Avoidance

Energy-aware Model Predictive Control with Obstacle Avoidanc...

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2021 International Conference on Unmanned Aircraft Systems, ICUAS 2021

作者： Santos, Marcelo A. Ferramosca, Antonio Raffo, Guilherme V. Federal University of Minas Gerais Graduate Program in Electrical Engineering Belo Horizonte Brazil University of Bergamo Department of Management Information and Production Engineering Dalmine24044 Italy Federal University of Minas Gerais Department of Electronics Engineering Belo Horizonte Brazil

ISBN: (纸本)9780738131153

This work proposes a single-layer finite-horizon optimal control strategy to solve the autonomous navigation problem while accounting for energy efficiency and providing obstacle avoidance feature in cluttered environments with unknown obstacles. Considering the rate capacity effect of electric batteries, the nonlinear state-of-charge behavior is described and included in the optimal control problem to achieve energy-awareness. Besides, artificial potential fields are considered to obtain obstacle avoidance capabilities. The control problem is formulated inspired by the tracking model predictive control framework, and it considers the central idea of including artificial variables into the control problem to obtain a closed-loop system with an enlarged domain of attraction and with feasibility insurance. Finally, numerical results in a case study considering a quadrotor UAV are provided to corroborate the proposed strategy. © 2021 IEEE.

关键词： Energy efficiency

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Reducing Errors and Powers in Lpddr for Dnn Inference: A Compression and Iecc-Based Approach

SSRN

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SSRN 2025年

作者： Hong, Jae-Youn Jang, Je-Woo Cho, Sung-Hyuk Kong, Youngbae Kim, Sungkyu Kang, Youngjung Ko, Jaehyung Chung, Jaeyong Yang, Joon-Sung Department of Electrical and Electronic Engineering Yonsei University Seoul Korea Republic of Memory Division Samsung Electronics Hwaseong Korea Republic of Department of System Semiconductor Engineering Yonsei University Seoul Korea Republic of BK21 Graduate Program in Intelligent Semiconductor Technology Yonsei University Seoul Korea Republic of

In modern edge systems, the demand for data processing for complex DNN tasks, is rapidly increasing. To address this, various compression schemes have been proposed to enable on-device AI while meeting the strictpower and storage constraints. However, despite these advancements, the compatibility of the compression methods with edge device memory(LPDDR), has not been thoroughly investigated. LPDDR operates at low voltage and faces reliability challenges, which is particularly concerning for applications where accuracy is critical, such as ADAS or medical devices. To address these concerns, ECC engine, known as IECC, is employed within each LPDDR bank. While IECC improves reliability, it also incurs performance penalties due to Read-Modify-Write(RMW) operations and parity storage overheads. This paper introduces RELIA, a DNN weight compression scheme with three-stage protection, aimed at enabling power-efficient and reliable DNN operations in mobile environments. RELIA reduces the operation granularity of the IECC engine from SEC(136,128) to SEC(72,64), eliminating RMW overhead. Additionally, it proposes SEC-FOEC(72,64) scheme that can correct 99.97% of LPDDR errors. To mitigate the added storage overhead, compression scheme based on DNN weight characteristics is introduced. Experimental results show RELIA reduces power, cycle, energy, and storage by 17.35%, 13.2%, 32.7%, and 23.6%, respectively, while offering superior reliability. © 2025, The Authors. All rights reserved.

关键词： Biomedical equipment

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Evaluation of Transformer-Based Encoder on Conditional Graph Generation

Evaluation of Transformer-Based Encoder on Conditional Graph...

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IEEE Annual International Computer Software and Applications Conference (COMPSAC)

作者： Thamila E.H Abeywickrama Sho Tsugawa Akiko Manada Kohei Watabe Graduate School of Engineering Nagaoka University of Technology Nagaoka Niigata Japan Institute of Systems and Information Engineering University of Tsukuba Tsukuba Ibaraki Japan Department of Electrical Electronics and Information Engineering Nagaoka University of Technology Nagaoka Niigata Japan Graduate School of Science and Engineering Saitama University Saitama Saitama Japan

ISBN: (数字)9798350376968

ISBN: (纸本)9798350376975

Generating graphs using computational models is a critical activity with numerous applications, including social network research and biological network modeling. Despite sig-nificant breakthroughs in graph-generating technologies, modern machine learning for simulating complex real-world networks still requires effective improvement. Specifically, the ability to conditionally generate graphs while accounting for local and global structural elements has not been fully explored. This study presents a novel approach to graph generation that combines Transformer encoders' strong contextual understanding with Long Short Term Memory (LSTM) decoders' sequence modeling capabilities, all within a Conditional Variational Auto Encoder (CVAE) framework. Our methodology aims to fine-tune the structural features of generated graphs more accurately, representing an advancement in conditional graph generation. Our results, based on extensive tests versus standard generative models utilizing graph datasets, show that our model can more clearly tune global-level structural features' values better than conventional models.

关键词： Social networking (online) Computational modeling Machine learning Transformers Software Encoding Decoding

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A Load Compensation Controller for Off-the-shelf Unmanned Aerial Vehicles

A Load Compensation Controller for Off-the-shelf Unmanned Ae...

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Vinícius Pacheco Bacheti Daniel Khéde Dourado Villa Alexandre Santos Brandão Mário Sarcinelli-Filho The Graduate Program on Electrical Engineering Federal University of Espírito Santo Vitória ES Brazil The Department of Electrical Engineering Federal University of Viçosa Viçosa MG Brazil

This paper addresses the problem of controlling a system composed of a unmanned aerial vehicle and a payload attached to it via a cable, while compensating for the payload effects on the drone. This work considers that many off-the-shelf UAVs have their own low-level controller which the user cannot access, and attempts to merge the classical approach of modeling a drone-mass system with controllers previously developed for use with drones equipped with low-level controllers. In order to test such an approach the robot Anafi, from Parrot Drones SAS, was used with a mass attached to it. The experiments show a consistent reduction on navigation errors, which helps validate the proposed method.

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Sensitivity Analysis for Neutral Reactor Optimization

Sensitivity Analysis for Neutral Reactor Optimization

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Workshop on Communication Networks and Power Systems (WCNPS)

作者： L. S. Balbino K. M. Dantas W. L.A. Neves Electrical Engineering Graduate Program Federal University of Campina Grande (UFCG) Campina Grande Brazil Department of Electrical Engineering Federal University of Campina Grande (UFCG) Campina Grande PB Brazil

This paper presents an approach for choosing neutral reactors in transmission lines (TL) with shunt compensation. Data from the Brazilian Power Grid were used for digital simulations with ATPDraw, and a sensitivity analysis was carried out with various parameters (line length, neutral reactor, fault location) to find curves that correlate the optimum reactor value with the transmission line shunt compensation level. The influence of line length and compensation level are discussed. Limitations are presented, and the results show that the approach allows reactors to be obtained efficiently for most of the compensation range.

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Effect of Retraining Graph Generative Models with Generated Graphs

Effect of Retraining Graph Generative Models with Generated ...

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IEEE Annual International Computer Software and Applications Conference (COMPSAC)

作者： Takeru Inada Sho Tsugawa Akiko Manada Kohei Watabe Graduate School of Engineering Nagaoka University of Technology Nagaoka Niigata Japan Institute of Systems and Information Engineering University of Tsukuba Tsukuba Ibaraki Japan Department of Electrical Electronics and Information Engineering Nagaoka University of Technology Nagaoka Niigata Japan Graduate School of Science and Engineering Saitama University Saitama Saitama Japan

ISBN: (数字)9798350376968

ISBN: (纸本)9798350376975

In recent years, there has been a growing demand for techniques to artificially generate graphs. Various proposals have been made for graph generation models using machine learning. Among these models, GraphTune is a model that allows to specify the features of the generated graphs. GraphTune has not achieved sufficient accuracy when specified values are in ranges where there are few samples in the training dataset. Therefore, in this paper, we propose a method to improve the accuracy of GraphTune by retraining it using graphs generated by the model itself. Through experiments using real-world graphs, we demonstrate that the higher accuracy can be achieved compared to the conventional method.

关键词： Training Accuracy Computational modeling Machine learning Software Proposals

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Revisiting Near-Far Field Boundary in Dual-Polarized XL-MIMO Systems

arXiv

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arXiv 2025年

作者： Zeng, Shuhao Di, Boya Zhang, Hongliang Han, Zhu Vincent Poor, H. School of Electronic and Computer Engineering Peking University Shenzhen Graduate School Shenzhen China Department of Electrical and Computer Engineering Princeton University NJ United States School of Electronics Peking University Beijing100871 China Electrical and Computer Engineering Department University of Houston HoustonTX United States Department of Computer Science and Engineering Kyung Hee University Seoul Korea Republic of

Extremely large-scale multiple-input multiple-output (XL-MIMO) is expected to be an important technology in future sixth generation (6G) networks. Compared with conventional single-polarized XL-MIMO, where signals are transmitted and received in only one polarization direction, dual-polarized XL-MIMO systems achieve higher data rate by improving multiplexing performances, and thus are the focus of this paper. Due to enlarged aperture, near-field regions become non-negligible in XL-MIMO communications, necessitating accurate near-far field boundary characterizations. However, existing boundaries developed for single-polarized systems only consider phase or power differences across array elements while irrespective of cross-polarization discrimination (XPD) variances in dual-polarized XL-MIMO systems, deteriorating transmit covariance optimization performances. In this paper, we revisit near-far field boundaries for dual-polarized XL-MIMO systems by taking XPD differences into account, which faces the following challenge. Unlike existing near-far field boundaries, which only need to consider co-polarized channel components, deriving boundaries for dual-polarized XL-MIMO systems requires modeling joint effects of co-polarized and cross-polarized components. To address this issue, we model XPD variations across antennas and introduce a non-uniform XPD distance to complement existing near-far field boundaries. Based on the new distance criterion, we propose an efficient scheme to optimize transmit covariance. Numerical results validate our analysis and demonstrate the proposed algorithm’s effectiveness. Copyright © 2025, The Authors. All rights reserved.

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Advance Artificial Intelligence Technique for Designing Double T-Shaped Monopole Antenna

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Computers, Materials & Continua 2021年第12期69卷 2983-2995页

作者： El-Sayed M.El-kenawy Hattan F.Abutarboush Ali Wagdy Mohamed Abdelhameed Ibrahim Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Electrical Engineering Department College of EngineeringTaibah UniversityMedina 42353Saudi Arabia Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza 12613Egypt Wireless Intelligent Networks Center(WINC) School of Engineering and Applied SciencesNile UniversityGizaEgypt Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt

Machine learning(ML)has taken the world by a tornado with its prevalent applications in automating ordinary tasks and using turbulent insights throughout scientific research and design *** is a massive area within artificial intelligence(AI)that focuses on obtaining valuable information out of data,explaining why ML has often been related to stats and data *** advanced meta-heuristic optimization algorithm is proposed in this work for the optimization problem of antenna architecture *** algorithm is designed,depending on the hybrid between the Sine Cosine Algorithm(SCA)and the Grey Wolf Optimizer(GWO),to train neural networkbased Multilayer Perceptron(MLP).The proposed optimization algorithm is a practical,versatile,and trustworthy platform to recognize the design parameters in an optimal way for an endorsement double T-shaped monopole *** proposed algorithm likewise shows a comparative and statistical analysis by different curves in addition to the ANOVA and *** offers the superiority and validation stability evaluation of the predicted results to verify the procedures’accuracy.

关键词： Antenna optimization machine learning artificial intelligence multilayer perceptron sine cosine algorithm grey wolf optimizer

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An Open-Source GPU-Based Acoustic Simulator for Fast and Accurate Modeling of Acoustic Scattering

An Open-Source GPU-Based Acoustic Simulator for Fast and Acc...

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IEEE International Symposium on Applications of Ferroelectrics (ISAF)

作者： Zixuan Tian Yun Jing Aiguo Han Department of Electrical and Computer Engineering University of Illinois Urbana-Champaign Urbana USA Graduate Program in Acoustics Pennsylvania State University USA Department of Biomedical Engineering and Mechanics Virginia Polytechnic Institute and State University Blacksburg USA

ISBN: (数字)9798350371901

ISBN: (纸本)9798350371918

Fast, accurate, and realistic simulations of ultrasonic scattering in biological tissues play an important role in biomedical ultrasound research. This study introduces UltraWave, a new open-source ultrasound simulation tool we developed for accurately modeling acoustic and elastic wave propagation in two- and three-dimensional heterogeneous media. UltraWave allows the utilization of multiple graphics processing units (GPUs) to deliver faster and more accurate full-wave simulations. The perfectly matched layer was integrated into the simulator. UltraWave was validated against well-established scattering theories in a variety of basic scattering scenarios, and achieved similar or higher accuracy than the widely used k-Wave toolbox. Additionally, UltraWave outperformed k-Wave in terms of computational efficiency with both central processing units (CPUs) and GPUs, particularly when using GPU acceleration for elastic wave simulations. These results demonstrated the potential of UltraWave as a promising tool for biomedical ultrasound simulations.

关键词： Solid modeling Accuracy Ultrasonic imaging Biological system modeling Computational modeling Graphics processing units Media Acoustics Computational efficiency Perfectly matched layers

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