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Giant Trevally Optimizer (GTO): Enhancing HVDC Transmission Capacity with Optimized Fault Current Limiters and HVDC Circuit Breaker Parameters 3

Giant Trevally Optimizer (GTO): Enhancing HVDC Transmission ...

引用

3rd International Conference on Electronics and Renewable systems, ICEARS 2025

作者： Ramkumar, M. Siva Saranya, N. Gopan, Gokul Baig, Rahmath Ulla Josha Daniel, S. Babu, M. Sns College of Technology Department of Ece India Karpagam College of Engineering Department of Artificial Intelligence and Data Science India Department of Mechanical Engineering Chennai602105 India Cambridge Institute of Technology Department of Artificial Intelligence and Machine Learning K R Puram Bangalore560086 India Hindustan College of Engineering and Technology Department of Eee India Hindusthan College of Engineering and Technology Master of Engineering in Embedded Systems India

ISBN: (纸本)9798331509675

The multi-terminal HVDC system relies heavily on circuit breakers (CBs) and fault current limiters (FCLs) for protection and performance reliability. This research describes a new Giant Trevally optimizer-based strategy for improving the performance of 4-terminal HVDC systems by optimizing crucial circuit breakers and fault current limiters. The proposed method uses time domain estimation to correctly capture fault dynamics, such as traveling waves and reflection coefficients and finds the worst-case fault locations. The multi-objective optimization seeks to optimize the overcurrent, overvoltage handling, fault clearance time, and energy absorption in arresters. This technology provides an effective, dependable protection solution that reduces fault recovery time and increases system stability. The output pulse of the HVDC system shows very low THD results 1.98% for the minimum load condition, 0.87% for median load, and 0.04% for peak load conditions. The results established the simulation of the model in a MATLAB environment. © 2025 IEEE.

关键词： MATLAB

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Onboard Perception-Assisted High Fidelity Simulation Framework for Autonomous Planetary Soft-Landing

Onboard Perception-Assisted High Fidelity Simulation Framewo...

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AIAA science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Alibekov, Ulugbek Banerjee, Avijit Satpute, Sumeet Gajanan Nikolakopoulos, George ERASMUS MUNDUS JOINT MASTER in Intelligent Field Robotic Systems Faculty of Informatics Eötvös Loránd University Budapest Hungary Robotics and AI research group Department of Computer Science Electrical and Space Engineering Luleå University of Technology Luleå Sweden

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

This article presents an onboard perception-assisted high-fidelity simulation framework for autonomous planetary soft-landing, enabling visual information processing tightly integrated with advanced onboard guidance system in a realistic simulation environments. Utilizing the open source Unity game engine, a physics-based simulation toolbox integrated with the Robotic Operating System (ROS2), we effectively emulate the motion of spacecraft approaching planetary terrain. The simulation environment features a realistic 3D terrain model and a lander spacecraft equipped with onboard camera to effectively capture detailed local terrain images. The simulation engine accurately captures the spacecraft’s 6-degrees of freedom motion, seamlessly integrating space craft orientation with the associated camera feed while incorporating various illumination conditions using a light source representing the Sun. To demonstrate the efficacy of the framework, we implement a recently developed attitude-constrained minimum jerk guidance algorithm to emulate spacecraft motion. Concurrently, the visual feed from the onboard RGB camera is processed through a gradient extraction-based perception system, providing the visual odometer. This system identifies provably safe landing sites, effectively avoiding potential risks of landing on uneven terrain. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Planetary landers

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Frequency-Spatial Feature Fusion Network for Infrared and Visible Image Fusion 13th

Frequency-Spatial Feature Fusion Network for Infrared and Vi...

引用

13th International Conference on Information Technology and its Applications, CITA 2024

作者： Song, Wenhao Gao, Mingliang Li, Qilei Jeon, Gwanggil Camacho, David School of Electrical and Electronic Engineering Shandong University of Technology Zibo255000 China School of Electronic Engineering and Computer Science Queen Mary University of London LondonE1 4NS United Kingdom Department of Embedded Systems Engineering Incheon National University Incheon22012 Korea Republic of Madrid Spain

ISBN: (纸本)9783031741265

Infrared and visible image fusion seeks to retain complementary information from source images and generate a comprehensive image. Most fusion methods ignore the detailed information in the frequency domain. To address this problem, we propose a Frequency-spatial Feature Fusion Network (F3Net) in this work. The F3Net consists of three modules, namely Frequency-Spatial Feature Extraction Module (FSFEM), Feature Fusion Module (FFM), and Image Reconstruction Module (IRM). First, the FSFEM is built to extract complementary information from the source image separately in the frequency and spatial domains. Then, the FMM is introduced to fuse the features of the frequency and spatial domains. Finally, the fused image is reconstructed by IRM. Comprehensive experiments demonstrate that the F3Net outperforms the state-of-the-art (SOTA) methods subjectively and objectively. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Image fusion

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Development of a Wireless CPR Assistance Glove to Monitor and Guide Rescuers in Performing Cardiopulmonary Resuscitation 16

Development of a Wireless CPR Assistance Glove to Monitor an...

引用

16th IEEE Malaysia International Conference on Communication, MICC 2023

作者： Chang, Kai Han Chong, Kim Soon Tiang, Sew Sun Lim, Wei Hong Mokayef, Mastaneh Tan, Bee Sian Technology & Built Environment UCSI University Faculty of Engineering Kuala Lumpur Malaysia UCSI University Department Electrical & Electronic Engineering Kuala Lumpur Malaysia Tunku Abdul Rahman University of Management and Technology Department of Computer Science and Embedded Systems Kuala Lumpur Malaysia

ISBN: (纸本)9798350304343

Cardiopulmonary resuscitation (CPR) assistance glove represents a valuable tool for monitoring chest compressions during CPR, which is crucial for effective cardiac arrest response. By incorporating an MPU6050 accelerometer sensor and a force sensing resistor, the glove enables accurate measurement of the chest compression rate and force exerted. Preliminary testing demonstrated the glove's effectiveness in simulating chest compressions, with data collected and transmitted wirelessly to MATLAB software. Manual counting and MATLAB analysis validated the accuracy of compression rate calculations, while force sensing resistor voltage readings provided insights into the force exerted during compressions. These results highlight the glove's potential to significantly enhance the precision and quality of CPR administration, improving outcomes for cardiac arrest patients. © 2023 IEEE.

关键词： Resuscitation

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Computational Network-on-Chip as Convolution Engine

Computational Network-on-Chip as Convolution Engine

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Technology, systems and Applications (VLSI-TSA/VLSI-DAT), International VLSI Symposium on

作者： Zhonghai Lu Mingrui Liu Department of Electrical Engineering School of EECS KTH Royal Institute of Technology Stockholm Sweden Embedded Systems master program School of EECS KTH Royal Institute of Technology Stockholm Sweden

ISBN: (数字)9798350360349

ISBN: (纸本)9798350360356

Inspired by PiN, Processing in Network-on-Chip (NoC), we propose a computational NoC as a convolution engine for accelerating convolutional neural networks in hardware. In contrast to traditional compute architectures where computation and communication are conducted serially and in separation, our computational NoC enables in-transit computation, meaning that computation is performed while packets are transferred in the network. In the paper, we present the router architecture that supports the novel in-transit computation concept, and use a running example to detail the entire convolution process in the computational NoC. Finally, we show simulated performance results in comparison with traditional NoC-based convolution engine.

关键词： Convolution Simulation Computer architecture Network-on-chip Very large scale integration Hardware Pins

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Age Feature Enhanced Neural Network for RUL Estimation of Power Electronic Devices

Age Feature Enhanced Neural Network for RUL Estimation of Po...

引用

International Conference on Prognostics and Health Management, PHM

作者： Zhonghai Lu Rui Shi Chao Guo Mingrui Liu Department of Electrical Engineering KTH Royal Institute of Technology Stockholm Sweden Embedded Systems Master Program KTH Royal Institute of Technology Stockholm Sweden

Like other deep learning problems, critical features are critical to enable effective estimation of Remaining Useful Lifetime (RUL) for power electronic devices using Neural Networks (NNs). However, these critical features are often indirectly obtained after data pre-processing, complicated either in form (high dimension) or in computation (computation-intensive pre-processing). In the paper, we suggest adding a simple direct feature, age, into the NN based RUL estimation technique. The rationale for incorporating this feature is that the device lifetime is a sum of past time (age) plus RUL. Thus it has a strong correlation to RUL. In our experiments using accelerated aging tests, we show that the new age feature enhanced Recurrent Neural Network (RNN) model can significantly improve estimation accuracy and shorten training convergence time. It also outperforms a state-of-the-art RNN model using derived time-domain statistical features.

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Digital Twin Ancient Architecture: The Exploration of the Digital Protection of Ancient Architecture

Digital Twin Ancient Architecture: The Exploration of the Di...

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作者： Li, Shanglin Lin, Anping School of Computer Science and Artificial Intelligence Xiangnan University Hunan Chenzhou423000 China Hunan Engineering Research Center of Advanced Embedded Computing and Intelligent Medical Systems Hunan Chenzhou China School of Physics and Electronic Electrical Engineering Xiangnan University Hunan Chenzhou China

The digital protection of ancient architectures has achieved important achievements. However, technology development has encountered a bottleneck. The main problem is that the digitization of ancient buildings is limited to building static and isolated three-dimensional models, which cannot meet the increasing professional requirements of digital protection. To solve the above problems, the concept of digital twin ancient architecture (DTAA) is proposed, focusing on the high-dimensional data integration method of the DTAA, as well as the construction method and technical route. Finally, the development and application of digital twin ancient architecture are discussed. The proposed method can bring new ideas to the field of digital protection of ancient architectures. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： 3D modeling

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Enhanced Prognostics and Health Management in Automated Driving systems: Using Graph Neural Networks to Recognize Operational Contexts

Enhanced Prognostics and Health Management in Automated Driv...

引用

Prognostics and System Health Management Conference (PHM)

作者： Peng Su Yeqi Wang Conglei Xiang Erik Wendel Madhav Mishra DeJiu Chen Department of Engineering Design Mechatronics Division KTH Royal Institute of Technology Stockholm Sweden Embedded Systems Master Program of Electrical Engineering and Computer Science (EECS) School KTH Royal Institute of Technology Stockholm Sweden Digital Systems Division RISE Research Institutes of Sweden Gothenburg Sweden

ISBN: (数字)9798350360585

ISBN: (纸本)9798350360592

Prognostics and health management (PHM) is an engineering discipline that aims to maintain system behaviour and function and ensure mission success, safety and effectiveness. Addressing the challenges in prognostics and health management for modern intelligent systems, especially automated driving systems, is complex due to the contextual nature of faults. This complexity necessitates a thorough understanding of spatial, and temporal conditions, and relationships within operational scenarios and life-cycle stages. This paper introduces a framework designed to automatically recognize driving scenarios in automated driving systems using graph neural networks (GNNs). The framework extracts relational data from image frames, constructing graph-based models and transforming unstructured sensory data into structured data with diverse node types and relationships. A specific graph neural network processes the graph model to reveal and detect operational conditions and relationships. The proposed framework is evaluated using the KITTI dataset, demonstrating superior performance compared to conventional feed-forward networks such as MLP, particularly in handling relational data.

关键词： Graph neural networks Data models Safety Complexity theory Data mining Prognostics and health management Intelligent systems

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Brainwave Analysis of the Correlation Between Listening to the Rain/Water Sounds and Reducing Human-Perceived Temperature 18th

Brainwave Analysis of the Correlation Between Listening to t...

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18th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2022

作者： Tey, Fu Jie Wu, Tin-Yu Liu, Mei-Yin Chen, Yi-Kai Department of Electrical Engineering National Taiwan University of Science and Technology Taipei City Taiwan Department of Management Information Systems National Pingtung University of Science and Technology Neipu Taiwan Master Program of E-Learning for Multimedia and Network Communications National Ilan University Yilan City Taiwan

ISBN: (纸本)9789819901043

This study focuses on the brainwave analysis of the correlation between listening to the rain and water sounds and reducing human-perceived temperature. Brainwave changes are monitored when experimental subjects listen to rain and water sounds at various frequencies. The experiment result shows that listening to the sounds of rain and water in an environment of high temperature and high humidity can boost α waves to induce feelings of calm and relaxed mental state. In order to investigate subjects’ psychological and physiological changes induced by brainwave changes while listening to rain and water sounds for different time durations in a high temperature and humidity environment, this study uses the Fourier transform to obtain the spectra of natural rain/water sounds and analyzes the sound frequencies. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Fourier analysis

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Device-Free 3D Drone Localization in RIS-Assisted mmWave MIMO Networks

Device-Free 3D Drone Localization in RIS-Assisted mmWave MIM...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： He, Jiguang Vanwynsberghe, Charles Chen, Hui Huang, Chongwen Fakhreddine, Aymen Great Bay University School of Computing and Information Technology Dongguan China Technology Innovation Institute Abu Dhabi9639 United Arab Emirates Chalmers University of Technology Department of Electrical Engineering Gothenburg Sweden Zhejiang University College of Information Science and Electronic Engineering Hangzhou310027 China University of Klagenfurt Institute of Networked and Embedded Systems Klagenfurt Austria

ISBN: (纸本)9798350351255

In this paper, we investigate the potential of reconfigurable intelligent surfaces (RISs) in facilitating passive/device-free three-dimensional (3D) drone localization within existing cellular infrastructure operating at millimeter-wave (mmWave) frequencies and employing multiple antennas at the transceivers. The developed localization system operates in the bi-static mode without requiring direct communication between the drone and the base station. We analyze the theoretical performance limits via Fisher information analysis and Cramér Rao lower bounds (CRLBs). Furthermore, we develop a low-complexity yet effective drone localization algorithm based on coordinate gradient descent and examine the impact of factors such as radar cross section (RCS) of the drone and training overhead on system performance. It is demonstrated that integrating RIS yields significant benefits over its RIS-free counterpart, as evidenced by both theoretical analyses and numerical simulations. © 2024 IEEE.

关键词： Cramer-Rao bounds

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