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检索条件"机构=Software and Computer Engineering"

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A Quad-Active Bridge (QAB)-Based Solid-State Transformer for Fast Charging of Light/Medium and Heavy Electric Vehicles 25

A Quad-Active Bridge (QAB)-Based Solid-State Transformer for...

引用

25th IEEE International Conference on Industrial Technology, ICIT 2024

作者： De Seram, Ruvini Lulbadda, Kushan Tharuka Sidhu, Tarlochan Williamson, Sheldon S. Ontario Tech University Department Of Electrical Computer And Software Engineering Oshawa Canada

ISBN: (纸本)9798350340266

Integrating electric vehicle (EV) fast charging stations with the medium voltage (MV) grid using a solid-state transformer (SST) has attracted more interest from researchers due to the reduced size and the smart functionalities it offers for maintaining the stability and power quality of the grid. However, the modular structure of SST requires many power converters and high-frequency transformers in the isolated DC/DC converter stage which again increases the space of the charging station. This paper proposes a design of an SST-based EV charging station using a quadruple-active-bridge (QAB) as the isolated DC/DC converter and investigates the power density enhancement compared to the dual-active-bridge (DAB)-based system. The proposed charging station can charge different EVs with different battery voltages (800V, 400V, and 200V) and capacities. The performance is validated by simulating a 1MVA, 10kV EV charging station using MATLAB. The control architecture and a detailed analysis of the system are included in the paper. © 2024 IEEE.

关键词： Bridges

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A Global-Local Probsparse Self-Attention Transformer for LEO Satellite Orbit Prediction 23

A Global-Local Probsparse Self-Attention Transformer for LEO...

引用

23rd IEEE International Conference on Machine Learning and Applications, ICMLA 2024

作者： Huang, Guan Shu, Tao Auburn University Department of Computer Science and Software Engineering Auburn United States

ISBN: (纸本)9798350374889

In recent years, the proliferation of LEO (Low-Earth Orbit) satellites and the accumulation of space debris have made Near-Earth space more and more crowded, and hence significantly increased the risk of collisions in this space. As a result, precise orbit prediction becomes essential for LEO satellites to avoid collision, maintain the right constellation, and perform normal space operations. Although machine learning(ML)-based satellite orbit prediction methods have been extensively explored, most existing methods are trained on simulated/synthetic orbit data, which essentially assumes a stationary orbit process and cannot reflect the non-stationary dynamic orbit changes in real-world LEO satellite constellations that are caused by satellite flight status adjustment (e.g., for the purpose of collision avoidance). In this study, we propose a novel multi-range (global-local) self-attention transformer-based ML model, the GloLoSAT (Global-Local Probsparse Self-Attention Transformer), and train the model over real-world LEO satellite orbit data crawled from *** to give more precise orbit prediction in case of a series of orbit adjustments. Theoretical analysis demonstrates our Global-Local Probsparse Self-Attention mechanism can achieve O(Llog(L)) computational complexity with respect to the input sequence length. Extensive experiments conducted on real satellite orbit tracking datasets demonstrate the efficacy of GloLoSAT in achieving consistent performance improvements across various prediction scenarios compared to their counterparts. © 2024 IEEE.

关键词： Space debris

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Real-time CAN Data Acquisition and Visualization: Synerging Physical-to-Virtual (P2V) Twinning of Automotive Battery Management Systems 50

Real-time CAN Data Acquisition and Visualization: Synerging ...

引用

50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Sharma, Mohit Samanta, Akash Chetri, Chandan Williamson, Sheldon Department of Electrical Computer and Software Engineering Ontario Tech University Oshawa Canada

ISBN: (纸本)9781665464543

Controller area network (CAN) is widely used in automotive applications and has become the standard communication protocol to enable efficient communication primarily between electronic control units (ECUs) to reduce the complexity and cost of electrical wiring in automobiles through multiplexing. Towards developing the cloud-based electric vehicle battery data monitoring and digital-twinning of a battery management system (BMS), this paper introduced an online CAN data acquisition and visualization technique from an automotive grade BMS of NXP®®. Python-based CAN data processing tool is developed to process the raw data from the NXP® BMS and an open-source platform Grafana® is utilized together with the InfluxDB for visualization of the time-series data in real-time from a battery module containing 14 SAMSUNG 21700 lithium-ion battery cells. Each of those elements is implemented through the Docker container platform to become a standardized unit called a container. Besides presenting the detailed architecture of the data acquisition and visualization platform and the python-based data processing tool, this paper demonstrated the capability of the proposed architecture through examples of visualizing individual cell voltage, current, and temperature in real-time and their applications and utility in implementing cloud-based BMS. © 2024 IEEE.

关键词： Problem oriented languages

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Cooperation among Multiple Medical Institutions on Retinal Disease Identification Based on Federated Learning and Unlearning 4

Cooperation among Multiple Medical Institutions on Retinal D...

引用

4th Asia-Pacific Conference on Communications Technology and computer Science, ACCTCS 2024

作者： Deng, Peng Jia, Wenjun Yang, Nan Xiao, Liwen School of Computer Science and Software Engineering Southwest Petroleum University Nanchong China

ISBN: (纸本)9798350359985

Due to the aging of the world's population, the incidence of retinal diseases is on the rise. Machine learning is expected to have a crucial role in identifying retinal disease. Multiple medical institutions cooperate on retinal disease identification using machine learning, which can effectively break down data silos, but it is often accompanied by privacy concerns. Federated learning (FL) solves the privacy problem in the process of collaborative model training, where data of each medical institution does not leave the local to avoid data leakage. With a series of privacy laws coming into place, it is critical to give medical institutions participating in FL training the right to be forgotten. Federated unlearning (FU) allows a medical institution requesting to exit the cooperation to eliminate its contribution from the global model. We simulate the scenarios of cooperation among multiple medical institutions on retinal disease identification, using data augmentation to deal with an imbalanced dataset and backdoor attacks to evaluate the effects of FU. Experimental results show that FL and FU have potential for application in cooperation among multiple medical institutions on retinal disease identification. © 2024 IEEE.

关键词： Federated learning

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Analyzing the Behavior of Solid State Protection System for Dual Active Bridge in Solid State Transformers Under Short Circuit Faults

Analyzing the Behavior of Solid State Protection System for ...

引用

2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Lulbadda, Kushan Tharuka De Seram, Ruvini Sidhu, Tarlochan Williamson, Sheldon S. Ontario Tech University Department of Electrical Computer and Software Engineering Oshawa Canada

ISBN: (纸本)9798350376067

DC microgrids equipped with solid-state transformers (SST) offer a contemporary alternative to traditional low-frequency transformers (LFT) by increasing the system's power density. The SST consists of a front-end AC/DC converter and a Dual Active Bridge (DAB) as the two major components. However, the protection of the SSTs is still under minor development as they need a fast and reliable protection system. Solid-state circuit breakers (SSCBs) are becoming more popular in DC power systems due to the need for protection at ultrafast speed. The main objective of this article is to analyze the performance of the SSCB-based protection system for DAB during short circuit faults. PLECS simulation environment has been used to simulate and analyze the protection system's reaction to short circuit failures. A 1kW SSCB integrated DAB has been implemented in testing with actual hardware to validate the simulation results. The SSCB-based protection system achieves a remarkably high speed tripping time of 340μs. For a better understanding of the system, the behavior of the SSCB during a short circuit has been demonstrated at 50V by achieving a response time of 55.4μs. Moreover, the system is tested for different voltage levels to demonstrate the response time. This illustrates how the SSCB can safeguard SST quickly and effectively, improving safety and reliability. © 2024 IEEE.

关键词： Transformer protection

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Transient Stability Improvement of Grid-Tied Photovoltaics using Deep Reinforcement Learning 22

Transient Stability Improvement of Grid-Tied Photovoltaics u...

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22nd IEEE International Conference on Industrial Informatics, INDIN 2024

作者： Dewantoro, Gunawan Swain, Akshya Patel, Nitish Department of Electrical Computer and Software Engineering The University of Auckland Auckland New Zealand

ISBN: (纸本)9798331527471

The imperative for global transformation towards energy sustainability leads to the increasing incorporation of photovoltaic generation into the power systems networks. The increase of photovoltaic (PV) capacity in power system, however, would reduce the system inertial response and may negatively affect the transient stability of the generators. This paper, therefore, proposes a deep reinforcement learning (DRL)-based controller to ensure the transient stability of the power grid with PV penetration. The agent of the proposed Deep Q-Network optimally learns the control actions and adjusts the excitation voltage to maintain the voltage and synchronism in the event of faults. The performance of the controller under different levels of PV penetration and LVRT capabilities are also investigated. The results are compared with that of power systems stabiliser (PSS) to verify the effectiveness. The results show that Deep Q-Network is superior to PSS in maintaining transient stability. Furthermore, the DQN is able to quickly damp out the transient oscillations at various levels of PV penetration and tripping conditions. © 2024 IEEE.

关键词： Photovoltaics

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DeSAM2: Detection-Driven SAM2 for Hyperspectral Object Tracking 14

DeSAM2: Detection-Driven SAM2 for Hyperspectral Object Track...

引用

14th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing, WHISPERS 2024

作者： He, Wangquan Ren, Qi Zhang, Hongtao Mo, Ziqian Li, Nanying Xu, Meng Jia, Sen College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China

ISBN: (纸本)9798331513139

Hyperspectral object tracking (HOT) captures subtle object features, enabling precise identification and tracking in complex backgrounds. However, the high-dimensional nature of data and rapid object changes in dynamic scenes make accurate and robust tracking challenging. This paper proposes a detection-driven Segment Anything Model 2 (SAM2) for HOT (named DeSAM2), which enhances tracking accuracy and robustness through the collaboration of initial prompt tracking and a detection-based self-prompt auxiliary mechanism. Specifically, The method first employs a key band selection strategy to ensure that the spectral difference between object and background is maximized in complex backgrounds. Then, initial prompt tracking is used to acquire initial position of the object, and this process uses SAM2 as a base scheme to maintain high accuracy tracking. Furthermore, to address missed and false detections in initial tracking results within complex scenes, a detection-based self-prompt auxiliary mechanism is designed to further refine and correct tracking, thereby enhancing the adaptability and continuity of the model in dynamic environments. Experimental results on the datasets provided by the HOT Challenge 2024 indicate that the proposed method demonstrates superior performance compared to other advanced trackers. © 2024 IEEE.

关键词： Object detection

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Towards Enhancing Aviation Safety Through Advanced Incident Analysis Using Large Language Models 34

Towards Enhancing Aviation Safety Through Advanced Incident ...

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34th Annual International Conference on Collaborative Advances in software and Computing, CASCON 2024

作者： Siddeshwar, Vaishali Azim, Akramul Alwidian, Sanaa Makrehchi, Masoud University of Ontario Institute of Technology Department of Electrical Computer and Software Engineering Canada

ISBN: (纸本)9798331504830

Aerospace incident reports, crucial for identifying abnormal aircraft occurrences, are submitted to regulatory authorities like FAA or EASA. These reports, often in natural language, offer clarity and context. Existing literature proposes incident-analysis tools utilizing manual rules and NLP techniques like Part-of-Speech Tagging and dependency parsers to extract entities from logs. However, these approaches may miss nuances, leading to incomplete or inaccurate extractions and potential mis-interpretations. This study aims to automate initial extraction using Large Language Models, extracting Aircraft Number/Model, contributing and human factors, primary root cause, and incident summaries. Automating this phase can expedite investigations and improve expert efficiency during review processes. © 2024 IEEE.

关键词： Aircraft accidents

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A New Control Strategy for a Voltage and Current Fed Multiport DC-DC Converter

A New Control Strategy for a Voltage and Current Fed Multipo...

引用

2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Power, Rupert Madawala, Udaya Swain, Akshya The University of Auckland Department of Electrical Computer and Software Engineering Auckland New Zealand

ISBN: (纸本)9798350376067

Electrical power systems are increasingly adopting DC-based loads like Electric Vehicles, DC-based energy sources like solar photovoltaic panels, and battery energy storage systems (BESS). This increasingly necessitates the control of power flows between multiple DC busses of different voltage levels. Multi-port DC-DC converters such as the Modular Multiple Active Bridge (MMAB) converter can address this requirement with a reduced component count compared to alternative approaches, and good design flexibility. However, some applications such as BESS require both voltage and current-source converter outputs. This paper proposes a new control strategy with Zero Voltage Switching (ZVS) for a voltage and current fed MMAB converter, focused on BESS applications. Theory and simulations are presented, followed by experimental validation to demonstrate the effectiveness of the proposed control strategy. It is demonstrated that the converter is stable and can achieve ZVS and high efficiency under practical conditions, and that it can operate with small passive component values that allow cost-effective design choices. © 2024 IEEE.

关键词： Solar power generation

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A Comparative Analysis of Implementation of Privacy by Design Principles on different Blockchain platforms 4

A Comparative Analysis of Implementation of Privacy by Desig...

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4th International Conference on Communication Technologies, ComTech 2023

作者： Alam, Muhammad Haroon Basit, Abdul Arif, Fahim MCS Department of Computer Software Engineering Islamabad Pakistan

ISBN: (纸本)9798350337211

Blockchain is a pillar in 4IR (4th Industrial Revolution) of the digital world. Selection of the right blockchain platform, for anonymity, is a challenge that can be overcome while getting acknowledged how anonymous a platform is. Even though privacy is ensured by most of the platforms yet a source to demonstrate which platform is ensuring it at its best is quite an urge and can be fulfilled after formulating the comparative analysis on each one of those platforms under consideration. This paper will provide that required analysis by comparing privacy by design principles on different blockchain platforms. It will be quite helpful for developing decentralized applications where privacy will be provided by design principles. © 2023 IEEE.

关键词： Blockchain

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