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IEEE Energy Conversion Congress and Exposition, ECCE

作者： Yidi Shen Daniel Zakzewski Arafat Hasnain Rakesh Resalayyan Alireza Khaligh Department of Electrical and Computer Engineering and The Institute for Systems Research Maryland Power Electronics Laboratory University of Maryland College Park MD USA

Active power decoupling (APD) circuit is of great importance in single-phase photovoltaic (PV) inverter systems for eliminating the fluctuating power drawn from the PV panel. The control of APD circuit is the key to the power decoupling performance and maximum power point tracking (MPPT) efficiency. This paper proposes a control approach for parallel boost type APD circuit with a single sensor, reducing the count of sensors compared to the conventional APD control approach. Operation of the APD circuit with control approach utilizing only the readings from the decoupling capacitor voltage sensor is analyzed in this work. Specifically, controller design for the APD circuit with reduced sensor applicable to a 40 V, 400 W microinverter is presented and experimentally verified with a GaN-based prototype.

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Dead-time Compensation Method for Bus-clamping Modulated Voltage Source Inverter

Dead-time Compensation Method for Bus-clamping Modulated Vol...

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IEEE Energy Conversion Congress and Exposition, ECCE

作者： Reza Asrar Ghaderloo Yidi Shen Chanaka Singhabahu Rakesh Resalayyan Alireza Khaligh Department of Electrical and Computer Engineering and The Institute for Systems Research Maryland Power Electronics Laboratory University of Maryland College Park MD USA

Bus-clamping Pulse Width Modulation (PWM) is an effective method to reduce the switching loss in a three-phase voltage source inverter (VSI). In bus-clamping PWM scheme, the phase legs are switched using high frequency PWM signals for two-third of the line cycle, while for the remaining duration of cycle, the pole voltage is clamped to either positive or negative rail of the DC bus. In PWM operation of a half bridge, a dead-time is applied between the gate signals of complementary switches to ensure safe and reliable operation. However, introduction of dead-time leads to poor power quality, increased Total Harmonic Distortion (THD) and variation in actual voltage compared to the intended pole voltage. Moreover, when the bus-clamping technique is used, the PWM has both high frequency switching region and clamped region in a line cycle, and consequently, the undesired effects of dead-time are further aggravated. Therefore, in order to enhance the quality of output voltage, this paper presents a dead-time compensation strategy for a VSI operating with bus-clamping PWM. The proposed method calculates the required compensation term to be added on the modulation signal considering wide range of operating conditions. Additionally, the compensation includes a new strategy for low current conditions near zero-crossing to avoid distortion. The proposed method is verified by simulation and experiments in a three-phase VSI with a switching frequency of 100 kHz and a fundamental frequency of 60Hz.

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DAMPER: A Dual-Stage Medical Report Generation Framework with Coarse-Grained MeSH Alignment and Fine-Grained Hypergraph Matching 39

DAMPER: A Dual-Stage Medical Report Generation Framework wit...

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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Huang, Xiaofei Chen, Wenting Liu, Jie Lu, Qisheng Luo, Xiaoling Shen, Linlin Computer Vision Institute College of Computer Science and Software Engineering Shenzhen University Shenzhen China Department of Electrical Engineering City University of Hong Kong Kowloon Hong Kong National Engineering Laboratory for Big Data System Computing Technology Shenzhen University China Guangdong Provincial Key Laboratory of Intelligent Information Processing China

ISBN: (纸本)157735897X

Medical report generation is crucial for clinical diagnosis and patient management, summarizing diagnoses and recommendations based on medical imaging. However, existing work often overlook the clinical pipeline involved in report writing, where physicians typically conduct an initial quick review followed by a detailed examination. Moreover, current alignment methods may lead to misaligned relationships. To address these issues, we propose DAMPER, a dual-stage framework for medical report generation that mimics the clinical pipeline of report writing in two stages. In the first stage, a MeSH-Guided Coarse-Grained Alignment (MCG) stage that aligns chest X-ray (CXR) image features with medical subject headings (MeSH) features to generate a rough keyphrase representation of the overall impression. In the second stage, a Hypergraph-Enhanced Fine-Grained Alignment (HFG) stage that constructs hypergraphs for image patches and report annotations, modeling high-order relationships within each modality and performing hypergraph matching to capture semantic correlations between image regions and textual phrases. Finally,the coarse-grained visual features, generated MeSH representations, and visual hypergraph features are fed into a report decoder to produce the final medical report. Extensive experiments on public datasets demonstrate the effectiveness of DAMPER in generating comprehensive and accurate medical reports, outperforming state-of-the-art methods across various evaluation metrics. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Diagnosis

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Distributed Software-Defined Network Architecture for Smart Grid Resilience to Denial-of-Service Attacks

Distributed Software-Defined Network Architecture for Smart ...

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IEEE General Meeting Power& Energy Society

作者： Dennis Agnew Sharon Boamah Reynold Mathieu Austin Cooper Janise McNair Arturo Bretas Department of Electrical and Computer Engineering University of Florida Gainesville FL Distributed Systems Group Pacific Northwest National Laboratory Richland WA

An important challenge for smart grid security is designing a secure and robust smart grid communications architecture to protect against cyber-threats, such as Denial-of-Service (DoS) attacks, that can adversely impact the operation of the power grid. Researchers have proposed using Software Defined Network frameworks to enhance cybersecurity of the smart grid, but there is a lack of benchmarking and comparative analyses among the many techniques. In this work, a distributed three-controller software-defined networking (D3-SDN) architecture, benchmarking, and comparative analysis with other techniques is presented. The selected distributed flat SDN architecture divides the network horizontally into multiple areas or clusters, where each cluster is handled by a single Open Network Operating System (ONOS) controller. A case study using the IEEE 118-bus system is provided to compare the performance of the presented ONOS-managed D3-SDN, against the POX controller. In addition, the proposed architecture outperforms a single SDN controller framework by a tenfold increase in throughput; a reduction in latency of > 20%; and an increase in throughput of approximately 11% during the DoS attack scenarios.

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Controller Verification of a Smart-Grid Compatible 200 kHz Single-stage Photovoltaic Microinverter

Controller Verification of a Smart-Grid Compatible 200 kHz S...

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Annual IEEE Conference on Applied Power Electronics Conference and Exposition (APEC)

作者： Daniel Zakzewski Rakesh Resalayyan Arafat Hasnain Chanaka Singhabahu Alireza Khaligh Department of Electrical and Computer Engineering Maryland Power Electronics Laboratory The Institute for Systems Research University of Maryland College Park United States

This paper presents control system design, implementation, and experimental validation of a single-stage 400 W, 200 kHz solar photovoltaic (PV) microinverter using hardware-in-the-loop (HIL) and hardware testing. The selected circuit topology is based on a Gallium Nitride (GaN) direct-matrix based dual active bridge (DAB) converter with a low voltage active power decoupler (APD) circuit. Control performance is verified, smart-grid compatibility is tested, and circuit operation is confirmed. Controller HIL (CHIL) is shown to aid in a complex power electronics system design by 1) enabling detailed control development prior to hardware implementation, 2) expanding the use of automated testing, and 3) increasing confidence in control performance prior to prototype testing. Altogether, these factors make HIL a valuable tool in complex power electronic designs.

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SELF-SUPERVISED GRAPH TRANSFORMER WITH CONTRASTIVE LEARNING FOR BRAIN CONNECTIVITY ANALYSIS TOWARDS IMPROVING AUTISM DETECTION

arXiv

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arXiv 2025年

作者： Leng, Yicheng Anwar, Syed Muhammad Rekik, Islem He, Sen Lee, Eung-Joo Department of Electrical and Computer Engineering University of Arizona Tucson United States Children’s National Hospital WashingtonDC United States Department of Computing Imperial College London London United Kingdom Department of Systems and Industrial Engineering University of Arizona Tucson United States

Functional Magnetic Resonance Imaging (fMRI) provides useful insights into the brain function both during task or rest. Representing fMRI data using correlation matrices is found to be a reliable method of analyzing the inherent connectivity of the brain in the resting and active states. Graph Neural Networks (GNNs) have been widely used for brain network analysis due to their inherent explainability capability. In this work, we introduce a novel framework using contrastive self-supervised learning graph transformers, incorporating a brain network transformer encoder with random graph alterations. The proposed network leverages both contrastive learning and graph alterations to effectively train the graph transformer for autism detection. Our approach, tested on Autism Brain Imaging Data Exchange (ABIDE) data, demonstrates superior autism detection, achieving an AUROC of 82.6 and an accuracy of 74%, surpassing current state-of-the-art methods. Copyright © 2025, The Authors. All rights reserved.

关键词： Self-supervised learning

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A Hybrid Scheme for Reconfigurable Intelligent Surfaces: How Many Elements Should be Estimated?

A Hybrid Scheme for Reconfigurable Intelligent Surfaces: How...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Andreas Nicolaides Constantinos Psomas Sheng Yang Ioannis Krikidis Department of Electrical and Computer Engineering University of Cyprus Nicosia Cyprus Laboratory of Signals and Systems CentraleSupélec Gif-sur-Yvette France

In this work, a low-complexity hybrid scheme is presented for a wireless network assisted by a reconfigurable intelligent surface (RIS), where channel estimation is required for only a subset of the elements. Specifically, in order to reduce the channel training overhead and boost the performance of the RIS-aided network, the RIS is partitioned in two sub-surfaces, which are sequentially activated to assist the communication. The elements of the first sub-surface align their phase shifts, based on the acquired channel state information (CSI) from a channel training period, whereas the elements of the second sub-surface randomly rotate the phase of the incident signals. The performance of the proposed scheme is investigated under the effect of imperfect CSI acquisition at the RIS. Analytical expressions for the outage probability are derived and useful insights on the optimal configuration of the RIS are provided. We show that, by optimizing the number of elements that need to be estimated, the proposed scheme provides significant performance gains and overcomes the limitations caused by the imperfect CSI acquisition.

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Design, Development and Deployment of an Underwater Cellular Network

Design, Development and Deployment of an Underwater Cellular...

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OCEANS

作者： Simon Etter Manu Ignatius Chinmay Pendharkar Esther Tan Mandar Chitre Jackie Ng Chun Long Lim Teck Jay Poh Jin Jie Subnero Pte. Ltd. Acoustic Research Laboratory and Department of Electrical and Computer Engineering National University of Singapore ST Engineering Unmanned & Integrated Systems Pte. Ltd.

ISBN: (数字)9798331540081

ISBN: (纸本)9798331540098

In today's rapidly evolving technological landscape, the need for efficient and reliable remote monitoring of under-water assets has never been more critical. A subsea cellular network solution ensures seamless connectivity and real-time data access to underwater assets such as marine robots and subsea IoT sensors, empowering organizations to optimize their operations and enhance asset management. With this need in mind, we present an underwater cellular network system that facilitates seamless communication with an arbitrary number of underwater assets and at the same time provides zero-overhead localization of the same. The presented system was tested out at sea in January 2024, and this paper describes in detail both the theoretical design of the system and the practical experience gained during these trials.

关键词： Cellular networks Location awareness Base stations Oceans Organizations Real-time systems Sensors Reliability Remote monitoring Marine robots

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Visual Multi-Object Tracking with Re-Identification and Occlusion Handling using Labeled Random Finite Sets

arXiv

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arXiv 2024年

作者： Van Ma, Linh Nguyen, Tran Thien Dat Shim, Changbeom Kim, Du Yong Ha, Namkoo Jeon, Moongu The School of Electrical Engineering and Computer Science GIST Gwangju Korea Republic of The School of Electrical Engineering Computing and Mathematical Sciences Curtin University Australia School of Engineering RMIT University Australia The Department of EO/IR Systems Research and Development LIG Nex1 Korea Republic of

This paper proposes an online visual multi-object tracking (MOT) algorithm that resolves object appearance-reappearance and occlusion. Our solution is based on the labeled random finite set (LRFS) filtering approach, which in principle, addresses disappearance, appearance, reappearance, and occlusion via a single Bayesian recursion. However, in practice, existing numerical approximations cause reappearing objects to be initialized as new tracks, especially after long periods of being undetected. In occlusion handling, the filter’s efficacy is dictated by trade-offs between the sophistication of the occlusion model and computational demand. Our contribution is a novel modeling method that exploits object features to address reappearing objects whilst maintaining a linear complexity in the number of detections. Moreover, to improve the filter’s occlusion handling, we propose a fuzzy detection model that takes into consideration the overlapping areas between tracks and their sizes. We also develop a fast version of the filter to further reduce the computational time. The source code is publicly available at https://***/linh-gist/VisualRFS. © 2024, CC BY.

关键词： Object detection

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VersaSens: An Extendable Multimodal Platform for Next-Generation Edge-AI Wearables

IEEE Transactions on Circuits and Systems for Artificial Int...

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IEEE Transactions on Circuits and systems for Artificial Intelligence 2024年第1期1卷 83-96页

作者： Taraneh Aminosharieh Najafi José Angel Miranda Calero Jérôme Thevenot Benjamin Duc Stefano Albini Alireza Amirshahi Hossein Taji María José Belda Beneyto Antonio Affanni David Atienza Embedded Systems Laboratory (ESL) Institute of Electrical and Micro Engineering École Polytechnique Fédérale de Lausanne (EPFL) Lausanne Switzerland Polytechnic Department of Engineering and Architecture Udine Italy Computer Architecture and Automation Department Universidad Complutense de Madrid Madrid Spain

The transition of healthcare towards digitalization is closely related to the advancement of health-related technologies, including wearable sensors and edge computing. In this paper, we present VersaSens, a versatile and customizable platform concept and its real implementation as a tool to boost research in wearable sensors. The platform embodies the core attributes of the VersaSens concept: versatility, flexibility, and extendability across multiple aspects of hardware, software, and processing components. It features a modular design, consisting of sensor, processor, and co-processor modules, allowing for various configurations. To evaluate the efficiency of the platform, we tested three use cases: cough monitoring, heartbeat classification and epileptic seizure detection. In all cases, the results indicate that the platform effectively executes the applications, achieving low energy consumption. In particular, our findings indicates that the integration of a domain-specific edge-AI co-processor [i.e., HEEP ocrates (Machetti et al., 2024)] equipped with several hardware accelerators further improved the overall execution time and energy consumption of the system. These results demonstrate the potential of VersaSens to effectively support a diverse range of edge-AI applications and configurations, thereby providing a robust foundation for the research and development of novel smart wearable sensor systems.

关键词： Sensors Wearable devices Artificial intelligence Wearable sensors Medical services Intelligent sensors Monitoring

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