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IEEE International Symposium on Biomedical Imaging

作者： Ashwini Subramanian Laleh Najafizadeh Department of Electrical and Computer Engineering Integrated System and NeuroImaging Laboratory Rutgers University

ISBN: (数字)9798331520526

ISBN: (纸本)9798331520533

Detecting pain is critical for developing adaptive systems in clinical and assistive settings, allowing for timely interventions. This work presents an approach to detect the presence of physical pain during the performance of cognitive tasks from cortical signals. Cortical signals from the motor and prefrontal cortices are acquired using functional near in-frared spectroscopy (fNIRS) during two cognitive tasks, per-formed in the absence and presence of physical pain. Visibil-ity graphs (VGs) of these signals are constructed, and graph metrics of averaged clustering coefficient $(C)$ and edge den-sity $(D)$ are extracted. Statistical analysis reveals differences in these metrics for graphs corresponding to tasks performed under no-pain (NP) versus with-pain (WP) conditions, partic-ularly for signals obtained from the motor cortex. The graph metrics were then used as features to a support vector machine (SVM), achieving an accuracy exceeding 80% in distinguishing between tasks performed with and without pain. Our findings suggest that metrics from VGs of cortical sig-nals may serve as potential biomarkers for pain during cog-nitive tasks. This approach could be especially beneficial for non-verbal patients using assistive brain-computer interfaces.

关键词： Measurement Support vector machines Deep learning Pain Statistical analysis Image edge detection Motors Feature extraction Complexity theory Functional near-infrared spectroscopy

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Prescribing Decision Conservativeness in Two-Stage Power Markets: A Distributionally Robust End-to-End Approach 59

Prescribing Decision Conservativeness in Two-Stage Power Mar...

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59th Annual Conference on Information Sciences and systems, CISS 2025

作者： Liang, Zhirui Li, Qi Liu, Anqi Dvorkin, Yury Johns Hopkins University Department of Applied Mathematics and Statistics BaltimoreMD United States Johns Hopkins University Department of Computer Science BaltimoreMD United States Johns Hopkins University Department of Electrical and Computer Engineering BaltimoreMD United States Johns Hopkins University Department of Civil and System Engineering BaltimoreMD United States

ISBN: (纸本)9798331513269

This paper presents an end-to-end framework for calibrating wind power forecast models to minimize operational costs in two-stage power markets, where the first stage involves a distributionally robust optimal power flow (DR-OPF) model. Unlike traditional methods that adjust forecast parameters and uncertainty quantification (UQ) separately, this framework jointly optimizes both the forecast model parameters and the decision conservativeness, which determines the size of the ambiguity set in the DR-OPF model. The framework aligns UQ with actual uncertainty realizations by directly optimizing downstream operational costs, a process referred to as cost-oriented calibration. The calibration is achieved using a gradient descent approach. To enable efficient differentiation, the DR-OPF problem is reformulated into a convex form, and the Envelope Theorem is leveraged to simplify gradient derivation in the two-stage setting. Additionally, the framework supports distributed implementation, effectively reducing computational overhead and enhancing efficiency. By proactively calibrating forecast parameters and prescribing optimal decision conservativeness, the framework significantly enhances cost efficiency and reliability in power system operations. Numerical experiments on an IEEE 5-bus system demonstrate the effectiveness and efficiency of the proposed approach. © 2025 IEEE.

关键词： Wind forecasting

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Skill-Based Edge-Brain Smart Manufacturing: A Case of Grasp Pose Selection Skill 6

Skill-Based Edge-Brain Smart Manufacturing: A Case of Grasp ...

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6th International Conference on Industry 4.0 and Smart Manufacturing, ISM 2024

作者： Lee, Sukhan Jang, Byungwoo Hyeon, Seokjong Lee, Soojin Lee, Jaesun Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of Department of Artificial Intelligence Sungkyunkwan University Suwon16419 Korea Republic of Department of Computer Science and Engineering Sungkyunkwan University Suwon16419 Korea Republic of Department of AI System Engineering Sungkyunkwan University Suwon16419 Korea Republic of Department of Regional Industry Innovation Korea Institute of Industrial Technology Ulsan44413 Korea Republic of

The edge-brain framework (EBF) is a S/W framework that allows manufacturers to easily integrate AI-empowered robot work skills into a legacy production system in an edge computing environment with minimal time and effort. For EBF-based smart manufacturing, is a skill-based task-level robot programming environment that plays a key role. In this paper, we present the grasp pose selection skill as a case study to demonstrate the proposed skill-based edge-brain smart manufacturing. The proposed grasp-pose selection skill determines the optimal 6D grasp pose associated with the target object in a cluttered workspace by taking into consideration grasp stability, object manipulability, and collision-free path efficacy. To achieve a real-time operation of optimal grasp pose selection skill, deep learning networks are designed to compute, in particular, the manipulability and collision-free path efficacy indices. Experiments demonstrate the effectiveness of the proposed real-time grasp pose selection skill developed for EBF-based smart manufacturing. © 2024 The Authors. Published by Elsevier B.V.

关键词： Smart manufacturing

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Resource Allocation for Fairness Enhancement in Multi-Cell Vehicular VLC system With Optical IRS: A Cooperative Transmission Approach

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IEEE Internet of Things Journal 2025年第11期12卷 16931-16946页

作者： An, Nan Yang, Fang Liu, Chang Cheng, Ling Song, Jian Han, Zhu Tsinghua University Beijing National Research Center for Information Science and Technology Department of Electronic Engineering Beijing100084 China Center of National Railway Intelligent Transportation System Engineering and Technology Beijing100081 China China Academy of Railway Sciences Corporation Limited Signal and Communication Research Institute Beijing100081 China University of the Witwatersrand School of Electrical and Information Engineering Johannesburg2050 South Africa Tsinghua University Department of Electronic Engineering Beijing National Research Center for Information Science and Technology Beijing100084 China Tsinghua University Shenzhen International Graduate School Shenzhen518055 China University of Houston Department of Electrical and Computer Engineering HoustonTX77004 United States Kyung Hee University Department of Computer Science and Engineering Seoul446-701 Korea Republic of

In multi-cell downlink vehicular visible light communication (VLC) systems, vehicles at a cell edge experience lower achievable data rates compared with those at a cell center, primarily due to the weaker channel gain and inter-cell interference, leading to unfairness among vehicles. In this paper, a cooperative transmission approach is proposed for a vehicular VLC system with optical intelligent reflecting surface (OIRS) to enhance the max-min fairness of the system by leveraging the additional OIRS-reflected channels and the interference-mitigating capabilities of cooperative transmission. To this end, the system model is established, followed by the formulation of a resource allocation problem aiming at enhancing max-min fairness, in which the minimum achievable data rate among vehicles is optimized. Then, an effective resource algorithm is proposed, transforming the original problem into an equivalent form and subsequently decomposing it into three subproblems, focusing on OIRS assignment, subchannel allocation, and power adjustment, respectively. By employing a block coordinate descent algorithm, the three subproblems are solved iteratively until convergence. In addition, simulation results confirm the improvement in max-min fairness brought by OIRS and the proposed cooperative transmission approach. Moreover, compared with various baselines, the proposed resource allocation algorithm significantly enhances in the max-min fairness for the vehicular VLC system, crucial for this application. © 2014 IEEE.

关键词： Resource allocation

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Online Credibility Assessment of Equipment Digital Twin for Discrete Manufacturing

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IEEE Transactions on Automation Science and engineering 2025年 22卷 14763-14774页

作者： Lu, Han Zhang, Lin Deen, M. Jamal Wang, Kunyu Cheng, Hongbo Yang, Laurence T. Beihang University Hangzhou International Innovation Institute Zhejiang 311115 China Beihang University School of Automation Science and Electrical Engineering Beijing100191 China State Key Laboratory of Intelligent Manufacturing System Technology Beijing100854 China AI Atlas Inc Canada Zhengzhou University School of Computer and Artificial Intelligence School of Software Engineering Zhengzhou China St. Francis Xavier University Department of Computer Science Antigonish Canada

The equipment digital twins (EDTs) for discrete manufacturing should be calibrated quickly to avoid irreversible physical damage to the equipment caused by biased control commands. Therefore, an online credibility assessment method for EDTs is urgently needed. However, existing assessment approaches consume too much time, and thus could not reveal dynamic faults in time. In this paper, the dynamic relationship between online evolution and actual applications of EDTs is investigated. Then, two steps are proposed to accelerate the assessment process significantly. One involves pre-constructing a performance-deviation-agent (PDA), and the other involves dynamically fitting the application-time-window (ATW) probability distribution. The methodology is applicable to discrete manufacturing processes. The dynamic credibility of EDT evolution process can be updated after every iteration of the model evolution. Sorting manufacturing equipment was used as a case study to demonstrate the effectiveness of this method. The time consumption was reduced by 90% compared with traditional assessment methods in the case. © 2025 IEEE.

关键词： Fabrication

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Low Chirp Dual-Racetrack Modulator for PAM-4 Modulation with Low Driving Voltage

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Journal of Lightwave Technology 2025年第10期43卷 4840-4847页

作者： Yu, Fuhao Zeng, Zhaobang Tang, Kaifei Yang, Shichong Ji, Xiang Xin, Yu Gu, Tingyi Jiang, Wei Nanjing University Key Laboratory of Intelligent Optical Sensing and Manipulation Engineering Research Center for Precision Photonics Integration & System Applications Ministry of Education Nanjing210023 China Nanjing University National Laboratory of Solid-State Microstructures College of Engineering and Applied Sciences Institute of Optical Communication Engineering Nanjing210023 China Nanjing University of Information Science & Technology School of Physics and Optoelectronic Engineering Nanjing210044 China University of Delaware Department of Electrical and Computer Engineering NewarkDE19716 United States

Micro-ring modulators with a small footprint and energy consumption have been explored for densely integrated high throughput optical interconnects. However, their strong dispersive response results in frequency chirp and pulse broadening, which limits their signal transmission distance. Here we explore the low chirp operation of a dual-racetrack modulator symmetrically coupled to a bus waveguide. With opposite index changes in the two resonators, the coherent couplings of two resonators' optical fields with the bus waveguide and their interference can cancel out the output phase variation due to a single resonator. This allows the push-pull operation to achieve a lower chirp compared to the single-drive operation. The advantage of lower chirp operation is experimentally verified through open eye diagram with 100 Gbps PAM-4 transmitted over 2 km single-mode fiber (SMF), with a peak-to-peak driving voltage of 1.6 V. © 1983-2012 IEEE.

关键词： Single mode fibers

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Architecture of AC-DC Energy Nodes in Supergrids: A Technical Foundation for Future Renewable Integration

Architecture of AC-DC Energy Nodes in Supergrids: A Technica...

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Applied Research in electrical engineering (AREE), National and International Conference on

作者： Mohammad Hossein Mousavi Hassan Moradi Kumars Rouzbehi Department of Computer and Electrical Engineering Razi University Kermanshah Iran Department of System Engineering and Automatic Control University of Seville Seville Spain

ISBN: (数字)9798350377170

ISBN: (纸本)9798350377187

The AC-DC Energy Nodes (ADENs) concept offers a transformative approach to modernizing power grids, particularly in the context of supergrids. By centralizing power flows from diverse renewable energy sources, such as offshore wind farms, ADENs enable efficient long-distance power transmission through HVDC technology. This design enhances the balance of supply and demand across regions and countries, significantly improving grid stability and resilience. However, the implementation of ADENs presents substantial technical, regulatory, and cybersecurity challenges. This study delves into these challenges while also addressing the geopolitical complexities of transnational connections, underscoring the critical importance of policy alignment for successful deployment.

关键词： Renewable energy sources Supply and demand Protocols HVDC transmission Wind farms Power system stability Stability analysis computer security Protection Resilience

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Damage-Free Neutral Beam Etching for Gate Recess in E-Mode AlGaN/GaN HEMTs

IEEE Electron Device Letters

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IEEE Electron Device Letters 2025年第5期46卷 705-708页

作者： Chen, Yi-Ho Chu, Fu-Chuan Aslam, Muhammad Lee, Yao-Jen Li, Yiming Samukawa, Seiji National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Graduate Degree Program of College of Electrical and Computer Engineering Hsinchu300093 Taiwan National Chung-Shan Institute of Science and Technology Solid State Devices Section Electronic System Research Division Taoyuan325 Taiwan National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program Hsinchu300093 Taiwan Institute of Pioneer Semiconductor Innovation National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Institute of Pioneer Semiconductor Innovation Institute of Artificial Intelligence Innovation National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Institute of Biomedical Engineering Department of Electronics and Electrical Engineering Institute of Communications Engineering Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Institute of Communications Engineering Department of Electronics and Electrical Engineering Hsinchu300093 Taiwan

Recess gate etching is a critical technique for achieving enhancement-mode (E-mode) AlGaN/GaN high-electron mobility transistors (HEMTs) because the interface is susceptible to the etching damage. This study fabricates recess gates using the neutral beam etching (NBE) technique. By adjusting the aperture thickness in the NBE apparatus, we simulate both NB-mode and plasma-mode etching. The electrical characteristics of E-mode HEMTs fabricated using these two modes are analyzed and compared through DC, noise, and pulsed IV measurements. The results demonstrate that NB-recessed HEMTs exhibit superior performance. © 1980-2012 IEEE.

关键词： Aluminum gallium nitride

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Scar-Aware Late Mechanical Activation Detection Network for Optimal Cardiac Resynchronization Therapy Planning

Scar-Aware Late Mechanical Activation Detection Network for ...

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IEEE International Symposium on Biomedical Imaging

作者： Jiarui Xing Shuo Wang Amit R. Petal Kenneth C. Bilchick Frederick H. Epstein Miaomiao Zhang Department of Electrical and Computer Engineering University of Virginia USA School of Medicine University of Virginia Health System USA Department of Biomedical Engineering University of Virginia Health System USA Department of Computer Science University of Virginia USA

ISBN: (数字)9798331520526

ISBN: (纸本)9798331520533

Accurate identification of late mechanical activation (LMA) regions is crucial for optimal cardiac resynchronization therapy (CRT) lead implantation. However, existing approaches using cardiac magnetic resonance (CMR) imaging often over-look myocardial scar information, which may be mistakenly identified as delayed activation regions. To address this issue, we propose a scar-aware LMA detection network that simultaneously detects myocardial scar and prevents LMA localization in these scarred regions. More specifically, our model integrates a pre-trained scar segmentation network using late gadolinium enhancement (LGE) CMRs into a LMA detection network based on highly accurate strain derived from displacement encoding with stimulated echoes (DENSE) CMRs. We introduce a novel scar-aware loss function that utilizes the segmented scar information to discourage false-positive detections of late activated areas. Our model can be trained with or without paired LGE data. During inference, our model does not require the input of LGE images, leveraging learned patterns from strain data alone to mitigate false-positive LMA detection in potential scar regions. We evaluate our model on subjects with and without myocardial scar, demonstrating significantly improved LMA detection accuracy in both scenarios. Our work paves the way for improved CRT planning, potentially leading to better patient outcomes.

关键词： Image segmentation Accuracy Motion segmentation Medical treatment Magnetic resonance Myocardium Lead Data models Planning Strain

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Nafion edge passivation and nitrogen annealing treatment to improve solar cell reliability under light and elevated temperature induced degradation (LeTID) investigation

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Current Applied Physics 2025年 75卷 1-7页

作者： Jony, Jaljalalul Abedin Yousuf, Hasnain Khokhar, Muhammad Quddamah Zahid, Muhammad Aleem Madara, Polgampola Chamani Rahman, Rafi Ur Alamgeer Chu, Mengmeng Sanyal, Simpy Wang, Fucheng Kim, Youngkuk Kim, Kyesoo Dhungel, Suresh Kumar Park, Sangheon Yi, Junsin Interdisciplinary Program in Photovoltaic System Engineering Sungkyunkwan University Gyeonggi-do Suwon16419 Korea Republic of Department of Electrical and Computer Engineering Sungkyunkwan University Gyeonggi-do Suwon16419 Korea Republic of University Tamilnadu 600124 India Research Institute for Clean Energy College of Information and Communication Engineering Sungkyunkwan University Gyeonggi-do Suwon16419 Korea Republic of Faculty of Technology Nepal Academy of Science and Technology 3323 Khumaltar Lalitpur Nepal

This research examines the effectiveness of nitrogen annealing and Nafion treatment in mitigating Light and Elevated Temperature Induced Degradation (LeTID) in Passivated Emitter and Rear Contact (PERC) solar cells, employing a 30-kW photovoltaic (PV) system for evaluation. As a photosensitive device, solar cells are susceptible to damage from laser irradiation, leading to reduced photoelectric conversion efficiency, structural damage, and functional loss. To minimize this loss, nitrogen annealing and Nafion treatments were applied, followed by the analysis of LeTID effects on untreated, Nafion-treated, and combined nitrogen-annealed and Nafion-treated PERC cells. Untreated cells showed an 8 % fall in open-circuit voltage (Voc) and a 7 % fill factor (FF) loss. The combined treatment (Combination of Nitrogen & Nafion Treatment) improved stability, reducing losses to 6 % in Voc and 5 % in FF. The Nafion treatment yielded the best results, limiting deterioration to 4 % in Voc and 3 % in FF. PVsyst simulations, incorporating real-world data, confirmed enhanced stability and efficiency, aiding in optimizing PV system design and maintenance. © 2025 Korean Physical Society

关键词： Annealing

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