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Annual Conference of Industrial Electronics Society

作者： Baza Somda Akshay Kumar Jain Haris Bin Ashraf Chen-Ching Liu Richard Zhang Alok Kumar Bharati Francis Tuffner Kevin Schneider Dan Ton Bradley Department of Electrical and Computer Engineering Virginia Tech Blacksburg Virginia Pacific Northwest National Laboratory Energy and Environment Directorate Richland Washington U.S. Department of Energy (DOE) Office of Electricity (OE) Microgrid R&D Program Washington DC

ISBN: (数字)9781665464543

ISBN: (纸本)9781665464550

With the adoption of ambitious climate action goals, the penetration level of distributed energy resources (DERs) is rapidly increasing. Microgrids are an efficient way to integrate these DERs, facilitating their operation and control. Additionally, microgrids enhance the overall resilience of the distribution system by serving critical loads both within and outside their boundaries. However, the need for substantial customized engineering leads to a high cost of development, installation and maintenance of microgrids. To address this challenge, Microgrid Building Blocks (MBB) are proposed to reduce the deployment cost of microgrids through modular, standardized design and implementation. This work presents a testbed demonstrating the integrated power conversion, control, and communication functionalities of an MBB. The testbed is formed by a real-time electromagnetic transient (EMT) simulation combined with a hardware and software prototype of MBB. The use cases supported by the MBB testbed are enumerated. The islanded operation, voltage regulation, and optimal dispatch capabilities of an MBB-based microgrid controller are validated through a case study.

关键词： Costs Refining Prototypes Microgrids Software Real-time systems Power conversion Voltage control Testing Resilience

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Cylindrical-Lens-Embedded Photonic Crystal Based on Self-Collimation 5

Cylindrical-Lens-Embedded Photonic Crystal Based on Self-Col...

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5th IEEE Research and Applications of Photonics in Defense Conference, RAPID 2022

作者： Xia, Chun Gutierrez, Jesus J. Kuebler, Stephen M. Rumpf, Raymond C. Touma, Jimmy University of Central Florida The College of Optics and Photonics Creol OrlandoFL32816 United States University of Texas at El Paso Em Lab Department of Electrical and Computer Engineering El PasoTX79968 United States Materials Science and Engineering University of Central Florida Creol The College of Optics and Photonics Chemistry Department OrlandoFL32816 United States Computational Science Program University of Texas at El Paso Em Lab Department of Electrical and Computer Engineering El PasoTX79968 United States Eglin Afb AFRL/Munitions Directorate Integrated Sensing and Processing Branch FL32542 United States

Independent optical power and phase control is experimentally demonstrated in a self-collimating PC based on rod-into-wall unit cell and fabricated in a low-refractive-index medium by multiphoton lithography. © 2... 详细信息

ISBN: (数字)9781665402231

ISBN: (纸本)9781665402231

关键词： Refractive index

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Multi-Level Branched Regularization for Federated Learning

arXiv

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arXiv 2022年

作者： Kim, Jinkyu Kim, Geeho Han, Bohyung Computer Vision Laboratory Department of Electrical and Computer Engineering & ASRI Seoul National University Korea Republic of Interdisciplinary Program of Artificial Intelligence Seoul National University Korea Republic of

A critical challenge of federated learning is data heterogeneity and imbalance across clients, which leads to inconsistency between local networks and unstable convergence of global models. To alleviate the limitations, we propose a novel architectural regularization technique that constructs multiple auxiliary branches in each local model by grafting local and global subnetworks at several different levels and that learns the representations of the main pathway in the local model congruent to the auxiliary hybrid pathways via online knowledge distillation. The proposed technique is effective to robustify the global model even in the non-iid setting and is applicable to various federated learning frameworks conveniently without incurring extra communication costs. We perform comprehensive empirical studies and demonstrate remarkable performance gains in terms of accuracy and efficiency compared to existing methods. The source code is available in our project page1 Copyright © 2022, The Authors. All rights reserved.

关键词： Distillation

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Minimizing File Transfer Time in Opportunistic Spectrum Access Model

arXiv

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arXiv 2022年

作者： Hu, Jie Doshi, Vishwaraj Eun, Do Young Department of Electrical and Computer Engineering United States Operations Research Graduate Program North Carolina State University RaleighNC United States

We study the file transfer problem in opportunistic spectrum access (OSA) model, which has been widely studied in throughput-oriented applications for max-throughput strategies and in delay-related works that commonly assume identical channel rates and fixed file sizes. Our work explicitly considers minimizing the file transfer time for a given file in a set of heterogeneous-rate Bernoulli channels, showing that max-throughput policy doesn’t minimize file transfer time in general. We formulate a mathematical framework for static extend to dynamic policies by mapping our file transfer problem to a stochastic shortest path problem. We analyze the performance of our proposed static and dynamic optimal policies over the max-throughput policy. We propose a mixed-integer programming formulation as an efficient alternative way to obtain the dynamic optimal policy and show a huge reduction in computation time. Then, we propose a heuristic policy that takes into account the performance-complexity tradeoff and consider the online implementation with unknown channel parameters. Furthermore, we present numerical simulations to support our analytical results and discuss the effect of switching delay on different policies. Finally, we extend the file transfer problem to Markovian channels and demonstrate the impact of the correlation of each channel. Copyright © 2022, The Authors. All rights reserved.

关键词： Stochastic systems

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Porous silicon on paper sensors: Factors affecting biosensing performance 17

Porous silicon on paper sensors: Factors affecting biosensin...

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Frontiers in Biological Detection: From Nanosensors to Systems XVII 2025

作者： An, Huijin Laibinis, Paul E. Locke, Andrea K. Weiss, Sharon M. Interdisciplinary Material Science Program Vanderbilt University NashvilleTN37235 United States Department of Electrical and Computer Engineering Vanderbilt University NashvilleTN37235 United States Department of Chemical and Biomolecular Engineering Vanderbilt University NashvilleTN37235 United States Department of Chemistry Vanderbilt University NashvilleTN37235 United States Department of Biomedical Engineering Vanderbilt University NashvilleTN37235 United States

ISBN: (纸本)9781510684249

A paper-based biosensor integrating a functionalized porous silicon (PSi) membrane as the active sensing element for quantifiable protein detection has been developed. For similar short-time exposures to an analyte, improved molecular transport in PSi membranes when on paper leads to larger signal changes compared to traditional PSi films that remain on a silicon substrate. In this work, we discuss controlling the incubation time of the analyte and the overall testing time of the sensor by incorporating different combinations of wicking and absorbent paper beneath the PSi membrane. With this control, the PSi-on-paper sensor platform has the potential to serve as an effective low-cost rapid diagnostic test with highly sensitive, quantitative readout for a wide range of analytes. © 2025 SPIE.

关键词： Porous silicon

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A model of indoor thermal condition based on traditional acehnese houses using artificial neural network

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Heliyon 2024年第23期10卷 e40644页

作者： Muslimsyah Munir, Abdul Away, Yuwaldi Abdullah Arif, Teuku Yuliar Novandri, Andri Doctoral Program School of Engineering Universitas Syiah Kuala Banda Aceh 23111 Indonesia Department of Architecture and Planning Universitas Syiah Kuala Banda Aceh 23111 Indonesia Department of Electrical and Computer Engineering Universitas Syiah Kuala Banda Aceh 23111 Indonesia Department of Civil Engineering Universitas Syiah Kuala Banda Aceh 23111 Indonesia Department of Computer Engineering Universitas Serambi Mekkah Banda Aceh 23249 Indonesia

This paper examines the thermal condition aspects of traditional Acehnese houses (Rumoh Aceh) in Indonesia. This study highlights the importance of considering traditional architecture in achieving comfortable living conditions. Through the integration of cultural values, architectural design, and environmental factors, this research evaluates the prediction of thermal conditions within Rumoh Aceh based on building orientation and location, serving as guidelines for architects in designing buildings in the Aceh region. The study employs an ANN (Artificial Neural Network) algorithm to predict thermal condition parameters including indoor: temperature, humidity, and wind speed. The sample data used to train the ANN model consists of thermal data from five different rooms and meteorological data. The ANN model is employed to predict the thermal conditions in the Rumoh Aceh building based on its orientation and location. In this study, two models were developed, namely MODEL_01, for predicting indoor temperature and humidity, and MODEL_02, for predicting indoor wind speed. In MODEL_01, the error tolerance level obtained is ±1.05, and in MODEL_02, it is ±0.03. The prediction results based on the building orientation show the lowest average indoor temperature value of 29.19 °C, occurring at an angle of 292.19°. Furthermore, the lowest average indoor humidity value is 74.57 %, which also occurs at an angle of 292.19°. However, for indoor wind speed, the angle of 260° records the lowest average value of 0.125 m/s, while the highest average value is observed at 292.19°, at 0.132 m/s. The prediction results based on the building's location show the lowest average temperature value, which is 29.44 °C in the Aceh Besar region. Furthermore, the lowest average humidity value is 75.11 % in the North Aceh region. Meanwhile, the highest average wind speed value is 0.174 m/s in the Sabang region. This study reveals that at the orientation angle of 292.19° (the qibla direction), it pr

关键词： ANN Orientation Region Rumoh aceh Thermal condition

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Modeling functional cell types in spike train data

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PLoS Computational Biology 2023年第10 October期19卷 e1011509-e1011509页

作者： Zdeblick, Daniel N. Shea-Brown, Eric T. Witten, Daniela M. Buice, Michael A. Department of Electrical and Computer Engineering University of Washington SeattleWA United States Department of Applied Math University of Washington SeattleWA United States MindScope Program Allen Institute SeattleWA United States Department of Statistics and Biostatistics University of Washington SeattleWA United States

A major goal of computational neuroscience is to build accurate models of the activity of neurons that can be used to interpret their function in circuits. Here, we explore using functional cell types to refine single-cell models by grouping them into functionally relevant classes. Formally, we define a hierarchical generative model for cell types, single-cell parameters, and neural responses, and then derive an expectation-maximization algorithm with variational inference that maximizes the likelihood of the neural recordings. We apply this "simultaneous" method to estimate cell types and fit single-cell models from simulated data, and find that it accurately recovers the ground truth parameters. We then apply our approach to in vitro neural recordings from neurons in mouse primary visual cortex, and find that it yields improved prediction of single-cell activity. We demonstrate that the discovered cell-type clusters are well separated and generalizable, and thus amenable to interpretation. We then compare discovered cluster memberships with locational, morphological, and transcriptomic data. Our findings reveal the potential to improve models of neural responses by explicitly allowing for shared functional properties across neurons. Copyright: © 2023 Zdeblick et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

关键词： Neurons

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Effective Loss Function for Unbalanced Breast Thermal Image Segmentation

Effective Loss Function for Unbalanced Breast Thermal Image ...

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2021 International Conference on computer System, Information Technology, and electrical engineering, COSITE 2021

作者： Roslidar, Roslidar Saddami, Khairun Irhamsyah, Muhammad Arnia, Fitri Syukri, Maimun Munadi, Khairul Universitas Syiah Kuala Doctoral Program Post Graduate Program School of Engineering Banda Aceh23111 Indonesia Universitas Syiah Kuala Department of Electrical and Computer Engineering Banda Aceh23111 Indonesia Universitas Syiah Kuala Medical Faculty Banda Aceh23111 Indonesia

ISBN: (纸本)9781665425094

The convolutional neural network's ability to learn images has reigned in computer vision tasks of object detection, classification, and segmentation. In segmentation, the CNN architectures of U-Net and SegNet have shown a good performance;thus, we implemented these networks to take the region of interest (ROI) of the breast thermal images from database for mastology research (DMR). We fine-tuned the networks to find the optimal hyperparameter that can result in the best learning performance. The networks were trained using the stochastic gradient descent optimization algorithm, and weights were updated using the error backpropagation of the algorithm. To minimize the error, the loss function is applied to evaluate a candidate solution of the weights. Thus, we conducted a preliminary study on finding the optimal loss function for breast thermal image segmentation. We applied loss functions of cross-entropy, dice, and focal and figured out the one that provides the highest segmentation accuracy. Then, to evaluate the segmentation result, we calculated the pixel accuracy rate and the dice coefficient to obtain the overlapping index measuring the overlay area between ground truth and predicted output. The result shows that the SegNet model with cross-entropy loss function can take the ROI of breast thermal images at the highest pixel accuracy and optimum dice coefficient of 0.8845 and 0.7928, respectively. © 2021 IEEE.

关键词： Image segmentation

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Surface engineering Towards Boosted Dielectric Properties for High-Temperature Polymers Under electrical Extremes

Surface Engineering Towards Boosted Dielectric Properties fo...

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Conference on electrical Insulation and Dielectric Phenomena, (CEIDP)

作者： Jierui Zhou Marina Dabaghian Anna Marie LaChance Jing Hao Wesley Zhong Luyi Sun Yang Cao Department of Electrical and Computer Engineering University of Connecticut Storrs CT USA Electrical Insulation Research Center Institute of Materials Science University of Connecticut Storrs CT USA Department of Chemical and Biomolecular Engineering University of Connecticut Storrs CT USA Polymer Program Institute of Materials Science University of Connecticut Storrs CT USA

Polymer-thin films are critical dielectric materials for capacitive energy storage in power and electronic systems. The rapid development of wide bandgap semiconductors urgently calls for polymers that can attain high energy density and high charge-discharge efficiency at elevated temperatures. However, high-temperature polymers usually suffer from compromised dielectric breakdown strength and soaring conduction loss due to the intrinsic constraint between their bandgaps and thermal stability. In this work, we propose a facile and high throughput interface engineering technique utilizing nanocoatings formed by montmorillonite (MMT) nanoclays, which can serve as an out-of-the-box solution to bypass this constraint. The highly ordered MMT-based nanocoatings with layered structure can significantly block the excessive charge injection at high electric fields and dissipate the charge carriers along the in-plane direction. The MMT-coated PI films exhibit improved breakdown strength, suppressed conduction loss, and boosted charging-discharging efficiency. This work holds the promise of improving the dielectric properties of polymers through surface engineering, enabling their application at concurrent electrical and thermal extremes.

关键词：

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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...

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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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