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2023 IEEE Energy Conversion Congress and Exposition, ECCE 2023

作者： Gao, Zihan Li, Dingrui Chen, Ruirui Bai, Hua Tolbert, Leon Wang, Fred The University of Tennessee Min H. Kao Department of Electrical Engineering and Computer Science KnoxvilleTN United States Oak Ridge National Laboratory Oak RidgeTN United States

ISBN: (纸本)9798350316445

In this paper, a 50-kW 1-kV/6.25-kV medium voltage dual-active-bridge (DAB) transformer has been designed and tested. The shell-type transformer structure with stacked small cores is selected to integrate the leakage inductance and reduce the eddy current loss. Dry-type insulation with selective shielding is adopted and both winding-to-ground and winding turn-to-turn insulation are considered. The transformer geometry-based design procedure is discussed to achieve high efficiency and power density considering the effect of eddy current loss and insulation constraint. Tests up to the full voltage and power were performed and the DAB transformer achieved 99.66% full-load efficiency and 13.5 kW/L density for the transformer. © 2023 IEEE.

关键词： Dual-active-bridge (DAB) converters medium voltage transformers

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Estimating ECG Intervals from Lead-I Alone: External Validation of Supervised Models

arXiv

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arXiv 2024年

作者： Alam, Ridwan Stultz, Collin M. the Research Laboratory of Electronics the Department of Electrical Engineering Computer Science the Massachusetts Institute of Technology United States

The diagnosis, prognosis, and treatment of a number of cardiovascular disorders rely on ECG interval measurements, including the PR, QRS, and QT intervals. These quantities are measured from the 12-lead ECG, either manually or using automated algorithms, which are readily available in clinical settings. A number of wearable devices, however, can acquire the lead-I ECG in an outpatient setting, thereby raising the potential for out-of-hospital monitoring for disorders that involve clinically significant changes in ECG intervals. In this work, we therefore developed a series of deep learning models for estimating the PR, QRS, and QT intervals using lead-I ECG. From a corpus of 4.2 million ECGs from patients at the Massachusetts General Hospital, we train and validate each of the models. At internal holdout validation, we achieve mean absolute errors (MAE) of 6.3 ms for QRS durations and 11.9 ms for QT intervals, and a MAE of 9.2 ms for estimating PR intervals. Moreover, as a well-defined P-wave does not always exist in ECG tracings – for example, when there is atrial fibrillation – we trained a model that can identify when there is a P-wave, and consequently, a measurable PR interval. We validate our models on three large external healthcare datasets without any finetuning or retraining - 3.2 million ECG from the Brigham and Women’s Hospital, 668 thousand from MIMIC-IV, and 20 thousand from PTB-XL - and achieve similar performance. Also, our models significantly outperform two publicly available baseline algorithms. This work demonstrates that ECG intervals can be tracked from only lead-I ECG using deep learning, and highlights the potential for out-of-hospital applications. © 2024, CC BY-NC-ND.

关键词： Electrocardiography

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Texture Analysis of Breast US Images Using Morphological Transforms, Hausdorff Dimension and Bagging Ensemble Method 32

Texture Analysis of Breast US Images Using Morphological Tra...

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32nd Mediterranean Conference on Control and Automation, MED 2024

作者： Tabacaru, Gigi Moldovanu, Simona Barbu, Marian 'Dunarea de Jos' University of Galati Faculty of Automation Computers Electrical Engineering and Electronics Department of Automatic Control and Electrical Engineering Romania 'Dunarea de Jos' University of Galati Computer Science and Information Technology Faculty of Automation Computers Electrical Engineering and Electronics Romania Dunarea de Jos University of Galati The Modelling & Simulation Laboratory Galati800008 Romania

ISBN: (纸本)9798350395440

In this work, an attempt is made for the first time to use the measurement pattern generated by morphological transformation quantified by Hausdorff fractal dimension (HFD) and classified with ensemble learning based on bagging. The proposed work uses three morphological transformations for image preprocessing: hit-and-miss transform (HMT), white (WHT), and black top-hat (BHT). The pattern texture of US breast images is described by extracting the HFD from the regions of interest (ROI) after the ultrasound (US) images have been preprocessed. The main objective of this study was achieved by comparatively analyzing the classification performance of features using the Random Forest (RF), Extra Trees (ET) classifier, and bagging ensemble method based on XGBoot classifier. In presented study, the XGBoost classifier and BHT image processing method give an accuracy of 89.8% in a binary classification, benign versus malignant breast cancer. © 2024 IEEE.

关键词： Fractal dimension

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Analysis of L-Band Microwave Propagation from Smapvex19-22 Data Using Full-Wave Simulations of Maxwell's Equations

Analysis of L-Band Microwave Propagation from Smapvex19-22 D...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Jongwoo Jeong Leung Tsang Xiaolan Xu Andreas Colliander Simon Yueh Department of Electrical Engineering and Computer Science University of Michigan Jet Propulsion Laboratory California Institute of Technology

ISBN: (数字)9798350360325

ISBN: (纸本)9798350360332

We reported on the progress of fast hybrid method (FHM) for full- wave simulations of propagation of L-band microwaves in forested environment. For L band, previously we performed full wave simulations of realistic trees initially at 8 meters [1], followed by 13 meters [2]. The progress in this work is at comparisons of the electromagnetic model simulations with SMAPVEX19-22 data: 1) The height of the trees have been extended to 17 meters with the multiple scattering effects of 91 trees in the spatial domain with simulated transmissivity at 0.57 2) the spatial patterns of electric field distribution are simulated with electric field as high as 1.6 that of the incident wave corresponding to 2.56 times the Poynying of the incident waves, and the patterns exhibits gaps and shadows 3) the effects of clustering of trees with gaps show different results from that of uniformly positioned trees and 4) tree structures are varied with examples of trees with two trunks branching out from the main trunk, and the case of tapering trunk radius.

关键词： Meters Vegetation Forestry Electromagnetic modeling Mathematical models Data models Sensors

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Magnon gap tuning in lithium-doped MnTe

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Physical Review B 2024年第21期109卷 214434-214434页

作者： George Yumnam Duncan H. Moseley Joseph A. M. Paddison Christiana Z. Suggs Emma Zappala David S. Parker Garrett E. Granroth Gerald D. Morris Md Mobarak Hossain Polash Daryoosh Vashaee Michael A. McGuire Huaizhou Zhao Michael E. Manley Benjamin A. Frandsen Raphaël P. Hermann Materials Science and Technology Division Department of Physics and Astronomy Neutron Scattering Division Centre for Molecular and Materials Science Department of Electrical and Computer Engineering Beijing National Laboratory for Condensed Matter Physics

Manganese telluride (MnTe) is a prospective platform for ultrafast carrier dynamics, spin-based thermoelectrics, and magnon-drag transport due to its unique electronic and magnetic properties. We use inelastic neutron scattering to study both pure and lithium-doped MnTe, focusing on the influence of doping in opening a magnon gap. We use neutron powder diffraction to determine critical exponents for the phase transition in both pure and Li-doped MnTe and complement this information with muon spin rotation/relaxation. The opening of the magnon gap and spin reorientation in Li-doped MnTe is mainly due to increased magnetic anisotropy along the [001] axis, a feature not present in pure MnTe.

关键词： Antiferromagnetism Exchange interaction First-principles calculations Magnetic anisotropy Magnons Density functional theory Inelastic neutron scattering Linear spin wave theory Muon spin relaxation & rotation Neutron diffraction

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Active Grammatical Inference for Non-Markovian Planning 32

Active Grammatical Inference for Non-Markovian Planning

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32nd International Conference on Automated Planning and Scheduling, ICAPS 2022

作者： Topper, Noah Atia, George Trivedi, Ashutosh Velasquez, Alvaro Department of Computer Science University of Central Florida United States Department of Electrical and Computer Engineering University of Central Florida United States Department of Computer Science University of Colorado Boulder United States Information Directorate Air Force Research Laboratory United States

ISBN: (纸本)9781577358749

Planning in finite stochastic environments is canonically posed as a Markov decision process where the transition and reward structures are explicitly known. Reinforcement learning (RL) lifts the explicitness assumption by working with sampling models instead. Further, with the advent of reward machines, we can relax the Markovian assumption on the reward. Angluin's active grammatical inference algorithm L∗ has found novel application in explicating reward machines for non-Markovian RL. We propose maintaining the assumption of explicit transition dynamics, but with an implicit non-Markovian reward signal, which must be inferred from experiments. We call this setting non-Markovian planning, as opposed to non-Markovian RL. The proposed approach leverages L∗ to explicate an automaton structure for the underlying planning objective. We exploit the environment model to learn an automaton faster and integrate it with value iteration to accelerate the planning. We compare against recent non-Markovian RL solutions which leverage grammatical inference, and establish complexity results that illustrate the difference in runtime between grammatical inference in planning and RL settings. © 2022, Association for the Advancement of Artificial Intelligence.

关键词： Reinforcement learning

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An Efficient Hardware Design of CoAP Protocol for The Internet of Things

An Efficient Hardware Design of CoAP Protocol for The Intern...

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Proceedings of the IEEE Dallas Circuits and Systems Workshop (DCAS)

作者： Kasem Khalil Tamador Mohaidat Mahmoud Darwich Ashok Kumar Magdy Bayoumi Department of Electrical and Computer Engineering University of Mississippi Mississippi USA Department of Mathematics and Computer Science University of Mount Union Alliance OH USA The Center for Advanced Computer Studies University of Louisiana at Lafayette LA USA Department of Electrical and Computer Engineering University of Louisiana at Lafayette LA USA

ISBN: (数字)9798350349535

ISBN: (纸本)9798350349542

CoAP (Constrained Application Protocol) plays a crucial role in IoT by providing a lightweight and efficient communication protocol tailored for resource-constrained devices, facilitating seamless and reliable data exchange. This paper proposes a novel hardware accelerator for CoAP to address critical performance challenges in the context of the Internet of Things (IoT). The proposed method focuses on optimizing two key parameters, namely latency and execution time, through a carefully designed hardware setup. Implemented using VHDL on Xilinx Virtex-7 FPGA, the study demonstrates through extensive evaluations that the proposed method outperforms traditional software-based CoAP implementations. It achieves reduced execution times and lower latency across varying payloads and sampling rates, with a power consumption of 4.63 mW. These results signify a notable improvement in CoAP functionality, positioning the proposed hardware acceleration approach as a promising candidate for enhancing communication protocols in IoT environments.

关键词： Performance evaluation Energy consumption Protocols VHDL Power demand Internet of Things Reliability

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Efficient Deep Learning Approach for Breast Cancer Detection

Efficient Deep Learning Approach for Breast Cancer Detection

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Omni-layer Intelligent Systems (COINS), International Conference on

ISBN: (数字)9798350349597

ISBN: (纸本)9798350349603

Breast cancer detection saves lives by enabling early diagnosis, timely intervention, and treatment. Early detection and treatment reduce patients' mortality rates and reduce the overall burden of the disease on affected individuals and healthcare systems. A scientific research challenge for breast cancer detection is achieving as high accuracy as possible. Machine learning is providing greater hope for achieving high accuracy. This paper proposes a high-accuracy breast cancer detection method utilizing feature correlation and a reconfigurable neural network (RNN). The proposed method has been comprehensively tested using breast cancer detection datasets and is compared against Support Vector Machine (SVM) and K-Nearest Neighbors (KNN) methods. The results demonstrate the superior performance of the proposed method, achieving an accuracy of 97.2% and sensitivity of 97.8 %, surpassing known traditional methods. The proposed method is implemented using VHDL on Xilinx Virtex-7 FPGA and incurs a lower power consumption of 0.984 W with acceptable resource utilization.

关键词： Support vector machines Accuracy VHDL Power demand Nearest neighbor methods Feature extraction Breast cancer

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Statistical Analysis of Electromagnetic Coupling to Printed Circuit Boards

Statistical Analysis of Electromagnetic Coupling to Printed ...

引用

IEEE International Symposium on Electromagnetic Compatibility (EMC)

作者： Shengxuan Xia Victor Khilkevich Daryl Beetner Electrical and Computer Engineering Department EMC Laboratory Missouri University of Science and Technology Rolla MO USA

ISBN: (数字)9798350360394

ISBN: (纸本)9798350360400

Determining electromagnetic (EM) coupling to printed circuit boards (PCBs) is essential to finding potential EM susceptibilities early in the design process. For realistic PCB structures, analysis usually relies heavily on time-consuming full-wave simulations because of the complexity of the geometries and the lack of analytical solutions. In this paper, we adopt a segmentation approach based on far-field reciprocity which allows for rapid estimation of the voltage induced at trace terminations over frequency, and which is then used to estimate statistical characteristic of coupling across trace geometries. Frequency-domain results can then be used to estimate time-domain responses with appropriate transformations. Super-position is then used to separate the coupling contributed by different PCB structures, which provides better insight into the mechanisms responsible for susceptibility.

关键词： Couplings Geometry Performance evaluation Statistical analysis Frequency-domain analysis Printed circuits Voltage Frequency estimation Time-domain analysis Integrated circuit modeling

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Fluctuation and dissipation in quantum nonlinear optics

Fluctuation and dissipation in quantum nonlinear optics

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2024 Conference on Lasers and Electro-Optics, CLEO 2024

作者： Uddin, Shiekh Zia Rivera, Nicholas Seyler, Devin Salamin, Yannick Sloan, Jamison Xu, Shutao Sander, Michelle Y. Soljačić, Marin Department of Physics Massachusetts Institute of Technology CambridgeMA02139 United States Research Laboratory of Electronics Massachusetts Institute of Technology CambridgeMA02139 United States Department of Physics Harvard University CambridgeMA02138 United States Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States Department of Electrical and Computer Engineering BU Photonics Center Boston University BostonMA02215 United States

We present a new fluctuation-dissipation relation that shows how quantum noise transforms under engineered nonlinear dissipation found in many important nonlinear optical devices and validate the theory with experimen... 详细信息

ISBN: (纸本)9781957171395

关键词： Quantum noise

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