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China Power Supply Society Electromagnetic Compatibility Conference (CPEMC)

作者： Huamin Jie Zhenyu Zhao Yongqi Chang Changdong Wang Shiqi Jiang Richard Xian-Ke Gao Kye Yak See School of Electrical and Electronic Engineering Nanyang Technological University Singapore Singapore Department of Electrical and Computer Engineering National Univeristy of Singapore Singapore Singapore Department of Control Science and Engineering Harbin Institute of Technology Harbin China School of Electronics and Information Engineering Harbin Institute of Technology Harbin China School of Electrical Engineering and Automation Harbin Institute of Technology Harbin China A*STAR Institute of High Performance Computing Singapore Singapore

ISBN: (数字)9798331509552

ISBN: (纸本)9798331509569

The complex permeability of magnetic cores acts as a vital factor in electromagnetic interference (EMI) filtering choke design and optimization. Many efforts have been reported for toroid cores, but fewer target those with other shapes, such as EE, EI, UU, and UI cores. Owing to their commonly used in planar EMI filters, determining the complex permeability of them is of significance. Targeting EE cores, this paper presents a flexible printed circuit board (PCB)-based fixture adapter tailored designed for performing the measurement, while the corresponding core permeability can be calculated through magnetic flux path length analysis. The experiments validate the effectiveness and accuracy of the proposed methods, spanning a wide frequency range up to 120 MHz.

关键词： Magnetic flux Accuracy Flexible printed circuits Magnetic cores Fixtures Electromagnetic interference Permeability measurement Length measurement Permeability Inductors

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A Framework for Jointly Training GAN with Person Re-Identification Model 25th

A Framework for Jointly Training GAN with Person Re-Identifi...

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25th International Conference on Pattern Recognition Workshops, ICPR 2020

作者： Zhao, Zhongwei Song, Ran Zhang, Qian Duan, Peng Zhang, Youmei School of Control Science and Engineering Shandong University Jinan China School of Computer Science Liaocheng University Liaocheng China School of Mathematics and Statistics Qilu University of Technology Jinan China

ISBN: (纸本)9783030687984

To cope with the problem caused by inadequate training data, many person re-identification (re-id) methods exploited generative adversarial networks (GAN) for data augmentation, where the training of GAN is typically independent of that of the re-id model. The coupling relation between them which probably brings in a performance gain of re-id is thus ignored. In this work, we propose a general framework to jointly train GAN and the re-id model. It can simultaneously achieve the optima of both the generator and the re-id model, where the training is guided by each other through a discriminator. The re-id model is boosted for two reasons: 1) The adversarial training that encourages it to fool the discriminator;2) The generated samples that augment the training data. Extensive results on benchmark datasets show that for the re-id model trained with the identification loss as well as the triplet loss, the proposed joint training framework outperforms existing methods with separated training and achieves state-of-the-art re-id performance. © 2021, Springer Nature Switzerland AG.

关键词： Generative adversarial networks

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STS-CCL: Spatial-Temporal Synchronous Contextual Contrastive Learning for Urban Traffic Forecasting

arXiv

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arXiv 2023年

作者： Li, Lincan Yang, Kaixiang Luo, Fengji Bi, Jichao School of Control Science and Engineering Zhejiang University Hangzhou China School of Computer Science and Engineering South China University of Technology Guangzhou China The University of Sydney Sydney Australia Chongqing University Zhejiang Institute of Industry and Information Technology Hangzhou China

Efficiently capturing the complex spatiotemporal representations from large-scale unlabeled traffic data remains to be a challenging task. In considering of the dilemma, this work employs the advanced contrastive learning and proposes a novel Spatial-Temporal Synchronous Contextual Contrastive Learning (STS-CCL) model. First, we elaborate the basic and strong augmentation methods for spatiotemporal graph data, which not only perturb the data in terms of graph structure and temporal characteristics, but also employ a learning-based dynamic graph view generator for adaptive augmentation. Second, we introduce a Spatial-Temporal Synchronous Contrastive Module (STS-CM) to simultaneously capture the decent spatial-temporal dependencies and realize graph-level contrasting. To further discriminate node individuals in negative filtering, a Semantic Contextual Contrastive method is designed based on semantic features and spatial heterogeneity, achieving node-level contrastive learning along with negative filtering. Finally, we present a hard mutual-view contrastive training scheme and extend the classic contrastive loss to an integrated objective function, yielding better performance. Extensive experiments and evaluations demonstrate that building a predictor upon STS-CCL contrastive learning model gains superior performance than existing traffic forecasting benchmarks. The proposed STS-CCL is highly suitable for large datasets with only a few labeled data and other spatiotemporal tasks with data scarcity issue. Copyright © 2023, The Authors. All rights reserved.

关键词： Large dataset

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Differential Co-expression Network Analysis to Investigate Sexual Dimorphism in Colon Cancer

Differential Co-expression Network Analysis to Investigate S...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Caterina Alfano Lorenzo Farina Manuela Petti PhD program in Network Oncology and Precision Medicine Sapienza University of Rome Rome Italy Dept. of Computer Control and Management Engineering PhD program in Network Oncology and Precision Medicine Sapienza University of Rome Rome Italy Dept. of Computer Control and Management Engineering Sapienza University of Rome Rome Italy

ISBN: (数字)9781665468190

ISBN: (纸本)9781665468206

Colorectal cancer is the third most diagnosed cancer in the world, but it has a higher mortality rate in men compared to women. However, we are not close to understanding how and why sex influences the outcome of the disease. This study focuses on mRNA expression profiles of colon cancer patients to look for molecular differences in the development of colon cancer between men and women. We used paired expression data (i.e., data collected in pairs of normal and cancer cells, by taking samples from the same individual), we identified differentially expressed genes (cancer vs normal) and computed co-expression and differential co-expression gene networks (men vs women). Doing so, we inferred the main changes and alterations happening in cancer tissues, and specifically how these changes were different among men and women. We found that the co-expression networks of women and men affected by colon cancer are quite different and we reported the genes that show the most differences in this comparison, checking if they could also be associated to sexual dimorphism or sexual hormones. Among these genes we found a interesting presence of genes associated to the Wnt signaling pathway which has been found to be regulated by estrogen and whose activation is strongly linked with colon cancer.

关键词： Network analyzers Biochemistry Colon Bioinformatics Cancer

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Development of a Converter-based Supercapacitor System Emulator for PV Applications

Development of a Converter-based Supercapacitor System Emula...

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IEEE Energy Conversion Congress and Exposition, ECCE

作者： Paychuda Kritprajun Elizabeth Sutton Leon M. Tolbert Yunting Liu Jingxin Wang Nattapat Praisuwanna Maximiliano Ferrari Department of Electrical Engineering and Computer Science The University of Tennessee Knoxville TN USA Department of Electrical Engineering The Pennsylvania State University University Park PA USA Grid Components and Control Oak Ridge National Laboratory Oak Ridge TN USA

As the utilization of supercapacitors in power system applications continues to increase, it is important to observe their behavior under transient and long-term operations in order to understand their impact on power grids. A real-time reconfigurable hardware testbed (HTB) is a power network emulator that provides flexibility to study various power system scenarios. This paper presents an emulation of a supercapacitor for a photovoltaic (PV) system on the HTB platform such that its dynamic behavior during power system scenarios can be observed. The developed emulator on the HTB is verified by comparing the emulation results with the model developed in MATLAB/Simulink. The experimental results of the emulator are consistent with the simulation results under the grid support scenarios. This supercapacitor emulator can be potentially used for various power system scenarios in addition to the PV applications presented in this paper.

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Multi-Modal Domain Adaptation Variational Autoencoder for EEG-Based Emotion Recognition

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IEEE/CAA Journal of Automatica Sinica 2022年第9期9卷 1612-1626页

作者： Yixin Wang Shuang Qiu Dan Li Changde Du Bao-Liang Lu Huiguang He the Research Center for Brain-inspired Intelligence National Laboratory of Pattern RecognitionInstitute of AutomationChinese Academy of ScienceBeijing 100190 the University of Chinese Academy of Sciences Beijing 100049 the Beijing Institute of Control and Electronic Technology Beijing 100038China the School of Mathematics and Information Sciences Yantai UniversityYantai 264003China the Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of ScienceBeijingChina the Department of Computer Science and Engineering Shanghai Jiao Tong UniversityShanghai 200240China

Traditional electroencephalograph(EEG)-based emotion recognition requires a large number of calibration samples to build a model for a specific subject,which restricts the application of the affective brain computer interface(BCI)in *** attempt to use the multi-modal data from the past session to realize emotion recognition in the case of a small amount of calibration *** solve this problem,we propose a multimodal domain adaptive variational autoencoder(MMDA-VAE)method,which learns shared cross-domain latent representations of the multi-modal *** method builds a multi-modal variational autoencoder(MVAE)to project the data of multiple modalities into a common *** adversarial learning and cycle-consistency regularization,our method can reduce the distribution difference of each domain on the shared latent representation layer and realize the transfer of *** experiments are conducted on two public datasets,SEED and SEED-IV,and the results show the superiority of our proposed *** work can effectively improve the performance of emotion recognition with a small amount of labelled multi-modal data.

关键词： Cycle-consistency domain adaptation electroencephalograph(EEG) multi modality variational autoencoder

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Parallel control of supercritical thermal power unit based on the ACP method 1

Parallel control of supercritical thermal power unit based o...

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1st IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2021

作者： Gong, Linjuan Hou, Guolian Gu, Hongqun Huang, Congzhi Lv, Xuming Wang, Lei School of Control and Computer Engineering North China Electric Power University Beijing China State Grid Liaoning Electric Power Supply Co. Ltd. Shenyang China

ISBN: (纸本)9781665433372

As a mature and stable electric power source, the control of thermal power unit has great significant in the safe and stable operation of the whole power grid. To provide appropriate reference for the control of thermal power unit for higher performance, an ACP method based parallel control scheme is structured in this paper. Firstly, an artificial control system whose characteristics are similar to the actual physic system is established. Secondly, the optimal plant model and the corresponding control strategy are selected for the artificial system to guide the behaviors of the physic system using computation experiments and evaluation. Thirdly, the operation stability and efficiency of the power generation process are guaranteed by the parallel execution of the artificial control system and physic control system. Finally, the superiorities of the presented parallel strategy are demonstrated through the simulation experiments on a 600MW supercritical thermal power unit. © 2021 IEEE.

关键词： control systems

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A New SOC Distribution Synergy Method for Capacity Configuration of Flywheel Energy Storage in Primary Frequency Regulation

SSRN

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SSRN 2024年

作者： Hong, Feng Wei, Kuanchang Ji, Weiming Hao, Junhong Fang, Fang Liu, Jizhen The State Key Laboratory of Alternate Electric Power System with Renewable Energy Sources North China Electric Power University Beijing102206 China School of Control and Computer Engineering North China Electric Power University Beijing102206 China

Energy storage systems, coupled with power sources, are applied as an important means of frequency modulation support for large-scale grid connection of new energy. Flywheel energy storage systems (FESS) are considered short-term energy storage solutions due to their capacity for rapid and efficient energy storage and release. However, the power output characteristic of flywheels is potentially correlated to the state of charge (SOC) in the process of continuous operation while the SOC distribution would be attributed to the output power and duration of the flywheel. This study theoretically developed analytical correlations between SOC distribution and flywheel dynamic characteristics on statistical performance based on a cross-entropy method under wide range sampling scenarios of SOC. The results demonstrate that various operation states of FESS have a disparity effect on the statistical performance of modules. A SOC management and capacity configuration method considering continuous operation states is proposed, and the results illustrate that the capital expenditure of capacity configuration cuts approximately 8.2% attaining the SOC stability under the homogenous frequency modulation scenario. Therefore, capacity configurations of FESS can effectively compensate for the capital loss caused by detrimental SOC so that the cross-entropy correlation method conducted in series has the capacity advantages. © 2024, The Authors. All rights reserved.

关键词： Frequency modulation

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Extension Principle and controller Design for Nonlinear Systems

Extension Principle and Controller Design for Nonlinear Syst...

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European control Conference (ECC)

作者： Altuğ İftar Farshad Khorrami Department of Electrical and Electronics Engineering Eskişehir Technical University Eskişehir Turkey Department of Electrical and Computer Engineering Control/Robotics Research Laboratory (CRRL) New York University 5 Metrotech Center Brooklyn NY U.S.A.

We generalize the principle of extension and controller design using this principle for nonlinear systems. We first define principles of inclusion and extension for nonlinear time-invariant (NLTI) systems. Thereafter, we present the necessary and sufficient conditions for a system to be an extension of another and show that when the expanded system is an extension of the original system, any controller designed for the expanded system can be contracted for implementation on the original system. Subsequently, we demonstrate how an overlappingly decomposed NLTI system can be expanded so that the expanded system is an extension of the original system, how decentralized controllers can be designed for the expanded system, and how these controllers can be contracted for implementation on the original system. An example is also provided to illustrate the extension and contraction concepts and show controller design using the proposed principles.

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A novel compaction approach for SBST test programs

arXiv

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arXiv 2021年

作者： Guerrero-Balaguera, Juan-David Condia, Josie E. Rodriguez Reorda, Matteo Sonza Department of Control and Computer Engineering Politecnico di Torino Torino Italy

In-field test of processor-based devices is a must when considering safety-critical systems (e.g., in robotics, aerospace, and automotive applications). During in-field testing, different solutions can be adopted, depending on the specific constraints of each scenario. In the last years, Self-Test Libraries (STLs) developed by IP or semiconductor companies became widely adopted. Given the strict constraints of in-field test, the size and time duration of a STL is a crucial parameter. This work introduces a novel approach to compress functional test programs belonging to an STL. The proposed approach is based on analyzing (via logic simulation) the interaction between the micro-architectural operation performed by each instruction and its capacity to propagate fault effects on any observable output, reducing the required fault simulations to only one. The proposed compaction strategy was validated by resorting to a RISC-V processor and several test programs stemming from diverse generation strategies. Results showed that the proposed compaction approach can reduce the length of test programs by up to 93.9% and their duration by up to 95%, with minimal effect on fault coverage. © 2021, CC BY-NC-ND.

关键词： Compaction

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