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Parallel computing of multi-contingency optimal power flow with transient stability constraints

Protection and Control of Modern Power systems 2018年第1期3卷 213-222页

作者： Yude Yang Anjun Song Hui Liu Zhijun Qin Jun Deng Junjian Qi Guangxi Key Laboratory of Power System Optimization and Energy Technology Guangxi UniversityNanningChina State Grid Shaanxi Electric Power Research Institute Xi’anChina Department of Electrical and Computer Engineering University of Central FloridaOrlandoFL 32816USA

To deal with the high dimensionality and computational density of the Optimal Power Flow model with Transient Stability Constraints(OTS),a credible criterion to determine transient stability is proposed based on swing curves of generator rotor and the characteristics of transient *** this method,the swing curves of all generator rotors will be independent one ***,when a parallel computing approach based on the MATLAB parallel toolbox is used to handle multi-contingency cases,the calculation speed is improved ***,numerical simulations on three test systems including the NE-39 system,the IEEE 300-bus system,and 703-bus systems,show the effectiveness of the proposed method in reducing the computing time of OTS calculation.

关键词： Power system Transient stability Multi-contingency Optimal power flow Parallel computing

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Compressive spectral imaging based on hexagonal blue noise coded apertures

arXiv

引用

arXiv 2019年

作者： Zhang, Hao Ma, Xu Lau, Daniel L. Arce, Gonzalo R. Key Laboratory of Photoelectronic Imaging Technology and System of Ministry of Education of China School of Optics and Photonics Beijing Institute of Technology Beijing100081 China Department of Electrical and Computer Engineering University of Kentucky LexingtonKY40506 United States Department of Electrical and Computer Engineering University of Delaware NewarkDE19716 United States

The coded aperture snapshot spectral imager (CASSI) is a computational imaging system that acquires a three dimensional (3D) spectral data cube by a single or a few two dimensional (2D) measurements. The 3D data cube is reconstructed computationally. Binary on-off random coded apertures with square pixels are primarily implemented in CASSI systems to modulate the spectral images in the image plane. The design and optimization of coded apertures have been shown to improve the imaging performance of these systems significantly. This work proposes a different approach to code design. Instead of using traditional squared tiled coded elements, hexagonal tiled elements are used. The dislocation between the binary hexagonal coded apertures and the squared detector pixels is shown to introduce an equivalent grey-scale spatial modulation that increases the degrees of freedom in the sensing matrix, thus further improving the spectral imaging performance. Based on the restricted isometry property (RIP) of compressive sensing theory, this paper proves that optimal coded aperture patterns under a hexagonal lattice obey blue noise spatial characteristic, where "on" elements are placed as far from each other as possible. In addition, optimal coded apertures used in different snapshots are complementary to each other. This paper also proves the superiority of the hexagonal blue noise coded aperture over the traditional coded apertures with squared tiled elements. Based on a set of simulations, the proposed hexagonal tiled coded apertures are shown to effectively improve the imaging performance of CASSI systems compared to that of traditional coded apertures on rectangular lattices. Copyright © 2019, The Authors. All rights reserved.

关键词： Spectroscopy

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Lightweight Protection of User Identity Privacy Based on Zero-knowledge Proof

Lightweight Protection of User Identity Privacy Based on Zer...

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IEEE International Conference on systems, Man and Cybernetics

作者： Zhengwei Ren Xianye Zha Kai Zhang Jing Liu Heng Zhao College of Computer Science and Technology Wuhan University of Science and Technology and Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan China College of Computer Science and Technology Wuhan University of Science and Technology Wuhan China Wuhan Digital and Engineering Institute Wuhan China

A number of solutions have been proposed to tackle the user privacy-preserving issue. Most of existing schemes, however, focus on methodology and techniques from the perspective of data processing. In this paper, we propose a lightweight privacy-preserving scheme for user identity from the perspective of data user and applied cryptography. The basic idea is to break the association relationships between User identity and his behaviors and ensure that User can access data or services as usual while the real identity will not be revealed. To this end, an interactive zero-knowledge proof protocol of identity is executed between CSP and User. Besides, a trusted third-party is introduced to manage user information, help CSP to validate User identity and establish secure channel between CSP and User via random shared key. After passing identity validation, User can log into cloud platform as usual without changing existing business process using random temporary account and password generated by CSP and sent to User by the secure channel which can further obscure the association relationships between identity and behaviors. Formal security analysis and theoretic and experimental evaluations are conducted, showing that the proposal is efficient and practical.

关键词： Proposals Data privacy Privacy Protocols Password Authentication

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Stochastic Link Flow Model for Signalized Traffic Networks with Uncertainty in Demand

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IFAC-PapersOnLine 2018年第9期51卷 458-463页

作者： Lin, S. Pan, T.L. Lam, W.H.K. Zhong, R.X. Schutter, B. De School of Computer and Control Engineering University of Chinese Academy of Sciences Key Laboratory of System Control and Information Processing Ministry of Education BeijingShanghai China Department of Civil and Structural Engineering The Hong Kong Polytechnic University Hong KongSAR Hong Kong School of Engineering Sun Yat-Sen University Guangzhou China Delft Center for Systems and Control Delft University of Technology Delft Netherlands

In order to investigate the stochastic features in urban traffic dynamics, we propose a Stochastic Link Flow Model (SLFM) for signalized traffic networks with demand uncertainties. In the proposed model, the link traffic state is described using four different link state modes, and the probability for each link state mode is determined based on the stochastic link states. The SLFM model is expressed as a finite mixture approximation of the link state probabilities and the dynamic link flow models for all the four link state modes. Using data from microscopic traffic simulator SUMO, we illustrate that the proposed model can provide a reliable estimation of the link traffic states, and as well as good estimations on the link state uncertainties propagating within a signalized traffic network. © 2018

关键词： Stochastic models Routers Stochastic systems Street traffic control Traffic signals Vehicle actuated signals Demand uncertainty Finite mixtures Stochastic features Stochastic traffic Traffic networks Traffic simulators Uncertainty in demand Urban traffic networks

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Blind motion deblurring based on generative adversarial networks

Blind motion deblurring based on generative adversarial netw...

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2019 International Conference on Video, Signal and Image Processing, VSIP 2019

作者： Su, Kai Li, Xueming Li, Xuewei School of Digital Media and Design Arts Beijing University of Posts and Telecommunications No.10 Xitucheng Road Haidian District Beijing China Beijing Key Laboratory of Network System and Network Culture Beijing University of Posts and Telecommunications No.10 Xitucheng Road Haidian District Beijing China Department of Information and Communication Engineering Beijing University of Posts and Telecommunications No.10 Xitucheng Road Haidian District Beijing China

ISBN: (纸本)9781450371483

In the past two years, GAN (Generative Adversarial Networks) has emerged and been applied to the image deblurring problem, showing good results, especially in restoring high-frequency texture details of the image. However, there are very few papers on GAN-based image deblurring so far, and it is not ideal for the processing of edge features. In this paper, an end-to-end blind image motion deblurring algorithm based on GAN is proposed. In the pixel domain, we use the weighted sum of cross entropy and L1 loss as the loss function. In the feature domain, the weighted sum of the features extracted by VGG and DenseNet is used to calculate the loss. And we add "deconvolution + PixelShuffle" module to the network. Experiments show that our method achieves the excellent performance in terms of PSNR (Peak Signal to Noise Ratio) and SSIM (Structural Similarity Index), simultaneously eliminates the checkerboards effectively. © 2019 Association for Computing Machinery.

关键词： Generative adversarial networks

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AI-Driven Ultrasound Detection of Ovarian Cancer that Generalizes: An International Multicentre Validation Study

SSRN

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SSRN 2024年

作者： Christiansen, Filip Konuk, Emir Ganeshan, Adithya Raju Welch, Robert Huix, Joana Palés Czekierdowski, Artur Leone, Francesco Paolo Giuseppe Haak, Lucia Anna Fruscio, Robert Gaurilcikas, Adrius Franchi, Dorella Fischerova, Daniela Mor, Elisa Savelli, Luca Pascual, Maria Àngela Kudla, Marek Guerriero, Stefano Buonomo, Francesca Liuba, Karina Montik, Nina Alcázar, Juan Luis Domali, Ekaterini Pangilinan, Nelinda Catherine P. Carella, Chiara Munaretto, Maria Šašková, Petra Verri, Debora Visenzi, Chiara Herman, Pawel Smith, Kevin Epstein, Elisabeth Department of Clinical Science and Education Södersjukhuset Karolinska Institutet Stockholm Sweden School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Science for Life Laboratory Stockholm Sweden Sweden Pathology Clinical Pharmacology and Safety Sciences AstraZeneca R&D Gothenburg Sweden Department of Obstetrics and Gynecology Södersjukhuset Stockholm Sweden Digital Futures KTH Royal Institute of Technology Stockholm Sweden First Department of Gynecological Oncology and Gynecology Medical University of Lublin Lublin Poland Unit of Obstetrics & Gynecology Department of Biomedical and Clinical Sciences Luigi Sacco University Hospital University of Milan Milan Italy Institute for the Care of Mother and Child Prague Czech Republic Third Faculty of Medicine Charles University Prague Czech Republic Department of Obstetrics and Gynecology IRCCS San Gerardo Dei Tintori Monza Italy Department of Medicine and Surgery University of Milano-Bicocca Milan Italy Department of Obstetrics and Gynaecology Lithuanian University of Health Sciences Kaunas Lithuania Unit of Preventive Gynecology European Institute of Oncology IRCCS Milan Italy Gynecologic Oncology Centre Department of Gynecology Obstetrics and Neonatology First Faculty of Medicine Charles University General University Hospital in Prague Prague Czech Republic Fondazione Poliambulanza Istituto Ospedaliero Brescia Italy Obstetrics and Gynecology Unit Forlì and Faenza Hospitals AUSL Romagna Italy Department of Obstetrics Gynecology and Reproduction Hospital Universitario Dexeus Barcelona Spain Department of Perinatology and Oncological Gynecology Faculty of Medical Sciences Medical University of Silesia Katowice Poland Centro Integrato di Procreazione Medicalmente Assistita e Diagnostica Ostetrico-Ginecologica Azienda Ospedaliero Universitaria-Policlinico Duilio Casula Monserrato University of Cagliari Cagliari Italy Institute for Maternal and Chi

Background: A critical shortage of expert ultrasound examiners has raised concerns of unnecessary interventions and delayed cancer diagnoses. Artificial intelligence (AI)-driven diagnostic support has the potential to alleviate this burden and improve patient outcomes. Deep learning, applied to ultrasound images, has recently demonstrated promising results in ovarian cancer detection;however, external validation is lacking. Our aim was to develop a deep neural network (DNN) model for ovarian cancer detection and evaluate its robustness and ability to generalize across different patient populations in a large multicentre setting. We also sought to assess an AI-assisted triage strategy and compare it to current practice in a retrospective ***: We retrospectively collected 17119 ultrasound images from 3652 women with an ovarian lesion (2224 benign, 1428 malignant) from 20 centres in 8 countries. A total of 2718 cases were externally reviewed by a minimum of 7 expert and 6 non-expert examiners. Using a leave-one-centre-out cross-validation scheme, for each centre in turn, we trained a transformer-based DNN model using data from the remaining 19 centres and compared the models' performance with that of expert and non-expert examiners in terms of accuracy, sensitivity, specificity, and F1 score. Furthermore, we retrospectively simulated and assessed how these models could be used in AI-assisted ***: Our models demonstrated robust performance across centres, ultrasound systems, and different histological diagnoses, with an overall area under the receiver operating characteristic curve (AUC) of 0·929 (95% CI, 0·919–0·938), and F1 score of 83·66% (95% CI, 82·25–85·04) on cases from unseen centres. They outperformed both expert and non-expert examiners, with F1 scores of 79·85% (95% CI, 78·32–81·33;Δ = 3·82 [95% CI, 2·42–5·24, p Interpretation: Our models exhibit strong generalization and outperform both expert and non-expert examiners in diagnostic

关键词： Deep neural networks

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Passivity and Synchronization of Coupled Complex-Valued Memristive Neural Networks

Passivity and Synchronization of Coupled Complex-Valued Memr...

引用

IEEE Symposium Series on Computational Intelligence (SSCI)

作者： Yanli Huang Jie Hou Shunyan Ren Erfu Yang Tianjin Key Laboratory of Optoelectronic Detection Technology and System School of Computer Science and Technology Tiangong University Tianjin China School of Mechanical Engineering Tiangong University Tianjin China Department of Design Manufacture and Engineering Management University of Strathclyde Glasgow Scotland UK

ISBN: (数字)9781728124858

ISBN: (纸本)9781728124865

The coupled complex-valued memristive neural networks (CCVMNNs) are investigated in this study. First, we analyze the passivity of the proposed network model by designing an appropriate controller and using certain inequalities as well as Lyapunov functional method, and provide a passivity condition for the considered CCVMNNs. In addition, a criterion for guaranteeing synchronization of this kind of network is established. Finally, the effectiveness and correctness of the acquired theoretical results are verified by a numerical example.

关键词： Synchronization Biological neural networks Memristors Couplings Neurons

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Front Cover: International Journal of Intelligent systems, Volume 37 Issue 11 November 2022

引用

International Journal of Intelligent systems 2022年第11期37卷

作者： Xianjia Meng Yong Yang Ximeng Liu Nan Jiang School of Information Science and Technology Northwest University Xi'an People's Republic of China Fujian Province Key Laboratory of Information Security of Network System and College of Computer and Data Science Fuzhou University Fuzhou People's Republic of China Cyberspace Security Research Center Peng Cheng Laboratory Shenzhen People's Republic of China Department of Internet of Things School of Information Engineering East China Jiao Tong University Nanchang People's Republic of China

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Identifying superword level parallelism with extended directed dependence graph reachability

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Science China(Information Sciences) 2017年第1期60卷 214-216页

作者： Jie ZHAO Rongcai ZHAO National Digital Switching System Engineering & Technological Research Center Computer Science Department cole Normale Supérieure

Dear editor,The increasing trend of multimedia applications’proliferation brings about multimedia extensions’wide use among existing microprocessors of mainstream manufacturers,e.g.,Intel’s MMX,AMD’s3DNow!,IBM’s VMX/Altivec,***,the implementation details behind these multimedia extensions vary from one architecture to another;hence,it generally comes in form of SIMD(single

关键词： node SIMD Identifying superword level parallelism with extended directed dependence graph reachability SLP

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Photonic radio frequency arbitrary waveform generator based on an integrated 49GHz FSR kerr micro-comb source

TechRxiv

引用

TechRxiv 2020年

作者： Moss, David J. Tan, Mengxi Xu, Xingyuan Boes, Andreas Corcoran, Bill Wu, Jiayang Nguyen, Thach G. Chu, Sai T. Little, Brent E. Morandotti, Roberto Mitchell, Arnan Optical Sciences Centre Swinburne University of Technology HawthornVIC3122 Australia Electro-Photonics Laboratory Department of Electrical and Computer Systems Engineering Monash University VIC3800 Australia School of Engineering RMIT University MelbourneVIC3001 Australia Department of Electrical and Computer System Engineering Monash University ClaytonVIC3168 Australia Department of Physics and Material Science City University of Hong Kong Tat Chee Avenue Hong Kong State Key Laboratory of Transient Optics and Photonics Xi'an Institute of Optics and Precision Mechanics Chinese Academy of Science Xi'an China INSR-Énergie Matériaux et Télécommunications 1650 Boulevard Lionel-Boulet VarennesQCJ3X 1S2 Canada Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology of China Chengdu610054 China

We report a photonic-based radio frequency (RF) arbitrary waveform generator (AWG) using a soliton crystal micro-comb source with a free spectral range (FSR) of 48.9 GHz. We successfully achieve arbitrary shapes including square waveforms with a tunable duty ratio ranging from 10% to 90%, sawtooth waveforms with a tunable slope ratio of 0.2 to 1, and a symmetric concave quadratic chirp waveform with an instantaneous frequency of sub GHz. We achieve good agreement between theory and experiment, validating the effectiveness of this approach towards realizing high-performance, broad bandwidth, nearly user-defined RF waveform generation. © 2020, CC BY.

关键词： Microwave photonics

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