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2019 2nd International Conference on computer science and Advanced Materials(CSAM 2019)

作者： Qian Sun Li Xin Faliang Chang Zengshun Zhao College of Electronics Communications and Phisics Shandong University of Science and Technology School of Control Science and Engineering Shandong University Department of Electrical& Computer Engineering University of Florida

Image classification being widely applied to computer vision is an im-age processing method to distinguish the different category targets according to the different features reflected by the image information. BOW-SVM is a relative-ly typical image classification method with higher precision, however, it's unsatis-factory in operation performance. To improve the performance and precision more efficiently, a high-efficiency image classification method based on HOG-PCA is proposed. First of all, it is to make the feature whitening by extracting the Histogram of Oriented Gradients(HOG) features, secondly, make the random down-sampling for the scale unification, afterwards, adopt the principal component analysis(PCA) for feature mapping and finally make the nearest neighbor classification through the minimum two-order norm determination. In the experiment, the proposed method is realized and tested on the P ASCAL 2012 data set through C++ on the basis of OPENCV and Darwin to compare the precision and operation performance of this method and BOW-SVM method;according to the experiment, the proposed has higher precision and better operation performance.

关键词： Deep Neural Network Multi-Layer Feature Learningl Minimum Two-Order Norm Image Classification Image Features

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Performance Analysis of Dual-Hop Mixed FSO/mmWave Systems

Performance Analysis of Dual-Hop Mixed FSO/mmWave Systems

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IEEE International Conference on Communications Workshops, ICC

作者： Yan Zhang Jiayi Zhang Liang Yang Dinh-Thuan Do Bo Ai School of Electronic and Information Engineering Beijing Jiaotong University Beijing China College of Computer Science and Electronic Engineering Hunan University Changsha China Faculty of Electrical and Electronics Engineering Ton Duc Thang University Ho Chi Minh City Vietnam State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China

ISBN: (数字)9781728174402

ISBN: (纸本)9781728174419

The combination of free-space optical (FSO)-based backhaul links and millimeter wave (mmWave)-based access links is considered as a key enabling technique to provide enhanced mobile broadband in ultra dense networks. In this paper, the generalized end-to-end performance of a dual-hop mixed FSO/mmWave relaying system is evaluated. The FSO link is assumed to follow the Gamma-Gamma fading with pointing error impairments, while the mmWave link experiences the fluctuating two-ray fading. Both heterodyne detection and indirect modulation/direct detection are accounted for in the FSO link. Using both amplify-and-forward and decode-and-forward relaying schemes, novel closed-form expressions for the outage probability and average bit error probability (BER) are derived in terms of bivariate Fox's H-functions. Furthermore, an asymptotic analysis for the outage probability and the average BER is provided to show the diversity order and other important engineering insights. Finally, the accuracy of our derived results is validated through Monte-Carlo simulations.

关键词： Radio frequency Fading channels Signal to noise ratio Relays Optical transmitters Power system reliability Probability

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Benchmark problems for transcranial ultrasound simulation: Intercomparison of compressional wave models

arXiv

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arXiv 2022年

作者： Aubry, Jean-Francois Bates, Oscar Boehm, Christian Pauly, Kim Butts Christensen, Douglas Cueto, Carlos Gélat, Pierre Guasch, Lluis Jaros, Jiri Jing, Yun Jones, Rebecca Li, Ningrui Marty, Patrick Montanaro, Hazael Neufeld, Esra Pichardo, Samuel Pinton, Gianmarco Pulkkinen, Aki Stanziola, Antonio Thielscher, Axel Treeby, Bradley Van't Wout, Elwin Physics for Medicine Paris INSERM U1273 ESPCI Paris PSL University CNRS UMR 8063 France Department of Bioengineering Imperial College London Exhibition Road LondonSW7 2AZ United Kingdom Institute of Geophysics ETH Zürich Sonneggstrasse 5 Zürich8092 Switzerland Department of Radiology Stanford University StanfordCA United States Department of Biomedical Engineering Department of Electrical and Computer Engineering University of Utah United States Department of Surgical Biotechnology Division of Surgery and Interventional Science University College London LondonNW3 2PF United Kingdom Earth Science and Engineering Department Imperial College London London United Kingdom Centre of Excellence IT4Innovations Faculty of Information Technology Brno University of Technology Bozetechova 2 Brno612 00 Czech Republic Graduate Program in Acoustics The Pennsylvania State University University Park PA16802 United States Joint Department of Biomedical Engineering University of North Carolina at Chapel Hill North Carolina State University NC United States Department of Electrical Engineering Stanford University StanfordCA United States Zurich Switzerland Laboratory for Acoustics / Noise control Empa Swiss Federal Laboratories for Materials Science and Technology Dubendorf Switzerland Zurich Switzerland Radiology and Clinical Neurosciences Departments Cumming School of Medicine University of Calgary Canada Department of Applied Physics University of Eastern Finland Kuopio70211 Finland Department of Medical Physics and Biomedical Engineering University College London Gower Street LondonWC1E 6BT United Kingdom Technical University of Denmark Denmark Danish Research Center for Magnetic Resonance Copenhagen University Hospital Hvidovre Denmark Institute for Mathematical and Computational Engineering School of Engineering and Faculty of Mathematics Pontificia Universidad Catolica de Chile Santiago Chile

Computational models of acoustic wave propagation are frequently used in transcranial ultrasound therapy, for example, to calculate the intracranial pressure field or to calculate phase delays to correct for skull distortions. To allow intercomparison between the different modeling tools and techniques used by the community, an international working group was convened to formulate a set of numerical benchmarks. Here, these benchmarks are presented, along with intercomparison results. Nine different benchmarks of increasing geometric complexity are defined. These include a single-layer planar bone immersed in water, a multi-layer bone, and a whole skull. Two transducer configurations are considered (a focused bowl and a plane piston), giving a total of 18 permutations of the benchmarks. Eleven different modeling tools are used to compute the benchmark results. The models span a wide range of numerical techniques, including the finite-difference time-domain method, angular-spectrum method, pseudospectral method, boundary-element method, and spectral-element method. Good agreement is found between the models, particularly for the position, size, and magnitude of the acoustic focus within the skull. When comparing results for each model with every other model in a cross comparison, the median values for each benchmark for the difference in focal pressure and position are less than 10% and 1 mm, respectively. The benchmark definitions, model results, and intercomparison codes are freely available to facilitate further comparisons. Copyright © 2022, The Authors. All rights reserved.

关键词： Bone

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A Markov Traffic Model for Signalized Traffic Networks Based on Bayesian Estimation

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IFAC-PapersOnLine 2020年第2期53卷 15029-15034页

作者： S.Y. Liu S. Lin Y.B. Wang B. De Schutter W.H.K. Lam School of Computer Science and Technology University of Chinese Academy of Sciences Beijing 100089 China Key Lab of Big Data Mining and Knowledge Management Chinese Academy of Sciences College of Civil Engineering and Architecture Zhejiang University PR China Delft Center for Systems and Control Delft University of Technology The Netherlands Department of Civil and Structural Engineering The Hong Kong Polytechnic University Hong Kong SAR China

In order to better understand the stochastic dynamic features of signalized traffic networks, we propose a Markov traffic model to simulate the dynamics of traffic link flow density for signalized urban traffic networks with demand uncertainty. In this model, we have four different state modes for the link according to different congestion levels of the link. Each link can only be in one of the four link state modes at any time, and the transition probability from one state to the other state is estimated by Bayesian estimation based on the distributions of the dynamic traffic flow densities, and the posterior probabilities. Therefore, we use a first-order Markov Chain Model to describe the dynamics of the traffic flow evolution process. We illustrate our approach for a small traffic network. Compared with the data from the microscopic traffic simulator SUMO, the proposed model can estimate the link traffic densities accurately and can give a reliable estimation of the uncertainties in the dynamic process of signalized traffic networks.

关键词： Markov traffic model Traffic signals Bayesian Urban traffic network

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ATT: Attention-based Timbre Transfer

ATT: Attention-based Timbre Transfer

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International Joint Conference on Neural Networks (IJCNN)

作者： Deepak Kumar Jain Akshi Kumar Linqin Cai Siddharth Singhal Vaibhav Kumar Key Laboratory of Intelligent Air-Ground Cooperative Control for Universities in Chongqing College of Automation Chongqing University of Posts and Telecommunications Chongqing China Department of Computer Science and Engineering Delhi Technological University New Delhi India Key Laboratory of Industrial Internet of Things and Networked Control Ministry of Education Chongqing University of Posts and Telecommunications Chongqing China

ISBN: (数字)9781728169262

ISBN: (纸本)9781728169279

In this paper, we tackle the issue of timbre transfer on a given monophonic music sample. The objective is to change the timbre of source audio from one instrument to another while preserving features such as loudness, pitch, and rhythm. Existing approaches use image-to-image translation techniques on the entire region of time-frequency representations of the raw audio wave, which may lead to the addition of unwanted elements in the final audio waveform. We propose Attention-based Timbre Transfer (ATT), an attention-based pipeline for transferring timbre. To the best of our knowledge, ATT is the first approach which leverages attention for achieving timbre transfer. Further, ATT uses MelGAN for spectrogram inversion, which provides a fast and parallel alternative to other autoregressive music generation approaches, without compromising on the quality. ATT shows promising results, thus efficaciously transferring timbre with minimal offset to other physical characteristics.

关键词： Timbre Spectrogram Generative adversarial networks Gallium nitride Instruments Time-frequency analysis

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State-control-limit-based rejuvenation modelling and optimisation of the virtualised cloud server

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International Journal of Reliability and Safety 2018年第4期12卷 406-428页

作者： Dang, Weichao Zeng, Jianchao College of Electrical and Information Engineering Lanzhou University of Technology Lanzhou730050 China Division of Industrial and System Engineering Taiyuan University of Science and Technology Taiyuan030024 China School of Computer Science and Control Engineering North University of China Taiyuan030051 China

Software rejuvenation modelling and optimisation of the virtualised cloud server has been studied. A software rejuvenation policy on the virtual machines and the virtual machine monitor has been proposed in order to ensure high availability of the virtualised cloud server. The multi-component system, composed of the virtual machines and the virtual machine monitor, which are structurally dependent, has been reduced to the multiple two-component systems. The state-control-limit-based rejuvenation policy has been proposed and the joint probability density of the degraded state of the two-component VM-VMM has been derived. Furthermore, the solution to the joint probability density has been proposed. Finally, the stationary unavailability of the virtualised cloud server has been modelled. Numerical experiments have verified the correctness of the probability density function and the feasibility of the rejuvenation policy. The state-control-limit-based rejuvenation policy leads to lower unavailability of the virtualised cloud server in comparison with the lifetime-based rejuvenation policy. Copyright © 2018 Inderscience Enterprises Ltd.

关键词： Availability

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Group maintenance strategy for stochastic selective maintenance

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International Journal of Wireless and Mobile Computing 2018年第4期14卷 362-368页

作者： Zhao, Jing Zeng, Jianchao Division of Industrial and System Engineering Taiyuan University of Science of Technology Taiyuan030024 China College of Information Engineering Guangdong Mechanical and Electrical Polytechnic Guangzhou510515 China School of Computer Science and Control Engineering North University of China Taiyuan030051 China

Selective maintenance is often applied to many industrial environments when the maintenance actions are performed between sequence missions. When the length of maintenance or work mission time is stochastic and there are multiple maintenance workers with different capacity, previous works to determine maintenance and mission times are unsuitable for it. Assuming that the time of work mission is random and maintenance time is determined, to maximise system reliability of next work mission, this paper proposes a stochastic model for a two-state system comprising several series-parallel components with multiple maintenance workers under the maintenance time limit. The optimal maintenance plan is obtained by hybrid intelligent optimisation algorithm. The validity and feasibility of the model are verified by the simulation. Copyright © 2018 Inderscience Enterprises Ltd.

关键词： Stochastic models

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Randomised benchmarking for characterizing and forecasting correlated processes

arXiv

引用

arXiv 2023年

作者： Zhang, Xinfang Wu, Zhihao White, Gregory A.L. Xiang, Zhongcheng Hu, Shun Peng, Zhihui Liu, Yong Zheng, Dongning Fu, Xiang Huang, Anqi Poletti, Dario Modi, Kavan Wu, Junjie Deng, Mingtang Guo, Chu Institute for Quantum Information State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Changsha410073 China School of Physics and Astronomy Monash University VIC3800 Australia Dahlem Center for Complex Quantum Systems Freie Universität Berlin Berlin14195 Germany Institute of Physics Chinese Academy of Sciences Beijing100190 China Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control of Ministry of Education Department of Physics Synergetic Innovation Center for Quantum Effects and Applications Hunan Normal University Changsha410081 China Science Mathematics and Technology Cluster and Engineering Product Development Pillar Singapore University of Technology and Design 8 Somapah Road 487372 Singapore Centre for Quantum Technologies National University of Singapore 117543 Singapore MajuLab CNRS-UNS-NUS-NTU International Joint Research Unit UMI 3654 Singapore Quantum for NSW Sydney2000 Australia

The development of fault-tolerant quantum processors relies on the ability to control noise. A particularly insidious form of noise is temporally correlated or non-Markovian noise. By combining randomized benchmarking with supervised machine learning algorithms, we develop a method to learn the details of temporally correlated noise. In particular, we can learn the time-independent evolution operator of system plus bath and this leads to (i) the ability to characterize the degree of non-Markovianity of the dynamics and (ii) the ability to predict the dynamics of the system even beyond the times we have used to train our model. We exemplify this by implementing our method on a superconducting quantum processor. Our experimental results show a drastic change between the Markovian and non-Markovian regimes for the learning accuracies. Copyright © 2023, The Authors. All rights reserved.

关键词： Benchmarking

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Review of renewable energy curtailment in China: Current situation and solutions

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AIP Conference Proceedings 2022年第1期2681卷

作者： Yingai Jin Yiwen Zhang Nan Jiang Mingjie Lv Hang Yin Wenyuan Sun Liang Li 1State Key Laboratory of Automotive Simulation and Control Jilin University Changchun 130025 China 2College of Automotive Engineering Jilin University Changchun 130025 China 3School of Physics Engineering and Computer Science University of Hertfordshire Hatfield AL10 9AB UK

In recent decades, China's renewable power generation has developed quickly. However, the randomness of output power causes wind and photovoltaic power curtailment. With the rapid development of renewable energy, renewable energy consumption has gradually become the focus of research. This article comprehensively reviews the current situation and practices of reducing the curtailment of renewable energy in China. From the perspective of methods used to stabilize the fluctuation characteristics of generation output, two modes are outlined: based on energy storage devices and complementary wind-solar system. Then, an Advanced Adiabatic Compressed Air Energy Storage (AA-CAES) system simulation model is proposed as a crucial solution to reduce renewable energy waste. Finally, the application and development trend of renewable energy and energy storage technology has prospected.

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TPFIANet: Three path feature progressive interactive attention learning network for medical image segmentation

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Knowledge-Based Systems 2025年 323卷

作者： Zhao, Yawu Wang, Shudong Ren, Yande Wang, Jiehuan Wang, Shaoqiang Qiao, Sibo Liu, Tiyao Pang, Shanchen Shandong Key Laboratory of Intelligent Oil & Gas Industrial Software Qingdao Institute of Software College of Computer Science and Technology China University of Petroleum Qingdao Shandong China Department of Medical Imaging Center Affiliated Hospital of Qingdao University Qingdao Shandong China Department of Medical Imaging Affiliated Hospital of Jining Medical University Jining Shandong China School of Information and Control Engineering Qingdao University of Technology Qingdao Shandong China School of Software Tiangong University Tianjin China

In the field of medical image segmentation, medical image segmentation methods with high accuracy and generalization capabilities are crucial for driving personalized healthcare solutions and enhancing patient experience. To address the inherent challenges of difficulty in acquiring complex structural features and weak generalization ability in medical image segmentation, we propose a three-path spatial learning (TPSL) module, which takes advantage of convolutional neural networks (CNNs) to skillfully learn specific details at different scales to acquire better feature representations, and then, we propose a progressive feature cross-fusion (PFCF) module, which aims to dynamically learn feature information under different levels in the encoder, which enhances the feature representation. Finally, we propose the feature interactive attention fusion (FIAF) module, which mixes features from different scales and channels, adaptively learns feature weights and enhances the connection between channel and local spatial information. Based on the above modules, we design a three path feature progressive interactive attention learning network (TPFIANet), which captures image features at different levels and scales. We demonstrate the segmentation performance of TPFIANet on three public datasets and three self-organized datasets. Notably, our TPFIANet also demonstrates amiable segmentation performance on datasets of different modalities while maintaining a lighter architecture. © 2025

关键词： Image segmentation

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