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Chinese Automation Congress (CAC)

作者： Xinqiang Ma Likai Shen Baoquan Zhong Yi Huang Yong Liu Maonian Wu College of Computer Science and Technology Guizhou University Guiyang China School of Computer Science Hangzhou Dianzi University Hangzhou China School of Artificial Intelligence Chongqing University of Arts and Sciences Chongqing China Institute of Cyber-Systems and Control Zhejiang University Hangzhou China School of Information Engineering Huzhou University Hangzhou China

In a large number of bidding cases, there exists a widespread phenomenon of supplier group hustling or lowering the price to win the bid. In order to solve this problem and curb this trend, we propose a supplier group identification framework based on supplier bidding behavior, business-relationship and geo-relationship. For the supplier bidding quotation data, we adopt the method of correlation coefficient of bidding sequence to extract feature vectors and the method of clustering to find groups. For the business-relationship data, we crawl the industrial and commercial information from the industrial and commercial website to build the graph database and find the interest-association group. For geo-relationship data, we divide supplier groups based on different administrative level regions. Finally, we innovatively introduce a group-results merging algorithm based on Apriori correlation analysis to merge multiple group results. In the B-value test, after removing the group found in our framework, the average price of effective quotation can be significantly reduced and be closer to the estimated cost price by state grid. So our framework is validated effectively in supplier group recognition through experiments.

关键词： Correlation Mathematical model Databases Feature extraction Clustering algorithms Companies Procurement

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Deep differentiable random forests for age estimation

arXiv

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arXiv 2019年

作者： Shen, Wei Guo, Yilu Wang, Yan Zhao, Kai Wang, Bo Yuille, Alan Department of Computer Science Johns Hopkins University BaltimoreMD21218-2608 United States School of Communication and Information Engineering Shanghai University Shanghai200444 China College of Computer and Control Engineering Nankai University Tianjin300071 China Vector Institute and Peter Munk Cardiac Center of University Health Network TorontoON Canada

Age estimation from facial images is typically cast as a label distribution learning or regression problem, since aging is a gradual progress. Its main challenge is the facial feature space w.r.t. ages is inhomogeneous, due to the large variation in facial appearance across different persons of the same age and the non-stationary property of aging. In this paper, we propose two Deep Differentiable Random Forests methods, Deep Label Distribution Learning Forest (DLDLF) and Deep Regression Forest (DRF), for age estimation. Both of them connect split nodes to the top layer of convolutional neural networks (CNNs) and deal with inhomogeneous data by jointly learning input-dependent data partitions at the split nodes and age distributions at the leaf nodes. This joint learning follows an alternating strategy: (1) Fixing the leaf nodes and optimizing the split nodes and the CNN parameters by Back-propagation;(2) Fixing the split nodes and optimizing the leaf nodes by Variational Bounding. Two Deterministic Annealing processes are introduced into the learning of the split and leaf nodes, respectively, to avoid poor local optima and obtain better estimates of tree parameters free of initial values. Experimental results show that DLDLF and DRF achieve state-of-the-art performance on three age estimation datasets. Copyright © 2019, The Authors. All rights reserved.

关键词： Regression analysis

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DIFFERENTIAL VARIATIONAL INEQUALITIES IN INFINITE BANACH SPACES

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Acta Mathematica Scientia 2017年第1期37卷 26-32页

作者：刘振海曾生达 Guangxi Key Laboratory of Universities Optimization Control and Engineering Calculation and College of SciencesGuangxi University for Nationalities Institute of Computer Science Faculty of Mathematics and Computer Science Jagiellonian University

In this paper,we consider a new differential variational inequality（DVI,for short）which is composed of an evolution equation and a variational inequality in infinite Banach *** kind of problems may be regarded as a special feedback control *** on the Browder＇s theorem and the optimal control theory,we show the existence of solutions to the mentioned problem.

关键词： differential variational inequality C0-semigroup monotone operator existcnceof solutions

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Coordinated control of Offshore Wind Farm and Onshore HVDC Converter for Effective Power Oscillation Damping

Coordinated Control of Offshore Wind Farm and Onshore HVDC C...

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IEEE General Meeting Power& Energy Society

作者： Yousef Pipelzadeh Nilanjan Ray Chaudhuri Balarko Chaudhuri Tim Green Control and Power Research Group Imperial College London Electrical Engineering and Computer Science Penn State College of Engineering

ISBN: (纸本)9781538677049;9781538677032

Damping contribution from wind farms (WFs) is likely to become a mandatory requirement as a part of the grid codes. For remote offshore WFs, connected through a voltage source converter (VSC)-based direct current link, the most convenient option for the onshore transmission system operator (TSO) is to modulate the reactive power at the onshore VSC within their own jurisdiction. In this paper, we show that supplementary control through the onshore VSC alone, although attractive for TSOs, could result in undesirable voltage variations in the onshore grid. On the other hand, modulation of active power output of the wind turbine generators (WTG) alone turns out to be inadequate due to the limited overload capability of the WTGs. Coordinated control over both onshore VSC and aggregated WF output overcomes the above limitations and is shown to be effective for power oscillation damping. A homotopy approach is used to design the coordinated controller, which can be implemented locally (at offshore WF and onshore converter site) using a decentralized architecture. This is a bilinear matrix inequality problem, which is solved by transforming these constraints into linear matrix inequality constraints. Case studies on two test systems show that the proposed controller yields similar system dynamic response as supplementary control through the WF alone.

关键词： Damping Wind farms Oscillators Linear matrix inequalities HVDC transmission computer science Converters

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Consensus of mixed-order multi-agent systems with directed topology

Consensus of mixed-order multi-agent systems with directed t...

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Chinese Intelligent Systems Conference, CISC 2017

作者： Geng, Hua Chen, Zengqiang Liu, Zhongxin Zhang, Chunyan Zhang, Qing School of Information Electrical Engineering Hebei University of Engineering Handan056038 China College of Computer and Control Engineering Nankai University Tianjin300071 China Tianjin Key Laboratory of Intelligent Robotics Nankai University Tianjin300071 China College of Science Civil Aviation University of China Tianjin300300 China

ISBN: (纸本)9789811064982

In this paper, an in-depth study about the consensus problem of mixed-order multi-agent system with directed topology is performed. Specifically, this system is composed of two classes of agents respectively described by first-order and second-order dynamics. By the aid of state transformation, two different methods are proposed to solve the consensus. Still, two meaningful examples are provided to verify the effectiveness of the gained theoretical results. This paper is expected to establish a more realistic model and provide effective measures to solve the consensus problem. © 2018, Springer Nature Singapore Pte Ltd.

关键词： Multi agent systems

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An Improved Event-triggered h„ Filtering for Nonlinear Systems

An Improved Event-triggered h„ Filtering for Nonlinear Syst...

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Chinese control and Decision Conference, CCDC

作者： Zhongda Lu Guangtao Ran Fengbin Zhang Fengxia Xu School of Computer and Control Engineering Qiqihar University Qiqihar College of Computer Science and Technology Harbin University of Science and Technology Harbin

ISBN: (纸本)9781538612453;9781538612446

This paper addresses event-triggered H ∞ filtering for nonlinear Networked control Systems with time-delay. A new event-triggered scheme is proposed to determine the state transmission only when satisfying trigger conditions. Considering the effects of the event-triggered scheme and network-induced, the fuzzy filtering error system is built based on T-S fuzzy model. An augmented Lyapunov function is constructed with integral items, and the Writinger inequality is first utilized to analysis and design H ∞ filtering error system to derived a less conservative stability criterion. An illustrative example is presented to demonstrate the merit of the proposed event-triggered scheme and the effectiveness of the proposed method.

关键词： Filtering Nonlinear systems Networked control systems Fuzzy systems Delays Electronic mail

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Region based Ensemble Learning Network for Fine-grained Classification

arXiv

引用

arXiv 2019年

作者： Li, Weikuang Wang, Tian Wang, Chuanyun Shan, Guangcun Zhang, Mengyi Snoussi, Hichem School of Computer Science Shenyang Aerospace University Shenyang China School of Automation Science and Electrical Engineering Beihang University Beijing China School of Instrumentation Science and Opto-electronics Engineering Beihang University Beijing China College of Electrical Engineering and Control Science Nanjing Tech University Nanjing China Institue Charles Delaunay-LM2S-UMR STMR 6279 CNRS University of Technology of Troyes Troyes France

As an important research topic in computer vision, fine-grained classification which aims to recognition subordinate-level categories has attracted significant attention. We propose a novel region based ensemble learning network for fine-grained classification. Our approach contains a detection module and a module for classification. The detection module is based on the faster R-CNN framework to locate the semantic regions of the object. The classification module using an ensemble learning method, which trains a set of sub-classifiers for different semantic regions and combines them together to get a stronger classifier. In the evaluation, we implement experiments on the CUB-2011 dataset and the result of experiments proves our method’s efficient for fine-grained classification. We also extend our approach to remote scene recognition and evaluate it on the NWPU-RESISC45 dataset. Copyright © 2019, The Authors. All rights reserved.

关键词： Classification (of information)

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Hierarchical Attention Networks for Image Classification of Remote Sensing Images Based on Visual Q&A Methods

Hierarchical Attention Networks for Image Classification of ...

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Chinese Automation Congress (CAC)

作者： Haochen Li Tian Wang Mengyi Zhang Aichun Zhu Guangcun Shan Hichem Snoussi School of Automation Science and Electrical Engineering Beihang University Beijing China College of Electrical Engineering and Control Science Nanjing Tech University Nanjing China School of Computer Science and Technology Nanjing Tech University Nanjing China School of Instrumentation Science and Opto-electronic Engineering Beihang University Beijing China Institue Charles Delaunay-LM2S FRE CNRS 2019 University of Technology of Troyes Troyes France

This paper provides a mixed attention network for remote sensing image classification whose idea comes from VQA methods. In this way, it could deal with more complex requests beyond just identifying what is in the picture. The HAN (Hierarchial Attention Network) consists of an attention model to detect details on one hand and a self-attention model to detect global information on the other hand. Through attention heat maps we could see division of work is really effective and the HAN has a great performance on NWPU-RESISC45 data set. Furthermore, we may add some other subnetworks to reinforce this ability in the future.

关键词： Feature extraction Remote sensing Airplanes Task analysis Visualization Airports Graphics processing units

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HIV and COVID-19 co-infection: A mathematical model and optimal control

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Informatics in Medicine Unlocked 2022年 31卷 100978页

作者： Ringa, N. Diagne, M.L. Rwezaura, H. Omame, A. Tchoumi, S.Y. Tchuenche, J.M. Data and Analytic Services British Columbia Centre for Disease Control 655 W 12th Ave Vancouver BC V5Z 4R4 Canada School of Population and Public Health University of British Columbia 2329 West Mall Vancouver BC V6T 1Z4 Canada Département de Mathématiques UFR des Sciences et Technologies Université de Thiès Thiès BP 967 Senegal Mathematics Department University of Dar es Salaam P.O. Box 35062 Dar es Salaam Tanzania Department of Mathematics Federal University of Technology Owerri Nigeria Abdus Salam School of Mathematical Sciences Government College University Lahore Pakistan Department of Mathematics and Computer Sciences ENSAI University of Ngaoundéré P.O. Box 455 Ngaoundéré Cameroon School of Computer Science and Applied Mathematics University of the Witwatersrand Private Bag 3 Wits 2050 Johannesburg South Africa School of Computational and Communication Sciences and Engineering Nelson Mandela African Institution of Science and Technology P.O. Box 447 Arusha Tanzania

A new mathematical model for COVID-19 and HIV/AIDS is considered to assess the impact of COVID-19 on HIV dynamics and vice-versa. Investigating the epidemiologic synergy between COVID-19 and HIV is important. The dynamics of the full model is driven by that of its sub-models;therefore, basic analysis of the two sub-models;HIV-only and COVID-19 only is carried out. The basic reproduction number is computed and used to prove local and global asymptotic stability of the sub-models’ disease-free and endemic equilibria. Using the fmincon function in the Optimization Toolbox of MATLAB, the model is fitted to real COVID-19 data set from South Africa. The impact of intervention measures, namely, COVID-19 and HIV prevention interventions and COVID-19 treatment are incorporated into the model using time-dependent controls. It is observed that HIV prevention measures can significantly reduce the burden of co-infections with COVID-19, while effective treatment of COVID-19 could reduce co-infections with opportunistic infections such as HIV/AIDS. In particular, the COVID-19 only prevention strategy averted about 10,500 new co-infection cases, with similar number also averted by the HIV-only prevention control. © 2022 The Author(s)

关键词： Basic reproduction number Co-infection COVID-19 HIV Optimal control

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Semantic Annotation of Arabic Web Documents using Deep Learning

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Procedia computer science 2018年 130卷 589-596页

作者： Saeed Albukhitan Ahmed Alnazer Tarek Helmy Information and Computer Science Department College of Computer Science & Engineering King Fahd University of Petroleum & Minerals Dhahran 31216 Mail Box 413 Saudi Arabia On leave from College of Engineering Department of Computers & Automatic Control Tanta University Egypt

The vision of Semantic Web is to have a Web of things instead of Web of documents in a form that can be processed by machines. This vision could be achieved on the existing Web using semantic annotation based on common and public ontologies. Due to exponential growth and the huge size of the Web sources, there is a need to have fast and automatic semantic annotation of Web documents. Arabic language received less attention in semantic Web research as compared to Latin languages especially in the field of semantic annotation. The aim of this paper is to investigate the feasibility of using word embeddings from deep learning algorithms for semantic annotation of Arabic Web documents. To evaluate the performance of the proposed framework, food, nutrition, and health ontologies were used to annotate some related Web documents. For a given set of Arabic documents and ontologies, the framework produces annotations of these documents using different output formats. The initial results show a promising performance which will support the research in the Semantic Web with respect to Arabic language. The proposed framework could be used for building semantic Web application and semantic search engines for Arabic Language.

关键词： Deep Learning Semantic Annotation Arabic Language Ontology

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