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12th Chinese Conference on Computer Supported Cooperative Work and Social Computing, ChineseCSCW 2017

作者： Lin, Dazhen Li, Lingxiao Cao, Donglin Li, Shaozi Cognitive Science Department Xiamen University Xiamen China Fujian Key Laboratory of Brain-inspired Computing Technique and Applications Xiamen University Xiamen China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou China

ISBN: (纸本)9781450353526

We address the challenge of multi-modal sentiment analysis. To solve the problem of the sentiment correlations among different modalities, we propose a Multi-modal Correlation Model (MCM). In contrast to other methods, MCM considers the hierarchical sentiment correlations among modalities. Specifically, a probabilistic graphical model (PGM) is subsequently built upon the proposed MCM model, which considers the correlations and simultaneously preserves the classification ability of each modality. In order to compute the posterior probabilities of sentiments in PGM, we optimize the model by Maximum Likelihood Estimation. Experimental results show that MCM achieves accuracy of 84.2% and beats existing multi-modal methods with 1.2-4% improvement. Results demonstrate: 1) the sentiment correlations among modalities are hierarchical;2) the importance of the correlations for multi-modal sentiment analysis. © 2017 Association for Computing Machinery.

关键词： Sentiment analysis

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An interactive system for eficient 3D furniture arrangement

An interactive system for eficient 3D furniture arrangement

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2017 Computer Graphics International Conference, CGI 2017

作者： Yan, Meng Chen, Xuejin Zhou, Jie CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Dept 6 P.O. Box 4 Hefei Anhui230026 China

ISBN: (纸本)9781450352284

We present an interactive example-based system for non-expert users to generate 3D indoor scenes intuitively. From a set of examples of an interior scene, we extract furniture layout constraints including pairwise and group relationships, ergonomic factors and user habits. Instead of inserting a single furniture object to a visual pleasing and functional position independently, we take advantages of manipulating a group of functionality-related furniture objects for smart editing. To deal with the arrangement problem which requires jointly optimizing a variety of functional and visual criteria, we introduce an efficient two-step pipeline consisting of rough arrangement and layout refinement. In the rough arrangement step, furniture objects are roughly placed according to pairwise relationships for accelerating the further optimization process. In the layout refinement step, we optimize the rough furniture layout to a semantical and functional layout considering spatial relationships, and ergonomic factors and avoiding collisions. User interactions are also allowed to move a specific object or a structural group while our system automatically refines the entire layout. The experimental results demonstrate that our system for scene generation measurably increases the visual quality and time efficiency compared with the completely manual scene editing or modeling. © 2017 ACM.

关键词： Virtual reality

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Unmanned Aerial Vehicle Path Planning Based on Improved Intelligent Water Drop Algorithm

Unmanned Aerial Vehicle Path Planning Based on Improved Inte...

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International Conference on Instrumentation, Measurement, Computer, Communication and control (IMCCC)

作者： Xixia Sun Su Pan Chao Cai Yanfang Chen Jie Chen Key Laboratory of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications Ministry of Education Nanjing China State Key Laboratory for Multispectral Information Processing Technologies School of Automation Huazhong University of Science and Technology Wuhan China Tianjin Zhong Wei Aerospace Data System Technology Co.Ltd Tianjin China

ISBN: (数字)9781538682463

ISBN: (纸本)9781538682470

The unmanned aerial vehicle (UAV) has been a research focus in recent years and the path planner is a key element of the UAV autonomous control module. In this paper, a novel UAV path planning method based on intelligent water drop algorithm is proposed. Firstly, the mathematical model of the UAV path planning problem is presented. Secondly, an improved intelligent water drop algorithm is proposed to solve the UAV path planning model. In the proposed algorithm, a novel path construction mechanism is proposed and an adaptive global soli update mechanism is developed. The proposed algorithm can overcome some shortages of the original ITD algorithm, such as slow search speed, easily falling into local minima, and so on. Experimental results demonstrate that the proposed planner outperforms the original ITD planner in a statistical manner.

关键词： Path planning Heuristic algorithms Optimization Unmanned aerial vehicles Mathematical model Soil Classification algorithms

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Mathematical model of brain tumour growth with drug resistance

arXiv

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arXiv 2020年

作者： Trobia, José Tian, Kun Batista, Antonio M. Grebogi, Celso Ren, Hai-Peng Santos, Moises S. Protachevicz, Paulo R. Borges, Fernando S. Szezech, José D. Viana, Ricardo L. Caldas, Iberê L. Iarosz, Kelly C. Department of Mathematics and Statistics State University of Ponta Grossa Ponta GrossaPR84030-900 Brazil Graduate in Science Program - Physics State University of Ponta Grossa Ponta GrossaPR84030-900 Brazil Shaanxi Key Lab of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’anPR710048 China Institute of Physics University of São Paulo São PauloSP05508-900 Brazil Institute for Complex Systems and Mathematical Biology University of Aberdeen AberdeenAB24 3UE United Kingdom Xi’an Technological University Xi’anPR710021 China Center for Mathematics Computation and Cognition Federal University of ABC São Bernardo do CampoSP09606-045 Brazil Department of Physics Federal University of Paraná CuritibaPR80060-000 Brazil Faculdade de Telêmaco Borba FATEB Telêmaco BorbaPR84266-010 Brazil

Brain tumours are masses of abnormal cells that can grow in an uncontrolled way in the brain. There are different types of malignant brain tumours. Gliomas are malignant brain tumours that grow from glial cells and are identified as astrocytoma, oligodendroglioma, and ependymoma. We study a mathematical model that describes glia-neuron interaction, glioma, and chemotherapeutic agent. In this work, we consider drug sensitive and resistant glioma cells. We show that continuous and pulsed chemotherapy can kill glioma cells with a minimal loss of neurons. © 2020, CC BY.

关键词： Tumors

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Research on Multi-Model of Computer Organization for system Capability

Research on Multi-Model of Computer Organization for System ...

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2018 3rd International Conference on Education,Sports,Arts and Management Engineering(ICESAME 2018)

作者： Li HUANG Wei HU Kai ZHANG Jianhua LU College of Computer Science and Technology Wuhan University of Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology National Computer Experimental Teaching Demonstration Center (Wuhan University of Science and Technology)

This paper studies the lack of systematic, teaching content and the obsolete teaching mode of the principle of computer composition in most colleges and universities in China. Proposed system-oriented teaching methods and modes. This paper expounds the teaching goal of cultivating system competence based on classroom teaching system, supported by gradient experiment teaching, combining MOOC platform and SPOC teaching mode, and taking the second class as the teaching implementation system expanded.

关键词： system capability multiple teaching mode computer organization

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Dependency-Enhanced Reordering Model for Chinese-English SMT 35

Dependency-Enhanced Reordering Model for Chinese-English SMT

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第35届中国控制会议

作者： WANG Miaomiao XIE Guo DU Jinhua Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing

ISBN: (纸本)9781509009107

This paper proposes a dependency-enhanced pre-reordering method for Chinese-English statistical machine translation(SMT).Firstly,two kinds of dependency structure-based rules are extracted based on the source-side dependency tree and corresponding word alignments between the source-side and the target-side *** a maximum entropy classifier is used to calculate the orientation probability in terms of swap or monotone between two *** a result,a reordering rule set is *** different ways are proposed to filter out the rule ***,the dependency parsing trees of the training data,development set and the test set are traversed,and if the syntactic sub-tree structure matches the rules in the rule set,the word orders will be ***,a reordered source-side sentence is generated and then fed into an SMT system for *** conducted on NIST Chinese-English MT data sets show that the proposed method significantly improves translation performance by 0.46 BLEU compared to the baseline system.

关键词： Statistical Machine Translation Word Alignment Dependency Syntactic Parsing

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The Identification of Stochastic Time-varying Parameters for Nonlinear system 35

The Identification of Stochastic Time-varying Parameters for...

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第35届中国控制会议

作者： XIE Guo ZHANG Dan QIAN Fucai Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing

ISBN: (纸本)9781509009107

In this paper, a method for a sort of nonlinear system identification with stochastic time-varying parameter is investigated. This kind of nonlinear systems is referring to the system where probability density functions(PDFs) of the parameters are known. This parameter identification and states estimation method is realized based on expectation maximization(EM) algorithm and particle filter. Firstly, parameter particles are generated randomly according to the PDF of parameter. Secondly, the particle filter is employed to estimate system states corresponding to each group of the parameters, and the weight of each group parameters is calculated according to the Bayesian theory. Then the new iteration of parameter is obtained by adopting the expectation maximization algorithm. Lastly, the real parameters are obtained along with system operation. Numerical illustrations are presented to exhibit the effectiveness of the method proposed herein, and the performance of the method is examined.

关键词： Stochastic time-varying parameter Parameter identification Nonlinear system Expectation Maximization algorithm(EM)

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An attention-based word-level interaction model: Relation detection for knowledge base question answering

arXiv

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arXiv 2018年

作者： Zhang, Hongzhi Xu, Guandong Liang, Xiao Huang, Tinglei Fu, Kun CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System Institute of Electronics Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China School of Software and Advanced Analytics University of Technology Sydney Australia

Relation detection plays a crucial role in Knowledge Base Question Answering (KBQA) because of the high variance of relation expression in the question. Traditional deep learning methods follow an encoding-comparing paradigm, where the question and the candidate relation are represented as vectors to compare their semantic similarity. Max- or average- pooling operation, which compresses the sequence of words into fixed-dimensional vectors, becomes the bottleneck of information. In this paper, we propose to learn attention-based word-level interactions between questions and relations to alleviate the bottleneck issue. Similar to the traditional models, the question and relation are firstly represented as sequences of vectors. Then, instead of merging the sequence into a single vector with pooling operation, soft alignments between words from the question and the relation are learned. The aligned words are subsequently compared with the convolutional neural network (CNN) and the comparison results are merged finally. Through performing the comparison on low-level representations, the attention-based word-level interaction model (ABWIM) relieves the information loss issue caused by merging the sequence into a fixed-dimensional vector before the comparison. The experimental results of relation detection on both SimpleQuestions and WebQuestions datasets show that ABWIM achieves state-of-the-art accuracy, demonstrating its effectiveness. Copyright © 2018, The Authors. All rights reserved.

关键词： Knowledge based systems

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DEEP SEMANTIC SEGMENTATION OF AERIAL IMAGERY BASED ON MULTI-MODAL DATA

DEEP SEMANTIC SEGMENTATION OF AERIAL IMAGERY BASED ON MULTI-...

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IEEE International Geoscience and Remote Sensing Symposium

作者： Kaiqiang Chen Kun Fu Xian Sun Michael Weinmann Stefan Hinz Boris Jutzi Martin Weinmann Key Laboratory of Spatial Information Processing and Application System Technology Chinese Academy of Sciences Beijing P.R. China Institute of Computer Science II University of Bonn Bonn Germany Institute of Photogrammetry and Remote Sensing Karlsruhe Institute of Technology Karlsruhe Germany

In this paper, we focus on the use of multi-modal data to achieve a semantic segmentation of aerial imagery. Thereby, the multi-modal data is composed of a true orthophoto, the Digital Surface Model (DSM) and further representations derived from these. Taking data of different modalities separately and in combination as input to a Residual Shuffling Convolutional Neural Network (RSCNN), we analyze their value for the classification task given with a benchmark dataset. The derived results reveal an improvement if different types of geometric features extracted from the DSM are used in addition to the true orthophoto.

关键词： Semantics Image segmentation Feature extraction Labeling Vegetation mapping Buildings Benchmark testing

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Indirect Measurement Method for High Earth Orbit Satellite Autonomous Navigation Based on Ultraviolet Sensor

Indirect Measurement Method for High Earth Orbit Satellite A...

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第36届中国控制会议

作者： YANG Wen-bo LI Shao-yuan Shanghai Polytechnic University Department of Automation Shanghai Jiao Tong Universityand Key Laboratory of System Control and Information ProcessingMinistry of Education

An autonomous navigation method based on UV sensor（ultraviolet sensor,UV sensor） for high earth orbit（HEO）satellites is proposed by considering the problem of accuracy decrease caused by the constant deviation in UV sensor imaging ***,the constant deviation is looked on as state variable of the navigation system to realize real-time estimate and ***,partial state information is deemed as indirect measurement,which makes design of the filter simplified and the systematic computation ***,simulation results are provided,which illustrate that the proposed navigation method can acquire good performance when applied to HEO satellite navigation system.

关键词： Autonomous navigation UV sensor Indirect measurement Deviation compensation

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