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Research and Development of Virtual Instruments System Based on Depth Camera

Research and Development of Virtual Instruments System Based...

The Third International Conference of Pioneering Computer Scientists, Engineers and Educators,ICPCSEE 2017(originally ICYCSEE)

作者： Xiao-li Xu Ming-hui Sun Xin-yue Sun Wei-yu Zhao Xiaoying Sun College of Computer Science and Technology Jilin University Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Jilin University College of Communication Engineering Jilin University

This paper takes advantage of the depth camera of somatosensory kinect and sensors to implement gesture recognition and design a virtual instrument system. As long as the user waves his arm without the help of other equipments, our system can automatically recognize the hand gesture and make suitable sound. In order to achieve depth camera's detection of hands movement, this paper introduce the depth imaging technology Light Coding and bone tracking technology to obtain the actual position information and hand movement information of the human body. Feet movement detection uses sensor technology, different stampede strength outputs different digital number after AD conversion so that the intensity can be controlled. A series of experiments show that the system has good fluency and practicality and increased the fun of playing instruments.

关键词： Virtual instrument Kinect Sensors Depth data processing Bone tracking

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Design and Implementation of Judge System for Old Man Fall Down

Design and Implementation of Judge System for Old Man Fall D...

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2017 International Conference on Mechanical,Electronic,Control and Automation engineering(MECAE 2017)

作者： Chao Sun Jindong Zhang Jiajia Lin Rui Song Xuan Zang Xiaohan Liu College of Software Jilin University College of Computer Science and Technology Jilin University Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Jilin University

ISBN: (纸本)9781510838451

This paper taking into account the universal use of Android phones, designs and implements judgments and notices the old man falling cell phone App. By calling the phones accelerometer, gyroscope collection campaigns after processing according to human body dynamics model to determine the specific state of the elderly, and get the specific latitude and longitude via GPS;Cell phone judge after the old man falls can send text messages to bound phone number in advance and inform the GPS to obtain location coordinates, after the fall in the elderly will be able to make the necessary relief in a timely manner.

关键词： APP Fall down Dynamic models GPS

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Reasoning and predicting POMDP planning complexity via covering numbers

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Frontiers of Computer Science 2016年第4期10卷 726-740页

作者： Zongzhang ZHANG Qiming FU Xiaofang ZHANG Quan LIU School of Computer Science and Technology Soochow University Suzhou 215000 China Collaborative Innovation Center of Novel Software Technology and Industrialization Nanjing 210000 China School of Electronic and Information Engineering Suzhou University of Science and Technology Suzhou 215000 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun 130012 China

Partially observable Markov decision processes （POMDPs） provide a rich mathematical framework for planning tasks in partially observable stochastic environments. The notion of the covering number, a metric of capturing the search space size of a POMDP planning problem, has been proposed as a complexity measure of approximate POMDP planning. Existing theoretical results are based on POMDPs with finite and discrete state spaces and measured in the l1- metric space. When considering heuristics, they are assumed to be always admissible. This paper extends the theoretical results on the covering numbers of different search spaces, including the newly defined space reachable under inadmissible heuristics, to the ln-metric spaces. We provide a simple but scalable algorithm for estimating covering numbers. Experimentally, we provide estimated covering numbers of the search spaces reachable by following different policies on several benchmark problems, and analyze their abilities to predict the runtime of POMDP planning algorithms.

关键词： POMDP planning complexity theory covering number search space

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Integrity constraint validation in dl-liter based ontology using rewriting 2nd

Integrity constraint validation in dl-liter based ontology u...

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2nd International Conference on Young Computer Scientists, Engineers and Educators, ICYCSEE 2016

作者： Cui, Xianji Ouyang, Dantong He, Jialiang College of Information and Communication Engineering Dalian Minzu University Dalian116600 China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University Changchun130012 China

ISBN: (纸本)9789811020971

With the rapid development of information technology, semantic web data present features of massiveness and complexity. As the data-centric science, social computing have great influence in collecting and analyzing semantic data. In our contribution, we propose an integrity constraint validation for DL-LiteR based ontology in view of data correctness issue in the progress of social computing applications. Firstly, at the basis of translations from integrity constraint axioms into a set of conjunctive queries, integrity constraint validation is converted into the conjunctive query answering over knowledge bases. Moreover, rewriting rules are used for reformulating the integrity constraint axioms using standard axioms. On this account, the integrity constraint validation can be reduced to the query evaluation over the ABox, and use query mechanisms in database management systems to optimize integrity constraint validation. Finally, the experimental result shows that the rewritingbased method greatly improves the efficiency of integrity constraint validation and is more appropriate to scalable data in the semantic web. © Springer Science+Business Media Singapore 2016.

关键词： Ontology

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A modified evidence theory model for data fusion

A modified evidence theory model for data fusion

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IEEE International Conference on Cloud Computing and Big Data Analysis (ICCCBDA)

作者： Jie Liu Dayou Liu Xinhua Wang Ni Ni Yungang Zhu Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University China College of Computer Science and Technology Jilin University Changchun China State Key Laboratory of Applied Optics Chinese Academy of Sciences Changchun China Bejing Entry-Exit Inspection and Quarantine Bureau Beijing China

ISBN: (纸本)9781509045006

To overcome the drawbacks of traditional convex evidence, in this paper we proposed a modified convex evidence theory model, we presented the modified combination function and use it to combine mass function of ordered propositions, we present the calculation of the parameters of the proposed combination function, and proposed a more accurate method to find the proposition which is most likely true. The theoretical analysis and experimental results demonstrate that the proposed method has higher accuracy than traditional convex evidence.

关键词： inference mechanisms sensor fusion uncertainty handling Soft computing Inference mechanisms Sensor fusion Data fusion Evidence Theory Convexity mass function Proposition data integration

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Integrating topic modeling with word embeddings by mixtures of vMFs 26

Integrating topic modeling with word embeddings by mixtures ...

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26th International Conference on computational Linguistics, COLING 2016

作者： Li, Ximing Chi, Jinjin Li, Changchun Ouyang, Jihong Fu, Bo College of Computer Science and Technology Jilin University China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education China College of Computer and Information Technology Liaoning Normal University China

ISBN: (纸本)9784879747020

Gaussian LDA integrates topic modeling with word embeddings by replacing discrete topic distribution over word types with multivariate Gaussian distribution on the embedding space. This can take semantic information of words into account. However, the Euclidean similarity used in Gaussian topics is not an optimal semantic measure for word embeddings. Acknowledgedly, the cosine similarity better describes the semantic relatedness between word embeddings. To employ the cosine measure and capture complex topic structure, we use von Mises-Fisher (vMF) mixture models to represent topics, and then develop a novel mix-vMF topic model (MvTM). Using public pre-trained word embeddings, we evaluate MvTM on three real-world data sets. Experimental results show that our model can discover more coherent topics than the state-of-the-art baseline models, and achieve competitive classification performance. © 1963-2018 ACL.

关键词： Embeddings

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Group sparse Bayesian learning for active surveillance on epidemic dynamics

arXiv

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arXiv 2017年

作者： Pei, Hongbin Yang, Bo Liu, Jiming Dong, Lei College of Computer Science and Technology Jilin University Changchun China Key Laboratory of Symbolic Computation Knowledge Engineering of Ministry of Education China Department of Computer Science Hong Kong Baptist University Hong Kong Institute of Remote Sensing and Geographical Information Systems Peking University Beijing China

Predicting epidemic dynamics is of great value in understanding and controlling diffusion processes, such as infectious disease spread and information propagation. This task is intractable, especially when surveillance resources are very limited. To address the challenge, we study the problem of active surveillance, i.e., how to identify a small portion of system components as sentinels to effect monitoring, such that the epidemic dynamics of an entire system can be readily predicted from the partial data collected by such sentinels. We propose a novel measure, the γ value, to identify the sentinels by modeling a sentinel network with row sparsity structure. We design a flexible group sparse Bayesian learning algorithm to mine the sentinel network suitable for handling both linear and non-linear dynamical systems by using the expectation maximization method and variational approximation. The efficacy of the proposed algorithm is theoretically analyzed and empirically validated using both synthetic and real-world data. Copyright © 2017, The Authors. All rights reserved.

关键词： Monitoring

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Author Correction: Multi-label Deep Learning for Gene Function Annotation in Cancer Pathways

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Scientific reports 2018年第1期8卷 8995页

作者： Renchu Guan Xu Wang Mary Qu Yang Yu Zhang Fengfeng Zhou Chen Yang Yanchun Liang Key Laboratory for Symbol Computation and Knowledge Engineering of National Education Ministry College of Computer Science and Technology Jilin University Changchun 130012 China. MidSouth Bioinformatics Center and Joint Bioinformatics Ph.D. Program of University of Arkansas at Little Rock and Univ. of Arkansas Medical Sciences Little Rock AR 72204 USA. Institute of Information Engineering Chinese Academy of Sciences School of Cyber Security University of Chinese Academy of Sciences Beijing 100093 China. College of Earth Sciences Jilin University Changchun 130061 China. yangc616@***. Key Laboratory for Symbol Computation and Knowledge Engineering of National Education Ministry College of Computer Science and Technology Jilin University Changchun 130012 China. ycliang@***. Zhuhai Laboratory of Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Zhuhai College of Jilin University Zhuhai 519041 China. ycliang@***.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.

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Pancreatic cancer biomarker detection using recursive feature elimination based on Support Vector Machine and large margin distribution machine

Pancreatic cancer biomarker detection using recursive featur...

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International Conference on Systems and Informatics (ICSAI)

作者： Yidan Lv Yan Wang Yongfei Tan Wei Du Keke Liu Hao Wang Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China Basic Medicine School Jilin University Changchun China Department of Hepatopancreatobiliary Surgery and Second Affiliated Hospital Harbin Medical University Harbin China

Pancreatic cancer acts as one of the leading causes of cancer-connective deaths. Its five-year overall survival rate being reported is about 7.7% from 2006 to 2012 by the National Cancer Institute. One of the main causes for its poor prognosis is because its non-typical symptoms make early diagnosis very challenging. Therefore, a predominant strategy for early accurate detection and prognostication on pancreatic cancer is vital to the whole course of comprehensive therapy. In this research, we proposed a method which combined Recursive Feature Elimination (RFE) method based on Support Vector Machine (SVM) and Large Margin Distribution Machine (LDM) to identify potential biomarkers for pancreatic cancer. In our experiments, we have strengthened the process of RFE to achieve better performance. The dataset GSE15471 we adopted are from GEO database with 39 pairs of pancreatic ductal carcinoma and adjacent control pancreatic tissues. Through experiments, a panel of twelve genes was identified as biomarkers in pancreatic cancer with 91.28% classification accuracy. The universality of the candidate genes was examined on another dataset GSE28735 and the classification accuracy was higher than 80%. In addition, by using the SVM, LDM and BP classifiers, we compared the ordered feature sets generated by our proposed method with T-test, SVM-RFE and LDM-RFE, and the results indicated our proposed method obtained higher average classification accuracy.

关键词： Cancer Support vector machines Feature extraction Tumors Training data Testing

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A local gradient based peak search algorithm for three-dimensional rotation electron diffraction image processing

A local gradient based peak search algorithm for three-dimen...

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International Conference on Systems and Informatics (ICSAI)

作者： Xinzheng Dong Yixuan Wang He Yin Zhuhai College of Jilin University Zhuhai Laboratory of Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Zhuhai China

ISBN: (纸本)9781509055227

Peak search for three-dimensional rotation electron diffraction image is almost the most important step in crystal structure determination. The difference of Gaussian method is the traditional approach for this task with the disadvantage that values of three tunable parameters need to be determined by users. To address this drawback, this paper presents a local gradient based peak search algorithm that needs only one tunable parameter. Experiments show that our proposed method is as effective as the difference of Gaussian method in peak detection task, but has obvious advantages in speed and convenience.

关键词： Diffraction Dogs Kernel Standards Software algorithms Shape

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