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Exploring anti-community structure in networks with application to incompatibility of traditional Chinese medicine

PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS 2017年 486卷 31-43页

作者： Zhu, Jiajing Liu, Yongguo Zhang, Yun Liu, Xiaofeng Xiao, Yonghua Wang, Shidong Wu, Xindong [a]Knowledge and Data Engineering Laboratory of Chinese Medicine School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu 610054 PR China [b]School of Basic Medical Science Beijing University of Chinese Medicine Beijing 100029 PR China [c]Dongzhimen Hospital Beijing University of Chinese Medicine Beijing 100700 PR China [d]School of Computing and Informatics University of Louisiana at Lafayette Lafayette LA 70503 USA

Community structure is one of the most important properties in networks, in which a node shares its most connections with the others in the same community. On the contrary, the anti-community structure means the nodes in the same group have few or no connections with each other. In Traditional Chinese Medicine (TCM), the incompatibility problem of herbs is a challenge to the clinical medication safety. In this paper, we propose a new anti community detection algorithm, Random non-nEighboring nOde expansioN (REON), to find anti-communities in networks, in which a new evaluation criterion, anti-modularity, is designed to measure the quality of the obtained anti-community structure. In order to establish anti-communities in REON, we expand the node set by non-neighboring node expansion and regard the node set with the highest anti-modularity as an anti-community. Inspired by the phenomenon that the node with higher degree has greater contribution to the anti-modularity, an improved algorithm called REONI is developed by expanding node set by the non-neighboring node with the maximum degree, which greatly enhances the efficiency of REON. Experiments on synthetic and real-world networks demonstrate the superiority of the proposed algorithms over the existing methods. In addition, by applying REONI to the herb network, we find that it can discover incompatible herb combinations. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Complex networks Anti-community detection Traditional Chinese medicine Incompatibility of herbs

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An unmanned aerial vehicle pose estimation system based on SLAM

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IOP Conference Series: Materials Science and engineering 2019年第4期569卷

作者： Xinglei Dou Yuzhou Huo Yongchang Liu Xin Wang College of Software Engineering Jilin University Changchun Jilin 130012 China College of Computer Science and Technology Jilin University Changchun Jilin 130012 China Key Laboratory of Symbolic Computation and Knowledge Engineer of Ministry of Education Jilin University Changchun Jilin 130012 China

This paper presents an unmanned aerial vehicle (UAV) pose estimation system based on monocular simultaneous localization and mapping (SLAM) guided by the desired shot. The system enables UAV to automatically adjust the pose to achieve a shot close to the desired shot provided by the user. The SLAM module in the system includes ORB feature-based visual odometry and Levenberg-Marquardt method-based optimizer. To ensure the reliability of the camera pose estimation result, the bag of words model is used to select an image which has enough good matches with the desired shot. The experimental results prove that the system is valid and effective.

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RJMIM: A new feature selection method based on joint mutual information

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Revista de la Facultad de Ingenieria 2016年第4期31卷 59-69页

作者： Peng, Liwen Liu, YongGuo Knowledge and Data Engineering Laboratory of Chinese Medicine School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu610054 China

Feature selection based on information theory plays an important role in classification algorithm due to its computational efficiency and independent from classification method. It is widely used in many application areas like data mining, bioinformatics and machine learning. But drawbacks of these methods are the neglect of the feature interaction and overestimation of features significance due to the limitations of goal functions criterion. To address this problem, we proposed a new feature goal function RJMIM. The method employed joint mutual information and information interaction, which alleviates the shortcomings of overestimation of the feature significance as demonstrated both theoretically and experimentally. The experiments conducted to verify the performance of the proposed method, it compared with four well-known feature selection methods use three publically available datasets from UCI. The average classification accuracy and C4.5 classifier is used to assess the effectiveness of RJMIM method.

关键词： Classification (of information)

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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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Iris Recognition Based on Adaptive Gabor Filter 12th

Iris Recognition Based on Adaptive Gabor Filter

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12th Chinese Conference on Biometric Recognition, CCBR 2017

作者： Liu, Shuai Liu, Yuanning Zhu, Xiaodong Huo, Guang Cui, Jingwei Chen, Yihao Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University ChangchunJilin130012 China School of Software Jilin University ChangchunJilin130012 China School of Computer Science and Technology Jilin University ChangchunJilin130012 China Informatization Office Northeast Electric Power University Jilin132012 China

ISBN: (纸本)9783319699226

Aiming at the problem of multi-category iris recognition, there proposes a method of iris recognition algorithm based on adaptive Gabor filter. Use DE-PSO to adaptive optimize the Gabor filter parameters. DE-PSO is composed of particle swarm optimization and differential evolution algorithm. Use 16 groups of 2D-Gabor filters with different frequencies and directions to process iris images. According to the direction and frequency of maximum response amplitude, transform iris features into 512-bit binary feature encoding. Calculate the Hamming distance of feature code and compare with the classification threshold, determine iris the type of iris. Experiment on a variety of iris databases with multiple Gabor filter algorithms, the results showed that this algorithm has higher recognition rate, the ROC curve is closer to the coordinate axis and the robustness is better, compare with other Gabor filter algorithm. © 2017, Springer International Publishing AG.

关键词： Hamming distance

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Accuracy estimation of link-based similarity measures and its application

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Frontiers of Computer Science 2016年第1期10卷 113-123页

作者： Yinglong ZHANG Cuiping LI Chengwang XIE Hong CHEN School of Software East China Jiaotong University Nanchang 330045 China Key Laboratory of Data Engineering and Knowledge Engineering of Ministry of Education and Department of Computer Science Renmin University of China Beijing 100872 China Intelligent Optimization and Information Processing Laboratory East China Jiaotong University Nanchang 330013 China

Link-based similarity measures play a significant role in many graph based applications. Consequently, mea- suring node similarity in a graph is a fundamental problem of graph data mining. Personalized PageRank （PPR） and Sim- Rank （SR） have emerged as the most popular and influen- tial link-based similarity measures. Recently, a novel link- based similarity measure, penetrating rank （P-Rank）, which enriches SR, was proposed. In practice, PPR, SR and P-Rank scores are calculated by iterative methods. As the number of iterations increases so does the overhead of the calcula- tion. The ideal solution is that computing similarity within the minimum number of iterations is sufficient to guaran- tee a desired accuracy. However, the existing upper bounds are too coarse to be useful in general. Therefore, we focus on designing an accurate and tight upper bounds for PPR, SR, and P-Rank in the paper. Our upper bounds are designed based on the following intuition： the smaller the difference between the two consecutive iteration steps is, the smaller the difference between the theoretical and iterative similar- ity scores becomes. Furthermore, we demonstrate the effec- tiveness of our upper bounds in the scenario of top-k similar nodes queries, where our upper bounds helps accelerate the speed of the query. We also run a comprehensive set of exper- iments on real world data sets to verify the effectiveness and efficiency of our upper bounds.

关键词： personalized PageRank SimRank P-Rank up-per bound

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Author Correction: Multiple similarly effective solutions exist for biomedical feature selection and classification problems

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Scientific reports 2018年第1期8卷 838页

作者： Jiamei Liu Cheng Xu Weifeng Yang Yayun Shu Weiwei Zheng Fengfeng Zhou College of Software Jilin University Changchun Jilin 130012 China. College of Computer Science and Technology and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun Jilin 130012 China. College of Software Jilin University Changchun Jilin 130012 China. fengfengzhou@***. College of Computer Science and Technology and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun Jilin 130012 China. fengfengzhou@***.

A correction to this article has been published and is linked from the HTML version of this paper. The error has been fixed in the paper.

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Publisher Correction: Multiple similarly effective solutions exist for biomedical feature selection and classification problems

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Scientific reports 2018年第1期8卷 4218页

作者： Jiamei Liu Cheng Xu Weifeng Yang Yayun Shu Weiwei Zheng Fengfeng Zhou College of Software Jilin University Changchun Jilin 130012 China. College of Computer Science and Technology and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun Jilin 130012 China. College of Software Jilin University Changchun Jilin 130012 China. FengfengZhou@***. College of Computer Science and Technology and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun Jilin 130012 China. FengfengZhou@***.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.

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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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Task Coordination Organization Model and the Task Allocation Algorithm for Resource Contention of the Syncretic System

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Tsinghua Science and Technology 2016年第4期21卷 459-470页

作者： Danfeng Wu Guangping Zeng Di He Zhaopeng Qian Qingchuan Zhang School of Computer&Communication Engineering University of Science&Technology BeijingBeijing 100083China School of Software Liaoning Technical UniversityHuludao 125105China Beijing Key Laboratory of Knowledge Engineering for Materials Science Beijing 100083China Graduate Center City University of New YorkNew YorkNY 10016USA

At present, robot embedded systems have some common problems such as closure and poor dynamic evolution. Aiming at resolving this situation, our paper focuses on improvements to the robot embedded system and sets up a new robot system architecture, and we propose a syncretic mechanism of a robot and SoftMan （SM）. In the syncretic system, the structural organization of the SoftMan group and its modes are particularly important in establishing the task coordination mechanism. This paper, therefore, proposes a coordination organization model based on the SoftMan group, and studies in detail the process of task allocation for resource contention, which facilitates a rational allocation of system resources. During our research, we introduced Resource Requirement Length Algorithm （RRLA） to calculate the resource requirements of the task and a resource conformity degree allocation algorithm of Resource Conformity Degree Algorithm （RCDA） for resource contention. Finally, a comparative evaluation of RCDA with five other frequently used task allocation algorithms shows that RCDA has higher success and accuracy rates with good stability and reliability.

关键词： SoftMan robot syncretic system organization model task allocation game theory

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