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International Conference on Pervasive computing and Applications (ICPCA)

作者： Chao Wang Xiangdong Wang Yueliang Qian Shouxun Lin Chinese Academy of Sciences Beijing China Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China

People with visual disabilities have difficulties in inputting Chinese into computer via conventional methods. Although some specialized devices and software can help Chinese blind users input Mandarin Braille into computers, translation of Mandarin Braille into Chinese is still a problem. In this paper, a new approach for translation of prevailing Mandarin Braille to Chinese character is proposed. By using characteristics of prevailing Mandarin Braille such as word segmentation-concatenation rule and tone information in the N-gram decoding process, the translating approach is able to achieve higher performance than current methods. Furthermore, under a paragraph and article translation scheme, language model adaptation is adopted by using combination of N-gram language model and cache-based language mode to improve translation performance. Experimental results show that the overall precision for the translation is 94.3%. If proper nouns are not considered, the precision can reach 95.1%.

关键词： Adaptation model Lattices Dictionaries Computers Algorithm design and analysis Accuracy Visualization

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A novel ant colony genetic hybrid algorithm

Journal of Software

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Journal of Software 2010年第11期5卷 1179-1186页

作者： Gao, Shang Zhang, Zaiyue Cao, Cungen School of Computer Science and Technology Jiangsu University of Science and Technology Zhenjiang 212003 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China

By use of the properties of ant colony algorithm and genetic algorithm, a novel ant colony genetic hybrid algorithm, whose framework of hybrid algorithm is genetic algorithm, is proposed to solve the traveling salesman problems. The selection operator is an artificial version of natural selection, and chromosomes with better length of tour have higher probabilities of being selected in the next generation. Based on the properties of pheromone in ant colony algorithm the ant colony crossover operation is given. Four mutation strategies are put forward using the characteristic of traveling salesman problems. The hybrid algorithm with 2-opt local search can effectively find better minimum beyond premature convergence. Ants choose several tours based on trail, and these tours will replace the worse solution. Compare with the simulated annealing algorithm, the standard genetic algorithm and the standard ant colony algorithm, all the 4 hybrid algorithms are proved effective. Especially the hybrid algorithm with strategy D is a simple and effective better algorithm than others. © 2010 ACADEMY PUBLISHER.

关键词： Genetic algorithms

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Socio-Natural Thought Semantic Link Network: A Method of Semantic Networking in the Cyber Physical Society

Socio-Natural Thought Semantic Link Network: A Method of Sem...

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International Conference on Advanced information Networking and Applications (AINA)

作者： Hai Zhuge Knowledge Grid Research Group Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China

ISBN: (纸本)9781424466955;9780769540184

Humans have been recognizing, establishing and making use of various relations consciously and unconsciously since the formation of human society. Waving and maintaining various relations accompany everyone's life. Humans' social behaviors create or emphasize relations. Various networks evolve with the development of society. Some relational networks gradually become independent of individuals' life during evolution so that they become a part of knowledge and culture sharable cross generations. The study of social relations trace back to the age of Laozi (576-BC), Confucius (551-479 BC), Thales (624 BC-546 BC) and Socrates (469 BC-399 BC). The formal definition of general relation traces to the invention of set theory in 1874. Humans have intelligence to observe and participate in social processes, to think, and to know the effect of establishing a relation. Humans can also actively select appropriate relations and persons according to requirement, situation and social rules. Machines are obviously limited in these abilities. Various graph-based models have been used to connect resources in the cyber space. Two issues are fundamental: (1) machines know little relation in human society and the nature, data structures in machines are for machines to process not for humans to read, so it is not realistic to expect machines to discover social and natural laws and resolve relevant issues without human instruction; and, (2) machines are hard to know the effect of establishing and making use of relations, and to explain computing result according to society and nature. The cause is that machines do not have any worldview. Connecting various networks and machines with nature, society, and even human minds can create a new world where individuals have semantic images that can enhance mutual understanding. The semantic images can be constructed by a Semantic Link Network SLN consisting of nodes with rich semantics, semantic links between nodes, and rules for reasoning, influe

关键词： Humans Societies Libraries Hypertext systems Spatial databases intelligent networks information processing Computers Set theory Machine intelligence

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Emotional talking agent: System and evaluation

Emotional talking agent: System and evaluation

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International Conference on Natural Computation (ICNC)

作者： Shen Zhang Jia Jia Yingjin Xu Lianhong Cai Key Laboratory of Pervasive Computing Ministry of Education State Key Laboratory on Intelligent Technology and Systems Tsinghua National Laboratory of Information Science and Technology Department of Computer Science and Technology Tsinghua University Beijing China

In this paper, we introduce a system that synthesizes the emotional audio-visual speech for a 3-D talking agent by adopting the PAD (Pleasure-Arousal-Dominance) emotional model. A GMM-based method is introduced to predict variation of acoustic features for emotional speech by PAD values, and a parametric framework of PAD-driven emotional facial expression synthesis is built. As the focus of this paper, we performed a series of perceptual evaluations to understand the reinforcement effect of vocal and facial expression of emotion, and investigated the usefulness and effectiveness of the emotional talking agent in human computer speech communications. Three questions are addressed: 1) To what extent do different interfaces affect human's comprehension of emotion? 2) How accurate the emotional information is conveyed by the talking agent? 3) Is the multimodal (audio-visual) interface helpful to human's emotion comprehension? An evaluation involving 19 participants was conducted to compare the effect of different interfaces (speech, mute agent and talking agent) on improving human's comprehension of emotion. The experimental results unveil the significant mutually reinforcing relationship between audio and video modality in emotion perception, and show that the users have a strong preference to multimodal interface for better comprehension of emotion. The results also prove the effectiveness of our PAD based emotional talking agent synthesis system.

关键词： Speech Visualization Humans Acoustics Speech synthesis Computers Feature extraction

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IEEE WIC ACM International Conference on Web Intelligence (WI)

作者： Xu Han Zhongzhi Shi Wenjia Niu Kunrong Chen Xinghua Yang Chinese Academy of Sciences Beijing China The Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China

With the rapid development of XML language which has good flexibility and interoperability, more and more log files of software running information are represented in XML format, especially for Web services. Fault diagnosis by analyzing semi-structured and XML like log files is becoming an important issue in this area. For most related learning methods, there is a basic assumption that training data should be in identical structure, which does not hold in many situations in practice. In order to learn from training data in different structures, we propose a similarity-based Bayesian learning approach for fault diagnosis in this paper. Our method is to first estimate similarity degrees of structural elements from different log files. Then the basic structure of combined Bayesian network (CBN) is constructed, and the similarity-based learning algorithm is used to compute probabilities in CBN. Finally, test log data can be classified into possible fault categories based on the generated CBN. Experimental results show our approach outperforms other learning approaches on those training datasets which have different structures.

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An Efficient Data Mining Framework on Hadoop using Java Persistence API

An Efficient Data Mining Framework on Hadoop using Java Pers...

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International Conference on Computer and information technology (CIT)

作者： Yang Lai Shi ZhongZhi Chinese Academy and Sciences Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China

Data indexing is common in data mining when working with high-dimensional, large-scale data sets. Hadoop, a cloud computing project using the MapReduce framework in Java, has become of significant interest in distributed data mining. A feasible distributed data indexing algorithm is proposed for Hadoop data mining, based on ZSCORE binning and inverted indexing and on the Hadoop SequenceFile format. A data mining framework on Hadoop using the Java Persistence API (JPA) and MySQL Cluster is proposed. The framework is elaborated in the implementation of a decision tree algorithm on Hadoop. We compare the data index-ing algorithm with Hadoop MapFile indexing, which performs a binary search, in a modest cloud environment. The results show the algorithm is more efficient than naïve MapFile indexing. We compare the JDBC and JPA implementations of the data mining framework. The performance shows the framework is efficient for data mining on Hadoop.

关键词： Data mining Indexing Distributed databases Pediatrics Clustering algorithms Decision trees

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Voting conditional random fields for multi-label image classification

Voting conditional random fields for multi-label image class...

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Congress on Image and Signal Processing, CISP

作者： Xishun Wang Xi Liu Zhiping Shi Zhongzhi Shi Hongjian Sui Chinese Academy of Sciences Beijing China The Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China

In our real world, there usually exist several different objects in one image, which brings intractable challenges to the traditional pattern recognition methods to classify the images. In this paper, we introduce a Conditional Random Fields (CRFs) model to deal with the Multi-label Image Classification problem. Considering the correlations of the objects, a second-order CRFs is constructed to capture the semantic associations between labels. Different initial feature weights are set to introduce the voting techniques for a better performance. We evaluate our methods on MSRC dataset and demonstrate high precision, recall and F 1 measure, showing that our method is competitive.

关键词： Visualization Training Image classification Correlation Buildings Image segmentation Semantics

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A parallel Hyper-Surface Classifier for high dimensional data

A parallel Hyper-Surface Classifier for high dimensional dat...

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International Symposium on Knowledge Acquisition and Modeling, KAM

作者： Qing He Qun Wang Chang-ying Du Xu-dong Ma Zhong-zhi Shi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China Chinese Academy of Sciences Beijing China

The enlarging volumes of data resources produced in real world makes classification of very large scale data a challenging task. Therefore, parallel process of very large high dimensional data is very important. Hyper-Surface Classification (HSC) is approved to be an effective and efficient classification algorithm to handle two and three dimensional data. Though HSC can be extended to deal with high dimensional data with dimension reduction or ensemble techniques, it is not trivial to tackle high dimensional data directly. Inspired by the decision tree idea, an improvement of HSC is proposed to deal with high dimensional data directly in this work. Furthermore, we parallelize the improved HSC algorithm (PHSC) to handle large scale high dimensional data based on MapReduce framework, which is a current and powerful parallel programming technique used in many fields. Experimental results show that the parallel improved HSC algorithm not only can directly deal with high dimensional data, but also can handle large scale data set. Furthermore, the evaluation criterions of scaleup, speedup and sizeup validate its efficiency.

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Risk analysis of system security based on evidence theory

Risk analysis of system security based on evidence theory

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2010 International Conference on Computer Design and Applications, ICCDA 2010

作者： Xu, Peida Xu, Jianling Deng, Yong Su, Xiaoyan Key Laboratory of Digital Agricultural Early-warning Technology Ministry of Agriculture of China Beijing China Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University China School of Electronics and Information Technology Shanghai Jiao Tong University Shanghai China Grain Economics Institute Nanjing University of Finance and Economics Nanjing China Hangzhou Key Lab. of E-Business and Information Security Hangzhou Normal University Hanzhou Zhejiang China Hangzhou Key Lab. of E-Business and Information Security Hangzhou Normal University Shanghai China

ISBN: (纸本)9781424471638

Risk evaluation is very important to the design and improvement of physical protection systems. In this paper, an evaluation method of multi-source information fusion is proposed based on the D-S evidence theory. In the proposed method, each individual component of the protection system in the simulated plane is modeled. Then, the threat report of each component according to the specific tactics is determined based on its real environment. Finally, the comprehensive threat distribution is obtained based on through the D-S evidence theory to combine multi-sources information. The proposed method can easily applied to the evaluation of the effectiveness of the protection system. We make the total threat of the protection system lowest through changes of the protection resources allocation. A numerical example is used to illustrate the efficiency of the proposed method. © 2010 IEEE.

关键词： information fusion

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Fast object detection using boosted co-occurrence histograms of oriented gradients

Fast object detection using boosted co-occurrence histograms...

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IEEE International Conference on Image Processing

作者： Haoyu Ren Cher-Keng Heng Wei Zheng Luhong Liang Xilin Chen Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China Panasonic Singapore Laboratories Private Limited Singapore

Co-occurrence histograms of oriented gradients (CoHOG) are powerful descriptors in object detection. In this paper, we propose to utilize a very large pool of CoHOG features with variable-location and variable-size blocks to capture salient characteristics of the object structure. We consider a CoHOG feature as a block with a special pattern described by the offset. A boosting algorithm is further introduced to select the appropriate locations and offsets to construct an efficient and accurate cascade classifier. Experimental results on public datasets show that our approach simultaneously achieves high accuracy and fast speed on both pedestrian detection and car detection tasks.

关键词： Classification algorithms Training Support vector machines Feature extraction Accuracy Boosting Object detection

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