Research on Query-by-Committee Method of Active Learning and Application
Active learning aims at reducing the number of training examples to be labeled by automatically processing the unlabeled examples, then selecting the most informative ones with respect to a given cost function for a human to label. The major problem is to find the best selection strategy function to quickly reach high classification accuracy. Query-by-Committee (QBC) method of active learning is less computation than other active learning approaches, but its classification accuracy can not achieve the same high as passive learning. In this paper, a new selection strategy for the QBC method is presented by combining Vote Entropy with Kullback-Leibler divergence. Experimental results show that the proposed algorithm is better than previous QBC approach in classification accuracy. It can reach the same accuracy as passive learning with few labeled training examples.

title: Evolving Model for Small-World Network Based on Benefit Choice
abstract: Based on reviewing the research progress of evolving model for small-world network, the defects of present studies were pointed out. Taking a square grid as the basis, an evolving model for small-world network based on benefit choice was built. This model is different from other papers in which limitation of vector' degree was considered. Then, the author proposed a simulation scheme and compared the network generated by simulation with a same scale random network. The results show that this network has small-world characteristic. Finally, several directions were given.

title: MBBNTree Classifier Algorithm Based on Active Learning from Unlabeled Samples
abstract: MBBNTree algorithm, which integrates the advantage of Markov blanket Bayesian networks (MBBN) and decision tree, would behave better performance than other Bayesian networks for classification. But the available training samples with actual classes are not enough for building MBBNTree classifier in practice. Active learning aims at reducing the number of training examples to be labeled by automatically processing the unlabeled examples, then selecting the most informative ones with respect to a given cost function for a human to label. In this paper, the MBBNTree classifier algorithm based on active learning would be presented to solve the problem of learning MBBNTree classifier from unlabeled samples. Experimental results show that the proposed algorithm can reach the same accuracy as passive learning with few labeled training examples.

title: Tibetan Language Continuous Speech Recognition Based on Dynamic Bayesian Network
abstract: Dynamic Bayesian Networks (DBN) area subset of the probabilistic graphical models (PGM) which include hidden Markov model (HMM) as a special case. One of the principle weaknesses of HMMs is the independence assumptions on the observed and hidden processes of speech. This paper proposed to use the DBN for Tibetan language continuous speech recognition.The proposed approach is based on structure learning paradigm in DBN framework. This approach has the advantage to guaranty that the resulting model represents speech with higher fidelity than HMM. The results of recognition experiments show that the proposed algorithm has better performance of recognition rate and noise suppression compared with HMM.

title: A Neighborhood-Based Clustering Algorithm
abstract: In this paper, we present a new clustering algorithm, NBC, i.e., Neighborhood Based Clustering, which discovers clusters based on the neighborhood characteristics of data. The NBC algorithm has the following advantages: (1) NBC is effective in discovering clusters of arbitrary shape and different densities; (2) NBC needs fewer input parameters than the existing clustering algorithms; (3) NBC can cluster both large and high-dimensional databases efficiently.

title: Recursive Algorithms for a Novel Identification Criterion
abstract: A new identification criterion is concerned for disturbed system with color noise in this paper. The cost function considers both the errors between the actual outputs and the estimation result and the difference of each estimation error. Under this performance function, a new recursive algorithm DSCN (Disturbed System with Color Noise) is proposed. It could reduce the influence of noise in system identification, further decrease the prediction error. Several simulation examples are given to illustrate the method's anti-disturbance performance.

title: 3-Coloring graphs embedded in surfaces
abstract: In this article, we show that there exists an integer k(Σ) ≥ 5 such that, if G is a graph embedded in a surface Σ without i-circuits, 4 ≤ i ≤ k(Σ), then G is 3-colorable.

title: A Working Model for Real-time Interactive Distance Education Support Systems
abstract: In Japan, most of the real time distance learning systems constructed over JGN (Japan Gigabit Network) are simple applications of video conference system equipped with high-quality audio/video transmission equipment. Such systems are not modeled to add distance educational support such as real time floor control, and are insufficient and inefficient to perform real time distance lecture or seminar when the number of sites get larger. This paper proposes a Working Model for distributed computer systems supporting real-time interactive distance lectures or seminars over JGN. As an application of the working model, functions for floor control and tele-presentation were discussed. The utility of the proposed working model was confirmed with an experimental system.

title: A conceptual model of public medical service system based-on cell phone mobile platform
abstract: In recent years, cell phones have played an increasingly important role in rapidly-developing global telecommunication services. At present, mobile business develops very fast. However, the development in other mobile service fields, such as public service, mobile medical service, etc, is still in its infant stage. Drawing on the experience of the ‘doctor workstation project’ which is cooperated by Renmin University of China and Norway Fredskorps Corporation, this paper discusses the research and implementation of the Doctor Workstation System based on cell phone mobile platform. From the practice of the Doctor Workstation System, the paper advances a conceptual model of public medical service system based-on cell phone mobile platform.