MFCC and SVM Based Recognition of Chinese Vowels
The recognition of vowels in Chinese speech is very important for Chinese speech recognition and understanding. However, it is rather difficult and there has been no efficient method to solve it yet. In this paper, we propose a new approach to the recognition of Chinese vowels via the support vector machine (SVM) with the Mel-Frequency Cepstral Coefficients (MFCCs) as the vowel’s features. It is shown by the experiments that this method can reach a high recognition accuracy on the given vowels database and outperform the SVM with the Linear Prediction Coding Cepstral (LPCC) coefficients as the vowel’s features.

title: Further Results on the Asymptotic Memory Capacity of the Generalized Hopfield Network
abstract: This paper presents a further theoretical analysis on the asymptotic memory capacity of the generalized Hopfield network (GHN) under the perceptron learning scheme. It has been proved that the asymptotic memory capacity of the GHN is exactly 2(n− 1), where n is the number of neurons in the network. That is, the GHN of n neurons can store 2(n− 1) bipolar sample patterns as its stable states when n is large, which has significantly improved the existing results on the asymptotic memory capacity of the GHN.

title: A Neural Network Approach to Real-Time Pattern Recognition
abstract: This paper presents a new neural network approach to real-time pattern recognition on a given set of binary (or bipolar) sample patterns. The perceptive neuron of a binary pattern is defined and constructed as a binary neuron with a neighborhood perceptive field. Letting its hidden units be the respective perceptive neurons of the patterns, a three-layer forward neural network is constructed to recognize these patterns with minimum error probability in a noisy environment. The theoretical and simulation analyses show that the network is effective for pattern recognition and can be under strict real-time constraints.

title: Learning to cluster web search results
abstract: Organizing Web search results into clusters facilitates users' quick browsing through search results. Traditional clustering techniques are inadequate since they don't generate clusters with highly readable names. In this paper, we reformalize the clustering problem as a salient phrase ranking problem. Given a query and the ranked list of documents (typically a list of titles and snippets) returned by a certain Web search engine, our method first extracts and ranks salient phrases as candidate cluster names, based on a regression model learned from human labeled training data. The documents are assigned to relevant salient phrases to form candidate clusters, and the final clusters are generated by merging these candidate clusters. Experimental results verify our method's feasibility and effectiveness.

title: The Stability of the Generalized Hopfield Networks in Randomly Asynchronous Mode
abstract: We present a study on the stability of the generalized Hopfield network in randomly asynchronous mode. First, the stability is investigated from the state space of the network. We introduce a concept of hole and define two kinds of stability in randomly asynchronous mode. By mathematical inductive method, we have proved that a generalized Hopfield network with non negative weights is strictly stable, that is, the network evolves to a simple hole-stable state with probability one when it starts at any initial state. For the general case, we made the simulation experiments on the networks with the number of neurons from 5 to 10. The empirical results have shown that almost any generalized Hopfield network with simple holes is strictly stable.

title: The asymptotic memory capacity of the generalized Hopfield network
abstract: This paper presents a theoretical analysis on the asymptotic memory capacity of the generalized Hopfield network. The perceptron learning scheme is proposed to store sample patterns as the stable states in a generalized Hopfield network. We have obtained that (n-1) and 2n are a lower and an upper bound of the asymptotic memory capacity of the network of n neurons, respectively, which shows that the generalized Hopfield network can store the larger number of sample patterns than Hopfield network.

title: Ubisafe Computing: Vision and Challenges (I)
abstract: In recent years, a variety of new computing paradigms have been proposed for various purposes. It is true that many of them intend to and really can gratify some of the people sometime, somewhere; a few of them can even gratify some of the people anytime, anywhere. However, at present, none of the computing paradigms intend to gratify all the people anytime, anywhere. With the rapid advance of information technology and the spread of information services, the IT disparity in age, social standing, and race of the people has been expanding and has become a critical social problem of the 21st century. Thus, we have a fundamental question: Can we construct, in a unified methodology, a computing environment that can gratify all the people in all situations, all places and all the time? We propose a novel and inclusive computing paradigm, named ubisafe computing, for studying and providing possible solutions to the above problem. The ultimate goal of ubisafe computing is to build a computing environment in which all people and organizations can benefit from ubiquitous services anytime anywhere with assured and desired satisfaction without worrying or thinking about safety. That is, the ubisafe computing vision emphasizes two basic aspects: ubiquitous safety and ubiquitous satisfaction to all people in all situations. This paper presents the motivations for the ubisafe computing vision but focuses on one basic aspect of ubiquitous safety that covers reliability, security, privacy, persistency, trust, risk, out of control, and other watchfulness while considering novel, essential ubicomp or percomp features of unobtrusive computers, diverse users/people and life-like systems.

title: The specification and implementation of a virtual university software system
abstract: Distance learning is one of the interesting research topics of distributed computing. This paper discusses a joint research project between the University of Aizu in Japan and Tamkang University in Taiwan. A software system supporting virtual university operations is proposed. The software architecture is designed based on three criteria of virtual university operations: administration, awareness and assessment. Specifications of each tools in the system are proposed, with some implementation details and solutions being discussed. We also point out some interesting research directions in the realization of a virtual university.

title: Simulation Study of AODV Performance over IEEE 802.15.4 MAC in WSN with Mobile Sinks
abstract: Mobility has been incorporated into wireless sensor networks in recent years in order to improve energy efficiency and network coverage. In particular, at the cost of increased message delivery delay, the energy conservation can be achieved by limiting the hop count between the communicating sensor-sink pair. In this paper we allow multihop routing between one sensor and mobile sinks, and consider the delay*energy metric, which is a compound metric to evaluate the performance of diverse data collection schemes. Through extensive simulation experiments of AODV performance over IEEE 802.15.4 MAC with clustered wireless sensor network setting, we investigate the fundamental problems of AODV without information of 802.15.4 MAC, and analyze the influence of incorporating multiple sinks.

title: The design and implementation of a distributed Web document database
abstract: Distance learning has become a very important mechanism for virtual university operation. In order to realize such an operation smoothly, it is necessary to consider distance learning from three perspectives: administration, awareness, and assessment. We are currently implementing a virtual university environment according to these guidelines. In this paper, we propose a new Web documentation database as a supporting environment of the Multimedia Micro-University project. The design of this database facilitates a Web documentation development paradigm that we have proposed earlier. From a script description, to its implementation as well as testing records, the database and its interface allow the user to design Web documents as virtual courses to be used in a Web-savvy virtual library. The database supports object reuse and sharing, as well as referential integrity and concurrence. In order to allow real-time course demonstration, i.e. also propose a simple course distribution mechanism, which allows the pre-broadcast of course materials. The System is implemented as a three-tier architecture which runs under MS Windows and other platforms.

title: A method for repairing the inconsistency of fuzzy preference relations
abstract: This paper investigates the inconsistency problems of preference information about alternatives expressed as a fuzzy preference relation by a decision maker. An analysis method is presented to identify the inconsistency and weak transitivity of a fuzzy preference relation and to repair its inconsistency to reach weak transitivity. First, several definitions are given on additive consistency, inconsistency and weak transitivity of a fuzzy preference relation. Next, two methods derived from graph theory are presented to judge whether a fuzzy preference relation has weak transitivity or not. Then, an algorithm is developed to repair an inconsistent fuzzy preference relation and to make it become one with weak transitivity, via a synthesis matrix which reflects the relationship between the fuzzy preference relation with additive consistency and the initial one given by a decision maker. A convergence theorem is also given for the algorithm. Lastly, two numerical examples are shown to illustrate the proposed method.