An Information Criterion for Informative Gene Selection
It is important in bioinformatics research and applications to select or discover informative genes of a tumor from microarray data. However, most of the existing methods are based on models which assume that the gene expressions are normal distributed, which is often violated in practice. In this paper, we propose an information criterion for informative gene selection by ranking the genes with the Kullback-Leiber discrimination information of two probability distributions of the expression levels on the tumor and normal (or another type of tumor) samples. We use support vector machine (SVM) to construct the tumor diagnosis system using certain top informative genes. The experiments on two well-known data sets (colon data and leukemia data) show that the information criterion can make the tumor diagnosis system reach 94.4% and 100% correctness rate of diagnosis on these two datasets, respectively.

title: The Mahalanobis Distance Based Rival Penalized Competitive Learning Algorithm
abstract: The rival penalized competitive learning (RPCL) algorithm has been developed to make the clustering analysis on a set of sample data in which the number of clusters is unknown, and recent theoretical analysis shows that it can be constructed by minimizing a special kind of cost function on the sample data. In this paper, we use the Mahalanobis distance instead of the Euclidean distance in the cost function computation and propose the Mahalanobis distance based rival penalized competitive learning (MDRPCL) algorithm. It is demonstrated by the experiments that the MDRPCL algorithm can be successful to determine the number of elliptical clusters in a data set and lead to a good classification result.

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: 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: MFCC and SVM Based Recognition of Chinese Vowels
abstract: 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: 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: Smart u-Things and Ubiquitous Intelligence
abstract: Smart u-things are real things with attached, embedded or blended computers, networks, and/or some other devices such as sensors, actors, e-tags and so on, and they can sense, compute, communicate and take some adaptive actions/reactions/proactions according to their goals, situated contexts, users’ needs, etc. It is envisioned that smart u-thing will be everywhere eventually towards ubiquitous intelligence and smart world. One of the profound implications of such ubiquitous smart u-things is that various kinds and levels of intelligence will exist pervasively in real everyday objects, environments, systems and even ourselves, and possibly be extended from man-made to natural things. The ubicomp/percomp can be regarded, in a sense, as the computing of all these smart/intelligent u-things, which are the basic elements and components of the smart world. After clarifying the essential features and three categories of smart u-things, i.e., smart object, smart space and smart system, the talk is devoted to discuss possible challenges in smart u-things’ research in terms of real world complexity. The main intentions are to examine the possible hard issues to suggest some potential research lines; and to let researchers in this field coolhead and being aware of the hardness of these challenges in making real things truly smart.

title: Fast interval-valued statistical modeling of interconnect and effective capacitance
abstract: Correlated interval representations of range uncertainty offer an attractive solution to approximating computations on statistical quantities. The key idea is to use finite intervals to approximate the essential mass of a probability density function (pdf) as it moves through numerical operators; the resulting compact interval-valued solution can be easily interpreted as a statistical distribution and efficiently sampled. This paper first describes improved interval-valued algorithms for asymptotic wave evaluation (AWE)/passive reduced-order interconnect macromodeling algorithm (PRIMA) model order reduction for tree-structured interconnect circuits with correlated resistance, inductance, and capacitance (RLC) parameter variations. By moving to a much faster interval-valued linear solver based on path-tracing ideas, and making more optimal tradeoffs between interval- and scalar-valued computations, the delay statistics roughly 10/spl times/ faster than classical Monte Carlo (MC) simulation, with accuracy to within 5% can be extracted. This improved interval analysis strategy is further applied in order to build statistical effective capacitance (C/sub eff/) models for variational interconnect, and show how to extract statistics of C/sub eff/ over 100/spl times/ faster than classical MC simulation, with errors less than 4%.

title: A distributed Web document database and its supporting environment
abstract: 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, we 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: Design and implementation of a P2P shared Web browser using JXTA
abstract: The most shared applications use the client/server model in which, however a server is usually very complex and heavy since all of group managements are done by the server and sometimes becomes a communication bottleneck as all of date exchange among group members are mediated via it. To solve the above problems, our shared browser adopted a pure peer-to-peer (P2P) architecture without using any server A group member or a device called a peer dynamically finds other peers via distributed searching, and directly exchange data with other peers. It supports not only sharing a Web document in a peer group but also synchronously viewing the document and manipulating the browser with further support of some group users' awareness information like a user's moving a cursor, entering a new URL and clicking a hyperlink. It is implemented using JXTA protocols and Java programming language. To make the system applicable over the Internet across firewalls and NATs, the HTTP protocol can be used to transfer data via a pipe, a communication mechanism in JXTA.

title: A Multiplatform P2P System: its implementation and applications
abstract: Peer-to-peer (P2P) computing offers many attractive features, such as collaboration, self-organization, load balancing, availability, fault tolerance and anonymity. However, it also faces many serious challenges. In our previous work, we implemented a synchronous P2P collaboration platform called TOMSCOP. Based on the elementary peer group services offered by the JXTA general framework, TOMSCOP provides the extra four types of services: synchronous message transportation, peer room administration, peer communication support and application space management. By using the four services, different kinds of shared applications for various specific purposes can be relatively easily developed and associated collaborative cyber spaces or communities can be quickly built across the JXTA virtual network overlaid on top of the existing physical networks. However, the TOMSCOP was implemented only in Windows XP OS. In this paper, we extend our previous work and present the implementation of a Multi-Platform P2P System (MPPS). The proposed system operates very smoothly in UNIX Solaris 9 OS, LINUX Suse 9.1 OS, Mac OSX, and Windows XP. In the future study, we would like to evaluate the implemented P2P platform and compare its performance with other P2P systems.