A Hybrid Neural Network of Addressable and Content-Addressable Memory
We investigate the memory structure and retrieval of the brain and propose a hybrid neural network of addressable and content-addressable memory which is a special database model and can memorize and retrieve any piece of information (a binary pattern) both addressably and content-addressably. The architecture of this hybrid neural network is hierarchical and takes the form of a tree of slabs which consist of binary neurons with the same array. Simplex memory neural networks are considered as the slabs of basic memory units, being distributed on the terminal vertexes of the tree. It is shown by theoretical analysis that the hybrid neural network is able to be constructed with Hebbian and competitive learning rules, and some other important characteristics of its learning and memory behavior are also consistent with those of the brain. Moreover, we demonstrate the hybrid neural network on a set of ten binary numeral patters

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: 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: 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: 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: A P2P Ubiquitous System for Testing Network Programs
abstract: This paper presents design and implementation of a peer-to-peer (P2P) ubiquitous system for assisting a programmer to efficiently test network programs in their development process by using multiple computers simultaneously. This system is implemented using the TOMSCOP (Technology Of Multi-user Synchronous COllaboration Platform). It is a synchronous P2P collaboration platform built atop the JXTA technology. JXTA is a set of protocols for developing P2P shared applications, and enables peers to find each other, form groups and exchange messages across firewalls and NATs. This system has the following three main features. Firstly, it enables the program source files being shared among peers. Secondly, a user is able to simultaneously compile, execute and stop network programs of all peers in a same group by simple operations on the system GUI. Lastly, due to using Java and JXTA technology, the system can run on any platform.

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: 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: Energy-Efficient Localized Topology Control Algorithms in IEEE 802.15.4-Based Sensor Networks
abstract: Sensor networks have emerged as a promising technology with various applications, where power efficiency is one of the critical requirements. The recent IEEE 802.15.4 standard offers a promising platform for wireless sensor networks. Since each node can act as a coordinator or a device in the IEEE 802.15.4 standard, 802.15.4-based sensor networks have various possible network topologies. To reduce power consumption, in this paper, we try to construct network topologies with a small number of coordinators while still maintaining network connectivity. By reducing the number of coordinators, the average duty cycle is reduced and the battery life is prolonged. Three topology control algorithms are proposed in this paper. Self-pruning (SP) is the simplest one with O(1) running time and provides the shortest path to the sink node. Ordinal pruning (OP) can significantly improve SP in terms of power saving with O(n) running time. Layered pruning (LP) is a trade off between the first two pruning algorithms with O(radicn) running time and has a slightly higher power consumption than OP. Furthermore, all three algorithms are independent of the physical radio propagation characteristics. Extensive simulations have been performed to verify the effectiveness of the proposed topology control schemes

title: A Dangerous Location Aware System for Assisting Kids Safety Care
abstract: This system focuses on a location-aware computing application and environment which provide preemptive information on dangerous locations in the kid's surroundings; i.e., the system alerts a kid on the move of the possible dangers whenever he/she is near accident prone areas. Using satellite-based GPS position sensing, this system can gradually learn and remember about the different locations that a kid routinely visits and/or passes by in his daily life, based on space-oriented contexts. The full set of system functionalities, including the map display, requires a graphical user interface. This location based services (LBSs) can compute the serious situations and alert kids to avoid dangerous situations. Our research can simulate the virtual environment as hyperspaces for kids safety care