A general purpose virtual collaboration room
The general purpose virtual collaboration room (VCR) is an Internet based desktop groupware system that enables a group of remote individuals to flexibly and naturally conduct their collaborative teaching/learning/working without constraints on collaboration types, working styles, group scales, and system platforms. To cope with the complexity, a room metaphor, i.e., emulating a physical room and objects in it, is used as a framework of the system. System implementation becomes no more complex than the case of using one object by identifying associated objects in communication messages between a room server and clients. The VCR provides rich and effective support of awareness of the user, object, space, and their mutual relations. With the use of Java applets for system implementations, users can enter and use a VCR from any standard Java enabled Web browser.

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: Implementation of a Pure P2p Collaboration Multiplatform and its 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 seri...

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: Towards global routing with RLC crosstalk constraints
abstract: Conventional global routing minimizes total wire length and congestion. Experiments using large industrial benchmark circuits show that up to 24% of nets in such routing solutions may have RLC crosstalk violations at 3GHz clock. We develop an extremely efficient length-scaled Keff (LSK) model that has a high fidelity for long-range RLC crosstalk. We formulate an extended global routing problem (denoted as GSINO) to consider simultaneous shield insertion and net ordering with RLC crosstalk constraints, then propose an effective three-phase GSINO algorithm. The GSINO algorithm completely eliminates the RLC crosstalk violations, and has small area and wire length overhead compared to conventional routing.

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

title: An Optimal Node Selection Scheme in Multi-hop Wireless Network
abstract: In this paper, a cooperative wireless multi-hop network is considered, cooperative diversity can be realized by allowing nodes close proximity to cooperate in transmission. In order to group receiver nodes into a cluster, it is necessary to select appropriate nodes. We introduce an optimal node selection algorithm based on MIMO antenna selection, this algorithm, combining with cooperative transmission strategy, gives an optimal node selection algorithm using convex optimization theory. Theoretical analysis and simulation indicate that this scheme can give good performance of maximizing the channel capacity through optimal node selection.

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.