9635823
Domain visualization for digital libraries
Domain visualization aims to reveal the most significant intellectual structure associated with a subject domain. This article illustrates how domain visualization enables novel ways of accessing scientific literature in digital libraries. The domain of computer graphics is visualized based on a citation analysis of articles appeared in the prestigious IEEE Computer Graphics and Applications over 18 years (1982-1999). The derived the high-dimensional domain structure is uncovered through the use of various visualization and animation techniques. Author co-citation maps open up new ways of visual information retrieval. Not only can users explore domain visualizations as a virtual landscape, but also invoke queries directly to a digital library. In this article, the domain visualization is linked to various citation-related information of scientific literature on the Web through NEC's ResearchIndex system.
15424500
Semantically modified diffusion limited aggregation for visualizing large-scale networks
Diffusion-limited aggregation (DLA) is a model of fractal growth. Computer models can simulate the fast aggregation of millions of particles. We propose a modified version of DLA, called semantically modified DLA (SM-DLA), for visualizing large-scale networks. SM-DLA introduces similarity measures between particles so that instead of attaching to the nearest particle in the aggregation, a new particle is stochastically directed to attach to particles that are similar to it. The results of our initial experiment with a co-citation network using SM-DLA are encouraging, suggesting that the algorithm has the potential as an alternative paradigm for visualizing large-scale networks. Further studies in this direction are recommended.
45076304
Spatial Semantic Virtual Worlds: The Structural Duality and Beyond
468820
Tracing knowledge diffusion
Knowledge diffusion is the adaptation of knowledge in a broad range of scientific and engineering research and development. Tracing knowledge diffusion between science and technology is a challenging issue due to the complexity of identifying emerging patterns in a diverse range of possible processes. In this article, we describe an approach that combines complex network theory, network visualization, and patent citation analysis in order to improve the means for the study of knowledge diffusion. In particular, we analyze patent citations in the field of tissue engineering. We emphasize that this is the beginning of a longer-term endeavor that aims to develop and deploy effective, progressive, and explanatory visualization techniques for us to capture the dynamics of the evolution of patent citation networks. The work has practical implications on resource allocation, strategic planning, and science policy.
46129433
Behavioural Patterns of Collaborative Writing with Hypertext - A State Transition Approach
This study investigates behavioural patterns of collaborative writing with a hypertext system by using a state-transition approach. State-transition models are empirically developed for capturing the dynamic nature of collaborative writing. Users were frequently engaged in tasks such as exploration, organization, and editing, whereas the use of collaborative support functions was transient in nature. The study shows that state-transition analysis is an important approach to task analysis, requirements engineering, and human-computer interaction studies. This study has produced some valuable experiences and lessons for researchers and practitioners in collaborative writing.
206109439
How did university departments interweave the Web: A study of connectivity and underlying factors
This paper presents two studies of the use of the WWW in Scottish universities and American land-grant universities. First, we investigated the relationship between the organisational profile of a university department in Scotland and its structural connectivity on the WWW. A Spearman rank order correlation analysis revealed a number of strong correlation relationships between structural connectivity measures and the organisational profile based on research assessment exercise ratings, teaching quality assessments, student‐staff ratios and funding levels. Linkage patterns from 13 Scottish academic sites to commercial sites in Britain and America highlighted the impact of culture and the appropriateness of information technologies on the acceptance of the WWW. The second study is a content survey of WWW-based education activities in American land-grant universities to investigate successful applications of these enabling techniques in education. The two studies together highlighted cultural, political and technological interactions in the use of the WWW. q 1998 Elsevier Science B.V. All rights reserved
195862034
Error bounded Pade approximation via bilinear conformal transformation
Since asymptotic waveform evaluation (AWE) was introduced, many interconnect model order reduction methods via Pade approximation have been proposed. Although the stability and precision of model reduction methods have been greatly improved, the following important question has not been answered: "What is the error bound in the time domain?". This problem is mainly caused by the "gap" between the frequency domain and the time domain, i.e., a good approximated transfer function in the frequency domain may not be a good approximation in the time domain. All of the existing methods approximate the transfer function directly in the frequency domain and hence can not provide error bounds in the time domain. In this paper, we present new moment matching methods which can provide guaranteed error bounds in the time domain. Our methods are based on the classic work by Teasdale (1953) which performs Pade approximation in a transformed domain by the bilinear conformal transformation s=(1-z)/(1+z).
14219803
A new method to measure the semantic similarity of GO terms
MOTIVATION
Although controlled biochemical or biological vocabularies, such as Gene Ontology (GO) (http://www.geneontology.org), address the need for consistent descriptions of genes in different data sources, there is still no effective method to determine the functional similarities of genes based on gene annotation information from heterogeneous data sources.


RESULTS
To address this critical need, we proposed a novel method to encode a GO term's semantics (biological meanings) into a numeric value by aggregating the semantic contributions of their ancestor terms (including this specific term) in the GO graph and, in turn, designed an algorithm to measure the semantic similarity of GO terms. Based on the semantic similarities of GO terms used for gene annotation, we designed a new algorithm to measure the functional similarity of genes. The results of using our algorithm to measure the functional similarities of genes in pathways retrieved from the saccharomyces genome database (SGD), and the outcomes of clustering these genes based on the similarity values obtained by our algorithm are shown to be consistent with human perspectives. Furthermore, we developed a set of online tools for gene similarity measurement and knowledge discovery.


AVAILABILITY
The online tools are available at: http://bioinformatics.clemson.edu/G-SESAME.


SUPPLEMENTARY INFORMATION
http://bioinformatics.clemson.edu/Publication/Supplement/gsp.htm.
6671949
Identification of critical genes in microarray experiments by a Neuro-Fuzzy approach
Gene expression profiling by microarray technology is usually difficult to interpret into a simpler pattern. One approach to resolve the complexity of gene expression profiles is the application of artificial neural networks (ANNs). A potential difficulty in this strategy, however, is that the non-linear nature of ANN makes it essentially a 'black-box' computation process. Addition of a fuzzy logic approach is useful because it can complement ANN by explicitly specifying membership function during computation. We employed a hybrid approach of neural network and fuzzy logic to further analyze a published microarray study of gene responses to eight bacteria in human macrophages. The original analysis by hierarchical clustering found common gene responses to all bacteria but did not address individual responses. Our method allowed exploration of the gene response of the host to individual bacterium. We implemented a two-layer, feed-forward neural network containing the principle of 'competitive learning' (i.e. 'winner-take-all'). The weights of the trained neural network were fed into a fuzzy logic inference system. A new measurement, called the impact rating (IR) was also introduced to explore the degree of importance of each gene. To assess the reliability of the IR value, a bootstrap re-sampling method was applied to the dataset and a confidence level for each IR was obtained. Our approach has successfully uncovered the unique features of host response to individual bacterium. Further, application of gene ontology (GO) annotation to the genes of high IR values in each response has suggested new biological pathways for individual host-pathogen interactions.
260704
An implementation of parallel dynamic load balancing for adaptive computing in VLSI device simulation
A new parallel semiconductor device simulation using the dynamic load balancing approach is presented. This semiconductor device simulation based on adaptive finite volume error estimation, and monotone iterative methods has been developed and implemented on a Linux-cluster with MPI library. Two different parallel versions of the algorithm to perform a complete device simulation are proposed. The first one is a dynamic parallel domain decomposition approach. The second version is a parallel current-voltage characteristic points simulation. The implementation shows that a well-designed load balancing simulation can reduce the execution time up to an order of magnitude. Compared with the measured data, numerical simulations on P-N diode, N-MOSFET, and DTMOS devices are presented to show the accuracy and efficiency of the method.
2154628
Distributed web-based simulation experiments for optimization
Abstract The web has grown tremendously over the past decade – with applications in education, marketing, financial services, and supply chain management. Web technology also has a significant impact on computer simulation. Most of the effort in web-based simulation is aimed at modeling, particularly at building simulation languages and at creating model libraries that can be assembled and executed over the web. This paper focuses on efficiency of simulation experimentation for optimization. We introduce a framework for combining the statistical efficiency of simulation optimization techniques with the effectiveness of parallel execution algorithms. In particular, a novel simulation sampling procedure, the Optimal Computing Budget Allocation (OCBA) algorithm, is implemented in a web-based environment for low-cost parallel and distributed simulation experimentation. A prototype implementation with some experimental results is presented to show the viability of web-enabled simulation environments.