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Full-Text Articles in Physical Sciences and Mathematics
An Empirical Comparison Of Networks And Routing Strategies For Parallel Computation, Ronald I. Greenberg, Lee Guan
An Empirical Comparison Of Networks And Routing Strategies For Parallel Computation, Ronald I. Greenberg, Lee Guan
Computer Science: Faculty Publications and Other Works
This paper compares message routing capabilities of important networks proposed for general-purpose parallel computing. All the networks have been proven to have some type of universality property, i.e., an ability to simulate other networks of comparable cost with modest slowdown, using appropriate cost and communication models. But in this paper we seek an empirical comparison of communication capability under typical direct use rather than an analysis of worst-case results for simulating message traffic of another network.
On Integrating Existing Bibliographic Databases And Structured Databases, Ying Lu, Ee Peng Lim
On Integrating Existing Bibliographic Databases And Structured Databases, Ying Lu, Ee Peng Lim
Research Collection School Of Computing and Information Systems
It is widely accepted that future digital library applications have to be built upon different kinds of database servers to draw different forms of data from them. These data include bibliographic data, text data, multimedia data, and structured data. We address the problem of integrating existing bibliographic and structured databases which reside at different locations in the network. To integrate bibliographic data and structured data, we extended the well-known SQL model to represent bibliographic related attributes and queries. In particular, we have added a new data type to model attributes in the bibliographic database. We have also designed specialized predicates …
New Wavelet Based Art Network For Texture Classification, Jiazhao Wang, Golshah Naghdy, Philip O. Ogunbona
New Wavelet Based Art Network For Texture Classification, Jiazhao Wang, Golshah Naghdy, Philip O. Ogunbona
Faculty of Informatics - Papers (Archive)
A new method for texture classification is proposed. It is composed of two processing stages, namely, a low level evolutionary feature extraction based on Gabor wavelets and a high level neural network based pattern recognition. This resembles the process involved in the human visual system. Gabor wavelets are exploited as the feature extractor. A neural network, Fuzzy Adaptive Resonance Theory (Fuzzy ART), acts as the high level decision making and recognition system. Some modifications to the Fuzzy ART make it capable of simulating the post-natal and evolutionary development of the human visual system. The proposed system has been evaluated using …