Web applications exhibit dynamic behaviour through such features as animation, rapidly changing presentations, and interactive forms. The growing complexity of web applications requires a rigorous modelling approach c...
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Automated analysis of object-oriented design models can provide insight into the quality of a given software design. Data obtained from automated analysis, however, is often too complex to be easily understood by a de...
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It has been an important task of discovering frequent fragments as particular patterns from large sequence databases generated from a variety of applications. In general, the patterns to be discovered may partially an...
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It has been an important task of discovering frequent fragments as particular patterns from large sequence databases generated from a variety of applications. In general, the patterns to be discovered may partially and asynchronously exist in sequences, and even contain gaps. In addition, it is necessary to collect the information regarding the locations and frequencies of the patterns. How to enumerate candidate patterns for evaluation without exponentially increasing the computation is another problem. In this paper, the modified periodicity transform is proposed to meet the requirements mentioned above. Also, a distributed computing framework is implemented to perform the mining task more efficiently. Both synthetic and biological sequences are utilized to examine the approach. The experimental results demonstrate the efficiency and effectiveness the system.
This paper presents a feature point tracking algorithm using optical flow under the non-prior training active feature model (NPT-AFM) framework. The proposed algorithm mainly focuses on analysis of deformable objects,...
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While feature selection is very difficult for high dimensional, unstructured data such as face image, it may be much easier to do if the data can be faithfully transformed into lower dimensional space. In this paper, ...
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In the Internet age, software is one of the core components for the operation of network and it penetrates almost all aspects of industry, commerce, and daily life. Since digital documents and objects can be duplicate...
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We propose adaptive nonlinear auto-associative modeling (ANAM) based on Locally Linear Embedding algorithm (LLE) for learning intrinsic principal features of each concept separately and recognition thereby. Unlike tra...
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As a new unsupervised learning technique, manifold learning has captured the attention of many researchers in the field of machine learning and cognitive sciences. The major algorithms include Isometric mapping (ISOMA...
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As a new unsupervised learning technique, manifold learning has captured the attention of many researchers in the field of machine learning and cognitive sciences. The major algorithms include Isometric mapping (ISOMAP) and Locally Linear Embedding (LLE). The approaches can be used for discovering the intrinsic dimensions of nonlinear high-dimensional data effectively and aim researchers to analyze the data better. How to quantitatively analyze the relationship between the intrinsic dimensions and the observation space, however, has fewer reports. And thus further works in manifold learning may have suffered some difficulties. The paper focuses on two kinds of manifold learning algorithms (ISOMAP, LLE), and discusses magnification factors and principal spread directions from the observation space to the intrinsic low-dimensional space. Also the corresponding algorithm is proposed. Experiments show the effectiveness and advantages of the research.
This paper presents a brief overview of current work at the University of Louisville toward the use of systemsengineering methodologies for control of the softwareengineering process. While this work is still in its...
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This paper presents a brief overview of current work at the University of Louisville toward the use of systemsengineering methodologies for control of the softwareengineering process. While this work is still in its initial stages, the methodologies for failure modes, effects and criticality analysis seem to be particularly appropriate. Two medium size software applications of these methodologies are currently under investigation in our laboratory.
A design technique of high speed digital signal PCB and investigates simulation, and verification methods based on IBIS models for CompactPCI bus single board computers was developed. The results on real application s...
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A design technique of high speed digital signal PCB and investigates simulation, and verification methods based on IBIS models for CompactPCI bus single board computers was developed. The results on real application show that it is effective and feasible.
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