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2010 Second International Conference on Knowledge and Systems Engineering

7-9 Oct. 2010

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  • [Front cover]

    Publication Year: 2010, Page(s): C1
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  • [Title page i]

    Publication Year: 2010, Page(s): i
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  • [Title page iii]

    Publication Year: 2010, Page(s): iii
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  • [Copyright notice]

    Publication Year: 2010, Page(s): iv
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  • Table of contents

    Publication Year: 2010, Page(s):v - vii
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  • Preface

    Publication Year: 2010, Page(s): viii
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  • KSE 2010 Organization

    Publication Year: 2010, Page(s):ix - x
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  • Invited talks

    Publication Year: 2010, Page(s):xi - xiii
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (107 KB) | HTML iconHTML

    Provides an abstract for each of the keynote presentations and a brief professional biography of each presenter. The complete presentations were not made available for publication as part of the conference proceedings. View full abstract»

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  • A New Method for Splitting Clumped Cells in Red Blood Images

    Publication Year: 2010, Page(s):3 - 8
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (446 KB) | HTML iconHTML

    Automated cell counting is a required task which helps examiners in evaluating blood smears. A problem is that clumped cells usually appear in images with various degree of overlapping. This study presents a new method for effectively splitting clumped cells using value in distance transform of image to quickly detect central point. Additionally, a boundary-covering degree of each point is applied... View full abstract»

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  • A Novel Computational Approach for Fire Detection

    Publication Year: 2010, Page(s):9 - 13
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (182 KB) | HTML iconHTML

    This paper proposes a model for detecting fire captured in video data by combining the methods of correlation coefficient, Gaussian Mixture Model - GMM and turbulent analysis. The method of correlation efficient is used to determine movement objects. We use GMM to cluster fire-colored pixel in the RGB space. The objective of turbulent analysis is to detect the flame of fire. A model built on three... View full abstract»

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  • EM-Coffee: An Improvement of M-Coffee

    Publication Year: 2010, Page(s):14 - 19
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (291 KB) | HTML iconHTML

    Multiple sequence alignment is a basic of sequence analysis. In the development of multiple sequence alignment (MSA) approaches, M-Coffee [1] was proposed as a meta-method for assembling outputs from different individual multiple aligners into one single MSA to boost the accuracy. Authors showed that M-Coffee outperformed individual alignment methods. In this paper, we propose an improvement of M-... View full abstract»

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  • Interactive Exploration of Hierarchical Density Clusters in Gene Expression Data

    Publication Year: 2010, Page(s):20 - 27
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (353 KB) | HTML iconHTML

    Clustering gene expression data is an important task in bioinformatics research and biomedical applications. In this paper, we present an effective clustering algorithm for gene expression data. The clustering algorithm is based on the analysis of data's density distribution. We propose an intersecting partition of gene expression data into the supports of data points. Density clusters are maximal... View full abstract»

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  • Investigation of the Hemodynamic Response in Near Infrared Spectroscopy Data Analysis

    Publication Year: 2010, Page(s):28 - 32
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (199 KB) | HTML iconHTML

    Near infrared spectroscopy (NIRS) is an effective technique for examining functional brain activity during cognitive tasks by enabling the measurement of the concentration changes of oxy-hemoglobin and deoxy-hemoglobin. In NIRS data analysis, accurate estimation of the hemodynamic response function (HRF) is still under investigation. Most existing methods assume that the shape of the HRF to be kno... View full abstract»

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  • SDA*: A Simple and Unifying Solution to Recent Bioinformatic Challenges for Conservation Genetics

    Publication Year: 2010, Page(s):33 - 37
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (175 KB) | HTML iconHTML

    Recently, several algorithms have been proposed to tackle different conservation questions under phylogenetic diversity. Such questions are variants of the more general problem of budgeted reserve selection under split diversity, an NP-hard problem. Here, we present a novel framework, Split Diversity Algorithm* (SDA*), to unify all these attempts. More specifically, SDA* transforms the budgeted re... View full abstract»

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  • An Effective Method for Ontology Integration by Propagating Inconsistency

    Publication Year: 2010, Page(s):41 - 46
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (407 KB) | HTML iconHTML

    Ontology integration is an important task which needs to be performed when several information systems share or exchange knowledge. We consider that most of previous methods of ontology integration merely involve blind or exhaustive matching among all concepts belonging to different ontologies. Therefore, semantic mismatches, logical inconsistencies and conceptual conflicts between ontologies are ... View full abstract»

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  • An Improvement of PIP for Time Series Dimensionality Reduction and Its Index Structure

    Publication Year: 2010, Page(s):47 - 54
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (270 KB) | HTML iconHTML

    In this paper, we introduce a new time series dimensionality reduction method, IPIP. This method takes full advantages of PIP (Perceptually Important Points) method, proposed by Chung et al., with some improvements in order that the new method can theoretically satisfy the lower bounding condition for time series dimensionality reduction methods. Furthermore, we can make IPIP index able by showing... View full abstract»

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  • Rule-Based Attribute-Oriented Induction for Knowledge Discovery

    Publication Year: 2010, Page(s):55 - 62
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (272 KB) | HTML iconHTML

    This paper introduces a rule-based Attribute-Oriented (AO) Induction method on rule-based concept hierarchies that can be constructed from generalization rules. Based on analyzing some major previous approaches such as rule-based AO induction with backtracking, path-id based AO induction and a cyclic graph based AO induction, we propose a new approach to facilitate induction on the rule based case... View full abstract»

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  • Supervised Feature Evaluation by Consistency Analysis: Application to Measure Sets Used to Characterise Geographic Objects

    Publication Year: 2010, Page(s):63 - 68
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (342 KB) | HTML iconHTML

    Nowadays, supervised learning is commonly used in many domains. Indeed, many works propose to learn new knowledge from examples that translate the expected behaviour of the considered system. A key issue of supervised learning concerns the description language used to represent the examples. In this paper, we propose a method to evaluate the feature set used to describe them. Our method is based o... View full abstract»

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  • Supervised Learning of a Color-Based Active Basis Model for Object Recognition

    Publication Year: 2010, Page(s):69 - 74
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (336 KB) | HTML iconHTML

    Wu and coworkers introduced an active basis model (ABM) for detecting generic objects in static images. A grey-value local power spectrum was utilized to find a common template and deformable templates from a set of training images and to detect an object in unknown images by template matching. In this paper, we propose a color-based active basis model (color-based ABM for short) which includes co... View full abstract»

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  • A Computational Framework for Adaptation in Military Mission Planning

    Publication Year: 2010, Page(s):77 - 84
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (270 KB) | HTML iconHTML

    Military missions are highly dynamic and uncertain. This characteristic comes from the nature of battlefields where such factors as enemies and terrains are not easy to be determined. Hence disruption of missions is likely to occur whenever happening a change. This requires generating plans that can adapt quickly to changes during execution of missions, while paying a less cost. In this paper, we ... View full abstract»

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  • Neural Networks Training Based on Sequential Extended Kalman Filtering for Single Trial EEG Classification

    Publication Year: 2010, Page(s):85 - 88
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (240 KB) | HTML iconHTML

    The nonstationary nature of the brain signals provides a rather unstable input resulting in uncertainty and complexity in the control. Intelligent processing algorithms adapted to the task are a prerequisite for reliable BCI applications. This work presents a novel intelligent processing strategy for the realization of an effective BCI which has the capability to improved classification accuracy a... View full abstract»

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  • Predicting the Tide with Genetic Programming and Semantic-based Crossovers

    Publication Year: 2010, Page(s):89 - 95
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (200 KB) | HTML iconHTML

    This paper proposes an improvement of a recently proposed semantic-based crossover, Semantic Similarity-based Crossover (SSC). The new crossover, called the Most Semantic Similarity-based Crossover (MSSC), is tested with Genetic Programming (GP) on a real world problem, as in predicting the tide in Venice Lagoon, Italy. The results are compared with GP using Standard Crossover (SC) and GP using va... View full abstract»

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  • Privacy Preserving Classification in Two-Dimension Distributed Data

    Publication Year: 2010, Page(s):96 - 103
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (224 KB) | HTML iconHTML

    Within the context of privacy preserving data mining, several solutions for privacy-preserving classification rules learning such as association rules mining have been proposed. Each solution was provided for horizontally or vertically distributed scenario. The aim of this work is to study privacy-preserving classification rules learning in two-dimension distributed data, which is a generalisation... View full abstract»

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  • Smoothing Supervised Learning of Neural Networks for Function Approximation

    Publication Year: 2010, Page(s):104 - 109
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (196 KB) | HTML iconHTML

    Two popular hazards in supervised learning of neural networks are local minima and over fitting. Application of the momentum technique dealing with the local optima has proved efficient but it is vulnerable to over fitting. In contrast, deployment of the early stopping technique might overcome the over fitting phenomena but it sometimes terminates into the local minima. This paper proposes a hybri... View full abstract»

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  • Constructive Generation of 3-COL Instances Focusing on Vertex Connectivity of Minimal Unsolvable Structures

    Publication Year: 2010, Page(s):113 - 118
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (537 KB) | HTML iconHTML

    Phase transition phenomena observed in most combinatorial search problems including constraint satisfaction problems (CSPs) are important for clarifying how structures make problem instances hard to solve. For the graph 3-colorability (3COL), which is one of the typical CSPs, the method to systematically generate hard problem instances by embedding original minimal unsolvable structures has been p... View full abstract»

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