Applied and Computational Mathematics

Volume 6, Issue 4, July 2017

  • Tutorial on Support Vector Machine

    Loc Nguyen

    Issue: Volume 6, Issue 4-1, July 2017
    Pages: 1-15
    Received: 07 September 2015
    Accepted: 08 September 2015
    Published: 17 June 2016
    DOI: 10.11648/j.acm.s.2017060401.11
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    Abstract: Support vector machine is a powerful machine learning method in data classification. Using it for applied researches is easy but comprehending it for further development requires a lot of efforts. This report is a tutorial on support vector machine with full of mathematical proofs and example, which help researchers to understand it by the fastest ... Show More
  • Tutorial on Hidden Markov Model

    Loc Nguyen

    Issue: Volume 6, Issue 4-1, July 2017
    Pages: 16-38
    Received: 11 September 2015
    Accepted: 13 September 2015
    Published: 17 June 2016
    DOI: 10.11648/j.acm.s.2017060401.12
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    Abstract: Hidden Markov model (HMM) is a powerful mathematical tool for prediction and recognition. Many computer software products implement HMM and hide its complexity, which assist scientists to use HMM for applied researches. However comprehending HMM in order to take advantages of its strong points requires a lot of efforts. This report is a tutorial on... Show More
  • Longest-path Algorithm to Solve Uncovering Problem of Hidden Markov Model

    Loc Nguyen

    Issue: Volume 6, Issue 4-1, July 2017
    Pages: 39-47
    Received: 12 March 2016
    Accepted: 14 March 2016
    Published: 17 June 2016
    DOI: 10.11648/j.acm.s.2017060401.13
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    Abstract: Uncovering problem is one of three main problems of hidden Markov model (HMM), which aims to find out optimal state sequence that is most likely to produce a given observation sequence. Although Viterbi is the best algorithm to solve uncovering problem, I introduce a new viewpoint of how to solve HMM uncovering problem. The proposed algorithm is ca... Show More
  • Comparison of Singular Perturbations Approximation Method and Meta-Heuristic-Based Techniques for Order Reduction of Linear Discrete Systems

    Anouar Bouazza

    Issue: Volume 6, Issue 4-1, July 2017
    Pages: 48-54
    Received: 16 August 2016
    Accepted: 12 September 2016
    Published: 08 December 2016
    DOI: 10.11648/j.acm.s.2017060401.14
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    Abstract: This paper presents a survey of Singular Perturbations Approximation (SPA) method and meta-heuristic techniques for order reduction of linear systems in discrete case. A comparison of intelligent techniques to determine the reduced order model of higher order linear systems is presented. Two approaches are considered: Particle Swarm Optimization (P... Show More
  • Using Structure Holes for Determining Key Factors: An Illustration of Reporting Eradication of Amoebiasis

    Tsair-Wei Chien, Shih-Bin Su

    Issue: Volume 6, Issue 4-1, July 2017
    Pages: 55-63
    Received: 20 December 2016
    Accepted: 09 January 2017
    Published: 24 January 2017
    DOI: 10.11648/j.acm.s.2017060401.15
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    Abstract: Background: Many researches aim to determine key factors affecting their concerns of interest using traditional statistical techniques, such as logistical or linear regressions. Social network analysis (SNA) is a newly novel way determining key roles through the use of network and graph theories recently. An example of commonly visualized through S... Show More
  • Mobile Online Computer-Adaptive Tests (CAT) for Gathering Patient Feedback in Pediatric Consultations

    Tsair-Wei Chien, Wen-Pin Lai, Ju-Hao Hsieh

    Issue: Volume 6, Issue 4-1, July 2017
    Pages: 64-71
    Received: 19 December 2016
    Accepted: 09 January 2017
    Published: 06 February 2017
    DOI: 10.11648/j.acm.s.2017060401.16
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    Abstract: Background: Few studies have used online patient feedback from smartphones for computer adaptive testing (CAT). Objective: We developed a mobile online CAT survey procedure and evaluated whether it was more precise and efficient than traditional non-adaptive testing (NAT) when gathering patient feedback about their perceptions of interaction with a... Show More
  • Global Optimization with Descending Region Algorithm

    Loc Nguyen

    Issue: Volume 6, Issue 4-1, July 2017
    Pages: 72-82
    Received: 08 April 2017
    Accepted: 10 April 2017
    Published: 09 June 2017
    DOI: 10.11648/j.acm.s.2017060401.17
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    Abstract: Global optimization is necessary in some cases when we want to achieve the best solution or we require a new solution which is better the old one. However global optimization is a hazard problem. Gradient descent method is a well-known technique to find out local optimizer whereas approximation solution approach aims to simplify how to solve the gl... Show More