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  • Open Access

    ARTICLE

    Detecting Outlier Behavior of Game Player Players Using Multimodal Physiology Data

    Shinjin Kang1, Taiwoo Park2,*

    Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 205-214, 2020, DOI:10.31209/2019.100000141

    Abstract This paper describes an outlier detection system based on a multimodal physiology data clustering algorithm in a PC gaming environment. The goal of this system is to provide information on a game player’s abnormal behavior with a bio-signal analysis. Using this information, the game platform can easily identify players with abnormal behavior in specific events. To do this, we propose a mouse device that measures the wearer's skin conductivity, temperature, and motion. We also suggest a Dynamic Time Warping (DTW) based clustering algorithm. The developed system examines the biometric information of 50 players in a bullet dodge game. This paper… More >

  • Open Access

    ARTICLE

    Statistical Analysis and Multimodal Classification on Noisy Eye Tracker and Application Log Data of Children with Autism and ADHD

    Mahiye Uluyagmur Ozturka, Ayse Rodopman Armanb, Gresa Carkaxhiu Bulutc, Onur Tugce Poyraz Findikb, Sultan Seval Yilmazd, Herdem Aslan Gencb, M. Yanki Yazgane,f, Umut Tekera, Zehra Cataltepea

    Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 891-905, 2018, DOI:10.31209/2018.100000058

    Abstract Emotion recognition behavior and performance may vary between people with major neurodevelopmental disorders such as Autism Spectrum Disorder (ASD), Attention Deficit Hyperactivity Disorder (ADHD) and control groups. It is crucial to identify these differences for early diagnosis and individual treatment purposes. This study represents a methodology by using statistical data analysis and machine learning to provide help to psychiatrists and therapists on the diagnosis and individualized treatment of participants with ASD and ADHD. In this paper we propose an emotion recognition experiment environment and collect eye tracker fixation data together with the application log data (APL). In order to detect… More >

  • Open Access

    ARTICLE

    An Accelerated Convergent Particle Swarm Optimizer (ACPSO) of Multimodal Functions

    Yasir Mehmood, Waseem Shahzad

    Intelligent Automation & Soft Computing, Vol.25, No.1, pp. 91-103, 2019, DOI:10.31209/2018.100000017

    Abstract Particle swarm optimization (PSO) algorithm is a global optimization technique that is used to find the optimal solution in multimodal problems. However, one of the limitation of PSO is its slow convergence rate along with a local trapping dilemma in complex multimodal problems. To address this issue, this paper provides an alternative technique known as ACPSO algorithm, which enables to adopt a new simplified velocity update rule to enhance the performance of PSO. As a result, the efficiency of convergence speed and solution accuracy can be maximized. The experimental results show that the ACPSO outperforms most of the compared PSO… More >

  • Open Access

    ARTICLE

    Fusion of Medical Images in Wavelet Domain: A Hybrid Implementation

    Satya Prakash Yadav1, *, Sachin Yadav2

    CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.1, pp. 303-321, 2020, DOI:10.32604/cmes.2020.08459

    Abstract This paper presents a low intricate, profoundly energy effective MRI Images combination intended for remote visual sensor frameworks which leads to improved understanding and implementation of treatment; especially for radiology. This is done by combining the original picture which leads to a significant reduction in the computation time and frequency. The proposed technique conquers the calculation and energy impediment of low power tools and is examined as far as picture quality and energy is concerned. Reenactments are performed utilizing MATLAB 2018a, to quantify the resultant vitality investment funds and the reproduction results show that the proposed calculation is very quick… More >

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