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  • Open Access

    ARTICLE

    Recommendation Learning System Model for Children with Autism

    V. Balaji*, S. Kanaga Suba Raja

    Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 1301-1315, 2022, DOI:10.32604/iasc.2022.020287

    Abstract Autism spectrum disorder (ASD), is a neurological developmental disorder. It affects how people communicate and interact with others, as well as how they behave and learn. The symptoms and signs appear when a child is very young. Derived with increased usage of machine learning procedure in the medicinal analysis investigations. In this paper, our objective is to find out the most significant attributes and automate the process using classification techniques and pattern clustering using K-means clustering. We have analyzed ASD datasets of children towards determining the best performance of classifier for these binary datasets considering recall, precision, accuracy and classification… More >

  • Open Access

    ARTICLE

    Mammogram Learning System for Breast Cancer Diagnosis Using Deep Learning SVM

    G. Jayandhi1,*, J.S. Leena Jasmine2, S. Mary Joans2

    Computer Systems Science and Engineering, Vol.40, No.2, pp. 491-503, 2022, DOI:10.32604/csse.2022.016376

    Abstract The most common form of cancer for women is breast cancer. Recent advances in medical imaging technologies increase the use of digital mammograms to diagnose breast cancer. Thus, an automated computerized system with high accuracy is needed. In this study, an efficient Deep Learning Architecture (DLA) with a Support Vector Machine (SVM) is designed for breast cancer diagnosis. It combines the ideas from DLA with SVM. The state-of-the-art Visual Geometric Group (VGG) architecture with 16 layers is employed in this study as it uses the small size of 3 × 3 convolution filters that reduces system complexity. The softmax layer… More >

  • Open Access

    ARTICLE

    COVID-DeepNet: Hybrid Multimodal Deep Learning System for Improving COVID-19 Pneumonia Detection in Chest X-ray Images

    A. S. Al-Waisy1, Mazin Abed Mohammed1, Shumoos Al-Fahdawi1, M. S. Maashi2, Begonya Garcia-Zapirain3, Karrar Hameed Abdulkareem4, S. A. Mostafa5, Nallapaneni Manoj Kumar6, Dac-Nhuong Le7,8,*

    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2409-2429, 2021, DOI:10.32604/cmc.2021.012955

    Abstract Coronavirus (COVID-19) epidemic outbreak has devastating effects on daily lives and healthcare systems worldwide. This newly recognized virus is highly transmissible, and no clinically approved vaccine or antiviral medicine is currently available. Early diagnosis of infected patients through effective screening is needed to control the rapid spread of this virus. Chest radiography imaging is an effective diagnosis tool for COVID-19 virus and follow-up. Here, a novel hybrid multimodal deep learning system for identifying COVID-19 virus in chest X-ray (CX-R) images is developed and termed as the COVID-DeepNet system to aid expert radiologists in rapid and accurate image interpretation. First, Contrast-Limited… More >

  • Open Access

    ARTICLE

    The Implementation of an English Word Learning System Feedback System and Smartphone App

    Ye Zhang

    Computer Systems Science and Engineering, Vol.35, No.3, pp. 207-214, 2020, DOI:10.32604/csse.2020.35.207

    Abstract Considering the issue of Chinese college students that are not interested in learning English and have a lack of enthusiasm for learning overall, a feedback and motivation application based on cloud computing to teach English vocabulary to Chinese college students has been developed. The mobile application can collect and analyze the problems that users encounter in the process of learning English through the cloud server in real-time, and advise on how to resolve these problems. The feedback system also allows users to access this data. In the case of uploading to designated teachers, teachers can adjust their teaching methods and… More >

  • Open Access

    ARTICLE

    A Reinforcement Learning System for Fault Detection and Diagnosis in Mechatronic Systems

    Wanxin Zhang1,*, Jihong Zhu2

    CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 1119-1130, 2020, DOI:10.32604/cmes.2020.010986

    Abstract With the increasing demand for the automation of operations and processes in mechatronic systems, fault detection and diagnosis has become a major topic to guarantee the process performance. There exist numerous studies on the topic of applying artificial intelligence methods for fault detection and diagnosis. However, much of the focus has been given on the detection of faults. In terms of the diagnosis of faults, on one hand, assumptions are required, which restricts the diagnosis range. On the other hand, different faults with similar symptoms cannot be distinguished, especially when the model is not trained by plenty of data. In… More >

  • Open Access

    ABSTRACT

    An e-learning system for CAE

    A. Kuwata1, H. Noguchi2, H. Kawai3

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.2, No.3, pp. 87-92, 2007, DOI:10.3970/icces.2007.002.087

    Abstract In this research, we constructed an e-learning system of the CAE (FEM) education. We analyzed about the usefulness of e-learning from each viewpoint of a software developer of the e-learning system, a system administrator of the system, and a user. In addition, we considered about the necessary technology in Web application. More >

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