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  • Open Access


    Analysis of OSA Syndrome from PPG Signal Using CART-PSO Classifier with Time Domain and Frequency Domain Features

    N. Kins Burk Sunil1, *, R. Ganesan2, B. Sankaragomathi3

    CMES-Computer Modeling in Engineering & Sciences, Vol.118, No.2, pp. 351-375, 2019, DOI:10.31614/cmes.2018.04484

    Abstract Obstructive Sleep Apnea (OSA) is a respiratory syndrome that occurs due to insufficient airflow through the respiratory or respiratory arrest while sleeping and sometimes due to the reduced oxygen saturation. The aim of this paper is to analyze the respiratory signal of a person to detect the Normal Breathing Activity and the Sleep Apnea (SA) activity. In the proposed method, the time domain and frequency domain features of respiration signal obtained from the PPG device are extracted. These features are applied to the Classification and Regression Tree (CART)-Particle Swarm Optimization (PSO) classifier which classifies the signal into normal breathing signal… More >

  • Open Access


    Human Behavior Classification Using Geometrical Features of Skeleton and Support Vector Machines

    Syed Muhammad Saqlain Shah1,*, Tahir Afzal Malik2, Robina khatoon1, Syed Saqlain Hassan3, Faiz Ali Shah4

    CMC-Computers, Materials & Continua, Vol.61, No.2, pp. 535-553, 2019, DOI:10.32604/cmc.2019.07948

    Abstract Classification of human actions under video surveillance is gaining a lot of attention from computer vision researchers. In this paper, we have presented methodology to recognize human behavior in thin crowd which may be very helpful in surveillance. Research have mostly focused the problem of human detection in thin crowd, overall behavior of the crowd and actions of individuals in video sequences. Vision based Human behavior modeling is a complex task as it involves human detection, tracking, classifying normal and abnormal behavior. The proposed methodology takes input video and applies Gaussian based segmentation technique followed by post processing through presenting… More >

  • Open Access


    An Image Classification Method Based on Deep Neural Network with Energy Model

    Yang Yang1,*, Jinbao Duan1, Haitao Yu1, Zhipeng Gao1, Xuesong Qiu1

    CMES-Computer Modeling in Engineering & Sciences, Vol.117, No.3, pp. 555-575, 2018, DOI:10.31614/cmes.2018.04249

    Abstract The development of deep learning has revolutionized image recognition technology. How to design faster and more accurate image classification algorithms has become our research interests. In this paper, we propose a new algorithm called stochastic depth networks with deep energy model (SADIE), and the model improves stochastic depth neural network with deep energy model to provide attributes of images and analysis their characteristics. First, the Bernoulli distribution probability is used to select the current layer of the neural network to prevent gradient dispersion during training. Then in the backpropagation process, the energy function is designed to optimize the target loss… More >

  • Open Access


    Classification of Crystallographic Groups of Alloy Systems by Isomap and Modularity Methods

    Kuan-Peng Chen1,3, An-Cheng Yang1,3, Wen-Jay Lee1, Yi-Ming Tseng2, Nien-Ti Tsou2, Nan-Yow Chen1,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.21, No.3, pp. 54-54, 2019, DOI:10.32604/icces.2019.05401

    Abstract Crystallographic classification of microstructure is a very important issue in material science especially numerous data were generated by experiments or Molecular Dynamic (MD) simulations. Some analysis tools were purposed, such as coordination analysis and Honeycutt-Anderson (HA) pair analysis [1], however, to analyze these huge amounts of data is still quite difficult. Sometimes, crystallography prior knowledge of their structures is also desired in the classification procedures. Not only the task is very labor intensive but also the result is susceptible to errors and is usually lack of objectivity. In this study, we developed a computational workflow which can get characteristic quantities… More >

  • Open Access


    A New Quadtree-based Image Compression Technique using Pattern Matching Algorithm

    F. Keissarian1

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.12, No.4, pp. 137-144, 2009, DOI:10.3970/icces.2009.012.137

    Abstract In this paper, a new image compression technique is proposed in which variable block size technique is adopted, using quadtree decomposition, for coding images at low bit rates. The proposed algorithm decomposes the host image into blocks of variable sizes according to histogram analysis of the block residuals. Variable block sizes are then encoded at different rates based on their visual activity levels. To preserve edge integrity, a high-detail block is coded by a set of parameters associated with the pattern appearing inside the block. The use of these parameters at the receiver together with the quadtree code reduces the… More >

  • Open Access


    Hybrid Deep VGG-NET Convolutional Classifier for Video Smoke Detection

    Princy Matlani1,*, Manish Shrivastava1

    CMES-Computer Modeling in Engineering & Sciences, Vol.119, No.3, pp. 427-458, 2019, DOI:10.32604/cmes.2019.04985

    Abstract Real-time wild smoke detection utilizing machine based identification method is not produced proper accuracy, and it is not suitable for accurate prediction. However, various video smoke detection approaches involve minimum lighting, and it is required for the cameras to identify the existence of smoke particles in a scene. To overcome such challenges, our proposed work introduces a novel concept like deep VGG-Net Convolutional Neural Network (CNN) for the classification of smoke particles. This Deep Feature Synthesis algorithm automatically generated the characteristics for relational datasets. Also hybrid ABC optimization rectifies the problem related to the slow convergence since complexity is reduced.… More >

  • Open Access


    A Novel Image Categorization Strategy Based on Salp Swarm Algorithm to Enhance Efficiency of MRI Images

    Mohammad Behrouzian Nejad1, Mohammad Ebrahim Shiri Ahmadabadi1, 2, *

    CMES-Computer Modeling in Engineering & Sciences, Vol.119, No.1, pp. 185-205, 2019, DOI:10.32604/cmes.2019.01838

    Abstract The main target of this paper is presentation of an efficient method for MRI images classification so that it can be used to diagnose patients and non-patients. Image classification is one of the prominent subset topics of machine learning and data mining that the most important image technique is the auto-categorization of images. MRI images with high resolution and appropriate accuracy allow physicians to decide on the diagnosis of various diseases and treat them. The auto categorization of MRI images toward diagnosing brain diseases has been being used to accurately diagnose hospitals, clinics, physicians and medical research centers. In this… More >

  • Open Access


    Research on Protecting Information Security Based on the Method of Hierarchical Classification in the Era of Big Data

    Guangyong Yang1,*, Mengke Yang2,*, Shafaq Salam3, Jianqiu Zeng4

    Journal of Cyber Security, Vol.1, No.1, pp. 19-28, 2019, DOI:10.32604/jcs.2019.05947

    Abstract Big data is becoming increasingly important because of the enormous information generation and storage in recent years. It has become a challenge to the data mining technique and management. Based on the characteristics of geometric explosion of information in the era of big data, this paper studies the possible approaches to balance the maximum value and privacy of information, and disposes the Nine-Cells information matrix, hierarchical classification. Furthermore, the paper uses the rough sets theory to proceed from the two dimensions of value and privacy, establishes information classification method, puts forward the countermeasures for information security. Taking spam messages for… More >

  • Open Access


    Analysis of the Efficiency-Energy with Regression and Classification in Household Using K-NN

    Qi Liu1,2, Zhiyun Yang1, Xiaodong Liu3, Scholas Mbonihankuye4,*

    Journal of New Media, Vol.1, No.2, pp. 101-113, 2019, DOI:10.32604/jnm.2019.06958

    Abstract This paper aims to study energy consumption in a house. Home energy man-agement system (HEMS) has become very important, because energy consumption of a residential sector accounts for a significant amount of total energy consumption. However, a conventional HEMS has some architectural limitations among dimensional variables reusability and interoperability. Furthermore, the cost of implementation in HEMS is very expensive, which leads to the disturbance of the spread of a HEMS. Therefore, this study proposes an Internet of Things (IoT) based HEMS with lightweight photovoltaic (PV) system over dynamic home area networks (DHANs), which enables the construction of a HEMS to… More >

  • Open Access


    Multi-Label Chinese Comments Categorization: Comparison of Multi-Label Learning Algorithms

    Jiahui He1, Chaozhi Wang1, Hongyu Wu1, Leiming Yan1,*, Christian Lu2

    Journal of New Media, Vol.1, No.2, pp. 51-61, 2019, DOI:10.32604/jnm.2019.06238

    Abstract Multi-label text categorization refers to the problem of categorizing text through a multi-label learning algorithm. Text classification for Asian languages such as Chinese is different from work for other languages such as English which use spaces to separate words. Before classifying text, it is necessary to perform a word segmentation operation to convert a continuous language into a list of separate words and then convert it into a vector of a certain dimension. Generally, multi-label learning algorithms can be divided into two categories, problem transformation methods and adapted algorithms. This work will use customer's comments about some hotels as a… More >

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