N. Kins Burk Sunil^{1, *}, 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 More >

Syed Muhammad Saqlain Shah^1,*, 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 More >

Kuan-Peng Chen^1,3, An-Cheng Yang^1,3, Wen-Jay Lee¹, Yi-Ming Tseng², Nien-Ti Tsou², Nan-Yow Chen^1,*

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… More >

Princy Matlani^1,*, 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… More >

Mohammad Behrouzian Nejad¹, Mohammad Ebrahim Shiri Ahmadabadi^{1, 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… More >

Guangyong Yang^1,*, Mengke Yang^2,*, 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 More >

Qi Liu^1,2, Zhiyun Yang¹, Xiaodong Liu³, Scholas Mbonihankuye^4,*

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 More >

Jiahui He¹, Chaozhi Wang¹, Hongyu Wu¹, Leiming Yan^1,*, 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 More >

Hao Wu¹, Qi Liu^{2, 3, *}, Xiaodong Liu⁴

CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 575-597, 2019, DOI:10.32604/cmc.2019.03595

Abstract Deep learning technology has brought great impetus to artificial intelligence, especially in the fields of image processing, pattern and object recognition in recent years. Present proposed artificial neural networks and optimization skills have effectively achieved large-scale deep learnt neural networks showing better performance with deeper depth and wider width of networks. With the efforts in the present deep learning approaches, factors, e.g., network structures, training methods and training data sets are playing critical roles in improving the performance of networks. In this paper, deep learning models in recent years are summarized and compared with detailed More >

Hoong-Chor Chin¹, Xingting Pang¹, Zhaoxia Wang^2,3,*

CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 455-463, 2019, DOI:10.32604/cmc.2019.05664

Abstract Passenger comfort is an important indicator that is often used to measure the quality of public transport services. It may also be a crucial factor in the passenger’s choice of transport mode. The typical method of assessing passenger comfort is through a passenger interview survey which can be tedious. This study aims to investigate the relationship between bus ride comfort based on ride smoothness and the vehicle’s motion detected by the smartphone sensors. An experiment was carried out on a bus fixed route within the University campus where comfort levels were rated on a 3-point… More >