Ibrahim Mufrah Almanjahie^{1, 2}, Zouaoui Chikr Elmezouar^{1, 2, 3, *}, Ali Laksaci^{1, 2}

CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 593-604, 2020, DOI:10.32604/cmc.2020.08901 - 01 May 2020

Abstract This paper examines the causal relationship between oil prices and the Gross Domestic Product (GDP) in the Kingdom of Saudi Arabia. The study is carried out by a data set collected quarterly, by Saudi Arabian Monetary Authority, over a period from 1974 to 2016. We seek how a change in real crude oil price affects the GDP of KSA. Based on a new technique, we treat this data in its continuous path. Precisely, we analyze the causality between these two variables, i.e., oil prices and GDP, by using their yearly curves observed in the four More >

Oakyoung Han¹, Jaehyoun Kim^{2, *}

CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 553-566, 2020, DOI:10.32604/cmc.2020.09362 - 01 May 2020

Abstract The processing of sound signals is significantly improved recently. Technique for sound signal processing focusing on music beyond speech area is getting attention due to the development of deep learning techniques. This study is for analysis and process of music signals to generate tow-dimensional tabular data and a new music. For analysis and process part, we represented normalized waveforms for each of input data via frequency domain signals. Then we looked into shorted segment to see the difference wave pattern for different singers. Fourier transform is applied to get spectrogram of the music signals. Filterbank… More >

Xiangao Jiang¹, Megan Coffee^{2, 3, *}, Anasse Bari^{4, *}, Junzhang Wang⁴, Xinyue Jiang⁵, Jianping Huang¹, Jichan Shi¹, Jianyi Dai¹, Jing Cai¹, Tianxiao Zhang⁶, Zhengxing Wu¹, Guiqing He¹, Yitong Huang⁷

CMC-Computers, Materials & Continua, Vol.63, No.1, pp. 537-551, 2020, DOI:10.32604/cmc.2020.010691 - 30 March 2020

Abstract The virus SARS-CoV2, which causes coronavirus disease (COVID-19) has become a pandemic and has spread to every inhabited continent. Given the increasing caseload, there is an urgent need to augment clinical skills in order to identify from among the many mild cases the few that will progress to critical illness. We present a first step towards building an artificial intelligence (AI) framework, with predictive analytics (PA) capabilities applied to real patient data, to provide rapid clinical decision-making support. COVID-19 has presented a pressing need as a) clinicians are still developing clinical acumen to this novel… More >

Shuyu Li¹, Guozheng Zhang^{1, *}

CMC-Computers, Materials & Continua, Vol.63, No.1, pp. 223-241, 2020, DOI:10.32604/cmc.2020.07499 - 30 March 2020

Abstract With the popularity of sensor-rich mobile devices, mobile crowdsensing (MCS) has emerged as an effective method for data collection and processing. However, MCS platform usually need workers’ precise locations for optimal task execution and collect sensing data from workers, which raises severe concerns of privacy leakage. Trying to preserve workers’ location and sensing data from the untrusted MCS platform, a differentially private data aggregation method based on worker partition and location obfuscation (DP-DAWL method) is proposed in the paper. DP-DAWL method firstly use an improved K-means algorithm to divide workers into groups and assign different… More >

Jieren Cheng^{1, 2}, Canting Cai^{1, *}, Xiangyan Tang¹, Victor S. Sheng³, Wei Guo¹, Mengyang Li¹

CMC-Computers, Materials & Continua, Vol.63, No.1, pp. 131-150, 2020, DOI:10.32604/cmc.2020.06175 - 30 March 2020

Abstract Traditional distributed denial of service (DDoS) detection methods need a lot of computing resource, and many of them which are based on single element have high missing rate and false alarm rate. In order to solve the problems, this paper proposes a DDoS attack information fusion method based on CNN for multi-element data. Firstly, according to the distribution, concentration and high traffic abruptness of DDoS attacks, this paper defines six features which are respectively obtained from the elements of source IP address, destination IP address, source port, destination port, packet size and the number of… More >

Rijia Ding¹, Xingyao Zhou^1,*, Rui Zhang¹, Wanqiu Lu²

Energy Engineering, Vol.117, No.1, pp. 27-39, 2020, DOI:10.32604/EE.2020.010372 - 28 February 2020

Abstract Coal is the main energy source in China. At present, the coal overcapacity is still serious in China. Accurately measuring the degree of China’s coal overcapacity can scientifically resolve the overcapacity, and is the premise of guiding the healthy development of coal industry and energy system. Using the translog cost function and the panel data of coal industry in all provinces of China from 2002 to 2011 and from 2012 to 2016, the research measures and compares the coal production capacity of “golden decade” and “cold winter” in China. The results show that: (1) The More >

Roberto Bellas^{1, *}, Javier Martínez¹, Ignacio Rivera², Ramón Touza², Miguel Gómez¹, Rafael Carreño¹

CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.3, pp. 971-995, 2020, DOI:10.32604/cmes.2020.07530 - 01 March 2020

Abstract The study of emergency evacuation in public spaces, buildings and large ships may present parallel characteristic in terms of complexity of the layout but there are also significant differences that can hindering passengers to reach muster stations or the lifeboats. There are many hazards on a ship that can cause an emergency evacuation, the most severe result in loss of lives. Providing safe and effective evacuation of passengers from ships in an emergency situation becomes critical. Recently, computer simulation has become an indispensable technology in various fields, among them, the evacuation models that recently evolved… More >

Jian Liu¹, Wantao Wang¹, Jie Chen^{2, *}, Guozhong Sun³, Alan Yang⁴

CMC-Computers, Materials & Continua, Vol.62, No.3, pp. 1187-1200, 2020, DOI:10.32604/cmc.2020.05883

Abstract Classification of skin lesions is a complex identification challenge. Due to the wide variety of skin lesions, doctors need to spend a lot of time and effort to judge the lesion image which zoomed through the dermatoscopy. The diagnosis which the algorithm of identifying pathological images assists doctors gets more and more attention. With the development of deep learning, the field of image recognition has made longterm progress. The effect of recognizing images through convolutional neural network models is better than traditional image recognition technology. In this work, we try to classify seven kinds of More >

Jinlin Wang¹, Xing Wang^{1, *}, Yuchen Yang¹, Hongli Zhang¹, Binxing Fang¹

CMC-Computers, Materials & Continua, Vol.62, No.3, pp. 1053-1075, 2020, DOI:10.32604/cmc.2020.08675

Abstract Web information system (WIS) is frequently-used and indispensable in daily social life. WIS provides information services in many scenarios, such as electronic commerce, communities, and edutainment. Data cleaning plays an essential role in various WIS scenarios to improve the quality of data service. In this paper, we present a review of the state-of-the-art methods for data cleaning in WIS. According to the characteristics of data cleaning, we extract the critical elements of WIS, such as interactive objects, application scenarios, and core technology, to classify the existing works. Then, after elaborating and analyzing each category, we More >

Yingjun Wang¹, Zhongyuan Liao¹, Shengyu Shi^{1, *}, Zhenpei Wang^{2, *}, Leong Hien Poh³

CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.2, pp. 433-458, 2020, DOI:10.32604/cmes.2020.08680 - 01 February 2020

Abstract Focusing on the structural optimization of auxetic materials using data-driven methods, a back-propagation neural network (BPNN) based design framework is developed for petal-shaped auxetics using isogeometric analysis. Adopting a NURBS-based parametric modelling scheme with a small number of design variables, the highly nonlinear relation between the input geometry variables and the effective material properties is obtained using BPNN-based fitting method, and demonstrated in this work to give high accuracy and efficiency. Such BPNN-based fitting functions also enable an easy analytical sensitivity analysis, in contrast to the generally complex procedures of typical shape and size sensitivity More >