Jiyoung Yun, Mainak Basak, Myung-Mook Han^*

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 2827-2843, 2021, DOI:10.32604/cmc.2021.017266

Abstract Coronavirus disease 2019 (COVID-19) has been termed a “Pandemic Disease” that has infected many people and caused many deaths on a nearly unprecedented level. As more people are infected each day, it continues to pose a serious threat to humanity worldwide. As a result, healthcare systems around the world are facing a shortage of medical space such as wards and sickbeds. In most cases, healthy people experience tolerable symptoms if they are infected. However, in other cases, patients may suffer severe symptoms and require treatment in an intensive care unit. Thus, hospitals should select patients who have a high risk… More >

Yanping Ruan^1,#, Xiangyu Liu^2,#, Haogang Zhu^3,*, Yijie Lu³, Xiaowei Liu¹, Jiancheng Han¹, Lin Sun¹, Ye Zhang¹, Xiaoyan Gu¹, Ying Zhao¹, Lei Li², Suzhen Ran⁴, Jingli Chen⁵, Qiong Yu⁶, Yan Xu⁷, Hongmei Xia⁸, Yihua He^1,*

Congenital Heart Disease, Vol.16, No.6, pp. 529-549, 2021, DOI:10.32604/CHD.2021.015862

Abstract Background: Current studies have confirmed that fetal congenital heart diseases (CHDs) are caused by various factors. However, the quantitative risk of CHD is not clear given the combined effects of multiple factors. Objective: This cross-sectional study aimed to detect associated factors of fetal CHD using a Bayesian network in a large sample and quantitatively analyze relative risk ratios (RRs). Methods: Pregnant women who underwent fetal echocardiography (N = 16,086 including 3,312 with CHD fetuses) were analyzed. Twenty-six maternal and fetal factors were obtained. A Bayesian network is constructed based on all variables through structural learning and parameter learning methods to… More >

Tian Liwei^1,2,*, Feng Li¹, Sun Yu³, Guo Yuankai⁴

Intelligent Automation & Soft Computing, Vol.29, No.3, pp. 855-868, 2021, DOI:10.32604/iasc.2021.016805

Abstract The prediction of the “ups and downs” of stock market prices is one of the important undertakings of the financial market. Since accurate prediction helps foster considerable economic benefits, stock market prediction has attracted significant interest by both investors and researchers. Efforts into building an accurate, stable and effective model to predict stock prices’ movements have been proliferating at a fast pace, to meet such a challenge. Firstly, this paper uses a correlation analysis to analyze the attributes of a stock dataset, processing missing values, determining the data attributes to be retained data, then divide it in a training set… More >

Gamal M. Ibrahim¹, Amal S. Hassan², Ehab M. Almetwally^3,*, Hisham M. Almongy⁴

Intelligent Automation & Soft Computing, Vol.29, No.2, pp. 353-371, 2021, DOI:10.32604/iasc.2021.017586

Abstract We introduce a new two-parameter lifetime model, referred to alpha power transformed inverted Topp-Leone, derived by combining the alpha power transformation-G family with the inverted Topp-Leone distribution. Structural properties of the proposed distribution are implemented like; quantile function, residual and reversed residual life, Rényi entropy measure, moments and incomplete moments. The maximum likelihood, weighted least squares, maximum product of spacing, and Bayesian methods of estimation are considered. A simulation study is worked out to evaluate the restricted sample properties of the proposed distribution. Numerical results showed that the Bayesian estimates give more accurate results than the corresponding other estimates in… More >

Tina Babu¹, Deepa Gupta¹, Tripty Singh^1,*, Shahin Hameed², Mohammed Zakariah³, Yousef Ajami Alotaibi⁴

CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 99-128, 2021, DOI:10.32604/cmc.2021.016341

Abstract Automated grading of colon biopsy images across all magnifications is challenging because of tailored segmentation and dependent features on each magnification. This work presents a novel approach of robust magnification-independent colon cancer grading framework to distinguish colon biopsy images into four classes: normal, well, moderate, and poor. The contribution of this research is to develop a magnification invariant hybrid feature set comprising cartoon feature, Gabor wavelet, wavelet moments, HSV histogram, color auto-correlogram, color moments, and morphological features that can be used to characterize different grades. Besides, the classifier is modeled as a multiclass structure with six binary class Bayesian optimized… More >

Abdul Rehman^1,*, Mohd Fadzil Hassan¹, Yew Kwang Hooi¹, Muhammad Aasim Qureshi², Tran Duc Chung³, Rehan Akbar⁴, Sohail Safdar⁵

CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 4125-4142, 2021, DOI:10.32604/CMC.2021.017620

Abstract Trust is one of the core components of any ad hoc network security system. Trust management (TM) has always been a challenging issue in a vehicular network. One such developing network is the Internet of vehicles (IoV), which is expected to be an essential part of smart cities. IoV originated from the merger of Vehicular ad hoc networks (VANET) and the Internet of things (IoT). Security is one of the main barriers in the on-road IoV implementation. Existing security standards are insufficient to meet the extremely dynamic and rapidly changing IoV requirements. Trust plays a vital role in ensuring security,… More >

Mohamed. A. H. Sabry^1,*, Ehab M. Almetwally², Hisham M. Almongy³, Gamal M. Ibrahim⁴

CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3737-3753, 2021, DOI:10.32604/cmc.2021.017510

Abstract In this paper, a joint analysis consisting of goodness-of-fit tests and Markov chain Monte Carlo simulations are used to assess the performance of some ranked set sampling designs. The Markov chain Monte Carlo simulations are conducted when Bayesian methods with Jeffery’s priors of the unknown parameters of Weibull distribution are used, while the goodness of fit analysis is conducted when the likelihood estimators are used and the corresponding empirical distributions are obtained. The ranked set sampling designs considered in this research are the usual ranked set sampling, extreme ranked set sampling, median ranked set sampling, and neoteric ranked set sampling… More >

Rashad Bantan¹, Amal S. Hassan², Ehab Almetwally³, M. Elgarhy⁴, Farrukh Jamal⁵, Christophe Chesneau⁶, Mahmoud Elsehetry^7,*

CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 2859-2875, 2021, DOI:10.32604/cmc.2021.015422

Abstract Accelerated life testing has been widely used in product life testing experiments because it can quickly provide information on the lifetime distributions by testing products or materials at higher than basic conditional levels of stress, such as pressure, temperature, vibration, voltage, or load to induce early failures. In this paper, a step stress partially accelerated life test (SS-PALT) is regarded under the progressive type-II censored data with random removals. The removals from the test are considered to have the binomial distribution. The life times of the testing items are assumed to follow length-biased weighted Lomax distribution. The maximum likelihood method… More >

Fulu Wei^1,2, Zhenggan Cai¹, Yongqing Guo^1,*, Pan Liu², Zhenyu Wang³, Zhibin Li²

Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 753-767, 2021, DOI:10.32604/iasc.2021.014661

Abstract The differences in traffic accident severity between urban and rural areas have been widely studied, but conclusions are still limited. To explore the factors influencing the occurrence of roadside accidents in urban and rural areas, 3735 roadside traffic accidents from 2017 to 2019 were analyzed. Fourteen variables from the aspects of driver, vehicle, driving environment, and other influencing factors were selected to establish a Bayesian binary logit model of roadside crashes. The deviance information criterion and receiver operating characteristic curve were used to test the goodness of fit for the traffic crash model. The results show that: (1) the Bayesian… More >

Mi Zichuan¹, Saddam Hussain¹, Zubair Ahmad^2,*, Omid Kharazmi³, Zahra Almaspoor²

Computer Systems Science and Engineering, Vol.38, No.1, pp. 79-92, 2021, DOI:10.32604/csse.2021.015146

Abstract Statistical distributions play a prominent role in applied sciences, particularly in biomedical sciences. The medical data sets are generally skewed to the right, and skewed distributions can be used quite effectively to model such kind of data sets. In the present study, therefore, we propose a new family of distributions suitable for modeling right-skewed medical data sets. The proposed family may be called a new generalized-X family. A special sub-model of the proposed family called a new generalized-Weibull distribution is discussed in detail. The maximum likelihood estimators of the model parameters are obtained. A brief Monte Carlo simulation study is… More >