Zhihui Xu¹, Shuwen Shang², Yuntong Pu³, Xiaoyan Su^2,*, Hong Qian², Xiaolei Pan²

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2597-2617, 2024, DOI:10.32604/cmes.2023.031247

Abstract Cognitive Reliability and Error Analysis Method (CREAM) is widely used in human reliability analysis (HRA). It defines nine common performance conditions (CPCs), which represent the factors that may affect human reliability and are used to modify the cognitive failure probability (CFP). However, the levels of CPCs are usually determined by domain experts, which may be subjective and uncertain. What’s more, the classic CREAM assumes that the CPCs are independent, which is unrealistic. Ignoring the dependence among CPCs will result in repeated calculations of the influence of the CPCs on CFP and lead to unreasonable reliability evaluation. To address the issue… More > Graphic Abstract

Refah Alotaibi¹, Mazen Nassar^2,3, Ahmed Elshahhat^4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2571-2596, 2024, DOI:10.32604/cmes.2023.030582

Abstract A novel extended Lindley lifetime model that exhibits unimodal or decreasing density shapes as well as increasing, bathtub or unimodal-then-bathtub failure rates, named the Marshall-Olkin-Lindley (MOL) model is studied. In this research, using a progressive Type-II censored, various inferences of the MOL model parameters of life are introduced. Utilizing the maximum likelihood method as a classical approach, the estimators of the model parameters and various reliability measures are investigated. Against both symmetric and asymmetric loss functions, the Bayesian estimates are obtained using the Markov Chain Monte Carlo (MCMC) technique with the assumption of independent gamma priors. From the Fisher information… More >

Xiaoyan Su^1,*, Shuwen Shang¹, Zhihui Xu², Hong Qian¹, Xiaolei Pan¹

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1813-1826, 2024, DOI:10.32604/cmes.2023.030957

Abstract With the improvement of equipment reliability, human factors have become the most uncertain part in the system. The standardized Plant Analysis of Risk-Human Reliability Analysis (SPAR-H) method is a reliable method in the field of human reliability analysis (HRA) to evaluate human reliability and assess risk in large complex systems. However, the classical SPAR-H method does not consider the dependencies among performance shaping factors (PSFs), which may cause overestimation or underestimation of the risk of the actual situation. To address this issue, this paper proposes a new method to deal with the dependencies among PSFs in SPAR-H based on the… More > Graphic Abstract

Qing Xia¹, Yonghua Li^2,*, Dongxu Zhang², Yufeng Wang²

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1769-1794, 2024, DOI:10.32604/cmes.2023.030724

Abstract For high-reliability systems in military, aerospace, and railway fields, the challenges of reliability analysis lie in dealing with unclear failure mechanisms, complex fault relationships, lack of fault data, and uncertainty of fault states. To overcome these problems, this paper proposes a reliability analysis method based on T-S fault tree analysis (T-S FTA) and Hyper-ellipsoidal Bayesian network (HE-BN). The method describes the connection between the various system fault events by T-S fuzzy gates and translates them into a Bayesian network (BN) model. Combining the advantages of T-S fault tree modeling with the advantages of Bayesian network computation, a reliability modeling method… More >

Shuo Cai¹, Tingyu Luo¹, Fei Yu^1,*, Pradip Kumar Sharma², Weizheng Wang¹, Lairong Yin³

CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 2763-2777, 2023, DOI:10.32604/cmc.2023.037825

Abstract In the Internet of Things (IoT) system, relay communication is widely used to solve the problem of energy loss in long-distance transmission and improve transmission efficiency. In Body Sensor Network (BSN) systems, biosensors communicate with receiving devices through relay nodes to improve their limited energy efficiency. When the relay node fails, the biosensor can communicate directly with the receiving device by releasing more transmitting power. However, if the remaining battery power of the biosensor is insufficient to enable it to communicate directly with the receiving device, the biosensor will be isolated by the system. Therefore, a new combinatorial analysis method… More >

Abdulrahman M. Abdulghani, Wilbur L. Walters, Khalid H. Abed^*

Journal of Blockchain and Intelligent Computing, Vol.1, pp. 1-13, 2023, DOI:10.32604/jbic.2023.041340

Abstract Blockchain technology is increasingly used to design trustworthy and reliable platforms for sharing information in a plethora of industries. It is a decentralized system that acts as an immutable record for storing data. It has the potential to disrupt a range of fields that rely on data, including autonomous systems like Unmanned Aerial Vehicles (UAVs). In this paper, we propose a framework based on blockchain and distributed ledger technology to improve transmission time and provide a secured and trusted method for UAVs to transfer data to the consumer efficiently while maintaining data reliability. The results show that our framework enables… More >

Tiantian Liang^*, Runze Wang, Xuxiu Zhang, Yingdong Wang, Jianxiong Yang

Structural Durability & Health Monitoring, Vol.17, No.5, pp. 433-455, 2023, DOI:10.32604/sdhm.2023.029331

Abstract In this study, an optimized long short-term memory (LSTM) network is proposed to predict the reliability and remaining useful life (RUL) of rolling bearings based on an improved whale-optimized algorithm (IWOA). The multi-domain features are extracted to construct the feature dataset because the single-domain features are difficult to characterize the performance degeneration of the rolling bearing. To provide covariates for reliability assessment, a kernel principal component analysis is used to reduce the dimensionality of the features. A Weibull distribution proportional hazard model (WPHM) is used for the reliability assessment of rolling bearing, and a beluga whale optimization (BWO) algorithm is… More > Graphic Abstract

Ting Wang¹, Markus Gerber², Fabian Herold³, Joseph Bardeen⁴, Sebastian Ludyga², Alyx Taylor⁵, Arthur F. Kramer^6,7, Liye Zou^1,*

International Journal of Mental Health Promotion, Vol.25, No.9, pp. 995-1008, 2023, DOI:10.32604/ijmhp.2023.029804

Abstract Affective exercise experience as an emerging theoretical concept has great potential to provide a more nuanced understanding of individual factors that influence exercise behavior. However, concerning the Affective Exercise Experiences (AFFEXX) questionnaire, it has not been examined yet whether the structural score of the AFFEXX is a useful index to predict physical activity (refers to any bodily movement produced by skeletal muscles that requires energy expenditure). Furthermore, there is currently a gap in knowledge regarding the psychological mechanisms that can explain the relationship between affective exercise experiences and the level of physical activity (PA). In order to adress these gaps… More >

Heba S. Mohammed¹, Mazen Nassar^2,3, Refah Alotaibi¹, Ahmed Elshahhat^4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2761-2793, 2023, DOI:10.32604/cmes.2023.028826

Abstract A new extended exponential lifetime model called Harris extended-exponential (HEE) distribution for data modelling with increasing and decreasing hazard rate shapes has been considered. In the reliability context, researchers prefer to use censoring plans to collect data in order to achieve a compromise between total test time and/or test sample size. So, this study considers both maximum likelihood and Bayesian estimates of the Harris extended-exponential distribution parameters and some of its reliability indices using a progressive Type-II censoring strategy. Under the premise of independent gamma priors, the Bayesian estimation is created using the squared-error and general entropy loss functions. Due… More >

Yousif Sufyan Jghef¹, Mohammed Jasim Mohammed Jasim², Subhi R. M. Zeebaree^3,*, Rizgar R. Zebari⁴

Computer Systems Science and Engineering, Vol.47, No.2, pp. 1651-1664, 2023, DOI:10.32604/csse.2023.037449

Abstract Wireless Sensor Networks (WSNs) gather data in physical environments, which is some type. These ubiquitous sensors face several challenges responsible for corrupting them (mostly sensor failure and intrusions in external agents). WSNs were disposed to error, and effectual fault detection techniques are utilized for detecting faults from WSNs in a timely approach. Machine learning (ML) was extremely utilized for detecting faults in WSNs. Therefore, this study proposes a billiards optimization algorithm with modified deep learning for fault detection (BIOMDL-FD) in WSN. The BIOMDLFD technique mainly concentrates on identifying sensor faults to enhance network efficiency. To do so, the presented BIOMDL-FD… More >