Malik Muhammad Ali Shahid¹, Shahida Sulaiman², Mohammed Al-Sarem^3,4, Aqeel Ur Rahman¹, Salman Iqbal¹, Rab Nawaz Bashir¹, Arfat Ahmad Khan^5,6, Momen M. Alrawi⁷, Rashiq R. Marie⁸, Settawit Poochaya^5,*

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6641-6663, 2023, DOI:10.32604/cmc.2023.031459

Abstract

Conventionally, the reliability of a web portal is validated with generalized conventional methods, but they fail to provide the desired results. Therefore, we need to include other quality factors that affect reliability such as usability for improving the reliability in addition to the conventional reliability testing. Actually, the primary objectives of web portals are to provide interactive integration of multiple functions confirming diverse requirements in an efficient way. In this paper, we employ testing profiles to measure the reliability through software operational profile, input space profile and usability profile along with qualitative measures of reliability and usability. Moreover, the case… More >

Ting Wang^1,#, Jin Kuang^1,#, Fabian Herold², Alyx Taylor³, Sebastian Ludyga⁴, Zhihao Zhang¹, Arthur F. Kramer^5,6, Liye Zou^1,*

International Journal of Mental Health Promotion, Vol.25, No.1, pp. 127-138, 2023, DOI:10.32604/ijmhp.2022.022504

Abstract The rising prevalence of physical inactivity is in all age groups (e.g., in college students) a major public health issue as not meeting the recommended minimum amount of regular physical activity is linked to adverse health events. Vice versa, there is mounting evidence that achieving the recommended amount of regular physical activity is a vital element to prevent chronic diseases, but there is often an insufficient adherence to planned and structured forms of physical activity (i.e., physical exercises). In this context, there is a large body of evidence indicating that exercise adherence is, among other factors, influenced by exercise-related affective… More >

Rong Yuan¹, Ruitao Chen², Haiqing Li^3,*, Wenke Yang¹, Xiaoxiao Li¹

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 2331-2347, 2023, DOI:10.32604/cmes.2023.023788

Abstract Wind power is a kind of important green energy. Thus, wind turbines have been widely utilized around the world. Wind turbines are composed of many important components. Among these components, the failure rate of the transmission system is relatively high in wind turbines. It is because the components are subjected to aerodynamic loads for a long time. In addition, its inertial load will result in fatigue fracture, wear and other problems. In this situation, wind turbines have to be repaired at a higher cost. Moreover, the traditional reliability methods are difficult to deal with the above challenges when performing the… More >

Qiang Qin^1,2,*, Xiaolei Cao¹, Shengpeng Zhang¹

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.2, pp. 1457-1480, 2023, DOI:10.32604/cmes.2023.022078

Abstract In this work, an improved active kriging method based on the AK-IS and truncated importance sampling (TIS) method is proposed to efficiently evaluate structural reliability. The novel method called AWK-TIS is inspired by AK-IS and RBF-GA previously published in the literature. The innovation of the AWK-TIS is that TIS is adopted to lessen the sample pool size significantly, and the whale optimization algorithm (WOA) is employed to acquire the optimal Kriging model and the most probable point (MPP). To verify the performance of the AWK-TIS method for structural reliability, four numerical cases which are utilized as benchmarks in literature and… More >

Hamayun Khan^1,*, Irfan Ud Din², Arshad Ali³, Mohammad Husain³

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 2097-2113, 2023, DOI:10.32604/cmc.2023.032999

Abstract Minimizing the energy consumption to increase the life span and performance of multiprocessor system on chip (MPSoC) has become an integral chip design issue for multiprocessor systems. The performance measurement of computational systems is changing with the advancement in technology. Due to shrinking and smaller chip size power densities on-chip are increasing rapidly that increasing chip temperature in multi-core embedded technologies. The operating speed of the device decreases when power consumption reaches a threshold that causes a delay in complementary metal oxide semiconductor (CMOS) circuits because high on-chip temperature adversely affects the life span of the chip. In this paper… More >

Hamayun Khan^1,*, Irfan Ud din², Arshad Ali³, Sami Alshmrany³

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 965-981, 2023, DOI:10.32604/cmc.2023.031223

Abstract Increasing the life span and efficiency of Multiprocessor System on Chip (MPSoC) by reducing power and energy utilization has become a critical chip design challenge for multiprocessor systems. With the advancement of technology, the performance management of central processing unit (CPU) is changing. Power densities and thermal effects are quickly increasing in multi-core embedded technologies due to shrinking of chip size. When energy consumption reaches a threshold that creates a delay in complementary metal oxide semiconductor (CMOS) circuits and reduces the speed by 10%–15% because excessive on-chip temperature shortens the chip’s life cycle. In this paper, we address the scheduling… More >

Yunwen Feng¹, Zhicen Song^1,*, Cheng Lu²

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.3, pp. 1925-1942, 2023, DOI:10.32604/cmes.2022.022680

Abstract To effectively predict the mechanical dispatch reliability (MDR), the artificial neural networks method combined with aircraft operation health status parameters is proposed, which introduces the real civil aircraft operation data for verification, to improve the modeling precision and computing efficiency. Grey relational analysis can identify the degree of correlation between aircraft system health status (such as the unscheduled maintenance event, unit report event, and services number) and dispatch release and screen out the most closely related systems to determine the set of input parameters required for the prediction model. The artificial neural network using radial basis function (RBF) as a… More >

Pengyu Chen, Cunbao Zhao^*, He Yao, Junliang Li

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.3, pp. 2057-2071, 2023, DOI:10.32604/cmes.2022.022394

Abstract Multiple failure modes tend to be identified in the reliability analysis of a redundant truss structure. This identification process involves updating the model for identifying the next potential failure members. Herein we intend to update the finite element model automatically in the identification process of failure modes and further perform the system reliability analysis efficiently. This study presents a framework that is implemented through the joint simulation of MATLAB and APDL and consists of three parts: reliability index of a single member, identification of dominant failure modes, and system-level reliability analysis for system reliability analysis of truss structures. Firstly, RSM… More > Graphic Abstract

Yongqiang Guo^1,2,*, Zhiyuan Lv³

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.3, pp. 1855-1870, 2023, DOI:10.32604/cmes.2022.022211

Abstract In uncertainty analysis and reliability-based multidisciplinary design and optimization (RBMDO) of engineering structures, the saddlepoint approximation (SA) method can be utilized to enhance the accuracy and efficiency of reliability evaluation. However, the random variables involved in SA should be easy to handle. Additionally, the corresponding saddlepoint equation should not be complicated. Both of them limit the application of SA for engineering problems. The moment method can construct an approximate cumulative distribution function of the performance function based on the first few statistical moments. However, the traditional moment matching method is not very accurate generally. In order to take advantage of… More >

Hong Zhang¹, Lukai Song^1,2,*, Guangchen Bai¹

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.3, pp. 1871-1897, 2023, DOI:10.32604/cmes.2022.021880

Abstract

The reliability and sensitivity analyses of stator blade regulator usually involve complex characteristics like high-nonlinearity, multi-failure regions, and small failure probability, which brings in unacceptable computing efficiency and accuracy of the current analysis methods. In this case, by fitting the implicit limit state function (LSF) with active Kriging (AK) model and reducing candidate sample pool with adaptive importance sampling (AIS), a novel AK-AIS method is proposed. Herein, the AK model and Markov chain Monte Carlo (MCMC) are first established to identify the most probable failure region(s) (MPFRs), and the adaptive kernel density estimation (AKDE) importance sampling function is constructed to… More >