Asad Ejaz¹, Yasir Nawaz¹, Muhammad Shoaib Arif^1,3,*, Daoud S. Mashat², Kamaleldin Abodayeh³

CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 489-506, 2022, DOI:10.32604/cmes.2022.019440

Abstract The present study is concerned with formulating a predator-prey eco-epidemiological mathematical model assuming that an infection exists in the predator species. The two classes of predator species (susceptible and infected) compete for the same sources available in the environment with the predation option. It is assumed that the disease does not spread vertically. The proposed model is analyzed for the stability of the coexistence of the predators and prey. The fixed points are carried out, and the coexisting fixed point is studied in detail by constructing the Lyapunov function. The movement of species in search of food or protection in… More >

Xiaowei Gu^1,#, Shuwen Chen^1,2,#,*, Huisheng Zhu¹, Mackenzie Brown^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 507-530, 2022, DOI:10.32604/cmes.2022.018948

Abstract Coronavirus disease 2019 brings a huge burden on the medical industry all over the world. In the background of artificial intelligence (AI) and Internet of Things (IoT) technologies, chest computed tomography (CT) and chest X-ray (CXR) scans are becoming more intelligent, and playing an increasingly vital role in the diagnosis and treatment of diseases. This paper will introduce the segmentation of methods and applications. CXR and CT diagnosis of COVID-19 based on deep learning, which can be widely used to fight against COVID-19. More >

Jian Xiong^1,*, Jinshui Yang², Hui Li³, Wu Xu⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 357-359, 2022, DOI:10.32604/cmes.2022.023418

Abstract This article has no abstract. More >

Debiao Meng^1,2,3, Shiyuan Yang¹, Tao Lin^4,5,*, Jiapeng Wang¹, Hengfei Yang¹, Zhiyuan Lv¹

CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 553-568, 2022, DOI:10.32604/cmes.2022.020756

Abstract Actual engineering systems will be inevitably affected by uncertain factors. Thus, the Reliability-Based Multidisciplinary Design Optimization (RBMDO) has become a hotspot for recent research and application in complex engineering system design. The Second-Order/First-Order Mean-Value Saddlepoint Approximate (SOMVSA/FOMVSA) are two popular reliability analysis strategies that are widely used in RBMDO. However, the SOMVSA method can only be used efficiently when the distribution of input variables is Gaussian distribution, which significantly limits its application. In this study, the Gaussian Mixture Model-based Second-Order Mean-Value Saddlepoint Approximation (GMM-SOMVSA) is introduced to tackle above problem. It is integrated with the Collaborative Optimization (CO) method to… More >

Evren Hincal, Amna Hashim Alzadjali

CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 393-411, 2022, DOI:10.32604/cmes.2022.019781

Abstract Excellent student’s academic performance is the uppermost priority and goal of educators and facilitators. The dubious marginal rate between admission and graduation rates unveils the rates of dropout and withdrawal from school. To improve the academic performance of students, we optimize the performance indices to the dynamics describing the academic performance in the form of nonlinear system ODE. We established the uniform boundedness of the model and the existence and uniqueness result. The independence and interdependence equilibria were found to be locally and globally asymptotically stable. The optimal control analysis was carried out, and lastly, numerical simulation was run to… More >

Mei Tao¹, Qingwen Ren^1,*, Hanbing Bian², Maosen Cao¹, Yun Jia³

CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 681-705, 2022, DOI:10.32604/cmes.2022.019522

Abstract Soil-rock mixture (SRM) filling in fault zone is an inhomogeneous geomaterial, which is composed of soil and rock block. It controls the deformation and stability of the abutment and dam foundation, and threatens the long-term safety of high arch dams. To study the macroscopic and mesoscopic mechanical properties of SRM, the development of a viable mesoscopic numerical simulation method with a mesoscopic model generation technology, and a reasonable parametric model is crucially desired to overcome the limitations of experimental conditions, specimen dimensions, and experiment fund. To this end, this study presents a mesoscopic numerical method for simulating the mechanical behavior… More >

Qiang Wu¹, Zhaoyang Han², Ghulam Mohiuddin³, Yongjun Ren^1,*

Computer Systems Science and Engineering, Vol.44, No.2, pp. 1633-1646, 2023, DOI:10.32604/csse.2023.030646

Abstract In the data communication system, the real-time information interaction of communication device increases the risk of privacy sensitive data being tampered with. Therefore, maintaining data security is one of the most important issues in network data communication. Because the timestamp is the most important way to authenticate data in information interaction, it is very necessary to provide timestamp service in the data communication system. However, the existing centralized timestamp mechanism is difficult to provide credible timestamp service, and users can conspire with timestamping servers to forge timestamps. Therefore, this paper designs a distributed timestamp mechanism based on continuous verifiable delay… More >

Nasser Ali Aljarallah^1,2, Ashit Kumar Dutta^3,*, Majed Alsanea⁴, Abdul Rahaman Wahab Sait⁵

Computer Systems Science and Engineering, Vol.44, No.2, pp. 1853-1868, 2023, DOI:10.32604/csse.2023.028755

Abstract A learning management system (LMS) is a software or web based application, commonly utilized for planning, designing, and assessing a particular learning procedure. Generally, the LMS offers a method of creating and delivering content to the instructor, monitoring students’ involvement, and validating their outcomes. Since mental health issues become common among studies in higher education globally, it is needed to properly determine it to improve mental stability. This article develops a new seven spot lady bird feature selection with optimal sparse autoencoder (SSLBFS-OSAE) model to assess students’ mental health on LMS. The major aim of the SSLBFS-OSAE model is to… More >

Pelin Yildirim Taser^*

Computer Systems Science and Engineering, Vol.44, No.2, pp. 1499-1516, 2023, DOI:10.32604/csse.2023.028083

Abstract Predictive Maintenance is a type of condition-based maintenance that assesses the equipment's states and estimates its failure probability and when maintenance should be performed. Although machine learning techniques have been frequently implemented in this area, the existing studies disregard to the natural order between the target attribute values of the historical sensor data. Thus, these methods cause losing the inherent order of the data that positively affects the prediction performances. To deal with this problem, a novel approach, named Ordinal Multi-dimensional Classification (OMDC), is proposed for estimating the conditions of a hydraulic system's four components by taking into the natural… More >

R. Soundhara Raja Pandian^*, C. Christopher Columbus

Computer Systems Science and Engineering, Vol.44, No.2, pp. 1749-1762, 2023, DOI:10.32604/csse.2023.028014

Abstract Currently, e-learning is one of the most prevalent educational methods because of its need in today’s world. Virtual classrooms and web-based learning are becoming the new method of teaching remotely. The students experience a lack of access to resources commonly the educational material. In remote locations, educational institutions face significant challenges in accessing various web-based materials due to bandwidth and network infrastructure limitations. The objective of this study is to demonstrate an optimization and queueing technique for allocating optimal servers and slots for users to access cloud-based e-learning applications. The proposed method provides the optimization and queueing algorithm for multi-server… More >