Liang Zeng^1,2, Junyang Shi¹, Yanyan Li¹, Shanshan Wang^1,2,*, Weigang Li³

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 375-392, 2024, DOI:10.32604/cmc.2023.045803

Abstract The job shop scheduling problem is a classical combinatorial optimization challenge frequently encountered in manufacturing systems. It involves determining the optimal execution sequences for a set of jobs on various machines to maximize production efficiency and meet multiple objectives. The Non-dominated Sorting Genetic Algorithm III (NSGA-III) is an effective approach for solving the multi-objective job shop scheduling problem. Nevertheless, it has some limitations in solving scheduling problems, including inadequate global search capability, susceptibility to premature convergence, and challenges in balancing convergence and diversity. To enhance its performance, this paper introduces a strengthened dominance relation NSGA-III algorithm based on differential evolution… More >

Abidhan Bardhan^1,*, Raushan Kumar Singh², Mohammed Alatiyyah³, Sulaiman Abdullah Alateyah^4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1521-1555, 2024, DOI:10.32604/cmes.2023.044467

Abstract This research proposes a highly effective soft computing paradigm for estimating the compressive strength (CS) of metakaolin-contained cemented materials. The proposed approach is a combination of an enhanced grey wolf optimizer (EGWO) and an extreme learning machine (ELM). EGWO is an augmented form of the classic grey wolf optimizer (GWO). Compared to standard GWO, EGWO has a better hunting mechanism and produces an optimal performance. The EGWO was used to optimize the ELM structure and a hybrid model, ELM-EGWO, was built. To train and validate the proposed ELM-EGWO model, a sum of 361 experimental results featuring five influencing factors was… More >

Kolli Ramujee^1,*, Pooja Sadula¹, Golla Madhu², Sandeep Kautish³, Abdulaziz S. Almazyad⁴, Guojiang Xiong⁵, Ali Wagdy Mohamed^6,7,*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1455-1486, 2024, DOI:10.32604/cmes.2023.043384

Abstract Geopolymer concrete emerges as a promising avenue for sustainable development and offers an effective solution to environmental problems. Its attributes as a non-toxic, low-carbon, and economical substitute for conventional cement concrete, coupled with its elevated compressive strength and reduced shrinkage properties, position it as a pivotal material for diverse applications spanning from architectural structures to transportation infrastructure. In this context, this study sets out the task of using machine learning (ML) algorithms to increase the accuracy and interpretability of predicting the compressive strength of geopolymer concrete in the civil engineering field. To achieve this goal, a new approach using convolutional… More >

Hayder Makki Shakir, Jaber Karimpour^*, Jafar Razmara

Computer Systems Science and Engineering, Vol.48, No.1, pp. 35-55, 2024, DOI:10.32604/csse.2023.038545

Abstract As the volume of data and data-generating equipment in healthcare settings grows, so do issues like latency and inefficient processing inside health monitoring systems. The Internet of Things (IoT) has been used to create a wide variety of health monitoring systems. Most modern health monitoring solutions are based on cloud computing. However, large-scale deployment of latency-sensitive healthcare applications is hampered by the cloud’s design, which introduces significant delays during the processing of vast data volumes. By strategically positioning servers close to end users, fog computing mitigates latency issues and dramatically improves scaling on demand, resource accessibility, and security. In this… More >

Kunjian Wang¹, Ruibin He¹, Qianhua Liao¹, Kun Xu¹, Wen Wang¹, Kan Chen^2,*

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.3, pp. 563-578, 2024, DOI:10.32604/fdmp.2023.030152

Abstract Fault fractures usually have large openings and considerable extension. Accordingly, cross-linked gel materials are generally considered more suitable plugging agents than water-based gels because the latter often undergo contamination via formation water, which prevents them from being effective over long times. Hence, in this study, a set of oil-based composite gels based on waste grease and epoxy resin has been developed. These materials have been observed to possess high compressive strength and resistance to the aforementioned contamination, thereby leading to notable increase in plugging success rate. The compressive strength, thickening time, and resistance to formation water pollution of these gels… More >

Yulan Yu^1,2, Rassamee Chotipanvithayakul³, Hujiao Kuang⁴, Wit Wichaidit^3,*, Chonghua Wan^1,2,*

International Journal of Mental Health Promotion, Vol.25, No.12, pp. 1343-1351, 2023, DOI:10.32604/ijmhp.2023.043446

Abstract Adverse childhood experiences (ACEs) can negatively affect mental health, whereas character strengths seem to be positively correlated with mental health. Detailed information on the history of ACEs among university students in China and the extent which mental health is associated with ACEs and character strengths can contribute to the needed empirical evidence for relevant stakeholders. Objectives of this study are 1) to estimate the prevalence of ACEs among undergraduate students in Southern China; and 2) to assess the extent which mental health outcomes (positive growth, well-being, and depression) are associated with ACEs and character strengths among undergraduate students in Southern… More >

Hongxia Wang^1,2, Zhiqiang Duan², Qingwei Guo², Yongmei Zhang^1,2,*, Yuhong Zhao^2,3,4,*

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1393-1409, 2023, DOI:10.32604/cmc.2023.045871

Abstract Due to the large unexplored compositional space, long development cycle, and high cost of traditional trial-anderror experiments, designing high strength aluminum-lithium alloys is a great challenge. This work establishes a performance-oriented machine learning design strategy for aluminum-lithium alloys to simplify and shorten the development cycle. The calculation results indicate that radial basis function (RBF) neural networks exhibit better predictive ability than back propagation (BP) neural networks. The RBF neural network predicted tensile and yield strengths with determination coefficients of 0.90 and 0.96, root mean square errors of 30.68 and 25.30, and mean absolute errors of 28.15 and 19.08, respectively. In… More >

Daisuke Ishihara^*, Naoto Takayama

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1237-1258, 2024, DOI:10.32604/cmes.2023.030211

Abstract In this study, we propose an algorithm selection method based on coupling strength for the partitioned analysis of structure-piezoelectric-circuit coupling, which includes two types of coupling or inverse and direct piezoelectric coupling and direct piezoelectric and circuit coupling. In the proposed method, implicit and explicit formulations are used for strong and weak coupling, respectively. Three feasible partitioned algorithms are generated, namely (1) a strongly coupled algorithm that uses a fully implicit formulation for both types of coupling, (2) a weakly coupled algorithm that uses a fully explicit formulation for both types of coupling, and (3) a partially strongly coupled and… More >

Huifeng Yang, Mingwang Wu, Rixin Gu, Hang Cao, Kai Xiao, Benkai Shi^*

Journal of Renewable Materials, Vol.11, No.12, pp. 4175-4195, 2023, DOI:10.32604/jrm.2023.028507

Abstract This article presents experimental results of steel-timber-steel (STS) joints loaded parallel to grain. Eight groups of specimens were designed, and tensile tests were performed. The fastener types and fastener numbers were considered to evaluate the tensile strengths and ductility performances of the STS joints. The screws with 6 mm diameter and the innovative steel-tubes with 18 mm diameter were adopted as connecting fasteners. The experimental results were discussed in terms of yielding and ultimate strengths, slip stiffness, and ductility factors. The ductility classification and failure mechanisms of each group of specimens were analyzed. It was demonstrated that the STS joint… More >

Cheng Hu^1,2, Weiheng Xiang^1,3,*, Ping Chen^2,3, Yi Yang^4,5, Libo Zhou³, Jiufang Jiang⁵, Shunkai Li^2,4, Yang Ming¹, Qing Li³

Journal of Renewable Materials, Vol.11, No.11, pp. 3945-3956, 2023, DOI:10.32604/jrm.2023.027544

Abstract The aim of this study is to enhance the value and utilization of red mud generated in the Bayer process by preparing composite cement mortars. The effects of two different types of Bayer red mud with varying physical and chemical characteristics on the fluidity, mechanical strength, mineral composition, and microstructure of the composite cement mortar were systematically evaluated. The results showed that the optimal addition of red mud A was 10 wt%, while it was 20 wt% for red mud B. The mechanical properties of the composite cement mortar met the standards for P·O42.5 cement. Furthermore, the composite mortar with… More >