Uzma Afzal¹, Tariq Mahmood², Ali Mustafa Qamar^3,*, Ayaz H. Khan^4,5

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 6251-6267, 2023, DOI:10.32604/cmc.2023.037653

Abstract A complex Laboratory Developed Test (LDT) is a clinical test developed within a single laboratory. It is typically configured from many feature constraints from clinical repositories, which are part of the existing Laboratory Information Management System (LIMS). Although these clinical repositories are automated, support for managing patient information with test results of an LDT is also integrated within the existing LIMS. Still, the support to configure LDTs design needs to be made available even in standard LIMS packages. The manual configuration of LDTs is a complex process and can generate configuration inconsistencies because many constraints between features can remain unsatisfied.… More >

Mohammad Yamin^1,*, Tom Gedeon², Saleh Bajaba³, Mona M. Abusurrah⁴

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5659-5674, 2023, DOI:10.32604/cmc.2023.034005

Abstract In recent years, the demand for biometric-based human recognition methods has drastically increased to meet the privacy and security requirements. Palm prints, palm veins, finger veins, fingerprints, hand veins and other anatomic and behavioral features are utilized in the development of different biometric recognition techniques. Amongst the available biometric recognition techniques, Finger Vein Recognition (FVR) is a general technique that analyzes the patterns of finger veins to authenticate the individuals. Deep Learning (DL)-based techniques have gained immense attention in the recent years, since it accomplishes excellent outcomes in various challenging domains such as computer vision, speech detection and Natural Language… More >

Yanjun Zhang¹, Yongqiang He², Jingbo Zhang¹, Yaru Zhao³, Zhihua Cui^1,*, Wensheng Zhang⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 363-383, 2023, DOI:10.32604/cmes.2023.025832

Abstract The video compression sensing method based on multi hypothesis has attracted extensive attention in the research of video codec with limited resources. However, the formation of high-quality prediction blocks in the multi hypothesis prediction stage is a challenging task. To resolve this problem, this paper constructs a novel compressed sensing-based high-quality adaptive video reconstruction optimization method. It mainly includes the optimization of prediction blocks (OPBS), the selection of search windows and the use of neighborhood information. Specifically, the OPBS consists of two parts: the selection of blocks and the optimization of prediction blocks. We combine the high-quality optimization reconstruction of… More >

Cun Wei¹, Yunpeng Zhao^2,*, Mingyang Cong¹, Zhigang Zhou^1,*, Jingzan Yan³, Ruixin Wang¹, Zhuoyang Li¹, Jing Liu¹

Energy Engineering, Vol.120, No.6, pp. 1465-1484, 2023, DOI:10.32604/ee.2023.026337

Abstract With increasing renewable energy utilization, the industry needs an accurate tool to select and size renewable energy equipment and evaluate the corresponding renewable energy plans. This study aims to bring new insights into sustainable and energy-efficient urban planning by developing a practical method for optimizing the production of renewable energy and carbon emission in urban areas. First, we provide a detailed formulation to calculate the renewable energy demand based on total energy demand. Second, we construct a dual-objective optimization model that represents the life cycle cost and carbon emission of renewable energy systems, after which we apply the differential evolution… More >

Muhammad Zulkifl Hasan^*, Zurina Mohd Hanapi, Muhammad Zunnurain Hussain

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 4065-4084, 2023, DOI:10.32604/cmc.2023.036444

Abstract A computer network can be defined as many computing devices connected via a communication medium like the internet. Computer network development has proposed how humans and devices communicate today. These networks have improved, facilitated, and made conventional forms of communication easier. However, it has also led to uptick in-network threats and assaults. In 2022, the global market for information technology is expected to reach $170.4 billion. However, in contrast, 95% of cyber security threats globally are caused by human action. These networks may be utilized in several control systems, such as home-automation, chemical and physical assault detection, intrusion detection, and… More >

Ming Cheng¹, Shiming Li^1,3,*, Yuhe Wang¹, Guohui Zhou¹, Peng Han¹, Yan Zhao²

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2527-2555, 2023, DOI:10.32604/cmc.2023.036427

Abstract To address the problem of network security situation assessment in the Industrial Internet, this paper adopts the evidential reasoning (ER)algorithm and belief rule base (BRB) method to establish an assessment model. First, this paper analyzes the influencing factors of the Industrial Internet and selects evaluation indicators that contain not only quantitative data but also qualitative knowledge. Second, the evaluation indicators are fused with expert knowledge and the ER algorithm. According to the fusion results, a network security situation assessment model of the Industrial Internet based on the ER and BRB method is established, and the projection covariance matrix adaptive evolution… More >

Edson Vinicius Pontes Bastos^1,*, Jorge Junio Moreira Antunes², Lino Guimarães Marujo¹, Peter Fernandes Wanke², Roberto Ivo da Rocha Lima Filho¹

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3175-3190, 2023, DOI:10.32604/iasc.2023.034582

Abstract Stock markets exhibit Brownian movement with random, non-linear, uncertain, evolutionary, non-parametric, nebulous, chaotic characteristics and dynamism with a high degree of complexity. Developing an algorithm to predict returns for decision-making is a challenging goal. In addition, the choice of variables that will serve as input to the model represents a non-triviality, since it is possible to observe endogeneity problems between the predictor and the predicted variables. Thus, the goal is to analyze the endogenous origin of the stock return prediction model based on technical indicators. For this, we structure a feed-forward neural network. We evaluate the endogenous feedback between the… More >

Ierin Babu^1,*, R. MathuSoothana², S. Kumar²

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3621-3636, 2023, DOI:10.32604/iasc.2023.033791

Abstract Educational Data Mining (EDM) is an emergent discipline that concentrates on the design of self-learning and adaptive approaches. Higher education institutions have started to utilize analytical tools to improve students’ grades and retention. Prediction of students’ performance is a difficult process owing to the massive quantity of educational data. Therefore, Artificial Intelligence (AI) techniques can be used for educational data mining in a big data environment. At the same time, in EDM, the feature selection process becomes necessary in creation of feature subsets. Since the feature selection performance affects the predictive performance of any model, it is important to elaborately… More >

Wenchao Yi, Zhilei Lin, Yong Chen, Zhi Pei^*, Jiansha Lu

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2841-2860, 2023, DOI:10.32604/cmes.2023.027055

Abstract Effective constrained optimization algorithms have been proposed for engineering problems recently. It is common to consider constraint violation and optimization algorithm as two separate parts. In this study, a pbest selection mechanism is proposed to integrate the current mutation strategy in constrained optimization problems. Based on the improved pbest selection method, an adaptive differential evolution approach is proposed, which helps the population jump out of the infeasible region. If all the individuals are infeasible, the top 5% of infeasible individuals are selected. In addition, a modified truncated ε-level method is proposed to avoid trapping in infeasible regions. The proposed adaptive… More > Graphic Abstract

Ying Wang^*, Zheng Yan, Yangyang Wu

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1339-1370, 2023, DOI:10.32604/cmes.2023.025830

Abstract In this paper, a numerical model of fretting fatigue analysis of cable wire and the fretting fatigue damage constitutive model considering the multi-axis effect were established, and the user material subroutine UMAT was written. Then, the constitutive model of wear morphology evolution of cable wire and the constitutive model of pitting evolution considering the mechanical-electrochemical effect were established, respectively. The corresponding subroutines UMESHMOTION_Wear and UMESHMOTION_Wear_Corrosion were written, and the fretting fatigue life was further predicted. The results show that the numerical simulation life obtained by the program in this paper has the same trend as the tested one; the error… More > Graphic Abstract