Hasan Sh. Majdi^a , Ammar Abdulkadhim^b,* , Azher M. Abed^b

Frontiers in Heat and Mass Transfer, Vol.12, pp. 1-14, 2019, DOI:10.5098/hmt.12.2

Abstract Fluid flow and natural convection heat transfer in a parallelogram enclosure with an inner circular cylinder using Cu-water nanofluid are studied numerically. Dimensionless Navier-Stokes and energy equations are solved numerically using finite element method based two-dimensional flow and steady-state conditions. This study evaluates the effect of different concentrations of Cu-water nanofluids (0% to 6%) with different Rayleigh numbers 10³ ≤ Ra ≤ 10⁶ under isotherm wall temperatures. The effects of geometrical parameters of the parallelogram enclosure (inclination angle in range of 0 ≤ α ≤ 30 and location of inner circular cylinder -0.2 ≤ H ≤ +0.2 on the flow… More >

Shehab Abdulhabib Alzaeemi¹, Kim Gaik Tay^1,*, Audrey Huong¹, Saratha Sathasivam², Majid Khan bin Majahar Ali²

Computer Systems Science and Engineering, Vol.47, No.1, pp. 1163-1184, 2023, DOI:10.32604/csse.2023.038912

Abstract Radial Basis Function Neural Network (RBFNN) ensembles have long suffered from non-efficient training, where incorrect parameter settings can be computationally disastrous. This paper examines different evolutionary algorithms for training the Symbolic Radial Basis Function Neural Network (SRBFNN) through the behavior’s integration of satisfiability programming. Inspired by evolutionary algorithms, which can iteratively find the near-optimal solution, different Evolutionary Algorithms (EAs) were designed to optimize the producer output weight of the SRBFNN that corresponds to the embedded logic programming 2Satisfiability representation (SRBFNN-2SAT). The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA),… More >

Muhammad Aasim Qureshi^1,*, Muhammad Asif², Saira Anwar³

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 439-453, 2023, DOI:10.32604/iasc.2023.036102

Abstract Learning programming and using programming languages are the essential aspects of computer science education. Students use programming languages to write their programs. These computer programs (students or practitioners written) make computers artificially intelligent and perform the tasks needed by the users. Without these programs, the computer may be visioned as a pointless machine. As the premise of writing programs is situated with specific programming languages, enormous efforts have been made to develop and create programming languages. However, each programming language is domain-specific and has its nuances, syntax and semantics, with specific pros and cons. These language-specific details, including syntax and… More >

Zainab Kareem Ghoben^a,*,†, Ahmed Kadhim Hussein^b

Frontiers in Heat and Mass Transfer, Vol.18, pp. 1-11, 2022, DOI:10.5098/hmt.18.6

Abstract he numerical analysis of a V-shaped baffle effect on the natural convection inside a parallelogrammical cavity filled with two different water-based nanofluids (Al2O3 and Cu) were studied in this work. The enclosure walls were maintained at a constant hot and cold temperatures on the left and right walls sequentially. The horizontal walls were isolated, while the baffles located on the right wall and sharing the same cold temperature with it. The finite element method was used to derive and solve the governing equations. The flow and thermal fields computed for different arrangements of: the number of baffles inside the cavity… More >

Khalil Chebil^1,2, Skander Htiouech³, Mahdi Khemakhem^1,2,4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 233-263, 2023, DOI:10.32604/cmes.2023.026476

Abstract Crowd management and analysis (CMA) systems have gained a lot of interest in the vulgarization of unmanned aerial vehicles (UAVs) use. Crowd tracking using UAVs is among the most important services provided by a CMA. In this paper, we studied the periodic crowd-tracking (PCT) problem. It consists in using UAVs to follow-up crowds, during the life-cycle of an open crowded area (OCA). Two criteria were considered for this purpose. The first is related to the CMA initial investment, while the second is to guarantee the quality of service (QoS). The existing works focus on very specified assumptions that are highly… More >

WEI BAO^1,#, QIANGUANG HAN^2,#, XIAO GUAN³, ZIJIE WANG², MIN GU^1,2,*

Oncology Research, Vol.31, No.2, pp. 181-192, 2023, DOI:10.32604/or.2023.028051

Abstract Background: Clear-cell renal cell carcinoma (ccRCC) is the most common malignant kidney cancer. However, the tumor microenvironment and crosstalk involved in metabolic reprogramming in ccRCC are not well-understood. Methods: We used The Cancer Genome Atlas to obtain ccRCC transcriptome data and clinical information. The E-MTAB-1980 cohort was used for external validation. The GENECARDS database contains the first 100 solute carrier (SLC)-related genes. The predictive value of SLC-related genes for ccRCC prognosis and treatment was assessed using univariate Cox regression analysis. An SLC-related predictive signature was developed through Lasso regression analysis and used to determine the risk profiles of patients with… More >

Hanen Yaakoubi¹, Hegazy Rezk², Mujahed Al-Dhaifallah^3,4,*, Joseph Haggège¹

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3657-3675, 2023, DOI:10.32604/cmc.2023.034929

Abstract The present paper aims at validating a Model Predictive Control (MPC), based on the Mixed Logical Dynamical (MLD) model, for Hybrid Dynamic Systems (HDSs) that explicitly involve continuous dynamics and discrete events. The proposed benchmark system is a three-tank process, which is a typical case study of HDSs. The MLD-MPC controller is applied to the level control of the considered tank system. The study is initially focused on the MLD approach that allows consideration of the interacting continuous dynamics with discrete events and includes the operating constraints. This feature of MLD modeling is very advantageous when an MPC controller synthesis… More >

Min Hu^1,2,3, Zhimin Chen⁴, Yuan Xia⁴, Liping Zhang^1,2,3,*, Qiuhua Tang^1,2,3

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2815-2840, 2023, DOI:10.32604/cmes.2023.027146

Abstract The multi-skill resource-constrained project scheduling problem (MS-RCPSP) is a significant management science problem that extends from the resource-constrained project scheduling problem (RCPSP) and is integrated with a real project and production environment. To solve MS-RCPSP, it is an efficient method to use dispatching rules combined with a parallel scheduling mechanism to generate a scheduling scheme. This paper proposes an improved gene expression programming (IGEP) approach to explore newly dispatching rules that can broadly solve MS-RCPSP. A new backward traversal decoding mechanism, and several neighborhood operators are applied in IGEP. The backward traversal decoding mechanism dramatically reduces the space complexity in… More > Graphic Abstract

Waleed Aldosari^*

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1253-1269, 2023, DOI:10.32604/cmc.2023.036111

Abstract This paper presents a machine-learning method for detecting jamming UAVs and classifying nodes during jamming attacks on Wireless Sensor Networks (WSNs). Jamming is a type of Denial of Service (DoS) attack and intentional interference where a malicious node transmits a high-power signal to increase noise on the receiver side to disrupt the communication channel and reduce performance significantly. To defend and prevent such attacks, the first step is to detect them. The current detection approaches use centralized techniques to detect jamming, where each node collects information and forwards it to the base station. As a result, overhead and communication costs… More >

Li Yan¹, Zulqurnain Sabir², Esin Ilhan³, Muhammad Asif Zahoor Raja⁴, Wei Gao⁵, Haci Mehmet Baskonus^6,*

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 201-221, 2023, DOI:10.32604/cmes.2023.025094

Abstract In this study, the design of a computational heuristic based on the nonlinear Liénard model is presented using the efficiency of artificial neural networks (ANNs) along with the hybridization procedures of global and local search approaches. The global search genetic algorithm (GA) and local search sequential quadratic programming scheme (SQPS) are implemented to solve the nonlinear Liénard model. An objective function using the differential model and boundary conditions is designed and optimized by the hybrid computing strength of the GA-SQPS. The motivation of the ANN procedures along with GA-SQPS comes to present reliable, feasible and precise frameworks to tackle stiff… More >