Adarsh Anand¹, Divya¹, Deepti Aggrawal², Omar H. Alhazmi^3,*

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 1529-1544, 2025, DOI:10.32604/cmc.2025.063361 - 09 June 2025

Abstract Software systems are vulnerable to security breaches as they expand in complexity and functionality. The confidentiality, integrity, and availability of data are gravely threatened by flaws in a system’s design, implementation, or configuration. To guarantee the durability & robustness of the software, vulnerability identification and fixation have become crucial areas of focus for developers, cybersecurity experts and industries. This paper presents a thorough multi-phase mathematical model for efficient patch management and vulnerability detection. To uniquely model these processes, the model incorporated the notion of the learning phenomenon in describing vulnerability fixation using a logistic learning… More >

Yongli Liu^1,2, Weihao Li^1,2,*, Haitao Wang^1,2,3, Taoren Du⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.2, pp. 2261-2286, 2025, DOI:10.32604/cmes.2025.064179 - 30 May 2025

Abstract Coal dust explosions are severe safety accidents in coal mine production, posing significant threats to life and property. Predicting the maximum explosion pressure () of coal dust using deep learning models can effectively assess potential risks and provide a scientific basis for preventing coal dust explosions. In this study, a 20-L explosion sphere apparatus was used to test the maximum explosion pressure of coal dust under seven different particle sizes and ten mass concentrations (), resulting in a dataset of 70 experimental groups. Through Spearman correlation analysis and random forest feature selection methods, particle size… More >

Ilesanmi Afolabi Daniyan^1,*, Rumbidzai Muvunzi², Festus Fameso³, Julius Ndambuki³, Williams Kupolati³, Jacques Snyman³

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 1623-1648, 2025, DOI:10.32604/cmc.2025.062092 - 16 April 2025

Abstract This study evaluates the Fuzzy Analytical Hierarchy Process (FAHP) as a multi-criteria decision (MCD) support tool for selecting appropriate additive manufacturing (AM) techniques that align with cleaner production and environmental sustainability. The FAHP model was validated using an example of the production of aircraft components (specifically fuselage) employing AM technologies such as Wire Arc Additive Manufacturing (WAAM), laser powder bed fusion (L-PBF), Binder Jetting (BJ), Selective Laser Sintering (SLS), and Laser Metal Deposition (LMD). The selection criteria prioritized eco-friendly manufacturing considerations, including the quality and properties of the final product (e.g., surface finish, high strength,… More >

Gehad Azmy, Mohamed El-Morsi, Omar Abdelaziz^*

Frontiers in Heat and Mass Transfer, Vol.23, No.1, pp. 1-54, 2025, DOI:10.32604/fhmt.2025.059710 - 26 February 2025

Abstract This review paper presents an in-depth investigation of the modeling techniques used to study conveyor belt dryers. These techniques are classified into four categories: theoretical modeling, computational fluid dynamics (CFD), empirical, and performance under different control strategies. Within the theoretical and CFD categories, the models are further classified as transient and steady state, as well as one-dimensional, two-dimensional, and three-dimensional. The empirical approach involves conducting experimental studies to collect moisture ratio data during the drying process and comparing it with empirical models. The methods of control are divided into classical and advanced controllers, with classical… More >

Efdal Kaya^*

Revue Internationale de Géomatique, Vol.34, pp. 103-123, 2025, DOI:10.32604/rig.2025.060420 - 24 February 2025

Abstract Global warming leads to climate change and hence effects tourism activities. Bioclimatic comfort indices are used to understand the changing climates of outdoor tourism. In this study, the models for the automatic calculation of the tourism climate index (TCI), heat index (HI), and new summer simmer index (NSSI) from bioclimatic comfort indices are used to determine the climatic conditions of outdoor tourism. The study compared the maps generated by the models with those manually created maps in ArcGIS. In order to statistically reveal how accurately the models produced maps, the relationship between the maps obtained… More >

Muhammad Aliff Haiqal Darmawan¹, Shahrul Nizan Abd Mukti², Khairul Nizam Tahar^1,*

Revue Internationale de Géomatique, Vol.34, pp. 21-35, 2025, DOI:10.32604/rig.2024.057266 - 13 January 2025

Abstract Potholes are the most prevalent type of structural defect found on roads, caused by aging infrastructure, heavy rains, heavy traffic, thin or weak substructures, and other factors. Regular assessment of road conditions is essential for maintaining and improving road networks. Current techniques for identifying potholes on urban roadways primarily rely on public reporting, such as hotlines or social networking websites, which are both time-consuming and inefficient. This study aims to detect potholes using Unmanned Aerial Vehicles (UAVs) images, enabling accurate analysis of their size, shape, and location, thereby enhancing detection efficiency compared to conventional methods.… More >

Duc-Dam Nguyen¹, Nguyen Viet Tiep^2,*, Quynh-Anh Thi Bui¹, Hiep Van Le¹, Indra Prakash³, Romulus Costache^4,5,6,7, Manish Pandey^8,9, Binh Thai Pham¹

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.1, pp. 467-500, 2025, DOI:10.32604/cmes.2024.056576 - 17 December 2024

Abstract This study was aimed to prepare landslide susceptibility maps for the Pithoragarh district in Uttarakhand, India, using advanced ensemble models that combined Radial Basis Function Networks (RBFN) with three ensemble learning techniques: DAGGING (DG), MULTIBOOST (MB), and ADABOOST (AB). This combination resulted in three distinct ensemble models: DG-RBFN, MB-RBFN, and AB-RBFN. Additionally, a traditional weighted method, Information Value (IV), and a benchmark machine learning (ML) model, Multilayer Perceptron Neural Network (MLP), were employed for comparison and validation. The models were developed using ten landslide conditioning factors, which included slope, aspect, elevation, curvature, land cover, geomorphology,… More >

Guochen Ding¹, Jing Zhang¹, Shurong Ding^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.32, No.1, pp. 1-1, 2024, DOI:10.32604/icces.2024.011410

Abstract Zirconium alloys have high strength, high corrosion resistance and low neutron absorption cross section, widely served as the nuclear cladding tubes or some other structural components. During the storage stage of spent fuels or in the lower-temperature reactor-core locations, the hydrogen atoms within the zirconium alloy components would diffuse to the crack tip owing to stress concentration, possibly initiating delayed hydride cracking (DHC) and posing a potential threat to nuclear safety. In this study, the CDM (continuum damage mechanics)-based multi-field coupling computational models are developed, with the hydride-induced hardening and embrittlement, hydride orientation contributions and… More >

Ching-Chi Hsu^1,*, Hsin-Hao Lin¹, Kao-Shang Shih²

The International Conference on Computational & Experimental Engineering and Sciences, Vol.31, No.3, pp. 1-2, 2024, DOI:10.32604/icces.2024.011792

Abstract Decompression surgery is one of the useful methods to relieve the pressure on the spinal cord and nerves [1]. In computational simulation, various bone material modelling strategies have been used to model cortical bone and cancellous bone of spinal vertebrae [2,3]. However, the effects of the bone material modelling strategies on the biomechanics of the thoracolumbar spine are unclear. Thus, this study aimed to investigate the biomechanics of the thoracolumbar spine with various bone modelling strategies using a patient-specific finite element modelling technique.
Three-dimensional finite element models of the human thoracolumbar spine were developed from the… More >

Yuhong Zhao^1,2,3,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.4, pp. 1-1, 2024, DOI:10.32604/icces.2024.012951

Abstract For a long time, the phase-field method has been considered as a mesoscale phenomenological method lacking physical accuracy and unable to be associated with the mechanical/functional properties of materials, etc. Some misunderstandings existing in these viewpoints need to be clarified. Therefore, it is necessary to propose or adopt the perspective of “unified or unifying phase-field modeling (UPFM)” to address these issues, which means that phase-field modeling has multiple unifications. Specifically, the phase-field method is the perfect unity of thermodynamics and kinetics, the unity of multi-scale models from micro- to meso- and then to macroscopic scale, More >