Quynh-Anh Thi Bui^1,*, Dam Duc Nguyen¹, Hiep Van Le¹, Indra Prakash², Binh Thai Pham^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.1, pp. 691-712, 2025, DOI:10.32604/cmes.2024.054766 - 17 December 2024

Abstract Determination of Shear Bond strength (SBS) at interlayer of double-layer asphalt concrete is crucial in flexible pavement structures. The study used three Machine Learning (ML) models, including K-Nearest Neighbors (KNN), Extra Trees (ET), and Light Gradient Boosting Machine (LGBM), to predict SBS based on easily determinable input parameters. Also, the Grid Search technique was employed for hyper-parameter tuning of the ML models, and cross-validation and learning curve analysis were used for training the models. The models were built on a database of 240 experimental results and three input variables: temperature, normal pressure, and tack coat… More >

Bhanu Pratap Reddy Bhavanam, Prashanth Ragam^*

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.1, pp. 425-466, 2025, DOI:10.32604/cmes.2024.052355 - 17 December 2024

Abstract The Internet of Things (IoT) has orchestrated various domains in numerous applications, contributing significantly to the growth of the smart world, even in regions with low literacy rates, boosting socio-economic development. This study provides valuable insights into optimizing wireless communication, paving the way for a more connected and productive future in the mining industry. The IoT revolution is advancing across industries, but harsh geometric environments, including open-pit mines, pose unique challenges for reliable communication. The advent of IoT in the mining industry has significantly improved communication for critical operations through the use of Radio Frequency… More >

Muhammad Akbar^1,2, Huali Pan^1,*, Jiangcheng Huang³, Bilal Ahmed⁴, Guoqiang Ou¹

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.3, pp. 2625-2625, 2024, DOI:10.32604/cmes.2024.059706 - 31 October 2024

Abstract This article has no abstract. More >

Shen Su^1,*, Daojing He², Neeraj Kumar³

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.3, pp. 1933-1937, 2024, DOI:10.32604/cmes.2024.059318 - 31 October 2024

Abstract This article has no abstract. More >

Ilsun You^1,*, Xiaofeng Chen², Vishal Sharma³, Gaurav Choudhary⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.3, pp. 1907-1909, 2024, DOI:10.32604/cmes.2024.058939 - 31 October 2024

Abstract This article has no abstract. More >

Amjad Rehman¹, Muhammad Mujahid¹, Robertas Damasevicius^2,*, Faten S Alamri³, Tanzila Saba¹

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.3, pp. 2375-2397, 2024, DOI:10.32604/cmes.2024.056937 - 31 October 2024

Abstract This study aims to develop a computational pathology approach that can properly detect and distinguish histology nuclei. This is crucial for histopathological image analysis, as it involves segmenting cell nuclei. However, challenges exist, such as determining the boundary region of normal and deformed nuclei and identifying small, irregular nuclei structures. Deep learning approaches are currently dominant in digital pathology for nucleus recognition and classification, but their complex features limit their practical use in clinical settings. The existing studies have limited accuracy, significant processing costs, and a lack of resilience and generalizability across diverse datasets. We… More >

Yaren Aydın¹, Gebrail Bekdaş^1,*, Sinan Melih Nigdeli¹, Zong Woo Geem^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.3, pp. 2471-2499, 2024, DOI:10.32604/cmes.2024.056693 - 31 October 2024

Abstract Dynamic impacts such as wind and earthquakes cause loss of life and economic damage. To ensure safety against these effects, various measures have been taken from past to present and solutions have been developed using different technologies. Tall buildings are more susceptible to vibrations such as wind and earthquakes. Therefore, vibration control has become an important issue in civil engineering. This study optimizes tuned mass damper inerter (TMDI) using far-fault ground motion records. This study derives the optimum parameters of TMDI using the Adaptive Harmony Search algorithm. Structure displacement and total acceleration against earthquake load More >

Taher Armaghani¹, Lioua Kolsi², Najiyah Safwa Khashi’ie^3,*, Ahmed Muhammed Rashad⁴, Muhammed Ahmed Mansour⁵, Taha Salah⁶, Aboulbaba Eladeb⁷

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.3, pp. 2225-2251, 2024, DOI:10.32604/cmes.2024.056676 - 31 October 2024

Abstract In this paper, the unsteady magnetohydrodynamic (MHD)-radiation-natural convection of a hybrid nanofluid within a U-shaped wavy porous cavity is investigated. This problem has relevant applications in optimizing thermal management systems in electronic devices, solar energy collectors, and other industrial applications where efficient heat transfer is very important. The study is based on the application of a numerical approach using the Finite Difference Method (FDM) for the resolution of the governing equations, which incorporates the Rosseland approximation for thermal radiation and the Darcy-Brinkman-Forchheimer model for porous media. It was found that the increase of Hartmann number… More >

Brij B. Gupta^1,2,3,4,*, Akshat Gaurav⁵, Varsha Arya^6,7, Razaz Waheeb Attar⁸, Shavi Bansal⁹, Ahmed Alhomoud¹⁰, Kwok Tai Chui¹¹

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.3, pp. 2165-2183, 2024, DOI:10.32604/cmes.2024.056473 - 31 October 2024

Abstract Phishing attacks present a serious threat to enterprise systems, requiring advanced detection techniques to protect sensitive data. This study introduces a phishing email detection framework that combines Bidirectional Encoder Representations from Transformers (BERT) for feature extraction and CNN for classification, specifically designed for enterprise information systems. BERT’s linguistic capabilities are used to extract key features from email content, which are then processed by a convolutional neural network (CNN) model optimized for phishing detection. Achieving an accuracy of 97.5%, our proposed model demonstrates strong proficiency in identifying phishing emails. This approach represents a significant advancement in More >

Hamad Naeem¹, Amjad Alsirhani^2,*, Faeiz M. Alserhani³, Farhan Ullah⁴, Ondrej Krejcar¹

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.3, pp. 2185-2223, 2024, DOI:10.32604/cmes.2024.056308 - 31 October 2024

Abstract When it comes to smart healthcare business systems, network-based intrusion detection systems are crucial for protecting the system and its networks from malicious network assaults. To protect IoMT devices and networks in healthcare and medical settings, our proposed model serves as a powerful tool for monitoring IoMT networks. This study presents a robust methodology for intrusion detection in Internet of Medical Things (IoMT) environments, integrating data augmentation, feature selection, and ensemble learning to effectively handle IoMT data complexity. Following rigorous preprocessing, including feature extraction, correlation removal, and Recursive Feature Elimination (RFE), selected features are standardized… More >