Mohamed A.G. Hazber^1,*, Ebrahim Mohammed Senan^2,3, Hezam Saud Alrashidi¹

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.3, pp. 3229-3254, 2025, DOI:10.32604/cmes.2025.062302 - 03 March 2025

Abstract Hepatitis is an infection that affects the liver through contaminated foods or blood transfusions, and it has many types, from normal to serious. Hepatitis is diagnosed through many blood tests and factors; Artificial Intelligence (AI) techniques have played an important role in early diagnosis and help physicians make decisions. This study evaluated the performance of Machine Learning (ML) algorithms on the hepatitis data set. The dataset contains missing values that have been processed and outliers removed. The dataset was counterbalanced by the Synthetic Minority Over-sampling Technique (SMOTE). The features of the data set were processed… More >

Oswaldo González-Gaxiola¹, Anjan Biswas^2,3,4,*, Ahmed H. Arnous⁵, Yakup Yildirim^6,7

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.3, pp. 2513-2525, 2025, DOI:10.32604/cmes.2025.062177 - 03 March 2025

Abstract Computational modeling plays a vital role in advancing our understanding and application of soliton theory. It allows researchers to both simulate and analyze complex soliton phenomena and discover new types of soliton solutions. In the present study, we computationally derive the bright and dark optical solitons for a Schrödinger equation that contains a specific type of nonlinearity. This nonlinearity in the model is the result of the combination of the parabolic law and the non-local law of self-phase modulation structures. The numerical simulation is accomplished through the application of an algorithm that integrates the classical… More >

So-Eun Jeon¹, Yeon-Ji Lee², Il-Gu Lee^1,2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.3, pp. 3213-3228, 2025, DOI:10.32604/cmes.2025.062082 - 03 March 2025

Abstract The Internet of Things (IoT) is extensively applied across various industrial domains, such as smart homes, factories, and intelligent transportation, becoming integral to daily life. Establishing robust policies for managing and governing IoT devices is imperative. Secure authentication for IoT devices in resource-constrained environments remains challenging due to the limitations of conventional complex protocols. Prior methodologies enhanced mutual authentication through key exchange protocols or complex operations, which are impractical for lightweight devices. To address this, our study introduces the privacy-preserving software-defined range proof (SDRP) model, which achieves secure authentication with low complexity. SDRP minimizes the More >

Syed Zain Ul Abideen¹, Mian Muhammad Kamal^2,*, Eaman Alharbi³, Ashfaq Ahmad Malik⁴, Wadee Alhalabi⁵, Muhammad Shahid Anwar^6,*, Liaqat Ali⁷

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.3, pp. 2191-2210, 2025, DOI:10.32604/cmes.2025.061744 - 03 March 2025

Abstract The rapid evolution of wireless technologies and the advent of 6G networks present new challenges and opportunities for Internet of Things (IoT) applications, particularly in terms of ultra-reliable, secure, and energy-efficient communication. This study explores the integration of Reconfigurable Intelligent Surfaces (RIS) into IoT networks to enhance communication performance. Unlike traditional passive reflector-based approaches, RIS is leveraged as an active optimization tool to improve both backscatter and direct communication modes, addressing critical IoT challenges such as energy efficiency, limited communication range, and double-fading effects in backscatter communication. We propose a novel computational framework that combines… More >

Donghyeok Park¹, Sumin Yeon², Hyeon Seo², Seok-Jun Buu², Suwon Lee^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.3, pp. 2725-2737, 2025, DOI:10.32604/cmes.2025.061732 - 03 March 2025

Abstract Recent research on adversarial attacks has primarily focused on white-box attack techniques, with limited exploration of black-box attack methods. Furthermore, in many black-box research scenarios, it is assumed that the output label and probability distribution can be observed without imposing any constraints on the number of attack attempts. Unfortunately, this disregard for the real-world practicality of attacks, particularly their potential for human detectability, has left a gap in the research landscape. Considering these limitations, our study focuses on using a similar color attack method, assuming access only to the output label, limiting the number of More >

Hyeonbin Jeong¹, Young Tae Ryu², Byung Duk Song^1,*, Sang-Duck Lee^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.3, pp. 2739-2769, 2025, DOI:10.32604/cmes.2025.061639 - 03 March 2025

Abstract This paper proposes a novel cargo loading algorithm applicable to automated conveyor-type loading systems. The algorithm offers improvements in computational efficiency and robustness by utilizing the concept of discrete derivatives and introducing logistics-related constraints. Optional consideration of the rotation of the cargoes was made to further enhance the optimality of the solutions, if possible to be physically implemented. Evaluation metrics were developed for accurate evaluation and enhancement of the algorithm’s ability to efficiently utilize the loading space and provide a high level of dynamic stability. Experimental results demonstrate the extensive robustness of the proposed algorithm More >

Tawfeeq Shawly¹, Ahmed A. Alsheikhy^2,*, Yahia Said³, Shaaban M. Shaaban³, Husam Lahza⁴, Aws I. AbuEid⁵, Abdulrahman Alzahrani⁶

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.3, pp. 3181-3212, 2025, DOI:10.32604/cmes.2025.061608 - 03 March 2025

Abstract Email communication plays a crucial role in both personal and professional contexts; however, it is frequently compromised by the ongoing challenge of spam, which detracts from productivity and introduces considerable security risks. Current spam detection techniques often struggle to keep pace with the evolving tactics employed by spammers, resulting in user dissatisfaction and potential data breaches. To address this issue, we introduce the Divide and Conquer-Generative Adversarial Network Squeeze and Excitation-Based Framework (DaC-GANSAEBF), an innovative deep-learning model designed to identify spam emails. This framework incorporates cutting-edge technologies, such as Generative Adversarial Networks (GAN), Squeeze and… More >

Ferzat Anka¹, Ghanshyam G. Tejani^2,3,*, Sunil Kumar Sharma⁴, Mohammed Baljon⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.3, pp. 2691-2724, 2025, DOI:10.32604/cmes.2025.061522 - 03 March 2025

Abstract Due to the intense data flow in expanding Internet of Things (IoT) applications, a heavy processing cost and workload on the fog-cloud side become inevitable. One of the most critical challenges is optimal task scheduling. Since this is an NP-hard problem type, a metaheuristic approach can be a good option. This study introduces a novel enhancement to the Artificial Rabbits Optimization (ARO) algorithm by integrating Chaotic maps and Levy flight strategies (CLARO). This dual approach addresses the limitations of standard ARO in terms of population diversity and convergence speed. It is designed for task scheduling… More >

Abdullah M. Alqahtani^1,*, Kamran Ahmad Awan², Abdulaziz Almaleh³, Osama Aletri⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.3, pp. 3155-3179, 2025, DOI:10.32604/cmes.2025.061472 - 03 March 2025

Abstract Efficient resource management within Internet of Things (IoT) environments remains a pressing challenge due to the increasing number of devices and their diverse functionalities. This study introduces a neural network-based model that uses Long-Short-Term Memory (LSTM) to optimize resource allocation under dynamically changing conditions. Designed to monitor the workload on individual IoT nodes, the model incorporates long-term data dependencies, enabling adaptive resource distribution in real time. The training process utilizes Min-Max normalization and grid search for hyperparameter tuning, ensuring high resource utilization and consistent performance. The simulation results demonstrate the effectiveness of the proposed method, More >

Baoping Zou^1,2, Chenhao Pei^1,*, Qizhi Chen^1,2, Yansheng Deng^1,2, Yongguo Chen^1,2, Xu Long^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.3, pp. 2457-2485, 2025, DOI:10.32604/cmes.2025.061429 - 03 March 2025

Abstract The utilization of multi-field coupling simulation methods has become a pivotal approach for the investigation of intricate fracture behavior and interaction mechanisms of rock masses in deep strata. The high temperatures, pressures and complex geological environments of deep strata frequently result in the coupling of multiple physical fields, including mechanical, thermal and hydraulic fields, during the fracturing of rocks. This review initially presents an overview of the coupling mechanisms of these physical fields, thereby elucidating the interaction processes of mechanical, thermal, and hydraulic fields within rock masses. Secondly, an in-depth analysis of multi-field coupling is… More >