Qichang Li^1,2,*, Bing Bu¹, Junyi Zhao¹

CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 4281-4313, 2025, DOI:10.32604/cmc.2025.061525 - 19 May 2025

Abstract With the integration of informatization and intelligence into the Communication-Based Train Control (CBTC) systems, the system is facing an increasing number of information security threats. As an important method of characterizing the system security status, the security situation assessment is used to analyze the system security situation. However, existing situation assessment methods fail to integrate the coupling relationship between the physical layer and the information layer of the CBTC systems, and cannot dynamically characterize the real-time security situation changes under cyber attacks. In this paper, a hierarchical security situation assessment approach is proposed to address… More >

Hamza Murad Khan¹, Anwar Khan^1,*, Santos Gracia Villar^2,3,4, Luis Alonso Dzul Lopez^2,5,6, Abdulaziz Almaleh⁷, Abdullah M. Al-Qahtani⁸

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 3369-3388, 2025, DOI:10.32604/cmc.2025.060474 - 16 April 2025

Abstract Traffic forecasting with high precision aids Intelligent Transport Systems (ITS) in formulating and optimizing traffic management strategies. The algorithms used for tuning the hyperparameters of the deep learning models often have accurate results at the expense of high computational complexity. To address this problem, this paper uses the Tree-structured Parzen Estimator (TPE) to tune the hyperparameters of the Long Short-term Memory (LSTM) deep learning framework. The Tree-structured Parzen Estimator (TPE) uses a probabilistic approach with an adaptive searching mechanism by classifying the objective function values into good and bad samples. This ensures fast convergence in… More >

He Zhang^1,2,*, He-Qing Mu^2,*, Xiao Zhang³, He Zhang², Yuedong Yang⁴

Structural Durability & Health Monitoring, Vol.19, No.3, pp. 499-530, 2025, DOI:10.32604/sdhm.2025.059070 - 03 April 2025

Abstract Safety evaluation of a bridge under Moving Abnormal Indivisible Loads (MAILs) directly relates to whether an oversized and/or overweight Large-Cargo Transportation (LCT) vehicle is permitted to pass the bridge. Safety evaluation can be updated by fusing bridge inspection data and load test data, but there are two fundamental difficulties in updating. The first difficulty is to develop an updating scheme to utilize the unstructured inspection data. The second difficulty is to develop a successive updating scheme using load test data based on the previous updating results of the inspection data. This paper proposed a framework,… More >

Chenhong Li¹, Guojin Han¹, Hua Zhong¹, Chao Zhang¹, Rui Zhang², Jonggeun Choe³, Chen Xing², Xuewen Cao², Jiang Bian^4,*

Energy Engineering, Vol.122, No.4, pp. 1287-1309, 2025, DOI:10.32604/ee.2025.060970 - 31 March 2025

Abstract Extracted natural gas hydrate is a multi-phase and multi-component mixture, and its complex composition poses significant challenges for transmission and transportation, including phase changes following extraction and sediment deposition within the pipeline. This study examines the flow and heat transfer characteristics of hydrates in a riser, focusing on the multi-phase flow behavior of natural gas hydrate in the development riser. Additionally, the effects of hydrate flow and seawater temperature on heat exchange are analyzed by simulating the ambient temperature conditions of the South China Sea. The findings reveal that the increase in unit pressure drop… More >

Yahia Said^1,2,*, Yahya Alassaf³, Refka Ghodhbani⁴, Taoufik Saidani⁴, Olfa Ben Rhaiem⁵

CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 3005-3018, 2025, DOI:10.32604/cmc.2025.060928 - 17 February 2025

Abstract Transportation systems are experiencing a significant transformation due to the integration of advanced technologies, including artificial intelligence and machine learning. In the context of intelligent transportation systems (ITS) and Advanced Driver Assistance Systems (ADAS), the development of efficient and reliable traffic light detection mechanisms is crucial for enhancing road safety and traffic management. This paper presents an optimized convolutional neural network (CNN) framework designed to detect traffic lights in real-time within complex urban environments. Leveraging multi-scale pyramid feature maps, the proposed model addresses key challenges such as the detection of small, occluded, and low-resolution traffic… More >

Ibrar Afzal¹, Noor ul Amin^1,*, Zulfiqar Ahmad^1,*, Abdulmohsen Algarni²

CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 1377-1399, 2025, DOI:10.32604/cmc.2024.057755 - 03 January 2025

Abstract The deployment of the Internet of Things (IoT) with smart sensors has facilitated the emergence of fog computing as an important technology for delivering services to smart environments such as campuses, smart cities, and smart transportation systems. Fog computing tackles a range of challenges, including processing, storage, bandwidth, latency, and reliability, by locally distributing secure information through end nodes. Consisting of endpoints, fog nodes, and back-end cloud infrastructure, it provides advanced capabilities beyond traditional cloud computing. In smart environments, particularly within smart city transportation systems, the abundance of devices and nodes poses significant challenges related… More >

Shorouq Alshawabkeh, Li Wu^*, Daojun Dong, Yao Cheng, Liping Li

CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 561-577, 2025, DOI:10.32604/cmc.2024.057213 - 03 January 2025

Abstract Detecting pavement cracks is critical for road safety and infrastructure management. Traditional methods, relying on manual inspection and basic image processing, are time-consuming and prone to errors. Recent deep-learning (DL) methods automate crack detection, but many still struggle with variable crack patterns and environmental conditions. This study aims to address these limitations by introducing the MaskerTransformer, a novel hybrid deep learning model that integrates the precise localization capabilities of Mask Region-based Convolutional Neural Network (Mask R-CNN) with the global contextual awareness of Vision Transformer (ViT). The research focuses on leveraging the strengths of both architectures… More >

Khadija El Fellah^1,*, Ikram El Azami^2,*, Adil El Makrani², Habiba Bouijij³, Oussama El Azzouzy⁴

Computer Systems Science and Engineering, Vol.49, pp. 99-122, 2025, DOI:10.32604/csse.2024.057754 - 03 January 2025

Abstract The rapid growth of the automotive industry has raised significant concerns about the security of connected vehicles and their integrated supply chains, which are increasingly vulnerable to advanced cyber threats. Traditional authentication methods have proven insufficient, exposing systems to risks such as Sybil, Denial of Service (DoS), and Eclipse attacks. This study critically examines the limitations of current security protocols, focusing on authentication and data exchange vulnerabilities, and explores blockchain technology as a potential solution. Blockchain’s decentralized and cryptographically secure framework can significantly enhance Vehicle-to-Vehicle (V2V) communication, ensure data integrity, and enable transparent, immutable transactions More >

Tatyana P. Lyubimova¹, Sergey A. Plotnikov², Albert N. Sharifulin², Vladimir Ya. Modorskii², Sergey S. Neshev², Stanislav L. Kalyulin^2,*

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.12, pp. 2775-2788, 2024, DOI:10.32604/fdmp.2024.054498 - 23 December 2024

Abstract Transporting and storing hydrogen is a complex technological task. A typical problem relates to the need to minimize the strength of fluid motion and heat transfer near the walls of the container. In this work this problem is tackled numerically assuming an infinite cavity of pipe square cross-section, located in a constant external temperature gradient. In particular, a method based on the application of vibrations to suppress the gravitational convection mechanism is explored. A parametric investigation is conducted and the limits of applicability of the method for small Grashof numbers (10e4) are determined. It is More >

Yahia Said^1,*, Yahya Alassaf², Taoufik Saidani³, Refka Ghodhbani³, Olfa Ben Rhaiem⁴, Ali Ahmad Alalawi¹

CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 4349-4370, 2024, DOI:10.32604/cmc.2024.058903 - 19 December 2024

Abstract The integration of Unmanned Aerial Vehicles (UAVs) into Intelligent Transportation Systems (ITS) holds transformative potential for real-time traffic monitoring, a critical component of emerging smart city infrastructure. UAVs offer unique advantages over stationary traffic cameras, including greater flexibility in monitoring large and dynamic urban areas. However, detecting small, densely packed vehicles in UAV imagery remains a significant challenge due to occlusion, variations in lighting, and the complexity of urban landscapes. Conventional models often struggle with these issues, leading to inaccurate detections and reduced performance in practical applications. To address these challenges, this paper introduces CFEMNet,… More >