Yuefan Liu, Ducheng Zhang, Chen Guo^*

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 3281-3299, 2024, DOI:10.32604/cmc.2024.057294 - 18 November 2024

Abstract Craniocerebral injuries represent the primary cause of fatalities among riders involved in two-wheeler accidents; nevertheless, the prevalence of helmet usage among these riders remains alarmingly low. Consequently, the accurate identification of riders who are wearing safety helmets is of paramount importance. Current detection algorithms exhibit several limitations, including inadequate accuracy, substantial model size, and suboptimal performance in complex environments with small targets. To address these challenges, we propose a novel lightweight detection algorithm, termed GL-YOLOv5, which is an enhancement of the You Only Look Once version 5 (YOLOv5) framework. This model incorporates a Global DualPooling… More >

Liangwei Jiang^1,2, Wei Zhang², Hongyin Yang^1,2,3,*, Xiucheng Zhang¹, Jinghan Wu², Zhangjun Liu²

Structural Durability & Health Monitoring, Vol.18, No.6, pp. 835-851, 2024, DOI:10.32604/sdhm.2024.051125 - 20 September 2024

Abstract Aiming at the problem that it is difficult to obtain the explicit expression of the structural matrix in the traditional train-bridge coupling vibration analysis, a combined simulation system of train-bridge coupling system (TBCS) under earthquake (MAETB) is developed based on the cooperative work of MATLAB and ANSYS. The simulation system is used to analyze the dynamic parameters of the TBCS of a prestressed concrete continuous rigid frame bridge benchmark model of a heavy-haul railway. The influence of different driving speeds, seismic wave intensities, and traveling wave effects on the dynamic response of the TBCS under More >

Shih-Lin Lin^*, Bo-Chen Lin

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 3555-3572, 2024, DOI:10.32604/cmc.2024.055456 - 12 September 2024

Abstract This paper explores the application of Model Predictive Control (MPC) to enhance safety and efficiency in autonomous vehicle (AV) navigation through optimized path planning. The evolution of AV technology has progressed rapidly, moving from basic driver-assistance systems (Level 1) to fully autonomous capabilities (Level 5). Central to this advancement are two key functionalities: Lane-Change Maneuvers (LCM) and Adaptive Cruise Control (ACC). In this study, a detailed simulation environment is created to replicate the road network between Nantun and Wuri on National Freeway No. 1 in Taiwan. The MPC controller is deployed to optimize vehicle trajectories,… More >

Licheng Sun¹, Heping Li^2,3, Liang Wang^1,4,*

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4543-4560, 2024, DOI:10.32604/cmc.2024.055115 - 12 September 2024

Abstract It is crucial to ensure workers wear safety helmets when working at a workplace with a high risk of safety accidents, such as construction sites and mine tunnels. Although existing methods can achieve helmet detection in images, their accuracy and speed still need improvements since complex, cluttered, and large-scale scenes of real workplaces cause server occlusion, illumination change, scale variation, and perspective distortion. So, a new safety helmet-wearing detection method based on deep learning is proposed. Firstly, a new multi-scale contextual aggregation module is proposed to aggregate multi-scale feature information globally and highlight the details… More >

Yahia Said^1,*, Yahya Alassaf², Refka Ghodhbani³, Yazan Ahmad Alsariera⁴, Taoufik Saidani³, Olfa Ben Rhaiem⁴, Mohamad Khaled Makhdoum¹, Manel Hleili⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.1, pp. 733-749, 2024, DOI:10.32604/cmes.2024.052369 - 20 August 2024

Abstract Enhancing road safety globally is imperative, especially given the significant portion of traffic-related fatalities attributed to motorcycle accidents resulting from non-compliance with helmet regulations. Acknowledging the critical role of helmets in rider protection, this paper presents an innovative approach to helmet violation detection using deep learning methodologies. The primary innovation involves the adaptation of the PerspectiveNet architecture, transitioning from the original Res2Net to the more efficient EfficientNet v2 backbone, aimed at bolstering detection capabilities. Through rigorous optimization techniques and extensive experimentation utilizing the India driving dataset (IDD) for training and validation, the system demonstrates exceptional More >

Liqiong Chen¹, Kai Zhang^1,*, Song Yang¹, Duo Xu¹, Weihe Huang¹, Hongxuan Hu², Haonan Liu²

Structural Durability & Health Monitoring, Vol.18, No.5, pp. 683-706, 2024, DOI:10.32604/sdhm.2024.049536 - 19 July 2024

Abstract The North China Plain and the agricultural region are crossed by the Shanxi-Beijing natural gas pipeline. Residents in the area use rototillers for planting and harvesting; however, the depth of the rototillers into the ground is greater than the depth of the pipeline, posing a significant threat to the safe operation of the pipeline. Therefore, it is of great significance to study the dynamic response of rotary tillers impacting pipelines to ensure the safe operation of pipelines. This article focuses on the Shanxi-Beijing natural gas pipeline, utilizing finite element simulation software to establish a finite More >

Farman Saifi^1,*, Mohd Javaid¹, Abid Haleem¹, S. M. Anas^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2747-2777, 2024, DOI:10.32604/cmes.2024.051490 - 08 July 2024

Abstract Recent industrial explosions globally have intensified the focus in mechanical engineering on designing infrastructure systems and networks capable of withstanding blast loading. Initially centered on high-profile facilities such as embassies and petrochemical plants, this concern now extends to a wider array of infrastructures and facilities. Engineers and scholars increasingly prioritize structural safety against explosions, particularly to prevent disproportionate collapse and damage to nearby structures. Urbanization has further amplified the reliance on oil and gas pipelines, making them vital for urban life and prime targets for terrorist activities. Consequently, there is a growing imperative for computational… More >

Rui Wang¹, Zhihui Liu^2,*, Hongdi Liu³, Baozhong Su⁴, Chuanyi Ma⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 3035-3049, 2024, DOI:10.32604/cmes.2024.050806 - 08 July 2024

Abstract In underground engineering, the detection of structural cracks on tunnel surfaces stands as a pivotal task in ensuring the health and reliability of tunnel structures. However, the dim and dusty environment inherent to underground engineering poses considerable challenges to crack segmentation. This paper proposes a crack segmentation algorithm termed as Focused Detection for Subsurface Cracks YOLOv8 (FDSC-YOLOv8) specifically designed for underground engineering structural surfaces. Firstly, to improve the extraction of multi-layer convolutional features, the fixed convolutional module is replaced with a deformable convolutional module. Secondly, the model’s receptive field is enhanced by introducing a multi-branch More >

Fuju Zhou^*, Li Li, Tengfei Jia, Yongchang Yin, Aixiang Shi, Shengrong Xu

Energy Engineering, Vol.121, No.6, pp. 1697-1711, 2024, DOI:10.32604/ee.2024.047680 - 21 May 2024

Abstract When a line failure occurs in a power grid, a load transfer is implemented to reconfigure the network by changing the states of tie-switches and load demands. Computation speed is one of the major performance indicators in power grid load transfer, as a fast load transfer model can greatly reduce the economic loss of post-fault power grids. In this study, a reinforcement learning method is developed based on a deep deterministic policy gradient. The tedious training process of the reinforcement learning model can be conducted offline, so the model shows satisfactory performance in real-time operation, More >

Xilong Zheng^*, Qiong Wang, Di Guan

Structural Durability & Health Monitoring, Vol.18, No.3, pp. 361-376, 2024, DOI:10.32604/sdhm.2024.048473 - 15 May 2024

Abstract The deteriorated continuous rigid frame bridge is strengthened by external prestressing. Static loading tests were conducted before and after the bridge rehabilitation to verify the effectiveness of the rehabilitation process. The stiffness of the repaired bridge is improved, and the maximum deflection of the load test is reduced from 37.9 to 27.6 mm. A bridge health monitoring system is installed after the bridge is reinforced. To achieve an easy assessment of the bridge’s safety status by directly using transferred data, a real-time safety warning system is created based on a five-level safety standard. The threshold More >