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  • Open Access

    ARTICLE

    Leveraging Augmented Reality, Semantic-Segmentation, and VANETs for Enhanced Driver’s Safety Assistance

    Sitara Afzal1, Imran Ullah Khan1, Irfan Mehmood2, Jong Weon Lee1,*

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1443-1460, 2024, DOI:10.32604/cmc.2023.046707

    Abstract Overtaking is a crucial maneuver in road transportation that requires a clear view of the road ahead. However, limited visibility of ahead vehicles can often make it challenging for drivers to assess the safety of overtaking maneuvers, leading to accidents and fatalities. In this paper, we consider atrous convolution, a powerful tool for explicitly adjusting the field-of-view of a filter as well as controlling the resolution of feature responses generated by Deep Convolutional Neural Networks in the context of semantic image segmentation. This article explores the potential of seeing-through vehicles as a solution to enhance overtaking safety. See-through vehicles leverage… More >

  • Open Access

    ARTICLE

    Detection of Safety Helmet-Wearing Based on the YOLO_CA Model

    Xiaoqin Wu, Songrong Qian*, Ming Yang

    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3349-3366, 2023, DOI:10.32604/cmc.2023.043671

    Abstract Safety helmets can reduce head injuries from object impacts and lower the probability of safety accidents, as well as being of great significance to construction safety. However, for a variety of reasons, construction workers nowadays may not strictly enforce the rules of wearing safety helmets. In order to strengthen the safety of construction site, the traditional practice is to manage it through methods such as regular inspections by safety officers, but the cost is high and the effect is poor. With the popularization and application of construction site video monitoring, manual video monitoring has been realized for management, but the… More >

  • Open Access

    ARTICLE

    Analysis on Operational Safety and Efficiency of FAO System in Urban Rail Transit

    Kaige Guo, Jin Zhou*, Xiaoming Zhang, Di Sun*, Zishuo Wang, Lixian Zhao

    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3677-3696, 2023, DOI:10.32604/cmc.2023.038660

    Abstract This paper discusses two urgent problems that need to be solved in fully automatic operation (FAO) for urban rail transit. The first is the analysis of safety in FAO, while another is the analysis of efficiency in FAO. Firstly, this paper establishes an operational safety evaluation index system from the perspective of operation for the unique or typical risk sources of the FAO system, and uses the analytic hierarchy process (AHP) to evaluate the indicators, analyzes various factors that affect the safe operation of FAO, and provides safety management recommendations for FAO lines operation to maintain the FAO system specifically.… More >

  • Open Access

    ARTICLE

    An Innovative Deep Architecture for Flight Safety Risk Assessment Based on Time Series Data

    Hong Sun1, Fangquan Yang2, Peiwen Zhang3,*, Yang Jiao4, Yunxiang Zhao5

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2549-2569, 2024, DOI:10.32604/cmes.2023.030131

    Abstract With the development of the integration of aviation safety and artificial intelligence, research on the combination of risk assessment and artificial intelligence is particularly important in the field of risk management, but searching for an efficient and accurate risk assessment algorithm has become a challenge for the civil aviation industry. Therefore, an improved risk assessment algorithm (PS-AE-LSTM) based on long short-term memory network (LSTM) with autoencoder (AE) is proposed for the various supervised deep learning algorithms in flight safety that cannot adequately address the problem of the quality on risk level labels. Firstly, based on the normal distribution characteristics of… More >

  • Open Access

    ARTICLE

    Study on Evacuation Strategy of Commercial High-Rise Building under Fire Based on FDS and Pathfinder

    Zheng Yan1, Ying Wang1,*, Longxiao Chao1, Jian Guo2

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1077-1102, 2024, DOI:10.32604/cmes.2023.030023

    Abstract With the development of economy and society and the growth of population, the high-rise and multi-function of commercial buildings have become an international trend. But it also poses huge fire hazards. Most of the existing studies’ research objects are predominantly high-rise residential buildings, without considering the impact of different functional zones (Standard floor, entertainment zone, office zone, equipment room and so on) and personnel distribution of commercial buildings evacuation. And the influence of using elevators to carry evacuees on the refuge floor on personnel evacuation is rarely studied. In this work, the fire scenario of the Yangtze River International Conference… More >

  • Open Access

    ARTICLE

    A Combustion Model for Explosive Charge Affected by a Bottom Gap in the Launch Environment

    Shibo Wu1, Weidong Chen1,*, Jingxin Ma2, Lan Liu1, Shengzhuo Lu1, Honglin Meng1, Xiquan Song3

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1207-1236, 2024, DOI:10.32604/cmes.2023.029471

    Abstract Launch safety of explosive charges has become an urgent problem to be solved by all countries in the world as launch situation of ammunition becomes consistently worse. However, the existing numerical models have different defects. This paper formulates an efficient computational model of the combustion of an explosive charge affected by a bottom gap in the launch environment in the context of the material point method. The current temperature is computed accurately from the heat balance equation, and different physical states of the explosive charges are considered through various equations of state. Microcracks in the explosive charges are described with… More > Graphic Abstract

    A Combustion Model for Explosive Charge Affected by a Bottom Gap in the Launch Environment

  • Open Access

    ARTICLE

    A Calculation Method of Double Strength Reduction for Layered Slope Based on the Reduction of Water Content Intensity

    Feng Shen1,*, Yang Zhao1, Bingyi Li1, Kai Wu2

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 221-243, 2024, DOI:10.32604/cmes.2023.029159

    Abstract The calculation of the factor of safety (FOS) is an important means of slope evaluation. This paper proposed an improved double strength reduction method (DRM) to analyze the safety of layered slopes. The physical properties of different soil layers of the slopes are different, so the single coefficient strength reduction method (SRM) is not enough to reflect the actual critical state of the slopes. Considering that the water content of the soil in the natural state is the main factor for the strength of the soil, the attenuation law of shear strength of clayey soil changing with water content is… More >

  • Open Access

    RETRACTION

    Retraction: Safety and Efficacy of Biodegradable Patent Foramen Ovale Occluder in Patients with Migraine: A Clinical Trial

    Xingbang Li1,#, Xuan Zheng2,#, Bowen Jin1, Yunyan Li1, Yongyu Shao1, Xiaoxian Deng1, Dingyang Li1, Shanshan Li1, Hongmei Zhou1, Jie Zhang3, Xianya Zhang4, Qunshan Shen1, Gangcheng Zhang2,*

    Congenital Heart Disease, Vol.18, No.4, pp. 489-489, 2023, DOI:10.32604/chd.2023.031413

    Abstract This article has no abstract. More >

  • Open Access

    ARTICLE

    AI Safety Approach for Minimizing Collisions in Autonomous Navigation

    Abdulghani M. Abdulghani, Mokhles M. Abdulghani, Wilbur L. Walters, Khalid H. Abed*

    Journal on Artificial Intelligence, Vol.5, pp. 1-14, 2023, DOI:10.32604/jai.2023.039786

    Abstract Autonomous agents can explore the environment around them when equipped with advanced hardware and software systems that help intelligent agents minimize collisions. These systems are developed under the term Artificial Intelligence (AI) safety. AI safety is essential to provide reliable service to consumers in various fields such as military, education, healthcare, and automotive. This paper presents the design of an AI safety algorithm for safe autonomous navigation using Reinforcement Learning (RL). Machine Learning Agents Toolkit (ML-Agents) was used to train the agent with a proximal policy optimizer algorithm with an intrinsic curiosity module (PPO + ICM). This training aims to improve AI… More >

  • Open Access

    ARTICLE

    Safety and Efficacy of Biodegradable Patent Foramen Ovale Occluder in Patients with Migraine: A Clinical Trial

    Xingbang Li1,#, Xuan Zheng2,#, Bowen Jin1, Yunyan Li1, Yongyu Shao1, Xiaoxian Deng1, Dingyang Li1, Shanshan Li1, Hongmei Zhou1, Jie Zhang3, Xianya Zhang4, Qunshan Shen1, Gangcheng Zhang2,*

    Congenital Heart Disease, Vol.18, No.3, pp. 373-385, 2023, DOI:10.32604/chd.2023.028979

    Abstract Background: Transcatheter closure of patent foramen ovale (PFO) has been widely accepted as a highly effective way to treat high-risk PFO-related diseases. However, traditional non-degradable occluders made of metal alloys will permanently exist in the body, resulting in thrombosis, valve damage, hemolysis, arrhythmia, or other complications. The biodegradable PFO occluder developed by Shanghai Mallow Medical Instrument Co., Ltd., China can be fully absorbed and degrade into nontoxic ingredients, reducing postoperative complications. Objectives: To study the safety and efficacy of biodegradable PFO occluders in treating PFO. Methods: This single-center clinical trial collected 30 patients treated with a biodegradable PFO occluder. The… More > Graphic Abstract

    Safety and Efficacy of Biodegradable Patent Foramen Ovale Occluder in Patients with Migraine: A Clinical Trial

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