Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (108)
  • Open Access


    Efficacy and Safety of Transcatheter Arterial Chemoembolization and Transcatheter Arterial Chemotherapy Infusion in Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis

    Xinyang Liu*1, Zhichao Wang*1, Zongwei Chen†1, Longzi Liu*, Lijie Ma*, Liangqing Dong*, Zhao Zhang*, Shu Zhang*, Liuxiao Yang*, Jieyi Shi*, Jia Fan*‡, Xiaoying Wang*, Qiang Gao*‡

    Oncology Research, Vol.26, No.2, pp. 231-239, 2018, DOI:10.3727/096504017X15051752095738

    Abstract Hepatocellular carcinoma (HCC) is a worldwide health threat with increasing incidence and a high mortality rate. Most HCC patients are diagnosed at an advanced stage and are unable to undergo potential curative surgery. Transcatheter arterial chemoembolization (TACE) and transcatheter arterial chemotherapy infusion (TACI) are two of the main palliative treatments for advanced HCC patients. The clinical efficacy and safety of TACE and TACI are controversial. For this reason, we conducted a systematic review and meta-analysis to summarize the current evidence. We searched for randomized controlled trials (RCTs) and cohort studies that compared the clinical outcomes… More >

  • Open Access


    Intelligent Power Grid Load Transferring Based on Safe Action-Correction Reinforcement Learning

    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

    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 >

  • Open Access


    Field Load Test Based SHM System Safety Standard Determination for Rigid Frame Bridge

    Xilong Zheng*, Qiong Wang, Di Guan

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

    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 >

  • Open Access


    Safety-Constrained Multi-Agent Reinforcement Learning for Power Quality Control in Distributed Renewable Energy Networks

    Yongjiang Zhao, Haoyi Zhong, Chang Cyoon Lim*

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 449-471, 2024, DOI:10.32604/cmc.2024.048771

    Abstract This paper examines the difficulties of managing distributed power systems, notably due to the increasing use of renewable energy sources, and focuses on voltage control challenges exacerbated by their variable nature in modern power grids. To tackle the unique challenges of voltage control in distributed renewable energy networks, researchers are increasingly turning towards multi-agent reinforcement learning (MARL). However, MARL raises safety concerns due to the unpredictability in agent actions during their exploration phase. This unpredictability can lead to unsafe control measures. To mitigate these safety concerns in MARL-based voltage control, our study introduces a novel… More >

  • Open Access


    A Game-Theoretic Approach to Safe Crowd Evacuation in Emergencies

    Maria Gul1, Imran Ali Khan1, Gohar Zaman2, Atta Rahman3,*, Jamaluddin Mir2, Sardar Asad Ali Biabani4,5, May Issa Aldossary6, Mustafa Youldash7, Ashraf Saadeldeen8, Maqsood Mahmud9, Asiya Abdus Salam6, Dania Alkhulaifi3, Abdullah AlTurkey3

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1631-1657, 2024, DOI:10.32604/cmc.2024.048289

    Abstract Obstacle removal in crowd evacuation is critical to safety and the evacuation system efficiency. Recently, many researchers proposed game theoretic models to avoid and remove obstacles for crowd evacuation. Game theoretical models aim to study and analyze the strategic behaviors of individuals within a crowd and their interactions during the evacuation. Game theoretical models have some limitations in the context of crowd evacuation. These models consider a group of individuals as homogeneous objects with the same goals, involve complex mathematical formulation, and cannot model real-world scenarios such as panic, environmental information, crowds that move dynamically,… More >

  • Open Access


    IR-YOLO: Real-Time Infrared Vehicle and Pedestrian Detection

    Xiao Luo1,3, Hao Zhu1,2,*, Zhenli Zhang1,2

    CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2667-2687, 2024, DOI:10.32604/cmc.2024.047988

    Abstract Road traffic safety can decrease when drivers drive in a low-visibility environment. The application of visual perception technology to detect vehicles and pedestrians in infrared images proves to be an effective means of reducing the risk of accidents. To tackle the challenges posed by the low recognition accuracy and the substantial computational burden associated with current infrared pedestrian-vehicle detection methods, an infrared pedestrian-vehicle detection method A proposal is presented, based on an enhanced version of You Only Look Once version 5 (YOLOv5). First, A head specifically designed for detecting small targets has been integrated into… More >

  • Open Access


    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… More >

  • Open Access


    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… More >

  • Open Access


    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… More >

  • Open Access


    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… More >

Displaying 1-10 on page 1 of 108. Per Page