Robust optimization method of emergency resource allocation for risk management in inland waterways

This study proposes a robust optimization method for waterborne emergency resource allocation in inland waterways that addresses the uncertainties and mismatches between supply and demand. To accomplish this, we integrate the risk evaluation of maritime with a robust optimization model and employ the Entropy Weighted Method (EWM)-Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)-Analytic Hierarchy Process (AHP) method to evaluate the risk of various areas. The approach enables exploration of the relationship between maritime risk and emergency resource allocation strategy. The robust optimization method is used to deal with uncertainty and derive the robust counterpart of the proposed model. We establish an emergency resource allocation model that considers both the economy and timeliness of emergency resource allocation. We construct an optimization model and transform it into an easily solvable robust counterpart model. The results demonstrate that the proposed method can adapt to real-world scenarios, and effectively optimize the configuration effect while improving rescue efficiency under reasonable resource allocation. Specifically, the proportion of rescue time saved ranges from 28.52% to 92.60%, and the proportion of total cost saved is 95.82%. Our approach has significant potential to provide a valuable reference for decision-making related to emergency resource allocation in maritime management

SHIP COLLISION RISK ASSESSMENT MODEL FOR QINZHOU PORT BASED ON EVENT SEQUENCE DIAGRAM

Qinzhou Port is one of the most important ports in the “Beibu Gulf” of China. It is also the main hub port of the "21st century maritime silk road" strategy. Based on a basic collision risk assessment approach, an Event Sequence Diagram (ESD) model that explains the four-stage collision avoidance decision-making procedure is proposed from the perspectives of perception, cognition, decision, and execution. Using the historical data derived from collision accident reports from the Qinzhou Port waters from 2013 to 2017, as well as the data elicited from expert knowledge, a quantitative evaluation of probability distributions of different collision failure modes is performed. The results are also compared with relevant results from other types of navigation waters to analyse collision risk level of Qinzhou waters. At the same time, the main failures paths of collision avoidance decision making are identified. The proposed model can provide with an overall collision risk picture from a macro perspective

REVIEW AND COMPARISON OF THE DEMAND ANALYSIS METHODS OF MARITIME EMERGENCY RESOURCES

The demand analysis method of maritime emergency resources is the key technology to promote a reasonable emergency resource allocation during maritime emergency management. It is widely used to improve the efficiency of maritime emergency rescue and reduce the loss of maritime accidents. However, it requires a scientific and effective method of the demand analysis of maritime emergency resources. This paper aims to analyze the underlying modeling paradigms and to assess the extent to which the demand analysis methods of maritime emergency resources can meet the requirements. Focusing on the demand analysis methods, this paper provides a broad overview of the current literature on maritime emergency resources of the last decades, by considering the models’ purposes, theoretical frameworks, factors, and outputs. The results indicate that the existing methods can be classified into three concepts: the linear regression theory, Back Propagation (BP) Neural Network, and Case-based Reasoning (CBR) technology. Combined with the characteristics of China\u27s maritime emergency management field, the interaction between theoretical framework and applications is not sufficiently understood and thus needs to be further studied. Being familiar with knowledge gaps acts as a catalyst for further research on scientific and efficient demand analysis methods of maritime emergency resources in various navigation conditions

Optimized Convolutional Neural Network Recognition for Athletes’ Pneumonia Image Based on Attention Mechanism

After high-intensity exercise, athletes have a greatly increased possibility of pneumonia infection due to the immune function of athletes decreasing. Diseases caused by pulmonary bacterial or viral infections can have serious consequences on the health of athletes in a short period of time, and can even lead to their early retirement. Therefore, early diagnosis is the key to athletes’ early recovery from pneumonia. Existing identification methods rely too much on professional medical knowledge, which leads to inefficient diagnosis due to the shortage of medical staff. To solve this problem, this paper presents an optimized convolutional neural network recognition method based on an attention mechanism after image enhancement. For the collected images of athlete pneumonia, we first use contrast boost to adjust the coefficient distribution. Then, the edge coefficient is extracted and enhanced to highlight the edge information, and enhanced images of the athlete lungs are obtained by using the inverse curvelet transformation. Finally, an optimized convolutional neural network with an attention mechanism is used to identify the athlete lung images. A series of experimental results show that, compared with the typical image recognition methods based on DecisionTree and RandomForest, the proposed method has higher recognition accuracy for lung images

A method for optimizing maritime emergency resource allocation in inland waterways

Funding Information: This research is supported by the National Key Technologies Research & Development Program ( 2017YFC0804900 ) and the Natural Science Foundation of Hubei Province ( 20221J0089 ). Funding Information: Many studies have investigated resource allocation in emergency response to ensure emergency rescue efficiency and reduce losses caused by accidents, as shown in Table 1. Azofra et al. (2007) used a gravitational model to propose an objective method for allocating maritime rescue resources. The model was used to define individual and zonal distribution models. Zhang et al. (2021a) developed a dynamic multi-objective location-routing model considering the effect of the dynamic motion of offshore oil film to support the practical emergency response in a large-scale oil spill accident. Zhang et al. (2017) established the dynamic demand of maritime emergency resources and proposed a robust optimization model to allocate the resources. Guo et al. (2019) proposed an integer nonlinear programming model to solve the problem of allocating a plurality of resources in a long-range maritime SAR. The model maximized both the probability of accomplishing the rescue operations and the benefits of allocating emergency resources. Ai and Zhang (2019) proposed a two-stage location optimization model, which integrates the problems of locating maritime emergency supply repertories, distributing emergency supplies, and cooperation between the government and enterprises.The input indicators were selected according to the emergency resources mainly used in emergency SAR. The emergency SAR of maritime traffic accidents is inseparable from the support of shore emergency rescue facilities. When a maritime traffic accident occurs, the personnel in the maritime emergency bases near the water area make the first emergency response. The maritime emergency base is a professional facility for maritime SAR. It has functions of docking ships, storing and repairing navigation marks, and some bases also have helicopter landing functions and storing oil spill emergency equipment. The number of maritime emergency bases determines the speed of emergency response and efficiency of emergency rescue. Therefore, the number of maritime emergency bases was selected as an emergency input indicator.The definition of material support resources is relatively broad. Common material support resources include life jackets, lifebuoys, life rafts, immersion suits, thermal insulation suits, and other life-saving appliances or supplies. These materials are difficult to quantify as life-saving materials because they are easy to consume and are stored in scattered places. Considering the independence of the evaluation indicators, we did not regard the scattered life-saving materials as an evaluation indicator. As an important traffic support resource, sea patrol boats are imperative in daily cruise and maritime emergency SAR. Sea patrol boats near the water often arrive first at maritime accident scenes and participate in rescue because they are fast, convenient, and flexible. In addition, other official ships of the fishery administration, marine police and other departments often participate in maritime emergency SAR, which is helpful for finding dangerous situations and personnel rescue. Therefore, sea patrol boats and other official vessels were regarded as transportation. Finally, tugs, as necessary ships in ports, are usually used to assist large ships to enter and leave the port and dock. For the rescue of ships in distress, the tug is also an independent resource in emergency SAR. Therefore, tugs were selected as an evaluation indicator of emergency resources.However, most of the current emergency management policies and guidelines in China focus on emergency rescue after accidents, ignoring pre-emergency preparation. Prominent problems still exist in maritime emergency SAR, such as inadequate policies and regulations as well as insufficient support capacity. Moreover, the guidelines and standards of inland river emergency management mostly appear effective in principle, whereas quantitative calculation standards are lacking for important emergency resource management, such as emergency personnel allocation, emergency base construction, and emergency material reserve. According to the Action Plan For New Infrastructure Construction in the Field of Transportation (2021–2025), in the future, China's inland waterway transportation system will rely on high-grade channels such as the Yangtze River trunk line, Xijiang shipping trunk line, Beijing Hangzhou canal, Wujiang River, Fujiang River, and Hangzhou Shenzhen line to construct intelligent waterways, thereby improving the operation guarantee, collaborative supervision, and comprehensive service capacities of inland waterways. Therefore, it is necessary to improve China's inland river emergency management system, which is crucial for constructing intelligent waterways.This research is supported by the National Key Technologies Research & Development Program (2017YFC0804900) and the Natural Science Foundation of Hubei Province (20221J0089). Publisher Copyright: © 2023 The AuthorsMaritime safety and emergency operation management are critical to preventing maritime accidents and mitigating risks. In this study, we propose a novel method to optimize maritime emergency resource allocation to improve emergency management efficiency. We combine the analytic hierarchy process (AHP) and coefficient of variation (CV) to develop an inverse comprehensive weight (CW) - data envelopment analysis (DEA) model. We apply this model to evaluate the efficiency of allocating emergency resources among ten Maritime Safety Administrations (MSAs) in the Jiangsu section of the Yangtze River in China. Our results indicate that five MSAs have low emergency management benefits, and we propose emergency resource allocation optimization options to improve their emergency management benefits. This study provides policymakers with valuable insights and guidelines for optimizing maritime emergency resource allocation in inland waterways.Peer reviewe