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When disasters occur, the Chinese national or local government and their relevant departments (hereinafter referred to as the government) probably need to acquire emergency supplies from suppliers. Before concluding a transaction, the public officials usually negotiate the quality and price of the emergency supplies with the suppliers. They expect to achieve the best relief effect while the suppliers want to maximize their own interests. Therefore, in order to help the government acquire inexpensive emergency supplies with high quality in a short time, the purpose of this paper is to examine the negotiation process and proposes a negotiation principle for the staff.

This paper first elaborates the characteristics and impact factors of emergency supplies requisition negotiation. Then it establishes a model describing the negotiation on price and quality of emergency supplies between the public officials and suppliers. Afterwards, it proposes an algorithm which can estimate the success rate of the negotiation. Finally, the paper employs the conclusion of the model and algorithm to analyze the emergency supplies requisition negotiation process during the China Lushan earthquake.

This paper proposes a “WRAD” principle of emergency supplies requisition negotiation of public officials in disasters. First, they should ensure the requisition price is not too low. Second, they would widen the difference between the high price and low price. Third, it is best for them to follow the principle of “ascending negotiation and descending choice” while selecting multiple suppliers to negotiate.

This paper establishes a model to study the emergency supplies requisition negotiation process between the public officials and suppliers based on evolutionary game theory. The model assumes that both the public officials and suppliers are not fully rational individuals, and they need time to consult with each other to find out the optimal solution. This paper proposes an innovative action principle of the public officials during the negotiation process which can help it to acquire inexpensive, high-quality, emergency supplies within a short period from the suppliers.

While scheduling and transporting emergency materials in disasters, the emergency materials and delivery vehicles are arriving at the distributing center constantly. Meanwhile, the information of the disaster reported to the government is updating continuously. Therefore, this paper aims to propose an approach to help the government make a transportation plan of vehicles in response to the disasters addressing the problem of material demand and vehicle amount continual alteration.

After elaborating the features and process of the emergency materials transportation, this paper proposes an emergency materials scheduling model in the case of material demand and vehicle amount continual alteration. To solve this model, the paper provides the vehicle transportation route allocation algorithm based on dynamic programming and the disaster area supply sequence self-learning algorithm based on ant colony optimization. Afterwards, the paper uses the model and the solution approach to computing the optimal transportation scheme of the food supply in Lushan earthquake in China.

The case study shows that the model and the solution approach proposed by this paper are valuable to make the emergency materials transportation scheme precise and efficient. The problem of material demand and vehicle amount changing continually during the process of the emergency materials transportation is solved promptly.

The model proposed by this paper improves the existing similar models in the following aspects: the model and the solution approach can not only solve the emergency materials transportation problem in the condition of varying demand and vehicle amount but also save much computing time; and the assumptions of this model are consistent with the actual situation of the emergency relief in disasters so that the model has a broad scope of application.

The purpose of this paper is to analyze the crowd stampede risk mechanism from the perspective of systems thinking.

Causal loop diagram is drawn to outline the non-linear interactions among complex factors across the whole system and dissect the contributory factors of crowd stampede accident. To systematically construct the theoretical framework and find fundamental solutions, co-word analysis with Citespace is used to get the critical data. An agent-based simulation using Pathfinder is conducted to develop a spatial model for the Shanghai Stampede Accident that happened in 2014.

The causal loop diagram is formed to not only illustrate the symptomatic solutions with a quick fix but also dissect the fundamental solutions through an underlying systemic analysis. The simulation shows that crowd stampede experiences an interactive process of accumulation, trigger, delay, break and diffusion of risk factors within the crowd system. A linkage effect among the multidimensional characters of individuals and the system accelerates the stampede risk deterioration. There exists delay of the result of effect from the deep-level measure.

A top-down approach is offered to policymakers for crowd stampede risk protocol design and synergic emergency control that may reduce the risk of the stampede.

In this study, SDFT paradigm is proposed as the critical solution for the crowd stampede accident. In addition, a chain effect of energy and a linkage effect within the crowd system is illustrated for in-depth understanding of crowd stampede risk.

The purpose of this paper is to propose a theoretical framework of applying the Internet of Things (IoT) technologies to the intelligent evacuation protocol in libraries at emergency situations.

The authors conducted field investigations on eight libraries in Wuhan, China, analyzed the characteristics of crowd gathering in libraries and the problems of the libraries’ existing evacuation plans. Therefore, an IoT-based intelligent evacuation protocol in libraries was proposed. Its basic structure consisted of five components: the information base, the protocol base, the IoT sensors, the information fusion system and the intelligent evacuation protocol generation system. In the information fusion system, Dempster–Shafer (D-S) evidence theory was employed as the information fusion algorithm to fuse the multi-sensor information at multiple time points, so as to reduce the uncertainty of disaster prediction. The authors also conducted a case study on the Library L in Wuhan, China. A specific evacuation route was generated for a fire and the crowd evacuation was simulated by the software Patherfind.

The proposed IoT-based evacuation protocol has four distinguishing features: scenario corresponding, precise evacuation, dynamic correction and intelligent decision-making. The case study shows that the proposed protocol is feasible in practice, indicating that the IoT technologies have great potential to be successfully applied to the safety management in libraries.

The software and hardware requirements as well as the Internet network requirements of IoT technologies need to be further discussed.

The proposed IoT-based intelligent evacuation protocol can be widely used in libraries, which is one of the inspirations for the use of IoT technologies in modern constructers.

The application of IoT technologies in libraries is a brand-new topic that has drawn much attention in academia recently. The crowd safety management in libraries is of great significance, and there is little professional literature on it. This paper proposes an IoT-based intelligent evacuation protocol, aiming at improving the safety management in libraries at emergency situations.

This research aims to figure out whether the pool testing method of SARS-CoV-2 for COVID-19 is effective and the optimal sample size is in one bunch. Additionally, since the infection rate was unknown at the beginning, this research aims to propose a multiple sampling approach that enables the pool testing method to be utilized successfully.

The authors verify that the pool testing method of SARS-CoV-2 for COVID-19 is effective under the situation of the shortage of nucleic acid detection kits based on probabilistic modeling. In this method, the testing is performed on several samples of the cases together as a bunch. If the test result of the bunch is negative, then it is shown that none of the cases in the bunch has been infected with the novel coronavirus. On the contrary, if the test result of the bunch is positive, then the samples are tested one by one to confirm which cases are infected.

If the infection rate is extremely low, while the same number of detection kits is used, the expected number of cases that can be tested by the pool testing method is far more than that by the one-by-one testing method. The pool testing method is effective only when the infection rate is less than 0.3078. The higher the infection rate, the smaller the optimal sample size in one bunch. If N samples are tested by the pool testing method, while the sample size in one bunch is G, the number of detection kits required is in the interval (N/G, N).

This research proves that the pool testing method is not only suitable for the situation of the shortage of detection kits but also the situation of the overall or sampling detection for a large population. More importantly, it calculates the optimal sample size in one bunch corresponding to different infection rates. Additionally, a multiple sampling approach is proposed. In this approach, the whole testing process is divided into several rounds in which the sample sizes in one bunch are different. The actual infection rate is estimated gradually precisely by sampling inspection in each round.

After the occurrence of a disaster, emergency supplies should arrive at disaster area in the shortest possible time. Therefore, it is of pivotal importance to speed up the preparation and scheduling process. In other words, only when the preparation process and scheduling process coordinate well, could the emergency supplies arrive at disaster area in time. Consequently, the purpose of this paper is to explore a method that can strengthen the coordination in various kinds of situations.

The paper first elaborates the preparation and scheduling process of emergency supplies in disasters. Then, it establishes a workflow simulation system of the emergency supplies preparation and scheduling based on Petri Net. Afterward, the paper proposes a simplified simulation system of emergency supplies preparation and scheduling which can be employed in actual emergency response. Finally, the paper takes China Lushan Earthquake for a case study.

By employing the simulation system proposed by this paper, decision makers can simulate the whole emergency supplies preparation and scheduling process, which can help them find a method that can optimize the current process. Specifically, by analyzing the simulation results, the government can obtain conclusions as follows. First, whether the preparation and scheduling process of emergency supplies can speed up or not. Second, which part of the process should be improved to realize the acceleration. Third, the workload of the staffs and experts. Fourth, whether it is necessary to add staffs or experts to work in parallel.

This paper proposes a system that can coordinate the preparation process and scheduling process of emergency supplies in disaster. Then, it employs the Petri Net based workflow model to do simulation. The simulation results show that the system designed is reasonable and can be used in practical decision making on the preparation and scheduling of emergency supplies.

Tourism is one of the upcoming service industry in India with high potentials for future growth, particularly in rural areas. Many potential barriers are affecting the growth of tourism in rural India. Therefore, it is essential to explore and prioritize the barriers to tourism growth in rural India.

Qualitative and quantitative responses from “16” experts related to tourism and hospitality management from central India are collected for this study. An integrated Multi-Criteria Decision Making (MCDM) based framework is adopted to identify and relate significant barriers to tourism growth in India.

The result of the study identified many significant barriers and their importance to tourism growth in rural India.

The findings of this study add to the knowledge base of tourism research in line with the previous literature. This study offers an in-depth understanding of barriers focusing on rural tourism growth and devising both the plan of action and the suggestive measures in dealing with rural tourism.

The study provides a robust framework by integrating Interpretive Structural Modelling(ISM) and Decision Making Trial and Evaluation Laboratory (DEMATEL) to explore and prioritizing the critical barriers to rural tourism growth in India. The results of this study can help the decision-maker to fundamentally improve the economy of India through the growth of rural tourism.

The purpose of this paper is to present an integrated leapfrogging mode of technological innovation for developing countries or latecomer enterprises in a certain industrial innovation field. Furthermore, this paper discusses the basic paradigm of the integrated leapfrogging innovation, analyzes the risk in the integrated leapfrogging mode, and describes the risk map of the integrated leapfrogging mode. Finally, taking the example of the integrated leapfrogging mode of technological innovation in developing China High‐speed Railway, this paper carries out the simulation analysis by employing system dynamics model.

In order to examine the impact of the integrated leapfrogging innovation risk on innovative achievements, main risk variables need to be extracted from the process of the integrated leapfrogging innovation, based on the system simulation, relationships among different variables and the impact on innovative achievements can be obtained.

To prevent the risk of the integrated leapfrogging innovation across the innovation, the first thing we need to improve is the contractual relationship, which is to be fair and reasonable, according to the symmetry principles of risks and benefits, and to achieve risk‐sharing and revenue sharing, in addition, all parties must be clear about their responsibilities and interests. The second is the reasonable position of the government's behavior, and it hints that the government cannot interfere too much, and its function is to provide service and support instead of ordering. The third is that enterprises should effectively prevent the risk of the integrated leapfrogging innovation through risk identification and risk early warning and risk pre‐control approach.

A new concept of integrated leapfrogging mode of technological innovation has been put forward, and the risk map of the integrated leapfrogging mode has been described. In addition, this paper proposes some suggestions to prevent the risks of the integrated leapfrogging innovation for enterprises as a reference.

There have been plenty of emergencies occurred in tourism all over the world in recent years. These events and disasters have brought the tourists and relevant organizations enormous loss of life and property. The main reasons are the lack of holistic coordination among different departments and response for social responsibility. In the process of prevention and response of tourism emergency, the local governments need to take synergic action. Meanwhile, the positive participation in the tourism emergency rescue is one of the ways to share social responsibility. This paper aims to examine the early-warning management of regional tourism emergencies, in order to minimize the loss on both tourists' life and money, from the perspective of systematic thinking.

The paper establishes a regional tourism emergency response model based on holistic assessment approach and Bayesian network technology. It analyzes most critical factors of regional tourism emergency and the mutual influence among them. Thereafter, it employs the Bayesian network technology to assess the influence of several factors on the final magnitude of casualties holistically. Based on this, the paper proposes the response principle and the response process to regional tourism emergency.

This paper constructs the “FRES” principle about the holistic response to regional tourism emergency, including “fulfillment of social responsibility”, “rapid action”, “experience accumulation” and “synergic response”. Based on this principle, the paper suggests a general process on the holistic response to regional tourism emergency. Finally, the paper takes the mudslides emergency in Taiwan on October 23, 2010 as an example to conduct an empirical analysis. The paper gives an optimal holistic solution to the responding process of this event in the light of the “FRES” principle.

This paper explains the social responsibility related to the regional tourism emergencies and employs the Bayesian network technology to analyze the systematical responding process to tourism emergency. It proposes originally a “FRES” principle and a general process on the response to regional tourism emergency which are proven to be effective in systematical response to regional tourism events. The research results can facilitate the various local governments to jointly fulfill their social responsibilities and optimize the management of regional tourism emergencies in a holistic way.

This paper aims to study the localization problem for autonomous industrial vehicles in the complex industrial environments. Aiming for practical applications, the pursuit is to build a map-less localization system which can be used in the presence of dynamic obstacles, short-term and long-term environment changes.

The proposed system contains four main modules, including long-term place graph updating, global localization and re-localization, location tracking and pose registration. The first two modules fully exploit the deep-learning based three-dimensional point cloud learning techniques to achieve the map-less global localization task in large-scale environment. The location tracking module implements the particle filter framework with a newly designed perception model to track the vehicle location during movements. Finally, the pose registration module uses visual information to exclude the influence of dynamic obstacles and short-term changes and further introduces point cloud registration network to estimate the accurate vehicle pose.

Comprehensive experiments in real industrial environments demonstrate the effectiveness, robustness and practical applicability of the map-less localization approach.

This paper provides comprehensive experiments in real industrial environments.

The system can be used in the practical automated industrial vehicles for long-term localization tasks. The dynamic objects, short-/long-term environment changes and hardware limitations of industrial vehicles are all considered in the system design. Thus, this work moves a big step toward achieving real implementations of the autonomous localization in practical industrial scenarios.