Siqing Shan

An emergency response decision support system framework for application in e-government

An emergency response decision support system (ERDSS) needs to assist decision makers to evaluate emergency plans and select an appropriate one during an emergency by supporting heterogeneous emergency response data sources and providing decision makers the access to appropriate emergency rescue knowledge. It also needs to provide differentiated services to meet requirements. Whether the system is effective or not depends on the framework it is based on. This study proposes an ERDSS framework that consists of ten functional modules: Emergency Service Helpdesk, Command and Coordination Center, Emergency Plan Management, Emergency Relief Supplies Management, Emergency Finance Budget Management, Emergency Organization and Activity Management, Emergency Knowledge Warehouse, Emergency Alarm Management, and Problem Analysis and Management. A case study is conducted on Shanghai emergency management decision support system, an EMDSS based on this framework and applied currently in Shanghai, China. The study demonstrates that the proposed ERDSS system framework can provide theoretical and practical guidance for designing and developing effective emergency response systems.

Research on e-Government evaluation model based on the principal component analysis

Over the last few years, the area of electronic government (e-Government) has received increasing prominence and attention; people are interacting with e-Government systems to an ever greater extent. It is therefore important to measure the development of e-Government. Adopting principal component analysis (PCA), this study presents, validates and updates an evaluation model with 5 dimensions based on Socio-Technical model and Stakeholder Theory, which captures the multidimensional and interdependent nature of e-Government system. The validity of the model is empirically investigated using a sample of local e-Government of 18 cities in China, all of which have high Internet penetration and mature ICT use. The five dimensions of the evaluation model include project construction, information security management, special construction, transparency of government affairs and informationized ability. K-means clustering is applied in the subspace created by PCA to evaluate the local e-Government stages of growth of these 18 cities. The findings provide several important implications for e-Government research and practice.

Modeling of emergency response decision-making process using stochastic Petri net: an e-service perspective

In this paper, we address the emergency response decision-making process based on stochastic Petri net from an e-service perspective. The emergency response decision-making process is modeled and designed considering service management. The process is modeled based on stochastic Petri net and a solution methodology is proposed to solve the model. In addition, an isomorphic Markov Chain model and a service performance model are developed for measuring and evaluating the service performance of emergency response decision-making process. Finally, a case study is presented to show the viability of our method.

Impact of quality management practices on the knowledge creation process: The Chinese aviation firm perspective

Contemporary quality management studies describe a range of quality improvement strategies. However, these studies do not consider the impact of quality management practices on the knowledge creation process. Based on a comprehensive literature review and a field survey, this study investigates the impact of quality management practices on the knowledge creation process. A proposed model and hypotheses are presented and tested using survey data collected from aviation firms in China. The test of the structural model supports some proposed hypotheses. We find that employee training, employee involvement, product design, benchmarking, and vision statement have significant direct impacts on the knowledge creation process. We also find that some other quality management practices, such as top management support, customer focus, supplier quality management, quality information, and recognition and rewards, do not have a direct impact on knowledge creation. Suggestions for the improvement of quality management in aviation firms in China are provided. The implications of the findings for researchers and practitioners are discussed, and further research directions are offered.

Optimization and adjustment policy of two-echelon reservoir inventory management with forecast updates

A finite-horizon, periodic-review inventory model with inflow forecasting updates following the Martingale Model of Forecast Evolution (MMFE) in multiresevoirs is considered. This model introduces a new method of determining an operating policy in which the policy is based on the Dynamic Programming (DP) model with a physical equation and a recursive equation. Some important constraints are described for the multireservoirs operation. We propose two methods to adjust the decision variable during the optimization. The adjustment policy is essential to improve the profit and decrease the shortage in multireservoirs management. Finally, to assess the effectiveness of the policies, the model is compared with other models and is applied to the Chinese South-North Water Diversion project.

Feature weighted naïve Bayes algorithm for information retrieval of enterprise systems

Automated information retrieval is critical for enterprise information systems to acquire knowledge from the vast amount of data sets. One challenge in information retrieval is text classification. Current practices rely heavily on the classical naïve Bayes algorithm due to its simplicity and robustness. However, results from this algorithm are not always satisfactory. In this article, the limitations of the naïve Bayes algorithm are discussed, and it is found that the assumption on the independence of terms is the main reason for an unsatisfactory classification in many real-world applications. To overcome the limitations, the dependent factors are considered by integrating a term frequency–inverse document frequency (TF-IDF) weighting algorithm in the naïve Bayes classification. Moreover, the TF-IDF algorithm itself is improved so that both frequencies and distribution information are taken into consideration. To illustrate the effectiveness of the proposed method, two simulation experiments were conducted, and the comparisons with other classification methods have shown that the proposed method has outperformed other existing algorithms in terms of precision and index recall rate.

The dynamic evolution of social ties and user-generated content: a case study on a Douban group

ABSTRACT As platforms based on user-generated content (UGC), social media platforms emphasise the social ties between users and user participation, which promote the communication and propagation of ideas and help to build and maintain relationships. However, many researchers have studied only predefined social networks, such as academic social networks. We believe that there are certain characteristics associated with the network’s UGC worth evaluating. We conducted research in communities in which content attracts discussion and new members and examined the evolution patterns of social and content networks in a topic-oriented Douban group. Datasets of user and content information in communities of interest were collected through web crawler software. Networks based on social and content ties were constructed and analysed. We chose scale, density, centrality, average path length and cluster coefficient as measures for exploring the evolution and correlation of both types of networks. These findings are valuable for social media marketing and helpful in directing and controlling public opinion.

Research on emergency dissemination models for social media based on information entropy

ABSTRACT The emergency information dissemination model discussed in this paper describes the dissemination and broadcasting characteristics of emergency information on the internet. This model is helpful for predicting the occurrence of incidents and improving the emergency response. We construct an emergency information dissemination model based on the information entropy method. We verify the validity of the model by obtaining emergency data from Sina Blog regarding the Ya’an and Wenchuan earthquakes. We find that the level of information entropy significantly influences emergency information dissemination. From the perspective of information entropy, we can more effectively describe and understand information on the internet concerning emergency responses.

An information dissemination model of product quality and safety based on scale-free networks

Abstract In the small-world model, information nodes’ positions are relatively ordered. However, information dissemination between nodes is unordered on the Internet. In this study, a product quality and safety information dissemination model on the Internet is proposed in terms of the characteristics of the scale-free model in the complex network. Using the simulation tests, we found that the information diffusion rate will speed up and the time needed for the system to reach the equilibrium will shorten when the spontaneous dissemination coefficient increases. Additionally, the scope of information coverage also increases as the system’s size increases. However, the time of information diffusion needed to cover the maximum area does not change with the system’s size. The media’s influence has also been found to have an effect on the information dissemination.

An adaptive genetic algorithm for demand-driven and resource-constrained project scheduling in aircraft assembly

Scheduling of aircraft assembling activities is proven as a non-deterministic polynomial-time hard problem; which is also known as a typical resource-constrained project scheduling problem (RCPSP). Not saying the scheduling of the complex assemblies of an aircraft, even for a simple product requiring a limited number of assembling operations, it is difficult or even infeasible to obtain the best solution for its RCPSP. To obtain a high quality solution in a short time frame, resource constraints are treated as the objective function of an RCPSP, and an adaptive genetic algorithm (GA) is proposed to solve demand-driven scheduling problems of aircraft assembly. In contrast to other GA-based heuristic algorithms, the proposed algorithm is innovative in sense that: (1) it executes a procedure with two crossovers and three mutations; (2) its fitness function is demand-driven. In the formulation of RCPSP for aircraft assembly, the optimizing criteria are the utilizations of working time, space, and operators. To validate the effectiveness of the proposed algorithm, two encoding approaches have been tested with the real data of demand.