Search results

The purpose of this study is to introduce the top-level design ideas and the overall architecture of earthquake early-warning system for high speed railways in China, which is based on P-wave earthquake early-warning and multiple ways of rapid treatment.

The paper describes the key technologies that are involved in the development of the system, such as P-wave identification and earthquake early-warning, multi-source seismic information fusion and earthquake emergency treatment technologies. The paper also presents the test results of the system, which show that it has complete functions and its major performance indicators meet the design requirements.

The study demonstrates that the high speed railways earthquake early-warning system serves as an important technical tool for high speed railways to cope with the threat of earthquake to the operation safety. The key technical indicators of the system have excellent performance: The first report time of the P-wave is less than three seconds. From the first arrival of P-wave to the beginning of train braking, the total delay of onboard emergency treatment is 3.63 seconds under 95% probability. The average total delay for power failures triggered by substations is 3.3 seconds.

The paper provides a valuable reference for the research and development of earthquake early-warning system for high speed railways in other countries and regions. It also contributes to the earthquake prevention and disaster reduction efforts.

This study aims to identify the gaps in current policy and propose a viable framework for policy improvement regarding people-centered tsunami early warning chain in Padang City. The objectives are: to describe the gaps and flaws in the current policy regarding local tsunami early warning chain, to identify potential actors to be involved in the tsunami early warning chain and to assess the roles and capacity of actors, and their potential for involvement in early warning.

This study is an exploratory study using social network analysis (SNA) on regulations and other legal documents, and primary data sources from a focus group discussion and semi-structured interviews.

The study found that the existed regulation lacks extension nodes to relay warnings to the populations at risk, often referred to as “the last mile.” Moreover, receiving warning information from both formal and informal sources is important to mobilize people evacuation more effectively during an emergency. The study found that mosque communities and disaster preparedness leaders are the potential actors who should be involved in the local early warning chain.

The research findings were presented as a recommendation to Padang City Government and have been legalized as the new tsunami early warning chain procedure in the Padang City Mayor Regulation 19/2018.

This research investigated local tsunami early warning dissemination in Padang City using SNA. The study demonstrates a close collaboration between researchers, practitioners and the community.

The purpose of this paper is to present an overview of the concept of early warning signs in projects and explain how a performance measurement system can be utilized as a source of data for an early warning approach signaling that a project is about to experience problems at some stage in the future.

Combination of action research and semi‐structured interviews and document analysis supplemented by a post‐mortem analysis after project close‐out.

Detection of early warning signals in projects can be better enabled through the application of a performance measurement system with properly defined key performance indicators. Utilization of this tool can positively affect the overall success of the project.

The case study involved only one project from the oil and gas industry.

The empirical case study was developed to illustrate the usefulness of exploiting a performance measurement system in a project. A procedure was demonstrated for developing and implementing an early warning system based on performance measurement, and specific performance indicators have been described for other projects to copy.

This paper highlights the gap in the literature concerning the link between early warning and project management and the link between early warning and performance measurement. It offers a new idea on how performance measurement can be used as an effective early warning system and is intended to be primarily of use to project management practitioners and practically‐oriented academics who are interested in developing fresh insights into new approaches for better management of projects.

The purpose of this paper is to research the impact of foreign direct investment (FDI) on China's economic growth, so as to measure reasonable scales of FDI and the safe coefficient of China's FDI utilization, make timely predictions, and suggest specific foreign capital management and controlling strategies for the policy makers to adopt under various conditions.

This paper builds early warning systems (EWSs)for China's FDI utilization, applies grey correlation model GM (1,1) to predict early warning indexes, and uses both of the grey correlation and analytic hierarchy process (AHP) to evaluate the weights of the indexes.

The paper finds that FDI can promote China's economic growth, make great contribution to the technology spillover and improve China's employment environment as well as the quality of employment. But its contribution is less than the domestic capital in the aspects of China's industrial structure, area structure and trade structure adjustment, and more seriously, FDI exacerbates the imbalance of the area distribution in China. Moreover, foreign capital focuses on the occupation and monopoly of the domestic market, which will reduce import and export trade and harm the development of China's economy.

Owing to data constraints, this paper is not detailed and comprehensive enough, and needs further exploration in the empirical work.

Given the strong evidence of the EWS for FDI utilization, this paper finds a precise way to evaluate the influence of FDI on China's economic growth, by which the government can implement different capital management and controlling strategies to smooth the openness process of FDI in China.

This paper applies EWS into the FDI utilization to evaluate the safe coefficient and achieve the warning indexes, which are evaluated by the combination of the grey correlation and AHP.

This paper aims to provide a general overview of the international Tsunami warning system mandated by the United Nations, particularly on cataloging past studies and a strategic focus in the Indian Ocean, particularly on the Bay of Bengal region.

Present research assimilates the secondary non-classified data on the Tsunami warning system installed in the Indian Ocean. Qualitative review and exploratory research methodology have been followed to provide a holistic profile of the Tsunami rarly warning system (TEWS) and its role in coastal resilience.

The study finds the need for strategic focus to expand and interlink regional early warning cooperation mechanisms and partnerships to enhance capacities through cooperation and international assistance and mobilize resources necessary to maintain the TEWS in the Indian Ocean region. The enhanced capacity of the TEWS certainly improves the resilience of Indian Ocean coastal communities and infrastructures.

The study is original research and useful for policy planning and regional cooperation on data interlinkages for effective TEWS in the Indian Ocean region.

This paper aims to focus on the gap assessment carried out in the existing early warning systems (EWSs) in Southeast Asia as a means to address such gaps in terms of communication and information dissemination.

This paper was based on the surveys conducted in some of the Southeast Asian countries through interviews, group discussions and consultation to get an understanding about people’s knowledge towards EWSs and their awareness towards warning information.

The conclusions showed that there exist gaps in the existing systems which need to be strengthened to increase its efficiency for providing reliable, timely and accurate information.

Limitation of finding more references to support the work.

This paper is based on the gap assessment carried out in different countries of Southeast Asia for strengthening EWSs. This paper is the original research and has never been published in any other journal.

This paper aims to explore the concept of early warning signs (EWSs) in offshore-outsourced software development (OOSD) projects at the team level. It also aims to identify the EWSs of failure in the onshore-offshore project context and understand how they are perceived by responsible managers.

A grounded theory approach is followed by gathering data from 19 failed OOSD projects using project managers from client and vendor sides as the key informants.

This study identified 13 EWSs of failure in five categories of trust and team cohesion, common project execution structures, awareness of shared work context, collaboration between teams and onshore-offshore team coordination capabilities. EWSs were found to comprise two components: early warning issues and early signals of failures.

India-based vendors’ data in the study formed the primary weakness of the work regarding generalizability, even though it brought homogeneity to data. Lack of triangulation of failure data through client or vendor peers proved impossible in this research as failure remains a very sensitive topic. Dual composition of EWSs could be applied to institutionalize an early warning tool in projects.

The paper develops an exploratory model of EWSs of failure and project failure in the OOSD project context. The two-component framework of EWSs allows project managers to eliminate false positives while identifying EWSs. It contributes to the information system failure, risk management and information technology offshoring research streams.

Food safety risk brought by environmental pollution seriously threatens human health and affects national economic and social development. In particular, heavy metal pollution and nutrient deficiency have caused regional diseases. Thus, the purpose of this paper is to present a risk early warning method of food safety considering environmental and nutritional factors.

A novel risk early warning modelling method based on the long short-term memory (LSTM) neural network integrating sum product based analytic hierarchy process (AHP-SP) is proposed. The data fuzzification method is adopted to overcome the uncertainty of food safety detection data and the processed data are viewed as the input of the LSTM. The AHP-SP method is used to fuse the risk of detection data and the obtained risk values are viewed as the expected output of the LSTM. Finally, the proposed method is applied on one group of sterilized milk data from a food detection agency in China.

The experimental results show that compared with the back propagation and the radial basis function neural networks, the proposed method has higher accuracy in predicting the development trend of food safety risk. Moreover, the causal factors of the risk can be figured out through the predicted results.

The proposed modelling method can achieve accurate prediction and early warning of food safety risk, and provide decision-making basis for the relevant departments to formulate targeted risk prevention and control measures, thereby avoiding food safety incidents caused by environmental pollution or nutritional deficiency.

Outlines previous research on company failure prediction and discusses some of the methodological issues involved. Extends an earlier study (Tan 1997) using artificial neural networks (ANN) to predict financial distress in Australian credit unions by extending the forecast period of the models, presents the results and compares them with probit model results. Finds the ANN models generally at least as good as the probit, although both types improved their accuracy rates (for Type I and Type II errors) when early warning signals were included. Believes ANN “is a promising technique” although more research is required, and suggests some avenues for this.

The purpose of this study is to evaluate the potential risks of copyright infringement in digital library based on the extension theory.

At first, the analytic hierarchy process (AHP) is used to determine the weights of the existing indicator system for early warning. Second, a model is built to evaluate the potential risks of copyright infringement based on the extension theory in digital library. Finally, a real-world application is presented to show the effectiveness and usefulness of this approach.

The main findings of this paper are as follows: the early warning extension theory model is effective in distinguishing the degree of the potential risks of copyright infringement in digital library; the ranges of the value and the values of the indicators can directly affect the results while using this approach, so the accuracy of these two aspects is a crucial question.

The social impact is that copyright infringement risks of digital library is reduced; the lawsuit rate and economic loss due to copyright infringement are thereby decreased as well.

This paper introduces the evaluation of the potential risks of copyright infringement based on the extension theory in digital library. The results provide support for the decision-makers in handling the potential risks of copyright infringement in digital library.