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Predicting the imminence of high risk behaviours in in‐patients with schizophrenia is an ongoing concern. The purpose of this paper is to explore the utility, validity and reliability of an adapted early warning signs methodology for dynamic risk assessment.

Nursing staff were interviewed to identify operationally defined early warning signs of high risk behaviours. Frequency of occurrence of the early warning signs and the high risk behaviour were rated over a one week period to establish the predictive validity of the methodology.

Support was found for the reliability of staff ratings of the relevance of identified early warning signs and their occurrence within a specified time period. ROC analysis indicates some modest predictive validity in predicting aggressive risk behaviours but effect sizes were small, and there were high rates of false positive predictions.

The small sample size limits generalisability. A longitudinal prospective study to better establish the added predictive power of the method over the use of largely actuarial methods is needed.

A dynamic risk assessment methodology to assess changes in risk for inpatients would benefit both staff and inpatients. No such methodology has been assessed to date.

The 2004 Boxing Day tsunami prompted global efforts to develop end-to-end multi-hazard warning systems. Taking this event as a starting point, and drawing on experiences from the following advancement of the Indonesian tsunami early warning system, this paper aims to highlight the importance of paying attention to human factors and the perceptions and behaviors of end recipients when trying to design efficient early warning systems.

The study is a viewpoint where theoretical frameworks for the design of efficient early warning systems are used as backdrop to an extensive review and analysis of secondary data, including scientific papers and newspaper articles.

The paper presents what an end-to-end warning system means, explores process problems related to perception and communication and concludes with views and recommendations toward more inclusive early warnings.

Research and practice related to early warning systems have traditionally had a strong focus on technological elements whilst the target groups of early warnings (i.e. communities) have received far less attention and resources. This paper focuses on the human dimension of warning systems and uses a real case to exemplify how efficient warning systems not only require a sound scientific and technological basis, but also depend on the awareness, trust and will of the people they aim to protect.

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.

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.

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.

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.

Persons with disabilities face the impacts of disasters differently. Early warning systems can be one of the powerful tools to reduce the vulnerabilities of persons with disabilities and mitigate the impacts of disasters. The main objective of this study was to assess the disability inclusiveness of the current early warning system (EWS) in flood-prone areas of Bangladesh.

A qualitative method was focused on getting in-depth information. Persons with disabilities participated in focus group discussions (FGDs) and shared the inclusiveness and gaps of the current EWS. Through extensive literature review, a checklist was developed to conduct the FGDs. QDA Miner 6.0.6 software was used for coding and analyzing the data.

Results indicated that, though persons with disabilities have proper risk knowledge, the current monitoring and warning service, dissemination and communication, and response capability are not fully inclusive. A significant gap in the EWS was found in response capability. Even if somehow persons with disabilities manage to receive a warning about a flood, they lack the capacity to respond to the warning.

The study proposed that to make an EWS inclusive and effective, the concerned authorities should focus on all four parts of the EWS.

Studies related to disability and disaster management are not very common. Conducting a qualitative study provided the persons with disabilities the opportunity to share their perspectives. Future studies can focus on vulnerability and capacity assessment of persons with disabilities to identify areas requiring interventions to enhance resilience.

The purpose of this paper is to improve the conceptual understanding of the process of participation in early warning systems (EWS) through a review of participatory EWS examples in the academic literature. Specifically, this paper asks: who is involved, what responsibilities do participants hold, what activities are they involved in, and what are the associated successes, issues and outcomes?

A total of 30 cases of participation in EWS documented in the academic literature were identified through online searches. Existing concepts in participation (power and responsibility, communication) and people-centred early warning (risk knowledge, monitoring and warning, communication and dissemination and response capability) were used to examine each paper.

Participation was found to take place through a range of activities across all elements of the EWS. Participation also varied in breadth of inclusion, ranging from the general public to selected volunteers. The majority of cases received support and facilitation from other actors, such as government and NGOs, but the extent of power and responsibility held by participants varied greatly within this. Common successes and issues associated with participatory EWS and the potential outcomes are presented, and the opportunities, challenges and gaps in knowledge are discussed.

This paper links participation and EWS literature to form a clearer conceptualisation of participation in EWS in support of future research in the field. It provides unique insights into who participates, their roles and relations with other actors and the outcomes of participation.

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.

The purpose of this paper is to make an evaluation and early warning prediction using grey prediction models and the index of process ability.

An early warning prediction for food security risk is proposed in this paper. A quality index is constructed and an improved grey prediction model is also presented. The quality index model is applied to measure the level of food quality; then the grey prediction model is applied to predict the trend of quality index for food in the future. A comparison between the predicted trends and standard limit proposed by experts is made to judge the food security risk.

The results in this paper indicate that more attention should be paid to the food security situation and steps should also should be taken to prevent harm to people's health from food.

The method presented in the paper could be used to make predictions for those systems which have the characteristic of small sample and poor information. The combination of grey prediction model and process ability index could also be applied to evaluation and early warning for those systems.

Food quality index is constructed for evaluating food security and an improved grey prediction model is also presented in this paper. The combination of these two models could be applied to make evaluation and warning prediction for food security risk with poor information.