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This paper seeks to provide a brief summary on the comprehensive earthquake education program for increasing the public awareness and preparedness for earthquake through an integrated educational program using all types of media, especially in the schools and amongst children.

The paper will provide an overview to the program on the disaster management education for the managers; general public; and especially children's earthquake safety education in schools. This priority could be better highlighted by looking at the wide coverage of schools as well as the young age structure of Iran.

There is still a is a long way to go to achieve a fully prepared and seismically safe community and for this stronger cooperation and participation of the whole of society are necessary for enhancing public safety.

Finally, the paper strongly believes that the Iran experience is successful, one that can be shared and from which one can learn.

The statistics show that older adults have been major fire victims in high-rise buildings. However, the fire safety building codes in most countries are not inclusive and do not reflect provisions for older adults. The research aims to develop a fire risk assessment index system for older adults living in high-rise residential buildings in India. The study further develops a fire rating system to improve fire safety provisions in high-rise buildings in India.

The paper employs Delphi, analytic hierarchy process (AHP) and fuzzy comprehensive risk evaluation techniques. It considers 18 in-depth interviews and group discussions with builders, developers, architects, policymakers, and fire safety experts and consultants to develop a fire risk assessment system for older occupants living in high-rise residential buildings in India.

The fire protection systems and fire management systems are not as per the needs of older adults. The egress system components need improvisation considering the challenges of older adults.

The study is limited to older adults living in high-rise residential buildings in the capital city of Gujarat, Ahmedabad.

This study will assist policymakers in developing fire safety standards that are targeted to the needs of older persons living in high-rise residential buildings during a fire evacuation.

While several approaches for measuring fire risk in high-rise residential buildings exist, no such system has been developed specifically for older adults in India.

In the study, a five-dimensional-safety risk assessment model (5D-SRAM) is developed to improve the construction safety risk assessment approaches available in the literature. To that purpose, a hybrid multi-dimensional fuzzy-based model is proposed, which provides a comprehensive ranking system for the safety risks existing in a project by considering the contextualization of the construction-related activities resulting in an accident.

The developed 5D-SRAM is based on an amalgamation of different fuzzy-based techniques. Through the proposed fuzzy analytic hierarchy process (AHP) method, the importance weights of essential risk dimensions playing role in defining the magnitude of the construction-related risks are obtained, while a precise prioritized ranking system for the identified safety risks is acquired using the proposed fuzzy technique of order preference similarity to the ideal solution (FTOPSIS).

Through the application of the proposed 5D-SRAM to a real-life case study – which is the case of green building construction projects located in Hong Kong – contributions are realized as follows: (1) determination of a more complete range of risk dimensions, (2) calculation of importance weightings for each risk dimension and (3) obtainment of a precise and inclusive ranking system for safety risks. Additionally, the supremacy of the developed 5D-SRAM against the other safety assessment approaches that are commonly adopted in the construction industry is proved.

The developed 5D-SRAM provides the concerned safety decision-makers with not only all the crucial dimensions that play roles toward the magnitude of safety risks posing threats to the workers involved in construction activities, but also they are given hindsight regarding the importance weights of these dimensions. Additionally, the concerned parties are embellished with the final ranking of safety risks in a more comprehensive way than those of existing assessment methods, leading to sagacious adoption of future prudent strategies for dealing with such risks occurring on construction sites.

Numerous studies have documented the safety risks faced by construction workers including proposals for risk assessment models. However, the dimensions considered by such models are limited, generally constrained to risk event probability combined with risk impact severity. Overlooking other dimensions that are essential towards the calculation of safety risks' magnitude culminates in overshadowing the further adoption of fruitful mitigative actions. To overcome this shortcoming, this study proposes a novel 5D-SRAM.

The purpose of this paper is to utilise the comprehensive Food Safety Knowledge Instrument to compare food hygiene knowledge across a population of high school and university students in Australia and the UK.

In total, 475 students from secondary schools and universities in Australia and the UK took part in a survey, which included a Food Safety Knowledge Instrument and demographic items.

Food safety knowledge was generally very low. High school students had a mean score of only 38 per cent, while university students just reached a “pass” with a mean of 54 per cent. Demographics accounted for 41 per cent of variance in food knowledge scores. Female gender, being at university rather than high school, and living out of home rather than with parents were associated with greater food knowledge. Residing in Australia rather than the UK and being older were also associated with greater knowledge; however, these findings were subsumed by education group. Socio-economic status was not a significant predictor of food knowledge.

Identifying demographic and cultural differences in food knowledge can help to identify at-risk populations to better target in theory and knowledge-based interventions.

This study is the first to apply the knowledge instrument in an Australian population. Understanding the baseline knowledge in this population is an important first step at developing effective interventions for food safety.

Consequence prediction is an emerging topic in safety management concerning the severity outcome of accidents. In practical applications, it is usually implemented through supervised learning methods; however, the evaluation of classification results remains a challenge. The previous studies mostly adopted simplex evaluation based on empirical and quantitative assessment strategies. This paper aims to shed new light on the comprehensive evaluation and comparison of diverse classification methods through visualization, clustering and ranking techniques.

An empirical study is conducted using 9 state-of-the-art classification methods on a real-world data set of 653 construction accidents in China for predicting the consequence with respect to 39 carefully featured factors and accident type. The proposed comprehensive evaluation enriches the interpretation of classification results from different perspectives. Furthermore, the critical factors leading to severe construction accidents are identified by analyzing the coefficients of a logistic regression model.

This paper identifies the critical factors that significantly influence the consequence of construction accidents, which include accident type (particularly collapse), improper accident reporting and handling (E21), inadequate supervision engineers (O41), no special safety department (O11), delayed or low-quality drawings (T11), unqualified contractor (C21), schedule pressure (C11), multi-level subcontracting (C22), lacking safety examination (S22), improper operation of mechanical equipment (R11) and improper construction procedure arrangement (T21). The prediction models and findings of critical factors help make safety intervention measures in a targeted way and enhance the experience of safety professionals in the construction industry.

The empirical study using some well-known classification methods for forecasting the consequences of construction accidents provides some evidence for the comprehensive evaluation of multiple classifiers. These techniques can be used jointly with other evaluation approaches for a comprehensive understanding of the classification algorithms. Despite the limitation of specific methods used in the study, the presented methodology can be configured with other classification methods and performance metrics and even applied to other decision-making problems such as clustering.

This study sheds new light on the comprehensive comparison and evaluation of classification results through visualization, clustering and ranking techniques using an empirical study of consequence prediction of construction accidents. The relevance of construction accident type is discussed with the severity of accidents. The critical factors influencing the accident consequence are identified for the sake of taking prevention measures for risk reduction. The proposed method can be applied to other decision-making tasks where the evaluation is involved as an important component.

This paper relays the process the authors used to develop a monitoring and evaluation (M&E) framework in the emergency services team at Australian Red Cross. The paper aims to provide useful information and guidance to support others to build and improve their M&E frameworks, which are fundamental for guiding achievement of department or organisational goals.

This paper uses a case study to describe the participatory agile methodology applied to develop the framework. The completed framework includes indicators mined from pre-existing literature and highlights the benefits of using an agile and participatory approach to cultivate user buy-in, enhance operational relevance and create timely results.

Development of the M&E framework streamlined measurement across the team, improved programmatic strategic alignment, identified gaps in data collection and promoted utilisation of evaluative information. Additionally, it was an exercise in evaluation capacity building, with many process uses, which positively influenced the implementation stage.

There are very few scholarly papers that outline the process taken to develop M&E frameworks, and none in the humanitarian, emergency services field. Additionally, this paper offers an innovative use of agile in facilitating a collaborative, sustainable and meaningful framework.

The purpose of this paper was to map the safety management research of construction industry by scientometric analysis, which can predict important highlights and future research directions of safety management research in the construction industry. As an important issue in the construction industry, safety management issues have been researched from different perspectives. Although previous studies make knowledge contributions to the safety management research of construction industry, there are still huge obstacles to distinguish the comprehensive knowledge map of safety management research in the construction industry.

This study applies three scientometric analysis methods, collaboration network analysis, co-occurrence network analysis and cocitation network analysis, to the safety management research of construction industry. 5,406 articles were retrieved from the core collection database of the Web of Science. CiteSpace was used for constructing a comprehensive analysis framework to analyze and visualize the safety management research of construction industry. According to integrating the analysis results, a knowledge map for the safety management research of construction industry can be constructed.

The analysis results revealed the academic communities, key research topics and knowledge body of safety management research in the construction industry. The evolution paths of safety management research in the construction industry were divided into three development stages: “construction safety management”, “multi-objective safety management” and “comprehensive safety management”. Five research directions were predicted on the future safety management research of construction industry, including (1) comprehensive assessment indicators system; (2) intelligent safety management; (3) cross-organization collaboration of safety management; (4) multilevel safety behavior perception and (5) comparative analysis of safety climate.

The findings can reveal the overall status of safety management research in the construction industry and represent a high-quality knowledge body of safety management research in the construction industry that accurately reflects the comprehensive knowledge map on the safety management research of construction industry. The findings also predict important highlights and future research directions of safety management research in the construction industry, which will help researchers in the safety management research of construction industry for future collaboration and work.

This study provides a safety prewarning mechanism, which includes a comprehensive risk assessment model and a safety prewarning system. The comprehensive risk assessment model is capable of assessing nine safety indicators, which can be categorised into workers’ behaviour, environment and machine-related safety indicators, and the model is embedded in the safety prewarning system. The safety prewarning system can automatically extract safety information from surveillance cameras based on computer vision, assess risks based on the embedded comprehensive risk assessment model, categorise risks into five levels and provide timely suggestions.

Firstly, the comprehensive risk assessment model is constructed by adopting grey multihierarchical analysis method. The method combines the Analytic Hierarchy Process (AHP) and the grey clustering evaluation in the grey theory. Expert knowledge, obtained through the questionnaire approach, contributes to set weights of risk indicators and evaluate risks. Secondly, a safety prewarning system is developed, including data acquisition layer, data processing layer and prewarning layer. Computer vision is applied in the system to automatically extract real-time safety information from the surveillance cameras. The safety information is then processed through the comprehensive risk assessment model and categorized into five risk levels. A case study is presented to verify the proposed mechanism.

Through a case study, the result shows that the proposed mechanism is capable of analyzing integrated human-machine-environment risk, timely categorising risks into five risk levels and providing potential suggestions.

The comprehensive risk assessment model is capable of assessing nine risk indicators, identifying three types of entities, workers, environment and machine on the construction site, presenting the integrated risk based on nine indicators. The proposed mechanism, which adopts expert knowledge through Building Information Modeling (BIM) safety simulation and extracts safety information based on computer vision, can perform a dynamic real-time risk analysis, categorize risks into five risk levels and provide potential suggestions to corresponding risk owners. The proposed mechanism can allow the project manager to take timely actions.

Few developers of school‐based health education programs actively involve the primary and secondary target audience in their program’s development. Kidskin was a sun protection intervention study involving a cohort of 1,776 children recruited from 33 primary schools in Perth, Western Australia. A formative evaluation to develop the Kidskin sun safety classroom and home education program for grades 1 to 4 children and their families was conducted. Process data collected from teachers revealed high levels of satisfaction with the program with the majority agreeing that the activities were developmentally appropriate, effective and enjoyable for students. Mailouts to students’ homes, reinforcing sun safety messages, were used to successfully reach most students and their families during the summer school holidays.