scholarly journals Construction Safety during Pandemics: Learning from the Xinjia Express Hotel Collapse during COVID-19 in China

2021 ◽  
Vol 18 (21) ◽  
pp. 11498
Author(s):  
Yu-Jie Huang ◽  
Jing Tao ◽  
Fu-Qiang Yang ◽  
Chao Chen
Keyword(s):  
Safety Management ◽  
Construction Safety ◽  
Causal Factors ◽  
Safety Issues ◽  
Severe Accidents ◽  
Safety Recommendations ◽  
Property Losses ◽  
Construction Accidents ◽  
The Relationship ◽  
Interactive Feedback

Many construction accidents occur in China each year, leading to a large number of deaths, injures, and property losses. Due to the outbreak of COVID-19, little attention is paid to construction safety, resulting in severe accidents. To prevent construction accidents and learn to how address safety issues in future pandemics, this study proposed an improved STAMP (Systems Theoretic Accident Modeling and Processes) model to analyze the collapse accident of the Xinjia Express Hotel used for COVID-19 quarantine in China. Through the application of the STAMP approach, the causes of the construction accident and the relationship between various causal factors are analyzed from a systematic perspective. The identified causes are divided into five categories: contractors, management of organizations, technical methods, participants, and interactive feedback. Finally, safety recommendations are drawn from this study to improve construction safety and safety management in pandemics.

scholarly journals The Attitude of Nurses in Hospitals of Kermanshah towards Safety Climate

2020 ◽  
Author(s):  
Hamed Yarmohammadi ◽  
Azam Jahangiri Mehr ◽  
Younes Sohrabi ◽  
Hosain Salimi ◽  
Arman Mohammadi ◽  
...  
Keyword(s):  
Data Collection ◽  
Safety Climate ◽  
Safety Management ◽  
Safety Issues ◽  
Occupational Characteristics ◽  
Rest Time ◽  
Analytical Research ◽  
The Mean ◽  
The Relationship ◽  
Morning Shift

Introduction: Safety climate is defined as the employees' common insights about safety management in a specific place and time. Nurses have a highly risky occupation, in which they are required to take safety issues into consideration. This study aimed at investigating the attitude of nurses towards safety climate in the hospitals of Kermanshah City, Iran. Methods: This descriptive-analytical research was conducted with 112 nurses in the hospitals of Kermanshah City. A two-section questionnaire was administered for data collection. The first part was related to the nurses' demographic and occupational characteristics and the second part contained the nurses' safety climate questionnaire. After data collection, the data were analyzed by SPSS-16. Results: Results showed that the mean and standard deviation of the safety climate in nurses was 0.56 ± 3.06. A significant relationship was found between all factors, except for the relationship between cumulative burnout and error reporting. The safety climate was almost equal between men and women. Moreover, safety climate was higher in single people than the married ones. In the morning shift, the highest safety climate was in the workplace. Furthermore, people with a second job felt safety climate more. Conclusion: Research results showed that safety climate was not at a satisfactory level in the studied nursing personnel. Therefore, it is suggested to improve the safety climate and its effects on the safety performance by training safety issues, holding technical courses on safety, and adjusting work-rest time.

Current Status and Future Directions of Deep Learning Applications for Safety Management in Construction

2021 ◽  
Vol 13 (24) ◽  
pp. 13579
Author(s):  
Hieu T. T. L. Pham ◽  
Mahdi Rafieizonooz ◽  
SangUk Han ◽  
Dong-Eun Lee
Keyword(s):  
Neural Networks ◽  
Deep Learning ◽  
Safety Management ◽  
High Reliability ◽  
Technical Aspect ◽  
Construction Safety ◽  
Current Status ◽  
Future Directions ◽  
Main Research ◽  
Safety Issues

The application of deep learning (DL) for solving construction safety issues has achieved remarkable results in recent years that are superior to traditional methods. However, there is limited literature examining the links between DL and safety management and highlighting the contributions of DL studies in practice. Thus, this study aims to synthesize the current status of DL studies on construction safety and outline practical challenges and future opportunities. A total of 66 influential construction safety articles were analyzed from a technical aspect, such as convolutional neural networks, recurrent neural networks, and general neural networks. In the context of safety management, three main research directions were identified: utilizing DL for behaviors, physical conditions, and management issues. Overall, applying DL can resolve important safety challenges with high reliability; therein the CNN-based method and behaviors were the most applied directions with percentages of 75% and 67%, respectively. Based on the review findings, three future opportunities aiming to address the corresponding limitations were proposed: expanding a comprehensive dataset, improving technical restrictions due to occlusions, and identifying individuals who performed unsafe behaviors. This review thus may allow the identification of key areas and future directions where further research efforts need to be made with priority.

MACHINE LEARNING APPLICATIONS IN CONSTRUCTION SAFETY LITERATURE

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Kerim Koc ◽  
Asli Pelin Gurgun
Keyword(s):  
Machine Learning ◽  
Literature Review ◽  
Management Practices ◽  
Prediction Models ◽  
Safety Management ◽  
Model Development ◽  
Construction Safety ◽  
Future Research ◽  
Support Vector ◽  
Construction Accidents

Despite significant improvements in safety management practices, the construction industry remains among the most unsafe industries. Thus, it is an essential need to reduce the number of construction accidents through prediction models. In this context, machine learning (ML) methods are extensively used in construction safety literature to predict several outcomes of construction accidents. This study provides a literature review in ML applications in construction safety literature to illustrate research directions for future research. Based on the literature review, 43 journal articles were deeply investigated, and distribution of the articles were classified based on six features: journal, year, adopted machine learning methods, model development approach, utilized dataset, and sub-topics. The findings show that the prediction models in construction safety have taken considerable attention recently. Besides, linear regression and logistic regression were used as a benchmark model, while support vector machine and decision tree were the most frequently implemented ML methods. The number of publications that considered classification problem is two times higher than those adopted regression models. Utilized data were mainly captured from national databases or construction companies. Severity evaluation of construction accidents was the most widely investigated sub-topic, while there is a gap in the literature related to effects of culture on accident outcome and conflict, claim and nonconformance. The findings of this study can provide valuable information for researchers with trends in construction safety literature.

scholarly journals Construction safety ontology development and alignment with industry foundation classes (IFC)

2022 ◽  
Vol 27 ◽  
pp. 94-108
Author(s):  
Karim Farghaly ◽  
Ranjith K. Soman ◽  
William Collinge ◽  
Mojgan Hadi Mosleh ◽  
Patrick Manu ◽  
...  
Keyword(s):  
Safety Management ◽  
Health And Safety ◽  
Construction Safety ◽  
Ontology Development ◽  
Conceptual Information ◽  
Safety Issues ◽  
Knowledge Based ◽  
Research Award ◽  
Safety Risks ◽  
Construction Safety Management

A pronounced gap often exists between expected and actual safety performance in the construction industry. The multifaceted causes of this performance gap are resulting from the misalignment between design assumptions and actual construction processes that take place on-site. In general, critical factors are rooted in the lack of interoperability around the building and work-environment information due to its heterogeneous nature. To overcome the interoperability challenge in safety management, this paper represents the development of an ontological model consisting of terms and relationships between these terms, creating a conceptual information model for construction safety management and linking that ontology to IfcOWL. The developed ontology, named Safety and Health Exchange (SHE), comprises eight concepts and their relationships required to identify and manage safety risks in the design and planning stages. The main concepts of the developed ontology are identified based on reviewing accident cases from 165 Reporting of Injuries, Diseases and Dangerous Occurrences Regulations (RIDDOR) and 31 Press Releases from the database of the Health and Safety Executive (HSE) in the United Kingdom. Consequently, a semantic mapping between the developed ontology and IfcOWL (the most popular ontology and schema for interoperability in the AEC sector) is proposed. Then several SPARQL queries were developed and implemented to evaluate the semantic consistency of the developed ontology and the cross-mapping. The proposed ontology and cross-mapping gained recognition for its innovation in utilising OpenBIM and won the BuildingSMART professional research award 2020. This work could facilitate developing a knowledge-based system in the BIM environment to assist designers in addressing health and safety issues during the design and planning phases in the construction sector.

The Research of Highway Construction Safety Management Based on Fuzzy Evaluation

2015 ◽  
Vol 737 ◽  
pp. 446-451
Author(s):  
Wen Wan ◽  
Jun Qi Yu ◽  
Jiang Ping Zhao
Keyword(s):  
Safety Management ◽  
Evaluation Model ◽  
Highway Construction ◽  
Construction Safety ◽  
Fuzzy Evaluation ◽  
Affecting Factors ◽  
Unsafe Behavior ◽  
Construction Safety Management ◽  
Unsafe Condition ◽  
Construction Accidents

According to the situation of high frequent accidents and supervision difficulties in highway construction project. The fuzzy evaluation model for the affecting factors of highway construction accidents was established. Through safety analysis on many accidents, it was considered that highway construction accidents were commonly affected by workers’ unsafe behavior, unsafe condition, environmental risk and management. Then the weight of relative factors were determined. Finally the highway construction safety management evaluation was built. It shows that this method is reasonable and handled, which provides a good thought for the scientific, quantitative and available evaluation of highway construction safety management.

scholarly journals Causes of Accident at Construction Sites in Bangladesh

2019 ◽  
Vol 11 (1) ◽  
pp. 1933-1951 ◽  
Author(s):  
Shakil Ahmed
Keyword(s):  
Construction Industry ◽  
Safety Management ◽  
The Body ◽  
Construction Site ◽  
Construction Sites ◽  
Safety Issues ◽  
Management Consultant ◽  
Importance Index ◽  
Construction Safety Management ◽  
Construction Accidents

Abstract Bangladeshi construction industry suffers more safety issues than other developing countries in the world. Among many of these, accidents at the construction site go far beyond and shape a horrific figure of death every year. The aims of this study are to identify and prioritize the causes of accidents. This study also analyses and discusses causes of accident at the construction site in Bangladesh. A widespread literature review and open discussion took place to identify the causes and design the questionnaire. The questionnaire-based survey was used to elicit the attitude of four stakeholders such as workers, owners, consultants and contractors towards the causes of accident. Mean and relative importance index (RII) were used to determine the rank of causes, and Statistical Package for the Social Sciences (SPSS) 23 was used to perform the data validation test. This study identifies 77 causes under 14 major groups and ranked them based on the mean and RII. The top five major groups of causes are management-, consultant-, technology-, labour- and contractor-related causes. The top five causes are unawareness of safety-related issue, lack of personal protective equipment, lack of safety eliminating/avoiding design, unfit equipment, lack of knowledge and training on equipment. This study will help the project participants and authorities to know and understand the various characteristics and linkage of causes of construction accidents to improve the construction safety management. It contributes to the body of knowledge, as it reveals for the first time the causes of acci dents in the Bangladeshi construction industry.

BIM-Based Quality Control for Safety Issues in the Design and Construction Phases

2015 ◽  
Vol 9 (3) ◽  
pp. 111 ◽  
Author(s):  
Seunghwa Park ◽  
Inhan Kim
Keyword(s):  
Decision Making ◽  
Traditional Method ◽  
Building Information Modeling ◽  
Safety Management ◽  
Information Modeling ◽  
Use Case ◽  
Safety Issues ◽  
Building Information ◽  
Building Safety

Today’s buildings are getting larger and more complex. As a result, the traditional method of manually checking the design of a building is no longer efficient since such a process is time-consuming and laborious. It is becoming increasingly important to establish and automate processes for checking the quality of buildings. By automatically checking whether buildings satisfy requirements, Building Information Modeling (BIM) allows for rapid decision-making and evaluation. In this context, the work presented here focuses on resolving building safety issues via a proposed BIM-based quality checking process. Through the use case studies, the efficiency and usability of the devised strategy is evaluated. This research can be beneficial in promoting the efficient use of BIM-based communication and collaboration among the project party concerned for improving safety management. In addition, the work presented here has the potential to expand research efforts in BIM-based quality checking processes.

scholarly journals Manual on the proper use of sodium astatide ([211At]NaAt) injections in clinical trials for targeted alpha therapy (1st edition)

2021 ◽  
Author(s):  
Tadashi Watabe ◽  
Makoto Hosono ◽  
Seigo Kinuya ◽  
Takahiro Yamada ◽  
Sachiko Yanagida ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Japanese Society ◽  
Radiation Safety ◽  
Safety Management ◽  
Evaluation Methodology ◽  
Targeted Alpha Therapy ◽  
Safety Issues ◽  
Safety Standards ◽  
And Training ◽  
Alpha Therapy

AbstractWe present the guideline for use of [211At] sodium astatide (NaAt) for targeted alpha therapy in clinical trials on the basis of radiation safety issues in Japan. This guideline was prepared by a study supported by the Ministry of Health, Labour, and Welfare, and approved by the Japanese Society of Nuclear Medicine on 8th Feb, 2021. The study showed that patients receiving [211At]NaAt do not need to be admitted to a radiotherapy room and outpatient treatment is possible. The radiation exposure from the patient is within the safety standards of the ICRP and IAEA recommendations for the general public and caregivers. Precautions for patients and their families, safety management associated with the use of [211At]NaAt, education and training, and disposal of medical radioactive contaminants are also included in this guideline. Treatment using [211At]NaAt in Japan should be carried out according to this guideline. Although this guideline is applied in Japan, the issues for radiation protection and evaluation methodology shown here are considered internationally useful as well.

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