• Journal of Construction Engineering and Project Management
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• v.1 no.2
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• pp.37-42
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• 2011

The key role in safety management is to identify any possible hazard before it occurs by identifying any possible risk factors which are critical to risk assessment. It is well known that falsework (temporary facilities) in construction projects is fundamentally important. This planning/assessment process is considered to be tedious and requires a lot of attention due to the following reasons: firstly, the installation and dismantling of those facilities are one of the high risk activities in the job sites. Secondly, temporary facilities are generally not clearly delineated on the building drawings. Therefore, it is our strong belief that safety tools have to be simple and convenient enough for the jobsite people to manage them easily and be flexible for any occasions to be occurred at various degrees. In order to develop a safety identification system of temporary facilities, this research utilizes the BIM technology in retrieving important information by importing data from BIM models and use it in the safety planning stage.

• Safety and Health at Work
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• v.15 no.2
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• pp.200-207
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• 2024

Background: Workers are often exposed to hazardous heat due to their work environment, leading to various injuries. As a result of climate change, heat-related injuries (HRIs) are becoming more problematic. This study aims to identify critical contributing factors to the severity of occupational HRIs. Methods: This study analyzed historical injury reports from the Occupational Safety and Health Administration (OSHA). Contributing factors to the severity of HRIs were identified using text mining and model-free machine learning methods. The Multinomial Logit Model (MNL) was applied to explore the relationship between impact factors and the severity of HRIs. Results: The results indicated a higher risk of fatal HRIs among middle-aged, older, and male workers, particularly in the construction, service, manufacturing, and agriculture industries. In addition, a higher heat index, collapses, heart attacks, and fall accidents increased the severity of HRIs, while symptoms such as dehydration, dizziness, cramps, faintness, and vomiting reduced the likelihood of fatal HRIs. Conclusions: The severity of HRIs was significantly influenced by factors like workers' age, gender, industry type, heat index , symptoms, and secondary injuries. The findings underscore the need for tailored preventive strategies and training across different worker groups to mitigate HRIs risks.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.3
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• pp.215-220
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• 2018

This paper limited the participation of large corporations in the mass information market by revising the Software Industry Promotion Act in order to increase business opportunity, equality of opportunity, and capacity building for small and medium sized IT companies. However, it is a fact that the medium and small SW companies have insufficient business capacity and expose various problems such as quality degradation of public information business, inadequate risk management, and deterioration of schedule management. In order to solve this problem, this paper derived the factors of quality deterioration in the system integration project and proposed to carry out the project by using some activities of VISUALIZATION, rigorous test management and Agile Methodology as a solution. Applying these measures to healthcare IT projects developed by midsize / small-sized IT companies has improved communications, improved quantitative progress management and improved project visibility. In addition, it contributed to minimizing defect resolution time, improving the requirement coverage ratio, and shortening unnecessary meeting time.

• Journal of Welding and Joining
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• v.31 no.5
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• pp.35-40
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• 2013

In this paper, we propose the Tangible Virtual Reality Representation Method to using haptic device and feature to morphology of created bead from Flux Cored Arc Welding. The virtual reality was started to rising for reduce to consumable materials and welding training risk. And, we will expected maximize virtual reality from virtual welding training. In this paper proposed method is get the database to changing the input factor such as work angle, travelling angle, speed, CTWD. And, it is visualization to bead from extract to optimal morphological feature information to using the Neural Network algorithm. The database was building without error to extract data from automatic robot welder. Also, the Neural Network algorithm was set a dataset of the highest accuracy from verification process in many times. The bead was created in virtual reality from extract to morphological feature information. We were implementation to final shape of bead and overlapped in process by time to using bead generation algorithm and calibration algorithm for generate to same bead shape to real database in process of generating bead. The best advantage of virtual welding training, it can be get the many data to training evaluation. In this paper, we were representation bead to similar shape from generated bead to Flux Cored Arc Welding. Therefore, we were reduce the gap to virtual welding training and real welding training. In addition, we were confirmed be able to maximize the performance of education from more effective evaluation system.

• Journal of the Korea Computer Graphics Society
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• v.22 no.4
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• pp.21-30
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• 2016

Risk management system should be able to support a decision making within a short time to analyze stream data in real time. Many analytical systems consist of CPU computation and disk based database. However, it is more problematic when existing system analyzes stream data in real time. Stream data has various production periods from 1ms to 1 hour, 1day. One sensor generates small data but tens of thousands sensors generate huge amount of data. If hundreds of thousands sensors generate 1GB data per second, CPU based system cannot analyze the data in real time. For this reason, it requires fast processing speed and scalability for analyze stream data. In this paper, we present a fast visualization technique that consists of hybrid database and GPU computation. In order to evaluate our technique, we demonstrate a visual analytics system that analyzes pipeline leak using sensor and tweet data.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.2
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• pp.719-722
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• 2016

Background: Cholangiocarcinoma (CCA) is a serious health problem in Thailand, particularly in northeastern and northern regions, but epidemiological studies are scarce and the spatial distribution of CCA remains to be determined. A database for the population at risk is required for monitoring, surveillance and organization of home health care. This study aim was to geo-visually display the distribution of CCA in northeast Thailand, using a geographic information system and Google Earth. Materials and Methods: A cross-sectional survey was carried out in 9 sub-districts and 133 villages in Chum Phuang district, Nakhon Ratchasima province during June and October 2015. Data on demography, and the population at risk for CCA were combined with the points of villages, sub-district boundaries, district boundaries, and points of hospitals in districts, then fed into a geographical information system. After the conversion, all of the data were imported into Google Earth for geo-visualization. Results: A total of 11,960 from 83,096 population were included in this study. Females and male were 52.5%, and 47.8%, the age group 41-50 years old 33.3%. Individual risk for CCA was identifed and classified by using the Korat CCA verbal screening test as low (92.8%), followed by high risk (6.74%), and no (0.49%), respectively. Gender ($X^2$-test=1143.63, p-value= 0.001), age group ($X^2$-test==211.36, p-value=0.0001), and sub-district ($X^2$-test=1471.858, p-value=0.0001) were significantly associated with CCA risk. Spatial distribution of the population at risk for CCA in Chum Phuang district was viewed with Google Earth. Geo-visual display followed Layer 1: District, Layer 2: Sub-district, Layer 3: Number of low risk in village, Layer 4: Number of high risk in village, and Layer 5: Hospital in Chum Phuang District and their related catchment areas. Conclusions: We present the first risk geo-visual display of CCA in this rural community, which is important for spatial targeting of control efforts. Risk appears to be strongly associated with gender, age group, and sub-district. Therefor, spatial distribution is suitable for the use in the further monitoring, surveillance, and home health care for CCA.

• Korean Journal of Construction Engineering and Management
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• v.23 no.4
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• pp.15-25
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• 2022

As the incidence and mortality of serious disasters in the construction industry are the highest, various efforts are being made in Korea to reduce them. Among them, risk assessment is used as data for disaster reduction measures and evaluation of risk factors at the construction stage. However, the existing risk assessment involves the subjectivity of the performer and is vulnerable to the domestic construction site. This study established a DB classification system for risk assessment with the aim of early identification and pre-removal of risks by quantitatively deriving risk factors using BIM in the risk assessment field and presents a methodology for risk assessment using BIM. Through this, prior removal of risks increases the safety of construction workers and reduces additional costs in the field of safety management. In addition, since it can be applied to new construction methods, it improves the understanding of project participants and becomes a tool for communication. This study proposes a framework for deriving quantitative risks based on BIM, and will be used as a base technology in the field of risk assessment using BIM in the future.

• Korean Journal of Community Nutrition
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• v.15 no.5
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• pp.656-669
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• 2010

Rapid shift to western dietary patterns and social drive of thinness would lead to increase the likelihood of developing eating disorders. This study was performed to analyze the associated factors between dietary pattern and self visualization in terms of body shape, which may increase the risk of disturbed eating attitudes among high school students in Korea. A cross-sectional study was conducted from 2009 to 2010 for high school students including both male and female students, from 6 schools in Gyunggi Province, Korea. A total of 766 students self-reported a questionnaire, including weight control practice, perceptions of self body image and ideal body image, dietary habit, and EAT-26 (Eating Attitude Test-26). Logistic regression analysis was used to fine the factors potentially associated with disturbed eating attitudes. Statistical analysis was conducted using SAS program (version 9.1). Results showed that disturbed eating attitudes were found in 8.7% of male high school students, and in 20.8% of female high school students. Experience of body weight control was reported by 56.2% of male students and by 87.3% of female students. According to multiple logistic regression analysis, obesity was independently associated with high risk of disturbed eating attitudes in male students [Odds Ratios (OR) 2.96, 95% Confidence Interval (CI) 0.90-9.71]. Body image dissatisfaction (OR 2.77, 95%CI 1.37-5.62) and extended family type (OR 2.70, 95%CI 1.05-6.90) were independently associated with high risk of disturbed eating attitudes, especially in female students. In conclusion, proper efforts in education for obesity and developing self-esteem to reduce the risks of disturbed eating attitudes should be implemented in high school nutrition program.

• Safety and Health at Work
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• v.11 no.2
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• pp.127-135
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• 2020

A safe work environment is crucial in high-risk industries, such as construction refurbishment. Safety incidents caused by uncertainty and unexpected events in construction refurbishment systems are difficult to control using conventional safety management techniques. Resilience engineering (RE) is proposed as an alternative to traditional safety management approaches. It presents a successful safety management methodology designed to deal with uncertainty in high-risk work environments. Despite the fact that RE resides in the safety domain, there is no common set of RE indicators to measure and assess resilient in the work environment. The main aim of this research is to explore RE indicators that have been identified as important in developing and assessing the resilient work environment in high-risk industries, particularly in construction refurbishment. Indicators have been attained through a systematic literature review of research and scholarly articles published between the years 2004 and 2019. The literature review explored RE indicators in various industries. Descriptive analysis and co-occurrence-based network visualization were used for data analysis. The findings revealed 28 RE indicators in 11 different high-risk industries. The results show that the four commonly used indicators were: top-management commitment, awareness, learning, and flexibility, all of which have a strong relationship with RE. The findings of this study are useful for stakeholders when making decisions concerning the most important RE indicators in the context of their research or practice as this would avoid the ambiguity and disparity in the identification of RE indicators.

• Journal of the Korea Institute of Building Construction
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• v.20 no.4
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• pp.347-355
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• 2020

The economic growth rate and the urban population of the Vietnam are steadily increasing. As a result, the size of the Vietnam's construction market for infrastructure development is expected to increase. However, Vietnam is adopting PPP(Public-Private Partnership) to solve this problem because the government lacks the financial and administrative capacity for infrastructure development. PPP is a business that lasts more than 10 years, so risk management is very important because it can be a long term damage in case of business failure. This study proposes a self-organization map (SOM) for analyzing the impact of risk factors and determining the priority of them. SOM is a visualization analysis method that analyzes the inherent correlation through the color pattern of each factor.