• Korean Journal of Health Education and Promotion
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• v.32 no.2
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• pp.53-63
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• 2015

Objectives: The purpose of this study was to investigate association of depressive symptom, fatalism with selected health behaviors among people aged 50-69 with no physical limitation in Seoul. Methods: In 2012, data were collected using a household based interview survey in Seoul. One person in each selected household aged between 50 and 69 was selected and responded. Data analysis was based on 1,190 subjects who answered they do not have any physical activity limitation. Results: Multiple logistic regression analysis showed significant association among variables including perceived health, depressive symptom and fatalism scores on some health behaviors. Multiple regression analysis showed that selected health risk behaviors(current smoking, monthly alcohol consumption, no regular health exam in two years) were significantly associated with depressive symptom and fatality scores in addition to demographic variables. The final regression model's adjusted R square was about 0.235. Conclusion: Demographic variables such as gender, age and socioeconomic status were significant variables in health behaviors and these behavioral factors were associated with perceived health, depressive symptom and fatalistic views. As a conclusion, depressive symptom and fatalism should be monitored and intervened in health education practice.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.481-483
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• 2022

With the advent of the era of artificial intelligence, more and more fields have begun to use artificial intelligence technology, especially the medical field. Cancer is one of the biggest problems in the medical field. [1] If it can be detected early and treated early, the possibility of cure will be greatly increased. Malignant skin cancer, as one of the types of cancer with the highest fatality rate in recent years has problems such as relying on the experience of doctors and being unable to be detected and detected in time. Therefore, if artificial intelligence technology can be used to help doctors in early detection of skin cancer, or to allow everyone to detect skin lesions or spots anytime, anywhere, it will have great practical significance. In this paper we used attention residual learning convolutional neural network (ARL-CNN) model [2] to classify skin cancer pictures.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.122-128
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• 2020

This research investigates how a Virtual Reality (VR)-based simulation could be used to train safe operation skills for forklift operators. Forklift operation is categorized as high-risk work by many occupational health and safety regulators and authorities due to high injury and fatality rates involved with forklifts. Therefore, many safety guidelines have been developed for forklift operators. Typically, forklift operation safety training is delivered based on instructional texts or videos, which have limitations in influencing people's safety behavior. Against this background, we propose a VR-based forklift simulator that can enable safe operation skills training through a feedback system. The training program consists of several modules to teach how to perform the basic tasks of forklift operation, such as driving, loading and unloading, following the safety guidelines. The system provides instantaneous instructions and feedback regarding safe operation. This training system is based on the model of "learning-by-doing". The user can repeat the training modules as many times as necessary before being able to perform the given task without violating any safety guidelines. The last training module tests the user's acquisition of all safety skills required. The user feedback from several demonstration sessions showed the potential usefulness of the proposed training system.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.3D
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• pp.391-401
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• 2011

The Implementation Semi-Public Management System of Intra-City Bus brings improvements of the position stability, work environment and welfare of the bus drivers. As these benefits prevent drivers' job changes, average age of the drivers increases. Some side effects such as fatality increase after the implementation of the new system are becoming social problems. To minimize such problems, it is necessary to prepare the measurements reflected drivers' age increase and driving characteristics of old drivers to decrease traffic accidents of intra-city buses. The existing measurements are mostly simple policy. To get over such limitations, this study grasped driving characteristics by surveys and driving aptitude test targeting old drivers and non-old drivers who brings about traffic accidents actually. As a result, the characteristics of the old drivers were understood precisely. The measures of decrease of the traffic accidents are suggested by the analysis of the behavior characteristics of the old drivers through the structural equation model.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.3
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• pp.391-398
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• 2019

In general, truck-involved crashes increase severity in terms of both injury level and crash impact level. Recently, although the frequency and fatality of truck-involved crashes in Korea are rising, their associative studies are very limited. Therefore, the objective of this study is to identify critical factors influencing on injury severity of truck-involved crashes on Korean freeway system. To carry out this objective, this study uses an ordered probit model (OPM) based on a 6-year crash dataset from 2012 to 2017. From the analysis, eight variables were found to have a great effect on injury severity: older driver, crash speed, rear-end collision, number of vehicles involved, drowsy driving, nighttime (0:00 to 6:00) driving, overturn or rollover, and vehicle's fire after crash. However, injury severity was less severe in crashes under snowy condition and crashes to traffic facilities (i.e., crash alone).

• KIPS Transactions on Software and Data Engineering
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• v.10 no.7
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• pp.257-262
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• 2021

Accidents caused by black ice occur frequently every winter, and the fatality rate is very high compared to other traffic accidents. Therefore, a systematic method is needed to predict the black ice formation before accidents. In this paper, we proposed a black ice prediction model based on heterogenous and multi-type data. To this end, 12,574,630 cases of 46 types of land, infrastructure, transport public data and meteorological public data were collected. Subsequently, the data cleansing process including missing value detection and normalization was followed by the establishment of approximately 600,000 refined datasets. We analyzed the correlation of 42 factors collected to predict the occurrence of black ice by selecting only 21 factors that have a valid effect on black ice prediction. The prediction model developed through this will eventually be used to derive the route-specific black ice risk index, which will be utilized as a preliminary study for black ice warning alart services.

• Journal of Korea Water Resources Association
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• v.47 no.10
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• pp.879-889
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• 2014

In this study, to estimate loss of life considered flood characteristics using the relationship derived from analysis of historical dam break cases and the factors determining loss of life, the loss of life module applying in LIFESim and loss of life estimation by means of a mortality function were suggested and applicability for domestic dam watershed was examined. The flood characteristics, such as water depth, flow velocity and arrival time were simulated by FLDWAV model and flood risk area were predicted by using inundation depth. Based on this, the effects of warning, evacuation and shelter were considered to estimate the number of people exposed to the flood. In order to estimate fatality rates based on the exposed population, flood hazard zone is assigned to three different zones. Then, total fatality numbers were predicted after determining lethality or mortality function for each zone. In the future, the prediction of loss of life due to dam break floods will quantitatively evaluate flood risk and employ to establish flood mitigation measures at downstream applying probabilistic flood scenarios.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.5
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• pp.19-29
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• 2023

The accident rate in South Korea is simply classified according to the road type and the number of lanes, but other countries apply various factors affect accidents. In this study, national highways where accidents occurred were divided into urban, rural, older, and modern roads using TAAS(Traffic Accident Analysis System) data, and a model of accident costs savings is suggested. As a result of analyzing 1,416.2 km, the fatality rate(person/100mil-vehicle·km) was 4.21 for urban-older, 1.37 for urban-modern, 2.18 for rural-older, and 0.99 for rural-modern roads. The rates of urban roads had a higher result than rural. The injury rate(person/100mil-vehicle·km) for urban-older was 182.63, that for urban-modern was 103.42, that for rural-older was 67.44, and that for rural-modern road was 42.96, which showed a similar pattern to fatality rates. Accident rates of a modern road were much lower than the KDI Guideline. The benefit of applying the result of this study was calculated and the valuation of accident costs savings is increased from 0.6% to 14.1%, while B/C is improved from 0.626 to 0.724.

• Journal of Korean Society of Transportation
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• v.24 no.7 s.93
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• pp.81-90
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• 2006

It is important to clarify the relationship between traffic accidents and various influencing factors in order to reduce the number of traffic accidents. This study developed a traffic accident frequency prediction model using by multi-linear regression and qualification theories which are commonly applied in the field of traffic safety to verify the influences of various factors into the traffic accident frequency The data were collected on the Korean National Highway 17 which shows the highest accident frequencies and fatality rates in Chonbuk province. In order to minimize the uncertainty of the data, the fuzzy theory and neural network theory were applied. The neural network theory can provide fair learning performance by modeling the human neural system mathematically. Tn conclusion, this study focused on the practicability of the fuzzy reasoning theory and the neural network theory for traffic safety analysis.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.3
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• pp.102-111
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• 2012

Expresway traffic accident is fatal accident by high speed, especially human injury is a great social issue. This paper aims to identify characteristic differences of highway accidents that involve human injuries or not. To analysis the elements that affect the two types of accidents used the logistic regression model. The analysis showed that human injury accident rate is increased in case of straight road, flat, or cut-slope areas, barriers, male driver, and older driver. These results provide the ground for actions to counter the problems. By discovering factors for accidents leading to fatality, this study can provide important implications for authorities that establish highway safety measures and policies in preventing human injuries or deaths from car accidents.