• Safety and Health at Work
• /
• v.9 no.2
• /
• pp.140-143
• /
• 2018

Background: The Occupational Safety and Health Monitoring and Assessment Tool (OSH-MAT) is a practical instrument that is currently used in the German woodworking and metalworking industries to monitor safety conditions at workplaces. The 12-item scoring system has three subscales rating technical, organizational, and personnel-related conditions in a company. Each item has a rating value ranging from 1 to 9, with higher values indicating higher standard of safety conditions. Methods: The reliability of this instrument was evaluated in a cross-sectional survey among 128 companies and its validity among 30,514 companies. The inter-rater reliability of the instrument was examined independently and simultaneously by two well-trained safety engineers. Agreement between the double ratings was quantified by the intraclass correlation coefficient and absolute agreement of the rating values. The content validity of the OSH-MAT was evaluated by quantifying the association between OSH-MAT values and 5-year average injury rates by Poisson regression analysis adjusted for the size of the companies and industrial sectors. The construct validity of OSH-MAT was examined by principle component factor analysis. Results: Our analysis indicated good to very good inter-rater reliability (intraclass correlation coefficient = 0.64-0.74) of OSH-MAT values with an absolute agreement of between 72% and 81%. Factor analysis identified three component subscales that met exactly the structure theory of this instrument. The Poisson regression analysis demonstrated a statistically significant exposure-response relationship between OSH-MAT values and the 5-year average injury rates. Conclusion: These analyses indicate that OSH-MAT is a valid and reliable instrument that can be used effectively to monitor safety conditions at workplaces.

• Journal of the Korean Data Analysis Society
• /
• v.20 no.6
• /
• pp.2941-2951
• /
• 2018

The purpose of this paper is to analyse the effect of ocean weather factors on shipments of swimming crab. We use the data of data portal and ocean weather factors (mean wind velocity, mean atmospheric pressure, mean relative humidity, mean air temperature, mean water temperature, mean maximum wave height, mean significant wave height, maximum significant wave height, maximum wave height, mean wave period, maximum wave period). We did statistical analysis using Poisson regression analysis and negative binomial regression analysis. As the result of study, important factors influential in the shipments of swimming crab turn out to be mean wind velocity, mean atmospheric pressure, mean relative humidity, mean water temperature, maximum wave height, mean wave period and maximum wave period. the shipments of swimming crab increases as mean wind velocity, mean atmospheric pressure, mean relative humidity, mean water temperature increases or mean wave period increase. However, as maximum wave height, maximum wave period decreases, the shipment of swimming crab increases.

• Tunnel and Underground Space
• /
• v.25 no.1
• /
• pp.24-36
• /
• 2015

The Geochang granite widely used in construction works is one of the most popular dimension stones in Korea. In order to evaluate the physical properties of rock, a lot of laboratory tests for the Geochang granite were conducted to find unit weight, absorption ratio, P wave velocity, S wave velocity, uniaxial compressive strength, Young's modulus, Poisson's ratio, tensile strength, cohesion, friction angle and point load strength index. The uniaxial compressive strength of the Geochang granite was 19.5 times tensile strength and also 8.6 times cohesion, besides P wave velocity was 1.5 times S wave velocity. Correlation analyses were also conducted to find the correlation among 11 different physical properties, where the uniaxial compressive strength showed Pearson correlation coefficient of more than 0.8 with Poisson's ratio, point load strength index and Young's modulus, respectively. Regression analyses were finally conducted by means of both linear and multiple analysis and the brief results including coefficient of determination of more than 0.7 were presented.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.22 no.1
• /
• pp.1-15
• /
• 2023

In this study, the number of truck traffic accidents was predicted by using Poisson and negative binomial regression analysis to understand what factors affect accidents using expressway data. Significant variables in the truck traffic accident prediction model were continuous driving time, link length, truck traffic volume. number of bridges and number of drowsy shelters. The calculated LOSS rating was expressed on the national expressway network to diagnose the risk of truck accidents. This is expected to be used as basic data for policy establishment to reduce truck accidents on expressways.

• Journal of the Korean Data and Information Science Society
• /
• v.28 no.6
• /
• pp.1511-1520
• /
• 2017

The purpose of this study is to analyze military combat training data to improve military operation and training methods and verify required military doctrine. We set the number of combat disabled enemies, which the individual combatants make using their weapons, as the response variable regarding offensive operations from scientific military training data of reinforced infantry battalion. Our response variable has more zero observations than would be allowed for by the traditional GLM such as Poisson regression. We used the zero-inflated regression and the hurdle regression for data analysis considering the over-dispersion and excessive zero observation problems. Our result can be utilized as an appropriate reference in order to verify a military doctrine for small units and analysis of various operational and tactical factors.

• Journal of the Korean Society of Safety
• /
• v.26 no.6
• /
• pp.118-123
• /
• 2011

This study deals with the traffic accidents of the arterial link sections. The purpose is to comparatively analyze the characteristics and models by accident type using the data of 24 arterial links in Cheongju. In pursuing the above, this study gives particular emphasis to modeling such the accidents as the side-right-angle collision, rear-end collision and side-swipe collision. The main results are the followings. First, six accident models are developed, which are all analyzed to be statistically significant. Second, the models are comparatively evaluated using the common and specific variables by accident type.

• International Journal of Highway Engineering
• /
• v.16 no.2
• /
• pp.119-129
• /
• 2014

PURPOSES : The purpose of this study is to develop the U-turn accident model at 4-legged signalized intersections in urban areas. METHODS : In order to analyze the characteristics of the accidents which are associated with U-turn operation at 4-legged signalized intersections in urban areas and develop an U-turn accident model by regression analysis, the tests of overdispersion and zero-inflation are conducted about the dependent variables of number of accidents and EPDO (Equivalent Property Damage Only). RESULTS : As their results, the Poisson model fits best for number of accident and the ZIP (Zero Inflated Poisson) fits best for EPOD, the variables of conflict traffic, width of opposing road, traffic passing speed are adopted as independent variable for both models. The variables of number of bus berths and rate of U-turn signal time at which the U-turn is permitted are adopted as independent variable only for EPDO. CONCLUSIONS : These study results suggest that U-turn would be permitted at the intersection where the width of opposing road is wider than 11.9 meters, the passing vehicle speed is not high and U-turn operation is not hindered by the buses stopping at bus stops.

• The Transactions of the Korea Information Processing Society
• /
• v.4 no.2
• /
• pp.395-400
• /
• 1997

An important quality characteristic of a software reliability.Software reliablilty growh models prvied the tools to evluate and moniter the reliabolty growth behavior of the sofwate during the testing phase Therefore failure data collected during the testing phase should be continmuosly analyzed on the basis of some selected software reliability growth models.For the cases where nonhomogeneous Poisson proxess models are the candiate models,we suggest Poisson regression model, which expresses the relationship between the expeted and actual failures counts in disjonint time intervals,for analyzing the failure count data.The weighted lest squares method is then used to-estimate the paramethers in the parameters in the model:The resulting estimators are equivalent to the maximum likelihood estimators. The method is illustrated by analyzing the failutr count data gathered from a large- scale switchong system.

• Journal of East-West Nursing Research
• /
• v.28 no.2
• /
• pp.160-169
• /
• 2022

Purpose: This study was conducted to identify predictors related to aggressive behavior of patients with mental illness admitted to a closed psychiatric ward. Methods: This study adopted a retrospective design which analyzed the hospital medical records of 363 patients with mental illness admitted to the psychiatric closed ward of a university hospital in Seoul, Korea. The collected data were analyzed using SPSS IBM 20.0 and STATA 12.0 SE. ZIP (Zero-Inflated Poisson) and count data analysis were used for the factor influencing the occurrence and frequency of aggressive behavior. Results: The results of ZIP model showed that the factors influencing non-probability of aggressive behavior were anxiety, non-adherence, and frustration. In addition, the factors influencing frequency of aggressive behavior were bipolar disorder and personality disorder trait. Conclusion: We found that bipolar disorder, frustration, and non-adherence are more likely to increase the likelihood of aggressive behavior in patients with mental illness. In particular, patients diagnosed with bipolar disorder were 1.95 times more likely to engage in repetitive aggressive behavior compared to those without a diagnose. However, since the results were different form previous studies, further studies on the traits of anxiety and personality disorders are needed.

• Journal of the Korean Geographical Society
• /
• v.46 no.2
• /
• pp.197-211
• /
• 2011

Due to the complexity of spatial interaction and the necessity of spatial representation and modeling, aggregation of spatial interaction data is indispensible. Given this, the purpose of this paper is to evaluate the effects of modifiable areal unit problem (MAUP) on a spatial interaction model. Four aggregation schemes are utilized at eight different scales: 1) randomly select seeds of district and then allocate basic spatial units to them, 2) minimize the sum of population weighted distance within a district, 3) maximize the proportion of flow within a district, and 4) minimize the proportion of flow within a district. A simple Poisson regression model with origin and destination constraints is utilized. Analysis results demonstrate that spatial characteristics of residuals, parameter values, and goodness-of-fit of the model were influenced by aggregation scale and schemes. Overall, the model responded more sensitively to aggregation scale than aggregation schemes and the scale effect on the model was varied according to aggregation schemes.