• The Transactions of the Korea Information Processing Society
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• v.7 no.4
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• pp.1103-1111
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• 2000

The hyper-geometric distribution software reliability growth model (HGDM) usually assumes that all the software faults detected are perfectly removed without introducing new faults. However, since new faults can be introduced during the test-and-debug phase, the perfect debugging assumption should be relaxed. In this context, Hou, Kuo and Chang [7] developed a modified HGDM for imperfect debugging environment, assuming tat the learning factor is constant. In this paper we extend the existing imperfect debugging HGDM for tow respects: introduction of random sensitivity factor and allowance of variable learning factor. Then the statistical characteristics of he suggested model are studied and its applications to two real data sets are demonstrated.

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

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.749-754
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• 2014

In this paper, we suggest tree-structure-aware GP (Genetic Programming) operators that heed tree distributions in structure space and their possible structural difficulties. The main idea of the proposed GP operators is to place the generated offspring of crossover and/or mutation in a specified region of tree structure space insofar as possible by biasing the tree structures of the altered subtrees, taking into account the observation that most solutions are found in that region. To demonstrate the effectiveness of the proposed approach, experiments on the binomial-3 regression, multiplexor and even parity problems are performed. The results show that the results using the proposed tree-structure-aware operators are superior to the results of standard GP for all three test problems in both success rate and number of evaluations.

• Journal of the Korean Society of Safety
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• v.29 no.1
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• pp.54-58
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• 2014

This study deals with the accidents of circular intersections in Korea. The goal is to develop the accident models for 94 circular intersections. In pursuing the above, this study gives particular attentions to collecting the data of geometric structure and accidents, and comparatively analyzing such the models as Poisson and NB regression and multiple regression model using SPSS 17.0 and LIMDEP 3.0. The main results are as follows. First, the negative binomial model among various models was analyzed to be the most appropriate. Second, 3 independent variables was adopted in the model, and these variables was analyzed to have a positive relation to the accident rate. Finally, the reduced width of circulatory roadway, removal of the parking lot within circulatory roadway and appropriate levels of approach lane were required to improve the safety of circular intersection.

• Journal of muscle and joint health
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• v.23 no.2
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• pp.125-137
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• 2016

Purpose: The purpose of this study was to identify the influences of hospital employees' daily life posture habits and work-related factors upon musculoskeletal subjective symptoms. Methods: This study was a descriptive survey study. Data were collected using structured a self-report questionnaire between April 1 and May 31, 2015. One hundred and ninety two employees were recruited in three hospitals. The collected data were analyzed using descriptive statistics, ${\chi}^2$ test, t-test, and binomial logistic regression. Results: The habit of leaning on one side and the habit of bending the back in an improper posture are key postures based on lifestyle affecting musculoskeletal subjective symptoms in neck, shoulders, arms, waist, and legs. Labours accompanying repeated arm movements for a long time are key work-related risk factors affecting musculoskeletal subjective symptoms in arms. Conclusion: The results of this study confirmed that, to prevent musculoskeletal diseases, it is necessary to identify and mediate personal factors like daily life posture habits as well as work-related risk factors. They may be utilized as basic materials for education of musculoskeletal health promotion and development of life guidance programs.

• Journal of Applied Reliability
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• v.14 no.4
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• pp.225-229
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• 2014

A one-shot device is defined as a product, system, weapon, or equipment that can be used only once. After use, the device is destroyed or must undergo extensive rebuild. Determining the reliability of a one-shot device poses a unique challenge to the manufacturers and users due to the destructive nature and costs of the testing. This paper presents a reliability growth prediction for a one-shot system. It is assumed that 1) test duration is discrete(i.e. trials or rounds); 2) trials are statistically independent; 3) the number of failures for a given system configuration is distributed according to a binomial distribution; and 4) the cumulative expected number of failures through any sequence of configurations is given by AMSAA model. When the system development is represented by three configurations and the number of trials and failures during configurations are given, the AMSAA model parameters and reliability at configuration 3 are estimated by using a reliability growth analysis software. Further, if the reliability growth predictions do not meet the target reliability, the sample size of an additional test is determined for achieving the target reliability.

• Journal of the Korean Society of Safety
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• v.33 no.3
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• pp.77-82
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• 2018

This paper aims to analyze the accident based on changing patterns of traffic culture index. For this purpose, this paper particularly focuses on classifying the traffic culture patterns and developing the traffic accidents using panel count data model. The main results are as follows. First, the traffic culture patterns are divided into 'increasing', 'decreasing' and 'other' patterns. The null hypotheses that the number of accident are the same over patterns are rejected. Second, 4 fixed effect negative binomial models which are all statistically significant are developed. Third, the regions with 'increasing' pattern are analyzed to be mostly the counties, and to demand the traffic law enforcement. Fourth, the regions with 'decreasing' pattern are evaluated to be mainly the districts and to require such the traffic culture as turn signal usage. Finally, the regions with 'other' pattern are analyzed to be mostly the cities and to ask for enhancing the level of traffic culture.

• Microbiology and Biotechnology Letters
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• v.49 no.2
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• pp.249-254
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• 2021

The study of the impact of weather on viral respiratory infections enables the assignment of causality to disease outbreaks caused by climatic factors. A better understanding of the seasonal distribution of viruses may facilitate the development of potential treatment approaches and effective preventive strategies for respiratory viral infections. We analyzed the incidence of human mastadenovirus infection using real-time reverse transcription polymerase chain reaction in 9,010 test samples obtained from Cheonan, South Korea, and simultaneously collected the weather data from January 1, 2012, to December 31, 2018. We used the data collected on the infection frequency to detect seasonal patterns of human mastadenovirus prevalence, which were directly compared with local weather data obtained over the same period. Descriptive statistical analysis, frequency analysis, t-test, and binomial logistic regression analysis were performed to examine the relationship between weather, particulate matter, and human mastadenovirus infections. Patients under 10 years of age showed the highest mastadenovirus infection rates (89.78%) at an average monthly temperature of 18.2℃. Moreover, we observed a negative correlation between human mastadenovirus infection and temperature, wind chill, and air pressure. The obtained results indicate that climatic factors affect the rate of human mastadenovirus infection. Therefore, it may be possible to predict the instance when preventive strategies would yield the most effective results.

• Journal of the Korean Data and Information Science Society
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• v.21 no.3
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• pp.407-417
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• 2010

In Basel II compliance, internal rating systems are allowed for banks to enhance the self control and the validation of the system are getting more important. The validation methods are composed of qualitative test and quantitative test, three basic standards of which are discriminatory power, stability and calibration. The aim of this article is to review the quantitative tests for calibration and find a new method for it. These methods for discrimination between forecasted PD and observed PD include binomial test, chi square test, Brier score, traffic lights approach, normal test and extended traffic lights approach. We introduce a modified extended traffic lights approach considering asset correlations.

• Journal of Korean Society of Transportation
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• v.32 no.4
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• pp.369-379
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• 2014

The Statistical regression model has been used to construct crash prediction models, despite its limitations in assuming data distribution and functional form. In response to the limitations associated with the statistical regression models, a few studies based on non-parametric methods such as neural networks have been proposed to develop crash prediction models. However, these models have a major limitation in that they work as black boxes, and therefore cannot be directly used to identify the relationships between crash frequency and crash factors. A genetic programming model can find a solution to a problem without any specified assumptions and remove the black box effect. Hence, this paper investigates the application of the genetic programming technique to develope the crash prediction model. The data collected from the Gyeongbu expressway during the past three years (2010-2012), were separated into straight and curve sections. The random forest technique was applied to select the important variables that affect crash occurrence. The genetic programming model was developed based on the variables that were selected by the random forest. To test the goodness of fit of the genetic programming model, the RMSE of each model was compared to that of the negative binomial regression model. The test results indicate that the goodness of fit of the genetic programming models is superior to that of the negative binomial models.