• Asian Pacific Journal of Cancer Prevention
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• v.15 no.11
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• pp.4575-4581
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• 2014

Turkey protects its entire population of 75 million people with all the MPOWER measures at the highest level. The aim of this study is to make a comparison of smoking and addiction data obtained from Sakarya University students in 2005-6 and 2012-13. A total of 4,200 (2,500 and 1,700 for each academic year) students at Sakarya University in Sakarya, Turkey, were randomly selected for sampling purposes. The selected participants represented Sakarya University students. Data were collected using a pretested anonymous and confidential, self-completed questionnaire which took 15-20 minutes to complete and Fagerstrom Test for nicotine dependence. Chi-squared, Spearman correlation, and binary logistic regression tests were used to define associations, if any. The level of significance was kept at alpha=0.05. Smoking prevalance dropped by 8.5% (from 26.9% to 18.5%). Male gender, older age, high family smoking index, low self-rated school success, and high peer smoker proportion were common variables that have correlation with smoking status. In the binary logistic regression test the highest contributor to "being a smoker" was found to be the rate of peer smokers. Having all friends smoking puts the student a a 47.5 and 58.0 times higher risk for smoking for males and females, respectively. Our results suggest an admirable diminution of smoking prevalance among Sakarya University students, which can be attributed to MPOWER protection.

• Journal of the Korean Society for information Management
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• v.23 no.1 s.59
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• pp.243-259
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• 2006

This paper examines the values of various library functions according to users' points of view. To execute this study, the several 'circumstance', related variables and 'condition' variables that lead to factors or functions of academic libraries were measured. Analysis was carried out in three stages. In the first, factor analysis was used on the three multi variable dimensions to ensure that the groups of variables loaded significantly and uniquely on the respective dimensions. The second phase of analysis involved the use of binary logistic regression analysis to complete research models. In the third phase, t-test was used to identify significant differences in the independent variables for additional explanation of the models. Books, competition & effectiveness and fee verses free (fee-free hereafter) are the three main factors that distinguish not only the purpose of using an academic library but also the degree of influence on knowledge, information and library facilities for the users. In addition, the fee-free factor related to digital library facilities was also uncovered.

• Journal of the Economic Geographical Society of Korea
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• v.19 no.1
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• pp.104-121
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• 2016

This study was conducted in order to investigate the factors affecting the elderly employment and especially focused on the factor of their residential areas. This paper performs binary logistic regression analysis with the micro data of 2014 Survey of Living Conditions and Welfare Needs of Older Koreans. To reveal the influence on the elderly employment, various dependent variables was used such as demographical, health, household, economic, lifelong job, living environment, and residential area characteristics. The elderly in rural areas have higher possibility of currently working than those in urban areas. Based on the results, more various and complex factors affected on the employment of the urban elderly. This suggested that differentiated policy supports were needed in the urban and rural areas.

• International Journal of Highway Engineering
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• v.13 no.2
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• pp.49-56
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• 2011

Understanding various casual factors affecting the occurrence of freeway traffic crash is a backbone of deriving effective countermeasures. The first step toward understanding such factors is to identify crash risks on freeways. Unlike existing studies, this study focused on the unsafe vehicle maneuvering that can be detected by in-vehicle sensors. The recent advancement of sensor technologies allows us to gather and analyze detailed microscopic events leading to crash occurrence such as the abrupt change in acceleration. This study used an accelerometer to capture the unsafe events. A set of candidate variables representing unsafe events were derived from analyzing acceleration data obtained by the accelerometer. Then, the crash risk was modeled by the binary logistic regression technique. The probabilistic outcome of crash risk can be provided by the proposed model. An application of the methodology assessing crash risk was presented, and further research items for the successful field implementation were also discussed.

• Journal of Korean Society of Transportation
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• v.26 no.1
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• pp.155-164
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• 2008

Variable Message Signs (VMS) is one of the major components for Intelligent Transport Systems (ITS) services that provides real-time traffic and incident information to drivers. The objective of this research was to develop a method determining the optimal location of VMS considering safety and driving characteristics of various drivers. A driving simulator was utilized to evaluate how drivers can safely exit to off-ramp depending on various VMS locations while information relating route diversion was provided. The binary logistic regression and factor analysis were applied in developing a probability model that predicts the success of safe off-ramp exiting. Based on the developed probability model, a method to estimate the spacing between VMS and off-ramp is suggested. It is expected that the products of this study would be utilized as a tool in determining VMS locations for ITS planners and designers.

• International Journal of Highway Engineering
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• v.12 no.1
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• pp.39-46
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• 2010

Delineator is a useful device to support driver's safer maneuver. Effective placement and operation of the delineator would lead to prevent traffic accidents on the roads. This study evaluates the effectiveness of parameters associated with delineator placement and operation, which include spacing, height and size, from the point of user's satisfaction. Also, this study devises a methodology for determining such parameters using binary logistic regression technique. The proposed model is capable of producing probabilistic measure of user's satisfaction according to the various parameters. The outcome of this study would be useful fundamentals for more effective placement and operation of delineators.

• Journal of Korean Society of Transportation
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• v.32 no.3
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• pp.198-206
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• 2014

According to the statistics of the National Police Agency, red light running (RLR) crashes represent a significant safety issue throughout Korea. This study deals with the RLR crashes occurred at signalized intersections in Cheongju. The objectives of this study are to comparatively analyze the characteristics of between RLR crashes and the Non-RLR crashes, and to find out factors using a Binary Logistic Regression(BLR) model. In pursuing the above, the study gives particular attentions to testing the differences between the above two groups with the data of 2,246 RLR/ 3,884 Non-RLR crashes (2007-2011). The main results are as follows. First, many RLR crashes were occurred in the nighttime and in going straight. Second, the difference between RLR and Non-RLR crashes were clearly defined by crash type, maneuver of vehicle before crash, age of driver (30s, 50s), alcohol use and accident pattern. Finally, a statistically significant model (Hosmer and Lemeshow test : 7.052, p-value : 0.531) was developed through the BLR model.

• Journal of Korean Society of Transportation
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• v.29 no.3
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• pp.73-82
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• 2011

Recent advancement in traffic surveillance systems has allowed the researchers to obtain more detailed vehicular movement such as individual vehicle trajectory data. Understanding the characteristics of interactions between leading and following vehicles in the traffic flow stream is a backbone for designing and evaluating more sophisticated traffic and vehicle control strategies. This study proposes a methodology for estimating rear-end crash potential, as a probabilistic measure, in real-time based on the analysis of vehicular movements. The methodology presented in this study consists of three components. The first predicts vehicle position and speed every second using a Kalman filtering technique. The second estimates the probability for the vehicle's trajectory to belong to either 'changing lane' or 'going straight'. A binary logistic regression (BLR) is used to model the lane-changing decision of the subject vehicle. The other component calculates crash probability by employing an exponential decay function that uses time-to-collision (TTC) between the subject vehicle and the front vehicle. The result of this study is expected to be adapted in developing traffic control and information systems, in particular, for crash prevention.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.3
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• pp.73-84
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• 2010

This study presents a novel method to identify hazardous segments of freeway using global positioning system(GPS) based probe vehicle data. A variety of candidate contributing factors leading to higher potential of accident occurrence were extracted from the probe vehicle dataset. The research problem was defined as a classification problem, then a well-known classifier, bayesian neural network was adopted to solve the problem. A binary logistic regression technique was also used for selecting salient input variables. Test results showed that the proposed method is promising in extracting hazardous freeway sections. The outcome of this study will be effectively used for evaluating the safety of freeway sections and deriving countermeasures to prevent accidents.

• Journal of the Economic Geographical Society of Korea
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• v.16 no.1
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• pp.1-16
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• 2013

This study investigates the spatial distribution characteristics of Korean fashion industries during the last decade, in which the economic geography of fashion industries has changed dynamically with economic globalization and "thus resulted in increased" demand "of" diversification. In particular, this study examines the spatial distribution patterns of fashion industries in the Seoul metropolitan area where fashion industries are highly agglomerated. For the purpose, this study applies Moran's I Index of spatial autocorrelation analysis for seven functional sectors of fashion industries related to fashion production. The global and local agglomeration patterns are examined for each functional sector. The results clarify the distinction in the spatial agglomeration patterns among the seven functional sectors of fashion industries in the Seoul Metropolitan area. Logit models are developed to examine the interrelationships among functional sectors in their spatial agglomeration distribution patterns. By conducting binary logistic regression analysis, we find out how the spatial agglomeration of each functional sector is related to the others.