• Title/Summary/Keyword: Negative Binomial Regression Model

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A Study on the Influence of Urban Environment on the Generation of Thermal Diseases (도시 환경이 온열질환 발생에 미치는 영향에 관한 연구)

  • Lee, Su-Mi;Kweon, Ihl;Kim, Yong-Jin
    • The Journal of the Korea Contents Association
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    • v.19 no.12
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    • pp.84-92
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    • 2019
  • The deterioration of the urban heat environment due to climate change and the occurrence of heat-related diseases have emerged as one of the major social problems. This has led to more research on climate change, including heat waves, but it is mainly focused on climate factors. However, the urban heat island phenomenon accelerates the summer heat wave, and the increasing trend of heat-related patients in urban areas suggests the impact of the city's environment. Thus, this study analyzed the effects of physical and social characteristics of urban areas on heat-related patients in Seoul and Gyeonggi-do. The analysis showed that the ratio of the total area of residential, commercial and industrial facilities, the main source of heat energy locality, among the land use statuses, was not statistically significant, but the road area and the green area were found to have a positive and negative The population density and the percentage of people aged 65 or older, the percentage of people living alone and the proportion of people receiving basic living were all shown to be significant, with only the ratio of elderly living alone and the ratio of population density having negative effects. The results of the study can be used to develop urban policy alternatives related to local warming patients.

A Study of Accident Models for Highway Interchange Ramps (고속도로 연결로의 교통사고 추정모형 연구)

  • Roh, Chang-Gyun;Park, Chong-Seo;Son, Bong-Soo
    • Journal of Korean Society of Transportation
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    • v.26 no.4
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    • pp.29-40
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    • 2008
  • Although a good understanding of the relationship between highway traffic accidents and highway geometric features is fundamental in highway design and safety, the relationship is not well understood quantitatively. The overall goal of this paper is to formulate a reliable statistical model fitting to historical highway accident data. The model can be used to estimate the effect of road design elements on safety for the practical purposes of highway design applications. En route to achieving this goal, a number of specific research objectives were accomplished: investigate the major design elements affecting highway safety; review the existing modeling approaches in order to assess the relationship between safety and highway design features; and formulate a statistical model fitting to the accident data in order to estimate the interchange ramp junction accident frequency of rural highways.

Characteristics of Geometric Conditions Affecting Freeway Traffic Safety at Nighttime, Sunrise, and Sunset (야간 및 일출몰 시간대 교통안전에 영향을 미치는 고속도로 기하구조 특성분석)

  • Hong, Sung-Min;Kim, Joon-Ki;Oh, Cheol
    • Journal of Korean Society of Transportation
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    • v.30 no.4
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    • pp.95-106
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    • 2012
  • Driver's capability of identifying the change in freeway alignments and environments is one of important factors associated with traffic safety on freeways. In particular, driver's visibility and recognition capability are highly dependent on the altitude of the sun by sunset, sunrise, and nighttime. The purpose of this study is to identify the characteristics of geometric conditions affecting crash occurrences at sunset, sunrise, and nighttime. Poisson and negative binomial regressions were adopted to predict freeway crash frequency in this study. Freeway crash data during 2007~2010 were used for developing the crash frequency models. A set of variables representing the characteristics of geometric conditions were identified as significant ones affecting crash occurrences. The results of this study would be useful in deriving effective countermeasures for preventing traffic crashes that mainly occur at sunset, sunrise, and nighttime on freeways.

Assessing the Impacts of Job insecurity, Job satisfaction and Relationship with customers on Intention of Retention of Employees in Social Enterprises (사회적기업 근로자의 직무불안, 직무만족, 고객과의 관계가 재직 의도에 미치는 영향)

  • Lee, Eun Jung
    • Journal of Digital Convergence
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    • v.11 no.12
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    • pp.835-843
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    • 2013
  • Despite their social mission, social enterprises work in the changing global economic environment and therefore face to comply with performance objectives. This situation means that human resources management strategy has a crucial role to play. Especially, the challenge in maintaining competitive efficiency depends on achieving a lower level of employee turnover. This study aims to investigate the role of job insecurity, job satisfaction, relationship with customers regarding the intention of retention among social enterprise workers. Data were collected in South Korea from 271 women employees in 36 social enterprises and the binomial logistic regression was used to assess the model hypothesized. As the result, social enterprise employees showed a considerably positive attitude toward the intent to stay their workplace. However, job insecurity appeared to have the strongest negative effect on the intention of retention, whereas job satisfaction and relationship with customers had the positive effects, above and beyond demographic variables and organization variables. The result suggested the human resource management can play a significant role in retaining social enterprise employees by reducing job instability and improving job satisfaction and customers management.

The Effect of Weather and Season on Pedestrian Volume in Urban Space (도시공간에서 날씨와 계절이 보행량에 미치는 영향)

  • Lee, Su-mi;Hong, Sungjo
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.20 no.9
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    • pp.56-65
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    • 2019
  • This study empirically analyzes the effect of weather on pedestrian volume in an urban space. We used data from the 2009 Seoul Flow Population Survey and constructed a model with the pedestrian volume as a dependent variable and the weather and physical environment as independent variables. We constructed 28 models and compared the results to determine the effects of weather on pedestrian volume by season, land use, and time zone. A negative binomial regression model was used because the dependent variable did not have a normal distribution. The results show that weather affects the volume of walking. Rain reduced walking volume in most models, and snow and thunderstorms reduced the volume in a small number of models. The effects of the weather depended on the season and land use, and the effects of environmental factors depended on the season. The results have various policy implications. First, it is necessary to provide semi-outdoor urban spaces that can cope with snow or rain. Second, it is necessary to have different policies to encourage walking for each season.

Global Big Data Analysis Exploring the Determinants of Application Ratings: Evidence from the Google Play Store

  • Seo, Min-Kyo;Yang, Oh-Suk;Yang, Yoon-Ho
    • Journal of Korea Trade
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    • v.24 no.7
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    • pp.1-28
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    • 2020
  • Purpose - This paper empirically investigates the predictors and main determinants of consumers' ratings of mobile applications in the Google Play Store. Using a linear and nonlinear model comparison to identify the function of users' review, in determining application rating across countries, this study estimates the direct effects of users' reviews on the application rating. In addition, extending our modelling into a sentimental analysis, this paper also aims to explore the effects of review polarity and subjectivity on the application rating, followed by an examination of the moderating effect of user reviews on the polarity-rating and subjectivity-rating relationships. Design/methodology - Our empirical model considers nonlinear association as well as linear causality between features and targets. This study employs competing theoretical frameworks - multiple regression, decision-tree and neural network models - to identify the predictors and main determinants of app ratings, using data from the Google Play Store. Using a cross-validation method, our analysis investigates the direct and moderating effects of predictors and main determinants of application ratings in a global app market. Findings - The main findings of this study can be summarized as follows: the number of user's review is positively associated with the ratings of a given app and it positively moderates the polarity-rating relationship. Applying the review polarity measured by a sentimental analysis to the modelling, it was found that the polarity is not significantly associated with the rating. This result best applies to the function of both positive and negative reviews in playing a word-of-mouth role, as well as serving as a channel for communication, leading to product innovation. Originality/value - Applying a proxy measured by binomial figures, previous studies have predominantly focused on positive and negative sentiment in examining the determinants of app ratings, assuming that they are significantly associated. Given the constraints to measurement of sentiment in current research, this paper employs sentimental analysis to measure the real integer for users' polarity and subjectivity. This paper also seeks to compare the suitability of three distinct models - linear regression, decision-tree and neural network models. Although a comparison between methodologies has long been considered important to the empirical approach, it has hitherto been underexplored in studies on the app market.

Analysis of Total Crime Count Data Based on Spatial Association Structure (공간적 연관구조를 고려한 총범죄 자료 분석)

  • Choi, Jung-Soon;Park, Man-Sik;Won, Yu-Bok;Kim, Hag-Yeol;Heo, Tae-Young
    • The Korean Journal of Applied Statistics
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    • v.23 no.2
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    • pp.335-344
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    • 2010
  • Reliability of the estimation is usually damaged in the situation where a linear regression model without spatial dependencies is employed to the spatial data analysis. In this study, we considered the conditional autoregressive model in order to construct spatial association structures and estimate the parameters via the Bayesian approaches. Finally, we compared the performances of the models with spatial effects and the ones without spatial effects. We analyzed the yearly total crime count data measured from each of 25 districts in Seoul, South Korea in 2007.

Predictors of Blood and Body Fluid Exposure and Mediating Effects of Infection Prevention Behavior in Shift-Working Nurses: Application of Analysis Method for Zero-Inflated Count Data (교대근무 간호사의 혈액과 체액 노출 사고 예측 요인과 감염예방행위의 매개효과: 영과잉 가산 자료 분석방법을 적용하여)

  • Ryu, Jae Geum;Choi-Kwon, Smi
    • Journal of Korean Academy of Nursing
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    • v.50 no.5
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    • pp.658-670
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    • 2020
  • Purpose: This study aimed to identify the predictors of blood and body fluid exposure (BBFE) in multifaceted individual (sleep disturbance and fatigue), occupational (occupational stress), and organizational (hospital safety climate) factors, as well as infection prevention behavior. We also aimed to test the mediating effect of infection prevention behavior in relation to multifaceted factors and the frequency of BBFE. Methods: This study was based on a secondary data analysis, using data of 246 nurses from the Shift Work Nurses' Health and Turnover study. Based on the characteristics of zero-inflated and over-dispersed count data of frequencies of BBFE, the data were analyzed to calculate zero-inflated negative binomial regression within a generalized linear model and to test the mediating effect using SPSS 25.0, Stata 14.1, and PROCESS macro. Results: We found that the frequency of BBFE increased in subjects with disturbed sleep (IRR = 1.87, p = .049), and the probability of non-BBFE increased in subjects showing higher infection prevention behavior (IRR = 15.05, p = .006) and a hospital safety climate (IRR = 28.46, p = .018). We also found that infection prevention behavior had mediating effects on the occupational stress-BBFE and hospital safety climate-BBFE relationships. Conclusion: Sleep disturbance is an important risk factor related to frequency of BBFE, whereas preventive factors are infection prevention behavior and hospital safety climate. We suggest individual and systemic efforts to improve sleep, occupational stress, and hospital safety climate to prevent BBFE occurrence.

Visualization analysis using R Shiny (R의 Shiny를 이용한 시각화 분석 활용 사례)

  • Na, Jonghwa;Hwang, Eunji
    • Journal of the Korean Data and Information Science Society
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    • v.28 no.6
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    • pp.1279-1290
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    • 2017
  • R's {shiny} package provides an environment for creating web applications with only R scripts. Shiny does not require knowledge of a separate web programming language and its development is very easy and straightforward. In addition, Shiny has a variety of extensibility, and its functions are expanding day by day. Therefore, the presentation of high-quality results is an excellent tool for R-based analysts. In this paper, we present actual cases of large data analysis using Shiny. First, geological anomaly zone is extracted by analyzing topographical data expressed in the form of contour lines by analysis related to spatial data. Next, we will construct a model to predict major diseases by 16 cities and provinces nationwide using weather, environment, and social media information. In this process, we want to show that Shiny is very effective for data visualization and analysis.

A Study on Improvement of Design Method for Freeway Diverging Areas (고속도로 분류부 설계기법 개선 연구)

  • Park, Jae-Beom;Lee, Seung-Jun;Gang, Jeong-Gyu;Kim, Il-Hwan
    • Journal of Korean Society of Transportation
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    • v.25 no.1 s.94
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    • pp.23-35
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    • 2007
  • Freeway diverging areas are very vulnerable to traffic accidents due to abrupt vehicle speed changes and geometric changes. Therefore, in designing diverging areas, much attention should be Paid to safety The Present design criteria about freeway diverging areas regulate transition sections for lane changes, deceleration lanes, transition corves for direction changes. and other similar items. However, the design criteria were often violated in implementation because of ambiguities in the criteria. This study aims at clarifying and improving the present design criteria for freeway diverging areas. For this, field survey data and traffic accident data for diverging areas were analyzed.