• Journal of the Korean Data and Information Science Society
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• v.20 no.5
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• pp.819-827
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• 2009

This study was conducted to investigate the relationship between the sociodemographic factors and the Korean consumers palatability evaluation grades with Hanwoo sensory evaluation data. The dichotomy logistic regression model and the multinomial logistic regression model are fitted with the independent variables such as the consumer living location, age, gender, occupation, monthly income, and beef cut and the the palatability grade as the dependent variable. Stepwise variable selection procedure is incorporated to find the final model and odds ratios are calculated to find the associations between categories.

• Journal of Sensor Science and Technology
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• v.29 no.5
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• pp.348-353
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• 2020

This paper presents an adaptive method to avoid obstacles in various environmental settings, using a two-dimensional (2D) LiDAR sensor for mobile robots. While the conventional reaction based smooth nearness diagram (SND) algorithms use a fixed safety distance criterion, the proposed algorithm autonomously changes the safety criterion considering the obstacle density around a robot. The fixed safety criterion for the whole SND obstacle avoidance process can induce inefficient motion controls in terms of the travel distance and action smoothness. We applied a multinomial logistic regression algorithm, softmax regression, to classify 2D LiDAR point clouds into seven obstacle structure classes. The trained model was used to recognize a current obstacle density situation using newly obtained 2D LiDAR data. Through the classification, the robot adaptively modifies the safety distance criterion according to the change in its environment. We experimentally verified that the motion controls generated by the proposed adaptive algorithm were smoother and more efficient compared to those of the conventional SND algorithms.

• Communications for Statistical Applications and Methods
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• v.27 no.2
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• pp.225-239
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• 2020

Analysis approaches for single compositional data are well established; however, effective analysis strategies for paired compositional data remain to be investigated. The current project was motivated by studies of age-related hearing loss (presbyacusis), where subjects are classified into four audiometric phenotypes that need to be ranked within these phenotypes based on their paired compositional data. We address this challenge by formulating this problem as a classification problem and integrating a penalized multinomial logistic regression model with compositional data analysis approaches. We utilize Elastic Net for a penalty function, while considering average, absolute difference, and perturbation operators for compositional data. We applied the proposed approach to the presbyacusis study of 532 subjects with probabilities that each ear of a subject belongs to each of four presbyacusis subtypes. We further investigated the ranking of presbyacusis subjects using the proposed approach based on previous literature. The data analysis results indicate that the proposed approach is effective for ranking subjects based on paired compositional data.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.4
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• pp.148-163
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• 2021

The diversification of the New Deal urban regeneration projects, that started in 2017 in accordance with the "Special Act on Urban Regeneration Activation and Support", generated the increased demand for the accuracy of data-driven diagnosis and project type forecast. Thus, this research was conducted to develop an application model able to identify the most appropriate New Deal project type for "eup", "myeon" and "dong" across the country. Data for application model development were collected through Statistical geographic information service(SGIS) and the 'Urban Regeneration Comprehensive Information Open System' of the Urban Regeneration Information System, and data for the analysis model was constructed through data pre-processing. Four models were derived and simulations were performed through polynomial regression analysis and multinomial logistic regression analysis for the application of the appropriate New Deal project type. I verified the applicability and validity of the four models by the comparative analysis of spatial distribution of the previously selected New Deal projects by targeting the sites located in Seoul by each model and the result showed that the DI-54 model had the highest concordance rate.

• Smart Media Journal
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• v.5 no.4
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• pp.75-82
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• 2016

Although Korea's economic and domestic automobile market through the change of road environment are growth, the traffic accident rate has also increased, and the casualties is at a serious level. For this reason, the government is establishing and promoting policies to open traffic accident data and solve problems. In this paper, describe the method of predicting traffic accidents by eliminating the class imbalance using the traffic accident data and constructing the Hybrid Model. Using the original traffic accident data and the sampled data as learning data which use FP-Growth algorithm it learn patterns associated with traffic accident injury severity. Accordingly, In this paper purpose a method for predicting the severity of a victim of a traffic accident by analyzing the association patterns of two learning data, we can extract the same related patterns, when a decision tree and multinomial logistic regression analysis are performed, a hybrid model is constructed by assigning weights to related attributes.

• Knowledge Management Research
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• v.6 no.2
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• pp.23-47
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• 2005

This study is performed the multinomial logistic regression with the officials needs level about a component of knowledge administration for drawing a demand estimation model in the knowledge administration activities. This study is not that an activity and domain of knowledge administration is to apply and to operate uniformly it in public sector, one is suggested an application with a demand diagnose of knowledge administration in order to saw a course of the knowledge administration programs to suit a function and role of public administration. A result of this study is that an activity and domain of the knowledge administration is different from a component of it namely, knowledge creating, knowledge organizing, knowledge sharing and distribution, knowledge utility, and knowledge store. And the officials individual characteristics, administration agency, a kind of business, and a function and role of work are different from demand of knowledge administration. Also, the practical use of KMS (knowledge management system) is not so high in public sector. Accordingly, the tools of knowledge administration will deliberate on a consolidation with the existing system in the device.

• Journal of the Korea Convergence Society
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• v.10 no.2
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• pp.75-81
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• 2019

The purpose of this study was to perform a convergence study for the investigation of the trend of research topics related to thyroid cancer in Korea. We collected related research papers from DBpia and employed LDA-based topic model. In result, we identified four research topics, each of which concerns "Surgery", "Disease aggressiveness", "Survival analysis", and "Well-being of patients". With multinomial logistic regression, we found significant time trend, where "Surgery"-related topic was popular before 2000, topics regarding "Disease aggressiveness" and "Survival analysis" were frequently addressed in the 2000s, and "Survival analysis" and especially "Well-being of patients" have been pursued since 2010. The findings would serve as a reference guide for research directions. Future work may examine whether the recent change in research topics is observed in other diseases.

• The Journal of the Convergence on Culture Technology
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• v.6 no.4
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• pp.453-468
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• 2020

This study was conducted to investigate factors influencing physical activity in female nursing students based on the habit formation model. The participants were 207 female students at G nursing college and J nursing college located in J city. All data were collected from 31, August to 14, September in 2020 and analyzed by descriptive statistics, ANOVA and Scheffĕ test, Pearson's correlation coefficient, Univariate, and Multivariate multinomial logistic regression using SPSS/WIN 22.0 program. The average level of physical activity measured by the Korean version of IPAQ was 2506.31±2807.05 MET-min/week. According to the physical activity category classified by IPAQ, there were 59students(28.5%) in the high group, 98students(47.3%) in the moderate group, and 50students(24.2%) in the low group. Physical activity habit strength was the significant factor influencing physical activity in female nursing students. Therefore, this study suggests that it is necessary to develop the habit formation program and verify effectiveness for enhancing and maintaining the physical activity in female nursing students.

• Journal of Construction Engineering and Project Management
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• v.8 no.2
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• pp.17-33
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• 2018

This study investigates the stability of professionals' cost variability factor-rankings across different levels of cost-variability and response scenarios. Descriptive statistics are used to examine the stability of factor-ranking for 20 cost variability factors and a Multinomial Logistic (MNL) regression model was implemented to examine the stability of cost variability factors across three cost variability levels. The finding on the descriptive statistics indicated that professionals' factors-rankings are stable only for external factors. The MNL regression results on factor-stability suggested that 8 out of the 20 evaluated factors were unstable determinant of lower cost variability levels. These factors are "risk associated with the project", "personal bias and poor professionalism of the estimators", "limited time available to complete the project", "lack of skills and experience by estimator" "geographical location of projects", "incomplete & rush designs for estimate", "unforeseen or unexpected site constraints", "high class bidders for the contractors". Similarly lack of experience and large size projects were observed to be unstable as well. These observations suggest that professionals' view on pre-tender cost variability factor-ranking yields unstable factor rankings hence should not be relied upon as the only mechanisms to mitigate cost related risks in construction projects.

• Journal of Korean Public Health Nursing
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• v.28 no.2
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• pp.333-346
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• 2014

Purpose: This study was conducted in order to identify factors that influence depression for low-income elderly who live at home from the International Classification of Functioning model (ICF). Methods: The subjects were 205 elderly people living at home in two public health centers located in metropolitan cities. Subjects were divided according to their depression scores, which were measured using the GDS-short form, including normal, risk, and depression groups. Each variable was consistent with factors of the ICF model, including health condition, individual factors, environmental factors, body function, activities, and participation. Data were collected using structured questionnaires. ANOVA, $x^2$, Pearson's correlation coefficient, and Multinomial logistic regression with IBM SPSS 21.0 were used for analysis of the data. Results: Statistically significant differences were observed among normal, risk, and depression groups regarding personal factors. Gender, education level, numbers of diseases, perceived health, life satisfaction, and social support were identified as the variables that had a significant impact on depression of low-income elderly living at home. Conclusion: Results of this study indicate that there is a need for construction and implementation of strategies that strengthen life satisfaction and social support in order to lower depression of low-income elderly.