• 제목/요약/키워드: Multinomial Logistic Regression

검색결과 196건 처리시간 0.023초

2차원 라이다 센서 데이터 분류를 이용한 적응형 장애물 회피 알고리즘 (Adaptive Obstacle Avoidance Algorithm using Classification of 2D LiDAR Data)

  • 이나라;권순환;유혜정
    • 센서학회지
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    • 제29권5호
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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.

1인가구의 주관적 건강상태 변화: 잠재계층성장모형을 활용하여 (Trajectories of Self-rated Health among One-person Households: A Latent Class Growth Analysis)

  • 김은주;김향;윤주영
    • 지역사회간호학회지
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    • 제30권4호
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    • pp.449-459
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    • 2019
  • Purpose: The aim of this study is to explore different types of self-rated health trajectories among one-person households in Korea. Methods: We used five time-point data derived from Korea Health Panel (2011~2015). A latent growth curve modeling was used to assess the overall feature of self-rated health trajectory in one-person households, and a latent class growth modeling was used to determine the number and shape of trajectories. We then applied multinomial logistic regression on each class to explore the predicting variables. Results: We found that the overall slope of self-rated health in one-person households decreases. In addition, latent class analysis demonstrated three classes: 1) High-Decreasing class (i.e., high intercept, significantly decreasing slope), 2) Moderate-Decreasing class (i.e., average intercept, significantly decreasing slope), and 3) Low-Stable class (i.e., low intercept, flat and nonsignificant slope). The multinomial logistic regression analysis showed that the predictors of each class were different. Especially, one-person households with poor health condition early were at greater risk of being Low-Stable class compared with High-Decreasing class group. Conclusion: The findings of this study demonstrate that more attentions to one-person households are needed to promote their health status. Policymakers may develop different health and welfare programs depending on different characteristics of one-person household trajectory groups in Korea.

노인의 구강건강상태와 체질량지수의 연관성 (Association between oral health status and body mass index in older adults)

  • 조윤영;이윤환;김진희
    • 한국치위생학회지
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    • 제16권1호
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    • pp.129-136
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    • 2016
  • Objectives: The purpose of the study is to investigate the relationship between oral health status and body mass index (BMI) in adults over 65 years old. Methods: The study subjects were 4,550 adults over 65 years old from the 5th Korea National Health and Nutrition Examination Survey(KNHANES V) in 2010-2012. Mastication-related oral health status included the number of remaining teeth, and mean number of decayed, missing, and filled permanent teeth(DMFT). Body mass index(BMI, $kg/m^2$) was categorized as underweight(<18.5), normal weight (18.5-22.9), overweight(23.0-24.9), and obese(${\geq}25.0$). Multinomial logistic regression analysis was performed to examine the association of BMI categories with the number of remaining teeth and DMFT. Results: The mean number of DMFT was highest($13.0{\pm}0.7$) in the underweight group and lowest($8.8{\pm}0.3$) in the obese group. Those having less favorable masticatory ability, and fewer number of remaining teeth and no prosthesis, tended to be underweight. Those having a higher number of remaining teeth and prosthetic teeth tended to be overweight or obese. In the multinomial logistic regression analysis, compared with those having 20 or more remaining teeth, including prosthetic teeth, those having less than 20 remaining teeth and no prosthesis had 4.48 times higher odds ratio of being underweight. DMFT was positively associated with underweight, while negatively associated with overweight or obesity. Conclusions: The masticatory ability and dental caries prevention maintained the healthy body weight in adults of old age.

센서 데이터를 이용한 전기 기관차의 이상 상태 요인분석 (Failure Analysis to Derive the Causes of Abnormal Condition of Electric Locomotive Subsystem)

  • 소민섭;전홍배;신종호
    • 산업경영시스템학회지
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    • 제41권2호
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    • pp.84-94
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    • 2018
  • In recent years, the diminishing of operation and maintenance cost using advanced maintenance technology is attracting many companies' attention. Especially, the heavy machinery industry regards it as a crucial problem since a failure of heavy machinery requires high cost and long downtime. To improve the current maintenance process, the heavy machinery industry tries to develop a methodology to predict failure in advance and to find its causes using usage data. A better analysis of failure causes requires more data so that various kinds of sensor are attached to machines and abundant amount of product usage data is collected through the sensor network. However, the systemic analysis of the collected product usage data is still in its infant stage. Many previous works have focused on failure occurrence as statistical data for reliability analysis. There have been less works to apply product usage data into root cause analysis of product failure. The product usage data collected while failures occur should be considered failure cause analysis. To do this, this study proposes a methodology to apply product usage data into failure cause analysis. The proposed methodology in this study is composed of several steps to transform product usage into failure causes. Various statistical analysis combined with product usage data such as multinomial logistic regression, T-test, and so on are used for the root cause analysis. The proposed methodology is applied to field data coming from operated locomotive and the analysis result shows its effectiveness.

안면골 골절의 발생 인자에 대한 통계학적 분석 (Statistical Analysis of Factors Associated with Facial Bone Fractures)

  • 서용훈;김영준
    • 대한두개안면성형외과학회지
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    • 제13권1호
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    • pp.36-40
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    • 2012
  • Purpose: Statistical analysis of facial bone fractures has been performed in various papers. However, reports on risk factors for facial bone fractures are rare. In order to prevent facial bone fractures, it is important to determine the risk factors for their occurrence. This study seeks to perform a statistical analysis on and identify the risk factors associated with facial bone fractures. Methods: A retrospective study was performed to assess facial bone fractures in patients presenting from October 2009 to January 2011 through a chart review. The data collected included age, gender, etiology, and alcohol consumption. Data was analyzed using multinomial logistic regression analysis. The significance level was set at p<0.05 and SAS ver. 9.2 was used. Results: A total of 489 patients were analyzed. The patients' age ranged from 2 to 85 years (mean age, $31.8{\pm}15.4$ years). The ratio of men to women was 5.0:1. The predominant group was age below 19 years old (30.9%). The main causes of facial bone fractures were assaults (37.8%), falls (27.2%), and sport accidents (19.5%). On multinomial logistic regression analysis, age, especially in the teen group was associated with assaults (p<0.05) resulting in facial bone fractures. Alcohol consumption was significantly associated with assaults and falls (p<0.05) leading to facial bone fractures. Conclusion: Facial bone fracture is a challenging problem, because of its high incidence and financial cost. The findings of this study indicate that more effective policies aimed at reducing alcohol intake and teenage violence are needed.

관광객 특성에 따른 어촌체험프로그램 선택의 영향력 분석 (A Study on Influence of Fishing Villages Experience Program Choice by the Tourist Characteristics)

  • 이서구;최규철;김정태
    • 농촌계획
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    • 제26권3호
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    • pp.1-12
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    • 2020
  • The purpose of this study is to analysis the influence of fishing villages experience programs choice by the tourist characteristics. As an analysis method, a statistical technique of multinomial logistic regression was used. The dependent variable have typified about 70 fishing experience programs, such as tidal-flat experience, fishery experience, and fishing experience, operated by the fishing village experience recreation villages into 9 programs. The independent variables consisted of 7 groups of people: gender, age, marital status, presence of children, experience of visiting a village in a rural and fishing village experience, preference of a village in a recreational experience, and recognition of a village in a fishing village experience. As a result of analysis, no significant differences were found that the selection group preferring 'fishing culture experience', 'leports experience', 'ecological craft experience', and 'festival and event experience' in the selection of fishing village experience program compared to the group choosing 'rural experience'. On the other hand, the group preferring 'tidal flat experience' analysis that 'married' is about 14 times higher than 'unmarried', and the group preferring 'fishing village experience' is 9.55 times higher than the group preferring 'rural village experience'. In the group preferring 'fishery experience' and 'fishing experience', the group preferring 'fishing experience recreation village' was 9.21 times and 14.34 times higher than the group preferring 'rural experience recreation village'. In the 'food experience', 'married' was 25 times higher than 'unmarried'.

COVID-19 전후 소비자의 간편식 구입 빈도 결정 요인 비교 (Analysis of Determinants of Home Meal Replacement Purchase Frequency before and after COVID-19 based on a Consumer Behavior Survey)

  • 오영진;장금일;김선웅
    • 한국식품영양학회지
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    • 제34권6호
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    • pp.576-583
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    • 2021
  • The purpose of this study was to estimate the influence of the determinants for home meal replacement (HMR) purchase frequency before and after COVID-19. Multinomial logistic regression was applied to the 2018~2020 Consumer Behavior Survey for Food data from the Korea Rural Economic Institute (KREI). Gender, age, number of households, monthly income, use of eating out, delivery and takeout order service, HMR food safety concern, the frequency of cooking at home, grocery shopping, and eating alone were applied as the explanatory variables to explain HMR purchase frequency. The results are as below. Compared to the previous year, the growth rate of HMR purchase frequency in 2020 was relatively high, indicating that the COVID-19 outbreak acted as a catalyst. Unlike in 2018 and 2019, there was no statistical difference in the HMR purchase frequency between single- and multi-person households in 2020, with indicating multi-person households began to emerge as one of the major HMR consumption groups. Unlike 2018, the 2020 HMR purchase frequency showed a statistically positive relationship with those of grocery shopping and eating alone. There was a positive relationship between the frequency of eating out/food delivery orders and HMR purchases. The more often cooking at home occurred, the less HMR food was purchased.

청소년 우울 증상의 변화 궤적에 따른 잠재계층유형 및 영향요인 (Latent Classes of Depressive Symptom Trajectories of Adolescents and Determinants of Classes)

  • 김은주
    • 지역사회간호학회지
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    • 제33권3호
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    • pp.299-311
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    • 2022
  • Purpose: Untreated depression in adolescents affects their entire life. It is important to detect and intervene early depression in adolescence considering the characteristics of adolescent's depressive symptoms accompanied by internalization and externalization. The aim of this study was to identify latent classes of depressive symptom trajectories of adolescents and determinants of classes in Korea. Methods: The three time-point (2018~2020) data derived from the Korean Children and Youth Panel Survey 2018 were used (N=2,325). Latent Growth Curve Modeling (LGCM) was conducted to explore the depressive symptom trajectories in all adolescents, and Latent Class Growth Modeling (LCGM) was conducted to identify each latent class. Multinomial logistic regression analysis was performed to confirm the determinants of each latent class. Results: The LGCM results showed that there was no statistically significant change in all adolescents' depressive symptoms for 3 years. However, the LCGM results showed that four latent classes showing different trajectories were distinguished: 1) Low-stable (intercept=14.39, non-significant slope), 2) moderate-increasing (intercept=19.62, significantly increasing slope), 3) high-stable (intercept=26.30, non-significant slope), and 4) high-rapidly decreasing (intercept=26.34, significantly rapidly decreasing slope). The multinomial logistic regression analysis showed that the significant determinants (i.e., gender, self-esteem, aggression, somatization, peer relationship) of each latent class were different. Conclusion: When screening adolescent's depression, it is necessary to monitor not only direct depression symptoms but also self-esteem, aggression, somatization symptoms, and peer relationships. The findings of this study may be valuable for nurses and policy makers to develop mental health programs for adolescents.

COVID-19 전후 건강식품 섭취 여부 결정요인 비교 - 2019년~2021년 식품소비행태조사 자료 이용 - (Comparison of Determinants of Healthy Food Intake Before and After COVID-19 - Based on 2019~2021 Consumer Behavior Survey for Food -)

  • 정수연;김나영;전은서;장금일;김선웅
    • 한국식품영양학회지
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    • 제36권4호
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    • pp.309-320
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    • 2023
  • This study examined the determinants of healthy food purchases before and after COVID-19 in Korea. Binomial and multinomial logistic regression models were applied to Korea Rural Economic Institute's Food Consumer Behavior Survey data from 2019 to 2021. The analysis revealed a significant decrease in the non-intake of healthy food in 2021 compared to 2019, suggesting the impact of COVID-19 on healthy food consumption. Consumption patterns also changed, with a decrease in direct purchases and an increase in gift-based purchases. Several variables showed significant effects on healthy food intake. Single-person households exhibited a higher probability of eating healthy food after COVID-19. The group perceiving themselves as healthy had a lower likelihood of consuming healthy food pre-COVID-19, but this changed after the pandemic. Online food purchases, eco-friendly food purchases, and nut consumption showed a gradual decrease in the probability of non-intake over time. Gender and age also influenced healthy food intake. The probability of eating healthy food increased in the older age group compared to the younger group, and the probability increased significantly after COVID-19. The probability of buying gifts was significantly higher in those in their 60s, indicating that the path to obtaining healthy food differed by age.

Safety Attitudes among Vietnamese Medical Staff in a Vietnam Disadvantaged Area: Latent Class Analysis

  • Thang Huu Nguyen;Thanh Hai Pham;Hue Thi Vu;Minh-Nguyet Thi Doan;Huong Thanh Tran;Mai Phuong Nguyen
    • 한국의료질향상학회지
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    • 제30권1호
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    • pp.3-14
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    • 2024
  • Purpose: We conducted this study with the aim of characterizing safety attitudes (SA) among medical staff in a disadvantaged area of Vietnam and examining associated factors with SA. Methods: A cross-sectional survey was conducted on 442 health staff members at four hospitals in Son La Province from June until August 2021. We used the Vietnamese shortened edition of the Safety Attitudes Questionnaire to measure the SA of study participations. We chose latent class analysis (LCA) to identifying the number of latent classes of SA among the study subjects. Multinomial logistic regression was used to examine factors associated with the identified SA classes. Results: The results of our LCA showed that there were three latent classes, namely high SA group (n=150, 33.9%), moderate SA group (n=236, 53.4%), and low SA group (n=56, 12.7%). The multinomial logistic regression analysis found that medical staff who had university education and above, who were nurses, and who served in non-clinical areas were more likely to be in the moderate SA group and in the high SA group than in the low SA group. Conclusion: Based on these results, several recommendations could be made to improve the SA of healthcare workers in disadvantaged areas. Further research with larger sample sizes and more diverse populations is needed to confirm these findings and to develop effective interventions to improve the SA of healthcare workers in disadvantaged areas.