• 전자공학회논문지 IE
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• v.43 no.3
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• pp.13-21
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• 2006

Ryu et al. proposed a multiple target angle tracking algorithm using the angular measurement obtained from the signal subspace estimated by the output of sensor array. Ryu's algorithm has good features that it has no data association problem and simple structure. But its performance is seriously degraded in the low signal-to-noise ratio, and it uses the angular measurement obtained from the signal subspace of sampling time, even though the signal subspace is continuously updated by the output of sensor array. For improving the tracking performance of Ryu's algorithm, a measurement fusion method is derived based on ML(Maximum Likelihood) in this paper, and it admits us to use the angular measurements obtained form the adjacent signal subspaces as well as the signal subspace of sampling time. The new target angle tracking algorithm is proposed using the derived measurement fusion method. The proposed algorithm has a better tracking performance than that of Ryu's algorithm and it sustains the good features of Ryu's algorithm.

• The Journal of the Korea Contents Association
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• v.11 no.8
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• pp.150-158
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• 2011

The purpose of this study is to investigate how the service quality of dance performance halls influences the satisfaction with performance halls and willingness of re-spectating. To perform this study, questionnaires were used and frequent analysis, factor analysis, correlation analysis, multiple regression analysis were used to analyze the collected data. Conclusions are as follows; First, the service quality of dance performance halls had an effect on the satisfaction of dance performance halls. Second, the service quality of dance performance halls had an effect on re-spectating. Third, the satisfaction with performance halls influenced the re-spectating. These results show that the higher the service quality becomes the more positive effect appears between the satisfaction of performance halls and re-spectating.

• Korean Security Journal
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• no.37
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• pp.109-135
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• 2013

The purpose of the study was to analyze how organizational learning of police officers affects empowerment components as this learning method works as a way to maximize the police organization. In order to achieve the research goal, the study selected a total of 170 police officers on duty in Gwangju Metropolitan Police Agency as a research subject for a month from July 14, 2013 to August 15. The subjects were selected via the random sampling method and were told to participate in a survey of a self-administrated method. A total of 163 (95.5%) references were used for the final analysis. The collected data was processed with SPSS for Win Version 18.0 and the variables were went through Pearson's Correlation Analysis and Multiple Regression Analysis. The results are summarized as follows. First, a hypothesis of "how social demographic characteristics have a different influence on organizational learning and empowerment" was partially confirmed. Second, another hypothesis of "how organizational learning affects empowerment of the members" was adopted.

• Journal of Digital Convergence
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• v.16 no.7
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• pp.71-78
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• 2018

The purpose of this study is to investigate the impact of win-win growth activity of domestic large firms on their management performance. we classified the management performance into four factors such as ROE(Return On Equity), ROA(Return On Assets), net income to net sales and operating income to sales. The finding of this study is outlined as follows. This paper show that the win-win growth activity has a negative impact on the firms' management performance. This study shows that win-win growth activity could generate additional costs of business activity. So, we think that industrial policy is needed for expansion of win-win growth activity.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.121-130
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• 2024

This study utilized data from 1,068 women aged 40-59, drawn from the 8th Korea National Health and Nutrition Examination Survey (KNHANES) conducted in 2020, to investigate factors impacting subjective health perception and health-related quality of life. Methodologically, STATA 15.0 was employed for complex sample mean and standard deviation calculations, complex sample weighted percentages, complex sample t-tests, and multiple regression analyses. Common factors influencing both subjective health and health-related quality of life included education level, household size, depression, and stress. Age, binge drinking, and physical activity were identified as factors influencing subjective health perception. Insurance type, employment status, and sleep disorders emerged as factors impacting health-related quality of life. Recognizing middle age as a crucial transitional phase into old age, the development of health policy programs aimed at enhancing subjective health and health-related quality of life during this period is deemed essential.

• Journal of the Korea Society of Computer and Information
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• v.29 no.8
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• pp.123-131
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• 2024

The purpose of this study is to identify the prevalence of diabetes and related factors and thereby to provide fundamental data for the prevention and management of diabetes. This study is a secondary analysis based on the raw data from the Korea National Health and Nutrition Examination Survey (KNHANES) for the years 2011 and 2021. Analysis method was frequency analysis, complex samples Chi-square test, complex samples logistic regression analysis. As a result of the study, the factors related to diabetes were sex, age, education level, hypertension, dyslipidemia, and subjective health recognition in 2011(Negelkerke R²=.255), and sex, age, education level, hypertension, dyslipidemia, mother's diabetes, and subjective health recognition in 2021(Negelkerke R²=.327). This study is meaningful in that the factors related to diabetes were identified according to time trend, and the changes in the related factors were confirmed. Development and application of an intervention program to prevent diabetes are necessary.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.3
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• pp.181-194
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• 2017

This study aims to develop a regression model for forest volume estimation using field-collected forest inventory information and airborne LiDAR data. The response variable of the model is forest stem volume, was measured by random sampling from each individual plot of the 30 circular sample plots collected in Bonghwa-gun, Gyeong sangbuk-do, while the predictor variables for the model are Height Percentiles(HP) and Height Bin(HB), which are metrics extracted from raw LiDAR data. In order to find the most appropriate model, the candidate models are constructed from simple linear regression, quadratic polynomial regression and multiple regression analysis and the cross-validation tests were conducted for verification purposes. As a result, $R^2$ of the multiple regression models of $HB_{5-10}$, $HB_{15-20}$, $HB_{20-25}$, and $HBgt_{25}$ among the estimated models was the highest at 0.509, and the PRESS statistic of the simple linear regression model of $HP_{25}$ was the lowest at 122.352. $HB_{5-10}$, $HB_{15-20}$, $HB_{20-25}$, and $HBgt_{25}-based$ models, thus, are comparatively considered more appropriate for Korean forests with complicated vertical structures.

• The korean journal of orthodontics
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• v.39 no.2
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• pp.112-119
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• 2009

Objective: To develop a mixed dentition analysis method in consideration of the normal variation of tooth sizes. Methods: According to the tooth-size of the maxillary central incisor, maxillary 1st molar, mandibular central incisor, mandibular lateral incisor, and mandibular 1st molar, 307 normal occlusion subjects were clustered into the smaller and larger tooth-size groups. Multiple regression analyses were then performed to predict the sizes of the canine and premolars for the 2 groups and both genders separately. For a cross validation dataset, 504 malocclusion patients were assigned into the 2 groups. Then multiple regression equations were applied. Results: Our results show that the maximum errors of the predicted space for the canine, 1st and 2nd premolars were 0.71 and 0.82 mm residual standard deviation for the normal occlusion and malocclusion groups, respectively. For malocclusion patients, the prediction errors did not imply a statistically significant difference depending on the types of malocclusion nor the types of tooth-size groups. The frequency of prediction error more than 1 mm and 2 mm were 17.3% and 1.8%, respectively. The overall prediction accuracy was dramatically improved in this study compared to that of previous studies. Conclusions: The computer aided calculation method used in this study appeared to be more efficient.

• Journal of Korean Society of Forest Science
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• v.102 no.3
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• pp.407-414
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• 2013

This study was conducted to classify forest cover types using the multivariate statistical analysis in the natural forest of western Mt. Jiri. On the basis of the vegetation data by point quarter sampling, the adopted analytical methods were species-area curve (SAC), hierarchical cluster analysis (HCA), indicator species analysis (ISA), and multiple discriminant analysis (MDA). SAC selected the outlier tree species which was likely to have no influence on the classification of forest cover types, excluded from all analytical process. Based on forest vegetative information, HCA classified the study area into 2 to 10 clusters and ISA indicated that the optimal number of clusters were seven. MDA was taken to test the clusters that classified with HCA and ISA. The seven clusters were classified appropriately as overall classification success were 91.3%. The classified forest cover types were named by the ratio of the dominant species in the upper layer of each cluster. They were (1) Quercus mongolica Pure forest, (2) Mixed mesophytic forest, (3) Q. mongolica - Q. serrata forest, (4) Abies koreana - Q. mongolica forest, (5) Fraxinus mandshurica forest, (6) Q. serrata forest, and (7) Carpinus laxiflora forest.

• The Korean Journal of Applied Statistics
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• v.23 no.5
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• pp.857-870
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• 2010

This study was conducted to investigate the relationship between the socio-demographic factors and the Korean consumers palatability evaluation grades with Hanwoo sensory evaluation data from 2006 to 2008 by National Institute of Animal Science. 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, beef cut and the the palatability grade as the categorical dependent variable and tenderness, 리avor and juiciness as the continuous dependent variable. Stepwise variable selection procedure is incorporated to find the final model and odds ratios are calculated to nd the associations between categories.