• Journal of the Korean Statistical Society
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• v.27 no.1
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• pp.113-132
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• 1998

In this paper, we consider a minimum distance (M.D.) estimation based on kernels for U-statistics. We use Cramer-von Mises type distance function which measures the discrepancy between U-empirical distribution function(d.f.) and modeled d.f. of kernel. In the distance function, we allow various integrating measures, which can be finite, $\sigma$-finite or discrete. Then we derive the asymptotic normality and study the qualitative robustness of M. D. estimates.

• The Journal of Korean Association of Computer Education
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• v.3 no.1
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• pp.127-134
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• 2000

Distance education, which emerged under the influence of both the rapid development of hi-tech information technology and the constructivism theory of learning, enables learners to acquire knowledge and skills needed by monitoring their learning process for themselves. Emphasis on web-based distance education and contructivism as a basis of learner-centered education does not mean that those education systems are performed without teachers or in noninterference. This study proposes a model of distance education system in which learners are taught in various levels of learning with the help of teacher agents. In the model teacher agents produce the learners' respective learning model considering the information on individual learners and also control the progress to the next step of learning with the result of the evaluation of learning accomplishment. The model of distance education system suggested in this study is able to help solve the problem that the learning resources web-based distance education provides were used only as objects of web search and to supply a basis of realizing learner-centered education.

• The Journal of the Acoustical Society of Korea
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• v.35 no.2
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• pp.83-91
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• 2016

Music-similarity computation is crucial in developing music information retrieval systems for browsing and classification. This paper overviews the recently-proposed centroid-model based music retrieval method and applies the distributional similarity measures to the model for retrieval-performance evaluation. Probabilistic distance measures (also called divergence) compute the distance between two probability distributions in a certain sense. In this paper, we consider the alpha divergence in computing distance between two centroid models for music retrieval. The alpha divergence includes the widely-used Kullback-Leibler divergence and Bhattacharyya distance depending on the values of alpha. Experiments were conducted on both genre and singer datasets. We compare the music-retrieval performance of the distributional similarity with that of the vector distances. The experimental results show that the alpha divergence improves the performance of the centroid-model based music retrieval.

• Journal of Distribution Science
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• v.13 no.8
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• pp.97-104
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• 2015

Purpose - This study examines the positive impact of the social distance between producers and users of online content, investigating and analyzing the most popular Web content. In addition, it tries to elicit the matching effect that appears when the individuals'cultural background is consistent with social distance. Research design, data, and methodology - We collected and analyzed actual data about 4,981 videos clips on YouTube, looking at six countries in order to verify the content of this study. Based on the results of the data analysis, the study conducted behavioral measurements on popularity, social distance, culture, and user engagement. The unit of analysis was the content and we collected information about the content producers and the content records. We controlled the views, comments, likes, calendar dates, and ages in the empirical models. The data was collected in 2011, with the records coming from South Korea, Japan, China, U.S., German, and France. A total of 4,980 elements were analyzed in the model. The empirical model estimated is the bivariate negative binomial distribution (NBD) model. Results - It turns out that there is a possibility that the matching effect can be diminished by variables that reflect the psychological involvement of user engagement. This study proposes academic and practical implications based on these research results. This research shows the positive effect of social distance between users and producers on the increased performance of the online content. We find the effect of social distance to be a stronger tendency in collectivism. The collectivists follow their sense of friendship and intimacy in their culture and, the social congruence effect can be found there as well. The effect, however, could erode in a social case where users are motivated by strong intrinsic and psychological factors. In addition, user engagement complicates the process of user decision making regarding the information. Conclusions - This study examines how the differential effects of social distance caused by culture could disappear through user commitment as a complicated user motivation. Some potential implications are as follows. First, a firm in the collectivism culture has to communicate based on the social distance. In fact, most online channels do not have a function that indicates the social distance as measured by favorites or subscribers. This function could help increase the performance of the content in online channels, but this increasing effect can only be found in a collectivist culture. Based on this, the firms have to communicate and announce to users the actual social distance between users and producers. Second, firms should develop a system that discovers the social distance and culture and shows these measures to users and producers, since the congruence effect between social distance and culture is found only for low user engagement. The firms can take the advantage of the congruence effect only for the development of the social distance and culture visualized system.

• Korean Journal of Environment and Ecology
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• v.28 no.4
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• pp.393-403
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• 2014

The aim of this study was to use the information deduced from biotopemap in Boryeong, Chungnam province conducted in 2011 and to select the wildlife survey point. The information used for the study was deduced from the knowledge and experience of wildlife specialists and was realized by 6 environmental variables (Outside distance from food vegetation, Outside distance from farm land, Outside distance from forest, Human density, Outside distance from road, Outside distance from water). 6 environmental variables were modeled by map overlay method and the model could deduce the correlation of 94.72% as a result of comparing with occurrence information. The areas predicted to have many occurrences were rural landscapes, forests, and valleys, and they can be used to deduce the quality wildlife survey results in the limit of survey range (area, schedule, and budget). However, it had the limit points such as the inside of forests was excluded, all species did not prefer the same habitat. The following studies are needed for this part in the future.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.9
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• pp.836-842
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• 2015

In this paper, the target size and model based target size estimator (TMBE) algorithm is presented for iimaging infrared (IIR) seeker. At the imaging seeker, target size information is important factor for accurate tracking. The model based target size estimator filter (MBEF) algorithm was proposed to estimate target size at imaging infrared seeker. But, the model based target size estimator filter algorithm need to know relative distance from the target. In order to overcome the problem, we propose target size and model based target size estimator filter (TMBEF) algorithm which based on the target size. The performance of proposed algorithm is tested at target intercept scenario. The experiment results show that the proposed algorithm has the accurate target size estimating performance.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.500-503
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• 2003

The navigation problem of robot is one of the main themes to deal with conficts or interferences between obstacles and the robot itself In this case, while the robot avoids obstacles on the space, the passage route should be determined efficiently. In order to solve problems above, we have come up with the distance field space medel (DFM) and then, under known environment, we have presented the distance field A algorithm for passage route path search. In this research, the method of performing the 3-dimensional passage route path search of robot under unknown environment is proposed. It is shown that the authors can build the distance search model the does not need space division by taking into account of sensor information to a distance field space model, and constructing this information as virtual obstacle information.

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.438-441
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• 2001

This paper describes a system for tracking a face in a input video sequence using facial convex hull based facial segmentation and a robust hausdorff distance. The algorithm adapts YCbCr color model for classifying face region by [l]. Then, we obtain an initial face model with preprocessing and convex hull. For tracking, a Robust Hausdorff distance is computed and the best possible displacement is selected. Finally, the previous face model is updated using the displacement t. It is robust to some noises and outliers. We provide an example to illustrate the proposed tracking algorithm in video sequences obtained from CCD camera.

• Korean Institute of Interior Design Journal
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• no.27
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• pp.12-19
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• 2001

The purpose of this study is to develope instructional strategies and assessment model for distance learning in interior design education in Korea. Literature from various sources were examined to provide guidelines for instructional and technical strategies, communication system, and administrative process. Strategies and assessment model for transition to distance learning from goal setting to program evaluation were introduced. The results of this study indicated that distance learning in interior design education is optimized when applied in studio critique, portfolio production, and professional practice and with other traditional programs depending on the characteristics of the instructional materials. It is suggested for further studies that various distance learning programs based on instructional theories to be conducted and evaluated in different areas of interior design education for their maximum application as instructional tool.

• ETRI Journal
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• v.32 no.5
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• pp.795-800
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• 2010

Embedding a large vocabulary speech recognition system in mobile devices requires a reduced acoustic model obtained by eliminating redundant model parameters. In conventional optimization methods based on the minimum description length (MDL) criterion, a binary Gaussian tree is built at each state of a hidden Markov model by iteratively finding and merging similar mixture components. An optimal subset of the tree nodes is then selected to generate a downsized acoustic model. To obtain a better binary Gaussian tree by improving the process of finding the most similar Gaussian components, this paper proposes a new distance measure that exploits the difference in likelihood values for cases before and after two components are combined. The mixture weight of Gaussian components is also introduced in the component merging step. Experimental results show that the proposed method outperforms MDL-based optimization using either a Kullback-Leibler (KL) divergence or weighted KL divergence measure. The proposed method could also reduce the acoustic model size by 50% with less than a 1.5% increase in error rate compared to a baseline system.