• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.615-618
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• 2007

It has able to express digital video/audio data from analog and to broadcast it via improvement of video/audio compression technology and publishing standard of MPEG-2 System. Nowaday many System Operators are provide regular digital broadcasting program to customer with their own access program. To provide access program, two process needs that are creating broadcasting information and remultiplexing it with video/audio data, and this solution is providing with high-cost system only. For this reason, digital access program bas week point to product. In this paper, we designed and implemented Generating PSIP Information System to product digital access program which generate PSIP information via receiving broadcasting information from user, and map PSIP information directly to video/audio data.

• Journal of KIISE:Databases
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• v.29 no.6
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• pp.477-491
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• 2002

The broadcast environment has asymmetric communication aspect that is typically much greater communication bandwidth available from server to clients than in the opposite direction. In addition, mobile computing systems generate mostly read-only transactions from mobile clients for retrieving different types of information such as stock data, traffic information and news updates. Since previous concurrency control protocols, however, do not consider such a particular characteristics, the performance degradation occurs when previous schemes are applied to the broadcast environment. In this paper, we propose optimistic concurrency control based on timestamp interval for broadcast environment. The following requirements are satisfied by adapting weak consistency that is the appropriate correctness criterion of read-only transactions: (1) the mutual consistency of data maintained by the server and read by clients (2) the currency of data read by clients. We also adopt the timestamp Interval protocol to check the weak consistency efficiently. As a result, we improved a performance by reducing unnecessary aborts and restarts of read-only transactions caused when global serializability was adopted.

• The KIPS Transactions:PartB
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• v.14B no.4
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• pp.303-310
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• 2007

In machine learning, the ensemble classifier that is a set of classifiers have been introduced for higher accuracy than individual classifiers. We propose a new ensemble learning method that employs a set of region based classifiers. To show the performance of the proposed method. we compared its performance with that of bagging and boosting, which ard existing ensemble methods. Since the distribution of data can be different in different regions in the feature space, we split the data and generate classifiers based on each region and apply a weighted voting among the classifiers. We used 11 data sets from the UCI Machine Learning Repository to compare the performance of our new ensemble method with that of individual classifiers as well as existing ensemble methods such as bagging and boosting. As a result, we found that our method produced improved performance, particularly when the base learner is Naive Bayes or SVM.

• The KIPS Transactions:PartA
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• v.17A no.6
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• pp.281-288
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• 2010

In this paper, we describe the development of a system for generating a 3-dimensional human face using 3D scanned facial data and photo images, and morphing animation. The system comprises a facial feature input tool, a 3-dimensional texture mapping interface, and a 3-dimensional facial morphing interface. The facial feature input tool supports texture mapping and morphing animation - facial morphing areas between two facial models are defined by inputting facial feature points interactively. The texture mapping is done first by means of three photo images - a front and two side images - of a face model. The morphing interface allows for the generation of a morphing animation between corresponding areas of two facial models after texture mapping. This system allows users to interactively generate morphing animations between two facial models, without programming, using 3D scanned facial data and photo images.

• The Korean Journal of Applied Statistics
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• v.16 no.2
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• pp.407-426
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• 2003

We consider the missing covariates problem in generalized estimating equations(GEE) model. If the covariate is partially missing, GEE can not be calculated. In this paper, we study the performance of 7 imputation methods to handle missing covariates in GEE models, and the properties of GEE estimators are investigated after missing covariates are imputed for ordinal data of repeated measurements. The 7 imputation methods include i) Naive Deletion ii) Sample Average Imputation iii) Row Average Imputation iv) Cross-wave Regression Imputation v) Carry-over Imputation vi) Bayesian Bootstrap vii) Approximate Bayesian Bootstrap. A Monte-Carlo simulation is used to compare the performance of these methods. For the missing mechanism generating the missing data, we assume ignorable nonresponse. Furthermore, we generate missing covariates with or without considering wave nonresp onse patterns.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.16 no.1
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• pp.31-49
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• 2012

In this paper, we propose a very efficient method which reconstructs the high resolution surface from a set of unorganized points. Our method is based on the level set method using adaptive octree. We start with the surface reconstruction model proposed in [20]. In [20], they introduced a very fast and efficient method which is different from the previous methods using the level set method. Most existing methods[21, 22] employed the time evolving process from an initial surface to point cloud. But in [20], they considered the surface reconstruction process as an elliptic problem in the narrow band including point cloud. So they could obtain very speedy method because they didn't have to limit the time evolution step by the finite speed of propagation. However, they implemented that model just on the uniform grid. So they still have the weakness that it needs so much memories because of being fulfilled only on the uniform grid. Their algorithm basically solves a large linear system of which size is the same as the number of the grid in a narrow band. Besides, it is not easy to make the width of band narrow enough since the decision of band width depends on the distribution of point data. After all, as far as it is implemented on the uniform grid, it is almost impossible to generate the surface on the high resolution because the memory requirement increases geometrically. We resolve it by adapting octree data structure[12, 11] to our problem and by introducing a new redistancing algorithm which is different from the existing one[19].

• Journal of The Korean Society of Agricultural Engineers
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• v.46 no.7
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• pp.3-12
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• 2004

The need to predict the rate of soil erosion, both under existing conditions and those expected to occur following soil conservation practice, has been led to the development of various models. In this study Morgan model especially developed for field-sized areas on hill slopes was applied to assess the rate of soil erosion using RS/GIS environment in the Dukchun river basin, one of two tributaries flowing into Jinyang lake. In order to run the model, land cover mapping was made by the supervised classification method with Landsat TM satellite image data, the digital soil map was generated from scanning and screen digitizing from the hard copy of soil maps, digital elevation map (DEM) in order to generate the slope map was made by the digital map (DM) produced by National Geographic Information Institute (NGII). Almost all model parameters were generated to the multiple raster data layers, and the map calculation was made by the raster based GIS software, IL WIS which was developed by ITC, the Netherlands. Model results show that the annual soil loss rates are 5.2, 18.4, 30.3, 58.2 and 60.2 ton/ha/year in forest, paddy fields, built-up area, bare soil, and upland fields respectively. The estimated rates seemed to be high under the normal climatic conditions because of exaggerated land slopes due to DEM generation using 100 m contour interval. However, the results were worthwhile to estimate soil loss in hilly areas and the more precise result could be expected when the more accurate slope data is available.

• Journal of KIISE:Databases
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• v.31 no.2
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• pp.183-194
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• 2004

As XML is a do facto standard for a data exchange language, there have been several researches on efficient processing XML queries. The most important thing to consider when processing XML queries is how efficiently we can process path expressions in queries. Some previous works make results by performing a sequence of join operations on all records corresponding to labels in the path expression. Others works check the existence of paths in the query using an RDBMS's string comparison operator and make results by extracting the records corresponding to the paths. In this paper we suggested a new query planning algorithm based on path containment relationships and two join operators supporting the planning algorithm. The join operators use only the records related to the paths in a query as input data, scan them only once, and generate result data using a pipelining mechanism. By analysis and experiments, we confirmed that our techniques(a new query planning algorithm and two join operators) achieved significantly higher performance than other previous works.

• Journal of KIISE
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• v.43 no.8
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• pp.910-918
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• 2016

A tensor is a multi-dimensional array that represents many data such as (user, user, time) in the social network system. A tensor generator is an important tool for multi-dimensional data mining research with various applications including simulation, multi-dimensional data modeling/understanding, and sampling/extrapolation. However, existing tensor generators cannot generate sparse tensors like real-world tensors that obey power law. In addition, they have limitations such as tensor sizes that can be processed and additional time required to upload generated tensor to distributed systems for further analysis. In this study, we propose TeT, a distributed tera-scale tensor generator to solve these problems. TeT generates sparse random tensor as well as sparse R-MAT and Kronecker tensor without any limitation on tensor sizes. In addition, a TeT-generated tensor is immediately ready for further tensor analysis on the same distributed system. The careful design of TeT facilitates nearly linear scalability on the number of machines.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2006.11a
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• pp.283-288
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• 2006

In the future television broadcasting a flood of information from various sources will not always be welcomed by everyone. The need of accessing specific information as required is becoming a necessity. We are interested to make the life of television consumer easier by providing an intelligent television set which can adaptively proposed certain shows to the viewer based on the user historical consumed shows. The TV watching history data consists of TV program titles with their respective genres, channels, watched times and durations, etc. The method proposed is by utilizing Hidden Markov Model (HMM) to model the user preference of kind of genres the viewer will watch based on recorded genres of several weeks time. We take watching schedule from 6 PM to midnight as boundary. The range thus divided into 3 independent time band of 2 hours each resulting in 3 time bands from 6 PM to 8 PM, 8 PM to 10 PM, and lastly 10 PM to midnight. Each time band will be represented by an HMM. From each HMM we can generate a sequence of predicted genre that the user will probably watch during corresponding time-band. Our approach assumes that the user shows a consistent behavior of watching pattern in week to week basis and during the moment of watching TV. To asses the method performance experiment is conducted using real data collected from December 2002 to May 2003. Some user's data are selected and based on that predictions are made. The resulting predictions are then compared with the actual user's history. The experiment shows satisfactory result for user with middle to high consistent behavior level.