• KIISE Transactions on Computing Practices
• /
• v.21 no.7
• /
• pp.488-493
• /
• 2015

An AddSIM(Adaptive distributed and parallel Simulation environment for Interoperable and reusable Models) is an integrated engagement simulation environment with high-resolution weapon system models for estimation and analysis of their performance and effectiveness. AddSIM can simultaneously handle the continuous dynamical system models based on continuous time, and command, control(C2) and network system models based on a discrete event. To accommodate legacies based on DEVS(Discrete Event System Specification) modeling, DEVS legacies must first be converted into AddSIM models. This paper describes how to implement DEVS models on AddSIM. In this study a method of mapping from hierarchical DEVS models to AddSIM players was developed: The hierarchical DEVS model should be flattened into a one layered model and four DEVS functions of the model, external transition, internal transition, output and time advance, should be mapped into functions of the AddSIM player.

• Journal of the Korean Regional Science Association
• /
• v.39 no.3
• /
• pp.49-63
• /
• 2023

This study investigates the occupational mobility patterns of young wage employees at the local level of the labor market and empirically examines the interplay between worker-level and local labor market-level determinants between 2010 and 2020. The 4th to 14th waves of the Youth Panel 2007 were integrated with the Korea Network for Occupations and Workers and the Local Area Labor Force Survey for estimation using hierarchical linear model. Our results indicate that Gross Regional Domestic Product per capita is key determinant of occupational upward mobility. Also, Estimates of employment size, population density, and the unemployment rate of local labor market have different effects depending on the education level and occupational location of youth workers, suggesting that the effects of structural factors of local labor market may not be distributed equally among all youth wage workers. The findings have policy implications regarding the recent rise in inequality and polarization in local labor markets.

• Journal of Broadcast Engineering
• /
• v.3 no.1
• /
• pp.85-92
• /
• 1998

The block matching algorithm is the most popular motion estimation method in image sequence coding. In this paper, we propose a VLSI architecture. for implementing a recently proposed fast bolck matching algorith, which uses spatial correlation of motion vectors and hierarchical searching scheme. The proposed architecture consists of a basic searching unit based on a systolic array and two shift register arrays. And it covers a search range of -32~ +31. By using the basic searching unit repeatedly, it reduces the number of gatyes for implementation. For basic searching unit implementation, a proper systolic array can be selected among various conventional ones by trading-off between speed and hardware cost. In this paper, a structure is selected as the basic searching unit so that the hardware cost can be minimized. The proposed overall architecture is fast enough for low bit-rate applications (frame size of $352{\times}288$, 3Oframes/sec) and can be implemented by less than 20,000 gates. Moreover, by simply modifying the basic searching unit, the architecture can be used for the higher bit-rate application of the frame size of $720{\times}480$ and 30 frames/sec.

• Journal of KIISE:Software and Applications
• /
• v.30 no.3_4
• /
• pp.251-258
• /
• 2003

A support vector machine (SVM) is supposed to provide a good generalization performance, but the actual performance of a actually implemented SVM is often far from the theoretically expected level. This is largely because the implementation is based on an approximated algorithm, due to the high complexity of time and space. To improve this limitation, we propose ensemble of SVMs by using Bagging (bootstrap aggregating) and Boosting. By a Bagging stage each individual SVM is trained independently using randomly chosen training samples via a bootstrap technique. By a Boosting stage an individual SVM is trained by choosing training samples according to their probability distribution. The probability distribution is updated by the error of independent classifiers, and the process is iterated. After the training stage, they are aggregated to make a collective decision in several ways, such ai majority voting, the LSE(least squares estimation) -based weighting, and double layer hierarchical combining. The simulation results for IRIS data classification, the hand-written digit recognition and Face detection show that the proposed SVM ensembles greatly outperforms a single SVM in terms of classification accuracy.

• Journal of the Korean Data and Information Science Society
• /
• v.26 no.3
• /
• pp.581-592
• /
• 2015

In the GORRAM, the estimation of resource requirements for wartime equipment is based on the ELCON of the USA. The number of vulnerability groups of ELCON are 22, but unfortunately it is hard to determine how the 22 groups are classified. Thus, in this research we collected 505 types of basic items used in wartime and classified those items into new vulnerability groups using AHP and cluster analysis methods. We selected 11 variables through AHP to classify those items with cluster analysis. Next, we decided the number of vulnerability groups through hierarchical clustering and then we classified 505 types of basic items into the new vulnerability groups through K-means clustering.This paper presents new vulnerability groups of 505 types of basic items fitted to Korean weapon systems. Furthermore, our approach can be applied to a new weapon system which needs to be classified into a vulnerability group. We believe that our approach will provide practitioners in the military with a reliable and rational method for classifying wartime equipment and thus consequentially predict the exact estimation of resource requirements in wartime.

• Journal of IKEEE
• /
• v.10 no.1 s.18
• /
• pp.40-48
• /
• 2006

This paper presents a new rooftop surface estimation method from 3D line segments. 3D rooftop surface estimation is based on the hierarchical grouping and initiated by 3D line merging for the disconnected 3D line segments. Merged 3D lines are applied to the detection of rooftop by surface estimating technique. To estimate surfaces we detect L-corner and T-corner points, and find fixed reliable junction points. The hypothesis of the possible rooftop surfaces are estimated as polygonal surfaces by these fixed junction points and building's rooftop models are generated by testing the possible surfaces in terms of assumptions of building surface properties. We carried out experiments by synthetic images on Avenches data set and the experimental results showed that we could reliably build 3D model with 3D surfaces, errors of which came up with 0.4 - 1.3 meter, 2.5 times more accurate than the elevation date from the conventional area-based stereo.

• Journal of the Korean Data and Information Science Society
• /
• v.23 no.4
• /
• pp.627-641
• /
• 2012

We consider a model estimation and model selection methods for the multi-way contingency table data with non-response or missing values. We also consider hierarchical Bayesian model in order to handle a boundary solution problem that can happen in the maximum likelihood estimation under non-ignorable non-response model and we deal with a model selection method to find the best model for the data. We utilized Bayes factors to handle model selection problem under Bayesian approach. We applied proposed method to the pre-election survey for the 2004 Korean National Assembly race. As a result, we got the non-ignorable non-response model was favored and the variable of voting intention was most suitable.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.41 no.6
• /
• pp.209-220
• /
• 2004

The main feature of H.264 standard against conventional video standards is the high coding efficiency and the network friendliness. In spite of these outstanding features, it is not easy to implement H.264 codec as a real-time system due to its high requirement of memory bandwidth and intensive computation. Although the variable block size motion compensation using multiple reference frames is one of the key coding tools to bring about its main performance gain, it demands substantial computational complexity due to SAD (Sum of Absolute Difference) calculation among all possible combinations of coding modes to find the best motion vector. For speedup of motion estimation process, therefore, this paper proposes fast algorithms for both integer-pel and fractional-pel motion search. Since many conventional fast integer-pel motion estimation algorithms are not suitable for H.264 having variable motion block sizes, we propose the motion field adaptive search using the hierarchical block structure based on the diamond search applicable to variable motion block sizes. Besides, we also propose fast fractional-pel motion search using small diamond search centered by predictive motion vector based on statistical characteristic of motion vector.

• Asian-Australasian Journal of Animal Sciences
• /
• v.14 no.7
• /
• pp.910-914
• /
• 2001

The teat number of a sow plays an important role for weaning pigs and has been utilized in selection of swine breeding stock. Various linear models have been employed for genetic analyses of teat number although the teat number can be considered as a count trait. Theoretically, Poisson error mixed models are more appropriate for count traits than Normal error mixed models. In this study, the two models were compared by analyzing data simulated with Poisson error. Considering the mean square errors and correlation coefficients between observed and fitted values, the Poisson generalized linear mixed model (PGLMM) fit the data better than the Normal error mixed model. Also these two models were applied to analyzing teat numbers in four breeds of swine (Landrace, Yorkshire, crossbred of Landrace and Yorkshire, crossbred of Landrace, Yorkshire, and Chinese indigenous Min pig) collected in China. However, when analyzed with the field data, the Normal error mixed model, on the contrary, fit better for all the breeds than the PGLMM. The results from both simulated and field data indicate that teat numbers of swine might not have variance equal to mean and thus not have a Poisson distribution.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2006.05a
• /
• pp.709-712
• /
• 2006

다양한 종류의 컴퓨터가 사람, 사물, 환경 속에 내재되어 있고, 이들이 서로 연결되어, 필요한 곳에서 활용할 수 있는 유비쿼터스 환경에서는 홈 네트워크를 통해 이 기종 기기간 다양한 데이터 교환을 요구한다. 더욱이 원활한 영상 데이터의 처리, 전송, 모니터링 기술은 핵심적 요소가 아닐 수 없다. 공간 및 시간적인 해상도, 컬러의 표현 그리고 화질의 측정방법 등 고전적 영상 처리 연구 분야뿐만 아니라 국한된 대역폭을 갖는 홈네트워크의 전송체계에서 전송률 문제에 대한 심도 있는 연구가 필요하다. 본 논문에서는 홈네트워크 상황에서 콘텐츠의 중심이 되는 영상 데이터의 전송과 처리 그리고 제어를 위하여 새로운 움직임 추정 알고리즘을 제안한다. 각도, 거리등 다양한 환경에서 전송되어지는 스테레오 카메라의 영상데이터들은 축소, 확대, 이동, 보정 등 전처리 후 제안된 변형계층 모션벡터 추정 알고리즘을 이용하여 압축 처리, 전송된다. 기존 모션벡터 추정 알고리즘의 장점을 계승하고 단점을 보완한 변형계층 알고리즘은 비정형, 소형 매크로 블록을 이용하여 휘도의 편차가 큰 영상의 효율적 움직임 추정에 이용된다. 본 논문에서 제안한 변형계층 알고리즘과 이를 이용해 구현된 영상시스템은 유비쿼터스 환경에서 다양하게 활용될 수 있다.