• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.6
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• pp.576-584
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• 2011

In order to develop a launch vehicle successfully, it is important to estimate development costs accurately but it is also important to plan the annual budget. In this paper, the statistical method was utilized for cost spreading. For cost spread modeling, the suitability of the model by analyzing several statistical models was evaluated and consequently, the beta-distribution model has been selected. In this study, the validity of the annual estimation cost model was verified through the comparison of the actual development cost distribution and the estimating cost distribution of Space Shuttle Main Engine. In addition, this paper estimated the annual budget required for the development of the KSLV-II using currently allocated cost for successful development. It is anticipated that the present cost spread model can be applied to not only launch vehicle development but also other large complex system development.

• The Journal of the Acoustical Society of Korea
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• v.15 no.1
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• pp.61-70
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• 1996

According to topics or speaker's intentions in a dialogue, utterance spoken by speaker has a different sentence structure of word combinations. Based on these facts, we have proposed the statistical approach. IDT(intention decision table), which is modeling the correlations between sentence patterns and the intention. In a IDT, the sentence is splitted into 5 different factors, and the intention of a sentence is determined by the similarity between and intention and 5 factors that have represent a sentence. From the experimental results, the IDT has indicated that the prediction rate of an intention is improved 10~18% over the word-intention correlations and is enhanced 3~12% compared with the MIG(Markov intention graph) that models the intention with a transition graph for word categories in a sentence. Based on these facts, we have found that the IDT is effective method for the prediction of an intention.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.327-330
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• 2007

This paper verifies that the normality assumption that the simulation output data, Project Completion Times (PCTs), follow normal distribution is not always acceptable and the existing belief may lead to misleading results. A risk quantification method, which measures the effect caused by the assumption, relative to the probability distribution of PCTs is implemented as an algorithm in MATLAB. To validate the reliability of the quantification, several series of simulation experiments have been carried out to analyze a set of simulation output data which are obtained from different type of Probability Distribution Function (PDF) assigned to activities'duration in a network. The method facilitates to find the effect of PDF type and its parameters. The procedure necessary for performing the risk quantification method is described in detail along with the findings. This paper contributes to improving the reliability of simulation based scheduling method, as well as increasing the accuracy of analysis results.

• Journal of the Korea Society for Simulation
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• v.30 no.1
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• pp.75-85
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• 2021

In this paper, we present a deep neural network-based prediction model that processes and analyzes the corporate credit and personal credit information of individual business owners as a new method to predict the default rate of individual business more accurately. In modeling research in various fields, feature selection techniques have been actively studied as a method for improving performance, especially in predictive models including many features. In this paper, after statistical verification of macroeconomic indicators (macro variables) and credit information (micro variables), which are input variables used in the default rate prediction model, additionally, through the credit information feature selection method, the final feature set that improves prediction performance was identified. The proposed credit information feature selection method as an iterative & hybrid method that combines the filter-based and wrapper-based method builds submodels, constructs subsets by extracting important variables of the maximum performance submodels, and determines the final feature set through prediction performance analysis of the subset and the subset combined set.

• Journal of the Korea Computer Graphics Society
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• v.29 no.1
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• pp.13-22
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• 2023

In this paper, we present a method for estimating full 3D shapes from given 2D silhouette images of human bodies. Because the silhouette only consists of the partial information on the true shape, it is an ill-posed problem. To address the problem, we use the statistical human shape space obtained from the existing large 3D human shape database. The method consists of three steps. First, we extract the boundary pixels and their appropriate normal vectors from the input silhouette images. Then, we initialize the correspondences of each pixel to the vertex of the statistically-deformable 3D human model. Finally, we numerically optimize the parameters of the statistical model to fit best to the given silhouettes. The viability and the robustness of the method is demonstrated with various experiments.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.144-144
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• 2020

국내의 하천은 급격한 도시화 및 산업화로 인해 자연하천의 모습은 사라지고 이수와 치수 기능 위주의 하천관리가 이루어졌다. 하천은 치수기능을 강조하여 인공적으로 변화하였을 뿐만 아니라 하천생태환경 내에 서식하는 동식물의 서식 환경에도 교란을 야기하였다. 최근 하천관리의 패러다임이 변화함에 따라서, 하천이 갖는 자연적 특성을 회복하는 환경적 측면을 강조한 생태하천 복원사업에 대한 관심이 높아지고 있으나, 수생생물 서식지 복원과 생태계에 필요한 환경유량에 관한 정량적인 평가를 위한 연구는 부족한 실정이다. 본 연구는 경상북도 김천시와 구미시를 관류하여 낙동강으로 합류되는 감천을 대상으로 하였으며, 댐 건설로 인한 하천 생태계 변화 및 하천유량에 대한 통계적 분석, 수리 모델링, 하천구역의 공간적 분석을 진행하였다. 통계적 분석을 위한 시계열 자료 구축은 감천 하류에 있는 선산관측소의 2002년 ~ 2019년까지 수위, 유량을 사용하였으며, 김천부항댐이 건설 된 2014년 1월 1일을 기점으로 댐 건설 전(2002 ~ 2013)과 댐 건설 후(2014 ~ 2019)로 구분하였다. HEC-EFM(Ecosystem Function Model)을 활용하여 어류를 포함한 수생생물의 성공적인 서식을 위한 환경유량을 산정하였다. 산정된 환경유량을 HEC-GeoRAS(Geographic River Analysis System)와 HEC-GeoEFM(Geographic Ecosystem Function Model)을 적용·연계하여 수생식생 도입이 가능한 하천 구간과 어류 산란 및 성장에 적합한 하천구간을 표현하였으며, 댐 건설 전후의 서식지 면적을 계산하여 수생생물의 성공적인 서식환경이 조성되었는지 확인하였다. 본 연구를 바탕으로 수생생물의 하천 서식지 개선을 위한 명확한 환경유량을 수립하는 데 도움이 될 것으로 판단된다.

• Journal of the Korea Computer Graphics Society
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• v.28 no.4
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• pp.1-11
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• 2022

The Skinned Multi-Person Linear Model (SMPL) is the most widely used parametric 3D Human Model optimized and learned from CAESAR, a 3D human scanned database created with measurements from 3,800 people living in United States in the 1990s. We point out the lack of racial diversity of body types in SMPL and propose K-SMPL that better represents Korean 3D body shapes. To this end, we develop a fitting algorithm to estimate 2,773 Korean 3D body shapes from Korean body measurement data. By conducting principle component analysis to the estimated Korean body shapes, we construct K-SMPL model that can generate various Korean body shape in 3D. K-SMPL model allows to improve the fitting accuracy over SMPL with respect to the Korean body measurement data. K-SMPL model can be widely used for avatar generation and human shape fitting for Korean.

• The KIPS Transactions:PartB
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• v.17B no.1
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• pp.69-78
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• 2010

Spectral modeling synthesis (SMS) has been used as a powerful tool for musical sound modeling. This technique considers a sound as a combination of a deterministic plus a stochastic component. The deterministic component is represented by the series of sinusoids that are described by amplitude, frequency, and phase functions and the stochastic component is represented by a series of magnitude spectrum envelopes that functions as a time varying filter excited by white noise. These representations make it possible for a synthesized sound to attain all the perceptual characteristics of the original sound. However, sometimes considerable phase variations occur in the deterministic component by using the conventional SMS for the complex sound such as whale sounds when the partial frequencies in successive frames differ. This is because it utilizes the calculated phase to synthesize deterministic component of the sound. As a result, it does not provide a good spectrum matching between original and synthesized spectrum in higher frequency region. To overcome this problem, we propose a modified SMS that provides good spectrum matching of original and synthesized sound by calculating complex residual spectrum in frequency domain and utilizing original phase information to synthesize the deterministic component of the sound. Analysis and simulation results for synthesizing whale sounds suggest that the proposed method is comparable to the conventional SMS in both time and frequency domain. However, the proposed method outperforms the SMS in better spectrum matching.

• Journal of KIISE:Software and Applications
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• v.30 no.1_2
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• pp.93-102
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• 2003

A slant correction method for handwritten Korean strings based on analysis of stroke distribution, which effectively reflects structural properties of Korean characters, is presented in this paper. The method aims to deal with typical problems which have been frequently observed in slant correction of handwritten Korean strings with conventional approaches developed for English/European languages. Extracted strokes from a line of text image are classified into two clusters by applying the K-means clustering. Gaussian modeling is applied to each of the clusters and the slant angle is estimated from the model which represents the vertical strokes. Experimental results support the effectiveness of the proposed method. For the performance comparison 1,300 handwritten address string images were used, and the results show that the proposed method has more superior performance than other conventional approaches.

• Annual Conference on Human and Language Technology
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• 1996.10a
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• pp.158-162
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• 1996

본 논문에서는 문자출력이 가능한 무선호출기에 음성인식 기술을 접목한, 특성화된 한 음성인식 시스템에 대하여 설명하고자 한다. 시스템 동작 과정은, 일단 호출자가 음성인식 서버와 접속하게 되면 서버는 호출자의 자연스런 입력음성을 인식, 그 결과를 문장 형태로 피호출자의 호출기 단말기에 출력시키는 방식으로 되어 있다. 본 시스템에서는 통계적 음성인식 기법을 도입하여, 각 단어를 연속 HMM으로 모델링하였다. 가우시안 혼합 확률밀도함수를 사용하는 각 모델은 전통적인 HMM 학습법들 중의 하나인 Baum-Welch 알고리듬에 의해 학습되고 인식시에는 이들에 비터비 빔 탐색을 적용하여 최선의 결과를 얻도록 한다. MFCC와 파워를 혼용한 26 차원 특징벡터를 각 프레임으로부터 추출하여, 최종적으로, 83 개의 도메인 어휘들 및 무음과 같은 특수어휘들에 대한 모델링을 완성하게 된다. 여기에 구문론적 기능과 의미론적 기능을 함께 수행하는 FSN을 결합시켜 자연발화음성에 대한 연속음성인식 시스템을 구성한다. 본문에서는 이상의 사항들 외에도 음성 데이터베이스, 레이블링 등과 갈이 시스템 성능과 직결되는 시스템의 외적 요소들에 대해 고찰하고, 시스템에 구현되어 있는 다양한 특성들에 대해 밝히며, 실험 결과 및 앞으로의 개선 방향 등에 대해 논의하기로 한다.