• Journal of Korean Library and Information Science Society
• /
• v.34 no.2
• /
• pp.273-296
• /
• 2003

Because all the subjects may become the targets of classification, it is necessary to change the enumerated into the faceted scheme. This study is to confirm that possibility of change and to proposed the new faceted structure scheme(faceted classification) based on the Literature. The proposed schemes are : 1) facet structure is simple, 2) meaning of facet is clearness, 3) because using mixed notation, it is complicated.

• The Korean Journal of Applied Statistics
• /
• v.23 no.1
• /
• pp.13-28
• /
• 2010

Assuming a mixture distribution for credit evaluation studies, we discuss estimating threshold methods to minimize errors that default borrowers are predicted as non defaults or non defaults are regarded as defaults. A method by using statistical hypotheses tests, the most powerful test and generalized likelihood ratio test, for the probability density functions which are defined with the score random variable and the parameter space consisted of only two elements such as the default and non default states is proposed to estimate a threshold. And anther optimal thresholds to maximize classification accuracy measures of the accuracy and the true rate for ROC and CAP curves are estimated as equations related with these probability density functions. Three kinds of optimal thresholds in terms of the hypotheses testing, the accuracy and the true rate are obtained from normal random samples with various means and variances. The sums of the type I and type II errors corresponding to each optimal threshold are obtained and compared. Finally we discuss about their efficiency and derive conclusions.

• Korean Journal of Remote Sensing
• /
• v.30 no.4
• /
• pp.511-524
• /
• 2014

In this study, we investigated the statistical occupations and interannual variations of land cover types over Northeast Asian region using the 12 years (2001-2012) MODerate Resolution Imaging Spectroradiometer(MODIS) land cover data sets. The spatial resolution and land cover types of MODIS land cover data sets are 500 m and 17, respectively. The 12-year average shows that more than 80% of the analysis region is covered by only 3 types of land cover, cropland (36.96%), grasslands (23.14%) and mixed forests (22.97%). Whereas, only minor portion is covered by cropland/natural vegetation mosaics (6.09%), deciduous broadleaf forests (4.26%), urban and built-up (2.46%) and savannas (1.54%). Although sampling period is small, the regression analysis showed that the occupations of evergreen needleleaf forests, deciduous broadleaf forests and mixed forests are increasing but the occupations of woody savannas and savannas are decreasing. In general, the pixels where the land cover types are classified differently with year are amount to more than 10%. And the interannual variations in the occupations of land cover types are most prominent in cropland (1.41%), mixed forests (0.82%) and grasslands (0.73%). In addition, the percentage of pixels classified as 1 type for 12 years is only 57% and the other pixels are classified as more than 2 types, even 9 types. The annual changes in the classification of land cover types are mainly occurred at the almost entire region, except for the eastern and northwestern parts of China, where the single type of land cover located. When we take into consider the time scale needed for the land cover changes, the results indicate that the MODIS land cover data sets over the Northeast Asian region should be used with caution.

• The Journal of the Acoustical Society of Korea
• /
• v.24 no.7
• /
• pp.410-415
• /
• 2005

Recently, most of the speaker verification systems are based on the pattern recognition approach method. And performance of the pattern-classifier depends on how to classify a variety of speakers' feature parameters. In order to classify feature parameters efficiently and effectively, it is of great importance to enlarge variations between speakers and effectively measure distances between feature parameters. Therefore, this paper would suggest the positively mixed model scheme that can enlarge inter-speaker variation by searching the individual model with world model at the same time. During decision procedure, we can maximize inter-speaker variation by using the proposed mixed model scheme. We also make use of a symbol probability weighting function in this system so as to reduce vector quantization errors by measuring symbol probability derived from the distance rate of between the world codebook and individual codebook. As the result of our experiment using this method, we could halve the Detection Cost Function (DCF) of the system from $2.37\%\;to\;1.16\%$.

• Transactions of the Korean Society of Mechanical Engineers
• /
• v.12 no.4
• /
• pp.876-891
• /
• 1988

This study was carried out to investigate the mixing flow of a turbulent cross jet in a cylindrical chamber. A study on the turbulent mixing flow of a cross jet at 45.deg. with respect to each other in the free atmospheric condition was conducted before this study and has given us some fundamental experimental results. Present data have been analyzed and compared with semi-empirical equations for a round and a plane jets. Interests on this kind of cross jets (flows) have been increasing during the past several years for the purpose of the analysis of mixing flows and their applications. In this study, a turbulent cross jet of air in a cylindrical chamber has been conducted and the turbulent characteristics in the mixing region have been analyzed experimentally. The experimental data were discussed by comparing with the semi-empirical equations of Hinze and Gortler. From the experimental curve, the semi-empirical equations of mean velocities and Reynolds stresses have been derived. Three dimensional data acquisitions and the statistical treatments of turbulence characteristics were carried out by on-line computer measurement system connected with the constant temperature type 2-channel hot-wire anemometer system.

• Journal of KIISE:Computing Practices and Letters
• /
• v.8 no.1
• /
• pp.107-115
• /
• 2002

We propose a new hybrid value predictor which achieves high performance by combining several predictors. Because the proposed hybrid value predictor can update the prediction table speculatively, it efficiently reduces the number of mispredicted instructions due to stale data. Also, the proposed predictor can enhance the prediction accuracy and efficiently decrease the hardware cost of predictor, because it allocates instructions into the best-suited predictor during instruction fetch stage by using the information of static classification which is obtained from the profile-based compiler implementation. For the 16-issue superscalar processors, simulation results based on the SimpleScalar/PISA tool set show that we achieve the average prediction rates of 73% by using speculative update and the average prediction rates of 88% by adding static classification for the SPECint95 benchmark programs.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2014.11a
• /
• pp.192-195
• /
• 2014

급변하는 글로벌 비즈니즈 환경속에서 물류의 역할은 나날이 증가하고 있다. 아울러 기존의 노동 집약적 물류 산업의 탈피가 가속화 되어 있으며, 고부과가치 물류 시스템 구축으로 융복합 기술을 활용한 새로운 모습으로 변화를 요구하고 있다. 특히, 물류 분야 중 자동차 생산 분류에 선재 관리를 통해 기업과 기업으로 서로 운송되어 분류되어 있으며, 차량 선재 분류는 자동화 통해 수행하고 있으나, 생산된 선재는 색깔별, 두께별로 일괄적으로 생산하여 나중에 선재를 작업자가 분류지를 보면서 작업을 하고 있하고 있다. 그러나, 선재 분류자는 반복적인 업무와 피로 누적으로 휴멘 에러가 발생으로 선재의 누락 혼합 발생되어 선재 물류 납품 시 이 차 기업으로 비용과 시간적 피해가 발생하게 된다. 따라서, 본 연구에서는 차량 선재 공정 분류와 그룹 모니터링 장치 기반의 선재 물류 분류 장치를 통해 공정을 개선하고자 한다.

• 베이커리
• /
• no.3 s.368
• /
• pp.114-116
• /
• 1999

• Journal of the Korea Society of Computer and Information
• /
• v.10 no.2 s.34
• /
• pp.113-121
• /
• 2005

In this paper, we design the hybrid learning algorithm of LVQ which is to perform EMG pattern recognition. The proposed hybrid LVQ learning algorithm is the modified Counter Propagation Networks(C.p Net. ) which is use SOM to learn initial reference vectors and out-star learning algorithm to determine the class of the output neurons of LVa. The weights of the proposed C.p. Net. which is between input layer and subclass layer can be learned to determine initial reference vectors by using SOM algorithm and to learn reference vectors by using LVd algorithm, and pattern vectors is classified into subclasses by neurons which is being in the subclass layer, and the weights which is between subclass layer and class layer of C.p. Net. is learned to classify the classified subclass. which is enclosed a class . To classify the pattern vectors of EMG. the proposed algorithm is simulated with ones of the conventional LVQ, and it was a confirmation that the proposed learning method is more successful classification than the conventional LVQ.

• Communications for Statistical Applications and Methods
• /
• v.2 no.2
• /
• pp.249-265
• /
• 1995

본 논문에서는 확률분포가 알려져 있지 않은 두 모집단 중 어느 하나로 새로운 관측치를 분류할 때 오분류확률이 분석자에 의해 사전에 정해진 수준에 부합할 수 있도록 커널 판별함수의 임계치를 결정하였다. 정해진 오분류확률을 만족시키기 위한 판별함수의 임계치는 붓스트랩(bootstrap)기법을 판별 함수에 적용시켜 계산된다. 본 논문에서 제시도된 방법은 모집단에 대한 모수적 가정이 없으므로 어느 분포에도 적용가능하며, 모집단이 정규분포, 대수정규분포, 이산형과 연속형 변수가 혼합된 분포의 경우 모의실험을 통하여 그 성능에 대한 검증을 하였다.