• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.506-506
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• 2015

수문자료는 국가적으로 중요한 자료로서 이에 대한 품질관리가 반드시 필요하다. 이에 우리나라 국토교통부에서는 국가 수문자료 품질관리시스템을 구축하여 실시간으로 수집되는 수문자료의 품질을 관리하고 있다. 국가 수문자료 품질관리시스템에서 사용되는 수문자료 자동점검기준은 실시간으로 수집되는 수문자료의 상태를 구분하기 위한 점검방법에서 설정한 기준 값을 말하며, 특히 수문자료의 오류 추출을 자동화하는데 핵심적인 역할을 하는 값이다. 해당 값은 점검 방법에 따라 다른 형태를 갖고 있으며, 관측소의 관측특성과 밀접한 연관이 있어 실무에서는 기존 관측자료의 통계적인 특성을 이용해 초기값을 추정하고 이후 관측자료들에 대한 실제 품질 판정을 기준으로 실제 상황을 고려하여 주기적으로 관리자가 수작업에 의해 시행착오법으로 보정하는 방법을 사용하고 있다. 이에 본 논문에서는 국가 수문자료 품질관리시스템에서 활용하고 있는 수문자료 자동점검기준을 대상으로 기존에 수작업으로 진행되던 자동점검기준의 보정을 자동화할 수 있는 평가지표와 평가 알고리즘을 개발하였으며, 이를 실제 자료에 적용하였다. 개발된 알고리즘은 그림1과 같은 추정 이상치 집합과 실제 이상치 집합의 상관관계를 이용하여 두 집합의 교집합인 A를 증가시키는 구조이다. 이를 이용해 자동점검기준의 적중률을 향상시킬 수 있었으며, 향후 실무에 적용될 경우 수문자료 자동점검기준을 신속하고 적절하게 보정함으로써 수문자료 품질관리업무의 효율성을 향상시킬 수 있을 것으로 기대된다.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.11a
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• pp.860-863
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• 2008

플래시 메모리는 우리 생활에 널리 사용되고 있는 휴대용 저장장치 중의 하나이다. 빠른 입출력 속도와 저전력, 무소음, 작은 크기 등의 장점을 가지나 덮어쓰기가 불가능하고 읽기/쓰기의 속도에 비해 소거 연산의 속도가 매우 느리다는 단점이 있다. 이를 보완하기 위해, 호스트와 플래시 메모리 사이에 버퍼 캐시를 두어 사용하고 있으며, 버퍼 캐시에 사용되는 교체 정책에 따라 플래시 메모리 장치의 성능이 크게 영향을 받는다. 본 논문에서는 블록 단위의 LRU 기법의 단점을 개선한 HPLRU 기법을 제안한다. HPLRU 기법은 최근에 자주 참조되었던 페이지인 핫 페이지 들을 모아 리스트를 만들어 관리하고, 이를 통해 페이지 적중률을 향상시키고 다른 페이지들로 인해 핫 페이지들이 소거되는 현상을 개선하였다. 이 알고리즘은 임의 데이터 패턴에 좋은 성능을 보이며 쓰기 발생 횟수를 많이 감소시키는 결과를 보였다.

• Journal of Korean Medical classics
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• v.19 no.4
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• pp.147-168
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• 2006

통과대이연화장개빈관우중풍관점적비교연구, 이급기대중풍적분류(以及基對中風的分類), 증상(證狀), 치료(治療), 예후적관점진행분석득출여하결론(豫後的觀點進行分析得出如下結論): 이연파중풍적원인분류위진중풍(李挻把中風的原因分類爲眞中風), 겸중풍(兼中風), 류중풍(類中風), 사중풍(似中風), 종이조취료구분외풍여내풍계기(從而造就了區分外風與內風契機). 대어중풍적원인(對於中風的原因), 장개빈주장배제외풍근한어내풍적관점(張介賓主張排除外風僅限於內風的觀點). 재차기초상(在此基礎上), 설기여조헌가주장진수고갈급진화허시기원인소재(薛己與趙獻可主張眞水枯褐及眞火虛是基原因所在), 대차관점(對此觀點), 장수신적"중풍각전"중, 기유찬동적(旣有贊同的), 역유지비판의견적내용(亦有持批判意見的內容). 대어중풍적증상(對於中風的證狀), 이연근거병사소재분위중장, 중부(中부), 중혈맥(中血脈), 중경등(中經等). 우기대중경증적분류(尤基對中經證的分類), 재기타의서중시무법견도적분류적표준(在基他醫書中是無法見到的分類的標準). 저가이인위(這可以認爲), 타이 "금궤요략" 위의거(爲依據), 시부합내풍적증상분류(是符合內風的症狀分類). 장개빈파비풍적증상종대적방면분위경병화장병(張介賓把非風的症狀從大的方面分爲經病和臟病), 연후재파경병세분위경증화위증(然後在把經病細分爲經證和危證), 장병세분위초경증화위증(臟病細分爲稍經證和危證). 진관경병출현어지체(盡管經病出現於肢體), 이장병출현정신이상(而臟病出現精神異常), 단시경병여장병균유경증화위증(但是經病與臟病均有經證和危證). 저일주장시흔유지이성적. 대중풍적치료(對中風的治療), 이연대체상견지료금원이전적치료방법. 기용신한혹신온거풍화담(旣用辛寒或辛溫去風化痰), 혹용신온발한(惑用辛溫發汗), 혹용고한공리등(或用苦寒攻裏等). 장개빈지출상술방법대원기쇠약적중풍부적합사용(張介賓指出上述方法對元氣衰弱的中風不適合使用), 차장수신지출차시거풍치법실제상부적합내용풍이적합어외풍적치료(且張壽신指出此時去風治法實際上不適合內風而適合於外風的治療). 장개빈인위비풍적원인시진양여진음지허이불시풍담(張介賓認爲非風的原因是眞陽與眞陰之虛而不是風痰), 진관시급성기(盡管是急性期), 여과몰유담증(如果沒有痰證), 타견결반대사용거담지법(他堅決反對使用祛痰之法). 재중풍치료상(在中風治療上), 장개빈인위한다(張介賓認爲汗多), 소변소(小便少), 시진액부족소치(是津液不足所致), 소이수유열증역불요사용삼리지법, 병지출유뇨증시신허소치적위증(幷指出遺尿症是腎虛所致的危證), 종이진일보강조료진액적중요성(從而進一步强調了津液的重要性).

• Journal of the Korean Society of Clothing and Textiles
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• v.29 no.7 s.144
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• pp.978-986
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• 2005

The color of apparel products have a close relationship with the face skin colors of consumers. In order to extract the favorable colors which flatter to consumer's face skin colors, this study was carried our to classify the face skin colors of Korean females. The criteria that select new subjects who have the classified face skin colors have to be decided. With color spectrometer, JX-777, face skin colors of subjects were measured and classified into three clusters that had similar hue, value and chroma with Munsell Color System. Sample size was 324 Korean females and other new 10 college girls. Data were analyzed by K-means cluster analysis, ANOVA, Duncan multiple range test, Stepwise discriminant analysis using SPSS Win. 12. Findings were as follows: 1. 324 subjects who have YR colors were clustered into 3 face skin color groups. 2. Discriminant variables of face skin colors were 5 variables : b value of cheek, V value of forehead, L value of cheek, C value of forehead and H value of cheek by the standardized canonical discriminant function coefficient 1. 3. Hit ratio of type 1 was $96.8\%$, of type 2 was $94.9\%$, of type 3 was $100.0\%$ and mean of hit ratio was $96.9\%$ by canonical discriminant function of 5 variables. 4. With the unstandardized canonical discriminant function coefficient and constant, canonical discriminant function equation 1 and 2 were calculated. And cutting score and range of score of the classified types were computed. The criteria that select the new subjects were decided.

• Journal of the Korean Society of Clothing and Textiles
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• v.29 no.7 s.144
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• pp.959-967
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• 2005

The color of apparels has the interaction of the face skin colors of the wearers. This study was carried out to classify the face skin colors of Korean males into several similar face skin colors in order to extract favorable colors which flatter to their face skin colors. The criterion that select the new subjects who have the classified face skin colors have to be decided. With color spectrometer, JX-777, face skin colors of subjects were measured quantitatively and classified into three clusters that had similar hue, value and chroma with Munsell Color System. Sample size was 418 Korean males and other 15 of new males subjects. Data were analyzed by K-means cluster analysis, ANOVA, Duncan multiple range test, Stepwise discriminant analysis using SPSS Win. 12. Findings were as follows: 1. 418 subjects who have YR colors were clustered into 3 kinds of face skin color groups. 2. Discriminant variables of face skin colors was 4 variables : L value of forehead, v value of cheek, c value of forehead, and b value of cheek from standardized canonical discriminant function coefficient 1 and c value of forehead, L value of forehead, b value of cheek. and L value of cheek from standardized canonical discriminant function coefficient 2. 3. Hit ratio of type 1 was $92.3\%$, of type 2 was $96.5\%$ and of type 3 was $92.6\%$ by the canonical discriminant function of 4 variables. 4. The canonical discriminant function equation 1 and 2 were calculated with the unstandardized canonical discriminant function coefficient and constant, the cutting score, and range of the score were computed. 5. The criterion that select the new subjects who have the classified face skin colors was decided.

• The Journal of Korean Association of Computer Education
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• v.16 no.2
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• pp.39-48
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• 2013

This study investigates the predictive model of the adolescents' computer entertainment behavior using neural network with the KYPS data (3449 in the junior high school; 1725 boys and 1724 girls). This study compares the results of neural network(model 1) to the logistic regression model and neural network(model 2) with the exact same variables used in logistic regression. The results reveal that the prediction of neural network model 1 is the highest among three models and with gender, computer use time, family income, the number of close friends, the number of misdeed friends, individual study time, self-control, private education time, leisure time, self-belief, stress, adaptation to school, and study related worries, the neural network model 1 predicts the computer entertainment behavior more efficiently. These results suggest that the neural network could be used for diagnosing and adjusting the adolescents' computer entertainment behavior.

• Journal of Forest and Environmental Science
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• v.14 no.1
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• pp.145-156
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• 1998

On the basis of data obtained from 5 forest roads(Backyang, Byongatae, Saorang, Bukyu and Dangrim forest road) collapsed under a heavy rainfall in Chunchon, Kangwondo, this study was carried out to predict the cutting slope failure of forest road by using Quantification theory(II). The results were summarized as follows; The cutting slope failure was chiefly occurred by correlated action of road structure, vegetation and topographical factors. The cutting slope failure predicted by partial correlation coefficients and range values was characterized by longer than 8m of cutting slope length, depper than 2.5m of soil depth, between $30^{\circ}$ and $50^{\circ}$ of original ground slope gradient, absence of vegetation coverage on cutting slope, and greater than $60^{\circ}$ of cutting slope gradient. And the rate of correct discrimination by analysis of cutting slope failure was 90.1%.

• Journal of Korea Multimedia Society
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• v.11 no.2
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• pp.237-246
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• 2008

According to the development of information & web technology and the amount of information increases, there have been numerous problems exposed. Although, software engineers try to overcome the limitations by using software agent and web service, there hasn't been satisfactory result in the paradigm of current software agent being a provider to the user's demand. Moreover, the latest configuration of software development is based on CBD (Component Based Development). However, to construct new component using CBD costs great deal of expenses and therefore, a new model which can acquirecomponent information on the web promptly and accurately with low expenses is required. In this paper, the repository management system which acquires and manages on the Semantic web is designed and compare them to the existing component repository management and present its analysis result. In addition, to overcome the limitations of existing component repository system; low accuracy of search result, restrictive search vocabulary and faulty information, the specific plan is presented to perform a knowledge search for the component.

• Journal of Digital Convergence
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• v.13 no.10
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• pp.313-318
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• 2015

A traditional speech enhancement methods distort the sound spectrum generated according to estimation of the remaining noise, or invalid noise is a problem of lowering the speech recognition performance. In this paper, we propose a speech detection method that convergence the sound energy distribution process and sound energy parameters. The proposed method was used to receive properties reduce the influence of noise to maximize voice energy. In addition, the smaller value from the feature parameters of the speech signal The log energy features of the interval having a more of the log energy value relative to the region having a large energy similar to the log energy feature of the size of the voice signal containing the noise which reducing the mismatch of the training and the recognition environment recognition experiments Results confirmed that the improved recognition performance are checked compared to the conventional method. Car noise environment of Pause Hit Rate is in the 0dB and 5dB lower SNR region showed an accuracy of 97.1% and 97.3% in the high SNR region 10dB and 15dB 98.3%, showed an accuracy of 98.6%.

• Journal of the Korean earth science society
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• v.23 no.7
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• pp.587-596
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• 2002

A super ensemble model was developed for the seasonal prediction of regional precipitation in Korea using the lag correlated large scale predictors, based on the empirical orthogonal function (EOF) analysis and multiple linear regression model. The predictability of this model was also evaluated by cross-validation. Correlation between the predicted and the observed value obtained from the super ensemble model showed 0.73 in spring, 0.61 in summer, 0.69 in autumn and 0.75 in winter. The predictability of categorical forecasting was also evaluated based on the three classes such as above normal, near normal and below normal that are clearly defined in terms of a priori specified by threshold values. Categorical forecasting by the super ensemble model has a hit rate with a range from 0.42 to 0.74 in seasonal precipitation.