• 전기학회논문지
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• 제64권9호
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• pp.1337-1346
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• 2015

In this paper, pattern classifier is designed to classify precipitation and non-precipitation events from weather radar data. The proposed classifier is based on Fuzzy Neural Network(FNN) and consists of three FNNs which operate in parallel. In the proposed network, the connection weights of the consequent part of fuzzy rules are expressed as two polynomial types such as constant or linear polynomial function, and their coefficients are learned by using Least Square Estimation(LSE). In addition, parametric as well as structural factors of the proposed classifier are optimized through Differential Evolution(DE) algorithm. After event classification between precipitation and non-precipitation echo, non-precipitation event is to get rid of all echo, while precipitation event including non-precipitation echo is to get rid of non-precipitation echo by classifier that is also based on Fuzzy Neural Network. Weather radar data obtained from meteorological office is to analysis and discuss performance of the proposed event and echo patter classifier, result of echo pattern classifier compare to QC(Quality Control) data obtained from meteorological office.

• 한국산학기술학회논문지
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• 제21권1호
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• pp.169-177
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• 2020

과학기술 분야의 연구·개발 결과는 연구보고서 형태로 국가과학기술정보서비스(NTIS)에 제출된다. 각 연구보고서는 국가과학기술 표준 분류체계 (K-NSCC)에 따른 분류코드를 가지고 있는데, 보고서 작성자가 제출 시에 수동으로 입력하게끔 되어있다. 하지만 2000여 개가 넘는 세분류를 가지고 있기에, 분류체계에 대한 정확한 이해가 없이는 부정확한 분류코드를 선택하기 십상이다. 새로이 수집되는 연구보고서의 양과 다양성을 고려해 볼 때, 이들을 기계적으로 보다 정확하게 분류할 수 있다면 보고서 제출자의 수고를 덜어줄 수 있을 뿐만 아니라, 다른 부가 가치적인 분석 서비스들과의 연계가 수월할 것이다. 하지만, 국내에서 과학기술표준 분류체계에 기반을 둔 문서 자동 분류 연구 사례는 거의 없으며 공개된 학습데이터도 전무하다. 본 연구는 KISTI가 보유하고 있는 최근 5년간 (2013년~2017년) NTIS 연구보고서 메타정보를 활용한 최초의 시도로써, 방대한 과학기술표준 분류체계를 기반으로 하는 국내 연구보고서들을 대상으로 높은 성능을 보이는 문서 자동 분류기법을 도출하는 연구를 진행하였다. 이를 위해, 과학기술 표준분류 체계에서 과학기술 분야의 연구보고서를 분류하기에 적합한 중분류 210여 개를 선별하였으며, 연구보고서 메타 데이터의 특성을 고려한 전처리를 진행하였다. 특히, 가장 영향력 있는 필드인 과제명(제목)과 키워드만을 이용한 TK_CNN 기반의 딥러닝 기법을 제안한다. 제안 모델은 텍스트 분류에서 좋은 성능을 보이고 있는 기계학습법들 (예, Linear SVC, CNN, GRU등)과 비교하였으며, Top-3 F1점수 기준으로 1~7%에 이르는 성능 우위를 확인하였다.

• 대한수학회지
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• 제54권5호
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• pp.1537-1556
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• 2017

In this paper, we introduce the notion of generating index ${\mathcal{I}}_1(A)$ (2-generating index ${\mathcal{I}}_2(A)$, resp.) of a left-symmetric algebra A, which is the maximum of the dimensions of the subalgebras generated by any element (any two elements, resp.). We give a classification of left-symmetric algebras with ${\mathcal{I}}_1(A)=1$ and ${\mathcal{I}}_2(A)=2$, 3 resp., and show that all such algebras can be constructed by linear and bilinear functions. Such algebras can be regarded as a generalization of those relating to the integrable (generalized) Burgers equation.

• 한국축산식품학회지
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• 제29권1호
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• pp.132-139
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• 2009

본 연구에서는 1,300명의 소비자들이 직접 먹어보고 평가한 한우고기 데이터를 이용하여 쇠고기 맛 등급을 구분 해 내기 위한 판별분석 방법들을 비교하였다. 한우 관능평가의 주요 세 변수인 연도, 다즙성, 향미를 포함한 정준 판별분석과 대표적인 맛 변수로 여겨지는 전반적인 기호도 만을 이용하여 선형판별분석과 비모수 판별분석을 하였다. 전반적인 기호도와 같은 한 개의 변수만을 사용할 경우 두 가지 모두 비슷한 분류율을 나타내지만 선형판별 함수는 이해와 사용 측면에서 장점이 있었던 반면에 비모수적 방법은 커널함수와 띠폭에 대한 선택이 불편하지만 잘 선택하면 정확한 분류율을 높일 수 있는 장점이 있었다. 그러나 다른 정보를 가진 변수들이 있음에도 불구하고 한 개의 변수만을 이용한 판별 분석은 판별에 영향을 미치는 다른 중요한 변수들의 정보를 활용하지 못한다는 문제점이 있다. 한편, 정준판별분석의 경우 정준판별함수의 오분류율이 일변량 선형 판별함수와 비모수 판별함수의 오분류율에 비해 크게 떨어지지 않으면서 분포에 대한 특별한 가정이 필요하지 않아 통계적 가정이 까다롭지 않고 또한 맛에 중요한 요인인 연도, 다즙성, 향미의 세 개변수를 모두 사용하므로 맛 정보를 최대로 활용한다는 장점이 있었다. 따라서 본 연구결과 연도, 다즙성, 향미의 세가지 변수 정보를 모두 포함한 다변량 정준판별분석법을 이용하는 것이 맛 등급을 구분하는데 가장 적절할 것으로 판단되었다.

• 대한화학회지
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• 제36권1호
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• pp.113-124
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• 1992

Chemometrics의 한 분야인 패턴인지(pattern recognition)법을 한국산 고대 유리시료 94종의 중성자방사화분석으로부터 얻은 다변수데이타에 적용하였다. unsupervised learning의 방법인 주성분분석과 비선형도시법으로 시료를 분류한 결과 유리시료는 6개의 군을 형성하였다. 6개의 참조시료셋트와 시험시료셋트에 supervised learning의 SIMCA법을 적용시켰다. 그 결과 참조시료셋트는 주성분분석법 및 비선형도시법의 결과와 일치하였고 시험시료셋트에서 33개의 시료 중 17개 시료에 대해 시료가 속한 군을 판정할 수 있었다.

• 대한조선학회논문집
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• 제43권2호
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• pp.197-205
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• 2006

In general, brackets found at tank boundary are design according to the Classification Society Rule. Since much man power is needed in manufacturing the brackets stiffened by flange, it is necessary to suggest alternative designs, of which flanges are removed, through the rigorous structural analysis. In this paper non-linear structural analysis for brackets with and/or without flange have been carried out to examine their structural behavior and ultimate strengths. Alternative designs for brackets are suggested based on the results of ultimate strength analysis so that the alternative brackets have the similar level of strength and stiffness to the original brackets. It has been seen that the structural safety of alternative brackets proposed in this paper are beyond the appropriate level. The primary benefit of replacing the original brackets by the alternatives is the reduction of man power in manufacturing brackets and 10 to 15% weight saving can be expected in additional. This paper ends with some comments about the extension of the present study.

• Archives of Plastic Surgery
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• 제38권2호
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• pp.143-147
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• 2011

Purpose: A Tessier classification number 7 cleft is an uncommon malformation that results from a failure of mesenchymal fusion within the maxillary and mandibular prominences of the 1st pharyngeal arch. Many operative techniques of the number 7 cleft repair have been proposed to restore function and improve aesthetics. Fifteen patients underwent repair of a number 7 cleft over 13 years by a modification of the surgical Technique, and an appraisal of the operative outcome is reported herein. Methods: A retrospective review was conducted involving 15 patients with number 7 clefts who underwent surgery from 1996 to 2009. The changes in surgical technique included skin closure, attachment of the orbicularis oris muscle, and position of the repaired commissure; the changes were analysed with a review of the medical records and the outcomes of surgery were analysed via photographs. Specifically, the technique of skin closure was changed from the a Z-plasty to a linear closure, the orbicularis oris muscle overlapped attachment was replaced by a side-to-side approximation with horizontal mattress sutures, and the position of the repaired commissure was changed from 1 mm laterally to 1 mm medially in reference to the non-cleft side. Results: A Z-plasty caused additional cutaneous scarring, an overlapped attachment of the orbicularis oris muscle caused a thick oral commissure, and the repaired commissure migrated to the lateral side, so a 1 mm, laterally-positioned commissure caused asymmetry. The altered procedure included a linear skin closure, a side-to-side orbicularis oris muscle approximation, and a 1 mm, medially-positioned commissure, which together resulted in a good outcome. Conclusion: The altered procedure for repair of a number 7 cleft as described herein, yields a short scar, no functional problems with the orbicularis oris muscle, a thin oral commissure, and symmetry of the repaired commissure.

• 대한의용생체공학회:의공학회지
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• 제37권4호
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• pp.127-133
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• 2016

This study proposes the feasibility for automatic classification of sleep/wakefulness using nasal pressure in patients with sleep-disordered breathing (SDB). First, SDB events were detected using the methods developed in our previous studies. In epochs for normal breathing, we extracted the features for classifying sleep/wakefulness based on time-domain, frequency-domain and non-linear analysis. And then, we conducted the independent two-sample t-test and calculated Mahalanobis distance (MD) between the two categories. As a results, $SD_{LEN}$ (MD = 0.84, p < 0.01), $P_{HF}$ (MD = 0.81, p < 0.01), $SD_{AMP}$ (MD = 0.76, p = 0.031) and $MEAN_{AMP}$ (MD = 0.75, p = 0.027) were selected as optimal feature. We classified sleep/wakefulness based on support vector machine (SVM). The classification results showed mean of sensitivity (Sen.), specificity (Spc.) and accuracy (Acc.) of 60.5%, 89.0% and 84.8% respectively. This method showed the possibilities to automatically classify sleep/wakefulness only using nasal pressure.

• 한국안전학회지
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• 제33권4호
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• pp.21-29
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• 2018

In many companies handling flammable liquids, explosion-proof electrical equipment have been installed according to the Korean Industrial Standards (KS C IEC 60079-10-1). In these standards, hazardous area for explosive gas atmospheres has to be classified by the evaluation of the evaporation rate of flammable liquid leakage. The evaporation rate is an important factor to determine the zones classification and hazardous area distance. However, there is no systematic method or rule for the estimation of evaporation rate in these standards and the first principle equations of a evaporation rate are very difficult. Thus, it is really hard for industrial workplaces to employ these equations. Thus, this problem can trigger inaccurate results for evaluating evaporation range. In this study, empirical models for estimating an evaporation rate of flammable liquid have been developed to tackle this problem. Throughout the sensitivity analysis of the first principle equations, it can be found that main factors for the evaporation rate are wind speed and temperature and empirical models have to be nonlinear. Polynomial regression is employed to build empirical models. Methanol, benzene, para-xylene and toluene are selected as case studies to verify the accuracy of empirical models.

• Journal of Information Processing Systems
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• 제1권1호
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• pp.22-26
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• 2005

In this paper, we classified the objectionable texts into four rates according to their harmfulness and proposed the hierarchical text rating system for objectionable documents. Since the documents in the same category have similarities in used words, expressions and structure of the document, the text rating system, which uses a single classification model, has low accuracy. To solve this problem, we separate objectionable documents into several subsets by using their properties, and then classify the subsets hierarchically. The proposed system consists of three layers. In each layer, we select features using the chi-square statistics, and then the weight of the features, which is calculated by using the TF-IDF weighting scheme, is used as an input of the non-linear SVM classifier. By means of a hierarchical scheme using the different features and the different number of features in each layer, we can characterize the objectionability of documents more effectively and expect to improve the performance of the rating system. We compared the performance of the proposed system and performance of several text rating systems and experimental results show that the proposed system can archive an excellent classification performance.