• 대한치과기공학회지
• /
• 제29권2호
• /
• pp.197-211
• /
• 2007

With the development of orthodontics and increasing concerns on physical appearance, the number of patients has been steadily increasing. It is quite important not only to make effective cure plans and accurate diagnoses but also to have a thorough grasp of patients' malocclusion types and their occurrence frequency, in addition to patients' personality in order to cure the patients appropriately. This study is based on 946 malocclusion patients who had visited Chong-A Dental Hospital from 1999 to 2004 and investigated their aspects of malocclusion and characteristics of their gender, age and residence. The results are as follows. 1. The number of patients per year had been decreased until 2001, after which year the number had fluctuated. The number was the largest in 1999, 169 and the smallest in 2001, 140. Female occupied 68.0% of the total, twice as many as male, 32.0%) 2. Based on the Angle's classification, 19 or over year - old group was the largest of the total, 59.3% and 6 or younger year - old group, the smallest, 0.5%. The 19 or over year old group was less than a half of the total (47.4%) in 2003 and there were no patients who belonged to the 6 or younger year - old group in 2003 and 2004. 3. Distributions on the types of malocclusion have shown that 39.9 % of the total are in the Class I, the largest, 31.0% in the Class I and 29.2 in the Class II, the smallest. 1) The number of the ClassI was 73, the largest, that of the Class III being 35, the smallest in 1999. On the whole, the number of the Class I accounted for the largest part of the total. 2) The number of male patients in the Class II was the smallest, generally being the largest in the Class I. In case of female, that of the Class III was the smallest. 3) Based on the age, the Class I was the highest in between 7 and 13 age group, the Class III the lowest. The Class I occupied the largest around 40%. 4) In the shape of physiognomy, the meso occupied the largest part among all the Class, of which the Class II was the highest, 64.2%. The bracy was the largest in the Class I, and the dolicho in the Class III. 5) In the profile, the convex shape was the largest in the Class I and II, and especially in the Class II, over 3/4 of the total, 75.4%. In contrast, the direct shape was the largest in the Class III and the sunken shape occupied 33.3%, which was nearly ten times more than the case of the Class I and III. 6) In the asymmetry of physiognomy, the number of patients of the Class IIIwas the largest, 34.1% and that of the Class II, the smallest, 19.5%. It was found that about one fourth of the malocclusion patients were under the asymmetry of physiognomy. 4. In the distribution of patients' residence, 81.4% were from the Seoul Metropolis and 48.2% from Gangnam-Gu where Chong-A Dental Hospital is located and Seocho-Gu and Songpa-Gu which are adjacent to Gangnam-Gu.

• ALGAE
• /
• 제31권2호
• /
• pp.155-165
• /
• 2016

Green microalgae from the class Chlorophyceae represent a major biodiversity component of eukaryotic algae in continental water. Identification and classification of this group through morphology is a hard task, since it may present cryptic species and phenotypic plasticity. Despite the increasing use of molecular methods for identification of microorganisms, no single standard barcode marker is yet established for this important group of green microalgae. Some available studies present results with a limited number of chlorophycean genera or using markers that require many different primers for different groups within the class. Thus, we aimed to find a single marker easily amplified and with wide coverage within Chlorophyceae using only one pair of primers. Here, we tested the universality of primers for different genes (tufA, ITS, rbcL, and UCP4) in 22 strains, comprising 18 different species from different orders of Chlorophyceae. The ITS primers sequenced only 3 strains and the UCP primer failed to amplify any strain. We tested two pairs of primers for rbcL and the best pair provided sequences for 10 strains whereas the second one provided sequences for only 7 strains. The pair of primers for the tufA gene presented good results for Chlorophyceae, successfully sequencing 21 strains and recovering the expected phylogeny relationships within the class. Thus, the tufA marker stands out as a good choice to be used as molecular marker for the class.

• 한국지구과학회지
• /
• 제37권1호
• /
• pp.21-28
• /
• 2016

한반도의 약 70% 이상을 차지하고 있는 산지는 많은 산들과 산맥으로 이루어져 있으며, 산맥들은 대기환경에 큰 영향을 준다. 산맥의 분류조사는 1900-1902년 일본학자에 의거 수행 된 후, 현재 산맥의 이름이 매우 많고 혼선이 되고 있다. 본 연구는 기존의 산맥 이름과 그 분류를 간단히 하여 사회적 교육적 활용에 가치를 두고 있다. 먼저, 중국의 만주로부터 (대)한반도까지 주축을 이루는 세계적인 제2차 중규모산맥을 단일 이름인 고려산맥으로 명명하였다. 그리고, 고려산맥에 수반되는 지역적인 제3차 산맥들은 지린(길림)산맥, 함경산맥, 태백산맥, 소백산맥으로 분류하고, 그 다음 제4차 산맥은 랴오닝산맥, 옌볜(연변)산맥, 함북산맥, 평북산맥, 황해산맥, 차령산맥, 경상산맥, 남해산맥 등 8개의 중소 산맥으로 분류 하였다. 일반적으로 한반도의 산맥들은 지구규모 대순환의 영향을 지속적으로 받고 있다. 산맥의 풍상과 풍하 측에서 발생하는 공기환경적인 변화에 따라, 인간과 생태계에 주는 대기환경의 영향평가와 그 감시의 필요성을 강조하였다.

• 한국항해학회지
• /
• 제20권2호
• /
• pp.51-58
• /
• 1996

For the smooth flow of traffic vehicles and its effective management, it is necessary to have an exact information on traffic condition, i.e., the volume of traffic, velocity, occupancy and classification of vehicles. In particular, for classification of vehicles, there has been only image processing method using camera, where the method can obtain much information but rather expensive. In this paper, an algorithm for the measurement of velocity and total length of vehicles has been proposed to develop a general traffic management system, which is necessary to discriminate the class of vehicles. In order to realize the proposed algorithm, we have developed an ultrasonic spatial filtering method, which has better performance than that of using the traditional vehicle detector. To have this system to be constructed, we have introduced three sets of ultrasonic devices where each has one transmitter and two receivers which are arranged to obtain the spatial difference of objects. The velocity of vehicles can be measured by analyzing the occurrence time of pulses and their time differences. The total length of vehicles can be given by multiplying velocity with time interval of pulses sequence. To confirm the effectiveness of this measuring system, the experiment by the spatial filtering method using the ultrasonic sensors has been carried out. As the results, it is found that the proposed method can be used as one of measurement tools in the general traffic management system.

• 한국정보처리학회:학술대회논문집
• /
• 한국정보처리학회 2011년도 춘계학술발표대회
• /
• pp.1060-1063
• /
• 2011

인간은 목적지를 향하여 가는 방법의 선택에 있어서 가고자 하는 목적, 목적지, 출발 시간 등에 영향을 받는다. 그러나 이러한 매개변수들과 더불어 중요하게 고려되는 것은 바로 인간의 습관이다. 다시 말해 인간이 목적지로 가는 방법을 선택하는데 습관이라는 매개변수와 밀접한 영향이 있다는 것이다. 이를 미루어 볼 때, 인간의 이동은 습관으로 인해 대부분 특정한 범주 안에서 이동을 할 것이라는 추측할 수 있다. 나아가, 사람들이 흔히 들고 다니는 GPS장치에서 측정된 데이터가 추측한 속성으로 인해 범주를 벗어나는 이상현상을 검출하는 것으로 확장을 할 수 있다. 즉, GPS장치에서 측정된 데이터는 개인별로 클래스화(Classification)가 가능함을 추론할 수 있다. 본 논문에서는 실제 사람이 이동한 좌표를 바탕으로 시간당 변화량을 계산하여 좌표에 사상시켰다. 그리고, 단일 클래스 서포트 백터 머신(OCSVM)을 가지고 클래스화 했으며, OCSVM의 커널 함수 내의 변수인에 따라 클래스의 크기 혹은 클래스 내부의 밀도에 영향을 받음을 알 수 있었으며, 그 둘 사이에는 적절한 교환(Tradeoff)이 발생하였다는 결론이 나왔다.

• 한국생물정보학회:학술대회논문집
• /
• 한국생물정보시스템생물학회 2005년도 BIOINFO 2005
• /
• pp.57-62
• /
• 2005

Microarray gene expression profiling technology is one of the most important research topics in clinical diagnosis of disease. Given thousands of genes, only a small number of them show strong correlation with a certain phenotype. To identify such an optimal subset from thousands of genes is intractable, which plays a crucial role when classify multiple-class genes express models from tumor samples. This paper proposes an efficient classifier design method to simultaneously select the most relevant genes using an intelligent genetic algorithm (IGA) and design an accurate classifier using Support Vector Machine (SVM). IGA with an intelligent crossover operation based on orthogonal experimental design can efficiently solve large-scale parameter optimization problems. Therefore, the parameters of SVM as well as the binary parameters for gene selection are all encoded in a chromosome to achieve simultaneous optimization of gene selection and the associated SVM for accurate tumor classification. The effectiveness of the proposed method IGA/SVM is evaluated using four benchmark datasets. It is shown by computer simulation that IGA/SVM performs better than the existing method in terms of classification accuracy.

• 대한원격탐사학회:학술대회논문집
• /
• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
• /
• pp.706-709
• /
• 2006

Cancer is one of the major causes of death; however, the survival rate can be increased if discovered at an early stage for timely treatment. According to the statistics of the World Health Organization of 2002, breast cancer was the most prevalent cancer for all cancers occurring in women worldwide, and it account for 16.8% of entire cancers inflicting Korean women today. In order to classify the type of breast cancer whether it is benign or malignant, this study was conducted with the use of the discriminant analysis and the decision tree of data mining with the breast cancer data disclosed on the web. The discriminant analysis is a statistical method to seek certain discriminant criteria and discriminant function to separate the population groups on the basis of observation values obtained from two or more population groups, and use the values obtained to allow the existing observation value to the population group thereto. The decision tree analyzes the record of data collected in the part to show it with the pattern existing in between them, namely, the combination of attribute for the characteristics of each class and make the classification model tree. Through this type of analysis, it may obtain the systematic information on the factors that cause the breast cancer in advance and prevent the risk of recurrence after the surgery.

• 인지과학
• /
• 제6권2호
• /
• pp.27-45
• /
• 1995

본 논문에서는 다중 분류기의 통합을 위해 퍼지 행위지식 공간을 구성하고 이를 이용하는 방법을 제안한다.기존의 행위지식 공간은 각 분류기들이 서로 독립적일 필요가 없고 적응적 학습이 가능한 것으로 단지 하나의 클래스 레이블만 을 출력하는 분류기들의 통합에 가장 최적의 방법으로 알려졌다.그러나 행위지식 공간은 각 분류기가 출력하는 클래스 레이블에 대한 측정값과 경험적 지식을 통합과정에 반영하기 어렵다는 문제점을 갖고 있다.이러한 행위지식 공간의 문제점을 해결하기 위해 본 논문에서는 퍼지개념을 이용한 퍼지 행위지식 공간을 정의하고 이를 다중 분류기의 통합에 적용하기 위한 방법을 기술한다.또한,퍼지 행위지식 공간의 유용성을 증명하기 위해 각 분류기로 부터 얻어진 클래스 레이블들과 이에 관련된 측정값을 포함하는 분류결과들의 통합에 적용된 실험결과를 기술한다.

• 한국초등과학교육학회지:초등과학교육
• /
• 제27권3호
• /
• pp.287-295
• /
• 2008

Elementary students' behaviors classifying leaves have been analyzed according to the material types provided for the classification class. 199 sixth grade students were participated in the task classifying the leaves of various plants for the research. The three types of materials provided to them for the class were real leaves, photos of the leaves and explanation cards including the photos of leaves. One of the research findings was that the only material made students handle in the observed behaviors was the real leave of the material types given as classifying. Three were differences between groups in the time required and the number of using criteria for the class. The numbers of criteria had been applied to analyzing their behaviors as classifying the real leaves which were less than those with photo materials. The amount of taken time to classify the real leaves and photo materials were less than those of another material. Finally, the contents of criteria did not differ between groups except appearing properties presented to the task with photo and explanation materials. It is expected that the research can be contributed for elementary school teachers and for curriculum developers to choose appropriate instructional materials as constructing curriculum contents for elementary science to make elementary school students acquire classifying skill in science classes.

• 해양환경안전학회지
• /
• 제27권7호
• /
• pp.1088-1097
• /
• 2021

기계 장비의 진동 데이터는 필연적으로 노이즈를 포함하고 있다. 이러한 노이즈는 기계 장비의 유지보수를 진행하는데 악영향을 끼친다. 그에 따라 데이터의 노이즈를 얼마나 효과적으로 제거해주냐에 따라 학습 모델의 성능을 좌우한다. 본 논문에서는 시계열 데이터를 전처리 함에 있어 특성추출 과정을 포함하지 않는 Denoising Auto Encoder 기법을 활용하여 데이터의 노이즈를 제거했다. 또한 기계 신호 처리에 널리 사용되는 Wavelet Transform과 성능 비교를 진행했다. 성능비교는 고장 탐지율을 계산하여 진행했으며 보다 정확한 비교를 위해 분류 성능 평가기준 중 하나인 F-1 Score를 계산하여 성능 비교를 진행했다. 고장을 탐지하는 과정에서는 One-Class SVM 기법을 활용하여 고장 데이터를 탐지했다. 성능 비교 결과 고장 진단율과 오차율 측면에서 Denoising Auto Encoder 기법이 Wavelet Transform 기법에 비해 보다 좋은 성능을 나타냈다.