• 기술혁신학회지
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• 제11권4호
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• pp.592-612
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• 2008

새로운 기술혁신의 돌파구로서 발생되고 발전해온 기술의 융합현상은 21세기 지식기반경제체제와 더불어 더욱 활발하게 진행되고 있다. 그러나 기술의 융합과 융합기술에 대한 이해와 활용성 제고 방안은 아직 도입기로서 더 많은 개념정리 및 분류체계 등의 연구가 필요한 실정이다. 그동안 부처별로 기존의 관련 기술 분류가 산발적이어서 중복투자에 대한 우려가 높았고, 상대적으로 기술의 융합이나 융합기술에 대해서는 적용이 미진한 측면이 많았으므로 기존개념의 정리와 기술융합 분야에 대한 새롭고 정확한 세부 분류체계가 필요하게 되었다. 본 연구에서는 기술의 융합현상을 동적인 흐름으로 파악하고 기술 융합형태에 따른 특성을 분석하여 종합적인 관점에서 기술의 융합특성별 새로운 분류체계를 제안하고자 한다.

• 사상체질의학회지
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• 제7권2호
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• pp.89-100
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• 1995

This study was conducted for the purpose of finding out an objective classification method for Sasang Constitutional medicine, which divides people into 4 groups of constitution and presents comprehensively physiology, pathology, diagnosis, therapy and recuperation regarding each constitution. Questionnaire of Sasang Constitution Classification(I) was administered to 328 inpatients at Kyung Hee Oriental Medicine Hospital. Data was collected during 10 months from June 1994 to Mar. 11, 1995. For the purposes of this study, the collected data was analyzed by crosstabs, variation analysis, and discrimination analysis. The analyzing program was SPSS PC+V4.0. For the purposes of this study, the collected data was analyzed by crosstabs, cariation analysis, and discrimination analysis. The analyzing program was SPSS PC+V4.0. The results were as follows : 1. There was significant differences of each group scales through variation analysis. The questions of each group had Sasang constitutional diagnostic discrimination abilities 2. The diagnostic discrimination abilities(Hit-ratio=56.10%) of the Questionnaire for Sasang Constitution Classification(I) were found to have over 20% improvement than the propotional chance criteria(33.3%), Especially, Hit-ratio for $So{\breve{u}}m$-In(63%) was higher than that of SoYang-In(55%) and $Ta{\breve{e}}um$-In(56.3%). 3. Through discrimination analysis on good questions of each group, the diagnostic discrimination abilities of the Questionnaire for Sasang Constitution Classification(I) was 57.93%. 4. This would be on the ground that the Questionnaire for Sasang Constitution Classification(I) could be used as a tool for Sasang constitution classification.

• Clinics in Shoulder and Elbow
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• 제25권4호
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• pp.304-310
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• 2022

Background: The Boileau classification distinguishes three surgical neck fracture patterns: types A, B, and C. However, the reproducibility of this classification on plain radiographs is unclear. Therefore, we questioned what the interobserver agreement and accuracy of displaced surgical neck fracture patterns is categorized according to the modified Boileau classification. Does the reliability to recognize these fracture patterns differ between orthopedic residents and attending surgeons? Methods: This interobserver study consisted of a randomly retrieved series of 30 plain radiographs representing clinical practice in a level 1 and a level 2 trauma center. Radiographs were included from patients (≥18 years) who sustained an isolated displaced surgical neck fracture if they were taken ≤1 week after initial injury. A ground truth was established by consensus among three senior orthopedic surgeons. All images were assessed by 17 orthopedic residents and 17 attending orthopedic trauma surgeons. Results: Agreement for the modified Boileau classification was fair (κ=0.37; 95% confidence interval [CI], 0.36-0.38) with an accuracy of 62% (95% CI, 57%-66%). Comparison of interobserver variability between residents and attending surgeons revealed a significant but clinically irrelevant difference in favor of attending surgeons (0.34 vs. 0.39, respectively, Δκ=0.05, 95% CI, 0.02-0.07). Conclusions: The modified Boileau classification yields a low interobserver agreement with an unsatisfactory accuracy in a panel of orthopedic residents and attending surgeons. This supports the hypothesis that surgical neck fractures are challenging to categorize and that this classification should not be used to determine prognosis if only plain radiographs are available.

• 대한원격탐사학회지
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• 제40권1호
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• pp.93-101
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• 2024

Accurate field crop classification is essential for various agricultural applications, yet existing methods face challenges due to diverse crop types and complex field conditions. This study aimed to address these issues by combining support vector machine (SVM) models with multi-seasonal unmanned aerial vehicle (UAV) images, texture information extracted from Gray Level Co-occurrence Matrix (GLCM), and RGB spectral data. Twelve high-resolution UAV image captures spanned March-October 2021, while field surveys on three dates provided ground truth data. We focused on data from August (-A), September (-S), and October (-O) images and trained four support vector classifier (SVC) models (SVC-A, SVC-S, SVC-O, SVC-AS) using visual bands and eight GLCM features. Farm maps provided by the Ministry of Agriculture, Food and Rural Affairs proved efficient for open-field crop identification and served as a reference for accuracy comparison. Our analysis showcased the significant impact of hyperparameter tuning (C and gamma) on SVM model performance, requiring careful optimization for each scenario. Importantly, we identified models exhibiting distinct high-accuracy zones, with SVC-O trained on October data achieving the highest overall and individual crop classification accuracy. This success likely stems from its ability to capture distinct texture information from mature crops.Incorporating GLCM features proved highly effective for all models,significantly boosting classification accuracy.Among these features, homogeneity, entropy, and correlation consistently demonstrated the most impactful contribution. However, balancing accuracy with computational efficiency and feature selection remains crucial for practical application. Performance analysis revealed that SVC-O achieved exceptional results in overall and individual crop classification, while soybeans and rice were consistently classified well by all models. Challenges were encountered with cabbage due to its early growth stage and low field cover density. The study demonstrates the potential of utilizing farm maps and GLCM features in conjunction with SVM models for accurate field crop classification. Careful parameter tuning and model selection based on specific scenarios are key for optimizing performance in real-world applications.

• 대한토목학회논문집
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• 제26권5D호
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• pp.885-894
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• 2006

본 논문의 의도는 하이퍼스펙트럴 영상의 다량의 밴드를 사용하면서도 효율적인 분류기법의 개발에 초점을 두고 있다. 본 연구에서는 하이퍼스펙트럴 영상의 분류에 있어 이론적으로 밴드수가 많아질수록 분류정확도가 높을 것이라 예상되는, 다변량 통계분석기법중의 하나인 정준상관분석을 적용한 분류기법을 제안한다. 그리고 기존의 대표적인 전통적 분류기법인 최대 우도분류 방법과 비교한다. 사용되는 하이퍼스펙트럴 영상은 2001년 9월 2일 취득된 EO1-Hyperion 영상이다. 실험을 위한 밴드수는 LANDSAT TM 영상에서 열밴드를 제외한 나머지 데이터의 파장대와 일치하는 부분을 감안하여 30개 밴드로 선정하였다. 지상실제데이터로서 비교기본도를 채택하였다. 이 비교기본도와 시각적으로 윤곽을 비교하고, 중첩분석하여 정확도를 평가하였다. 최대우도분류의 경우 수역 분류를 제외하고는 전혀 분류기법으로서의 역할을 하지 못하는 것으로 판단되며, 수역의 경우도 큰 호수 외에 작은 호수나 골프장내 연못, 부분적으로 물이 존재하는 작은 영역 등은 전혀 분류하지 못하고 있는 것으로 나타났다. 그러나 정준상관분류결과는 비교기본도와 형태적으로 시각적 비교를 해볼 때 골프장잔디를 거의 명확히 분류해 내고 있으며, 도시역에 대해서도 고속도로의 선형 등을 상당히 잘 분류해내고 있음을 알 수 있다. 또한 수역의 경우도 골프장 연못이나 대학교내 연못, 기타지역의 연못, 웅덩이 등 까지도 잘 분류해내고 있음을 확인할 수 있다. 결과적으로 정준상관분석 알고리즘의 개념상 트레이닝 영역 선정시 시행착오를 겪지 않고도 정확한 분류를 할 수 있었다. 또한 분류항목 중에서 잔디와 그 외 식물을 구분해 내는 능력과 수역을 추출해 내는 능력이 최대우도분류기법에 비해 우수하였다. 이상의 결과로 판단해 볼 때 하이퍼스펙트럴영상에 적용되는 정준상관분류기법은 농작물 작황 예측과 지표수 탐사에 매우 유용하리라 판단되며, 나아가서는 분광적 고해상도 영상인 하이퍼스펙트럴 데이터를 이용한 GIS 데이터베이스 구축에 중요한 역할을 할 수 있을 것으로 기대된다.

• 한국지리정보학회지
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• 제6권2호
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• pp.80-91
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• 2003

본 연구에서는 밴드간 연산데이터를 재사용하는 방법이 위성영상를 이용한 토지피복 분류시의 정확도를 향상시키는 방법으로 제안되고 검증되었다. 분류항목별로 연산에 사용할 밴드를 결정하기 위해 밴드 6을 제외한 6개의 밴드를 조합이 가능한 수로 조합하고 감독분류의 최대우도법으로 토지피복 분류를 실시하였다. 49가지로 조합된 밴드의 토지피복 분류결과에서, 정확도가 상위 10위내에 분류된 밴드조합에서 사용된 횟수가 많은 두 밴드를 선정하고 연산하였다. 여기서 얻어진 연산결과를 재구성하여 다시 토지피복 분류를 실시하였다. 그리고 원 데이터를 사용한 토지피복 분류결과와 비교, 검토하였다. 연산 결과를 재구성한 데이터와 원 데이터를 사용한 토지피복 분류를 비교 검토한 결과, 연산결과를 재구성하여 사용한 토지피복 분류에서 나지에 대한 정확도가 조금 떨어진 반면 전체적으로 정확도가 향상됨을 알 수 있었다. 특히 인공지물에 대한 정확도가 향상되었기 때문에 이후 도시역에 대한 토지피복 분류 및 지표정보를 분석할 때 밴드간 연산데이터를 재 사용하는 방법이 유용할 것으로 판단된다.

• Journal of Plant Biology
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• 제9권1_2호
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• pp.7-16
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• 1966

In order to determine the factors related to site quality, 13 areas of Larch growing in the Kwangung and its vicinity forest as sample plots, were examined. Sample plots included various site classes as well as age classes. Three were divided into two groups (major and minor trees). Average height of dominant trees was determined through messurement of 5 to 6 dominant tree in each sample plots. Average height of dominant 30 year-old trees was the basis for site index. A Standard Yield Table for the larch produced in Kwangnung forest was made by various data, which included age class 5, ranging from 10 to 45 years. The relationship of the height of the trees, the site conditions, and ground vegetation are investigated in this paper. The site indexes of 40 forest class age in 28-B and 28-G forest classes of the larch associations for ground vegetation had comparatively rarge differences due to the sampled areas. The relation of the direction of forest communities to the height and the diameter of the tree shwoed that its communiteis of northest and northwest parts appeared higher valueof the height and the diameter. The diameter and the height of trees were closely realted to each other. The samller the occupied area per tree and the smaller the average distance among trees, the more density was increased. The larger the density was the lower height of the trees. In the ground vegetation of the larch communities, there seems to be a definite correlation between the height of trees and the occupied area per tree or the average distance among the trees. The height of trees and site index of two larch communities were as follow: 28-B forest class site index 20.8, height 24.0m, 28-G forest class site index 18.4, height 20.9m. The ground layer was analyzed by the method of Quadrat(20/20sq. cm) with an interval of 1M. It set up 40 Quadrats of the larch communiteis. The community structure of the ground vegetation of two larch was analyzed, and important value was calculated and then evaluated. The ground vegetation under the larch had developed Burmannii Beauv stratal society below the 28-B and 28-G the forest class. Accordingly, the first important value of Burmannii Beauv was found in two ground vegetation below the larch. Therefore, this species could be quantitatively considered as the forest indicator species. Common species of each community appeared 18 species out of 34 species in the ground vegetation under two larch communities. The ground vegetation of the 28-B forest class showed more than that of the 28-G forest class. the similarity of the ground vegetation was measrued by the Frequency Index Community Coefficient. The differences between the associations were lcearly manifested by the ground vegetation tested by Gleason's Frequency Index of Community Coefficient for the analysis of each stratal society of all associations. According to F.I.C.C. the ground vegetation under two larch(28-B and 28-G) forest classes showed higher value. An investigation into the relationship of physical and chemical properties of soil and site was considered the next step to be taken in the study of the larch site classification.

• 한국실내디자인학회논문집
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• 제23권6호
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• pp.195-203
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• 2014

This study selects factors affecting form type of hospital architecture by considering studies and references on hospital architecture type in korea and other countries in general. Also this study classifies general hospitals chronologically and analyzes type change of general hospitals in relation with periodic change of healthcare environment. Through this, this study aims to analyze chronological change of general hospitals' form type and provide the current of hospital architecture's general type. The form type classification of this study is classification according to the form of ward, classification according to the relationship between ward and D.T.D(Diagnostic and Treatment department), classification according to the relationship between O.P.D(Out Patient department) and D.T.D, classification according to the rate of centralization, classification according to the circulation system. The form type of ward changed from plate type to tower type, and the circulation system of ward changed from middle corridor to double corridor, the number of Team Nursing chaged from 1 to 2 in 1990. On the other hand the chage of others classifications took place from 1990' to 2010'. It is judged that this overall change is appeared by a change from an inpatien-oriented system to an outpatient-oriented system followed by an increase in number of outpatients, an increase in amenities in ground floor and adoption of healing environment for patients and visitors.

• 로봇학회논문지
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• 제7권3호
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• pp.171-181
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• 2012

Outdoor mobile robots are faced with various terrain types having different characteristics. To run safely and carry out the mission, mobile robot should recognize terrain types, physical and geometric characteristics and so on. It is essential to control appropriate motion for each terrain characteristics. One way to determine the terrain types is to use non-contact sensor data such as vision and laser sensor. Another way is to use contact sensor data such as slope of body, vibration and current of motor that are reaction data from the ground to the tire. In this paper, we presented experimental results on terrain classification using contact sensor data. We made a mobile robot for collecting contact sensor data and collected data from four terrains we chose for experimental terrains. Through analysis of the collecting data, we suggested a new method of terrain feature extraction considering physical characteristics and confirmed that the proposed method can classify the four terrains that we chose for experimental terrains. We can also be confirmed that terrain feature extraction method using Fast Fourier Transform (FFT) typically used in previous studies and the proposed method have similar classification performance through back propagation learning algorithm. However, both methods differ in the amount of data including terrain feature information. So we defined an index determined by the amount of terrain feature information and classification error rate. And the index can evaluate classification efficiency. We compared the results of each method through the index. The comparison showed that our method is more efficient than the existing method.

• 대한원격탐사학회지
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• 제20권2호
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• pp.139-152
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• 2004

본 연구에서는 수정이방성복원 후 지역확장분할 영상분류의 분류오류를 Markov Random Field(MRF) 기반 분류자를 사용하여 개선시킬 것을 제안하고 있다. 제안 접근법은 지역확장분할 분류에 의해 생성된 결과에서 분류오류의 발생 가능성이 높은 경계지역을 정의하고 경계지역내의 화소들에 대해 재분류를 수행하여 수정하는 것이다. 재분류를 위한 MRF 기반 분류자는 지역확장분할 분류에 의해 추정된 클래스 수와 클래스 특성 값을 기반으로 하여 분류를 수행하는 반복적인 기법이다. 모의자료에 대한 실험은 제안 기법이 분류 정확성을 향상시킴을 보여주었다 그러나 실제적으로 많은 탐사지역의 피복형태는 매우 복잡한 구조를 갖고 있으므로 일반적 MRF 기반 기법의 사용은 원격탐사 영상의 정확한 분석을 이끌어 내지 못할 수 있으므로 본 연구는 다중 분류자를 사용하는 다단계 경계지역 수정기법을 제안한다. 한반도의 실제 원격탐사 영상자료에 대한 적용결과는 다단계 기법의 효과성을 잘 보여주고 있다. 다단계 반복적 경계지역 내 분류수정은 분석지역에 존재하는 자세한 구조를 보존하는 한편 지역적 명확한 구분의 분류결과를 생성한다.