• 제목/요약/키워드: discriminant functions

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한국과 영국 사이의 국립공원 자연 경관 특색의 판별 분석 - 내용기반 영상검색의 저단계 기능 측면에서 - (Discriminant Analysis of Natural Landscape Features in National Parks between Korea and Scotland - Using Low-Level Functions of Content-Based Image Retrieval -)

  • 이덕재
    • 한국환경생태학회지
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    • 제22권3호
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    • pp.289-300
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    • 2008
  • 질감, 모양, 색채 등 내용기반 영상검색(CBIR)의 기능을 이용하여 한국의 지리산 국립공원과 영국의 케이른고럼스 국립공원의 자연 경관에 있어서의 차이를 판별하는데 본 연구의 목적이 있다. 먼저 각 국립공원의 자연경관을 디지털 사진영상으로 촬영한 후, 전형적인 경관사진을 선별하였다. 사진영상의 저단계 기능(Low-level function)이 계량화되어 수직적으로 회전된 다섯 개의 요인으로 축약되었다. 이 중 유의한 차이를 보이지 않은 물 관련 요인이 제외된 나머지 네 개의 요인에 근거한 판별선이 케이른고럼스 경관과 지리산 경관 사이에서 도출되어, 판별함수가 두 그룹을 유의하게 분할하였다($x^2(4)$=61.433; p<0.001). 고유치 2.417과 월크스 람다 0.293에 의하여 전체 변이가 두 그룹의 판별함수 평균의 차이에서 대부분 산출되었음을 확인하였다. 또한, 네 개의 독립변수가 종속변수 전체 분산의 70.7%를 설명하는 것으로 추정되었다. 경관에 대하여 가장 큰 효과를 나타내는 변수는 원거리관련 변수(r=1.073)이며, 다음으로 근거리관련 변수(r=0.896)였으며, 전체적으로 90.7%가 타당하게 분류되었다. 이는 케이른고럼스 국립공원과 지리산 국립공원 자연경관 사이에서 사진영상의 근거리 요인뿐만 아니라, 원거리 요인이 보다 경관 차이에 유의한 판별력을 보이는 것으로 해석되므로, 국립공원의 경관정체성과 관련한 원거리 스카이라인의 시각적 중요성을 보여주는 것이라 하겠다.

다차원 컬러벡터 기반 백태 및 황태 분류 판별함수 설계 (Design of Discriminant Function for White and Yellow Coating with Multi-dimensional Color Vectors)

  • 이전;최은지;유현희;이혜정;이유정;박경모;김종열
    • 한국한의학연구원논문집
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    • 제13권2호통권20호
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    • pp.47-52
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    • 2007
  • In Oriental medicine, the status of tongue is the important indicator to diagnose one's health, because it represents physiological and clinicopathological changes of inner parts of the body. The method of tongue diagnosis is not only convenient but also non-invasive, therefore, tongue diagnosis is one of the most widely used in Oriental medicine. But tongue diagnosis is affected by examination circumstances a lot. It depends on a light source, degrees of an angle, doctor's condition and so on. So it is not easy to make an objective and standardized tongue diagnosis. As part of way to solve this problem, in this study, we tried to design a discriminant function for white and yellow coating with multi-dimensional color vectors. There were 62 subjects involved in this study, among them 48 subjects diagnosed as white-coated tongue and 14 subjects diagnosed as yellow-coated tongue by oriental doctors. And their tongue images were acquired by a well-made Digital Tongue Diagnosis System. From those acquired tongue images, each coating section were extracted by oriental doctors, and then mean values of multi -dimensional color vectors in each coating section were calculated. By statistical analysis, two significant vectors, R in RGB space and H in HSV space, were found that they were able to describe the difference between white coating section and yellow coating section very well. Using these two values, we designed the discriminant function for coating classification and examined how good it works. As a result, the overall accuracy of coating classification was 98.4%. We can expect that the discriminant function for other coatings can be obtained in a similar way. Furthermore, if an automated segmentation algorithm of tongue coating is combined with these discriminant functions, an automated tongue coating diagnosis can be accomplished.

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Index of Union와 다른 정확도 측도들 (Index of union and other accuracy measures)

  • 홍종선;최소연;임동휘
    • 응용통계연구
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    • 제33권4호
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    • pp.395-407
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    • 2020
  • 최적분류점에 대한 대부분의 정확도 측도들은 두 종류의 누적분포함수와 확률밀도함수를 기반으로 정의하거나 또는 ROC 곡선과 AUC를 기반으로 정의하는 방법으로 구분하는데, Unal (2017)은 두 가지 방법을 혼합하여 누적분포함수와 AUC를 모두 고려하는 정확도 측도 Index of Union (IU) 통계량을 제안하였다. 본 연구에서는 IU 통계량을 포함한 열 개의 정확도 측도들을 여섯 종류의 범주로 구분하여 각 범주에 속하는 측도들을 비교하면서 IU의 장점을 연구한다. 다양한 정규혼합분포를 설정하여 각각의 측도들에 대응하는 최적분류점들을 구하고 각 분류점에 대응하는 제1종과 제2종 오류 그리고 두 종류의 오류합을 구해서 오류들의 크기를 비교하면서 분류정확도 측도들의 판별력을 비교하면서 IU의 성격과 특징을 탐색한다. 두 종류 분포들의 평균 차이가 증가할수록 IU 통계량의 제1종 오류와 오류합의 크기가 최고의 분류정확도를 갖는 제2범주의 정확도 측도의 오류에 수렴하는 것을 발견하였다. 그러므로 IU는 모형의 판별력을 평가하는 정확도 측도로 활용할 수 있다.

판별함수에 의한 진해만 적조예측 (The Prediction of Red Tides in Jinhae Bay using a Discriminant Function)

  • 이문옥;백상호
    • 한국환경과학회지
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    • 제7권1호
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    • pp.8-19
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    • 1998
  • The dicriminant function was introduced to understand the cause and establish the prediction method of red tides occurring In Jinhae Bay. Korea. Two sea re91ons of Masan and Haengam Bays and Dang- dong and Wonmun Bays had different types of causes and patterns for red tides. In Masan and Haengam Bays, the red tides concentrically occurred during June and September. For example, in .lune the red tides occurred from physical and meteorological factors, which are related to the stratification and the increase in planktons. However in August the red tides occurred from the water quality environment, based on these conditoins. Futhermore, in September the red tides were caused by the balance between the meteorological and water quality environmental factors. In contrast to those, In Dangdong and Won-mun Bays, the red tides mainly occurred during July and October and the frequency of occurrence was not as much as Masan and Haengam Bays. Especially, in August and September most meteorological and physical factors or water quality environmental factors appeared to contribute to the occurrence of red tides. This indicates that red tides do not easily occur as they are controlled by various environmental factors particularly in these regions The discriminant functions were applied to predict red tides which they were actually occurred In Masan and Haengam Bays in June. The results showed that they were successful for the prediction of red tide at Haengam Bay but not at Masan Bay. The reason for their discrepancy in Masan Bay could have come from using a slight higher value of pH or COD in May, instead of its value in June.

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파킨슨병 환자와 정상노인 간의 문장 읽기에 나타난 운율 특성 비교 (A study of prosodic features of patients with idiopathic Parkinson's disease)

  • 강영애;성철재;윤규철
    • 말소리와 음성과학
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    • 제3권1호
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    • pp.145-151
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    • 2011
  • In view of the hypothesis that the effects of Parkinson's disease on voice production can be detected before pharmacological intervention, the prosodic features of patients with idiopathic Parkinson's disease (IPD) and a healthy aging group were diagnostically analyzed with the long term object of establishing, for clinical purposes, early disease-progression biomarkers. Twenty patients (male 8; female 12) with IPD (prior to pharmacological intervention) and a healthy control group of 22 (male 10; female 12) were selected. Ten sentences were recorded with a head-worn microphone. One sentence was chosen for the analysis of this paper. Relevant parameters, i.e. 3-dimensional model (F0, intensity, duration) and pitch and intensity related slopes (maxEnergy, maxF0, meanAbS, semiT, meanEnergy, meanF0), were analyzed by two-group discriminant analysis. The stepwise estimation method of discriminant analysis was performed by gender. The discriminant functions predicted 83.9% of the male test data correctly while the prediction rate was 93.1% for the female group. The results showed that meanF0_slope and semiT_slope were more important parameters than the others for the male group. For the female group, the meanEnergy_slope and maxEnergy_slope were the important ones. These findings indicate that significant parameters are different for the male and female group. Gender lifestyle may be responsible for this difference. Dysprosodic features of IPD show not simultaneously but progressively in terms of F0, intensity and duration.

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Judging spinal deformity by two characteristic axes on a human back

  • Ishikawa, Seiji;Eguchi, Takemi;Yamaguchi, Toshihiko;Ki, Hyoung-Seop;Otsuka, Yoshinori
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1996년도 Proceedings of the Korea Automatic Control Conference, 11th (KACC); Pohang, Korea; 24-26 Oct. 1996
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    • pp.438-441
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    • 1996
  • Spinal deformity is a serious disease especially for teenagers and it is desirable for school children to be checked possible spinal deformity by moire photographic inspection method. The moire images of children's backs are visually inspected by doctors, which may cause misjudge because of a large amount of data they have to examine. A technique is proposed in this paper for automating this inspection by computer. Two characteristic axes, a potential symmetry axis approximating the human middle line and a principal axis representing the direction of a moire pattern are employed. Two principal axes are extracted locally on a back and their gradients against the potential symmetry axis are calculated. These gradients compose a 2D feature space and a linear discriminant function (LDF) is defined there which separates normal cases from suspicious cases. The LDF defined by 40 training, data was employed in the experiment to examine 40 test data and 77.5% of them were classified correctly. This amounts to 88.8% if the training data is included.

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Optimized Polynomial Neural Network Classifier Designed with the Aid of Space Search Simultaneous Tuning Strategy and Data Preprocessing Techniques

  • Huang, Wei;Oh, Sung-Kwun
    • Journal of Electrical Engineering and Technology
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    • 제12권2호
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    • pp.911-917
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    • 2017
  • There are generally three folds when developing neural network classifiers. They are as follows: 1) discriminant function; 2) lots of parameters in the design of classifier; and 3) high dimensional training data. Along with this viewpoint, we propose space search optimized polynomial neural network classifier (PNNC) with the aid of data preprocessing technique and simultaneous tuning strategy, which is a balance optimization strategy used in the design of PNNC when running space search optimization. Unlike the conventional probabilistic neural network classifier, the proposed neural network classifier adopts two type of polynomials for developing discriminant functions. The overall optimization of PNNC is realized with the aid of so-called structure optimization and parameter optimization with the use of simultaneous tuning strategy. Space search optimization algorithm is considered as a optimize vehicle to help the implement both structure and parameter optimization in the construction of PNNC. Furthermore, principal component analysis and linear discriminate analysis are selected as the data preprocessing techniques for PNNC. Experimental results show that the proposed neural network classifier obtains better performance in comparison with some other well-known classifiers in terms of accuracy classification rate.

간호사의 이직의도 판별예측인자 (Discriminating factors of turnover intention among Korean staff nurses)

  • 이해정;황선경
    • 간호행정학회지
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    • 제8권3호
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    • pp.381-392
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    • 2002
  • Purpose : The purpose of this study was to examine the degrees of turnover intention among Korean staff nurses(N=175) and to identify discriminating factors of their turnover intention. Method : The data were driven from a larger study and staff nurses who had worked more than 1 year as nurses were included in the analyses. The original data were collected from May 1999 to March 2000. Descriptive and discriminant analyses were utilized. Results : 87% of the participants reported turnover intention. Nurses were grouped into three group(GP)s depending on the frequencies of turnover intention: Never GP(N=23), Sometimes GP(N=107), Frequent GP(N=43). With three GPs, two functions were produced and only function 1 was significant that significantly discriminated Never and Frequent GPs. Additional discriminant analysis with only Never and Frequent GPs produced function classified 93% of the participants correctly into two GPs. Sub-dimensions of work satisfaction were significant discriminating factors. Nurses who are satisfied with doctor and nurse relationship, pay, and hospital administration tend to report no intention in turnover. Conclusion : Based on the findings of this study, possible managemental intervention for increasing interpersonal skills and assertiveness of nurses, inviting medical residents in ward team meeting, increasing incentives or baseline adjustment of annual income for registered nurses were suggested.

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Statistical Approach for Corrosion Prediction Under Fuzzy Soil Environment

  • Kim, Mincheol;Inakazu, Toyono;Koizumi, Akira;Koo, Jayong
    • Environmental Engineering Research
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    • 제18권1호
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    • pp.37-43
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    • 2013
  • Water distribution pipes installed underground have potential risks of pipe failure and burst. After years of use, pipe walls tend to be corroded due to aggressive soil environments where they are located. The present study aims to assess the degree of external corrosion of a distribution pipe network. In situ data obtained through test pit excavation and direct sampling are carefully collated and assessed. A statistical approach is useful to predict severity of pipe corrosion at present and in future. First, criteria functions defined by discriminant function analysis are formulated to judge whether the pipes are seriously corroded. Data utilized in the analyses are those related to soil property, i.e., soil resistivity, pH, water content, and chloride ion. Secondly, corrosion factors that significantly affect pipe wall pitting (vertical) and spread (horizontal) on the pipe surface are identified with a view to quantifying a degree of the pipe corrosion. Finally, a most reliable model represented in the form of a multiple regression equation is developed for this purpose. From these analyses, it can be concluded that our proposed model is effective to predict the severity and rate of pipe corrosion utilizing selected factors that reflect the fuzzy soil environment.