• 대한예방의학회:학술대회논문집
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• 대한예방의학회 1994년도 교수 연수회(역학)
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• pp.137-141
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• 1994

The purpose of this paper is to examine what is meant by a ralid measure of health. Guyatt, Kirshner and Jaeschke propose that health tests should be designed so as to have one of several kinds of validity: 'longitudinal construct validity' for those which are used for longitudinal research designs, and 'cross-sectional construct validity' for those which are used for cross-sectional designs. Williams and Naylor argue that this approach to test classification and validation confuses what a test purports to measure with the purpose for which it is used, and that some tests have multiple uses. A review of the meanings of validity in the psychologica test literature shows that both sets of authors use the term validity in an idiosyncratic way. Although the use of a test (evaluated by content validity) should not be conflated with whether the test actually measures a specified construct (evaluated by construct validity);' if health is actually made up of several constructs (as suggested in Hyland's interactional model) then there may be an association between types of construct and types of purpose. Evidence is reviewed that people make several, independent judgements about their health: cognitive perceptions of health problems are likely to be more sensitive to change in a longitudinal research design. whereas emotional evaluations of health provide less bias in cross-sectional designs. Thus. a classification of health measures in terms of the purpose of the test may parallel a classification in terms of what tests purport to measure.

• 한국과학교육학회지
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• 제36권1호
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• pp.87-101
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• 2016

본 연구의 목적은 초등학교에서 개발 시행된 서술형 평가 문항의 내용타당도를 분석하는데 있으며, 이 평가 문항들의 개선을 위한 기초자료를 제시하는데 연구의 의의가 있다. 이를 위하여 여러 초등학교의 서술형 평가문항을 수집하고, 이원분류표의 평가목표와 문항의 평가목표가 요구하는 행동소를 비율차 검정하였다. 분석의 결과 교사가 제작한 서술형 평가문항은 '지식', '이해'를 주로 측정하고 있으며, 행동영역의 내용타당도가 낮음을 확인하였다. 내용타당도가 낮은 결과를 설명하기 위해 9명의 초등 교사를 대상으로 면담을 실시하였다. 면담의 결과 초등학교 과학과 서술형 평가문항의 내용타당도 확보를 저해하는 요인으로 교사내적요인과 교사외적요인을 추출하였다. 교사내적요인에는 바르지 않은 이원분류표의 작성법, 초등학생의 발달 단계 고려, 난이도, 채점의 용이성, 경로의존성 등이 포함되었다. 그리고 교사외적으로는 교육과정 및 학부모 그리고 행정적 요소 등이었다. 이상의 결과를 바탕으로 과학교사의 서술형 평가전문성을 위한 요인들을 제언하였다.

• 한국멀티미디어학회논문지
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• 제18권11호
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• pp.1261-1267
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• 2015

The problem of underwater target detection and classification has been attracted a substantial amount of attention and studied from many researchers for both military and non-military purposes. The difficulty is complicate due to various environmental conditions. In this paper, we study classifier ensemble methods for active sonar target classification to improve the classification performance. In general, classifier ensemble method is useful for classifiers whose variances relatively large such as decision trees and neural networks. Bagging, Random selection samples, Random subspace and Rotation forest are selected as classifier ensemble methods. Using the four ensemble methods based on 31 neural network classifiers, the classification tests were carried out and performances were compared.

• Journal of Radiation Protection and Research
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• 제32권1호
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• pp.35-44
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• 2007

밀봉선원은 과학기술부고시에 의거하여 사용용도별로 등급에 따라 해당 성능시험을 수행하고, 각 성능시험을 거친 후 해당 방사성핵종의 방사능 누설량이 200베크렐을 초과하지 아니하여야 한다. 이러한 성능시험은 온도시험, 의부압력시험, 충격시험, 진동시험 및 관통시험으로 구성되어 있으며 등급에 따라서 각 성능시험의 조건이 각각 다르다. 본 연구에서는 진동시험을 제외한 성능시험을 위한 장치를 개발하고 이를 세 가지 종류의 밀봉선원의 성능시험에 적용하였다. 의료용 근접치료기에 사용되는 근접치료기용 선원은 5등급의 온도시험, 3등급의 외압시험, 2등급의 충격시험을 수행하여 'C53211' 등급의 기준에 적합함을 보였다. 산업용 조사기에 사용되는 $^{75}Se$ 및 $^{169}Yb$ 선원에 대하여 4등급의 온도시험, 3등급의 외압시험, 5등급의 충격시험과 관통시험을 실시하여 'C43515' 등급의 기준에 적합함을 입증하였다.

• Journal of Information Processing Systems
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• 제7권4호
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• pp.717-732
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• 2011

Classification in biomedical applications is an important task that predicts or classifies an outcome based on a given set of input variables such as diagnostic tests or the symptoms of a patient. Traditionally the classification algorithms would have to digest a stationary set of historical data in order to train up a decision-tree model and the learned model could then be used for testing new samples. However, a new breed of classification called stream-based classification can handle continuous data streams, which are ever evolving, unbound, and unstructured, for instance--biosignal live feeds. These emerging algorithms can potentially be used for real-time classification over biosignal data streams like EEG and ECG, etc. This paper presents a pioneer effort that studies the feasibility of classification algorithms for analyzing biosignals in the forms of infinite data streams. First, a performance comparison is made between traditional and stream-based classification. The results show that accuracy declines intermittently for traditional classification due to the requirement of model re-learning as new data arrives. Second, we show by a simulation that biosignal data streams can be processed with a satisfactory level of performance in terms of accuracy, memory requirement, and speed, by using a collection of stream-mining algorithms called Optimized Very Fast Decision Trees. The algorithms can effectively serve as a corner-stone technology for real-time classification in future biomedical applications.

• Spatial Information Research
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• 제12권1호
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• pp.111-125
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• 2004

위성영상 분류에 관한 주요 주제 중 하나는 분류 정확도 향상에 있다. 동일지역에 대한 동일시기의 위성영상을 취득할 수 있는 기회가 많아지는 현실을 감안할 때, 복수의 위성영상 데이터를 이용하여 분류정확도가 향상된 분류결과를 도출하는 것은 의미 있는 일일 것이다. 본 연구 주제는 최대우도법을 사용하여 계산된 데이터의 사후확률 및 분류 불확실도를 Dempster-Shafer의 증거이론에 적용하여 분류정확도를 향상시키고자 하는 것이다. 분석결과 개별적인 데이터 분류나 데이터간 융합에 의한 분류보다 본 연구에서 제안한 방법이 전체정확도와 Kappa 지수 모두 높은 정확도를 나타냈으며, 정확도 차에 대한 검정을 실시하여 본 연구에서 제안한 방법이 다른 방법에 비해 우수함을 통계적으로 증명하였다.

• 토지주택연구
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• 제3권4호
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• pp.389-397
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• 2012

In this study, crosshole seismic test, donwhole seismic test, SPT uphole test, and suspension PS logging (SPS logging) were conducted and the shear wave velocities of these tests were compared. The test demonstrated the following result: Downhole tests showed similar results compared to those of crosshole tests, which is known to be relatively accurate. SPS logging showed reliable results in the case of no casing, i.e. in the rock mass, while, in the case of soil ground, its values were lower or higher than those of other tests. SPT-uphole tests showed similar results in the soil ground and upper area of rock mass compared to other methods. However, reliable results could not be obtained from these tests because SPT sampler could not penetrate into the rock mass for the tests.

• Journal of Information Processing Systems
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• 제13권2호
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• pp.215-235
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• 2017

Foraging is a biological process, where a bacterium moves to search for nutriments, and avoids harmful substances. This paper proposes a hybrid approach integrating the bacterial foraging optimization algorithm (BFOA) in a radial basis function neural network, applied to image classification, in order to improve the classification rate and the objective function value. At the beginning, the proposed approach is presented and described. Then its performance is studied with an accent on the variation of the number of bacteria in the population, the number of reproduction steps, the number of elimination-dispersal steps and the number of chemotactic steps of bacteria. By using various values of BFOA parameters, and after different tests, it is found that the proposed hybrid approach is very robust and efficient for several-image classification.

• Steel and Composite Structures
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• 제7권3호
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• pp.185-200
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• 2007

Tubular construction is widely used in a range of civil and structural engineering applications. To date, the principal product range has comprised square, rectangular and circular hollow sections. However, hot-rolled structural steel elliptical hollow sections have been recently introduced and offer further choice to engineers and architects. Currently though, a lack of fundamental structural performance data and verified structural design guidance is inhibiting uptake. Of fundamental importance to structural metallic design is the concept of cross-section classification. This paper proposes slenderness parameters and a system of cross-section classification limits for elliptical hollow sections, developed on the basis of laboratory tests and numerical simulations. Four classes of cross-sections, namely Class 1 to 4 have been defined with limiting slenderness values. For the special case of elliptical hollow sections with an aspect ratio of unity, consistency with the slenderness limits for circular hollow sections in Eurocode 3 has been achieved. The proposed system of cross-section classification underpins the development of further design guidance for elliptical hollow sections.

• 한국컴퓨터정보학회논문지
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• 제24권1호
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• pp.9-23
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• 2019

In this paper, we propose a layer structure of a pest image classifier model using CNN (Convolutional Neural Network) and background removal image processing algorithm for improving classification accuracy in order to build a smart monitoring system for pine wilt pest control. In this study, we have constructed and trained a CNN classifier model by collecting image data of pine wilt pest mediators, and experimented to verify the classification accuracy of the model and the effect of the proposed classification algorithm. Experimental results showed that the proposed method successfully detected and preprocessed the region of the object accurately for all the test images, resulting in showing classification accuracy of about 98.91%. This study shows that the layer structure of the proposed CNN classifier model classified the targeted pest image effectively in various environments. In the field test using the Smart Trap for capturing the pine wilt pest mediators, the proposed classification algorithm is effective in the real environment, showing a classification accuracy of 88.25%, which is improved by about 8.12% according to whether the image cropping preprocessing is performed. Ultimately, we will proceed with procedures to apply the techniques and verify the functionality to field tests on various sites.