• 한국석유지질학회:학술대회논문집
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• 한국석유지질학회 1998년도 제5차 학술발표회 발표논문집
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• pp.10-14
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• 1998

A systematic methodology is developed for the electrofacies determination from wireline log data using multivariate statistical analysis. To consider corresponding contribution of each log and reduce the computational dimension, multivariate logs are transformed into a single variable through principal components analysis. Resultant principal components logs are segmented using the statistical zonation method to enhance the efficiency and quality of the interpreted results. Hierarchical cluster analysis is then used to group the segments into electrofacies. Optimal number of groups is determined on the basis of the ratio of within-group variance to total variance and core data. This technique is applied to the wells in the Korea Continental Shelf. The results of field application demonstrate that the prediction of lithology based on the electrofacies classification matches well to the core and the cutting data with high reliability This methodology for electrofacies classification can be used to define the reservoir characteristics which are helpful to the reservoir management.

• 한국어정보학회:학술대회논문집
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• 한국어정보학회 2017년도 제29회 한글및한국어정보처리학술대회
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• pp.51-55
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• 2017

대규모 분류체계를 사용하는 경우, 기존 방법의 딥 러닝으로는 분류 정확도가 현저히 떨어진다. 이를 해결하기 위해 계층 구조를 활용한 네거티브 샘플링 방법을 제안한다. 학습 문서가 속한 카테고리의 상위 카테고리와 일정부분 겹치는 범위에서 네거티브 샘플을 선택하면, 하나의 큰 문제를 다수개의 하위 문제로 쪼개서 해결하는 학습 효과가 있다. 소규모 분류 체계와 대규모 분류체계 각각에서 샘플링 전략을 차용하였을 때를 비교한 결과, 대규모에서 효과가 좋았으며 그 때의 정확도가 150배 이상 차이가 나는 것을 보였다.

• 한국멀티미디어학회논문지
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• 제21권8호
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• pp.960-968
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• 2018

The mobile visual search service uses a query image to acquire linkage information through pre-constructed DB search. From the standpoint of this purpose, it would be more useful if you could perform a search on a web-based keyword search system instead of a pre-built DB search. In this paper, we propose a representative query extraction algorithm to be used as a keyword on a web-based search system. To do this, we use image classification labels generated by the CNN (Convolutional Neural Network) algorithm based on Deep Learning, which has a remarkable performance in image recognition. In the query extraction algorithm, dictionary meaningful words are extracted using Wikipedia, and hierarchical categories are constructed using WordNet. The performance of the proposed algorithm is evaluated by measuring the system response time.

• 품질경영학회지
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• 제22권2호
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• pp.143-153
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• 1994

Cluster analysis is a primitive technique in which no assumptions are made concerning the data structure. And the number of groups is known a priori discriminant analysis provides an information how well N individuals are classified into their own groups. In this study, clustering, which is any partition of a collection of data points, generated by the application of eight hierarchical clustering methods was re-classified by discriminant analysis. Then correct classification ratios were obtained for the application of discriminant analysis through each clustering method and the direct application of discriminant analysis. By comparing the correct classification ratios, the applicability of cluster analysis and discriminant analysis considered.

• KIEAE Journal
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• 제3권4호
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• pp.15-22
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• 2003

Open housing is an emerging, new concept in housing development that combines demand-orientation with environment-friendliness. Its methodology, however, has not been analyzed in a systematic way. In this study, the features of planning method in open housing were analyzed to systematize types of the planning method. The existing planning methods of open housing was reviewed and they can be classified into three approaches such as pattern, module and organization planning. Given three approaches, the existing planning methods of open housing can be sub-classified as follows; free and patterned planning by patterns, modular and non-modular planning by modules, and hierarchical and non-hierarchial planning by organizations. The framework for the typological analysis was made based on the classification and a composite typological system was drawn from the analysis of the existing planning features. The suggested classification of features in open housing is expected to contribute to the clear definition of characteristics on open housing to provide a basis for the concrete realization method, to analyzing problems with the existing planning methods and to providing their solutions.

• Management Science and Financial Engineering
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• 제16권1호
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• pp.17-46
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• 2010

This paper studies six different AHP (Analytic Hierarchy Process) approaches and suggests that the features of the approaches are classified by application circumstances in order to contribute to the applicability and quality usage of the AHP. Our study investigates the hierarchical principles and characteristics of the AHP, and historical debates on the AHP evaluation in which the six approaches have been involved. One of six approaches is an ANP (Analytic Network Process) application that is directly connected to AHP usage. The application differences among the six approaches are validated with a plain example. Then, the four circumstances of AHP applications are classified by two dimensions: the first dimension is whether or not the importance (weights) of criteria is independent of restrictively setting alternatives, and the second dimension is whether or not preference (priorities) of alternatives is independent of adding alternative(s) to or removing alternative(s) from the considering set of alternatives. Then featuring way of weighting criteria is classified. We suggest the distinguishing manners and describe the implications of the AHP application. Finally, we discuss rank reversal and multiplicative AHP.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1995년도 하계학술대회 논문집 B
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• pp.959-961
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• 1995

The objective of most image proccessing applications is to extract meaningful information from one or more pictures. It is accomplished efficiently using neural networks, which is used in image classification and image recognition. In neural networks, background and meaningful information are processed with same weight in input layer. In this paper, we propose the image classification method using neural networks, especially EBP(Error Back Propagation). Preprocessing is needed. In preprocessing, background is compressed and meaningful information is emphasized. We use the quadtree approach, which is a hierarchical data structure based on a regular decomposition of space.

• 대한인간공학회지
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• 제31권4호
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• pp.493-498
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• 2012

Objective: The purpose of this study is to suggest the hierarchical structure with three layers of input task, input interaction, and input device. Background: Understanding the input interaction is very helpful to design an interface design. Method: We made a model of three layered input structure based on empirical approach and applied to a gesture interaction in TV. Result: We categorized the input tasks into six elementary tasks which are select, position, orient, text, and quantify. The five interactions described in this paper could accomplish the full range of input interaction, although the criteria for classification were not consistent. We analyzed the Microsoft kinect with this structure. Conclusion: The input interactions of command, 4 way, cursor, touch, and intelligence are basic interaction structure to understanding input system. Application: It is expected the model can be used to design a new input interaction and user interface.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1993년도 하계학술대회 논문집 A
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• pp.439-441
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• 1993

A tire tread pattern recognition scheme of which the pattern recognition algorithm is designed based on the fuzzy hierarchical clustering method is proposed and compared with the scheme based on the conventional FCM. The features are extracted from the binary images of the tire tread patterns. In the proposed scheme, the protoypes are obtained more easily and schematically than obtained prototypes using FCM. The experimental results of classification for the practical situations are given and shows the usefulness of the proposed scheme.

• 인터넷정보학회논문지
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• 제21권6호
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• pp.81-94
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• 2020

This study developed evaluation indicators for the comfort experience of virtual reality (VR) headsets by classifying, defining, and weighting cybersickness-causing factors using the Delphi research method and analytic hierarchical process (AHP) approach. Four surveys were conducted with 20 experts on VR motion sickness. The expert surveys involved the 1) classification and definition of cybersickness-causing dimensions, classification of sub-factors for each dimension, and selection of evaluation indicators, 2) self-reassessment of the results of each step, 3) validity revaluation, and 4) final weighting calculation. Based on the surveys, the evaluation indicators for the comfort experience of VR headsets were classified into eight sub-factors: field of view (FoV)-device FoV, latency-device latency, framerate-device framerate, V-sync-device V-sync, rig-camera angle view, rig-no-parallax point, resolution-device resolution, and resolution-pixels per inch (PPI). A total of six dimensions and eight sub-factors were identified; sub-factor-based evaluation indicators were also developed.