• 대한수학교육학회지:수학교육학연구
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• 제22권2호
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• pp.163-178
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• 2012

수를 십진체계에 기초하여 표현하려는 노력은 초 중등학교의 관련 수학 지식들에 대한 개념망 구축과 지도의의에 대한 본질적 이해를 준다. 나아가 고유한 표현의 자연수, 정수, 유리수, 실수를 십진체계로 표현하려는 과정에서 확대된 십진체계인 소수를 분류할 수 있으며, 실수 분류를 위한 하나의 관점을 얻게 된다. 본 연구에서는 자연수의 십진체계 표현에서 출발하여 실수를 십진체계 형태로 표현하려는 과정에서 나타나는 수학적 지식들의 교수학적 의의를 고찰하고, 실수의 분류에 관한 이론적 근거를 제공한다. 이러한 연구는 초 중등학교의 교사가 학교수학을 비판적 안목에서 이해하게 하며, 관련지식에 대한 이론적 배경을 제공한다. 나아가 관련된 수학적 지식들의 내적 연결성과 일관성 있는 교육과정 구성의 단초를 제공한다.

• 전자공학회논문지S
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• 제35S권3호
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• pp.150-158
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• 1998

This paper describes the classification of remotely sensed image data using fuzzy neural network, whose algorithm was obtained by replacing real numbers used for inputs and outputs in the standard back propagation algorithm with fuzzy numbers. In the proposed method, fuzzy patterns, generated based on the histogram ofeach category for the training data, are put into the fuzzy neural network with real numbers. The results show that the generalization and appoximation are better than that ofthe conventional network in determining the complex boundary of patterns.

• 한국도서관정보학회지
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• 제42권2호
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• pp.151-170
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• 2011

이 연구에서는 분석합성식 문헌분류이론이 실생활에 적용되어 활용되고 있는 사례들을 찾아 이를 새로운 시각에서 분석하고자 시도하였다. 이를 위해 우리가 일상적으로 사용하는 한글의 초성과 중성, 종성의 합성 사례와 함께, 대구광역시 및 서울특별시의 시내버스번호, 주요 결혼관련업체의 회원정보, 부동산중개 및 경매관련정보, 우편번호와 광역전화통화권역(DDD) 번호 등의 사례를 문헌분류의 시각에서 분석해보고 그것이 주는 시사점을 제시하였다. 분석합성식 분류이론과 그 기법을 적용할 경우 특히 각 시스템의 기호법의 개선에 도움이 될 수 있음을 밝히고 있다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -2
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• pp.1256-1259
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• 2002

In this paper, we have proposed license plate recognition system for multi-national vehicle license plate using geometric features along with hybrid and seven segment pattern vectors. In the proposed system, we suggested to find horizontal and vertical relation after going through preparation process with inputted real-time license plate image of Korea and Japan, and then to classify license plate with using characteristic and geometric information of license plates. It classifies the extracted license plate images into letters and numbers, such as local name, local number, classification character and license consecutive numbers, and recognize license plate of Korea and Japan by applying hybrid and seven segments pattern vectors to classified letter and number region. License plate extraction step of the proposed system uses width and length information along with relative rate of Korean and Japanese license plate. Moreover, it exactly segmentation by letters with using each letter and number position information within license plate region, and recognizes Korean and Japanese license plates by applying hybrid and seven segment pattern vectors, containing characteristics related to letter size and movement within segmented letter area. As the result of testing the proposed system in real experiment, it recognized regardless of external lighting conditions as well as classifying license plates by nations, Korea and Japan. We have developed a system, recognizing regardless of inputted structural character of vehicle licenses and external environment.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제2권2호
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• pp.159-165
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• 2002

This paper proposes a GA and Gradient Descent Method-based method for choosing an appropriate set of fuzzy rules for classification problems. The aim of the proposed method is to fond a minimum set of fuzzy rules that can correctly classify all training patterns. The number of inference rules and the shapes of the membership functions in the antecedent part of the fuzzy rules are determined by the genetic algorithms. The real numbers in the consequent parts of the fuzzy rules are obtained through the use of the descent method. A fitness function is used to maximize the number of correctly classified patterns, and to minimize the number of fuzzy rules. A solution obtained by the genetic algorithm is a set of fuzzy rules, and its fitness is determined by the two objectives, in a combinatorial optimization problem. In order to demonstrate the effectiveness of the proposed method, computer simulation results are shown.

• 인지과학
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• 제6권3호
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• pp.25-40
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• 1995

본 논문에서는 유전과 강하 기법(GA-GDM)을 이용해 퍼지 규칙 생성 방법을 제안하고 이들 규칙을 식별 문제에 응용해 본다. 퍼지 규칙의 조건부에 있는 추론 규칙의 수와 소속함수는 유전 방법을 이용하고,결론부의 값은 강하 기법을 이용해 규칙을 생성한다.식별 문제는 최소의 규칙으로 최대의 식별을 목적으로 한다.제안한 방법의 목적은 최소의 퍼지 규칙 생성으로 정확히 학습 패턴을 식별하는데 있다.유전 알고리즘의 적합도는 제안한 방법의 목적으로 정의한다.마직막으로 제안한 방법의 유효성을 보이기 위해 시뮬레이션 결과를 보인다.

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

• 성인간호학회지
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• 제24권4호
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• pp.358-369
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• 2012

Purpose: This study was performed to compare the costs of nursing interventions implemented for the obstetrical and gynecological patients using Korean Reimbursement System and ABC codes system developed in the US for costing out interventions performed by health care professional. Methods: First, the narrative data on nursing interventions were extracted from electronic medical record system of a tertiary university and mapped with Nursing Intervention Classification (NIC) by two researchers until 100% consent was reached. Narrative nursing interventions mapped with NIC were then remapped with ABC codes system using the electronic program developed in the research. The mapping data were analyzed with real numbers, frequency, percentage, mean, and standard deviation. Results: More nursing interventions were mapped with ABC codes than Korean reimbursement system. Total of 97 different types of narrative interventions could be mapped with NIC, 43 NIC interventions could be reimbursed by ABC code but only 16 NIC interventions were reimbursed by Korea Reimbursement System. Conclusion: Korean medical insurance fee system needs amendment to include more comprehensively interventions performed by nurses which are very important to patient outcomes. Further study is needed to develop strategies to costing out nursing interventions.

• 통합자연과학논문집
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• 제11권4호
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• pp.167-183
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• 2018

Electroencephalogram (EEG) recording provides a new way to support human-machine communication. It gives us an opportunity to analyze the neuro-dynamics of human cognition. Machine learning is a powerful for the EEG classification. In addition, machine learning can compensate for high variability of EEG when analyzing data in real time. However, the optimal EEG electrode location must be prioritized in order to extract the most relevant features from brain wave data. In this paper, we propose an intelligent system model for the extraction of EEG data by training the optimal electrode location of EEG in a specific problem. The proposed system is basically a fuzzy system and uses a neural network structurally. The fuzzy clustering method is used to determine the optimal number of fuzzy rules using the features extracted from the EEG data. The parameters and weight values found in the process of determining the number of rules determined here must be tuned for optimization in the learning process. Genetic algorithms are used to obtain optimized parameters. We present useful results by using optimal rule numbers and non - symmetric membership function using EEG data for four movements with the right arm through various experiments.

• 가정과삶의질연구
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• 제22권2호
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• pp.85-95
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• 2004

The purpose of this study was to classify the household financial strategies and find out variables affecting the type of the household financial strategies. The data of 3994 households from Korean Labor and Income Panel Study(1999-2000) were used. The major findings were as follows: (1) the household financial strategies were Residual Saver Type(44.6%), Unformal Institute Saver Type(13.3%), Financial asset Saver Type(16.7%), Real estate Saver Type(13.4%) and Diversities(12.0%). (2) The household financial strategy types were changed rapidly during short term. (3) In 3994 households, the variables which influence on the change of the household financial strategies were education, job, numbers of children, place of residence, home ownership. Similarly, in each type, the change of household financial strategies was significantly different according to the household characteristics variables.