• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.11a
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• pp.179-182
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• 2006

현재 감정을 인식할 수 있는 방법으로는 음성, 뇌파, 심박, 표정 등 많은 방법들이 존재한다. 본 논문은 이러한 방법 중 음성 신호를 이용한 방법으로써 특징들은 크게 피치, 에너지, 포만트 3가지 특징 점을 고려하였으며 이렇게 다양한 특징들을 사용하는 이유는 아직 획기적인 특징점이 정립되지 않았기 때문이며 이러한 선택의 문제를 해결하기 위해 본 논문에서는 특징 선택 방법 중 Multi Feature Selection(MFS) 방법을 사용하였으며 학습 알고리즘은 Self Organizing Map 알고리즘을 이용하여 음성 신호의 감정 특징 패턴을 분류하는 방법을 제안한다.

• The Journal of the Korea Contents Association
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• v.10 no.3
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• pp.72-79
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• 2010

A EAARS(Electronic Attendance-Absence Recording System) is the important LSS(Learning Support System) for blending a on-line learning in the face-to-face classroom. However, the EAARS based on the smart card can not identify a real owner of the checked card. Therefore, we develop the CS(Client-Sever) system that manages the attendance-absence checking automatically, which is used the self-organizing neural network for the face recognition. A client system creates the ID file by extracting the face feature, a server system analyzes the ID file sent from client system, and performs a student identification by using the Recognized weight file saved in Database. As a result, The proposed CS EAARS shows the 92% efficiency in the CS environment that includes the various face image database of the real classroom.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.24 no.2
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• pp.141-148
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• 2011

This study presents the optimal grouping technique of columns which groups together columns of similar shortening trends to improve the efficiency of column shortening compensation. Here, Kohonen's self-organizing feature map which can classify patterns of input data by itself with unsupervised learning was used as the optimal grouping algorithm. The Kohonen network applied in this study is composed of two input neurons and variable output neurons, here the number of output neuron is equal to the column groups to be classified. In input neurons the normalized mean and standard deviation of shortening of each columns are inputted and in the output neurons the classified column groups are presented. The applicability of the proposed algorithm was evaluated by applying it to the two buildings where column shortening analyses had already been performed. The proposed algorithm was able to classify columns with similar shortening trends as one group, and from this we were able to ascertain the field-applicability of the proposed algorithm as the optimal grouping of column shortening.

• Journal of the Korea Convergence Society
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• v.12 no.12
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• pp.49-57
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• 2021

With the advent of the era of the fourth industry, more and more scientific techniques are being used to solve decision-making problems. In particular, big data analysis technology is developing as it becomes easier to collect numerical data. Therefore, in this study, in order to overcome the limitations of qualitatively analyzing investment trends, the association of various products was analyzed using associated analysis techniques. For the experiment, two experimental periods were divided based on the COVID-19 economic crisis, and sales information from individuals, institutions, and foreign investors was collected, and related analysis algorithms were implemented through r software. As a result of the experiment, institutions and foreigners recently invested in the KOSPI and KOSDAQ markets and bought futures and products such as ETF. Individuals purchased ETN and ETF products together, which is presumed to be the result of the recent great interest in sector investment. In addition, after COVID-19, all investors tended to be passive in investing in high-risk products of futures and options. This paper is thought to be a useful reference for product sales and product design in the financial field.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.07a
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• pp.315-316
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• 2019

전투복, 군용 천막 등에 사용되는 위장무늬는 군 작전 수행 시 주변 환경의 색상, 패턴을 모사하여 개인병사 및 무기체계의 위장 기능을 극대화하고, 이를 통해 아군의 생명과 시설피해를 최소화하기 위한 목적으로 사용된다. 특히 최근 들어 군의 작전환경과 임무가 복잡하고 다양해짐에 따라, 작전환경에 대한 데이터의 취득 및 정량적 분석을 통해 전장 환경에 최적화된 위장무늬 패턴 및 색상 추출에 대한 연구의 필요성이 증대되고 있다. 본 논문에서는 한반도 자연환경 영상에 대한 자기 조직화 지도(SOM, Self-organizing Map) 기반의 한반도 자연환경 대표 색상 군집화 연구 방법에 대해 서술한다. 이를 위해 한반도 내 위도를 고려한 장소에서 시간별, 계절별 자연환경 영상 수집을 진행하며, 수집된 영상 내 다수의 화소의 군집화를 위해 2차원 SOM을 활용한다. 영상 내 각 화소의 색상 값에 대한 SOM의 학습 시, RGB공간상의 색차/색상 인지 왜곡을 피하기 위하여 CIEDE2000 색차 식을 통해 군집화를 진행한다. 실험결과에서는 온라인상으로 수집한 여름 및 가을철 대표 색상 군집화 결과와, 현재까지 수집된 계절별 자연환경 사진 내 6억 7648개 화소에 대한 대표 색상 군집화 결과를 보여준다.

• Communications of Mathematical Education
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• v.25 no.2
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• pp.473-495
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• 2011

Across the secondary school, students deal with the algebraic conditions like as identity, inverse, commutative law, associative law and distributive law. The algebraic structures, group, ring and field, are determined by these algebraic conditions. But the conditioning of these algebraic structures are not mentioned at all, as well as the meaning of the algebraic structures. Thus, students is likely to be considered the algebraic conditions as productions from the number sets. In this study, we systematize didactically the meanings of algebraic conditions and algebraic structures, considering connections between the number systems and the solutions of the equation. Didactically systematizing is to construct the model for student's natural mental activity, that is, to construct the stream of experience through which students are considered mathematical concepts as productions from necessities and high probability. For this purpose, we develop the program for the gifted, which its objective is to teach the meanings of the number system and to grasp the algebraic structure conceptually that is guaranteed to solve equations. And we verify the effectiveness of this developed program using didactical experiment. Moreover, the program can be used in ordinary students by replacement the term 'algebraic structure' with the term such as identity, inverse, commutative law, associative law and distributive law, to teach their meaning.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.6
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• pp.839-850
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• 2018

The flood damage in urban areas due to torrential rain is increasing with urbanization. For this reason, accurate and rapid flooding forecasting and expected inundation maps are needed. Predicting the extent of flooding for certain rainfalls is a very important issue in preparing flood in advance. Recently, government agencies are trying to provide expected inundation maps to the public. However, there is a lack of quantifying the extent of inundation caused by a particular rainfall scenario and the real-time prediction method for flood extent within a short time. Therefore the real-time prediction of flood extent is needed based on rainfall-runoff-inundation analysis. One/two dimensional model are continued to analyize drainage network, manhole overflow and inundation propagation by rainfall condition. By applying the various rainfall scenarios considering rainfall duration/distribution and return periods, the inundation volume and depth can be estimated and stored on a database. The Rainfall-Duration-Flooding Quantity (RDF) relationship curve based on the hydraulic analysis results and the Self-Organizing Map (SOM) that conducts unsupervised learning are applied to predict flooded area with particular rainfall condition. The validity of the proposed methodology was examined by comparing the results of the expected flood map with the 2-dimensional hydraulic model. Based on the result of the study, it is judged that this methodology will be useful to provide an unknown flood map according to medium-sized rainfall or frequency scenario. Furthermore, it will be used as a fundamental data for flood forecast by establishing the RDF curve which the relationship of rainfall-outflow-flood is considered and the database of expected inundation maps.

• School Mathematics
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• v.6 no.4
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• pp.325-344
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• 2004

This study was carried out to investigate effects of the mindmap note-taking for the formation of the mathematical concepts structure and the matjematical creativity. Two classes were randomly chosen for this study from the third grade students of a middle school located in a medium size city. Thirty one lecture hours of the mindmap note-taking on the quadratic equation and functions were administered to the experimental class of 41 students, while same lecture hours of the ordinary instruction on the same contents were administered to the control class of 40 students. It was shown from this experiment that there ware significant evidences of improvement both in the formation of students' mathematical concepts structure and mathematical creativity through the mindmap note-taking lecture. Hence, the mindmap note-taking lecture is suggested for the improvement in the formation of student's mathematical concepts structure and mathematical creativity.

• Korean Journal of Cognitive Science
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• v.11 no.1
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• pp.47-65
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• 2000

Categorization systems of homepages in search engines are likely to be constructed considering system's efficiency only but not user-centered. This study I investigated user's mental model of superordinate and subordinate categories using category terms of major Korean search engines. From this result, we constructed two kinds of categorization system; redundant system and singular system. In the redundant system, for example, a subordinate category can belong to a number of superordinate categories, but in the singular system to only one superordinate category Three prototype categorization systems, with 'Simmani', were designed and search performances of each system were observed repetitively Overall results, with frequency of correct a answers, number of steps and time taken in solution taken into account, showed the redundant system was superior to the other two systems. This indicates that categorization search could be improved with appropriate categorizaton system. However. l in recognition test score in singular system was the best, which indicates that search performance and recognition memory of categorization reveal different aspects of categorization system learning. Issues of category organization. ways of interface, prior knowledge, exploratory learning, and application areas are discussed further.

• School Mathematics
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• v.15 no.4
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• pp.785-799
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• 2013

The researchers developed the teaching-learning materials for 9th grade mathematically gifted students in terms of the hypothesis that the students would have opportunity for problem solving and develop various mathematical thinking through the mathematical modeling lessons. The researchers analyzed what mathematical thinking abilities were shown on each stage of modeling process through the application of the materials. Organization of information ability appears in the real-world exploratory stage. Intuition insight ability, spatialization/visualization ability, mathematical reasoning ability and reflective thinking ability appears in the pre-mathematical model development stage. Mathematical abstraction ability, spatialization/visualization ability, mathematical reasoning ability and reflective thinking ability appears in the mathematical model development stage. Generalization and application ability and reflective thinking ability appears in the model application stage. The developed modeling assignments have provided the opportunities for mathematically-gifted students' mathematical thinking ability to develop and expand.