• 한국수학사학회지
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• 제17권4호
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• pp.133-152
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• 2004

18세기 오일러와 베르누이에 의해 최초로 등장했던 고유치의 개념 발생의 장은 탄성을 가진 물체의 변위에 관련된 미분 방정식의 풀이 해법 문제였다. 역사 발생적 원리에 따라 용수철에 매달린 물체의 변위 문제를 모델로 개혁 미분 방정식 수업에 기반한 학습자의 고유치 고유벡터의 효과적인 개념 발생의 가능성을 논한다. 소그룹 토의 학습으로 진행된 교수 학습 모델의 실제 적용 과정과 방법, 효과적인 인지변화에 대한 교수학적 요인과 학생들의 수학에 대한 정의적 태도의 변화를 진술한다.

• 디지털산업정보학회논문지
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• 제15권4호
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• pp.131-136
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• 2019

As the NCS(National Competency Standards) classification system continued to be developed and supplemented, NCS became widespread. Qualifications were redesigned to actively reflect industry demands, reduce the burden of redundant acquisition of unnecessary qualifications, and to evaluate objective capacities of the workforce. In addition to the learning modules to be developed in the future, previously developed NCS-based learning modules and lectures should be reorganized based on the new qualification design. In this paper, the Java programming subject designed based on NCS was redesigned according to SW new qualification design. Since the redesigned Java programming subjects consider the qualification design direction or qualification roadmap, not only can they be recognized as a test subject in qualification assessment through course evaluation, but also can be used as individual qualification data.

• 대한치과의사협회지
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• 제54권9호
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• pp.712-728
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• 2016

These days, the clinical course of dental imaging sector has done a lot of implant-related imaging courses, including cone beam CT. In contrast, the general image reading course is not given a lot of opportunities to learn. Therefore, it is imperative that we talk about the general image interpretation that can be read easily applied in a dental clinic. When we see a strange radiographic finding of our patient in the dental clinic, we should first check whether the radiographic finding is a normal finding or a morbidity. If the finding is diagnosed as a morbidity, you should make plans for the appropriate therapy. The most important step is classification between normal state and morbidity. Some lesions may occur without any clinical symptoms. Therefore, we should read all the parts of radiographs, even the patient does not have clinical symptoms.

• 한국정보시스템학회지:정보시스템연구
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• 제26권4호
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• pp.17-37
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• 2017

Purpose Customer Loyalty is the most important factor of customer relationship management (CRM). Especially in retailing industry, where customers have many options of where to spend their money. Classifying loyal customers through customers' data can help retailing companies build more efficient marketing strategies and gain competitive advantages. This study aims to construct classification models of distinguishing the loyal customers within a Korean retailing company using data mining techniques with R language. Design/methodology/approach In order to classify retailing customers, we used combination of support vector machines (SVMs) and other classification algorithms of machine learning (ML) with the support of recursive feature elimination (RFE). In particular, we first clean the dataset to remove outlier and impute the missing value. Then we used a RFE framework for electing most significant predictors. Finally, we construct models with classification algorithms, tune the best parameters and compare the performances among them. Findings The results reveal that ML classification techniques can work well with CRM data in Korean retailing industry. Moreover, customer loyalty is impacted by not only unique factor such as net promoter score but also other purchase habits such as expensive goods preferring or multi-branch visiting and so on. We also prove that with retailing customer's dataset the model constructed by SVMs algorithm has given better performance than others. We expect that the models in this study can be used by other retailing companies to classify their customers, then they can focus on giving services to these potential vip group. We also hope that the results of this ML algorithm using R language could be useful to other researchers for selecting appropriate ML algorithms.

• 보험의학회지
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• 제32권1호
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• pp.21-27
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• 2013

In case of neoplasm claims, it is important to make a decision of differentiating malignant and benign. In Korean insurance market, there are many insurance products that cover cancer. In the insurance claims adjustment, differentiation between malignant and benign is according to histologic findings. However there are many neoplasms of bad clinical course in spite of benign histopathologic classification. In this article; astrocytoma, thymoma, gastrointestinal stromal tumor, colonic intramucosal carcinoma, gastric high grade adenoma/dysplasia, carcinoid tumor, MALT lymphoma, revision of Korean Classification of Disease-6th edition, and bladder tumors are reviewed in terms of differentiation between malignant and benign in the insurance claims. It may be helpful for claims staff to review important neoplasms in terms of differentiation between malignant and benign.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2001년도 하계종합학술대회 논문집(5)
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• pp.61-64
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• 2001

This paper describes a basic study for the classification of cognitive mental states as a basic research of a human-computer interface technique. To recognize the mental states, we obtained 22 subjects’brain waves in course of two types of experiments. One of the experiments is to choose an answer among yes, no or reject buttons, to underlying questions and the other is to select an icon displayed in a monitor screen. After acquiring the brain wave signals, we construct a feature set with the percent power increase for a given segment with respect to that of the reference period. The linear discriminative algorithm is used to classify the cognitive yes/no mental states.

• 한국정보시스템학회지:정보시스템연구
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• 제14권3호
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• pp.82-88
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• 2005

Much information has been hierarchically organized to facilitate information browsing, retrieval, and dissemination. In practice, much information may be entered at any time, but only a small subset of the information may be classified into some categories in a hierarchy. Therefore, achieving document filtering (DF) in the course of document classification (DC) is an essential basis to develop an information center, which classifies suitable documents into suitable categories, reducing information overload while facilitating information sharing. In this paper, we present a technique ICenter, which conducts DF and DC by recognizing the context of discussion (COD) of each document and category. Experiments on real-world data show that, through COD recognition, the performance of ICenter is significantly better. The results are of theoretical and practical significance. ICenter may server as an essential basis to develop an information center for a user community, which shares and organizes a hierarchy of textual information.

• 한국수학사학회지
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• 제18권1호
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• pp.49-66
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• 2005

과거에 계산 도구의 주종을 이루었던 수판과 산대의 역사를 간략하게 알아본다. 그리고 산대셈과 수판셈의 원리와 방법을 곱셈과 나눗셈을 중심으로 구체적인 예를 통해 소개하고 비교한다. 이를 통해 수판셈의 원리는 산대셈으로부터 전승되었음을 확인하고, 수판의 교육적 가치를 모색한다.

• 대한수학회논문집
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• 제33권1호
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• pp.325-335
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• 2018

We prove every oriented compact cyclic 3-orbifold has a contact structure. There is another proof in the web by Daniel Herr in his uploaded thesis which depends on open book decompositions, ours is independent of that. We define overtwisted contact structures, tight contact structures and Lutz twist on oriented compact cyclic 3-orbifolds. We show that every contact structure in an oriented compact cyclic 3-orbifold contactified by our method is homotopic to an overtwisted structure with the overtwisted disc intersecting the singular locus of the orbifolds. In course of proving the above results we prove a classification result for compact oriented cyclic-3 orbifolds which has not been seen by us in literature before.

• 대한원격탐사학회지
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• 제38권4호
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• pp.435-446
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• 2022

Identifying ship types is an important process to prevent illegal activities on territorial waters and assess marine traffic of Vessel Traffic Services Officer (VTSO). However, the Terrestrial Automatic Identification System (T-AIS) collected at the ground station has over 50% of vessels that do not contain the ship type information. Therefore, this study proposes a method of identifying ship types through the Random Forest Classifier (RFC) from dynamic and static data of AIS and V-Pass for one year and the Ulsan waters. With the hypothesis that six features, the speed, course, length, breadth, time, and location, enable to estimate of the ship type, four classification models were generated depending on length or breadth information since 81.9% of ships fully contain the two information. The accuracy were average 96.4% and 77.4% in the presence and absence of size information. The result shows that the proposed method is adaptable to identifying ship types.