• Journal of the korean academy of Pediatric Dentistry
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• v.38 no.2
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• pp.202-209
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• 2011

Current treatment concept of dental caries has been changed, because it has been proved that it is a preventable disease. The philosophy has been changed from purely restorative treatment to preventive caries control. Therefore the methods or criteria of oral examination has been changed. The clinician have to detect not only cavitation, but also the lesion of non-cavitation stage. International Caries Detection and Assessment System II (ICDAS II) was developed recently, which is a new criteria of classification of dental caries. This system was based on the current concept of prevention, early detection and patient-centered management of caries. Therefore this philosophy is in accord with the perspective of pediatric dentistry. The purpose of this article is to introduce this system for oral examination of children.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.4
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• pp.817-827
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• 2015

In this modern society, people are having a close relationship with smartphone. This makes easier for hackers to gain the user's information by installing the malware in the user's smartphone without the user's authority. This kind of action are threats to the user's privacy. The malware characteristics are different to the general applications. It requires the user's authority. In this paper, we proposed a new classification method of user requirements method by each application using the Principle Component Analysis(PCA) and Probabilistic K-Nearest Neighbor(PKNN) methods. The combination of those method outputs the improved result to classify between malware and general applications. By using the K-fold Cross Validation, the measurement precision of PKNN is improved compare to the previous K-Nearest Neighbor(KNN). The classification which difficult to solve by KNN also can be solve by PKNN with optimizing the discovering the parameter k and ${\beta}$. Also the sample that has being use in this experiment is based on the Contagio.

• Journal of the Korean Society for information Management
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• v.36 no.4
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• pp.83-105
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• 2019

This study aims to suggest an effective method for the automatic classification of keywords with similar patterns by calculating pattern similarity of temporal data. For this, large scale news on the Web were collected and time series data composed of 120 time segments were built. To make training data set for the performance test of the proposed model, 440 representative keywords were manually classified according to 8 types of trend. This study introduces a Dynamic Time Warping(DTW) method which have been commonly used in the field of time series analytics, and proposes an application model, MA-DTW based on a Moving Average(MA) method which gives a good explanation on a tendency of trend curve. As a result of the automatic classification by a k-Nearest Neighbor(kNN) algorithm, Euclidean Distance(ED) and DTW showed 48.2% and 66.6% of maximum micro-averaged F1 score respectively, whereas the proposed model represented 74.3% of the best micro-averaged F1 score. In all respect of the comprehensive experiments, the suggested model outperformed the methods of ED and DTW.

• Journal of the Korea Convergence Society
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• v.11 no.11
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• pp.103-114
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• 2020

This paper's research objective is to test educational content with different dimensions of knowledge during a graphic basic design course, while also proposing teaching plans and opinions for courses in flipped classrooms as well as enhancing educational efficiency. It categorizes educational content of courses based on the dimensions of knowledge in the learning objectives of Bloom's taxonomy. 120 students are divided into four experimental groups to respectively under go flipped classroom learning by using different dimensions of knowledge involved in course content. Course pretests and post tests are used to obtain and analyze experimental data. Among this knowledge, factual and conceptual knowledge obtained during extra curricular independent learning as well as programmed and meta-cognitive knowledge obtained during in-class learning from a flipped classroom can stimulate student's learning initiative and also enhance learning efficiency. According to research results and student feedback, this paper will propose targeted categorization methods for course content and also suggest educational strategies for these courses' flipped classroom model.

• Journal of Digital Contents Society
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• v.13 no.3
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• pp.317-324
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• 2012

Recently, coordination task of similarity between national R&D programs is emphasized on view from the R&D investment efficiency. But the previous similarity search method like text-based similarity search which using keyword of R&D projects has reached the limit due to deviation of document's quality. For the solve the limitations of text-based similarity search using the keyword extraction, in this study, utilization of R&D project's technical classification will be discussed as a new similarity search method when analyzed of similarity between national R&D programs. To this end, extracts the Science and Technology Standard Classification of R & D projects which are collected when national R&D Survey & analysis, and creates peculiar vector model of each R&D programs. Verify a reliability of this study by calculate the cosine-based and Euclidean distance-based similarity and compare with calculated the text-based similarity.

• Korean Journal of Construction Engineering and Management
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• v.14 no.3
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• pp.88-96
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• 2013

Recent proliferation of building information modeling (BIM) has actively stimulated integrated utilization of geometric (graphic) and non-geometric (non-graphic) data. Nevertheless, physically and logically, linking and maintaining these two different types of data in an integrated manner requires enormous overhead efforts for practical implementation. In order to address this problem, this paper proposes a concept and structure of the object breakdown structure (OBS) that facilitates advanced BIM implementations in an automated and effective manner. Proposed OBS numbering system has secure rules for organizing graphic objects in full considerations of effectively integrating with non-geometric data (e.g. cost and schedule). It also removes repetitive linking process caused by design changes or modifications. The result of applying this concept to a housing project revealed that only 120 definitions controled over 6,000 graphic objects for full integration with cost and schedule functions.

• Journal of The Geomorphological Association of Korea
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• v.21 no.4
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• pp.85-96
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• 2014

A waterfall is a channel unit with steep bedrock. No strict criteria for height, water volume, gradient to define waterfalls exist in Korea. The goal of our study is to classify waterfalls based on morphological forms which are the outcomes of developmental processes. The genesis of waterfall depends upon erosional properties of waterfall. The height, gradient, bedrock strength and stream power of waterfalls are regarded as the main factors, by which waterfalls can be classified. We find out that the most important factor for the development of waterfalls is joint system. Development of joint system varies depending on bedrocks. Flow directions and erosional types are decided by the density and direction of joint system in the bedrock, which also decide the height and gradient of stream bed. Joint type decides the gradients of the bed, gradient and height of waterfalls, therefore, decides morphological forms.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.563-567
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• 2015

우리나라 하천관리의 패러다임은 1990년대 이후 기존의 치수 및 이수능력을 고려함과 동시에 하천환경의 보전 및 복원을 새로운 목표로 설정한 자연친화적 방식으로 변화되었다. 하천법령 및 제도적 측면에서도 수자원 장기종합계획 및 유역 종합 치수계획은 하천의 환경보전 및 다목적 이용계획을 포함하도록 규정하고 있으며, 국내 하천법에 따르면 하천기본계획 수립 또한 자연친화적 하천조성 및 이와 관련된 보전지구 지정 등을 포함하도록 규정하고 있다. 하천설계기준, 자연 친화적 하천관리에 관한 통합지침, 또는 수자원 장기종합계획에서 적용하고 있는 하천환경조사 및 평가지표는 서로 다를 뿐만 아니라 과학적인 근거가 명확하지 않는 등 국가차원의 표준화가 이루어지지 못한 상태라 할 수 있다. 1990년대 이후 미국, 독일, 영국, 호주 등 선진국들은 하천환경 복원사업의 추진과정에서 복원사업의 타당성 제고 및 성공적인 사업수행을 위하여 그들 국가의 하천특성에 적합한 하천환경 평가 체계를 구축한 바 있으며, 이들 평가체계는 새로운 과학적 지식과 기술의 축적에 힘입어 지속적으로 발전되고 있다. Fujita의 유형화(Segment 분류)법에 의하면, 하천구간(Segment)은 하상경사, 하상재료, 식생, 생태 등이 통계적으로 동질인 하천 구간으로서, 하도 특성과 하천생태계 공간을 구분하는 단위이다. 자연하천에서 동일한 경사를 갖는 하천구간은 하상재료, 소류력, 저수로 폭, 수심 등이 대체로 동일한 값을 나타내고 있으며, 하도 특성을 지배하는 주요 인자로 각 하천의 평균 연최대유량, 하상재료의 대표입경, 하상경사 등을 설정하고 있다. 본 연구에서는 하천구간을 유형화하는 기준을 하상경사로 적용하여 평가단위를 분류하였으며, 평가체계는 미국의 USEPA를 한국형 하천환경에 맞도록 수정보완 하였다. 특히 미국의 USEPA의 지표 중 하안영역의 식생피복, 하반림 등은 생물분야 식생영역과 상충되어 제외하고 우리나라 특성에 적합한 하천횡단형상, 하천횡단 구조물 등의 평가기준을 재정립하여 내성천에 평가적용 분석하였다. 하천환경의 수리 및 하도 특성 평가기준 개발에 따라 평가체계의 개념적 틀을 토대로 통합적이고 표준화된 한국형 하천평가기준 개발을 위한 방법론을 정립하고, 나아가 하천환경의 지속가능성을 전제로 한 하천복원사업의 장 단기적 성공 여부를 평가할 수 있는 실무지침의 과학적 근거를 제시하고자 한다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.4
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• pp.169-174
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• 2019

In this study, I use surveillance data collection and data mining, clustered by clustering method, and use supervised learning to judge similarity. I aim to use feature extraction algorithms and supervised learning to analyze the suitability of the correlations of personality. After conducting the questionnaire survey, the researchers refine the collected data based on the questionnaire, classify the data sets through the clustering techniques of WEKA, an open source data mining tool, and judge similarity using supervised learning. I then use feature extraction algorithms and supervised learning to determine the suitability of the results for personality. As a result, it was found that the highest degree of similarity classification was obtained by EM classification and supervised learning by Naïve Bayes. The results of feature classification and supervised learning were found to be useful for judging fitness. I found that the accuracy of each Big-5 personality was changed according to the addition and deletion of the items, and analyzed the differences for each personality.

• Journal of Broadcast Engineering
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• v.24 no.1
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• pp.67-76
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• 2019

In this paper, we propose an efficient object classification method based on semantic segmentation for multi-labeled image data. In addition to various pixel unit information and processing techniques such as color information, contour, contrast, and saturation included in image data, a detailed region in which each object is located is extracted as a meaningful unit and the experiment is conducted to reflect the result in the inference. We use a neural network that has been proven to perform well in image classification to understand which object is located where image data containing various class objects are located. Based on these researches, we aim to provide artificial intelligence services that can classify real-time detailed areas of complex images containing various objects in the future.