• Journal of Gifted/Talented Education
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• v.20 no.3
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• pp.1027-1037
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• 2010

Comparing to the other subject, the relationship among physics contents is strong from the perspective of knowledge order as grades go up. That is, The things already that students learned, are learning and will learn are closed related from grade to grade. We expect students to be proactive and creative in studying physics, which is the goal of 21th century, analyzing their knowledge structure based on the knowledge order through assessment. Especially, using computer system, we provide students with substantial feedback for the assessment as well as objective validity is increased along with speedy and exact process in a bid to help students' mathematical understanding grow. This paper seeks to analyze the data from assessment applying knowledge spaces of the scientifical gifted in the force and the motion concept to applicate on teaching method.

• Restorative Dentistry and Endodontics
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• v.21 no.2
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• pp.664-676
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• 1996

테트라싸이클린에 의한 치아 변색은 심미성을 고려한 임상 치료시 커다란 난제로 남아 있다. 본 연구는 백서 치아에 테트라싸이클린을 주입하여 야기되는 색상과 구조적인 변화도를 측정하여 향후 연구에 기초자료를 제공하기 위해 시행되었다. 24 마리의 백서를 각기 8 마리씩 3 군으로 분류하여 대조군은 정상적인 사육을 식염수군은 TC군과 동량의 식염수를 주사하였으며 TC군은 12 ml에 용해시킨 60 mg의 테트라싸이클린을 복강내로 2 주간 주입하였다. 최종 주입후 1 주간 정상 사육한 다음 cervical dislocation법에 의해 희생시켜 시편을 채득한 후 각 치아를 횡단하여 실물현미경과 FlexCam을 이용하여 컴퓨터에 영상을 저장한 다음 색 변화량을 Adobe Photoshop으로 측정하였으며 구조변화는 주사전자 현미경을 이용하였다. 치아색 변화량의 유의성 검정은 ANOVA와 Scheffe test를 이용하였으며 본 실험 결과는 다음과 같다. 1. 각 군의 $a^*$ 수치는 대조군 -6.12 (1.18), 식염수군 -8.00 (1.33), TC군 -18.56 (2.52)로 나타났으며 $b^*$ 수치는 대조군 1.12 (2.13), 식염수군 1.62 (1.45), TC군 28.67 (5.18)을 보였다. 즉 테트라싸이클린에 의해 $a^*$와 $b^*$의 수치가 유의성있게 (p<0.01) 초록색과 노란색 방향으로 변화하였다. 2. 테트라싸이클린에 의해 치경부 법랑질 외면이 검게 변색되었으며 울퉁불퉁한 양태로 변화되었다. 그러나 법랑소주의 형태, 방향등은 차이를 보이지 않았다. 3. 각 군간 상아세관의 수, 방향, 크기등이 차이가 없었다. 치수측에서의 관찰결과 대조군과 식염수군에서는 상아세관들의 입구가 크고 명확하게 보인 반면 TC군에서는 입구가 좁고 부분적으로 막힌 양태도 관찰되었다.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.11
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• pp.403-408
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• 2014

In the Internet of Things(IoT) era, many of the things or objects that enclose our environments are able to associate with those things on the Internet. To construct IoT systems, it needs to consider a component for acquiring and aggregating of sensory data via things with sensors and instruments, which is connected by diverse networks, in IoT environment. An IoT system is intrinsically distributed in a variety of ways. In addition, to manage an IoT system efficiently, interoperability is needed to meet requirements while the IoT system is designed to deliver data among its applications. In this paper, a reference architecture based on asynchronous messaging is defined and used for designing an IoT system. To apply the architecture, we discuss how to manage data streams with real-time characteristics and make a prototype based on pipe-and-filter to produce and consume them by a pub/sub messaging system NaradaBrokering.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.6
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• pp.1228-1234
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• 2007

In this paper, we develop the thinking extension education program for the gifted students of information and prove the validity and effectiveness of the proposed model by presenting the Tic-tac-toe problem as the practical example of the information-gifted students. This model consists of four phases which has the game tree as data structure and the search of game lee as control structure. And the search of game tree becomes the basis of the thinking extension education program. This model gives the help for students to learn representing the problem as tree structure and solving the problem of tree structure using the search method of game tree. The internal ability of the information-gifted for thinking extension of this education program contains the fluency, perceptiveness, originality, power of concentration, imaginative power, analyzing skills, pattern recognition, space sense, synthesizing, problem-solving.

• Journal of agriculture & life science
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• v.44 no.3
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• pp.79-87
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• 2010

In this study, rainwater resources facilities were constructed on the slope as a feasibility study. It is considered that rainwater resources facilities were constructed with the selected cross-section, and the stability analyses in cases of normal and abnormal condition were conducted as using the computer model. As a result of the stability analysis, the stability of the selected cross-section in the case of normal operation was lower than in the case of abnormal condition. Therefore, In order to design and maintain the rainwater resources facilities, it is likely that soil surveys are certainly carried out before the decision of the specification of rainwater resources facilities.

• Journal of Korean Society of Archives and Records Management
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• v.3 no.2
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• pp.34-51
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• 2003

The purposes of this study are to categorize the archival body of knowledge based on the analysis of two guidelines and websites of 10 archival graduate programs in the United States, and to make suggestions for the development of archival education in Korea. Basic knowledge, core knowledge, complementary knowledge, practical knowledge, and research knowledge are found as components of the archival body of knowledge. The basic knowledge is the ability to understand general circumstances related to records and archives. The core one is to master the required competence as archivists. The complementary one is to understand other disciplinary backgrounds and their various research methods. The practical one is to be obtained from field experiences and the research one is to make a scholastic contribution through a deep research process. Curriculum development for preservation, electronic records management, use of computer technologies, archival services and advocacy, more interdisciplinary courses and internship programs are suggested as important factors for the future archival education. And cooperative research and appointment of more faculty members are also suggested. Finally, the development of guideline for Korean archival graduate programs are strongly suggested.

• Journal of Digital Convergence
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• v.19 no.10
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• pp.143-149
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• 2021

As the need to establish a big data system for rapid provision of big data and efficient management of resources has emerged due to rapid entry into the hyper-connected intelligence information society, public institutions are pushing to establish a big data system. Therefore, this study analyzed and combined the success factors of big data-related studies and the specific aspects of big data in public institutions based on the measurement of environmental factors for establishing an integrated information system for higher education institutions. In addition, 19 measurement items reflecting big data characteristics were derived from big data experts using brainstorming and Delphi methods, and a plan to successfully apply them to public institutions that want to build big data systems was proposed. We hope that this research results will be used as a foundation for the successful establishment of big data systems in public institutions.

• Journal of the Korea Convergence Society
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• v.12 no.9
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• pp.39-47
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• 2021

This study was conducted to propose a product planning prediction model using logistic regression algorithm to predict seasonal factors and rapidly changing product trends. First, we collected unstructured data of consumers in portal sites and online markets using web crawling, and analyzed meaningful information about products through preprocessing for transformation of standardized data. The datasets of 11,200 were analyzed by Logistic Regression to analyze consumer satisfaction, frequency analysis, and advantages and disadvantages of products. The result of analysis showed that the satisfaction of consumers was 92% and the defective issues of products were confirmed through frequency analysis. The results of analysis on the use satisfaction, system efficiency, and system effectiveness items of the developed product planning prediction program showed that the satisfaction was high. Defective issues are very meaningful data in that they provide information necessary for quickly recognizing the current problem of products and establishing improvement strategies.

• Journal of the Korea Convergence Society
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• v.12 no.9
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• pp.21-30
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• 2021

Unlike behaviors that are generally known, information regarding unspecific behaviors is insufficient. For an education or guidance regarding the unspecific behaviors, collection and management of data regarding the unspecific behaviors of special-needs students are needed. In this paper, a consultation management model based on behavior classification of special-needs students using machine learning is proposed. It collects data by photographing the behavior of special students in real time, analyzes the behavior pattern, composes a data set, and trains it in the suggestion system. It is possible to improve the accuracy by comparing the behavior of special students photographed later into the suggestion system and analyzing the results by comparing it with the existing data again. The test has been performed by arbitrarily applying unspecific behaviors that are not stored in the database, and the forecast model has accurately classified and grouped the input data. Also, it has been verified that it is possible to accurately distinguish and classify the behaviors through the feature data of the behaviors even if there are some errors in the input process.

• Smart Media Journal
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• v.7 no.4
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• pp.17-23
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• 2018

We proposed a LSTM-based RNN model that can effectively perform the automatic spacing characteristics. For those long or noisy sentences which are known to be difficult to handle within Neural Network Learning, we defined a proper input data format and decoding data format, and added dropout, bidirectional multi-layer LSTM, layer normalization, and attention mechanism to improve the performance. Despite of the fact that Sejong corpus contains some spacing errors, a noise-robust learning model developed in this study with no overfitting through a dropout method helped training and returned meaningful results of Korean word spacing and its patterns. The experimental results showed that the performance of LSTM sequence-to-sequence model is 0.94 in F1-measure, which is better than the rule-based deep-learning method of GRU-CRF.