• 정보교육학회논문지
• /
• 제21권3호
• /
• pp.297-307
• /
• 2017

본 연구의 목적은 초중등학생 대상 알고리즘 교육을 위한 알고리즘 분류체계를 제안하는 것이다. 연구자는 알고리즘의 구성요소를 정의하고, 분석합성식 방법으로 알고리즘 분류체계를 표현하였다. 연구의 내용은 다음과 같다. 첫째, 분류의 목적과 분류의 종류에 대한 이론적인 탐색을 실시하였다. 둘째, 기존에 제안된 알고리즘 내용에 대한 분류체계의 내용과 그 한계에 대해 살펴보았다. 이와 더불어 알고리즘 교육 연구에서 사용되었던 알고리즘 교육 내용 및 선정 기준에 대해 살펴보았다. 셋째, 알고리즘의 분류를 위해 알고리즘 구성요소를 NRC에서 제시한 핵심 아이디어와 관통 개념을 사용하여 재정의하였다. 그리고 알고리즘 관통 개념을 디자인 구조와 자료구조로 세분화하여 그 내용을 제시하였으며, 이 내용을 분석합성식 분류체계를 사용하여 표현하였다. 마지막으로 전문가 집단의 검토를 통해 제안한 내용에 대한 타당도를 검증하였다. 알고리즘 분류체계에 대한 연구는 알고리즘 교육에 있어 내용 선정 및 교육 방법에 많은 시사점을 제공할 것으로 기대한다.

• Journal of Mechanical Science and Technology
• /
• 제18권11호
• /
• pp.1923-1931
• /
• 2004

Manufacturing of complex surface plates in stern and stem is a major factor in cost of a preliminary ship design by computing process. If these hull plate parts are effectively classified, it helps to compute the processing cost and find the way to cut-down the processing cost. This paper presents a new method to classify surface plates effectively in the preliminary ship design using neural network. A neural-network-based ship hull plate classification program was developed and tested for the automatic classification of ship design. The input variables are regarded as Gaussian curvature distributions on the plate. Various applicable rules of network topology are applied in the ship design. In automation of hull plate classification, two different numbers of input variables are used. By observing the results of the proposed method, the effectiveness of the proposed method is discussed. As a result, high prediction rate was achieved in the ship design. Accordingly, to the initial design stage, the ship hull plate classification program can be used to predict the ship production cost. And the proposed method will contribute to reduce the production cost of ship.

• 한국생활과학회지
• /
• 제21권6호
• /
• pp.1129-1144
• /
• 2012

The purpose of this study was to investigate the gender difference in adolescent's problem behavior and depression, and The main aim of this study was to develop a fundamental web design to provide information content that would be easy for average consumers to understand based on the classification of information related to food safety. Based on the information obtained through in-depth interviews, the researchers developed an information classification system that meets the needs of consumers, and which serve as a basic framework for a homepage for a food safety information center. A total of 62 food items in 6 areas were selected based on reports of food safety related events occurring between 1998-2009 (KFDA 2008). The classification system of risk factors such as chemical risk factors and biological risk factors were categorized. The specific features of the information content for individual food items provided for classification based on evaluation by professional food scientists and the importance of risk factors. By providing a consumer participation section and company participation section, it was anticipated that the food safety information center would be able to act as a moderator for food safety information communication among consumers, the food industry, and the government. Based on the development of a classification system and framework, a design plan and tree-map for the internet site was developed.

• 대한임베디드공학회논문지
• /
• 제19권1호
• /
• pp.47-55
• /
• 2024

We spend a lot of time in indoor space, and the space has a huge impact on our lives. Interior design plays a significant role to make an indoor space attractive and functional. However, it should consider a lot of complex elements such as color, pattern, and material etc. With the increasing demand for interior design, there is a growing need for technologies that analyze these design elements accurately and efficiently. To address this need, this study suggests a deep learning-based design analysis system. The proposed system consists of a semantic segmentation model that classifies spatial components and an image classification model that classifies attributes such as color, pattern, and material from the segmented components. Semantic segmentation model was trained using a dataset of 30000 personal indoor interior images collected for research, and during inference, the model separate the input image pixel into 34 categories. And experiments were conducted with various backbones in order to obtain the optimal performance of the deep learning model for the collected interior dataset. Finally, the model achieved good performance of 89.05% and 0.5768 in terms of accuracy and mean intersection over union (mIoU). In classification part convolutional neural network (CNN) model which has recorded high performance in other image recognition tasks was used. To improve the performance of the classification model we suggests an approach that how to handle data that has data imbalance and vulnerable to light intensity. Using our methods, we achieve satisfactory results in classifying interior design component attributes. In this paper, we propose indoor space design analysis system that automatically analyzes and classifies the attributes of indoor images using a deep learning-based model. This analysis system, used as a core module in the A.I interior recommendation service, can help users pursuing self-interior design to complete their designs more easily and efficiently.

• 한국지진공학회논문집
• /
• 제20권4호
• /
• pp.257-268
• /
• 2016

In the companion papers (I, II), site-specific response analyses were performed at more than 300 domestic sites and a new site classification system and design response spectra (DRS) were proposed using the results of the site-specific response analyses. In this paper, the proposed site classification system and the design response spectra are compared with those in other seismic codes and verified by different methods. Firstly, the design response spectra are compared with the design response spectra in Eurocode 8, KBC 2016 and MOCT 1997 to estimate quantitative differences and general trends. Secondly, site-specific response analyses are carried out using $V_S$-profiles obtained using field seismic tests and the results are compared with the proposed DRS in order to reduce the uncertainty in using the SPT-N value in site-specific response analyses in the companion paper (I). In addition, site coefficients from real earthquake records measured in Korean peninsula are used to compare with the proposed site coefficients. Finally, dynamic centrifuge tests are also performed to simulate the representative Korean site conditions, such as shallow depth to bedrock and short-period amplification characteristics. The overall results showed that the proposed site classification system and design response spectra reasonably represented the site amplification characteristic of shallow bedrock condition in Korea.

• 한국지능시스템학회논문지
• /
• 제11권7호
• /
• pp.598-602
• /
• 2001

Recently, due to the widely use of personal computers and internet, many computer users requested intelligent system that can cope with various types of requirements and user-friendly interfaces. Based on this background, researches on the intelligent agent are now activating in various fields. In this paper, we modeled, designed and implemented an intelligent agent system for pattern classification by adopting intelligent agent concepts. We also investigated the pattern classification method by utilizing some pattern classification algorithms for the common data. As a result, we identified that 300 3-dimensional data are applied to three pattern classification algorithms and returned correct results. Our system showed a distinguished user-friendly interface feature by adopting various agents including graphic agent.

• 한국디자인학회:학술대회논문집
• /
• 한국디자인학회 2002년도 봄 학술발표회 논문집
• /
• pp.56-57
• /
• 2002

• International Journal of Knowledge Content Development & Technology
• /
• 제7권2호
• /
• pp.85-105
• /
• 2017

Given the variety of approaches to mapping the universe of knowledge that have been presented and discussed in the literature, the purpose of this paper is to systematize their main principles and their applications in the major general modern library classification schemes. We conducted an analysis of the literature on classification and the main classification systems, namely Dewey/Universal Decimal Classification, Cutter's Expansive Classification, Subject Classification of J.D. Brown, Colon Classification, Library of Congress Classification, Bibliographic Classification, Rider's International Classification, Bibliothecal Bibliographic Klassification (BBK), and Broad System of Ordering (BSO). We conclude that the arrangement of the main classes can be done following four principles that are not mutually exclusive: ideological principle, social purpose principle, scientific order, and division by discipline. The paper provides examples and analysis of each system. We also conclude that as knowledge is ever-changing, classifications also change and present a different structure of knowledge depending upon the society and time of their design.

• 한국도서관정보학회지
• /
• 제18권
• /
• pp.139-192
• /
• 1991

Though the computer has become deeply entrenched as the major tool in information processing(library works), it may be obvious that automatic book classification techniques ate still under experimentation, and the techniques have not yet been tested against the criterion of usefulness. The purpose of this study is to design of knowledge base for automatic book classification which can be put to use in library operation, and to present a methodology of application of the automatic classification into the library. Since the enumerative classification schemes which are existing are manual systems, it cannot be applied to the automatic classification, the principle of faceted classification based on concept analysis is brought in and studied. The result of this study are summarized as follows : 1. The design of knowledge base confined the field of agriculture and medicine. 2. If title is entered by the computer keyboard it will be searched in knowledge base, and then be classified by the principle of automatic classification. 3. Program flowcharts are designed as a bases of classification procedures for automatic subject recognition and classification. 4. 283 books in agriculture, 196 books in medicine were drawn at random from Taegu University Library and Young-Nal Medical Center Library respectively. 5. The experiment of automatic classification is performed 143 books in agriculture 166 books in medicine except for other subject books. 6. It was proved that automatic book classification is possible by design of knowledge base. In addition the expected values from design of knowledge base for automatic book classification are as follows : 1. The prompt and accurate process of classification is possible. 2. Though some title is classified in any library, it can be classified the some classification number by a program. 3. The user can retrieve the classification codes of books for which he or she wants to search through the computer. 4. Since the concept coordination method is employed the representing of a multisubject concept is make simple. 5. By performing automatic book classification the automation of total system can be achieved. 6. The efficient international information transfer will be advanced since all the institution maintain unified classification number.

• 산업경영시스템학회지
• /
• 제22권50호
• /
• pp.195-207
• /
• 1999

Classification and Coding(C&C) systems as a core of design information management have been accomplished by many studies in terms of design and manufacturing attribute based on Group Technology. Those are very difficult to apply in make-to-order(MTO) manufacturing because the environment of MTO has various characteristics of product, many licensors, engineering change, insufficiency of integrated management system for codes and so on. This paper presents a suitable C&C system to MTO manufacturing which consider management level and drawing. The steps of developing the C&C system are as follows: 1) analysis of existing coding system and drawing type; 2) design of C&C system; 3) practice of designed coding system to a field.