• Title/Summary/Keyword: Basic Classification

Search Result 1,399, Processing Time 0.033 seconds

Development of Classification System and Online Service Methods for Collections in Larchiveum-Type Institutions: The Case of the National Memorial of the Korean Provisional Government (라키비움 형식의 기관 소장 자료에 관한 분류체계 개발 및 온라인 서비스 방안: 국립대한민국임시정부기념관을 사례로)

  • Hyeyun Lee;Hae-young Rieh
    • Journal of Korean Society of Archives and Records Management
    • /
    • v.24 no.2
    • /
    • pp.113-137
    • /
    • 2024
  • In this study, considering the National Memorial of the Korean Provisional Government as a "Larchiveum," the researchers attempted to develop a classification system that can comprehensively categorize various types of materials and propose a method of providing an online service. To this end, as a case study, the researchers examined the classification system structure and contents of the National Archives of Korea, National Assembly Archives, and Archives of Korean History of the National Institute of Korean History, which are the current material collection institutions of the Korean Provisional Government. Regarding online services, apart from the three institutions above, the Imperial War Museum and the Hoover Institution at Stanford University were also explored. Through the implications derived from the case analysis of domestic and foreign institutions, a basic hierarchical classification system by provenance for the materials held by the institution was established, and a multi-classification system was presented according to the classification criteria of "by type, by era, and by subject." In addition, methods of applying the developed classification system to online services were proposed.

Classification System of EEG Signals During Mental Tasks

  • Seo Hee Don;Kim Min Soo;Eoh Soo Hae;Huang Xiyue;Rajanna K.
    • Proceedings of the IEEK Conference
    • /
    • 2004.08c
    • /
    • pp.671-674
    • /
    • 2004
  • We propose accurate classification method of EEG signals during mental tasks. In the experimental task, the tasks of subjects show 3 major measurements; there are mathematical tasks, color decision tasks, and Chinese phrase tasks. The classifier implemented for this work is a feed-forward neural network that trained with the error back-propagation algorithm. The new BCI system is proposed by using neural network. In this system, tr e architecture of the neural network is composed of three layers with a feed-forward network, which implements the error back propagation-learning algorithm. By applying this algorithm to 4 subjects, we achieved $95{\%}$ classification rates. The results for BCI mathematical task experiments show performance better than those of the Chinese phrase tasks. The selection time of each task depends on the mental task of subjects. We expect that the proposed detection method can be a basic technology for brain-computer interface by combining with left/right hand movement or yes/no discrimination methods.

  • PDF

Risk Classification and Relational Database Schema in Overseas Power Plant Construction (해외 발전플랜트 리스크 분류체계 및 관계형 데이터베이스 구축 방안)

  • Kim, Min;Jung, Youngsoo
    • Proceedings of the Korean Institute of Building Construction Conference
    • /
    • 2014.05a
    • /
    • pp.192-193
    • /
    • 2014
  • Due to the decreasing domestic construction market since 2007, Korean construction companies are expanding overseas market. As a result, the international market share by Korea has been continuously increased and achieved 65.2 billion dollars in 2013. Despite of such visible results, profitability concerns are constantly arising. It is pointed out that the low-priced bid competition between Korean construction companies and various unpredictable risks are the most crucial factors which aggravate the profitability in the overseas projects. From this point of view, predicting the risks in advance and controling them could be the most important tasks to improve the profitability. This research proposed 202 risk factors with a hierarchy and relational database schema for power plant construction, which is based on the 24 risk classifications in previous research (Kim & Jung 2013). Proposed risk classification and relational database schema could be utilized as the basic data in risk management system.

  • PDF

Genetic Algorithm Application to Machine Learning

  • Han, Myung-mook;Lee, Yill-byung
    • Journal of the Korean Institute of Intelligent Systems
    • /
    • v.11 no.7
    • /
    • pp.633-640
    • /
    • 2001
  • In this paper we examine the machine learning issues raised by the domain of the Intrusion Detection Systems(IDS), which have difficulty successfully classifying intruders. There systems also require a significant amount of computational overhead making it difficult to create robust real-time IDS. Machine learning techniques can reduce the human effort required to build these systems and can improve their performance. Genetic algorithms are used to improve the performance of search problems, while data mining has been used for data analysis. Data Mining is the exploration and analysis of large quantities of data to discover meaningful patterns and rules. Among the tasks for data mining, we concentrate the classification task. Since classification is the basic element of human way of thinking, it is a well-studied problem in a wide variety of application. In this paper, we propose a classifier system based on genetic algorithm, and the proposed system is evaluated by applying it to IDS problem related to classification task in data mining. We report our experiments in using these method on KDD audit data.

  • PDF

Obstacle Classification for Mobile Robot Traversability using 2-dimensional Laser Scanning (2차원 레이저 스캔을 이용한 로봇의 산악 주행 장애물 판단)

  • Kim, Min-Hee;Kwak, Kyung-Woon;Kim, Soo-Hyun
    • Journal of the Korea Institute of Military Science and Technology
    • /
    • v.15 no.1
    • /
    • pp.1-8
    • /
    • 2012
  • Obstacle detection is much studied by using sensors such as laser, vision, radar and ultrasonic in path planning for UGV(Unmanned Ground Vehicle), but not much reported about its characterization. In this paper not only an obstacle classification method using 2-dimensional LMS(Laser Measurement System) but also a decision making method whether to avoid or traverse the obstacle is proposed. The basic idea of decision making is to classify the characteristics by 2D laser scanned data and intensity data. Roughness features are obtained by range data using a simple linear regression model. The standard deviations of roughness and intensity data are used as measures for decision making by comparing with those of reference data. The obstacle classification and decision making for the UGV can facilitate a short path to the target position and the survivability of the robot.

A Basic Study for Establishing of Numerical Range Criteria for Classification of Value Improvement Types (VE 가치향상 유형별 수치적 범위기준 설정을 위한 기초연구)

  • Nam, Keong Woo;Jang, Myunghoun
    • Proceedings of the Korean Institute of Building Construction Conference
    • /
    • 2018.05a
    • /
    • pp.74-75
    • /
    • 2018
  • VE, rather than just cost reduction tool, have established as a value enhancement tool of the construction industry. Value improvement types of VE proposal can show the effect of VE activities, also acts as an important element in which the owner adopts a proposal and confirms the results of the VE activities. However, problems in the process of quantification for VE proposal and ambiguous standards in classification of value improvement types is need to be supplemented. Accordingly, This study suggests the plan for establishing of numerical range criteria for classification of value improvement types of VE proposal. Implementing this plan will be able to improve the reliability and availability for VE activities.

  • PDF

Category Factor Based Feature Selection for Document Classification

  • Kang Yun-Hee
    • International Journal of Contents
    • /
    • v.1 no.2
    • /
    • pp.26-30
    • /
    • 2005
  • According to the fast growth of information on the Internet, it is becoming increasingly difficult to find and organize useful information. To reduce information overload, it needs to exploit automatic text classification for handling enormous documents. Support Vector Machine (SVM) is a model that is calculated as a weighted sum of kernel function outputs. This paper describes a document classifier for web documents in the fields of Information Technology and uses SVM to learn a model, which is constructed from the training sets and its representative terms. The basic idea is to exploit the representative terms meaning distribution in coherent thematic texts of each category by simple statistics methods. Vector-space model is applied to represent documents in the categories by using feature selection scheme based on TFiDF. We apply a category factor which represents effects in category of any term to the feature selection. Experiments show the results of categorization and the correlation of vector length.

  • PDF

The Basic Analysis for Estimating the Value of Household Work (가사노동 가치평가를 위한 기초적 분석)

  • 문숙재;최민영
    • Journal of Family Resource Management and Policy Review
    • /
    • v.6 no.1
    • /
    • pp.35-51
    • /
    • 2002
  • This study is the basic step of including the economical value of household labor into the existing GDP. Therefore this study analyzes statistical data; $\mathbb{\ulcorner}$Economical Active Population Survey$\mathbb{\lrcorner}$, $\mathbb{\ulcorner}$Time Used Survey$\mathbb{\lrcorner}$, $\mathbb{\ulcorner}$Basic Wage Structural Survey$\mathbb{\lrcorner}$, and $\mathbb{\ulcorner}$City Household Survey$\mathbb{\lrcorner}$ for that step and will help people to reconsider the importance of the economical value household work. Economical Active Population Survey classifies housework as economically nonoproductive activity Time Use Survey does not have an clear classification for action. Basic Wage Structural Survey must give subdividable information on wage. City Household Survey should include more details and more data of household durables.

  • PDF

Elementary School Teachers' Perceptions on Effects of 'Basic Inquiry' Units in Experimental Grade 3~4 Science Textbooks developed for 2009 Revised National Curriculum (2009 개정 교육과정에 따른 초등학교 3~4학년 과학 교과용 도서 실험본의 '기초탐구' 단원의 효과에 대한 초등학교 교사의 인식)

  • Lee, Dae-Hyung;Kang, Hunsik;Yoon, Hye-Gyoung
    • Journal of Korean Elementary Science Education
    • /
    • v.33 no.1
    • /
    • pp.30-43
    • /
    • 2014
  • 'Basic Inquiry' unit was newly included in the grade 3~4 science textbook developed for 2009 revised national curriculum. The unit deals with six basic inquiry skills such as 'observation', 'measurement', 'classification', 'prediction', 'inference', and 'communication'. This study investigated elementary school teachers' perceptions on the effects of 'Basic Inquiry' unit by questionnaires (N=104 for pre-survey, N=90 for post-survey). The results showed that how the teachers have taught basic inquiry skills before this new textbook and how they perceived the educational effects of the unit after experimental teaching period in three aspects; development of basic inquiry skills, facilitating science learning in other units, and implementation of open inquiry. The reasons of positive perceptions as well as negative perceptions were analyzed and discussed with the suggestions for further study.

Adult women's back type classification and Development of the Basic Bodice Pattern (성인여성의 등면형상 유형화와 길 원형 설계)

  • 최선윤;이정란
    • Journal of the Korean Society of Clothing and Textiles
    • /
    • v.27 no.7
    • /
    • pp.758-769
    • /
    • 2003
  • In this research, I classified adult women's back types through anthropometric measurement and photographic measurement to present a judging individual body size according to the type. Also, Ⅰ calculated regression fomula by types and presented the basic bodice pattern. The results were as follows: 1. The result of factor analysis indicated that 5 factors were extracted and those factors comprised 75.89% of total variance. 2. According to the cluster analysis, Ⅰclassified the back types into 6 types. Type 1 was passive posture in the upper and the lower parts of the back. Type 2 was active posture in the upper and the lower parts of the back. Type 3 had the lowest protrusion of the back. Type 4 had the upper part of the back which is mostly bent downward. Type 5 was the most suitable shape. Type 6 had the lower part of the back which was turned over the most. 3. Ⅰconducted a discriminant analysis to judge the body types of individuals. 4. For the calculation of measurements necessary for the basic bodice pattern, Ⅰpresented regression formulas by each type. 5. By conducting the wearing experiments, Ⅰsuccessfully made the final basic bodice patterns by types. As a result of comparative experiments between the basic bodice patterns and comparison bodice pattern, the suitability of basic bodice patterns were more highly assessed.