• Title/Summary/Keyword: Structured Data

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Analysis of periodontal data using mixed effects models

  • Cho, Young Il;Kim, Hae-Young
    • Journal of Periodontal and Implant Science
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    • v.45 no.1
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    • pp.2-7
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    • 2015
  • A fundamental problem in analyzing complex multilevel-structured periodontal data is the violation of independency among the observations, which is an assumption in traditional statistical models (e.g., analysis of variance and ordinary least squares regression). In many cases, aggregation (i.e., mean or sum scores) has been employed to overcome this problem. However, the aggregation approach still exhibits certain limitations, such as a loss of power and detailed information, no cross-level relationship analysis, and the potential for creating an ecological fallacy. In order to handle multilevel-structured data appropriately, mixed effects models have been introduced and employed in dental research using periodontal data. The use of mixed effects models might account for the potential bias due to the violation of the independency assumption as well as provide accurate estimates.

Three dimensional data acquisition system using structured light and image processing (구조화 조명과 영상 처리를 이용한 3차원 데이터 획득 시스템)

  • 전희성;박제홍;고문석
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.35S no.5
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    • pp.83-93
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    • 1998
  • Three dimensional data acquisition system based on the structured light is developed in this work. The system is composed of a CCD camera, slide projector, and various image processing programs. Calibration procedures and several image processing steps which are necessary to get the rnage data are described. A new grid labeling technique and a grid pattern are devised to improve the accuracy of th eobtained data. Preliminary experimental result shows that the developed system may be used as a simple and cheap 3D data acquisition system. Severla suggestions are included for further research.

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Security tendency analysis techniques through machine learning algorithms applications in big data environments (빅데이터 환경에서 기계학습 알고리즘 응용을 통한 보안 성향 분석 기법)

  • Choi, Do-Hyeon;Park, Jung-Oh
    • Journal of Digital Convergence
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    • v.13 no.9
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    • pp.269-276
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    • 2015
  • Recently, with the activation of the industry related to the big data, the global security companies have expanded their scopes from structured to unstructured data for the intelligent security threat monitoring and prevention, and they show the trend to utilize the technique of user's tendency analysis for security prevention. This is because the information scope that can be deducted from the existing structured data(Quantify existing available data) analysis is limited. This study is to utilize the analysis of security tendency(Items classified purpose distinction, positive, negative judgment, key analysis of keyword relevance) applying the machine learning algorithm($Na{\ddot{i}}ve$ Bayes, Decision Tree, K-nearest neighbor, Apriori) in the big data environment. Upon the capability analysis, it was confirmed that the security items and specific indexes for the decision of security tendency could be extracted from structured and unstructured data.

An Extended Dynamic Schema for Storing Semi-structured Data

  • Nakata, Mitsuru;Ge, Qi-Wei;Hochin, Teruhisa;Tsuji, Tatsuo
    • Proceedings of the IEEK Conference
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    • 2002.07a
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    • pp.301-304
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    • 2002
  • Recently, database technologies have been used commonly. But, ordinary technologies aren't suitable to construct a complicated database such as a classical literature database or an archaeological relic's database. Because this kinds of data are semi-structured data that doesn't have regular structures, database schema can't be defined before databases. We have proposed DREAM model for semi-structured databases. In this model, a database consists of five elements and the model has operations similar to operation of set theory. And further we have introduced dynamic schema "shape" showing structure of each element. We have already realized a prototype of DBMS adopting DREAM model (DREAM DBMS) and constructing function of shapes. However, shape is imperfect to describe database structures because it can't explain nested structures of elements. In this paper, we will profuse a "shape graph"that is dynamic schema showing database structures more exactly and extend the DREAM DBMS. Further we will evaluate the performance of constructing function of shapes and shape graphs.

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The Effect of the Types of Learning Material and Epistemological Beliefs in an Ill-structured Problem Solving

  • OH, Suna;KIM, Yeonsoon;KANG, Sungkwan
    • Educational Technology International
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    • v.16 no.2
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    • pp.183-200
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    • 2015
  • This study investigated the effect of learning achievements and cognitive load according to different types of presenting learning materials and epistemological beliefs (EB). Learning achievements in this study were composed by retention and transfer of ill-structured problem. A total of 80 college students participated in the study. Prior to the learning, students were guided to fill out a questionnaire regarding epistemological beliefs and a prior knowledge test. The students of each group studied with a different type of reading material: full text (FT), full text including key questions (KeyFT) and full text including a concept map (CmFT). After a session of study was finished, they were asked to complete the posttest: retention and transfer. The results showed that there was a significant difference in transfer achievements. CmFT outperformed higher scores than the other types. There was no significant difference in retention among the groups. It is strongly believed that the types of presenting learning materials may have affected the understanding of ill-structured problem solving skills. Students with sophisticated EB showed higher achievements on retention and transfer than naive-EB and mixed-EB. Even though the data showed decrease of the cognitive load on the type of materials and EB, there were no significant differences on the cognitive load. We should consider a positive effect of types of presenting learning materials and EB enhancing capabilities of solving ill-structured problems in real life.

Modeling Element Relations as Structured Graphs Via Neural Structured Learning to Improve BIM Element Classification (Neural Structured Learning 기반 그래프 합성을 활용한 BIM 부재 자동분류 모델 성능 향상 방안에 관한 연구)

  • Yu, Youngsu;Lee, Koeun;Koo, Bonsang;Lee, Kwanhoon
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.41 no.3
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    • pp.277-288
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    • 2021
  • Building information modeling (BIM) element to industry foundation classes (IFC) entity mappings need to be checked to ensure the semantic integrity of BIM models. Existing studies have demonstrated that machine learning algorithms trained on geometric features are able to classify BIM elements, thereby enabling the checking of these mappings. However, reliance on geometry is limited, especially for elements with similar geometric features. This study investigated the employment of relational data between elements, with the assumption that such additions provide higher classification performance. Neural structured learning, a novel approach for combining structured graph data as features to machine learning input, was used to realize the experiment. Results demonstrated that a significant improvement was attained when trained and tested on eight BIM element types with their relational semantics explicitly represented.

A Methodology for Deriving An Object Model by Using Structured Analysis Results (구조적 분석 산출물을 이용한 객체 모델 유도 방법론)

  • 이희석;배한욱;유천수
    • Journal of the Korean Operations Research and Management Science Society
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    • v.21 no.3
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    • pp.175-195
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    • 1996
  • In conventional analysis methods, data and process are loosely coupled for building information systems. Several object oriented approaches have been proposed to integrate data and process. However, object oriented analysis requires a radical paradigm and thus system analysts find difficulties in generating object models direcctly from end users. To alleviate these difficulties, this paper proposes a methodology for deriving an object model by using structured analysis results. Objects are obtianed primarily from entities in Entity-Relationship Diagram. Methods are obtained through the analysis of the relationship between processes and data stores in Data Flow Diagram Methods are assigned to the objects by using object/process matrices. A real-life case is illustrated to demonstrate the usefulness of the methodology.

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Design & Implementation of Extractor for Design Sequence of DB tables using Data Flow Diagrams (자료흐름도를 사용한 테이블 설계순서 추출기의 설계 및 구현)

  • Lim, Eun-Ki
    • Journal of Korea Society of Industrial Information Systems
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    • v.17 no.3
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    • pp.43-49
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    • 2012
  • Information obtained from DFD(Data Flow Diagram) are very important in system maintenance, because most legacy systems are analyzed using DFD in structured analysis. In our thesis, we design and implement an extractor for design sequence of database tables using DFD. Our extractor gets DFDs as input data, transform them into a directed graph, and extract design sequence of DB tables. We show practicality of our extractor by applying it to a s/w system in operation.

Building an Ontology for Structured Data Entry of Signs and Symptoms in Oriental Medicine (Protege를 이용한 한의학의 구조화된 증상 입력을 위한 온톨로지 개발)

  • Park Kyung Mo;Lim Hee Sook;Park Jong Hyun
    • Journal of Physiology & Pathology in Korean Medicine
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    • v.17 no.5
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    • pp.1151-1156
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    • 2003
  • To obtain both of the fast and complete data entry and the acquisition of reusable data in a Computer-based Patient Record system (CPR), we are building the ontology that is used by the entry supporting agents. Our application domain is Traditional Chinese Medicine. As the tool for the implementation, we used protege 2000 which is ontology building tool and provides frame knowledge representation language. In this paper, the construction methodology of our ontology is reported.

A House Design Automation System Based on the "Design-by-Novice" Paradigm

  • Kim, Uk;Choi, Jinwon;Kim, SungAh
    • Architectural research
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    • v.1 no.1
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    • pp.23-30
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    • 1999
  • This research investigates a system for house design automation. The system is based on an object-oriented building data model, aiming to support the house design process conducted by non-expert users. Its object model, with simple yet powerful user interfaces, enables a CAD system to handle a complicated building system with much ease. Hence, the model dramatically simplifies the design process beyond just the automatic document generation. In this paper, we discuss the aspects of the building data model, introduce critical concepts such as grid objects and structured floor plan, and present a prototype system called GPLAN. The system is implemented in the framework of our building data model, and it provides a host of intelligent features that have been proved useful for house design automation.

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