• Title/Summary/Keyword: Object Data

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A Multimedia Query Language for Object-Oriented Multimedia Databases (객체 지향 멀티미디어 데이타베이스를 위한 멀티미디어 질의어)

  • 노윤묵;이석호;김규철
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.32B no.5
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    • pp.671-682
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    • 1995
  • In this paper, we propose a multimedia query language MQL which defines and manipulates multimedia data as integration of monomedia data in time and space. The MQL is designed for a multimedia data model, called the object-relationship model, and based on the multimedia object calculus which formally describes operations on multimedia data. The SQL- like syntax for class definition and object manipulation, such as retrieval, insert, update, and delete, is defined. We show how the MQL can represent the user queries using composite temporal-spatial class structures and various relationships, such as equivalence and sequence.

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Cancer Genomics Object Model: An Object Model for Cancer Research Using Microarray

  • Park, Yu-Rang;Lee, Hye-Won;Cho, Sung-Bum;Kim, Ju-Han
    • Proceedings of the Korean Society for Bioinformatics Conference
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    • 2005.09a
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    • pp.29-34
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    • 2005
  • DNA microarray becomes a major tool for the investigation of global gene expression in all aspects of cancer and biomedical research. DNA microarray experiment generates enormous amounts of data and they are meaningful only in the context of a detailed description of microarrays, biomaterials, and conditions under which they were generated. MicroArray Gene Expression Data (MGED) society has established microarray standard for structured management of these diverse and large amount data. MGED MAGE-OM (MicroArray Gene Expression Object Model) is an object oriented data model, which attempts to define standard objects for gene expression. To assess the relevance of DNA microarray analysis of cancer research it is required to combine clinical and genomics data. MAGE-OM, however, does not have an appropriate structure to describe clinical information of cancer. For systematic integration of gene expression and clinical data, we create a new model, Cancer Genomics Object Model.

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Development of Data Object Layer (DOL) In Object-Oriented ERP Systems (객체지향 ERP 시스템에서 데이터 객체 계층의 구축)

  • Kim, Chang-Ouk;Jun, Jin
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.23 no.58
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    • pp.1-16
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    • 2000
  • To develop a generic ERP(Enterprise Resource Planning) system which can accommodate various types of manufacturing enterprises, object-oriented methods are commonly applied from analysis to implementation. The objective of OO-ERP (Object-Oriented ERP) systems is the reusability of business objects(components). In practice, one of the critical features for the reusable OO-ERP system would be the capability of interfacing with distributed, heterogeneous data repositories. Consequently, it is essential to provide data repository transparency in OO-ERP systems - business objects do not take care of the locations and types of data repositories. In this paper, we propose Data Object Layer(DOL) that supports such transparency. DOL is a horizontal component through which OO-ERP systems can be seamlessly connected with diverse data repositories.

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Deriving the Properties of Object Types for Research Data Relation Model

  • Kim, Suntae
    • Journal of Information Science Theory and Practice
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    • v.1 no.2
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    • pp.84-92
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    • 2013
  • In this study, the properties of the object types required to describe the relationship among research data resources, which may be generated during the life cycle of the research, are derived. The properties of Fedora Commons and DSpace, which are open source software used for resource management, and schema properties published in DataCite were analyzed. Based on relation names of Fedora Commons, nine new relation names were derived. Thirty-eight object type properties consolidating the target properties of the analysis were derived. The result of this study can be used as basic material for crosswalk research studies of object type relation terms to ensure interoperability among the systems.

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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Motion Estimation of 3D Planar Objects using Multi-Sensor Data Fusion (센서 융합을 이용한 움직이는 물체의 동작예측에 관한 연구)

  • Yang, Woo-Suk
    • Journal of Sensor Science and Technology
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    • v.5 no.4
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    • pp.57-70
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    • 1996
  • Motion can be estimated continuously from each sensor through the analysis of the instantaneous states of an object. This paper is aimed to introduce a method to estimate the general 3D motion of a planar object from the instantaneous states of an object using multi-sensor data fusion. The instantaneous states of an object is estimated using the linear feedback estimation algorithm. The motion estimated from each sensor is fused to provide more accurate and reliable information about the motion of an unknown planar object. We present a fusion algorithm which combines averaging and deciding. With the assumption that the motion is smooth, the approach can handle the data sequences from multiple sensors with different sampling times. Simulation results show proposed algorithm is advantageous in terms of accuracy, speed, and versatility.

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Identification of Surfaces of a 3-Dimensional Object from Range Data (Range 데이터를 이용한 3-D 물체의 면 인식 방법에 관한 연구)

  • Park, Doo-Yeong
    • The Journal of Engineering Research
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    • v.2 no.1
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    • pp.63-71
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    • 1997
  • In this paper, we describe an approach that determines the identity of surfaces of an object with planar and curved surfaces from range data of the object in the scene. The proposed matching scheme presents that surface correspondence of an object is achieved by simple comparison of values for representing surfaces of the object with model in order to avoid unnecessary matching procedures. We use uniquely assigned Surface Representing Value(SRV) for representing surfaces of the object, which are sums of all weighted view-point independent features. And, the proposed method is simple, quite effective and insensitive to occlusion and noise in sensor data.

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Object-Based Modeling and Language for an Object-Oriented Spatiao-Temporal Database System (객체지향 시공간 데이터베이스 시스템의 객체기반 설계 및 질의어)

  • Kim, Yang Hee
    • The Journal of Korean Association of Computer Education
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    • v.10 no.2
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    • pp.101-113
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    • 2007
  • In this paper, we present an object-based modeling and language for an object-oriented spatio-temporal database system. For handling the structure of spatio-temporal objects and the spatio-temporal operators, we propose the two layers of data modeling: a spatio-temporal object model (STOM) and an spatio_temporal internal description model (STIM). We then propose STOQL, a spatio-temporal object-oriented query language. STOQL provides an integrated mechanism for the graphical display of spatial objects and the retrieval of spatio-temporal and aspatial objects.

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Yolo based Light Source Object Detection for Traffic Image Big Data Processing (교통 영상 빅데이터 처리를 위한 Yolo 기반 광원 객체 탐지)

  • Kang, Ji-Soo;Shim, Se-Eun;Jo, Sun-Moon;Chung, Kyungyong
    • Journal of Convergence for Information Technology
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    • v.10 no.8
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    • pp.40-46
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    • 2020
  • As interest in traffic safety increases, research on autonomous driving, which reduces the incidence of traffic accidents, is increased. Object recognition and detection are essential for autonomous driving. Therefore, research on object recognition and detection through traffic image big data is being actively conducted to determine the road conditions. However, because most existing studies use only daytime data, it is difficult to recognize objects on night roads. Particularly, in the case of a light source object, it is difficult to use the features of the daytime as it is due to light smudging and whitening. Therefore, this study proposes Yolo based light source object detection for traffic image big data processing. The proposed method performs image processing by applying color model transitions to night traffic image. The object group is determined by extracting the characteristics of the object through image processing. It is possible to increase the recognition rate of light source object detection on a night road through a deep learning model using candidate group data.

Design and Implementation of the Spatio-Temporal DSMS for Moving Object Data Streams (이동체 데이타 스트림을 위한 시공간 DSMS의 설계 및 구현)

  • Lee, Ki-Young;Kim, Joung-Joon
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.8 no.5
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    • pp.159-166
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    • 2008
  • Recently, according to the rapid development of location positioning technology and wireless communications technology and increasement of usage of moving object data, many researches and developments on the real-time locating systems which provides real time service of moving object data stream are under proceeding. However, MO (Moving Object) DBMS used based system in the in these systems is the inefficient management of moving object data streams, and the existing DSMS (Data Stream Management System) has problems that spatio-temporal data are not handled efficiently. Therefore, in this thesis, we designed and implemented spatio-temporal DSMS for efficient real-time management of moving object data stream. This thesis implemented spatio-temporal DSMS based STREAM (STanford stREam dAta Manager) of Stanford University is supporting real-time management of moving object data stream and spatio-temproal query processing and filtering for reduce the input loading. Specifically, spatio-temporal operators of the spatio-temporal DSMS support standard interface of SQL form which extended "Simple Feature Specification for SQL" standard specifications presented by OGC for compatibility. Finally, implemented spatio-temporal DSMS in this thesis, proved the effectiveness of the system that as applied real-time monitoring areas that require real-time locating of object data stream DSMS.

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