• 한국통신학회논문지
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• 제23권9A호
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• pp.2258-2270
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• 1998

Recently, the distributed processing environments provide various open multimedia serivces through telecommunication network and have been developing into information networking structure based on object oriented concepts and distributed systems which can apply new services with a few changes the existing networks. This paper proposes the object group model which is the collection of objects and can functionally and efficiently manage the individual object. this paper presents the analysis of the requirement and the function specifications to propose the object group model, and depicts the functional structure in details using its analysis. The goal of this paper is to decrease the complexity of the object's management and to voercome the limitations of among the components of object group for management and service functions based on our proposed the object group model and show interaction procedures to eTD (event tracing diagram)s and finally we design the object group model by TINA-ODL.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1995년도 봄 학술발표회 논문집
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• pp.160-169
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• 1995

This study presents an application of object-oriented methodology for structural dcsign process. A prototype system of integrated a structural design system is developed by introducing a structural analysis object model(SAOM) and structural design object model(SDOM). The SAOM module. which is modeled as a part of structural member, performs structural analysis using FEM approach and the SDOM module checks structural members based on Korea steel design standard. Above mentionedmodelsareabstraclencapsulatibleandreusable.

• 디지털산업정보학회논문지
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• 제14권2호
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• pp.35-47
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• 2018

The 4th industrial revolution, digital image technology has developed beyond the limit of multimedia industry to advanced IT fusion and composite industry. Particularly, application technology related to HCI element algorithm in 3D image object recognition field is actively developed. 3D image object recognition technology evolved into intelligent image sensing and recognition technology through 3D modeling. In particular, image recognition technology has been actively studied in image processing using object recognition recognition processing, face recognition, object recognition, and 3D object recognition. In this paper, we propose a research method of human factor 3D image recognition technology applying human factor algorithm for 3D object recognition. 1. Methods of 3D object recognition using 3D modeling, image system analysis, design and human cognitive technology analysis 2. We propose a 3D object recognition parameter estimation method using FACS algorithm and optimal object recognition measurement method. In this paper, we propose a method to effectively evaluate psychological research techniques using 3D image objects. We studied the 3D 3D recognition and applied the result to the object recognition element to extract and study the characteristic points of the recognition technology.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2003년도 제2차 연례학술대회 발표논문집
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• pp.147-154
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• 2003

Microarray information system is a complex system to manage, analyze and interpretate microarray gene expression data. Establishment of well-defined development process is very essential for understanding the complexity and organization of the system. We performed object-oriented analysis using Unified Modeling Language (UML) in specifying, visualizing and documenting microarray information system. The object-oriented analysis consists of three major steps: (i) use case modeling to describe various functionalities from the user's perspective (ii) dynamic modeling to illustrate behavioral aspects of the system (iii) object modeling to represent structural aspects of the system. As a result of our modeling activities we provide the UML diagrams showing various views of the microarray information system. We believe that the object-oriented analysis ensures effective documentations and communication of information system requirements. Another useful feature of object-oriented technique is structural continuity to standard microarray data model MAGE-OM (Microarray Gene Expression Object Model). The proposed modeling e(forts can be applicable for integration of biomedical information system.

• 대한임베디드공학회논문지
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• 제18권3호
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• pp.125-132
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• 2023

Roundabouts have strengths in traffic flow and safety but can present difficulties for inexperienced drivers. Demand to acquire and analyze drone images has increased to enhance a traffic environment allowing drivers to deal with roundabouts easily. In this paper, we propose a roundabout traffic analysis system that detects, tracks, and analyzes vehicles using a deep learning-based object detection model (YOLOv7) in drone images. About 3600 images for object detection model learning and testing were extracted and labeled from 1 hour of drone video. Through training diverse conditions and evaluating the performance of object detection models, we achieved an average precision (AP) of up to 97.2%. In addition, we utilized SORT (Simple Online and Realtime Tracking) and OC-SORT (Observation-Centric SORT), a real-time object tracking algorithm, which resulted in an average MOTA (Multiple Object Tracking Accuracy) of up to 89.2%. By implementing a method for measuring roundabout entry speed, we achieved an accuracy of 94.5%.

• International Journal of Advanced Culture Technology
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• 제6권3호
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• pp.142-150
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• 2018

This paper describes the algorithm that lowers the dimension, maintains the object recognition and significantly reduces the eigenspace configuration time by combining the edge orientation histogram and principle component analysis. By using the detected object region as a recognition input image, in this paper the object recognition method combined with principle component analysis and the multi-layer network which is one of the intelligent classification was suggested and its performance was evaluated. As a pre-processing algorithm of input object image, this method computes the eigenspace through principle component analysis and expresses the training images with it as a fundamental vector. Each image takes the set of weights for the fundamental vector as a feature vector and it reduces the dimension of image at the same time, and then the object recognition is performed by inputting the multi-layer neural network.

• 해양환경안전학회지
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• 제1권2호
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• pp.83-94
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• 1995

The purpose of this paper is to develop an integrated environment system for finite element structural analysis using OOA(Object-Oriented Analysis) and OOD(Object-Oriented Design), with may reduce inconveniencies in use such as file input of macro command and improve lacks of graphic presentation in the established finite element analysis program. This paper is attempted to suggest an easy approach to object-oriented concept and convenient programming. Two languages are used together in this paper instead of single C++ language for the development of object-oriented program. : Visual Basic with CDK(Custom Development Kit), and Borland C++ with OWL(Object Windows Library).

• International Journal of Internet, Broadcasting and Communication
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• 제11권4호
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• pp.76-85
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• 2019

We introduce a vision-based object detection method for real-time video surveillance system in low-end edge computing environments. Recently, the accuracy of object detection has been improved due to the performance of approaches based on deep learning algorithm such as Region Convolutional Neural Network(R-CNN) which has two stage for inferencing. On the other hand, one stage detection algorithms such as single-shot detection (SSD) and you only look once (YOLO) have been developed at the expense of some accuracy and can be used for real-time systems. However, high-performance hardware such as General-Purpose computing on Graphics Processing Unit(GPGPU) is required to still achieve excellent object detection performance and speed. To address hardware requirement that is burdensome to low-end edge computing environments, We propose sub-frame analysis method for the object detection. In specific, We divide a whole image frame into smaller ones then inference them on Convolutional Neural Network (CNN) based image detection network, which is much faster than conventional network designed forfull frame image. We reduced its computationalrequirementsignificantly without losing throughput and object detection accuracy with the proposed method.

• 전산구조공학
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• 제5권4호
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• pp.125-132
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• 1992

본 연구에서는 C++언어를 이용한 객체지향 프로그래밍 기법으로 매트릭스 연산과 평면뼈대 구조물의 해석이 가능한 PC용 구조해석 프로그램을 개발하였다. 객체지향 프로그래밍에서의 주요 개념인 객체, 클래스, 처리방식, 상속성 및 다형성을 도식화하여 설명하였으며, 매트릭스 연산과 평면뼈대 구조해석에 대한 예제 해석 결과는 이 프로그램의 효율성과 타당성을 보여 주었다. 따라서 본 연구는 객체지향 프로그래밍기법의 특징인 프로그램의 확장성과 재사용성 및 다양한 GUI의 구현가능성을 이용하여 앞으로의 객체지향 유한요소 프로그램 개발에 활용될 것이다.

• 한국컴퓨터산업학회논문지
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• 제5권4호
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• pp.461-470
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• 2004

본 연구는 지하수 관정 인터페이스를 객체지향 기반으로 설계하였다. 복합적 형태의 현실 세계의 지리 객체를 위한 지리 데이터베이스 구현을 위하여 추상화 단계에서 분석 유형에 대하여 연구하였다. 응용영역에 적합한 유형을 규정하고 객체지향 방법론에 기반 한 UML을 이용하여 분석유형을 설계함으로서 대규모 개방 시스템을 개발하고 배포할 수 있는 컴포넌트의 재사용 성을 증가시키는데 기여하고자 한다.