• 한국철도학회:학술대회논문집
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• 한국철도학회 2003년도 추계학술대회 논문집(III)
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• pp.587-593
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• 2003

There has been much interest in the Bluetooth technology since it could enable users to connect to a wide range of computing and telecommunication devices without the need to carry or connect cables. It delivers opportunities for rapid, ad-hoc connections, and in the future, could possibly enable automatic, unconscious, connections between devices. In this paper, we discussed a scatternet formation protocol for Bluetooth-based ad hoc networks and proposed the identification system of an object using Bluetooth Scatternets. Over the past few years, several studies have been made on the identification of an object by several RF(Radio Frequency) systems. But there are still some problems, the interference of signals as an example, for the identification of an object. The critical question is how to identify an object precisely without the interference of signals. This paper is an investigation of the Scatternet formation protocol for Bluetooth-based ad hoc networks and the identification system of an object using Bluetooth Scatternets composed of multiple Piconets.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 Proceedings of the Korea Automatic Control Conference, 11th (KACC); Pohang, Korea; 24-26 Oct. 1996
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• pp.145-148
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• 1996

In moving object tracking based on the visual sensory feedback, a prerequisite is to determine which feature or which object is to be tracked and then the feature or the object identification precedes the tracking. In this paper, we focus on the object identification not image feature identification. The target identification is realized by finding out corresponding line segments to the hypothesized model segments of the target. The key idea is the combination of the Mahalanobis distance with the geometrica relationship between model segments and extracted line segments. We demonstrate the robustness and feasibility of the proposed target identification algorithm by a moving vehicle identification and tracking in the video traffic surveillance system over images of a road scene.

• 대한인간공학회:학술대회논문집
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• 대한인간공학회 1996년도 추계학술대회논문집
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• pp.197-205
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• 1996

Unification of neural network with a hierarchical pattern recognition is presented for recognizing large set of objects. A two-step identification procedure is developed for pattern recognition: coarse and fine identification. The coarse identification is designed for finding a class of object while the fine identification procedure is to identify a specific object. During the training phase a course neural network is trained for clustering larger set of reference objects into a number of groups. For training a fine neural network, expert neural network is also trained to identify a specific object within a group. The presented idea can be interpreted as two step identification. Experimental results are given to verify the proposed methodology.

• 한국정보처리학회논문지
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• 제6권10호
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• pp.2693-2706
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• 1999

Reengineering to object-oriented system is needed to maintain the system and satisfy requirements of structure change. Target systems which should be reengineered to object-oriented system are difficult to change because these systems have no design document or their design document is inconsistent of source code. Using design document to identifying objects for these systems is improper. There are several researches which identify objects through procedural source code analysis. In this paper, we propose automatic object identification method based on clustering of VTFG(Variable-Type-Function Graph) which represents relations among variables, types, and functions. VTFG includes relations among variables, types, and functions that may be basis of objects, and weights of these relations. By clustering related variables, types, and functions using their weights, our method overcomes limit of existing researches which identify too big objects or objects excluding many functions. The method proposed in this paper minimizes user's interaction through automatic object identification and make it easy to reenginner procedural system to object-oriented system.

• 정보처리학회논문지:컴퓨터 및 통신 시스템
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• 제6권2호
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• pp.51-58
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• 2017

안전과 보안상의 이유로 감시 카메라의 시장이 확대되고 있으며 이에 대해 영상 인식 및 추적에 관한 연구도 활발히 진행 중에 있으나 인식 및 추적되는 객체의 정보를 획득하여 객체를 식별하는 데는 한계가 있다. 특히, 감시카메라가 활용되는 쇼핑몰, 공항 등과 같은 개방된 공간에서는 다수의 객체들을 식별하기란 더욱 어렵다. 따라서 본 논문에서는 기존의 영상기반 객체 인식 및 추적 시스템에 RFID 기술을 더하여 객체 식별기능을 추가하고자 하였으며 영상 기반과 RFID의 문제 해결을 위해 상호 보완하고자 하였다. 그리하여 시스템의 모듈별 상호작용을 통해 영상기반 객체 인식 및 추적에 실패할 수 있는 문제와 RFID의 인식 오류로 발생할 수 있는 문제에 대한 해결 방안을 제시하였다. 객체의 식별 정도를 4단계로 분류하여 가장 최상의 단계로 객체가 식별이 되도록 시스템을 설계해 식별된 객체의 데이터 신뢰성을 유지할 수 있도록 하였다. 시스템의 효율성 판단을 위해 시뮬레이션 프로그램을 구현하여 이를 입증하였다.

• ETRI Journal
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• 제25권2호
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• pp.121-132
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• 2003

To enhance the productivity of software development and accelerate time to market, software developers have recently paid more attention to a component-based development (CBD) approach due to the benefits of component reuse. Among CBD processes, the identification of reusable components is a key but difficult process. Currently, component identification depends mainly on the intuition and experience of domain experts. In addition, there are few systematic methods or tools for component identification that enable domain experts to identify reusable components. This paper presents a systematic method and its tool called a component identifier that identifies software components by using object-oriented domain information, namely, use case models, domain object models, and sequence diagrams. To illustrate our method, we use the component identifier to identify candidates of reusable components from the object-oriented domain models of a banking system. The component identifier enables domain experts to easily identify reusable components by assisting and automating identification processes in an earlier development phase.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제9권4호
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• pp.381-392
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• 2003

소프트웨어 재사용에 중점을 두고 있는 컴포넌트 기반 개발(CBD): Component-Based Development) 기술은 생산성을 극대화하려는 소프트웨어 개발 업체로부터 많은 관심을 끌고 있다. 하지만, CBD 기술의 핵심 프로세스인 컴포넌트 식변 프로세스는 주로 도메인 전문가의 경험과 직관에 의존하여 지원 도구 개발에 어려움이 많았다. 이 논문에서는 객체 의존성과 객체 사용 패턴 정보를 이용하여 체계적인 컴포넌트 식별 과정을 제안하고 이를 지원하는 도구를 설계 및 구현한다. 객체 지향 도메인 모델에서는 다양한 관점의 다이어그램들이 존재하므로 이틀로부터 객체 간의 연관성 정보를 추출하고 통합하여 객체 의존 네트워크로 나타내고 이를 기반으로 수행되는 컴포넌트 식별 알고리즘을 제안한다 마지막으로 컴포넌트 시벽 프로세스 및 도구에 대한 적용성을 평가하기 위해 인터넷 뱅킹 시스템에서의 컴포넌트 식벽 과정을 설명한다.

• 산경연구논집
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• 제8권7호
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• pp.51-61
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• 2017

Purpose - Present study investigates character identification and emotional response to character that may affect consumers' intention to purchase the character-attached products. And this study explores whether symbolic relevance and object relevance affect the character identification, and whether character attractiveness and character salience affect the emotional response to characters. Research design, data, and methodology - SNS characters, animated characters, game characters, and traditional characters were used as experimental characters. And stationery as experimental product was used. 250 college students participated in the empirical study, and structural equation model was used to verify hypotheses. Results - First, the character identification and emotional response to characters affected the intention to purchase the products positively, and the emotional response to characters also positively affected character identification; second, symbolic relevance had no positive impact upon character identification, while object relevance had positive influence on character identification; and third, character attractiveness and salience had a positive effect on the emotional response. Conclusions - Present study contributes to the progress of character theories. Marketers should find ways to increase consumers' object relevance to characters and the level of characters' attractiveness and salience in order to promote the intent to purchase the products.

• 한국생산제조학회지
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• 제25권6호
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• pp.522-531
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• 2016

In this study, we propose an object identification method for bin-picking developed for industrial robots. We identify the grasp posture and the associated geometric parameters of grasp objects using the joint data of a robotic gripper. Prior to grasp identification, we analyze the grasping motion in a low-dimensional space using principle component analysis (PCA) to reduce the dimensions. We collected the joint data from a human hand to demonstrate the grasp-identification algorithm. For data acquisition of the human grasp data, we conducted additional research on the motion characteristics of a human hand. We explain the method for using the algorithm of grasp identification for bin-picking. Finally, we present a subject for future research using our proposed algorithm of grasp model and identification.

• 전기학회논문지
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• 제64권7호
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• pp.1047-1055
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• 2015

We proposes a method for improving the identification and tracking of the moving objects in intelligent video surveillance system. The proposed method consists of 3 parts: object detection, object recognition, and object tracking. First of all, we use a GMM(Gaussian Mixture Model) to eliminate the background, and extract the moving object. Next, we propose a labeling technique forrecognition of the moving object. and the method for identifying the recognized object by using the optical flow and EMD algorithm. Lastly, we proposes method to track the location of the identified moving object regions by using location information of moving objects and Kalman filter. Finally, we demonstrate the feasibility and applicability of the proposed algorithms through some experiments.