• International journal of advanced smart convergence
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• 제11권3호
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• pp.1-6
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• 2022

In this paper, we estimate the mean number of objects in the M/H₂/1 model for web service when the mean object size in the M/H₂/1 model is equal to that of the M/G/1/PS and M/BP/1 models. To this end, we use the mean object size obtained by assuming that the mean latency of deterministic model is equal to that of M/H₂/1, M/G/1/PS, and M/BP/1 models, respectively. Computational experiments show that if the shape parameter of the M/BP/1 model is 1.1 and the system load is greater than 0.35, the mean number of objects in the M/H₂/1 model when mean object size of M/H₂/1 model is the same as that of M/G/1/PS model is almost equal to the mean number of objects in the M/H₂/1 model when the mean object size of M/H₂/1 model is the same as that of M/BP/1 model. In addition, as the upper limit of the M/BP/1 model increases, the number of objects in the M/H₂/1 model converges to one, which increases latency. These results mean that it is efficient to use small-sized objects in the web service environment.

• Journal of Information Processing Systems
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• 제10권2호
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• pp.271-282
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• 2014

The advancement of knowledge society has enabled the social network community (SNC) to be perceived as another space for learning where individuals produce, share, and apply content in self-directed ways. The content generated within social networks provides information of value for the participants in real time. Thus, this study proposes the social network community activity-based content model (SoACo Model), which takes SNC-based activities and embodies them within learning objects. The SoACo Model consists of content objects, aggregation levels, and information models. Content objects are composed of relationship-building elements, including real-time, changeable activities such as making friends, and participation-activity elements such as "Liking" specific content. Aggregation levels apply one of three granularity levels considering the reusability of elements: activity assets, real-time, changeable learning objects, and content. The SoACo Model is meaningful because it transforms SNC-based activities into learning objects for learning and teaching activities and applies to learning management systems since they organize activities -- such as tweets from Twitter -- depending on the teacher's intention.

• 정보처리학회논문지D
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• 제9D권1호
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• pp.43-56
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• 2002

지금까지 시공간 객체를 다양한 관점에서 접근하여 표현하려는 많은 연구가 이루어졌다. 이 대부분의 연구는 GIS적 관점과 시간 데이터베이스 관점, 그리고 객체 지향적 관점 및 데이터타입 접근 방법으로 시공간 객체를 표현하고 있다. 시공간 객체는 공간 속성이 불연속적으로 변하는 객체, 위치 정보가 연속적으로 변하는 객체, 그리고 면적과 위치가 연속적으로 변하는 객체로 분류된다. 그러나 기존의 시공간 모델들은 한 종류의 객체에만 초점을 맞추고 있다. 따라서 이 논문에서는 유클리드 평면상에서 세가지 형태의 객체를 모두 표현할 수 있는 시공간 객체 모델을 제안한다. 이를 위해 유효시간 개념을 확장한 시간 모델과 함께 객체의 연속된 두 버전간의 관계성을 정의하여 이동 객체와 이력 객체 모두를 표현하는 방식을 사용한다. 여기서 제안하는 2차원 시공간 객체 모델은 개방형 GIS 명세서에서 제시하고 있는 2차원 공간 객체 모델을 따름으로써 표준 공간 모델과의 호환성을 보장한다.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2001년도 춘계종합학술대회
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• pp.633-637
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• 2001

본 논문은 모델기반 다중이동물체 추적을 위한 모델생성 알고리즘을 제안하였다. 제안한 알고리즘은 배경영상에 이동물체가 초기 진입했을 때의 초기모델생성 단계와 이동물체 추적 단계에서의 모델 갱신 단계로 구분하였다. 초기모델생성 단계에서는 차영상과 클러스터링 기법을 이용하여 분할된 분할영상과 현재프레임 영상에 대한 윤곽선 영상과의 로직 AND 연산을 수행하여 초기모델을 생성하였다. 모델갱신 단계에서는 하우스돌프 거리(Hausdorff Distance)와 2D-Logarithmic 탐색 알고리즘을 이용하여 추적중인 이동물체의 형태변화에 적응할 수 있도록 매 프레임 마다 새로운 모델을 갱신하였다. 실험은 도로에서 주행하는 자동차를 대상으로 도_의 실험을 수행하였다. 그 결과 도로에서 주행하는 자동차의 진입방향과 추적 대상 수가 불규칙한 경우에도 모델생성이 98% 이상 이루어짐을 알 수 있었다.

• 한국농공학회지
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• 제44권1호
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• pp.57-68
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• 2002

In the irrigation facilities, the irrigation system is connected systematically, and thus, it agrees to the object-oriented concept. Since it is necessary to go through comparative evaluations and to devise several alternatives plans in designing the irrigation system, it will be very efficient to use the objects that contain the design data. In this study, the object-oriented methodology has been proposed to define the objects, which will be used in the design system of irrigation facility. Furthermore, as for the essential elements of the objects, concept of element objects is formulated. By employing this concept, appropriate element objects have been derided for the irrigation facility. Necessary data model for realization of the objects is examined and selected. And then, required elements for applying the selected data model to the irrigation facility will be proposed

• 대한기계학회논문집A
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• 제25권12호
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• pp.1919-1925
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• 2001

Overhead cranes consist of trolley, girder, rope, objects, trolley motor, girder motor, and hoist motor. If objects are regarded as mass point, and the acceleration of hoisting motion for objects is neglected, analytical model of overhead cranes becomes a nonlinear model because the length of a rope changes. Equations of motion this model is derived of simultaneous differential equations fur motors and object. Positions of the model are controlled by optimal inputs which obtain from a nonlinear optimal control method. From the results of computer simulation, even if initial states of objects suing, it is founded that position of overhead cranes is controlled, and that swing of objects is suppressed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권8호
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• pp.2688-2703
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• 2022

Research on the advanced detection of harmful objects in airport cargo for passenger safety against terrorism has increased recently. However, because associated studies are primarily focused on the detection of relatively large objects, research on the detection of small objects is lacking, and the detection performance for small objects has remained considerably low. Here, we verified the limitations of existing research on object detection and developed a new model called the Small Hazardous Object detection enhanced and reconstructed Model based on the You Only Look Once version 5 (YOLOv5) algorithm to overcome these limitations. We also examined the performance of the proposed model through different experiments based on YOLOv5, a recently launched object detection model. The detection performance of our model was found to be enhanced by 0.3 in terms of the mean average precision (mAP) index and 1.1 in terms of mAP (.5:.95) with respect to the YOLOv5 model. The proposed model is especially useful for the detection of small objects of different types in overlapping environments where objects of different sizes are densely packed. The contributions of the study are reconstructed layers for the Small Hazardous Object detection enhanced and reconstructed Model based on YOLOv5 and the non-requirement of data preprocessing for immediate industrial application without any performance degradation.

• 한국정밀공학회지
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• 제19권11호
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• pp.54-64
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• 2002

This paper deals with the problem of synthesis of stable and optimal grasps with unknown objects by 3-finger hand. Previous robot grasp research has mainly analyzed with either unknown objects 2-dimensionally by vision sensor or known objects, such as cylindrical objects, 3-dimensionally. As extending the previous work, in this study we propose an algorithm to analyze grasp of unknown objects 3-dimensionally by using vision sensor. This is archived by two steps. The first step is to make a 3-dimensional geometrical model for unknown objects by using stereo matching. The second step is to find the optimal grasping points. In this step, we choose the 3-finger hand which has the characteristic of multi-finger hand and is easy to model. To find the optimal grasping points, genetic algorithm is employed and objective function minimizes the admissible force of finger tip applied to the objects. The algorithm is verified by computer simulation by which optimal grasping points of known objects with different angle are checked.

• 제어로봇시스템학회논문지
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• 제14권1호
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• pp.54-61
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• 2008

This paper proposes a new algorithm for detecting and recognizing overlapped objects among a stack of arbitrarily located objects using a signature representation scheme. The proposed algorithm consists of two processes of detecting overlap of objects and of determining the boundary between overlapping objects. To determine overlap of objects, in the first step, the edge image of object region is extracted and those areas in the object region are considered as the object areas if an area is surrounded by a closed edge. For each object, its signature image is constructed by measuring the distances of those edge points from the center of the object, along the angle axis, which are located at every angle with reference to the center of the object. When an object is not overlapped, its features which consist of the positions and angles of outstanding points in the signature are searched in the database to find its corresponding model. When an object is overlapped, its features are partially matched with those object models among which the best matching model is selected as the corresponding model. The boundary among the overlapping objects is determined by projecting the signature to the original image. The performance of the proposed algorithm has been tested with the task of picking the top or non-overlapped object from a stack of arbitrarily located objects. In the experiment, a recognition rate of 98% has been achieved.

• 한국통신학회논문지
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• 제12권5호
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• pp.415-427
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• 1987

본 논문은 겹친 2차원 물체 인식과 좌표이동에 관한 실험적 시각 시스템 설계와 알고리즘에 관한 연구이다. 대상 물체는 실제 공구를 사용하였고 공구의 모양은 변하지 않으며 평편하다고 가정한다. 인식 시스템에서의 영상내의 물체의 형태는 물체의 인식에 이용되는 형태로 서술된다. 입력 데이터는 물체의 윤곽선의 순차적 배열로 감축되고 윤곽 데이터는 다각 근사화에 의해 최소한의 윤곽 꼭지점으로 줄어든다. 인식은 모델과 새로 입력된 영상과의 매칭에서 유사성을 찾는 과정이다. 다음 모델에서 겹친 물체로의 좌표이동에 의하여 은선은 재구성된다. 최상의 매칭은 유사성 검출의 최적화에 의해 얻어진다.