• 한국컴퓨터산업학회논문지
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• 제3권8호
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• pp.1019-1026
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• 2002

이기종 분산환경에서 객체지향기술과 분산기술에 기반한 개방형 정보 통신망 구조의 연구가 진행되고 있다. 객체 그룹화의 목적은 다양하고 복잡한 분산 멀티미디어 서비스를 단순하게 관리하고 서비스를 지원하는데 있다. 본 논문은 이러한 분산 객체그룹 플랫폼 상에 편집자 직접조판을 위한 CTS를 설계한다. 논문의 결과로서 분산CTS 시스템의 기본구조와 객체들 간의 서비스 인터페이스를 설계한다.

• 한국시뮬레이션학회:학술대회논문집
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• 한국시뮬레이션학회 2004년도 춘계학술대회 논문집
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• pp.136-140
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• 2004

A power-plant simulation tool has been developed for training the plant operators and testing a plant control system. The simulation tool is composed of a graphic editor, a component model builder and a system simulation solver. Such new programing techniques as object-oriented modeling and GUI(Graphical User Interface) are employed in developing the simulation tool. The graphic editor is based on the OpenGL library for effective implementation of GUI while the component model builder is based on object-oriented programming for efficient generalization of component models. The developed tool has been verified through the simulation of a real power plant.

• 대한임베디드공학회논문지
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• 제19권2호
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• pp.91-99
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• 2024

Collision avoidance system is important to improve the robustness and functional safety of autonomous vehicles. This paper proposes an object-level distance estimation method to develop a collision avoidance system, and it is applied to golfcarts utilized in country club environments. To improve the detection accuracy, we continually trained an object detection model based on pseudo labels generated by a pre-trained detector. Moreover, we propose object-aware depth estimation (OADE) method which trains a depth model focusing on object regions. In the OADE algorithm, we generated dense depth information for object regions by utilizing detection results and sparse LiDAR points, and it is referred to as object-aware LiDAR projection (OALP). By using the OALP maps, a depth estimation model was trained by backpropagating more gradients of the loss on object regions. Experiments were conducted on our custom dataset, which was collected for the travel distance of 22 km on 54 holes in three country clubs under various weather conditions. The precision and recall rate were respectively improved from 70.5% and 49.1% to 95.3% and 92.1% after the continual learning with pseudo labels. Moreover, the OADE algorithm reduces the absolute relative error from 4.76% to 4.27% for estimating distances to obstacles.

• 대한전자공학회논문지SP
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• 제41권5호
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• pp.23-34
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• 2004

본 논문에서는 사전학습이 필요 없는 능동 특징점 모델(non-prior training active feature model; NPT AFM) 기반에서 광류(optical flow)를 이용한 객체추적 기술을 제안한다. 제안한 알고리듬은 비정형 객체에 대한 분석[1]에 초점을 두고 있으며, 실시간에서 NPT-AFM을 사용한 강건한 추적을 가능하게 한다. NPT-AFM 알고리듬은 관심 객체의 위치를 파악하는 과정 (localization)과 이전 프레임 정보와 현재 프레임 정보를 이용하여, 객체의 위치를 예측(prediction), 보정(correction)하는 과정으로 나눌 수 있다 위치 파악 과정에서는 움직임 분할(motion segmentation)을 수행한 후 개선된 Shi-Tomasi의 특징점 추적 알고리듬[2]을 사용 하였다. 예측 및 보정 과정에서는 광류 정보를 사용하여 특징점을 추적하고[3] 만약, 특징점이 적절히 추적 되지 않거나 추적에 실패하면 특징점들의 시간(temporal), 공간(spatial)적 정보를 이용하여 예측, 보정하게 된다. 객체의 형태 (shape)대신 특징점을 사용하였으며, 객체를 추적하는 과정에서 특징점들은 능동 특징점 모델(active feature model; AFM)을 위한 학습 집합(training sets)의 요소로 갱신된다. 실험결과, 제안한 NPT-AF% 기반 추적 알고리듬은 실시간에서 비정형 객체를 추적하는데 강건함을 보석준다.

• 경영과학
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• 제14권1호
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• pp.87-105
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• 1997

There have been lots of research on temporal data management for the past two decades. Most of them are based on some logical data model, especially on the relational data model, although there are some conceptual data models which are independent of logical data models. Also, many properties or issues regarding temporal data models and temporal query languages have been studied. But some of them were shown to be incompatible, which means there could not be a complete temporal data model, satisfying all the desired properties at the same time. Many modeling issues discussed in the papers, do not have to be done so, if they take object-oriented data model as a base model. Therefore, this paper proposes a temporal data model, which is based on the object-oriented data model, mainly discussing the most essential issues that are common to many temporal data models. Our new temporal data model and query language will be illustrated with a small database, created by a set of sample transaction.

• 한국경영과학회지
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• 제14권1호
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• pp.87-87
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• 1989

There have been lots of research on temporal data management for the past two decades. Most of them are based on some logical data model, especially on the relational data model, although there are some conceptual data models which are independent of logical data models. Also, many properties or issues regarding temporal data models and temporal query languages have been studied. But some of them were shown to be incompatible, which means there could not be a complete temporal data model, satisfying all the desired properties at the same time. Many modeling issues discussed in the papers, do not have to be done so, if they take object-oriented data model as a base model. Therefore, this paper proposes a temporal data model, which is based on the object-oriented data model, mainly discussing the most essential issues that are common to many temporal data models. Our new temporal data model and query language will be illustrated with a small database, created by a set of sample transaction.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제4권3호
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• pp.358-379
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• 2010

Multiple object association is an important capability in visual surveillance system with multiple cameras. In this paper, we introduce locally initiating line-based object association with the parallel projection camera model, which can be applicable to the situation without the common (ground) plane. The parallel projection camera model supports the camera movement (i.e. panning, tilting and zooming) by using the simple table based compensation for non-ideal camera parameters. We propose the threshold distance based homographic line generation algorithm. This takes account of uncertain parameters such as transformation error, height uncertainty of objects and synchronization issue between cameras. Thus, the proposed algorithm associates multiple objects on demand in the surveillance system where the camera movement dynamically changes. We verify the proposed method with actual image frames. Finally, we discuss the strategy to improve the association performance by using the temporal and spatial redundancy.

• 한국지능시스템학회논문지
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• 제18권3호
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• pp.291-296
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• 2008

본 논문에서는 군집로봇시스템에서 목표물 추적을 위하여 SVM을 이용한 12각형 기반의 Q-learning 알고리즘을 제안한다. 제안한 알고리즘의 유효성을 보이기 위해 본 논문에서는 여러 대의 로봇과 장애물 그리고 하나의 목표물로 정하고, 각각의 로봇이 숨겨진 목표물을 찾아내는 실험을 가정하여 무작위, DBAM과 AMAB의 융합 모델, 마지막으로는 본 논문에서 제안한 SVM과 12각형 기반의 Q-learning 알고리즘을 이용하여 실험을 수행하고, 이 3가지 방법을 비교하여 본 논문의 유효성을 검증하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권4호
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• pp.1989-2011
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• 2019

Vehicle detection based on aerial images is an interesting and challenging research topic. Most of the traditional vehicle detection methods are based on the sliding window search algorithm, but these methods are not sufficient for the extraction of object features, and accompanied with heavy computational costs. Recent studies have shown that convolutional neural network algorithm has made a significant progress in computer vision, especially Faster R-CNN. However, this algorithm mainly detects objects in natural scenes, it is not suitable for detecting small object in aerial view. In this paper, an accurate and effective vehicle detection algorithm based on Faster R-CNN is proposed. Our method fuse a hyperactive feature map network with Eltwise model and Concat model, which is more conducive to the extraction of small object features. Moreover, setting suitable anchor boxes based on the size of the object is used in our model, which also effectively improves the performance of the detection. We evaluate the detection performance of our method on the Munich dataset and our collected dataset, with improvements in accuracy and effectivity compared with other methods. Our model achieves 82.2% in recall rate and 90.2% accuracy rate on Munich dataset, which has increased by 2.5 and 1.3 percentage points respectively over the state-of-the-art methods.

• Journal of Information Technology Applications and Management
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• 제14권3호
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• pp.49-77
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• 2007

Role-based access control (RBAC) models are recently receiving considerable attention as a generalized approach to access control. In line with the increase in applications that deal with spatial data. an advanced RBAC model whose entities and constraints depend on the characteristics of spatial data is required. Even if some approaches have been proposed for geographic information systems. most studies focus on the location of users instead of the characteristics of spatial data. In this paper. we extend the traditional RBAC model in order to deal with the characteristics of spatial data and propose new spatial constraints. We use the object-oriented modeling based on open GIS consortium geometric model to formalize spatial objects and spatial relations such as hierarchy relation and topology relation. As a result of the formalization for spatial relations. we present spatial constraints classified according to the characteristics of each relation. We demonstrate our extended-RBAC model called OOGIS-RBAC and spatial constraints through case studies. Finally. we compare our OOGIS-RBAC model and the DAC model in the management of access control to prove the efficiency of our model.