• 한국컴퓨터정보학회논문지
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• 제8권2호
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• pp.31-36
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• 2003

본 논문은 주성분 분석에 의한 특징 탐색 기법의 가속화 방법을 제안하고 있다. 특징 탐색이란 주어진 영상이 찾고자 하는 특징을 포함하고 있는지의 여부를 판단하고, 만일 그 특징이 포함되어 있다면 그 위치와 영역을 결정하는 방법이다. 탐색 대상으로 하는 얼굴 또는 특징의 위치와 스케일을 미리 알 수 없으므로 모든 위치에서 다양한 스케일의 특징에 대한 존재 가능성을 계산해야하는데 이것은 방대한 공간에서의 탐색문제이다. 본 논문에서는 다단계 예측맵과 윤곽선 예측맵을 이용함으로써 탐색공간을 축소하고 빠른 얼굴 및 특징 탐색을 가능케하는 방법을 제안하고 있다. 실험결과, 제안된 방법이 기존의 전역탐색방법에 비하여 계산량을 10％이하로 줄일 수 있었다.

• 한국군사과학기술학회지
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• 제12권1호
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• pp.8-17
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• 2009

This paper proposes robust ship wake search method in the target evasion environment. Moving surface ships generate a long trailing wake in the rear of a surface ship. Wake homing torpedo sensing this wake can detect the surface target and engage it automatically. In wake homing torpedo, wake search method is important element to maximize effectiveness of wake homing torpedo. This paper proposes one-side, two-side and centering mode according to passing wake boundary scenarios. Also, wake deflection angle is deduced by using the principle of deflection angle of acoustic torpedo. The representative experimental results using monte-carlo simulation demonstrate that the searching method using one-side mode is superior to two-side and centering mode in the target evasion environment.

• 한국지능시스템학회논문지
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• 제15권4호
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• pp.406-411
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• 2005

본 논문에서는 다수 로봇의 목표물 탐색을 위한 area-based Q-learning 알고리즘에 대해 논한다. 선험적 정보가 없는 공간내의 목표물을 탐색하기 위해, 로봇들은 주위의 환경을 인식하고 스스로 다음 행동에 대한 결정을 내릴 수 있어야 한다. Area-based Q-learning에서, 먼저 각 로봇은 정육각형을 이루도록 배치된 6개의 적외선 센서를 통해 자신과 주변 환경 사이의 거리를 구한다. 다음으로 이 거리데이터들로부터 6방향의 면적(area)을 계산하여, 보다 넓은 행동반경을 보장해주는 영역으로 이동(action)한다. 이동 후 다시 6방향의 면적을 계산, 이전 상태에서의 이동에 대한 Q-value를 업데이트 한다. 본 논문의 실험에서는 5대의 로봇을 이용하여 선험적 지식이 없고, 장애물이 놓여 있는 공간에서의 목표물 탐색을 시도하였다. 결론에서는 3개의 제어 알고리즘-랜덤 탐색, area-based action making (ABAM), hexagonal area-based Q-learning - 을 이용하여 목표물 탐색을 시도한 결과를 보인다.

• 대한인간공학회지
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• 제31권6호
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• pp.705-713
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• 2012

Objective: The aim of this study is to predict human visual target search using ACT-R cognitive architecture in real scene images. Background: Human uses both the method of bottom-up and top-down process at the same time using characteristics of image itself and knowledge about images. Modeling of human visual search also needs to include both processes. Method: In this study, visual target object search performance in real scene images was analyzed comparing experimental data and result of ACT-R model. 10 students participated in this experiment and the model was simulated ten times. This experiment was conducted in two conditions, indoor images and outdoor images. The ACT-R model considering the first saccade region through calculating the saliency map and spatial layout was established. Proposed model in this study used the guide of visual search and adopted visual search strategies according to the guide. Results: In the analysis results, no significant difference on performance time between model prediction and empirical data was found. Conclusion: The proposed ACT-R model is able to predict the human visual search process in real scene images using salience map and spatial layout. Application: This study is useful in conducting model-based evaluation in visual search, particularly in real images. Also, this study is able to adopt in diverse image processing program such as helper of the visually impaired.

• 산업경영시스템학회지
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• 제38권4호
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• pp.11-21
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• 2015

In order to achieve success in ground operations, searching for moving targets is one of critical factors. Usually, the system of searching for adversary ground moving targets has complex properties which includes target's moving characteristics, camouflage level, terrain, weather, available search time window, distance between target and searcher, moving speed, target's tactics, etc. The purpose of this paper is to present a practical quantitative method for effectively searching for infiltrated moving targets considering aforementioned complex properties. Based upon search theories, this paper consists of two parts. One is infiltration route analysis, through terrain and mobility analysis. The other is building dynamic probability maps through Monte Carlo simulation to determine the prioritized searching area for moving targets. This study primarily considers ground moving targets' moving pattern. These move by foot and because terrain has a great effect on the target's movement, they generally travel along a constrained path. With the ideas based on the terrain's effect, this study deliberately performed terrain and mobility analysis and built a constrained path. In addition, dynamic probability maps taking terrain condition and a target's moving speed into consideration is proposed. This analysis is considerably distinct from other existing studies using supposed transition probability for searching moving targets. A case study is performed to validate the effectiveness and usefulness of our methodology. Also, this study suggests that the proposed approach can be used for searching for infiltrated ground moving target within critical time window. The proposed method could be used not only to assist a searcher's mission planning, but also to support the tactical commander's timely decision making ability and ensure the operations' success.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권10호
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• pp.4929-4947
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• 2017

In visual object tracking, Correlation Filter-based Tracking (CFT) systems have arouse recently to be the most accurate and efficient methods. The CFT's circularly shifts the larger search window to find most likely position of the target. The need of larger search window to cover both background and object make an algorithm sensitive to the background and the target occlusions. Further, the use of fixed-sized windows for training makes them incapable to handle scale variations during tracking. To address these problems, we propose two layer target representation in which both global and local appearances of the target is considered. Multiple local patches in the local layer provide robustness to the background changes and the target occlusion. The target representation is enhanced by employing additional reversed RGB channels to prevent the loss of black objects in background during tracking. The final target position is obtained by the adaptive weighted average of confidence maps from global and local layers. Furthermore, the target scale variation in tracking is handled by the statistical model, which is governed by adaptive constraints to ensure reliability and accuracy in scale estimation. The proposed structural enhancement is tested on VTBv1.0 benchmark for its accuracy and robustness.

• 한국경영과학회지
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• 제35권2호
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• pp.89-114
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• 2010

This study empirically investigated the effects of the target costing system as well as information technology(IT) infrastructure on the knowledge management processes(i.e., socialization, externalization, combination and internalization) and the performance of a firm. This study also examined an impact of the social capital(i.e., inter-departmental communication, trust, cooperation and integration) on the adoption and development of the target costing and the IT infrastructure. The results of this study showed that inter-departmental communication, trust and integration have a significant positive impact on the adoption of the target costing. It was also found that the effects of inter-departmental communication and integration on the development of storage and transfer infrastructure are significant and positive. However, in the adoption of search infrastructure, only the impact of inter-departmental integration was significant. The results of regression analyses presented that the target costing has significant influence on the four processes of knowledge management. It was also observed that the effects of storage and transfer infrastructure on combination are significant and positive. In search infrastructure, the impact on combination and internalization was significant. According to the results of this study, it was found that when the adoption level of the target costing is high, search infrastructure mainly affects the three processes(i.e., socialization, combination and internalization). However, under a low adoption level of the target costing, the impact of storage and transfer infrastructure on the whole processes was significant and positive. Thus, it is assumed that storage and transfer infrastructure complements a low level of the target costing adoption through the active transfer and sharing of explicit and tacit knowledge.

• 한국군사과학기술학회지
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• 제21권2호
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• pp.225-234
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• 2018

In this paper, we consider a problem of partitioning a search area into smaller rectangular regions, so that multiple platforms can conduct search operations independently without requiring unnecessary coordination among themselves. The search area consists of cells where each cell has some prior information regarding the probability of target existence. The detection probability in particular cell is evaluated by multiplying the observation probability of the platform and the target existence probability in that cell. The total detection probability within the search area is defined as the cumulative detection probability for each cell. However, since this search area partitioning problem is NP-Hard, we decompose the problem into three sequential phases to solve this computationally intractable problem. Additionally, we discuss a special case of this problem, which can provide an optimal analytic solution. We also examine the performance of the proposed approach by comparing our results with the optimal analytic solution.

• 방송공학회논문지
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• 제13권1호
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• pp.43-52
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• 2008

암호화된 다양한 멀티미디어 컨텐츠(multimedia contents)를 공개하고 사용자가 서버에게 검색어에 대한 정보를 들어내지 않고 검색어를 포함하고 있는 멀티미디어 컨텐츠를 검색하는 검색에서의 문제점을 연구한다. 최근 Ogata와 Kurosawa는 Oblivious Transfer의 개념을 이용하여 검색 프로토콜을 제안하였다. 하지만 그들의 방식은 하나의 검색어를 이용하여 데이터를 검색할 때 공개된 모든 암호화된 데이터 수만큼의 비교를 위한 계산량이 요구된다. 이러한 문제점을 해결하기 위해 본 논문에서는 사용자가 모든 데이터를 비교 검색하지 않아도 되는 Oblivious Transfer기술을 이용한 효율적인 검색 기술을 제안한다. 본 논문에서는 제안된 프로토콜이 RSA known target inversion 문제의 어려움에 기반을 두고 안전하다는 것을 보인다.

• 전자공학회논문지C
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• 제35C권1호
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• pp.25-33
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• 1998

This paepr presents an algorithm for searching an object in a fast way which contains a continuous moving object in multi-dimensional spatical databases. This algorithm improves the search method of R-tree for the case that a target object is continuously moving in a spatial database. It starts the searching from the current node instead of the root of R-tree. Thus, the algorithm will find the target object from the entries of current node or sibling nodes in the most cases. The performance analysis shows that it is more efficient than the existing algorithm for R-tree when search windows or target objects are continuously moving.