• Title/Summary/Keyword: 탐색 범위

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Efficient restriction of route search area in cluster based wireless ad hoc networks (클러스터 기반 무선 애드 혹 네트워크에서의 효율적인 경로 탐색 지역 제어)

  • Lee, Jangsu;Kim, Sungchun
    • Proceedings of the Korea Information Processing Society Conference
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    • 2012.11a
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    • pp.792-795
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    • 2012
  • 애드 혹 네트워크(MANET: Mobile Ad hoc NETworks)는 기본적인 내부구조(infrastructure) 없이 노드들만으로 네트워크 망을 구성한다. 경로 탐색 정책으로 리액티브(reactive) 방식과 프로액티브(proactive) 방식이 있는데, 전통적으로 리액티브 방식의 성능이 더 좋은 것으로 평가된다. 그리고 두가지 방식의 장점을 취합한 하이브리드(hybrid) 방식의 클러스터 토폴로지(cluster topology) 도입에 관한 연구가 이루어지고 있다. 그 중, HCR(Hybrid Cluster Routing)이 제안되었는데, 이는 프로액티브 방식에 보다 중심을 둔 기법이다. HCR 은 리액티브 방식 경로 탐색 방법인 플라딩(flooding)의 탐색 지역을 한정된 범위로 제한할 수 있으나, 프로액티브 방식의 전체 네트워크 구성 정보 유지에 따른 막대한 오버헤드를 발생한다. 본 논문에서는 이러한 오버헤드를 줄이기 위해, 클러스터 내부 경로 탐색 기법인 MICF(Maginot path based Intra Cluster Flooding)를 제안한다. MICF 는 HCR 을 개선한 FSRS(First Search and Reverse Setting) 기반의 기법으로서, 클러스터 내부의 마지노 패스(maginot path)를 기준으로 경로 탐색 지역을 제한한다. MICF 는 게이트웨이(gateway) 간 최단 거리가 항상 클러스터 헤드(cluster head)를 중점으로 원의 내각 지역에 존재함을 바탕으로 하며, 최단 경로의 보장과 플라딩 지역 제한을 동시에 만족한다. 실험 결과, MICF 는 FSRS 기반의 기존 클러스터 내부 플라딩 방식보다 총 에너지의 7.79%만큼 더 에너지를 보존하였다. 결론적으로, MICF 역시 기존의 방식보다 에너지를 더 효율적으로 사용할 수 있으며, 마지노패스 설정과 이를 기반으로 한 제어 과정에 추가적인 오버헤드가 발생하지 않는다. 그리고 플라딩 면적이 작을수록 오버헤드가 줄어들게 됨을 알 수 있다.

Binary Image Search using Hierarchical Bintree (계층적 이분트리를 활용한 이진 이미지 탐색 기법)

  • Kim, Sung Wan
    • Journal of Creative Information Culture
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    • v.6 no.1
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    • pp.41-48
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    • 2020
  • In order to represent and process spatial data, hierarchical data structures such as a quadtree or a bintree are used. Various approaches for linearly representing the bintree have been proposed. S-Tree has the advantage of compressing the storage space by expressing binary region image data as a linear binary bit stream, but the higher the resolution of the image, the longer the length of the binary bit stream, the longer the storage space and the lower the search performance. In this paper, we construct a hierarchical structure of multiple separated bintrees with a full binary tree structure and express each bintree as two linear binary bit streams to reduce the range required for image search. It improves the overall search performance by performing a simple number conversion instead of searching directly the binary bit string path. Through the performance evaluation by the worst-case space-time complexity analysis, it was analyzed that the proposed method has better search performance and space efficiency than the previous one.

Performance Improvement of Traffic Identification by Categorizing Signature Matching Type (시그니쳐 매칭 유형 분류를 통한 트래픽 분석 시스템의 처리 속도 향상)

  • Jung, Woo-Suk;Park, Jun-Sang;Kim, Myung-Sup
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.40 no.7
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    • pp.1339-1346
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    • 2015
  • The traffic identification is a preliminary and essential step for stable network service provision and efficient network resource management. While a number of identification methods have been introduced in literature, the payload signature-based identification method shows the highest performance in terms of accuracy, completeness, and practicality. However, the payload signature-based method's processing speed is much slower than other identification method such as header-based and statistical methods. In this paper, we first classifies signatures by matching type based on range, order, and direction of packet in a flow which was automatically extracted. By using this classification, we suggest a novel method to improve processing speed of payload signature-based identification by reducing searching space.

Mutual Information-based Circular Template Matching for Image Registration (영상등록을 위한 Mutual Information 기반의 원형 템플릿 정합)

  • Ye, Chul-Soo
    • Korean Journal of Remote Sensing
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    • v.30 no.5
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    • pp.547-557
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    • 2014
  • This paper presents a method for designing circular template used in similarity measurement for image registration. Circular template has translation and rotation invariant property, which results in correct matching of control points for image registration under the condition of translation and rotation between reference and sensed images. Circular template consisting of the pixels located on the multiple circumferences of the circles whose radii vary from zero to a certain distance, is converted to two-dimensional Discrete Polar Coordinate Matrix (DPCM), whose elements are the pixels of the circular template. For sensed image, the same type of circular template and DPCM are created by rotating the circular template repeatedly by a certain degree in the range between 0 and 360 degrees and then similarity is calculated using mutual information of the two DPCMs. The best match is determined when the mutual information for each rotation angle at each pixel in search area is maximum. The proposed algorithm was tested using KOMPSAT-2 images acquired at two different times and the results indicate high accurate matching performance under image rotation.

Hyperparameter Optimization for Image Classification in Convolutional Neural Network (합성곱 신경망에서 이미지 분류를 위한 하이퍼파라미터 최적화)

  • Lee, Jae-Eun;Kim, Young-Bong;Kim, Jong-Nam
    • Journal of the Institute of Convergence Signal Processing
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    • v.21 no.3
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    • pp.148-153
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    • 2020
  • In order to obtain high accuracy with an convolutional neural network(CNN), it is necessary to set the optimal hyperparameters. However, the exact value of the hyperparameter that can make high performance is not known, and the optimal hyperparameter value is different based on the type of the dataset, therefore, it is necessary to find it through various experiments. In addition, since the range of hyperparameter values is wide and the number of combinations is large, it is necessary to find the optimal values of the hyperparameters after the experimental design in order to save time and computational costs. In this paper, we suggest an algorithm that use the design of experiments and grid search algorithm to determine the optimal hyperparameters for a classification problem. This algorithm determines the optima values of the hyperparameters that yields high performance using the factorial design of experiments. It is shown that the amount of computational time can be efficiently reduced and the accuracy can be improved by performing a grid search after reducing the search range of each hyperparameter through the experimental design. Moreover, Based on the experimental results, it was shown that the learning rate is the only hyperparameter that has the greatest effect on the performance of the model.

The Accuracy Analysis of SIV(Surface Image Velocimetry) Associated with Correlation Coefficient (상관계수에 따른 표면영상유속계의 정확도 분석)

  • Joo, Yong-Woo;Kim, Seo-Jun;Yu, Kwoon-Kyu;Yoon, Byung-Man
    • Proceedings of the Korea Water Resources Association Conference
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    • 2009.05a
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    • pp.1894-1897
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    • 2009
  • 최근 개발된 표면영상유속계(Surface Image Velocimetry)를 이용한 유량측정기법은 비교적 짧은 시간에 급변하는 홍수량을 정확도를 유지하면서도 간편하고 안전하게 측정할 수 있다는 장점이 있다. 그러나 표면영상유속계는 현장 상황과 사용 방법에 따라 측정된 유속값의 오차가 얼마나 발생하는지에 대한 근거가 없으며, 그 오차 범위가 명확하게 제시된 바가 없기 때문에 표면영상유속계의 신뢰성에 대해 의구심을 갖는 경우가 많다. 표면영상유속계의 유속측정 원리는 일정 시간간격을 갖는 두 영상내의 입자군 이동을 추적하여 유속벡터를 산정하는 것이다. 즉, 두 영상의 탐색 영역(searching area)내에서 각 입자군의 상관계수를 계산하여 최대상관계수를 갖는 입자군을 동일 입자군으로 판별하고, 동일 입자군의 도심간 거리와 두 영상의 시간간격을 이용하여 유속을 구하게 된다. 그러므로 상관계수가 높을수록 유속값이 정확하다고 할 수 있다. 따라서 본 연구에서는 상관계수에 따른 유속측정 오차를 분석하여 상관계수에 따른 표면영상유속계의 오차범위를 결정하고자 한다. 분석방법은 활차의 속도와 영상분석을 통해 얻은 속도를 비교하여 상관계수에 따른 오차범위를 살펴보았고, 실제 적용을 위하여 개수로내의 표면유속를 측정하여 상관계수에 따른 오차를 분석하였다. 분석 결과 상관계수가 0.7 이상인 측정유속의 정확도는 10% 이내로 확인되었으며, 향후 표면영상 유속계를 이용한 유속측정시 상관계수별 오차범위를 이용하여 현장적용시 정확도 개선을 위해 많은 도움이 될 것으로 기대된다.

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Iterative Generalized Hough Transform using Multiresolution Search (다중해상도 탐색을 이용한 반복 일반화 허프 변환)

  • ;W. Nick Street
    • Journal of KIISE:Software and Applications
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    • v.30 no.10
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    • pp.973-982
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    • 2003
  • This paper presents an efficient method for automatically detecting objects in a given image. The GHT is a robust template matching algorithm for automatic object detection in order to find objects of various shapes. Many different templates are applied by the GHT in order to find objects of various shapes and size. Every boundary detected by the GHT scan be used as an initial outline for more precise contour-finding techniques. The main weakness of the GHT is the excessive time and memory requirements. In order to overcome this drawback, the proposed algorithm uses a multiresolution search by scaling down the original image to half-sized and quarter-sized images. Using the information from the first iterative GHT on a quarter-sized image, the range of nuclear sizes is determined to limit the parameter space of the half-sized image. After the second iterative GHT on the half-sized image, nuclei are detected by the fine search and segmented with edge information which helps determine the exact boundary. The experimental results show that this method gives reduction in computation time and memory usage without loss of accuracy.

The feature of scanning path algorithm shown at natural visual search activities of space user (공간사용자의 본능적 시선탐색활동에 나타난 주사경로 알고리즘 특성)

  • Kim, Jong-Ha;Kim, Ju-Yeon
    • Science of Emotion and Sensibility
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    • v.17 no.2
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    • pp.111-122
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    • 2014
  • This study has analyzed the scanning path algorithm shown at the process of exploring spatial information through an observation experiment with the object of lobby in subway station. In the estimation of observation time by section, the frequency of scanning type was found to increase as the observation time got longer, which makes it possible that the longer the observation lasts the more the observation interruptions occur. In addition, the observation slipped out of the range of imaging when any fatigue was caused from the observation or the more active exploration took place. Furthermore, when the trend line was employed for the examination of the changes to the scanning type by time section, "concentration" "diagonal or vertical" showed a sharp and a gentle increases along with the increase of time section respectively, while "circulation. combination, horizontal" showed a reduction. The observation data of the subjects observing a space include various visual information. The analysis of the scanning type found at "attention concentration" enabled to draw this significant conclusion. The features of increase and decrease of scanning types can be a fundamental data for understanding the scanning tendency by time.

A Study on the Effects of Digital Platform Capabilities and Customer Orientation of Financial Institutions on Service Innovation Behavior (금융기관의 디지털플랫폼역량과 고객지향성이 서비스혁신행동에 미치는 영향연구)

  • Kim, Sang-Chul;Seo, Young-Wook
    • Journal of Digital Convergence
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    • v.18 no.10
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    • pp.207-217
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    • 2020
  • The purpose of this study is to examine the structural relationship between the digital platform capabilities of financial institutions and the impact of customer orientation on service innovation behavior through exploitation/exploration. A survey was conducted on employees of financial institutions to verify the research model, and the final 280 copies of the questionnaire were analyzed using SPSS 25 and SmartPLS 2.0. As a major research result, First, digital platform competency has a positive effect on exploitation and exploration. Second, customer orientation has a positive effect on exploitation, but not on exploration. Third, both exploitation and exploration have a positive impact on service innovation behavior. Through this research, this study shed new light on the relationship between digital platform capability and customer orientation that affects service innovation behavior of financial institutions, and expanded the scope of research through empirical research. Future research will require research attempts on various variables and research samples.

Motion Estimation Algorithm to Guarantee Hard Realtime Operation (경성 실시간 동작을 보장하는 움직임 추정 알고리즘)

  • Yang, Hyeon-Cheol;Lee, Seongsoo
    • Journal of IKEEE
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    • v.17 no.1
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    • pp.36-43
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    • 2013
  • This paper proposes a motion estimation algorithm with run-time adaptive workload control. It has optimized performance within limited hardware resources while guaranteeing hard realtime operation. It performs maximum searches within hard realtime constraints, since it determines search steps and workload adaptively. It reduces the hardware size to 1/4~1/400 of conventional algorithms, while its PSNR degradation is only 0.02~0.44 dB. It can be easily applied to most conventional fast algorithms, so it is useful to design realtime encoder chips.