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Development of Delaunay Triangulation Algorithm Using Oct-subdivision in Three Dimensions (3차원 8분할 Delaunay 삼각화 알고리즘 개발)

  • Park S.H.;Lee S.S.
    • Korean Journal of Computational Design and Engineering
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    • v.10 no.3
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    • pp.168-178
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    • 2005
  • The Delaunay triangular net is primarily characterized by a balance of the whole by improving divided triangular patches into a regular triangle, which closely resembles an equiangular triangle. A triangular net occurring in certain, point-clustered, data is unique and can always create the same triangular net. Due to such unique characteristics, Delaunay triangulation is used in various fields., such as shape reconstruction, solid modeling and volume rendering. There are many algorithms available for Delaunay triangulation but, efficient sequential algorithms are rare. When these grids involve a set of points whose distribution are not well proportioned, the execution speed becomes slower than in a well-proportioned grid. In order to make up for this weakness, the ids are divided into sub-grids when the sets are integrated inside the grid. A method for finding a mate in an incremental construction algorithm is to first search the area with a higher possibility of forming a regular triangular net, while the existing method is to find a set of points inside the grid that includes the circumscribed sphere, increasing the radius of the circumscribed sphere to a certain extent. Therefore, due to its more efficient searching performance, it takes a shorer time to form a triangular net than general incremental algorithms.

New Acoustic Imaging Method Development for Localization of an Underground Acoustic Source Using a Passive SONAR System

  • Jarng, Soon-Suck
    • The Journal of the Acoustical Society of Korea
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    • v.18 no.2E
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    • pp.10-17
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    • 1999
  • The aim of the work described in this paper is to develop a complex underground acoustic system which detects and localizes the origin of an underground hammering sound using an array of hydrophones located about 100m underground. Three different methods for the sound localization will be presented, a time-delay method, a power-attenuation method and a hybrid method. In the time-delay method, the cross correlation of the signals received from the array of sensors is used to calculate the time delays between those signals. In the power-attenuation method, the powers of the received signals provide a measure of the distances of the source from the sensors. In the hybrid method, both informations of time-delays and power-ratios are coupled together to produce better performance of position estimation. A new acoustic imaging technique has been developed for improving the hybrid method. This new acoustic imaging method shows the multi-dimensional distribution of the normalized cost function, so as to indicate the trend of the minimizing direction toward the source location. For each method the sound localization is carried out in three dimensions underground. The distance between the true and estimated origins of the source is 28m for a search area of radius 250m.

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Beacon-Based O2O Marketing for Financial Institutions

  • Kwon, Young-Man;Park, Jin-Soo;Lee, Hyun-Jong;Kim, Myung-Gwan
    • The Journal of Industrial Distribution & Business
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    • v.5 no.4
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    • pp.23-29
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    • 2014
  • Purpose - This thesis aims to propose a method to help financial institutions improve their customers' convenience online and offline through a Bluetooth based App using the tool of a beacon. The emergence of smartphones in the 21st century and their increasing use makes it possible to search for information easily. Research design, data, and methodology - With the short-distance Bluetooth technology for smartphones, which finds users within a radius of 50m to provide the functions of message transmission and mobile payment, users can access information services and use mobile coupons in certain premises. Thus, beacon-based O2O technology has been developed. Results - This study offers a method of attracting customers through an O2O marketing strategy that overcomes the existing limitations of Web and Offline media. Conclusions -Since beacon technology has the advantage of more accurate positioning than GPS, financial institutions provide their product information for users through the basic function of a beacon, using an O2O (Online to Offline) marketing solution and, therefore, effectively enable customers to make relevant payments online and conduct their financial actions offline.

Development of Halfway Station Recommendation Application Using Dijkstra's Algorithm (다익스트라 알고리즘을 활용한 중간지점 추천 애플리케이션 개발)

  • Park, Naeun;Mun, Jiyeon;Jeoung, Yuna;Cho, Seoyeon;Huh, Won Whoi
    • Journal of Korea Multimedia Society
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    • v.24 no.2
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    • pp.312-319
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    • 2021
  • This study aims to help users to have a more satisfying encounter based on the problems found by comparing and analyzing similar applications. That is, an application that derives intermediate points through the subway, which is a public transportation means, and provides information on nearby convenience facilities was proposed. The middle point calculation process uses the dijkstra algorithm, which stores the minimum number of nodes in the stored path from the first input location to the last location. The stack and arraylist are used to search all paths from the first input position to the last position, and then the path with the smallest number of nodes is selected. After that, the number of stations in the route is divided in half and the resulting station is output. In addition, this study provides information on convenience facilities near intermediate points in order to have differences from similar applications. It categorizes within a 1km radius of the point and provides a function that helps to conveniently identify only facilities around the middle point. In particular, by visualizing the number of convenience facilities with radar charts and numbers, it is possible to grasp the commercial district around the midpoint at a glance.

Combined Image Retrieval System using Clustering and Condensation Method (클러스터링과 차원축약 기법을 통합한 영상 검색 시스템)

  • Lee Se-Han;Cho Jungwon;Choi Byung-Uk
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.43 no.1 s.307
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    • pp.53-66
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    • 2006
  • This paper proposes the combined image retrieval system that gives the same relevance as exhaustive search method while its performance can be considerably improved. This system is combined with two different retrieval methods and each gives the same results that full exhaustive search method does. Both of them are two-stage method. One uses condensation of feature vectors, and the other uses binary-tree clustering. These two methods extract the candidate images that always include correct answers at the first stage, and then filter out the incorrect images at the second stage. Inasmuch as these methods use equal algorithm, they can get the same result as full exhaustive search. The first method condenses the dimension of feature vectors, and it uses these condensed feature vectors to compute similarity of query and images in database. It can be found that there is an optimal condensation ratio which minimizes the overall retrieval time. The optimal ratio is applied to first stage of this method. Binary-tree clustering method, searching with recursive 2-means clustering, classifies each cluster dynamically with the same radius. For preserving relevance, its range of query has to be compensated at first stage. After candidate clusters were selected, final results are retrieved by computing similarities again at second stage. The proposed method is combined with above two methods. Because they are not dependent on each other, combined retrieval system can make a remarkable progress in performance.

Optimization of PRISM Parameters and Digital Elevation Model Resolution for Estimating the Spatial Distribution of Precipitation in South Korea (남한 강수량 분포 추정을 위한 PRISM 매개변수 및 수치표고모형 최적화)

  • Park, Jong-Chul;Jung, Il-Won;Chang, Hee-Jun;Kim, Man-Kyu
    • Journal of the Korean Association of Geographic Information Studies
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    • v.15 no.3
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    • pp.36-51
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    • 2012
  • The demand for a climatological dataset with a regular spaced grid is increasing in diverse fields such as ecological and hydrological modeling as well as regional climate impact studies. PRISM(Precipitation-Elevation Regressions on Independent Slopes Model) is a useful method to estimate high-altitude precipitation. However, it is not well discussed over the optimization of PRISM parameters and DEM(Digital Elevation Model) resolution in South Korea. This study developed the PRISM and then optimized parameters of the model and DEM resolution for producing a gridded annual average precipitation data of South Korea with 1km spatial resolution during the period 2000-2005. SCE-UA (Shuffled Complex Evolution-University of Arizona) method employed for the optimization. In addition, sensitivity analysis investigates the change in the model output with respect to the parameter and the DEM spatial resolution variations. The study result shows that maximum radius within which station search will be conducted is 67km. Minimum radius within which all stations are included is 31km. Minimum number of stations required for cell precipitation and elevation regression calculation is four. Optimizing DEM resolution is $1{\times}1km$. This study also shows that the PRISM output very sensitive to DEM spatial resolution variations. This study contributes to improving the accuracy of PRISM technique as it applies to South Korea.

The Statistically and Economically Significant Clustering Method for Economic Clusters in an Urban Region (통계적 및 경제적 유의성을 가진 경제 클러스터 탐식방법에 대한 연구)

  • Shin Jungyeop
    • Journal of the Korean Geographical Society
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    • v.40 no.2 s.107
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    • pp.187-201
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    • 2005
  • With the trend of urban polynucleation, the issue of detecting economic clusters or urban employment centers has been considered as crucial. However, the prior researches had some limitations in detecting economic clusters in the empirical analysis: i.e. inherent inefficiency of density-based clustering methods, difficulty in detecting linear types of spatial clusters and lacks of consideration of economic significance. The purpose of this paper is to propose the clustering method with the procedure of testing statistical and economic significance named as VCEC (Variable Clumping method for Economic Clusters) and to apply it to a case analysis of Erie County, New York, in order to test its validity. By applying a search radius and a total employment as an economic threshold, 'the both statistically and economically significant clusters' were detected in the Erie County, and proved to be efficient.

Personal Identification Using One Dimension Iris Signals (일차원 홍채 신호를 이용한 개인 식별)

  • Park, Yeong-Gyu;No, Seung-In;Yun, Hun-Ju;Kim, Jae-Hui
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.39 no.1
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    • pp.70-76
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    • 2002
  • In this paper, we proposed a personal identification algorithm using the iris region which has discriminant features. First, we acquired the eye image with the black and white CCD camera and extracted the iris region by using a circular edge detector which minimizes the search space for real center and radius of the iris. And then, we localized the iris region into several circles and extracted the features by filtering signals on the perimeters of circles with one dimensional Gabor filter We identified a person by comparing ,correlation values of input signals with the registered signals. We also decided threshold value minimizing average error rate for FRR(Type I)error rate and FAR(Type II)error rate. Experimental results show that proposed algorithm has average error rate less than 5.2%.

Obstacle Avoidance for Unmanned Air Vehicles Using Monocular-SLAM with Chain-Based Path Planning in GPS Denied Environments

  • Bharadwaja, Yathirajam;Vaitheeswaran, S.M;Ananda, C.M
    • Journal of Aerospace System Engineering
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    • v.14 no.2
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    • pp.1-11
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    • 2020
  • Detecting obstacles and generating a suitable path to avoid obstacles in real time is a prime mission requirement for UAVs. In areas, close to buildings and people, detecting obstacles in the path and estimating its own position (egomotion) in GPS degraded/denied environments are usually addressed with vision-based Simultaneous Localization and Mapping (SLAM) techniques. This presents possibilities and challenges for the feasible path generation with constraints of vehicle dynamics in the configuration space. In this paper, a near real-time feasible path is shown to be generated in the ORB-SLAM framework using a chain-based path planning approach in a force field with dynamic constraints on path length and minimum turn radius. The chain-based path plan approach generates a set of nodes which moves in a force field that permits modifications of path rapidly in real time as the reward function changes. This is different from the usual approach of generating potentials in the entire search space around UAV, instead a set of connected waypoints in a simulated chain. The popular ORB-SLAM, suited for real time approach is used for building the map of the environment and UAV position and the UAV path is then generated continuously in the shortest time to navigate to the goal position. The principal contribution are (a) Chain-based path planning approach with built in obstacle avoidance in conjunction with ORB-SLAM for the first time, (b) Generation of path with minimum overheads and (c) Implementation in near real time.

Modified Scan Line Based Generalized Symmetry Transform with Selectively Directional Attention (선택적 방향주의를 가지는 수정된 스캔라인 일반화 대칭 변환)

  • Kim, Dong-Su;Jin, Seong-Il
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.38 no.4
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    • pp.411-421
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    • 2001
  • The generalized symmetry transform evaluates symmetry without segmentation and extracts regions of interest in an image by combining locality and reflectional symmetry The demand that the symmetry transform be local is reflected by the distance weight function. When calculating large regions-of-interest, we should select a large standard deviation of distance weight function. But such a large standard deviation makes the execution time increase in the second power of r, which is a radius of search area. In this paper we propose modified scan line based GST with selectively directional attention to improve time complexity The symmetry map of our proposed GST is found to be very similar to that of the existing GST. However the computation time of the proposed GST increases linearly with respect to r because our proposed GST evaluates symmetry between a pair of edge pixels along the scan lines. The GST computation decreases considerably when the proposed GST is peformed with selectively directional attention in case of large r. Several experiments in this paper demonstrate the time efficiency and the usefulness of our proposed GST.

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