• Title/Summary/Keyword: Distance Function

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Clustering Method Using Characteristic Points with Marketing Data (마케팅자료에서 특성점들을 이용한 군집방법)

  • Moon Soog-Kyung;Kim Woo-Sung
    • Journal of Korean Society for Quality Management
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    • v.32 no.4
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    • pp.265-273
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    • 2004
  • We got the growth distance curve by spline smoothing method with observed marketing data and the growth velocity curve by the derivation of the growth distance curve. Using this growth velocity curve, we defined the several characteristic points which describe the variation of marketing data. In this paper, to specify several patterns of marketing data, we suggested characteristic function by using these characteristic points. In addition, we applied characteristic function to the seventeen brands of electric home products data.

Monocular Camera based Real-Time Object Detection and Distance Estimation Using Deep Learning (딥러닝을 활용한 단안 카메라 기반 실시간 물체 검출 및 거리 추정)

  • Kim, Hyunwoo;Park, Sanghyun
    • The Journal of Korea Robotics Society
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    • v.14 no.4
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    • pp.357-362
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    • 2019
  • This paper proposes a model and train method that can real-time detect objects and distances estimation based on a monocular camera by applying deep learning. It used YOLOv2 model which is applied to autonomous or robot due to the fast image processing speed. We have changed and learned the loss function so that the YOLOv2 model can detect objects and distances at the same time. The YOLOv2 loss function added a term for learning bounding box values x, y, w, h, and distance values z as 클래스ification losses. In addition, the learning was carried out by multiplying the distance term with parameters for the balance of learning. we trained the model location, recognition by camera and distance data measured by lidar so that we enable the model to estimate distance and objects from a monocular camera, even when the vehicle is going up or down hill. To evaluate the performance of object detection and distance estimation, MAP (Mean Average Precision) and Adjust R square were used and performance was compared with previous research papers. In addition, we compared the original YOLOv2 model FPS (Frame Per Second) for speed measurement with FPS of our model.

Robot motion planning for time-varying obstacle avoidance using distance function (거리 함수를 이용한 로보트의 시변 장애물 회피 동작계획)

  • 전흥주;고낙용;남윤석;이범희;고명삼
    • 제어로봇시스템학회:학술대회논문집
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    • 1991.10a
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    • pp.1034-1039
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    • 1991
  • A robot motion planning algorithm for time-varying obstacle avoidance is proposed. The robot motion planning problem is replaced with the optimization problem by using the distance function with the divided configuration space. To divide the configuration space, the polar coordinate system is used. For each divided configuration space, the admissible region where the robot can reach without collisions is obtained using the distance function. For an object moving in a plane, the admissible region is described by linear constraints on the polar coordinate system. A numerical algorithm that solves the optimization problem is shown and the computer simulation is carried out.

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Content similarity matching for video sequence identification

  • Kim, Sang-Hyun
    • International Journal of Contents
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    • v.6 no.3
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    • pp.5-9
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    • 2010
  • To manage large database system with video, effective video indexing and retrieval are required. A large number of video retrieval algorithms have been presented for frame-wise user query or video content query, whereas a few video identification algorithms have been proposed for video sequence query. In this paper, we propose an effective video identification algorithm for video sequence query that employs the Cauchy function of histograms between successive frames and the modified Hausdorff distance. To effectively match the video sequences with a low computational load, we make use of the key frames extracted by the cumulative Cauchy function and compare the set of key frames using the modified Hausdorff distance. Experimental results with several color video sequences show that the proposed algorithm for video identification yields remarkably higher performance than conventional algorithms such as Euclidean metric, and directed divergence methods.

Collision Avoidance Method Using Minimum Distance Functions for Multi-Robot System (최소거리함수를 이용한 다중 로보트 시스템에서의 충돌회피 방법)

  • Chang, C.;Chung, M.J.
    • Proceedings of the KIEE Conference
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    • 1987.11a
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    • pp.425-429
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    • 1987
  • This paper describes a collision avoidance method for planning safe trajectories for multi-robot system in common work space. Usually objects have been approximated to convex polyhedra in most previous researches, but in case using such the approximation method it is difficult to represent objects analytically in terms of functions and also to describe tile relationship between the objects. In this paper, in order to solve such problems a modeling method which approximates objects to cylinder ended by hemispheres and or sphere is used and the maximum distance functions is defined which call be calculated simply. Using an objective function with inequality constraints which are related to minimum distance functions, work range and maximum allowable angular velocities of the robots, tile collision avoidance for two robots is formulated to a constrained function optimization problem. With a view to solve tile problem a penalty function having simple form is defined and used. A simple numerical example involving two PUMA-type robots is described.

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Position Estimation of a Mobile Robot using Distance Error Weight Function (Distance Error Weight Function을 이용한 이동 로봇의 위치 추정 시스템의 설계)

  • Kho, Jee-Won;Park, Jae-Joon;Lee, Ki-Cheol;Park, Mig-Non
    • Proceedings of the KIEE Conference
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    • 1999.07g
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    • pp.3048-3050
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    • 1999
  • This paper suggests a position estimating algorithm using mono vision system with projective geometry method. Generally, 3-D information can not be easily extracted from mono vision system which is taken by a camera at a specific point. But this defect is overcome by adopting model-based image analysis and selecting lines and points on the ground as natural landmarks. And this paper suggests a method that estimates position from many natural landmarks by distance error weight function.

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Molecular Dynamic Study of a Polymeric Solution (I). Chain-Length Effect

  • Lee Young Seek;Ree Taikyue
    • Bulletin of the Korean Chemical Society
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    • v.3 no.2
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    • pp.44-49
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    • 1982
  • Dynamic and equilibrium structures of a polymer chain immersed in solvent molecules have been investigated by a molecular dynamic method. The calculation employs the Lennard-Jones potential function to represent the interactions between two solvent molecules (SS) and between a constituent particle (monomer unit) of the polymer chain and a solvent molecule (CS) as well as between two non-nearest neighbor constituent particles of the polymer chain (CC), while the chemical bond for nearest neighbor constituent particles was chosen to follow a harmonic oscillator potential law. The correlation function for the SS, CS and CC pairs, the end-to-end distance square and the radius of gyration square were calculated by varying the chain length (= 5, 10, 15, 20). The computed end-to-end distance square and the radius of gyration square were found to be in a fairly good agreement with the corresponding results from the random-flight model. Unlike earlier works, the present simulation rsesult shows that the autocorrelation function of radius of gyration square decays slower than that of the end-to-end distance square.

A Method of Reducing the Processing Cost of Similarity Queries in Databases (데이터베이스에서 유사도 질의 처리 비용 감소 방법)

  • Kim, Sunkyung;Park, Ji Su;Shon, Jin Gon
    • KIPS Transactions on Software and Data Engineering
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    • v.11 no.4
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    • pp.157-162
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    • 2022
  • Today, most data is stored in a database (DB). In the DB environment, the users requests the DB to find the data they wants. Similarity Query has predicate that explained by a similarity. However, in the process of processing the similarity query, it is difficult to use an index that can reduce the range of processed records, so the cost of calculating the similarity for all records in the table is high each time. To solve this problem, this paper defines a lightweight similarity function. The lightweight similarity function has lower data filtering accuracy than the similarity function, but consumes less cost than the similarity function. We present a method for reducing similarity query processing cost by using the lightweight similarity function features. Then, Chebyshev distance is presented as a lightweight similarity function to the Euclidean distance function, and the processing cost of a query using the existing similarity function and a query using the lightweight similarity function is compared. And through experiments, it is confirmed that the similarity query processing cost is reduced when Chebyshev distance is applied as a lightweight similarity function for Euclidean similarity.

Extraction of a Distance Parameter in Optical Scanning Holography Using Axis Transformation

  • Kim, Tae-Geun;Kim, You-Seok
    • Journal of the Optical Society of Korea
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    • v.14 no.2
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    • pp.104-108
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    • 2010
  • We proposed an axis transformation technique which reveals a distance parameter directly from optical scanning holography (OSH). After synthesis of a real-only spectrum hologram and power fringe adjusted filtering, we transform an original frequency axis to a new frequency axis using interpolation. In the new frequency axis, the filtered hologram has a single frequency which is linearly proportional to the distance parameter. Thus, the inverse Fourier transformation of the filtered hologram gives a delta function pair in the new spatial axis. Finally, we extract the distance parameter by detecting the location of the delta function pair.