• Title/Summary/Keyword: Unknown Object

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Borehole magnetics for the estimation of unknown foundation pile depth (시추공자력계를 이용한 기초파일 근입심도 추정)

  • Jo, Churl-Hyun;Chung, Hyun-Key;Cho, Kwang-Ho
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.3 no.2
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    • pp.161-167
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    • 1999
  • There is an increasing need for the estimation of foundation piles whose depths are unknown. Especially in repair and reinforcement works or in safety inspection and assessment to the big structures whose foundations are piles, the accurate information about the depth of foundation piles is one of the most important factors. A borehole magnetic tool has been developed and tested to meet this object. The fundamental base is that there usually exist many re-bars inside the foundation structure such as piles, and these re-bars are ferromagnetic materials which cause strong induced magnetic field comparable to the earth magnetic field. It utilizes flux-gate type magnetometer which measures 3-components of the magnetic field. Taking vertical derivatives of vertical component of the measured magnetic field, we can expect the error limit of estimating the depth of the pile end less than 20 cm in favorable condition. The maximum measurable distance is about 3 m to the pile from the borehole. The field data show that borehole magnetics is one of the most accurate, fast, and reliable methods for this object so far, as long as there is no magnetic materials such as deep located steel pipe or power cables close to the foundation piles.

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Back Analysis Method for Material Properties of Multi-layers Ground Considering Multiple Unknown Variables (다중 미지변수를 고려한 다층지반 역해석)

  • Kim, Se-Jin;Kim, Moon-Kyum;Won, Jong-Hwa;Kim, Jung-Soo
    • Journal of the Korean Geotechnical Society
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    • v.25 no.9
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    • pp.93-100
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    • 2009
  • A core procedure of the direct search method used in this study is optimizing a difference between objective function and real displacement and correcting unknown variables. Because the research procedure comes from back-analyzing of the unknown variable of each layer, back-analyzing results need an additional optimization to minimize interferential effects of unknown variables. Therefore, the direct search method Is used to obtain optimized solutions without a partial differentiation of an objective function. The object of this research is developing the back analysis technique for multi-unknown variables by modeling the soil including underground structure Into upper and lower layer. In order to minimize interferent errors, repeated back analysis is performed and applicability on the real tunnel is examined. Consequently, the multi-layer analysis model is more precise in describing the real behavior of underground structure. It shows the validity of back analysis far multi-layer model which is the understructure placed on multi-layer boundaries.

Performance Evaluation of Location Estimation System Using a Non Fixed Single Receiver

  • Myagmar, Enkhzaya;Kwon, Soon-Ryang
    • International Journal of Contents
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    • v.10 no.4
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    • pp.69-74
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    • 2014
  • General location aware systems are only applied to indoor and outdoor environments using more than three transmitters to estimate a fixed object location. Those kinds of systems have environmental restrictions that require an already established infrastructure. To solve this problem, an Object Location Estimation (OLE) algorithm based on PTP (Point To Point) communication has been proposed. However, the problem with this method is that deduction of performance parameters is not enough and location estimation is very difficult because of unknown restriction conditions. From experimental tests in this research, we determined that the performance parameters for restriction conditions are a maximum transmission distance of CSS communication and an optimum moving distance interval between personal locations. In this paper, a system applied OLE algorithm based on PTP communication is implemented using a CSS (Chirp Spread Spectrum) communication module. A maximum transmission distance for CSS communication and an optimum moving distance interval between personal locations are then deducted and studied to estimate a fixed object location for generalization.

Classification and Tracking of Unknown Multiple Underwater Moving Objects Using Neural Networks (신경망에 의한 미지의 다중 수중 이동물체의 판별 및 추적)

  • 하석운
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.3 no.2
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    • pp.389-396
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    • 1999
  • In this paper, we propose a multiple underwater object classification and tracking algorithm using the narrowband tonal and frequency line features extracted from the frequency spectrum of the acoustic signal. The general algorithm using the wideband and narrowband energy has a high tracking error when objects are close and cross each other. But the proposed algorithm shows a good tracking performance for the simulation scenarios generated by the real acoustic data.

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Robust Visual Tracking for 3-D Moving Object using Kalman Filter (칼만필터를 이용한 3-D 이동물체의 강건한 시각추적)

  • 조지승;정병묵
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2003.06a
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    • pp.1055-1058
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    • 2003
  • The robustness and reliability of vision algorithms is the key issue in robotic research and industrial applications. In this paper robust real time visual tracking in complex scene is considered. A common approach to increase robustness of a tracking system is the use of different model (CAD model etc.) known a priori. Also fusion or multiple features facilitates robust detection and tracking of objects in scenes of realistic complexity. Voting-based fusion of cues is adapted. In voting. a very simple or no model is used for fusion. The approach for this algorithm is tested in a 3D Cartesian robot which tracks a toy vehicle moving along 3D rail, and the Kalman filter is used to estimate the motion parameters. namely the system state vector of moving object with unknown dynamics. Experimental results show that fusion of cues and motion estimation in a tracking system has a robust performance.

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The 3-D Object Recognition Using the Shape from Stereo Algorithm (스테레오 기법의 형태정보를 이용한 3차원 물체 인식)

  • 박성만;곽윤식;이대영
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.24 no.8B
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    • pp.1500-1505
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    • 1999
  • In this paper, we presented the stereo algorithm for 3-D object recognition. In order to solve the problem for matching time in existed methods, we proposed the method which used the moving direction vector. On the other hand, after we extracted the moving vectors by moving direction of objects, rotated object was matched on axis of it. Using the Hough transform, we obtained the 2-D synthesed image as reference images corresponding to the rate of moving, and then compared with the unknown input images.

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Mobile Robot Navigation in Indoor Environments using Object Recognition

  • Lee, Won-Hee;Park, Min-Gyu;Lee, Min-Cheul;Kim, Dong-Soo
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.126.1-126
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    • 2001
  • Navigation in unknown environments, where the robot has no exact geometric information in advance, requires the robot to obtain the destination positions without a map. The utilization of model-based object recognition would be a solution, where the robot can estimate the destination positions from geometric relationships between the recognized objects and the robot. This paper presents a robot System for this kind of navigation, in Which the robot navigates itself to the room designated by room number. Object recognition technique is used to find a door and character recognition is utilized to interpret the room number on the number plate near the door and to determine whether it is the destination or not. The robot has ...

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Automatic Detection of Left Ventricular Contour from 2-D Echocardiograms using Fuzzy Hough Transform (퍼지 Hough 변환에 의한 2-D 심초음파도에서의 좌심실 윤곽 자동검출)

  • ;K.P
    • Journal of Biomedical Engineering Research
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    • v.13 no.2
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    • pp.115-124
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    • 1992
  • An algorithm has been proposed for the automatic detection of optimal epiand endocardial left ventricular borders from 2-D short axis echocardiogram which is degraded by noise and echo drop out. For the implementation of the algorithm, we modified Ballard's Generalized Hough Transform which can be applicable only for deterministic object border, and newly proposed Fuzzy Hough Transform method. The algorithm presented here allows detection of object whose exact shapes are unknown. The algorithm only requires an approximate model of target object based on anatomical data. To detect the approximate epicardial contour of left ventricle, Fuzzy Hough Transform was applied to the echocardiogram. The optimal epicardial contour was founded by using graph searching method which contains cost function analysis process. Using this optimal epicardial contour and average thickness imformation of left ventricular wall, the approximate endocardial line was founded, and graph searching method was also used to detect optimal endocardial contour.

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Simple Denoising Method for Novel Speckle-shifting Ghost Imaging with Connected-region Labeling

  • Yuan, Sheng;Liu, Xuemei;Bing, Pibin
    • Current Optics and Photonics
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    • v.3 no.3
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    • pp.220-226
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    • 2019
  • A novel speckle-shifting ghost imaging (SSGI) technique is proposed in this paper. This method can effectively extract the edge of an unknown object without achieving its clear ghost image beforehand. However, owing to the imaging mechanism of SSGI, the imaging result generally contains serious noise. To solve the problem, we further propose a simple and effective method to remove noise from the speckle-shifting ghost image with a connected-region labeling (CRL) algorithm. In this method, two ghost images of an object are first generated according to SSGI. A threshold and the CRL are then used to remove noise from the imaging results in turn. This method can retrieve a high-quality image of an object with fewer measurements. Numerical simulations are carried out to verify the feasibility and effectiveness.

Extended Kalman Filter Approach to Dynamic Electrical Impedance Tomography with Internal Electrodes

  • S.I. Kang;Kim, K.Y.;Kim, H.C.;Kim, M.C.;Kim, S.;Lee, H.J.;Lee, Y.J.;W.C. Cho
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.39.1-39
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    • 2001
  • Impedance tomography (EIT) is a relatively new imaging modality in which the internal impedivity distribution is reconstructed based on the known sets of injected currents through the electrodes and induced voltages on the surface of the object. We describe a dynamic EIT imaging technique for the case where the resistivity distribution inside the object changes rapidly within the time taken to acquire a full set of independent measurement data, In doing so, the inverse problem is treated as the nonlinear state estimation problem and the unknown state (resistivity) is estimated with the aid of extended Kalman filter in a minimum mean square error sense. In particular, additional electrodes are attached to the known internal structure of the object ...

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