• Title/Summary/Keyword: maximum detection depth

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Effect of geometry of underground structure and electrode on electrical resistance measurement: A numerical study

  • Tae-Young Kim;Hee-Hwan Ryu;Meiyan Kang;Suyoung Choi;Song-Hun Chong
    • Geomechanics and Engineering
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    • v.39 no.1
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    • pp.105-113
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    • 2024
  • Recently, electrical resistivity surveys have been used to obtain information related to underground structures including burial structure type and depth. However, various field conditions hinder understanding measured electrical resistance, and thus there is a need to understand how various geometries affect electrical resistance. This study explores the effect of geometric parameters of a structure and electrodes on electrical resistance in the framework of the finite element method. First, an electrical resistance module is developed using the generalized mesh modeling technique, and the accuracy of the module is verified by comparing the results with the analytical solution for a cylindrical electrode with conical tip. Then, 387 cases of numerical analysis including geometric parameters of a buried structure and electrodes are conducted to quantitatively estimate the detection depth under a steady-state current condition. The results show that electrical resistance is increased as (1) shallower burial depth of structure, (2) closer distance between ground electrode and structure, (3) longer horizontal electrode distance. In addition, the maximum detection depth corresponding to converged electrical resistance is deeper as (4) closer distance between ground electrode and structure, (5) shorter horizontal electrode distance. The distribution of the electric potential around the electrodes and underground structure is analyzed to provide a better understanding of the measured electrical resistance. As engineering purpose, the empirical equation is proposed to calculate maximum detection depth as first approximation.

Depth-first branch-and-bound-based decoder with low complexity (검출 복잡도를 감소 시키는 Depth-first branch and bound 알고리즘 기반 디코더)

  • Lee, Eun-Ju;Kabir, S.M.Humayun;Yoon, Gi-Wan
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.13 no.12
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    • pp.2525-2532
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    • 2009
  • In this paper, a fast sphere decoder is proposed for the joint detection of phase-shift keying (PSK) signals in uncoded Vertical Bell Laboratories Layered Space Time (V-BLAST) systems. The proposed decoder, PSD, consists of preprocessing stage and search stage. The search stage of PSD relies on the depth-first branch-and-bound (BB) algorithm with "best-first" orders stored in lookup tables. Simulation results show that the PSD is able to provide the system with the maximum likelihood (ML) performance at low complexity.

Seasonal Variations and Characteristics of the Stratification Depth and Strength in the Seas Near the Korea Peninsular using the Relative Potential Energy Anomaly (한반도 근해의 상대적 위치에너지 편차 변화를 이용한 성층화의 특성과 계절별 변화에 대한 연구)

  • Cho, Chang-Bong;Kim, Young-Gyu;Chang, Kyung-Il
    • Journal of the Korea Institute of Military Science and Technology
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    • v.14 no.2
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    • pp.205-212
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    • 2011
  • In this paper, we have proposed a method for quantization of the stratification strength in the sea water and analysing the distributions of the maximum stratification depths calculated by the method at the seas near the Korean peninsular. For calculating the stratification strength, modified and applied the potential energy anomaly formular which was suggested by Simpson in 1977. The data had been collected by NFRDI from 1971 to 2008 were used to determine the maximum vertical density gradient depth and the relative potential energy anomaly at that depth. In the East Sea, the stratification depth has become deepened about 20m in February and April since 1971. In Yellow-South Sea, the maximum density gradient depth has been deepened about 10m only in December during the same period and the difference of the stratification depth between summer and winter has been enlarged. These trends of variation of stratification strength and depth near the Korean peninsular should be investigated more carefully and continuously. And the results of these studies could be adopted for the more efficient operation of underwater weapon and detection systems.

Study on Development of Embedded Source Depth Assessment Method Using Gamma Spectrum Ratio (감마선 스펙트럼 비율을 이용한 매립 선원의 깊이 평가 방법론 개발 연구)

  • Kim, Jun-Ha;Cheong, Jea-Hak;Hong, Sang-Bum;Seo, Bum-Kyung;Lee, Byung Chae
    • Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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    • v.18 no.1
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    • pp.51-62
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    • 2020
  • This study was conducted to develop a method for depth assessment of embedded sources using gamma-spectrum ratio and for the evaluation of field applicability. To this end, Peak to Compton and Peak to valley ratio changes were evaluated according to 137Cs, 60Co, 152Eu point source depth using HPGe detector and MCNP simulation. The effects of measurement distance of PTV and PTC methods were evaluated. Using the results, the source depth assessment equation using the PTC and PTV methods was derived based on the detection distance of 50 cm. In addition, the sensitivity of detection distance changes was assessed when using PTV and PTC methods, and error increased by 3 to 4 cm when detection distance decreased by 20 cm based on 50 cm. However, it was confirmed that if the detection distance was increased to 100 cm, the effects of detection distance were small. And PTV and PTC methods were compared with the two distance measurement method which evaluates the depth of source by the change of net peak counting rate according to the detection distance. As a result of source depth assessment, the PTV and PTC showed a maximum error of 1.87 cm and the two distance measurement method showed maximum error of 2.69 cm. The results of the experiment confirmed that the accuracy of the PTV and PTC methods was higher than two distance measurement. In addition, Sensitivity evaluation by horizontal position error of source has maximum error of less than 25.59 cm for the two distance measurement method. On the other hand, PTV and PTC method showed high accuracy with maximum error of less than 8.04 cm. In addition, the PTC method has lowest standard deviation for the same time measurement, which is expected to enable rapid measurement.

Design and Implementation of Depth Image Based Real-Time Human Detection

  • Lee, SangJun;Nguyen, Duc Dung;Jeon, Jae Wook
    • JSTS:Journal of Semiconductor Technology and Science
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    • v.14 no.2
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    • pp.212-226
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    • 2014
  • This paper presents the design and implementation of a pipelined architecture and a method for real-time human detection using depth image from a Time-of-Flight (ToF) camera. In the proposed method, we use Euclidean Distance Transform (EDT) in order to extract human body location, and we then use the 1D, 2D scanning window in order to extract human joint location. The EDT-based human extraction method is robust against noise. In addition, the 1D, 2D scanning window helps extracting human joint locations easily from a distance image. The proposed method is designed using Verilog HDL (Hardware Description Language) as the dedicated hardware architecture based on pipeline architecture. We implement the dedicated hardware architecture on a Xilinx Virtex6 LX750 Field Programmable Gate Arrays (FPGA). The FPGA implementation can run 80 MHz of maximum operating frequency and show over 60fps of processing performance in the QVGA ($320{\times}240$) resolution depth image.

On the Yellow Sand Detection using KOMPSAT OSMI Data (KOMPSAT OSMI 자료를 이용한 황사탐지)

  • 김영섭;박경원;서애숙
    • Korean Journal of Remote Sensing
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    • v.18 no.4
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    • pp.201-207
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    • 2002
  • Radiative transfer model was used to detect the yellow sand using KOMPSAT-1/0SMI data. With OSMI and SeaWiFS data, spectrum analysis for spatial and channel were carried out to investigate the characteristics of sensor for the detection of yellow sand. It was compared and analyzed the optical depth of OSMI and SeaWiFS data. Spectral characteristics of x-axis is similar in 765 and 865nm according to spectral analysis for OSMI and SeaWiFS data. It is considered that band 7 and 8(765 and 865nm) of OSMI is suitable for detecting the yellow sand. Compared the yellow sand images by OSMI and MODIS, the data of OSMI are applicable to monitor the yellow sand phenomena. The optical depth of yellow sand event was about 0.8 with 1.0 maximum.

A Study on the Non-Contact Detection Technique of Defects Using AC Current - The Influence of Frequency and lift-off - (교류전류를 이용한 비접촉결함탐상법에 관한 연구 - 주파수 lift-off의 영향 -)

  • Kim, Hoon;Na, Eu-Gyun
    • Journal of the Korean Society for Nondestructive Testing
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    • v.22 no.1
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    • pp.53-58
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    • 2002
  • New nondestructive inspection (NDI) technique to detect the defect in metal was developed in which an electromagnetic field is induced in a metal by AC current flowing in the magnetic coil and the leak magnetic-flux disturbed by defects is measured using a tape-recorder head with air gap. This technique can be applied in evaluating the location and sizing of surface defects in components of the ferromagnetic body by means of the non-contacting measurement. In this paper, we have applied this technique to the evaluation of two-dimensional surface cracks in ferromagnetic metal, and also investigated the influence of the various frequencies and lift-off. Defects were detected with maximum values in the distribution of voltage and it was found that the maximum values tend to increase with the defect depth. Although the maximum values for defects are affected by the frequency and lift-off, the depth of small defects can be estimated from the linear relationship between the depth and voltage rate$(V_0/V_{ave})$.

An ERD-TOF System for the Depth Profiling of Light Elements (경원소 적층 분석을 위한 탄성되튐-비행시간 측정시스템)

  • Kim, Y. S.;Woo, H. J.;Kim, J. K.;Kim, D. K.;Choi, H. W.;Hong, W.
    • Journal of the Korean Vacuum Society
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    • v.5 no.1
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    • pp.25-32
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    • 1996
  • An ERD-TOF system is constructed for the nondestructive depth profiling of light elements in thin films in the range of several thousand angstroms. The particles, recoiled by 10 $MeV^{35}Cl$ projectiles, were detected by a Time-Of-Flight spectrometer composed of a MCP (Micro Channel Plate) and a SSB (Silicon Surface Barrier) detector. A two parameter data acquisition system composed of two PC's was constructed for registering simultaneous time and energy signals. A $Si_3N_4$/poly-Si/$SiO_2$/Si sample was anlayzed and the result is compared with RBS. The detection limit, maximum probable depth and depth resolution for light elements in silicon are about $4\times10^{14}atoms/\textrm{cm}^2$, 5, 000$\AA$ and 100$\AA$, respectively.

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Accurate Detection of a Defective Area by Adopting a Divide and Conquer Strategy in Infrared Thermal Imaging Measurement

  • Jiangfei, Wang;Lihua, Yuan;Zhengguang, Zhu;Mingyuan, Yuan
    • Journal of the Korean Physical Society
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    • v.73 no.11
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    • pp.1644-1649
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    • 2018
  • Aiming at infrared thermal images with different buried depth defects, we study a variety of image segmentation algorithms based on the threshold to develop global search ability and the ability to find the defect area accurately. Firstly, the iterative thresholding method, the maximum entropy method, the minimum error method, the Ostu method and the minimum skewness method are applied to image segmentation of the same infrared thermal image. The study shows that the maximum entropy method and the minimum error method have strong global search capability and can simultaneously extract defects at different depths. However none of these five methods can accurately calculate the defect area at different depths. In order to solve this problem, we put forward a strategy of "divide and conquer". The infrared thermal image is divided into several local thermal maps, with each map containing only one defect, and the defect area is calculated after local image processing of the different buried defects one by one. The results show that, under the "divide and conquer" strategy, the iterative threshold method and the Ostu method have the advantage of high precision and can accurately extract the area of different defects at different depths, with an error of less than 5%.

Effective machine learning-based haze removal technique using haze-related features (안개관련 특징을 이용한 효과적인 머신러닝 기반 안개제거 기법)

  • Lee, Ju-Hee;Kang, Bong-Soon
    • Journal of IKEEE
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    • v.25 no.1
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    • pp.83-87
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    • 2021
  • In harsh environments such as fog or fine dust, the cameras' detection ability for object recognition may significantly decrease. In order to accurately obtain important information even in bad weather, fog removal algorithms are necessarily required. Research has been conducted in various ways, such as computer vision/data-based fog removal technology. In those techniques, estimating the amount of fog through the input image's depth information is an important procedure. In this paper, a linear model is presented under the assumption that the image dark channel dictionary, saturation ∗ value, and sharpness characteristics are linearly related to depth information. The proposed method of haze removal through a linear model shows the superiority of algorithm performance in quantitative numerical evaluation.