• Geotechnical Engineering
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• v.28 no.1
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• pp.39-44
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• 2011

TDR 함수량계는 전자기파를 이용하여 흙의 밀도와 함수비를 비파괴적으로 신속하게 평가하는 유망한 기술이다. TDR 시험법은 10~20cm 길이의 2~3개의 탐침을 지중에 관입시킨 후 전자기파의 이동시간을 측정하여 유전상수($K_a$)를 산정한다. 제안식을 이용하여 유전상수로부터 체적함수비(${\theta}$)의 산정이 가능하므로, 이 시험법은 흙의 함수비를 측정할 수 있는 비파괴시험 장치로 개발되어 활용되고 있다. 또한, 흙의 종류에 따른 보정상수가 파악되어 있는 경우에는 현장 밀도와 현장 함수비를 동시에 평가할 수 있으므로, TDR 함수량계를 이용하여 성토지만비나 노상토에 대한 신속하고 간편한 다짐관리가 기능하다.

• Korean Journal of Remote Sensing
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• v.33 no.2
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• pp.231-242
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• 2017

Monitoring of facilities such as roads, dams and bridges is important for their long-term sustainable usage. It has usually suffered with safety and cost problems, which makes more frequent monitoring difficult. As an efficient and economicalsolution to these problems, one may consider the use of smartphone to capture the status of the facilities. To derive quantitative analysis results with the smartphone images for facility monitoring, one should first rectify the images in a way as automatic and economical as possible. In thisstudy, we propose such a rectification method, which rectifiessmartphone images acquired from arbitrary locations based on reference images.In the proposed method, we determine the camera extrinsic parameters of each smartphone images using the reference imagesrather than ground control points, and project the image to the target surface of the facility based on the determined camera parameters. The method were applied to test data acquired from a small dam toward water-area facility monitoring. The experimental results showed that the camera extrinsic parameters were determined with the accuracy of 5 cm and $0.28^{\circ}$ in the position and attitude. The accuracy of the distance measured from the rectified image was evaluated to 10 cm. With the rectified images, one can accurately determine the location and length of the target objects required for facility monitoring.

• Journal of Korean Society of Environmental Engineers
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• v.22 no.4
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• pp.785-796
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• 2000

In this study, the possibility of application of TUNVEN model was investigated through the validation and calibration processes. In order to validate and calibrate the TUNVEN model developed in USA to obtain prediction of the quasi-steady state longitudinal air velocities and the pollutants concentrations by solving the coupled one-dimensional steady state tunnel aerodynamic and advection equations. The major input parameters such as the concentration data for CO and $NO_x$, meteorological data and traffic volume in Hawngryung tunnel were measured. Prior to preparing the input parameters, the sensitivity analysis was conducted to identify the input parameters which need to be most accurately estimated in TUNVEN program. In order to establish the relationships between the model values and the measured values, the linear regression analysis was applied. In linear regression analysis, the model values were taken as independent parameter(X) and the measured values were taken as dependent parameter(Y) for four cases of data sef. From the results of linear regression analysis, the correlation coefficient(r) for four cases were calculated more than 0.91 and the values of slope and interception were analyzed as 0.5~2.2 and 0.01~2.3 respectively. From the above results, we concluded that the suitability of TUNVEN model was identified in prediction the longitudinal pollutant concentrations in tunnel.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.4
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• pp.161-172
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• 2023

Autonomous driving vehicles recognize the surroundings through various sensors mounted on the vehicle and control the vehicle based on the collected information. The level of autonomous driving technology is improving due to the development of sensor technology and algorithms that process collected data, but the implementation of perfect autonomous driving technology has not been achieved. To overcome these limitations, through autonomous cooperative driving centered on infrastructure. In this study, developed a position correction sign that provides a reference for positioning of autonomous vehicles. First of all, an analysis was performed on the current status of positioning technology for autonomous driving. And measure the number of point clouds for the 1st sample consisting of two square reflective surfaces and 2nd sample that increased the vertical length of each reflective surface. Experimental results show that both primary and secondary products are installed at least 15 m apart It could be recognized as a sensor, and it was confirmed that the secondary production that increased the length of the top and bottom had a higher number of point clouds than the primary production and better expressed the shape of the facility.

• Korean Journal of Optics and Photonics
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• v.10 no.1
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• pp.21-26
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• 1999

The technique for calibrating standard particles larger than 1 $\mu$m by using an optical array sizing method has been established. The system consists of an optical microscope with transmission light source, a CCD camera, and a computer equipped with a frame grabber. The center distance between two spheres located at both ends of a row which consists of N spheres is measured in terms of pixel numbers, and divided by (N-1) to obtain the average pixel numbers per particle. This value is multiplied by length conversion constant, which has been determined in advance, to obtain the mean diameter of polystylene spheres. The length conversion constant is found from the microscopic image of calibrated standard stage micrometer plate. In order to reduce error in finding center positions of the scale and particles in the image, a software filter which dilates bright (or dark) object has been used. Spheres having nominal size of 1, 2, 3, 5, and 10$\mu$m were measured, and the maximum deviation of the measured mean diameter valus from their certified values was 0.7%. Standard particles which is larger than 1 $\mu$m can be calibrated by this method with measuredment uncertainy (k=2) lees than 1.53%.

• Spatial Information Research
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• v.7 no.1
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• pp.89-101
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• 1999

This paper represents methods to calculate heights of buildings by estimating their shadow lengths in a single and panchromatic image of the KVR-1000 camera system Shadows are identified Com brightness intensity of each pixel, and their lengths are measured. Two methods are implemented to estimate heights from shadows. One method is to use a ratio of shadow s lengths with respect to heights of reference buildings measured on site. The other method uses sun elevation angles calculated from various camera s parameters at the exposure time. The estimated heights of 20 buildings are compared with heights measured on site, and the RMS errors for each method are 1.70m and 1.75m, respectively. When a resampling method to enhance identification of shadows is used and their lengths are accordingly re-calculated, the estimated errors for each method are significantly reduced to 1.17m and 1.16m, respectively. Meanwhile, effects of land slope on shadows can be hardly obtained unless detailed DTM(digital terrain model) are available, and they introduce additional errors up to 25m.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.12
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• pp.903-909
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• 2018

In this paper, performance analysis of machine vision techniques is presented to improve the convenience and speed of automatic inspection in the industrial field when machine vision is applied to the image not taken in the stationary state, but in the moving state on a conveyer. When the length of cylindrical rods used for automobiles was measured using the edge detection method, the conveying speed increased, and the uncertainty of the boundary between the background and the part image increased, which resulted in a shorter image of the object taken. This paper proposes a linear compensation method to predict the biased errors of the length measurements after examining the pattern of biased and random errors, respectively, with 6 different types of specimens and 7 velocity stages. The length measurement corrected by the linear compensation method had the same accuracy as the stationary state within the speed range of 30 cm/s and could enhance the application capability in automatic inspections.

• Progress in Medical Physics
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• v.9 no.3
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• pp.163-173
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• 1998

Nuclear medicine emission computed tomography(ECT) can be very useful to diagnose early stage of neuronal diseases and to measure theraputic results objectively, if we can quantitate energy metabolism, blood flow, biochemical processes, or dopamine receptor and transporter using ECT. However, physical factors including attenuation, scatter, partial volume effect, noise, and reconstruction algorithm make it very difficult to quantitate independent of type of SPECT. In this study, we quantitated the effects of attenuation and scatter using brain SPECT and three-dimensional brain phantom with and without applying their correction methods. Dual energy window method was applied for scatter correction. The photopeak energy window and scatter energy window were set to 140ke${\pm}$10% and 119ke${\pm}$6% and 100% of scatter window data were subtracted from the photopeak window prior to reconstruction. The projection data were reconstructed using Butterworth filter with cutoff frequency of 0.95cycles/cm and order of 10. Attenuation correction was done by Chang's method with attenuation coefficients of 0.12/cm and 0.15/cm for the reconstruction data without scatter correction and with scatter correction, respectively. For quantitation, regions of interest (ROIs) were drawn on the three slices selected at the level of the basal ganglia. Without scatter correction, the ratios of ROI average values between basal ganglia and background with attenuation correction and without attenuation correction were 2.2 and 2.1, respectively. However, the ratios between basal ganglia and background were very similar for with and without attenuation correction. With scatter correction, the ratios of ROI average values between basal ganglia and background with attenuation correction and without attenuation correction were 2.69 and 2.64, respectively. These results indicate that the attenuation correction is necessary for the quantitation. When true ratios between basal ganglia and background were 6.58, 4.68, 1.86, the measured ratios with scatter and attenuation correction were 76%, 80%, 82% of their true ratios, respectively. The approximate 20% underestimation could be partially due to the effect of partial volume and reconstruction algorithm which we have not investigated in this study, and partially due to imperfect scatter and attenuation correction methods that we have applied in consideration of clinical applications.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.23-23
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• 2018

본 연구에서는 다중분위회귀분석모형(Multiple Quantile Regression Model, MQRM)과 MODIS(MODerate resolution Imaging Spectroradiometer) LST (Land Surface Temperature) 자료를 이용하여 전국 공간토양수분을 산정하였다. 공간토양수분을 산정하기 위한 과정은 크게 두가지로 구분된다. 첫 번째로 기존의 MODIS LST 자료를 조건부 합성 보정기법을 적용하여 실측 LST 자료와 비교하여 위성 LST 자료가 갖고 있는 오차를 보정하였다. 그 결과, 조건부 합성 보정기법을 적용하기전 전국 71개 지상관측지점에서 관측한 실측 LST와 MODIS LST의 $R^2$는 전체 평균 0.70으로 어는정도 유의성 있는 상관관계를 나타냈으나 조건부 합성 보정기법을 적용한 후 실측 LST와 MODIS LST의 $R^2$는 전체 평균 0.92로 상당히 크게 향상됨을 알 수 있었다. 두 번째로 보정된 MODIS LST를 이용하여 다중분위회귀분석 모형을 개발하고 토양수분을 예측하는 단계로 입력자료로 위성영상 자료와 관측자료를 융합하여 사용하였다. 위성영상 자료로는 보정된 MODIS LST와 MODIS NDV를 구축하였고 일단위 강수량 및 일조시간의 기상자료는 기상청으로부터 전국 71개 지점에 대해 구축하여 IDW 공간보간기법을 이용한 공간자료로 구축하였다. 토양수분 결과를 비교하기 위한 관측 토양수분은 자동농업기상관측(Automated Agriculture Observing System, AAOS)지점에서 2013년 1월부터 2015년 12월까지의 실측 일단위 토양수분 자료를 구축하여 사용하였다. 다중분위회귀분석 모형은 LST 인자를 중심으로 각각의 분위(0.05, 0.25, 0.5, 0.75, 0.95)에 해당되는 값의 회귀식을 NDVI, 강수 입력자료를 독립인자로서 조합하여 계절 및 토성에 따른 총 80개의 회귀식을 산정하였다. 관측 토양수분과 모의 토양수분을 비교한 결과 $R^2$가 0.70 (철원), 0.90 (춘천), 0.85 (수원), 0.65 (서산), 0.78 (청주), 0.82 (전주), 0.62 (순천), 0.63 (진주), 0.78 (보성)로 높은 상관성을 보였다. 본 연구에서는 다중분위회귀 모형의 성능을 검증하기 위해 기존의 다중선형회귀모형의 결과와 비교하여 크게 개선됨을 나타냈다.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.164-164
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• 2017

토지이용 및 토지피복 변화는 인간의 활동에 따른 결과를 반영하며 자연환경의 변화와도 밀접한 관련이 있다. 수문환경의 변화는 수로 건설이나 하천정비, 사진개간, 도시화 등과 같은 인위적인 변화와 지구온난화에 따라 변화하는 기후 패턴에도 많은 영향을 받고 있다. 본 연구에서는 안성천 공도수위관측소 상류유역을 대상으로 SWAT(Soil and Water Assessment) 모형을 이용하여 현재의 유역 수문환경조건을 보다 현실적으로 분석하기 위해 연구를 실시하였다. 유역의 수문환경 조건을 정량적으로 파악하기 위하여 CLUE-s 모형을 이용한 토지이용변화가 기후변화 시나리오에 따른 수문학적 거동(지표유출, 증발산량, 총유출량, 수질거동)에 미치는 영향을 SWAT모형을 이용하여 파악하고자 하였다. 안성천의 공도 수위관측소($366.5km^2$)을 대상으로 유역 내 3지점의 기상관측소(이천, 수원, 천안)를 대상으로 40년(1976~2015)동안의 일 기상자료를 수집하여 SWAT 모형을 구축하였다. 평년 및 가뭄년을 포함하는 선별된 기간에 대하여 다양한 목적함수($R^2$, NSE, RMSE)를 활용하여 일반적인 전체기간 검보정 방법이 아닌 각각의 조합된 기간의 극단적 유출특성에 초점을 맞추어 검보정을 수행하였다. 이와 같이, 앞서 실시한 연구로 모형의 매개변수들을 해당 유역에 가뭄과 같은 극단적 유출상황에 따라 선행보정 실시하였으며, 이는 이번 연구에서의 모형의 신뢰성 있는 수문 및 수질 거동 분석을 할 수 있을 것이라 생각된다. 선행 연구 자료를 이용하여 토지이용변화를 고려한 본 연구를 통해 미래의 유역 수문환경조건 변화에 따라 수자원을 정량적으로 파악하는 데에 도움이 될 수 있을 것으로 판단된다.