• Title/Summary/Keyword: 평균절대오차

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Updating Digital Map using Images from Airborne Digital Camera (항공디지털카메라 영상을 이용한 수치지도 갱신)

  • Hwang, Won-Soon;Kim, Kam-Rae
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.25 no.6_2
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    • pp.635-643
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    • 2007
  • As the availability of images from Airborne Digital Camera with high resolution is expanded, a lot of concern are in the production and update of digital map. This study presents the method of updating the digital map at the scale of 1/1,000 using images from Aerial Digital Camera. Geometric correction was completed using GPS surveying data. For digital mapping, digital photogrammetric system was utilized to digitize buildings and roads. The absolute positional accuracy was evaluated using GPS surveying data and the relative positional accuracy was evaluated using the digital map produced by analytical mapping. The absolute positional accuracy was as follows: RMSE in X and Y were ${\pm}0.172m\;and\;{\pm}0.127m$, and average distance error was 0.208m. The relative positional accuracy was as follows: RMSE in X and Y were ${\pm}0.238m\;and\;{\pm}0.281m$, and average distance error was 0.337m. Accuracies of updating digital map using images from airborne Digital Camera were within allowable error established by NGII. Consequently, images from airborne Digital Camera can be used in various fields including the production of the national basic map and the GIS of local government.

Estimation Error Analysis on the Sediment Grain Size Information in the Coastal Zone (연안해역 퇴적물 입도정보 추정오차 분석)

  • Cho, Hong-Yeon;Kim, Chang-Il;Oh, Young-Min
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.18 no.2
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    • pp.124-136
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    • 2006
  • The change pattern of the sediment grain size distribution information (median grain size(D50)) due to some gridding method and sampling density is analyzed with reference to the grid information estimated by the 90 sediment samples which was collected in the coastal water off the Baengnyeongdo Island, in June 2004. The standard deviation of absolute deviation (AD) estimated the selected gridding method shows 8.0 ${\mu}m$ at June, 2004 and 10 ${\mu}m$ November, 2004. The estimated statistical information of absolute deviation in comparison with the grid information of reference and changed sampling density shows that the AD mean error trends increase as the number of samples decrease. The AD mean error is below 10% in the case of the information estimation using 50-sample with reference to the 90-sample information. In this case, the sampling density is suggested as about 9 sediment samples per $km^2$, at coastal zone in Yoggipo port in the condition of the study area is 5.9 $km^2$.

The Usefulness Assessment of Verifying Daily Output by Using CHECKMATE$^{TM}$ (CHECKMATE$^{TM}$를 이용한 일일 출력 검증의 유용성 평가)

  • Cho, Han-Sang;Nam, Sang-Soo;Park, Hae-Jin;Kim, Mi-Hwa;Park, An-Tae
    • The Journal of Korean Society for Radiation Therapy
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    • v.23 no.1
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    • pp.51-58
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    • 2011
  • Purpose: In this study, we tried to check the usefulness of two Linear Accelerators, Clinac IX and 21EX (Varian, Palo Alto, CA), which are equipped in Ajou Medical Center. From 2008 to 2010, we evaluated the error range of Absolute Dose based on the daily output, which was measured by CHECKMATE$^{TM}$ (Sun Nuclear, Melbourne, FL). Materials and Methods: For Daily Q.A, photon beams of two linear accelerators, 21EX and IX (6 MV and 10 MV, respectively) were measured daily by using CHECKMATE$^{TM}$ just before the treatment began, while the absolute dose was measured biweekly by using water phantom. We analyzed the data of measured values from the daily Q.A and the absolute dose from 2008 to 2010 for 21EX, and from 2009 to 2010 for IX. We utilized Excel 2007 (Microsoft, USA) to evaluate Average, Standard deviation and Confidence level of the data. Furthermore, in order to check the measured values of CHECKMATE$^{TM}$ and the significance of absolute dose, each error value was compared and analyzed. Results: During the observation period, the output of two equipment's absolute dose increased in process of time and in both 6 MV and 10 MV, there was a similar increasing trend. In addition, the error rate of the measured value of CHECKMATE$^{TM}$ and the value of absolute dose were under 0.34, which means that there is a similarity relationship between the two measured values. After checking that the measured value of CHECKMATE$^{TM}$ increased, We measured the absolute dose to adjust that. When the error range was close to 2~3%, the number of changing the output was four for 21EX and three for IX. Conclusion: As a result of measuring and analyzing the daily output changes for two years by using CHECKMATE$^{TM}$, we could find that there is a significance between the output which we should obey during Q.A, and the measured value of absolute dose within the error tolerance of 2~3%. Thus, the use of CHECKMATE$^{TM}$ can be positively considered for more efficient and reliable daily output verification of linear accelerator. It can also be a good standard for other medical centers to understand the trends of linear accelerator and to refer to for the correction of each output.

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An Analysis of Saturation Headway at Signalized Intersections by Using Fuzzy Inference (퍼지추론을 이용한 신호교차로에서의 포화차두시간 분석)

  • Kim, Kyung-Whan;Ha, Man-Bok;Kang, Duk-Ho
    • Journal of Korean Society of Transportation
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    • v.22 no.1 s.72
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    • pp.73-82
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    • 2004
  • 신호 교차로에서 포화차두시간에 영향을 미치는 영향인자는 도로조건, 교통조건, 환경조건으로 분류된다. 이러한 요인들의 복합적인 관계가 포화차두시간에 영향을 미친다. 현재 포화교통류율은 이상적인 조건일 때의 포화차두시간을 산출하고, 이를 이용해서 기본 포화교통류율을 구하고, 여기에 좌 우회전, 차로폭, 경사, 중차량 보정계수을 고려함으로써 특정 차로군의 포화교통류율을 산정하고 있다. 포화차두시간에 영향을 미치는 인자들 중에서 정량적으로 나타내기 어려운 인자 즉, 퍼지적 성격을 가진 인자들은 고려하지 않고 있다. 따라서 본 연구에서는 퍼지 근사추론 방법을 이용하여 정성적 인자의 영향을 고려한 모형을 구축하였다. 모형의 입력자료는 강우조건과 주변밝기의 정도, 중차량 구성비의 언어적 표현를 사용하였다. 이러한 변수들에 대하여 설문조사를 통해서 퍼지집합의 멤버쉽함수를 설정하였으며. 이에 기초하여 교차로에서 각 조건별로 포화차두시간을 관측하였다. 이러한 현장 관측치를 바탕으로 퍼지 제어규칙을 설정하고 모형을 구축하였다. 모형의 평가는 추론치와 실측치를 비교함으로써 이루어 졌으며, 결정계수인 $R^2$와 평균절대오차(MAE)와 평균제곱오차(MSE)를 사용하여 분석한 결과 본 모형의 설명력이 높은 것으로 평가되었다. 본 연구의 과정에서 강우에 의한 교통용량 감소는 중차량 구성비가 클수록 주변밝기의 정도가 나쁠수록 더욱 큰 것으로 나타났으며 그 감소율은 5.3%에서 21.8%에 이르는 넓은 범위의 값을 보였고. 주변밝기 정도에 따른 교통용량 감소는 4.7$\sim$7.5% 수준으로 나타났다.

Application of Meteorological Drought Index in East Asia using Satellite-Based Rainfall Products (위성영상 기반 강수량을 활용한 동아시아 지역의 기상학적 가뭄지수 적용)

  • Mun, Young-Sik;Nam, Won-Ho;Kim, Taegon;Svoboda, Mark D.;Hayes, Michael J.
    • Proceedings of the Korea Water Resources Association Conference
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    • 2019.05a
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    • pp.123-123
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    • 2019
  • 최근 기후변화로 인해 중국, 한국, 일본, 몽골 등을 포함한 동아시아 지역은 태풍, 가뭄, 홍수와 같은 자연재해의 발생 빈도가 증가하고 있는 추세이다. 중국의 경우 2017년 극심한 가뭄으로 1,850만 (ha)의 농작물 피해가 발생하였으며, 몽골 또한 2017년 4월 이후 극심한 가뭄으로 사막화가 급속도로 진행되고 있다. 위성 기반의 강우 자료는 공간과 시간 해상도가 높아짐에 따라 지상관측소 강수량 자료의 대체 수단으로 이용되고 있다. 본 연구에서는 Climate Hazards Groups InfraRed Precipitation with Station (CHIRPS), Precipitation Estimation From Remotely Sensed Information Using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR), Global Precipitation Climatology Centre (GPCC) 강우 위성 자료를 활용하여 기상학적 가뭄지수인 표준강수지수 (Standardized Precipitation Index, SPI)를 산정하였다. 시간 해상도는 월별 영상을 기준으로 2008년부터 2017년까지 지난 10년간의 데이터를 이용하였으며, 각각 격자가 다른 위성영상을 기존 기상관측소와 비교하였다. 피어슨 상관계수 (Pearson Correlation Coefficient, R)를 활용하여 강우 위성 영상과 지상관측소의 상관관계를 분석하고, 평균절대오차 (Mean Absolute Error, MAE), 평균제곱근오차 (Root Mean Square Error, RMSE)를 통해 통계적으로 정확도를 분석하였다. 인공위성 강수량 자료는 미계측 지역이 많은 곳이나 측정이 불가능한 지역에 효율성 측면에서 중요한 이점을 제공할 것으로 판단된다.

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Prediction of Chest Deflection Using Frontal Impact Test Results and Deep Learning Model (정면충돌 시험결과와 딥러닝 모델을 이용한 흉부변형량의 예측)

  • Kwon-Hee Lee;Jaemoon Lim
    • Journal of Auto-vehicle Safety Association
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    • v.15 no.1
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    • pp.55-62
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    • 2023
  • In this study, a chest deflection is predicted by introducing a deep learning technique with the results of the frontal impact of the USNCAP conducted for 110 car models from MY2018 to MY2020. The 120 data are divided into training data and test data, and the training data is divided into training data and validation data to determine the hyperparameters. In this process, the deceleration data of each vehicle is averaged in units of 10 ms from crash pulses measured up to 100 ms. The performance of the deep learning model is measured by the indices of the mean squared error and the mean absolute error on the test data. A DNN (Deep Neural Network) model can give different predictions for the same hyperparameter values at every run. Considering this, the mean and standard deviation of the MSE (Mean Squared Error) and the MAE (Mean Absolute Error) are calculated. In addition, the deep learning model performance according to the inclusion of CVW (Curb Vehicle Weight) is also reviewed.

Estimation of streamflow using river characteristics and satellite images (하천특성 및 위성영상을 활용한 하천유량 추정)

  • Chung, Soo-Un;Jang, Chang-Lae;Jung, Kwansue
    • Proceedings of the Korea Water Resources Association Conference
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    • 2021.06a
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    • pp.36-36
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    • 2021
  • 최근 기후변화로 인한 집중홍우 등으로 홍수 등 재난이 증가하고 있으며, 이를 과학적으로 조사하고 분석하기에는 공간적으로 범위가 넓다. 특히, 미계측유역은 자료를 수집하고 정량적으로 분석 및 예측하는 데에는 한계가 많은 실정이다. 따라서 본 연구에서는 위성영상 자료를 활용하여, 하천폭, 수면경사, 수위 등 자료를 추출하고, 이를 유량조사를 수행한 지점의 자료와 비교하여 수리 기하적 상관성을 분석하였다. 특히, 하도특성을 고려하여 중·하류로 구분하고 유량과 수리기하 학의 관계를 분석하였다. 위성영상 중 취득이 용이한 Sentinel 자료를 선별하여 수리특성인자를 추출하였다. 영상자료의 해상도가 20 m이며, 자료의 한계에 따른 하천폭, 경사, 수위에 대한 유효 기준을 제시하고 경사가 완만하고 하폭이 넓은 대하천에 적용하였다. 그리고, 하천수리인자 특성을 입력변수로 하는 유량을 추정하기 위한 회귀모형을 구축하고, 모의유량과 실측유량을 비교하여 그 적용성을 평가하였다. 개발된 모형은 규모가 유사한 시험유역을 미계측 유역으로 간주하여 평균제곱근오차(RMSE) 와 평균절대오차(MAE)를 이용하여 정확도를 추정하였다. 본 연구를 통해 주요하천의 수리기하 특성을 통계화하고 유량과의 특성을 도출하여 국내하천의 특성을 범주화 할 수 있었고, 미계측 유역에서의 유량을 원격탐사와 같은 간접적인 방법을 통해 추정하고 적용할 수 있을 것으로 기대된다.

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Analysis of Statistical Characteristics of Annual Precipitation in Korea Using Data Screeening Technique (데이터 스크린 기법을 이용한 연강수량의 통계적 특성 분석)

  • Jeung, Se-Jin;Lim, Ga-Kyun;Kim, Byung-Sik
    • Journal of Korean Society of Disaster and Security
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    • v.13 no.3
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    • pp.15-28
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    • 2020
  • Hydrological data is very important in understanding the hydrological process and identifying its characteristics to protect human life and property from natural disasters. In particular, hydrological analysis are often performed assuming that hydrological data are stationary. However, recently climate change has raised the issue of climate stationary, and it is necessary to analyze the nonstationary of the climate. In this study, a method to analyze the stationarity of hydrological data was examined using the annual precipitation of 37 meteorological stations with long - term record data. Therefore, in this study, the stationary was determined by analyzing the persistence, trend, and stability using annual precipitation. Overall results showed that a trend was observed in 4 out of 37 stations, stable was investigated at 15 stations, and persistence was shown at 4 stations. In the stationary analysis using the annual precipitation data, 25 stations (67% of 37 stations) were nonstationary.

An Implementation of High-precision Three-phase Linear Absolute Position Sensor (고정도 3상 직선형 절대 위치 센서의 구현)

  • Lee, Chang Su
    • Journal of IKEEE
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    • v.19 no.3
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    • pp.335-341
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    • 2015
  • Recently a demand for high precision absolute position transducer is increasing in order to control thickness in steel industry. LVDT (linear variable differential transformer) is widely used to measure the absolute position in the linearly moving cylinder under poor factory environment. In this paper we implement the three phase LVDT with a high resolution of one micron and L/D (LVDT to digital) converter. First we designed U, V, and W three phase signaling using FPGA. Second a pulse output algorithm is designed for position information with A and B phase waveforms. Finally the performance is compared with previous sensors. Experiments show that the linearity deviation error is 0.009788 [mm] and the average sinusoidal THD is 0.0751%, which means 2.2% and 33% more improved result than the previous sensors respectively.

A Fast Block Matching Algorithm Using Mean Absolute Error of Neighbor Search Point and Search Region Reduction (이웃 탐색점에서의 평균 절대치 오차 및 탐색영역 줄임을 이용한 고속 블록 정합 알고리듬)

  • 정원식;이법기;한찬호;권성근;장종국;이건일
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.25 no.1B
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    • pp.128-140
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    • 2000
  • In this paper, we propose a fast block matching algorithm using the mean absolute error (MAE) of neighbor search point and search region reduction. The proposed algorithm is composed of two stages. At the first stage,the search region is divided into nonoverlapped 3$\times$3 areas and MAE of the center point of each area iscalculated. The minimum MAE value of all the calculated MAE's is determined as reference MAE. At thesecond stage, because the possibility that final motion vector exist near the position of reference MAE is veryhigh, we use smaller search region than first stage, And, using the MAE of center point of each area, the lowerbound of rest search point of each area is calculated and block matching process is performed only at the searchpoints that the lower bound is smaller than reference MAE. By doing so, we can significantly reduce thecomputational complexity while keep the increasement of motion estimation error small.

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