• Title/Summary/Keyword: Accuracy estimation

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Application of Slope-area Discharge Estimation Method using Continuously Observed Water Level Data in a Gravel Bed River -Case Study of the Dal Cheon River- (자갈하천에서 연속적인 수위 자료를 이용한 경사면적법 유량 산정 -달천 사례연구-)

  • Lee, Chan-Joo;Kim, Ji-Sung;Kim, Chi-Young;Kim, Dong-Gu
    • Journal of Korea Water Resources Association
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    • v.41 no.5
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    • pp.503-515
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    • 2008
  • In this study we calculate discharge by slope-area method using continuously observed water level data and analyse the results. This study is performed in the Dalcheon river reach of 960 m length including riffles and a pool, which is located downstream of the Goesan Dam. Three values of roughness coefficient are applied to discharge calculation, which are established using bed material size analysis. Another roughness coefficient value obtained from the river improvement plan is also used. Calculated discharges by slope-area method are compared with dam discharges. Relative difference from dam discharges appears to be largely affected by roughness values and a value of 0.042 or more seems most suitable for the entire study reach. Smaller roughness value is suitable to the reach which has gentler water surface slope than mean channel slope of the entire study reach, while a larger value to steeper reach. In case roughness value is set considering overall slope of the channel, it is desirable to select the entire calculation reach including both gentler and steeper sub-reaches. Since relative difference becomes nearly constant at over 500 cms, in case that verification of applied roughness is conducted with other directly measured discharge, accuracy of measurement by slope-area method for larger discharge may be improved.

Earth-Volume Measurement of Small Area Using Low-cost UAV (저가형 UAV를 이용한 소규모지역의 토량 측정)

  • Seong, Ji Hoon;Han, You Kyung;Lee, Won Hee
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.36 no.4
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    • pp.279-286
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    • 2018
  • In the civil works, the measurement of earth-volume is one of the important elements in the estimation of the reasonable construction cost. Related studies mainly used GPS (Global Positioning System) or total station to obtain information on civil work areas. However, these methods are difficult to implement in inaccessible areas. Therefore, the aim of this paper is to use the UAV (Unmanned Aerial Vehicle) to measure the earth-volume. The study area is located in a reservoir construction site in Sangju-si, Gyeongsangbuk-do, Republic of Korea. We compared the earth-volume amounts acquired by UAV-based surveying to ones acquired by total station-based and GPS-based surveying, respectively. In the site, the amount of earth-volume acquired by GPS was $147,286.79m^3$. The amount of earth-volume acquired by total station was $147,286.79m^3$, which is the 96.13% accuracy compared to the GPS-based surveying. The earth-volume obtained by UAV was $143,997.05m^3$ when measured without GCPs (Ground Control Points), $147,251.71m^3$ with 4 GCPs measurement, and $146,963.81m^3$ with 7 GCPs measurement. Compared to the GPS-based surveying, 97.77%, 99.98%, and 99.78% accuracies were obtained from the UAV-based surveying without GCP, 4 GCPs, and 7 GCPs, respectively. Therefore, it can be confirmed that the UAV-based surveying can be used for the earth-volume measurement.

Estimate Saliency map based on Multi Feature Assistance of Learning Algorithm (다중 특징을 지원하는 학습 기반의 saliency map에 관한 연구)

  • Han, Hyun-Ho;Lee, Gang-Seong;Park, Young-Soo;Lee, Sang-Hun
    • Journal of the Korea Convergence Society
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    • v.8 no.6
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    • pp.29-36
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    • 2017
  • In this paper, we propose a method for generating improved saliency map by learning multiple features to improve the accuracy and reliability of saliency map which has similar result to human visual perception type. In order to overcome the inaccurate result of reverse selection or partial loss in color based salient area estimation in existing salience map generation, the proposed method generates multi feature data based on learning. The features to be considered in the image are analyzed through the process of distinguishing the color pattern and the region having the specificity in the original image, and the learning data is composed by the combination of the similar protrusion area definition and the specificity area using the LAB color space based color analysis. After combining the training data with the extrinsic information obtained from low level features such as frequency, color, and focus information, we reconstructed the final saliency map to minimize the inaccurate saliency area. For the experiment, we compared the ground truth image with the experimental results and obtained the precision-recall value.

Development of Sludge Concentration Estimation Method using Neuro-Fuzzy Algorithm (뉴로-퍼지 알고리즘을 이용한 슬러지 농도 추정 기법 개발)

  • Jang, Sang-Bok;Lee, Ho-Hyun;Lee, Dae-Jong;Kweon, Jin-Hee;Chun, Myung-Geun
    • Journal of the Korean Institute of Intelligent Systems
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    • v.25 no.2
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    • pp.119-125
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    • 2015
  • A concentration meter is widely used at purification plants, sewage treatment plants and waste water treatment plants to sort and transfer high concentration sludge and to control the amount of chemical dosage. When the strange substance is contained in the sludge, however, the attenuation of ultrasonic wave could be increased or not be transmitted to the receiver. At that case, the value of concentration meter is higher than the actual density value or vibrated up and down. It has also been difficult to automate the residuals treatment process according to the problems as sludge attachment or damage of a sensor. Multi-beam ultrasonic concentration meter has been developed to solve these problems, but the failure of the ultrasonic beam of a specific concentration measurement value degrade the performance of the entire system. This paper proposes the method to improve the accuracy of sludge concentration rate by choosing reliable sensor values and learning them by proposed algorithm. The prediction algorithm is chosen as neuro-fuzzy model, which is tested by the various experiments.

A Study on Estimation of Systolic Blood Pressure using PTT (PTT를 이용한 수축기 혈압의 측정에 관한 연구)

  • Park E. K.;Lee S. M.;Han Y. H.;Lee J. Y.;Kwon S. Y.;Kim I. Y.;Kim Sun I.
    • Journal of Biomedical Engineering Research
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    • v.25 no.6
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    • pp.605-609
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    • 2004
  • Blood pressure (BP) is one of the important physiological parameters for diagnosing cardiovascula diseases by means of noninvasive method. Existing noninvasive methods for measuring arterial BP have to use cuff and difficult in measuring arterial BP continuously. Systolic blood pressure (SBP) and pulse transit time (PTT) have a kind of inverse relationship. We acquired PTT data when subjects were in relaxation and also after exercise. We performed the linear regression analysis for making the regression equations for each subject and the regression equation for all subjects. We compared the estimated SBP with the measured SBP to check the accuracy of our regression equations. From the result, the regression equations for each subject was appropriate according to the American National Standards Institute of the Association of the Advancement of Medical Instrument (ANSI/AAMI) which says that BP devices should have ±5mmHg mean of error and 8mmHg standard deviation of error. However, the regression equation for all subjects was not proper to ANSI/AAMI recommendation. The result means that, without cuff, we can continuously estimate each subject's SBP through PTT and indivisual calibration.

AdaBoost-based Gesture Recognition Using Time Interval Window Applied Global and Local Feature Vectors with Mono Camera (모노 카메라 영상기반 시간 간격 윈도우를 이용한 광역 및 지역 특징 벡터 적용 AdaBoost기반 제스처 인식)

  • Hwang, Seung-Jun;Ko, Ha-Yoon;Baek, Joong-Hwan
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.22 no.3
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    • pp.471-479
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    • 2018
  • Recently, the spread of smart TV based Android iOS Set Top box has become common. This paper propose a new approach to control the TV using gestures away from the era of controlling the TV using remote control. In this paper, the AdaBoost algorithm is applied to gesture recognition by using a mono camera. First, we use Camshift-based Body tracking and estimation algorithm based on Gaussian background removal for body coordinate extraction. Using global and local feature vectors, we recognized gestures with speed change. By tracking the time interval trajectories of hand and wrist, the AdaBoost algorithm with CART algorithm is used to train and classify gestures. The principal component feature vector with high classification success rate is searched using CART algorithm. As a result, 24 optimal feature vectors were found, which showed lower error rate (3.73%) and higher accuracy rate (95.17%) than the existing algorithm.

Technical Consideration for Production Data Analysis with Transient Flow Data on Shale Gas Well (셰일가스정 천이유동 생산자료분석의 기술적 고려사항)

  • Han, Dong-kwon;Kwon, Sun-il
    • Journal of the Korean Institute of Gas
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    • v.20 no.1
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    • pp.13-22
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    • 2016
  • This paper presents development of an appropriate procedure and flow chart to analyze shale gas production data obtained from a multi-fractured horizontal well according to flow characteristics in order to calculate an estimated ultimate recovery. Also, the technical considerations were proposed when a rate transient analysis was performed with field production data occurred to only $1^{st}$ transient flow. If production data show the $1^{st}$ transient flow from log-log and square root time plot analysis, production forecasting must be performed by applying different method as before and after of the end of $1^{st}$ linear flow. It is estimated by an area of stimulated reservoir volume which can be calculated from analysis results of micro-seismic data. If there are no bottomhole pressure data or micro-seismic data, an empirical decline curve method can be used to forecast production performance. If production period is relatively short, an accuracy of production data analysis could be improved by analyzing except the early production data, if it is necessary, after evaluating appropriation with near well data. Also, because over- or under-estimation for stimulated reservoir volume could take place according to analysis method or analyzer's own mind, it is necessary to recalculate it with fracture modeling, reservoir simulation and rate transient analysis, if it is necessary, after adequacy evaluation for fracture stage, injection volume of fracture fluid and productivity of producers.

Estimation of Surface Reflectance by Utilizing Single Visible Reflectance from COMS Meteorological Imager - Analysis of BAOD correction effect - (천리안위성 기상 탑재체의 가시 채널 관측을 이용한 지표면 반사도 산출 - 배경광학두께 보정의 효과 분석 -)

  • Kim, Mijin;Kim, Jhoon;Yoon, Jongmin
    • Korean Journal of Remote Sensing
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    • v.30 no.5
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    • pp.627-639
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    • 2014
  • Accurate correction of surface effect from back scattered solar radiance is one of key issue to retrieve aerosol information from satellite measurements. In this study, two different methods are applied to retrieve surface reflectance by using single visible channel measurement from meteorological imager onboard COMS. The first one is minimum reflectance method, which composes the minimum value among previously measured reflectances at each pixel over a certain search window length. This method assumes that the darkest pixel corresponds to the aerosol-free condition, and deduces surface reflectance by correcting atmospheric scattering from the measured visible reflectance. The second method, named as the "atmospheric correction method" in this study, estimates the result by correcting aerosol and atmospheric scattering with ground-based observation of aerosol optical properties. The purpose of this study is to investigate the retrieval accuracy of the widelyused minimum reflectance method. Also, the retrieval error caused by the loading of background aerosol is mainly estimated. The comparison between surface reflectances retrieved from the two methods shows good agreement with the correlation coefficient of 0.87. However, the results from the minimum reflectance method are slightly overestimated than the values from the atmospheric correction method when surface reflectance is lower than 0.2. The average difference between the two results is 0.012 without the background aerosol correction. By considering the background aerosol effect, however, the difference is reduced to 0.010.

Development of Continuous Rainfall-Runoff Model for Flood Forecasting on the Large-Scale Basin (대유역 홍수예측을 위한 연속형 강우-유출모형 개발)

  • Bae, Deg-Hyo;Lee, Byong-Ju
    • Journal of Korea Water Resources Association
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    • v.44 no.1
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    • pp.51-64
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    • 2011
  • The objective of this study is to develop a continuous rainfall-runoff model for flood prediction on a large-scale basin. For this study, the hourly surface runoff estimation method based on the variable retention parameter and runoff curve number is developed. This model is composed that the soil moisture to continuous rainfall can be simulated with applying the hydrologic components to the continuous equation for soil moisture. The runoff can be simulated by linking the hydrologic components with the storage function model continuously. The runoff simulation to large basins can be performed by using channel storage function model. Nakdong river basin is selected as the study area. The model accuracy is evaluated at the 8 measurement sites during flood season in 2006 (calibration period) and 2007~2008 (verification period). The calibrated model simulations are well fitted to the observations. Nash and Sutcliffe model efficiencies in the calibration and verification periods exist in the range of 0.81 to 0.95 and 0.70 to 0.94, respectively. The behavior of soil moisture depending on the rainfall and the annual loadings of simulated hydrologic components are rational. From this results, continuous rainfall-runoff model developed in this study can be used to predict the discharge on large basins.

Development of Operating Speed Prediction Models Reflecting Alignment Characteristics of the Upstream Road Sections at Four-Lane Rural Uninterrupted Flow Facility (상류부 선형특성을 반영한 지방부 왕복 4차로 연속류 도로의 주행속도 예측모형 개발)

  • Jo, Won-Beom;Kim, Yong-Seok;Choe, Jae-Seong;Kim, Sang-Yeop;Kim, Jin-Guk
    • Journal of Korean Society of Transportation
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    • v.28 no.5
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    • pp.141-153
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    • 2010
  • The study is about the development of operating speed prediction models aimed for an evaluation of design consistency of four lane rural roads. The main differences of this study relative to previous research are the method of data collection and classification of road alignments. The previous studies collected speed data at several points in the horizontal curve and approaching tangent. This method of collection is based on the assumption that acceleration and deceleration only occurs at horizontal tangents and the speed is kept constant at horizontal curves. However, this assumption leads to an unreliable speed estimation, so drivers' behavior is not well represented. Contrary to the previous approach, speed data were collected with one and data analysis using a speed profile is made for data selection before building final models. A total of six speed prediction models were made according to the combination of horizontal and vertical alignments. The study predicts that the speed data analysis and selection for model building employed in this study can improve the prediction accuracy of models and be useful to analyze drivers' speed behavior in a more detailed way. Furthermore, it is expected that the operating speed prediction models can help complement the current design-speed-based guidelines, so more benefits to drivers as real road users, rather than engineers or decision makers, can be achieved.