• Title/Summary/Keyword: Flow estimation

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A Study on the Estimation of Regional Myocardial Blood Flow in Experimental Canine Model with Coronary Thrombosis using Rb-82 Dynamic Myocardial Positron Emission Tomography (실험 개에서 Rb-82 심근 Dynamic PET 영상을 이용한 국소 심근 혈류 예측의 기본 모델 연구)

  • Kwark, Cheol-Eun;Lee, Dong-Soo;Kang, Keon-Wook;Hwang, Eun-Kyung;Jeong, Jae-Min;Chang, Kee-Hyun;Chung, June-Key;Lee, Myung-Chul;Seo, Joung-Don;Koh, Chang-Soon
    • The Korean Journal of Nuclear Medicine
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    • v.29 no.1
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    • pp.48-53
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    • 1995
  • This study investigates a simple mathematical model for the quantitative estimation of regional myocardial blood flow in experimental canine coronary artery thrombosis using Rb-82 dynamic myocardial positron emission tomography. The coronary thrombosis was induced using the new catheter technique by narrowing the lumen of coronary vessel gradually, which finally led to partial obstruction of coronary artery. Ten Rb-82 dynamic myocardial PET scans were performed sequentially for each experiment using our 5, 10 and 20 second acquisition protocol, respectively, and three regions of interest were drawn on the transaxial slices, one on left ventricular chamber for input function and the other two on normal and decreased perfusion segments for the flow estimation in those regions. Single compartment model has been applied to the measured sets of regional PET data, and the rate constants of influx to myocardial tissue were calculated for regional myocardial flow estimates with the three parameter fits of raw data by the Levenberg-Marquardt method. The results showed that, (1) single compartment model suggested by Kety-Schmidt could be used for the simple estimation of regional myocardial blood flow, (2) the calculated regional myocardial blood flow estimates were dependent on the selection of input function, which reflected partial volume effect and left ventricular wall motion, and (3) mathematically fitted input and tissue time activity curves were more suitable than the direct application of the measured data in terms of convergence.

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Estimation of stream flow discharge using the satellite synthetic aperture radar images at the mid to small size streams (합성개구레이더 인공위성 영상을 활용한 중소규모 하천에서의 유량 추정)

  • Seo, Minji;Kim, Dongkyun;Ahmad, Waqas;Cha, Jun-Ho
    • Journal of Korea Water Resources Association
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    • v.51 no.12
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    • pp.1181-1194
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    • 2018
  • This study suggests a novel approach of estimating stream flow discharge using the Synthetic Aperture Radar (SAR) images taken from 2015 to 2017 by European Space Agency Sentinel-1 satellite. Fifteen small to medium sized rivers in the Han River basin were selected as study area, and the SAR satellite images and flow data from water level and flow observation system operated by the Korea Institute of Hydrological Survey were used for model construction. First, we apply the histogram matching technique to 12 SAR images that have undergone various preprocessing processes for error correction to make the brightness distribution of the images the same. Then, the flow estimation model was constructed by deriving the relationship between the area of the stream water body extracted using the threshold classification method and the in-situ flow data. As a result, we could construct a power function type flow estimation model at the fourteen study areas except for one station. The minimum, the mean, and the maximum coefficient of determination ($R^2$) of the models of at fourteen study areas were 0.30, 0.80, and 0.99, respectively.

SWAT Direct Runoff and Baseflow Evaluation using Web-based Flow Clustering EI Estimation System (웹기반의 유량 군집화 EI 평가시스템을 이용한 SWAT 직접유출과 기저유출 평가)

  • Jang, Won Seok;Moon, Jong Pil;Kim, Nam Won;Yoo, Dong Sun;Kum, Dong Hyuk;Kim, Ik Jae;Mun, Yuri;Lim, Kyoung Jae
    • Journal of Korean Society on Water Environment
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    • v.27 no.1
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    • pp.61-72
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    • 2011
  • In order to assess hydrologic and nonpoint source pollutant behaviors in a watershed with Soil and Water Assessment Tool (SWAT) model, the accuracy evaluation of SWAT model should be conducted prior to the application of it to a watershed. When calibrating and validating hydrological components of SWAT model, the Nash-Sutcliffe efficiency coefficient (EI) has been widely used. However, the EI value has been known as it is affected sensitively by big numbers among the range of numbers. In this study, a Web-based flow clustering EI estimation system using K-means clustering algorithm was developed and used for SWAT hydrology evaluation. Even though the EI of total streamflow was high, the EI values of hydrologic components (i.e., direct runoff and baseflow) were not high. Also when the EI values of flow group I and II (i.e., low and high value group) clustered from direct runoff and baseflow were computed, respectively, the EI values of them were much lower with negative EI values for some flow group comparison. The SWAT auto-calibration tool estimated values also showed negative EI values for most flow group I and II of direct runoff and baseflow although EI value of total streamflow was high. The result obtained in this study indicates that the SWAT hydrology component should be calibrated until all four positive EI values for each flow group of direct runoff and baseflow are obtained for better accuracy both in direct runoff and baseflow.

Comparative Study on Evaluating Standard Flow in Partially Gauged and Ungauged Watershed (부분계측 및 미계측 유역에서 기준유량 산정 방법 비교 연구)

  • Kim, Gyeonghoon;Kim, Jeongmin;Jeong, Hyunki;Im, Taehyo;Kim, Seongmin;Kim, Yongseok;Seo, Mijin
    • Journal of Korean Society on Water Environment
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    • v.35 no.6
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    • pp.481-496
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    • 2019
  • The Ministry of Environment has measured streamflow at eight-day intervals for the estimation of standard flow of the Total Maximum Daily Loads (TMDL) system. This study identified the availability of the partially measured the eight-day interval data for estimating standard flow and found the optimal extension techniques of standard flow. The study area was selected for the Nakbon-A watershed in the Nakdong River, and four streamflow record extension techniques of standard flow were considered: extension, percentile, drainagearea, and regional regression methods. The flow duration curve (FDC) using the eight-day interval streamflow data indicated very high Nash and Sutcliffe Efficiency (NSE) values above 90 % from FDC-II to FDC-VII compared to FDC-VIII, the standard FDC. This result demonstrates that FDC using daily data of three-six cumulative years could represent standard FDC fairly well. For the streamflow record extension techniques of standard flow, the percentile method was selected as the optimal alternative, showing the minimal difference from FDC-VIII. These results validate the availability of the eight-day interval streamflow data in the standard flow estimation and the application of extension techniques. It seems that these results could reduce the uncertainty of partially measured streamflow data for water quantity and quality management.

The Estimation of Blood Velocity from Heart in Medical Images using Regional Segmentation (영상분할을 이용한 의학영상에서의 심장혈류 측정)

  • 정철곤;김중규;김경섭
    • Proceedings of the IEEK Conference
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    • 1999.11a
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    • pp.517-520
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    • 1999
  • In this paper, we propose a non-invasive method to estimate blood velocity from the real medical images. To measure the magnitude and direction components associated with the blood velocity, we apply the optical flow analysis algorithm. It is demonstrated that the accuracy of the blood velocity estimate could possibly be increased by segmenting the optical flow region. We call this the Region Optical Flow(ROF) algorithm. We carried out some preliminary experiments using the aorta medical images, and corresponding regional optical flow diagrams are provided.

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Estimation of Flow Population of Seoul Walking Tour Courses Using Telecommunications Data (통신 데이터를 활용한 도보관광코스 유동인구 추정 및 분석)

  • Park, Ye Rim;Kang, Youngok
    • Journal of Cadastre & Land InformatiX
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    • v.49 no.1
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    • pp.181-195
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    • 2019
  • This study aims to analyze the spatial context by analyzing the flow characteristics of the walking tour course and visualizing effectively using the floating population data constructed through the communication data. The floating population data refinement algorithm was developed for estimation flow population along the road and the floating population data for each walking tour courses was constructed. In order to adopt the algorithm for forming suitable for the analysis of the walking tour courses, the estimation of floating population considering the area of the road and the estimation of floating population considering the value of floating population around the road were compared. As a result, the estimation of floating population considering ambient the values of flow population was adopted, which is more appropriate to apply analysis method due to the relatively consistent data. Then, a datamining algorithm for walking tour course was constructed according to the characteristics of the floating population data, the absence of missing values. Finally, this study analyzed the flow characteristics and spatial patterns of 18 walking trails in Seoul through the floating population data according to walking tour course. To do this, the kernel density analysis and the Getis-Ord $G^*_i$ statistical hotspot analysis were applied to visualize the main characteristics of each walking tour course.

Motion Parameter Estimation and Segmentation with Probabilistic Clustering (활률적 클러스터링에 의한 움직임 파라미터 추정과 세그맨테이션)

  • 정차근
    • Journal of Broadcast Engineering
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    • v.3 no.1
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    • pp.50-60
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    • 1998
  • This paper addresses a problem of extraction of parameteric motion estimation and structural motion segmentation for compact image sequence representation and object-based generic video coding. In order to extract meaningful motion structure from image sequences, a direct parameteric motion estimation based on a pre-segmentation is proposed. The pre-segmentation which considers the motion of the moving objects is canied out based on probabilistic clustering with mixture models using optical flow and image intensities. Parametric motion segmentation can be obtained by iterated estimation of motion model parameters and region reassignment according to a criterion using Gauss-Newton iterative optimization algorithm. The efficiency of the proposed methoo is verified with computer simulation using elF real image sequences.

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Calculation of ice clearing resistance using normal vector of hull form and direct calculation of buoyancy force under the hull

  • Park, Kyung-Duk;Kim, Moon-Chan;Kim, Hyun-Soo
    • International Journal of Naval Architecture and Ocean Engineering
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    • v.7 no.4
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    • pp.699-707
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    • 2015
  • The ice-resistance estimation technique for icebreaking ships had been studied intensively over recent years to meet the needs of designing Arctic vessels. Before testing in the ice model basin, the estimation of a ship's ice resistance with high reliability is very important to decide the delivered power necessary for level ice operation. The main idea of previous studies came from several empirical formulas, such as Poznyak and Ionov (1981), Enkvist (1972) and Shimansky (1938) methods, in which ice resistance components such as icebreaking, buoyancy and clearing resistances were represented by the integral equations along the Design Load Water Line (DLWL). The current study proposes a few modified methods not only considering the DLWL shape, but also the hull shape under the DLWL. In the proposed methodology, the DLWL shape for icebreaking resistance and the hull shape under the DLWL for buoyancy and clearing resistances can be directly considered in the calculation. Especially, when calculating clearing resistance, the flow pattern of ice particles under the DLWL of ship is assumed to be in accordance with the ice flow observed during ice model testing. This paper also deals with application examples for a few ship designs and its ice model testing programs at the AARC ice model basin. From the comparison of results of the model test and the estimation, the reliability of this estimation technique has been discussed.

Count-Min HyperLogLog : Cardinality Estimation Algorithm for Big Network Data (Count-Min HyperLogLog : 네트워크 빅데이터를 위한 카디널리티 추정 알고리즘)

  • Sinjung Kang;DaeHun Nyang
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.33 no.3
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    • pp.427-435
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    • 2023
  • Cardinality estimation is used in wide range of applications and a fundamental problem processing a large range of data. While the internet moves into the era of big data, the function addressing cardinality estimation use only on-chip cache memory. To use memory efficiently, there have been various methods proposed. However, because of the noises between estimator, which is data structure per flow, loss of accuracy occurs in these algorithms. In this paper, we focus on minimizing noises. We propose multiple data structure that each estimator has the number of estimated value as many as the number of structures and choose the minimum value, which is one with minimum noises, We discover that the proposed algorithm achieves better performance than the best existing work using the same tight memory, such as 1 bit per flow, through experiment.