• Korean Journal of Clinical Laboratory Science
• /
• v.36 no.2
• /
• pp.199-204
• /
• 2004

Height has become one of the most important factors to determine the pulmonary function test index, and there is a high correlation between them, so that they have been utilized for evaluating pulmonary function test predictive value or nomogram. Therefore, we have tried to find out that difference and if there is any correlation and linear relationship between height and forced expiratory flow curve. There were a total of 163 subjects, male 93 and female 70. This study was done at the Department of Pulmonary Function Test of Jeon-Ju Presbyterian Hospital and we measured the index at the forced expiratory flow curve of FVC, $FEV_{1.0}$, $FEV_{1.0}$/FVC, $FEF_{25-75%}$, and $FEF_{200-1200m{\ell}}$. When we subjected the group of height more than 160cm, there were gradual increments at FVC(p<0.001), $FEV_{1.0}$(p<0.001), $FEF_{25-75%}$(p<0.05) and $FEF_{200-1200m{\ell}}$(p<0.001), but no changes at $FEV_{1.0}$/FVC in terms of forced expiratory flow curve index. We have analyzed the relationship between height and forced expiratory flow curve, there was a close relationship at FVC(r=0.670, p<0.01), $FEV_{1.0}$(r=0.491, p<0.01), $FEF_{25-75%}$ (r=0.175, p<0.05) and $FEF_{200-1200m{\ell}}$(r=0.370, p<0.01) but there was reciprocal relationship at $FEV_{1.0}$/FVC(r=-0.215, p<0.01). We have tried simple regression analysis to see if height affects forced expiratory flow curve index as a sector, and the result was $FVC(\ell)=0.0642{\times}height(cm)-7.2978$(p<0.01, $R^2=0.449$), $FEV_{1.0}(\ell)=0.0407{\times}height(cm)-4.2774$ (p<0.01, $R^2=0.2411$), $FEV_{1.0}/FVC(%)=-0.2892{\times}height(cm)+121.44$(p<0.01, $R^2=0.0464$), $FEF_{25-75%}(\ell/sec)=0.0176{\times}height(cm)-0.7876$(p<0.05, $R^2=0.0237$), $FEF_{200-1200m{\ell}}(\ell/sec)=0.0967{\times}height(cm)-11.037$(p<0.01, $R^2=0.1214$) this was approved statistically. According to this study, if height is taller than average, forced expiratory flow curve index were increased, there was a close relationship between height and forced expiratory flow curve, and there was a linear relationship as sector between height and forced expiratory flow curve index. Therefore, researches that study other factors such as sex, age, weight, body surface area, and obesity indexes other than height should be done to see if there are any further relationships.

• Korean Journal of Clinical Laboratory Science
• /
• v.41 no.3
• /
• pp.135-139
• /
• 2009

Pulmonary function test has been know to be greatly affected by body indices, such as sex, age, height, body weight, body surface area (BSA) and body mass index (BMI), so hat this study was focused to see the relationship between body index and flow-volume curves. Subjects were 156 (male 90, female 66) and they were examined for pulmonary function test in terms of body index and correlation/multiple regression analysis of flow-volume curves at Presbyterian Medical Center from March to August, 2009. The followings results after analyzing the correlation between body index and flow-volume curves. Although flow-volume curve FEF25-75% showed close correlation with age, body weight, and body surface area, but not with body mass index. In addition, multiple regression analysis was performed to see how each body index affects flow-volume curve FEF25-75%, and FEF25-75% dispersion was explained as 74.5% with age only, 94.2% with age and height, and 96% with age, height, and sex. Therefore, sex, age and height that are mainly used for predictive formular of pulmonary function test and nomogram were important factors for pulmonary function test itself, and further study must be done for other body index.

• Journal of Korea Water Resources Association
• /
• v.54 no.spc1
• /
• pp.1183-1193
• /
• 2021

Low flow affects various fields such as river water supply management and planning, and irrigation water. A sufficient period of flow data is required to calculate the Flow Duration Curve. However, in order to calculate the Flow Duration Curve, it is essential to secure flow data for more than 30 years. However, in the case of rivers below the national river unit, there is no long-term flow data or there are observed data missing for a certain period in the middle, so there is a limit to calculating the Flow Duration Curve for each river. In the past, statistical-based methods such as Multiple Regression Analysis and ARIMA models were used to predict sulfur in the unmeasured watershed, but recently, the demand for machine learning and deep learning models is increasing. Therefore, in this study, we present the DNN technique, which is a machine learning technique that fits the latest paradigm. The DNN technique is a method that compensates for the shortcomings of the ANN technique, such as difficult to find optimal parameter values in the learning process and slow learning time. Therefore, in this study, the Flow Duration Curve applicable to the unmeasured watershed is calculated using the DNN model. First, the factors affecting the Flow Duration Curve were collected and statistically significant variables were selected through multicollinearity analysis between the factors, and input data were built into the machine learning model. The effectiveness of machine learning techniques was reviewed through statistical verification.

• Journal of Korean Society on Water Environment
• /
• v.28 no.2
• /
• pp.224-231
• /
• 2012

It is necessary to develop flow duration curve (FDC) on each unit watershed in order to analyze flow conditions in the stream for the management of Total Maximum Daily Loads (TMDLs). This study investigated a simple method to develop FDC for the general use of the curve. A simple equation for daily flow estimation was derived from the regression analysis between the 8-day interval flow data of a unit watershed and the daily flow monitoring data of an adjacent upstream region. FDC can be prepared with the calculation of daily flow by the equation for each unit watershed. An annual and a full-period FDC were drawn for each unit watershed in Guem river basin. Standard flow such as low and ordinary flow can be obtained from the annual FDC. Major percentile of flow such as 10, 25, 50, 75 or 90% can be obtained from the full-period FDC. It is considered that this simple method of developing FDC can be utilized more widely for the calculation of standard flow and the assessment of water quality in the process of TMDLs.

• Journal of Korean Society of Water and Wastewater
• /
• v.17 no.4
• /
• pp.495-502
• /
• 2003

In order to modify incorrect flow data in the sewage system, the method using the stage-discharge relation and hydraulic characteristic curve of sewer pipe are applied. The modified data were verified with field measured data and the infiltration analysis using the modified data was carried out. When flowrate were measured using the flow-meter in fair weather, the stage data were comparatively consistent but velocity data were very poor for the most part. Therefore, it was recommended that sewage flowrate variation characteristic curve and infiltration were computed using the modified data on the basis of stage data. Especially, in the case of using the hydraulic characteristic curve, extrapolation results of the rainy season flowrate using regression curve on the basis of the data in fair weather were also reasonable.

• Journal of Korea Water Resources Association
• /
• v.36 no.1
• /
• pp.33-44
• /
• 2003

Flow duration curves provide a compact summary of streamflow variability. In this study, characteristics of the dimensionless flow duration curve in natural rivers with the unregulated discharge were investigated. An analysis of flow duration characteristics was conducted with discharge data at stage-gauging stations of IHP representative basins and of the major rivers in Korea. Discharge characteristics are dependent on area of watershed. However, flow duration coefficients except drought duration coefficient are independent on that. Abundant flow duration coefficient was constant value. The coefficient of flow duration variability defined in this study as the ratio of the normal stream flow over the drought one is decreased with increasing of the watershed area, which implies that the watershed area affects the drought flow duration variability more than the low flow one. And the coefficient of flow duration variability is increased with the river gradient.

• The KSFM Journal of Fluid Machinery
• /
• v.14 no.6
• /
• pp.26-34
• /
• 2011

Waterhammer and slamming phenomena can occur when power is cut off due to reversal flow in pipeline and sudden close of check valve. Therefore analysis of reversal flow time, which means the time of reversal flow in pipeline due to pumping station blackout, is needed to protect facilities from waterhammer economically and efficiently. However systematic study on reversal flow time has not been done yet. So theory of reversal flow time analysis is proposed and verified with experiment using several parameters like pump specific speed, motor pole number, and characteristic curve of pipeline in this study.

• Journal of the Korean Geotechnical Society
• /
• v.39 no.5
• /
• pp.13-26
• /
• 2023

This study examined the soil-water characteristic curve (SWCC), considering the volume change, using wetting curves on the field monitoring data of a wireless sensor network. Special attention was given to evaluating the landslide vulnerability by deriving a matric suction suitable for the actual site during the wetting process. Laboratory drying SWCC and shrinkage laboratory tests were used to perform the combined analysis of landslide and debris flow. The results showed that the safety factor of the wetting curve, considering the volume change of soil, was lower than that of the drying curve. As a result of numerical analyses of the debris flow simulation, more debris flow occurred in the wetting curve than in the drying curve. It was also found that the landslide analysis with the drying curve tends to overestimate the actual safety factor with the in situ wetting curve. Finally, it is confirmed that calculating the matric suction through SWCC considering the volume change is more appropriate and reasonable for the field landslide analysis.

• Journal of Environmental Science International
• /
• v.5 no.3
• /
• pp.377-385
• /
• 1996

This study aims at the estimation of a river management flow in urban basin analyzing Sinchun basin to be the tributary of Kumho river basin. The river management flow has to satisfy a low flow as natural flow and an environmental preservation flow estimated by a dilution flow to satisfy a target water quality in drought flow. Therefore for the estimation of a river management flow in Sinchun in this study, first Tank model as a basin runoff model estimates a low flow, a drought flow from a flow duration curve in Sinchun, second QUAL2E model as water quality model simulates water quality in Sinchun and estimates environmental preservation flow to satisfy a target water qua%its, BOD 8 mg/l by a dilution flow derived from Kumho river, Nakdong river and around water. And the river management flow is estimated by addition of a use flow and a loss flow to more flow between a low-flow and an environmental preservation flow.

• Journal of Korean Society on Water Environment
• /
• v.28 no.6
• /
• pp.890-895
• /
• 2012

Duration curves describe the percentage of time that a certain water quality (total/fecal coliform (=TC/FC)) or discharge is exceeded. The curves methodology are usually based on daily records and are useful in estimating how many days per year and event will be exceeded. The technique was further applied to estimated TC/FC loading to the Geumho River, using the daily mean flow rate and TC/FC concentration data during January, 2001 and December, 2011 for the Geumhogang6 (=Seongseo water level station) where an automated monitoring station is located in Gangchang-bridge. Low flow of the Seongseo (=11.1 cms) was equivalent to 75.3% on an exceedance probability scale. Load Duration curve for TC/FC loading at the Seongseo was constructed. Standard load duration curve was constructed with the water quality criteria for class III (TC/FC concentration = 5000/1000 CFU/ 100 mL). By plotting TC/FC observed load duration curve with standard load duration curve, it could be revealed that water quality do not meet the desired water quality for 68.8/11.2% on an exceedance probability scale. IF linear correlation between flow rate and coliform concentration is assumed, it can be interpreted that water quality exceed desired criteria when daily average flow rate is over 11.9/109.9 cms.