Proceedings of the Korean Institute of Building Construction Conference
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2021.11a
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pp.250-251
/
2021
A subcontract work order is the basis of the construction process and consists of the root and trunk of the construction industry. The construction process through a subcontract work order is an important element of project success, and it is the basic unit of creating profit in the construction industry. Therefore, correct analysis and forecasting of subcontract work orders allow correct estimation of construction cost and profit which is the foundation of corporate decision making. This study has started to provide predictions of subcontractor's bidding-ratio for decision-making. Since the actual project data has been used in this study, the contribution level of the model is highly expected in actual field. The statistical confidential level of adjusted decision coefficient is concluded low because of limited sample numbers. However, its accuracy and confidence level can be increased through increasing sample numbers, considering more variables, and studying of reducing error.
Kim, Eung-Seok;Noh, Yeon-Sik;Seo, Kwang-Seok;Park, Sung-Bin;Yoon, Hyung-Ro
Journal of Biomedical Engineering Research
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v.31
no.5
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pp.375-384
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2010
The purpose of this study is to determine whether there is a correlation between the segmental bio-impedance measurement with the frequency modulations and the life-style disease of obesity. An obesity is not simply the factor for estimating the life-style disease of obesity, but also the risk factor occurring. There are many methods (BMI, WHR, Waist, CT, DEXA, BIA, etc.) for measuring a degree of obesity; the bio-impedance measurement is more economic and more effective than others. The physical examination, the blood test, the medical imaging diagnosis and the bio-impedancemeasurementswithmultiple frequencies for each body parts have been conducted for 77 people. The estimated value has been calculated through a segmental bio-impedance model based on multi-frequency that was created to reflect the highest correlation by analyzing correlation with linear regression analysis method for the measured bio-impedance and the risk factors. Then we compared with the clinical diagnosis. In case of high level cholesterol, low HDL-C and high LDL-C for life-style disease, the sensitivity is 80~100%and the specificity is 83~100%. This study has shown conclusively that bio-impedance can be a possible predictor to analyze the disease risk rate of population and individual health maintenance. And also the multi-frequency segmental bio-impedance can be used as early predictor to estimate the life-style disease of obesity.
In this study, the empirical models were established to estimate the concentrations of surface-level $PM_{2.5}$ over Seoul, Korea from 1 January 2012 to 31 December 2013. We used six different multiple linear regression models with aerosol optical thickness (AOT), ${\AA}ngstr{\ddot{o}}m$ exponents (AE) data from Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Terra and Aqua satellites, meteorological data, and planetary boundary layer depth (PBLD) data. The results showed that $M_6$ was the best empirical model and AOT, AE, relative humidity (RH), wind speed, wind direction, PBLD, and air temperature data were used as input data. Statistical analysis showed that the result between the observed $PM_{2.5}$ and the estimated $PM_{2.5}$ concentrations using $M_6$ model were correlations (R=0.62) and root square mean error ($RMSE=10.70{\mu}gm^{-3}$). In addition, our study show that the relation strongly depends on the seasons due to seasonal observation characteristics of AOT, with a relatively better correlation in spring (R=0.66) and autumntime (R=0.75) than summer and wintertime (R was about 0.38 and 0.56). These results were due to cloud contamination of summertime and the influence of snow/ice surface of wintertime, compared with those of other seasons. Therefore, the empirical multiple linear regression model used in this study showed that the AOT data retrieved from the satellite was important a dominant variable and we will need to use additional weather variables to improve the results of $PM_{2.5}$. Also, the result calculated for $PM_{2.5}$ using empirical multi linear regression model will be useful as a method to enable monitoring of atmospheric environment from satellite and ground meteorological data.
Journal of the Korean Society of Fisheries and Ocean Technology
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v.57
no.3
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pp.236-245
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2021
In this study, a drifting test using a experimental vessel (2,966 tons) in the northern waters of Jeju was carried out for the first time in order to obtain the fundamental data for drift. During the test, it was shown that the average leeway speed and direction by GPS position were 0.362 m/s and 155.54° respectively and the leeway rate for wind speed was 8.80%. The analysis of linear regression modes about leeway speed and direction of the experimental vessel indicated that wind or current (i.e. explanatory variable) had a greater influence upon response variable (e.g. leeway speed or direction) with the speed of the wind and current rather than their directions. On the other hand, the result of multiple regression model analysis was able to predict that the direction was negative, and it was demonstrated that predicted values of leeway speed and direction using an experimental vessel is to be more influential by current than wind while the leeway speed through variance and covariance was positive. In terms of the leeway direction of the experimental vessel, the same result of the leeway speed appeared except for a possibility of the existence of multi-collinearity. Then, it can be interpreted that the explanatory variables were less descriptive in the predicted values of the leeway direction. As a result, the prediction of leeway speed and direction can be demonstrated as following equations. Ŷ1= 0.4031-0.0032X1+0.0631X2-0.0010X3+0.4110X4 Ŷ2= 0.4031-0.6662X1+27.1955X2-0.6787X3-420.4833X4 However, many drift tests using actual vessels and various drifting objects will provide reasonable estimations, so that they can help search and rescue fishing gears as well.
The objective of this study was to develop models to predict freshness factors (total viable counts (TVC), pH, volatile basic nitrogen (VBN), trimethylamine (TMA), and thiobarbituric acid (TBA) values) and the storage period in beef using a visible and near-infrared (NIR) spectroscopic technique. A total of 216 beef spectra were collected during the storage period from 0 to 14 d at a $10^{\circ}C$ storage. A spectrophotometer was used to measure reflectance spectra from beef samples, and beef freshness spectra were divided into a calibration set and a validation set. Multi-linear regression (MLR) models using the stepwise method were developed to predict the factors. The MLR results showed that beef freshness had a good correlation between the predicted and measured factors using the selected wavelength. The correlation of determination ($r^2$), standard error of prediction (SEP), and ratio of standard deviation to SEP (RPD) of the prediction set for TVC was 0.74, 0.64, and 2.75 Log CFU/$cm^2$, respectively. The $r^2$, SEP, and RPD values for pH were 0.43, 0.10, and 1.10; those for VBN were 0.73, 1.45, and 2.00 mg%; those for TMA were 0.70, 0.19, and 2.58 mg%; those for TBA values were 0.73, 0.13, and 2.77 mg MA/kg; and those for storage period were 0.77, 1.94, and 2.53 d, respectively. The results indicate that visible and NIR spectroscopy can predict beef freshness during storage.
Soil compaction is affected by soil texture, organic matter (OM), strength (ST) and soil moisture, which is difficult to understand the degree and effects of related factors. The purpose of the study is to assess the impact of them on the compaction with bulk density (BD). The analysis was conducted with data collected from national-wide monitoring sites including 105 upland soils, 246 orchard soils, and 408 paddy soils between 2009 and 2012. The distributions of soil physical properties were measured. The correlation and multi linear regression analysis were performed between soil physical properties using SAS. The regression equation of BD(y) includes ST, gravitational water contents (GWC), and OM as variables commonly, having additional factors, clay content and sand content in paddy soil and upland soil for only subsoil (p<0.001). Our results show that the BD could be explained about 40~50% by various physical properties. The regression was mainly determined by ST in orchard and upland soil and by the GWC in paddy soil. To mitigate soil compaction, it is important to maintain the proper level of OM in upland soil and to consider the moisture condition with soil texture in paddy soil when making work plan. Furthermore, it would be recommended the management criteria classified by soil texture for the paddy soils.
Magazine of the Korean Society of Agricultural Engineers
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v.44
no.7
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pp.64-73
/
2002
This study was performed to evaluate effects of physical characteristics of both watershed and reservoir on nutrient-chlorophyll relationship in Korean reservoirs. Simple linear models were developed with published data in Korea including 415 reservoirs and 11 multi-purpose dams, and physico-chemical parameters of reservoirs and characteristics relationship of models were analyzed. Theoretical residence time in Korean reservoirs was strongly correlated with the ratio of TA/ST (drainage area + surface area / storage volume) in the logarithmic function. As a result of monthly nutrients-chlorophyll-a regression analysis, significant Chl-a-TP relationship appeared during May~July. The high Chl-a yields per total phosphorus appeared during this time (R$\^$2/=0.51, p<0.001, N= 1088). Chlorophyll-a demonstrated much stronger relationship with TP. than TN. Seasonal algal-nutrient coupling were closely related with N:P ratio in the reservoir water, and it was, in turn, dependent on the monsoon climatic condition (precipitation). Based on the results of regression analysis and high N:P ratio, a major limiting factor of algal growth appeared to be phosphorus during this time. Unlikely TA/ST ratio, DA/SA ratio (drainage area f surface area) was likely to influence directly on the nutrient-Chl-a relationship, indicating that if storage volume and inflowing water volume were the same, algal biomass could be developed more in reservoirs with large surface area. Thus, DA/SA ratio seemed to be an important factor to affect the development of algal biomass in Korean reservoirs. With low determination coefficient of TP-Chl-a relationship, our findings indicated not only nutrient (phosphorus) but also other physical factors, such as DA/SA ratio, may affect algal biomass development in Korean reservoirs, where actual residence time appears to be more closely related to reservoir surface area rather than storage volume.
Journal of Korean Society of Coastal and Ocean Engineers
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v.19
no.2
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pp.128-135
/
2007
In response to anthropogenic global warming due to a buildup greenhouse gas, the effect of the air temperature on water temperature has been noticed. Therefore, effects have been made to build an air/water temperature relationship at three study regions using the data collected by the Ministry of the Maritime Affairs and Fisheries (MOMAF). The air/water relationship varies with time-scale and weekly time-scale was chosen for the study. The data were fitted to the S-shaped non-linear relationship, and the parameters for the S-curve were derived using a single-criteria multi-parameter optimization scheme. Separate regression curves were fitted to consider seasonal hysteresis at the Masan site. The study results support the S-shaped non-linear relationship is the best fit for the air/water relationship at the Korean coastal zone. This study will contribute to determine the future policy regarding water quality and ecosystem for the decision-driving organization.
The objectives of this study were to determine the effects of stream nutrient regime, N:P ratios and suspended solids on fish tolerance/trophic compositions and stream ecosystem health, based on multi-metric model, during 2008-2013. Also, stream ecosystem health was evaluated in relation to chlorophyll-a (CHL) as a measure of algal productivity or indicators of trophic state to water chemical parameters. Total number of sampled fish species were 50 and showed a decreasing trend from 2008 to 2013. The minnow of Zacco platypus, based on the catch per unit effort (CPUE), was the most dominant species (25.9%) among the all species. Spatial heterogeneity was evident in the fish tolerance guilds that showed the dominance of sensitive species (89%) in the headwaters (S1) and the dominance of tolerant species (57%) in the urban. These conditions were directly influenced by concentrations of nutrients and organic matter (COD). The N:P ratios, as a barometer of water pollution, had a negative linear function (R2 = 0.40, P < 0.01) with CHL, and the ratios had an important role in changes of COD concentration (R2 = 0.40, P < 0.01). Under the circumstances, the N:P ratio directly influenced the relative proportions of fish trophic/tolerance compositions. According to the regression analysis of omnivore (Om) and insectivore sp. (In) on total nitrogen and total phosphorus, nitrogen had no significant influences (P > 0.05) to the two compositions, but phosphorus influenced directly the two guilds [slope (a) = -32.3, R2 = 0.25, P < 0.01 in the In; a = 40.7, R2 = 0.19, P < 0.01 in the Om]. Such water chemistry and fish trophic guilds determined the stream ecosystem health, based on the multi-metric fish model.
Journal of the Korean Society of Environmental Restoration Technology
/
v.18
no.3
/
pp.65-77
/
2015
The urban park has important functions as a habitat for wildlife as well as open space of rest and community for people. This study was carried out to find what factors of structure and vegetation of urban parks could affect forest bird species diversity in Cheonan city. The study surveyed bird and vegetation species in 26 urban parks, Cheonan city. A correlation analysis and multiple linear regressions were performed to test whether habitat structure and vegetation were the major correlate with species diversity. The results showed the Dujeong park was the most high bird species diversity (H' = 2.13), and the Dujeong-8 park (H' = 2.02) and the Cheongsa park (H' = 1.73) were considerably higher than the other urban parks. The variables that were strongly correlated with bird species diversity were park area, number of subtree species, canopy of shrub, number of shrub species, shape index, canopy of subtree, canopy of tree, and impervious surface ratio. The regression of bird species diversity against the environmental variables showed that 3 variables of park area, canopy of subtree, and canopy of tree were included in the best model. Model variable selection was broadly similar for the 5 optimal models. It means park area and multi-layer vegetation were the most consistent and significant predictor of bird species diversity, because urban parks were isolated by built-up areas. Especially the subtree coverage that provides shelter and food for forest birds was an important variable. Therefore, to make parks circular-shaped and abundant multi-layer vegetation, which could be a buffer to external disturbances and improve the quality of habitats, may be used to enhance species diversity in creation and management of urban parks.
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