• Korean Journal of Construction Engineering and Management
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• v.17 no.5
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• pp.22-34
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• 2016

The Project Delivery System (PDS) is used in mixed way without clear classification from tendering system and the standard itself that can be selected is set with project budget or estimated cost only. Essentially, the PDS should consider and reflect project characteristics and types, internal and external factors for the purpose of improving the lives of citizens and their welfare. However, the current status is not operated flexibly due to the given budget, period and uniform laws and regulations. In order to solve this problem, this study suggests a Decision Support Model to select the optimal PDS for public construction projects. The current problem of the PDS for public construction projects were identified and the application of a decision support model was proposed. Subsequently a decision-making model was suggested for each PDS using the identified factors and linear discriminant function of discriminant analysis. An additional questionnaire survey and actual practical case analysis were carried out to verify the effectiveness and applicability of the model to actual work. It can be used by adjusting the decision support model and detailed factors according to the specific characteristics of public organization, ability of person in charge and project type.

• Journal of Convergence for Information Technology
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• v.9 no.6
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• pp.1-6
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• 2019

In this study, the development of a weight estimation model of electronic scale with nonlinear characteristics is presented using polynomial regression analysis. The output voltage of the load cell was measured directly using the reference mass. And a polynomial regression model was obtained using the matrix and curve fitting function of MS Office Excel. The weight was measured in 100g units using a load cell electronic scale measuring up to 5kg and the polynomial regression model was obtained. The error was calculated for simple($1^{st}$), $2^{nd}$ and $3^{rd}$ order polynomial regression. To analyze the suitability of the regression function for each model, the coefficient of determination was presented to indicate the correlation between the estimated mass and the measured data. Using the third order polynomial model proposed here, a very accurate model was obtained with a standard deviation of 10g and the determinant coefficient of 1.0. Based on the theory of multi regression model presented here, it can be used in various statistical researches such as weather forecast, new drug development and economic indicators analysis using logistic regression analysis, which has been widely used in artificial intelligence fields.

• Asian-Australasian Journal of Animal Sciences
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• v.16 no.12
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• pp.1705-1710
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• 2003

A small body size of Brown Tsaiya laying duck is desirable to reduce maintenance requirements, so the body weight at 40 weeks of age (BW40) has to be maintained at its current level. Egg weight has to be maintained at around 65 g to meet market requirements. Eggshell strength at 40 weeks of age (ES40) must to be increased in order to maintain a low incidence of broken eggs. Thus, number of eggs laid up to 52 weeks of age (EN52) has to be increased without negative correlated response on ES40. A new linear genetic selection index was used: $I_g=a_0{\times}GEW40\;(g)+a_1{\times}GBW40\;(g)+a_2{\times}GES40\;(kg/cm^2)+a_3{\times}GEN52\;(eggs)$ where GEW40, GBW40, GES40 and GEN52 were the multitrait best linear unbiased prediction (MT-BLUP) animal model predictors of the breeding values respectively of egg weight and body weight at 40 weeks of age (EW40, BW40), ES40 and EN52. The coefficients $a_0$, $a_1$, $a_2$ and $a_3$ were calculated with constraints of 0.0 g, 0.0 g and $0.013kg/cm^2$ for expected genetic gains in EW40, BW40 and ES40 respectively and maximum gain in EN52. Since 1997, the drakes and the ducks were selected according to their own indexes, with this new genetic selection index. From G0 to G4, the average per generation predicted genetic responses in female duck were +0.05 g for EW40, +0.92 g for BW40, $+0.035kg/cm^2$ for ES40 and +2.13 eggs for EN52. Which represented respectively 0.07%, 0.06%, 0.67% and 1.0% of the means of the EW40, BW40, ES40 and EN52. For ES40 and EN52, it represented also respectively 16.1% and 21.6% of the additive genetic standard deviation of these traits. Thevse results indicated that selection of laying Brown Tsaiya by a restricted genetic selection index and with MT-BLUP animal model could be an efficient tool for improving the efficiency of egg production, increasing egg shell strength and egg number while holding egg weight and body weight constants.

• Safety and Health at Work
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• v.10 no.4
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• pp.452-460
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• 2019

Background: Monitoring and control of PM_2.5 are being recognized as key to address health issues attributed to PM_2.5. Availability of low-cost PM_2.5 sensors made it possible to introduce a number of portable PM_2.5 monitors based on light scattering to the consumer market at an affordable price. Accuracy of light scatteringe-based PM_2.5 monitors significantly depends on the method of calibration. Static calibration curve is used as the most popular calibration method for low-cost PM_2.5 sensors particularly because of ease of application. Drawback in this approach is, however, the lack of accuracy. Methods: This study discussed the calibration of a low-cost PM_2.5-monitoring device (PMD) to improve the accuracy and reliability for practical use. The proposed method is based on construction of the PM_2.5 sensor network using Message Queuing Telemetry Transport (MQTT) protocol and web query of reference measurement data available at government-authorized PM monitoring station (GAMS) in the republic of Korea. Four machine learning (ML) algorithms such as support vector machine, k-nearest neighbors, random forest, and extreme gradient boosting were used as regression models to calibrate the PMD measurements of PM_2.5. Performance of each ML algorithm was evaluated using stratified K-fold cross-validation, and a linear regression model was used as a reference. Results: Based on the performance of ML algorithms used, regression of the output of the PMD to PM_2.5 concentrations data available from the GAMS through web query was effective. The extreme gradient boosting algorithm showed the best performance with a mean coefficient of determination (R²) of 0.78 and standard error of 5.0 ㎍/㎥, corresponding to 8% increase in R² and 12% decrease in root mean square error in comparison with the linear regression model. Minimum 100 hours of calibration period was found required to calibrate the PMD to its full capacity. Calibration method proposed poses a limitation on the location of the PMD being in the vicinity of the GAMS. As the number of the PMD participating in the sensor network increases, however, calibrated PMDs can be used as reference devices to nearby PMDs that require calibration, forming a calibration chain through MQTT protocol. Conclusions: Calibration of a low-cost PMD, which is based on construction of PM_2.5 sensor network using MQTT protocol and web query of reference measurement data available at a GAMS, significantly improves the accuracy and reliability of a PMD, thereby making practical use of the low-cost PMD possible.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1435-1447
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• 2020

The seasonal variations in weather parameters can significantly affect the atmospheric transmission characteristics. Herein, we propose a novel augmented multiple regression algorithm for the accurate estimation of atmospheric transmittance and solar irradiance over highly localized areas. The algorithm employs 1) adaptive atmospheric model selection using measured meteorological data and 2) multiple linear regression computation augmented with the conventional application of MODerate resolution atmospheric TRANsmission (MODTRAN). In this study, the proposed algorithm was employed to estimate the solar irradiance over Taean coastal area using the 2018 clear days' meteorological data of the area, and the results were compared with the measurement data. The difference between the measured and computed solar irradiance significantly improved from 89.27 ± 48.08σ W/㎡ (with standard MODTRAN) to 21.35 ± 16.54σ W/㎡ (with augmented multiple regression algorithm). The novel method proposed herein can be a useful tool for the accurate estimation of solar irradiance and atmospheric transmission characteristics of highly localized areas with various weather conditions; it can also be used to correct remotely sensed atmospheric data of such areas.

• Journal of Korean Neurosurgical Society
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• v.65 no.6
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• pp.779-789
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• 2022

Objective : To analyze the effects of the number and shape of fenestrations on the mechanical strength of pedicle screws and the effects of bone cement augmentation (BCA) on the pull-out strength (POS) of screws used in conventional BCA. Methods : For the control group, a conventional screw was defined as C1, a screw with cannulated end-holes was defined as C2, a C2 screw with six pinholes was defined as C3, and the control group type was set. Among the experimental screws, T1 was designed using symmetrically placed thru-hole type fenestrations with an elliptical shape, while T2 was designed with half-moon (HM)-shaped asymmetrical fenestrations. T3 and T4 were designed with single HM-shaped fenestrations covering three pitches and five pitches, respectively. T5 and T6 were designed with 0.6-mm and 1-mm wider fenestrations than T3. BCA was performed by injecting 3 mL of commercial bone cement in the screw, and mechanical strength and POS tests were performed according to ASTM F1717 and ASTM F543 standards. Synthetic bone (model #1522-505) made of polyurethane foam was used as a model of osteoporotic bone, and radiographic examinations were performed using computed tomography and fluoroscopy. Results : In the fatigue test, at 75% ultimate load, fractures occurred 7781 and 9189 times; at 50%, they occurred 36122 and 82067 times; and at 25%, no fractures occurred. The mean ultimate load for each screw type was 219.1±52.39 N for T1, 234.74±15.9 N for T2, 220.70±59.23 N for T3, 216.45±32.4 N for T4, 181.55±54.78 N for T5, and 216.47±29.25 N for T6. In comparison with C1, T1, T2, T3, T4, and T6 showed significantly different ultimate load values (p<0.05). However, when the values for C2 and the fenestrated screws were evaluated with an unpaired t test, the ultimate load value of C2 significantly differed only from that of T2 (p=0.025). The ultimate load value of C3 differed significantly from those of T1 and T2 (C3 vs. T1 : p=0.048; C3 vs. T2 : p<0.001). Linear correlation analysis revealed a significant correlation between the fenestration area and the volume of bone cement (Pearson's correlation coefficient r=0.288, p=0.036). The bone cement volume and ultimate load significantly correlated with each other in linear correlation analysis (r=0.403, p=0.003). Conclusion : Fenestration yielded a superior ultimate load in comparison with standard BCA using a conventional screw. In T2 screws with asymmetrical two-way fenestrations showed the maximal increase in ultimate load. The fenestrated screws can be expected to show a stable position for the formation of the cement mass.

• Magazine of the Korean Society of Agricultural Engineers
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• v.26 no.4
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• pp.52-65
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• 1984

In general precise estimation of hourly of daily distribution of the long-term run-off should be very important in a design of source of irrigation. However, there have not been a satisfying method for forecasting of stationar'y long-term run-off in Korea. Solving this problem, this study introduces unit-hydrograph method frequently used in short-term run-off analysis into the long-term run-off analysis, of which model basin was selected to be Sumgin-river catchment area. In the estimation of effective rainfall, conventional method neglects the Soil moisture condition of catchment area, but in this study, the initial discharge (qb) occurred just before rising phase of the hydrograph was selected as the index of a basin soil moisture condition and then introduced as 3rd variable in the analysis of the reationship between cumulative rainfall and cumulative loss of rainfall, which built a new type of separation method of effective rainfall. In next step, in order to normalize significant potential error included in hydrological data, especially in vast catchment area, Snyder's correlation method was applied. A key to solution in this study is multiple correlation method or multiple regressional analysis, which is primarily based on the method of least squres and which is solved by the form of systems of linear equations. And for verification of the change of characteristics of unit hydrograph according to the variation of a various kind of hydrological charateristics (for example, precipitation, tree cover, soil condition, etc),seasonal unit hydrograph models of dry season(autumn, winter), semi-dry season (spring), rainy season (summer) were made respectively. The results obtained in this study were summarized as follows; 1.During the test period of 1966-1971, effective rainfall was estimated for the total 114 run-off hydrograph. From this estimation results, relative error of estimation to the ovservation value was 6%, -which is mush smaller than 12% of the error of conventional method. 2.During the test period, daily distribution of long-term run-off discharge was estimated by the unit hydrograph model. From this estimation results, relative error of estimation by the application of standard unit hydrograph model was 12%. When estimating by each seasonal unit bydrograph model, the relative error was 14% during dry season 10% during semi-dry season and 7% during rainy season, which is much smaller than 37% of conventional method. Summing up the analysis results obtained above, it is convinced that qb-index method of this study for the estimation of effective rainfall be preciser than any other method developed before. Because even recently no method has been developed for the estimation of daily distribution of long-term run-off dicharge, therefore estimation value by unit hydrograph model was only compared with that due to kaziyama method which estimates monthly run-off discharge. However this method due to this study turns out to have high accuracy. If specially mentioned from the results of this study, there is no need to use each seasonal unit hydrograph model separately except the case of semi-dry season. The author hopes to analyze the latter case in future sudies.

• Animal Bioscience
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• v.35 no.10
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• pp.1499-1511
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• 2022

Objective: This study was aimed to estimate the genetic parameters, including genetic and phenotypic correlations, of milk yield, lactation curve traits and milk composition of Thai dairy cattle from three government research farms. Methods: The data of 25,789 test-day milk yield and milk composition records of 1,468 cattle from lactation 1 to 3 of Holstein Friesian (HF) and crossbred HF dairy cattle calved between 1990 and 2015 from three government research farms in Thailand were analysed. 305-day milk yield was estimated by the Wood model and a test interval method. The Wood model was used for estimating cumulative 305-day milk yield, peak milk yield, days to peak milk yield and persistency. Genetic parameters were estimated using linear mixed models with herd, breed group, year and season of calving as fixed effects, and animals linked to a pedigree as random effects, together with a residual error. Univariate models were used to estimate variance components, heritability, estimated breeding values (EBVs) and repeatability of each trait, while pairwise bivariate models were used to estimate covariance components and correlations between traits in the same lactation and in the same trait across lactations. Results: The heritability of 305-day milk yield, peak milk yield and protein percentage have moderate to high estimates ranging from 0.19 to 0.45 while days to peak milk yield, persistency and fat percentage have low heritability ranging from 0.08 to 0.14 in lactation 1 cows. Further, heritability of most traits considered was higher in lactation 1 compared with lactations 2 and 3. For cows in lactation 1, high genetic correlations were found between 305-day milk yield and peak milk yield (0.86±0.07) and days to peak milk yield and persistency (0.99±0.02) while estimates of genetic correlations between the remaining traits were imprecise due to the high standard errors. The genetic correlations within the traits across lactation were high. There was no consistent trend of EBVs for most traits in the first lactation over the study period. Conclusion: Both the Wood model and test interval method can be used for milk yield estimates in these herds. However, the Wood model has advantages over the test interval method as it can be fitted using fewer test-day records and the estimated model parameters can be used to derive estimates of other lactation curve parameters. Milk yield, peak milk yield and protein percentage can be improved by a selection and mating program while days to peak milk yield, persistency and fat percentage can be improved by including into a selection index.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.5 no.2
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• pp.160-171
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• 1995

The size characteristics of lead particle which is one of the important factors associated with absorption of lead were ignored in establishing lead standard. This study was conducted to investigate distribution of lead particles by operation of industry. Aerodynamic Mass Median Diameters (MMD) of airborne lead particles in the battery and litharge manufacturing industry were $14.1{\mu}m$ and $15.1{\mu}m$, respectively. There was no significant difference between those two values(p>0.05). However, the diameters in radiator manufacturing and secondary smelting industry were $1.3{\mu}m$, $4.9{\mu}m$, respectively. Those were significantly smaller than the particle sizes in other industries(p<0.05). Total lead concentrations in the secondary smelting industry were higher than those in the battery and litharge manufacturing industry. Total lead concentrations in other industries except radiator manufacturing industry exceeded the standard of $50{\mu}g/m^3$. Only radiator manufacturing industry indicated lead concentrations significantly lower than those in other industries(p<0.05). Concentrations of lead particles smaller than $1{\mu}m$ defined as respirable fraction by OSHA's CPA model assumption were $72.4{\mu}g/m^3$ in the secondary smelting industry, exceeding $50{\mu}g/m^3$. The relationship of concentrations between total lead and lead of particles smaller than $1{\mu}m$ was log Y = 0.46 logX + 0.06(n=119, $r^2=0.44$, p=0.0001). Relationship of respirable lead concentrations between OSHA and ACGIH was significantly detected in the litharge and battery manufacturing industry(p=0.0001), but was not significant in the radiator(p=0.2720) and secondary smelting manufacturing industry(p=0.2394). As MMDs of lead particles generated in industry were small, difference of respirable lead concentration between OSHA and ACGIH became smaller. There was a significant difference between concentrations respirable lead defined by two organizations such as OSHA and ACGIH in the battery and litharge manufacturing industry. Average concentration of respirable lead by ACGIH definition was 43.3 % of total lead in secondary smelting and 48.9 % in radiator manufacturing industry, and lower fractions were indicated in battery and litharge manufacturing industry. Relationships of total lead with IPM, TPM, and RPM were significant respectively(p=0.0001) and lead concentrations by particle size could be estimated using this relationship. Linear regression equation between total lead concentration(X) and ACGIH-RPM concentration(Y) was log Y = 0.76 log X - 0.40($r^2=0.89$, p=0.0001).

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.1
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• pp.35-41
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• 2016

GNSS/Geoid positioning technology allows orthometric height determination using both the geoidal height calculated from geoid model and the ellipsoidal height achieved by GNSS survey. In this study, Network-RTK surveying was performed through the Benchmarks in the study area to analyze the possibility of height positioning of the Network-RTK. And the orthometric heights were calculated by applying the Korean national geoid model KNGeoid13 according to the condition of with site calibration and without site calibration and the results were compared. Simplex algorithm was adopted for liner programming in this study and the heights of all Benchmarks were calculated in both case of applying site calibration and does not applying site calibration. The results were compared to Benchmark official height of the National Geographic Information Institute. The results showed that the average value of the height difference was 0.060m, and the standard deviation was 0.072m in Network-RTK without site calibration and the average value of the height difference was 0.040m, and the standard deviation was 0.047m in Network-RTK with the application of the site calibration. With linearization method to obtain the optimal solution for observations it showed that the height determination within 0.033m was available in GNSS Network-RTK positioning.