• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.14 no.2
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• pp.127-139
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• 1996

This paper presents a procedure to recover sea surface heights (SSH) and free-air (FA) gravity anomalies from dense satellite altimeter SSH data with enhanced accuracies over the full spectrum of the gravity field. A wavenumber correlation filtering (WCF) of co-linear SSH tracks is developed for the coherent signals of sub-surface geological masses. Orbital cross-over adjustments with bias parameters are applied to the filtered SSH data, which are then separated into two groups of ascending and descending tracks and gridded with tensioned splines. A directional sensitive filter (DSF) is developed to reduce residual errors in the orbital adjustments that appear as track patterned SSH. Finally, FA gravity anomalies can be obtained by the application of a gradient filter on a high resolution estimate of geoid undulations after subtracting dynamic sea surface topography (DSST) from the SSH. These procedures are applied to the Geosat Geodetic Mission (GM) data of the southern oceans in a test area of ca. $900km\;\times{1,200}\;km$ to resolve geoid undulations and FA gravity anomalies to wavelengths of-10 km and larger. Comparisons with gravity data from ship surveys, predictions by least squares collocation (LSC), and 2 versions of NOAA's predictions using vertical deflections illustrate the performance of this procedure for recovering all elements of the gravity spectrum. Statistics on differences between precise ship data and predicted FA gravity anomalies show a mean of 0.1 mgal, an RMS of 3.5 mgal, maximum differences of 10. 2 mgal and -18.6 mgal, and a correlation coefficient of 0.993 over four straight ship tracks of ca. 1,600 km where gravity changes over 150 mgals.

• Journal of Korea Water Resources Association
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• v.41 no.3
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• pp.325-340
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• 2008

This study employs Bayesian multiple regression analysis using the ordinary least squares method for regional low flow frequency analysis. The parameter estimates using the Bayesian multiple regression analysis were compared to conventional analysis using the t-distribution. In these comparisons, the mean values from the t-distribution and the Bayesian analysis at each return period are not significantly different. However, the difference between upper and lower limits is remarkably reduced using the Bayesian multiple regression. Therefore, from the point of view of uncertainty analysis, Bayesian multiple regression analysis is more attractive than the conventional method based on a t-distribution because the low flow sample size at the site of interest is typically insufficient to perform low flow frequency analysis. Also, we performed low flow prediction, including confidence interval, at two ungauged catchments in the Nakdong River basin using the developed Bayesian multiple regression model. The Bayesian prediction proves effective to infer the low flow characteristic at the ungauged catchment.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.4
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• pp.45-54
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• 2012

Location-based services with GPS positioning technology as a key technology, but recognizing the current location through satellite communication is not possible in an indoor location-aware technology, low-power short-range communication is primarily made of the study. Especially, as Chirp Spread Spectrum(CSS) based location-aware approach for low-power physical layer IEEE802.15.4a is selected as a standard, Ranging distance estimation techniques and data transfer speed enhancements have been more developed. It is known that the distance measured by CSS ranging has quite a lot of noise as well as its bias. However, the noise problem can be adjusted by modeling the non-zero mean noise value by a scaling factor which corresponds to the change of magnitude of a measured distance vector. In this paper, we propose a localization system using the CSS signal to measure distance for a mobile node taken a measurement of the exact coordinates. By applying the extended kalman filter and least mean squares method, the localization system is faster, more stable. Finally, we evaluate the reliability and accuracy of the proposed algorithm's performance by the experiment for the realization of localization system.

• Journal of Korea Water Resources Association
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• v.33 no.2
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• pp.263-276
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• 2000

This paper is to derive the probable rainfall depths and the probable rainfall intensity formulas for Inchon Metropolitan district. The annual maximum rainfall data from 10 min. to 6 hours have been collected from the Inchon weather station. Eleven types of probability distribution are considered to estimate probable rainfall depths for 12 different storm durations at the Inchon Metropolitan district. Three tests including Chi-square, Kolmogorov-Smimov and Cramer Von Mises with the graphical analysis are adopted to select the best probability distribution. The probable rainfall intensity formulas are then determined by the least squares method using the trial and error approach. Five types of Talbot type, Sherman type, Japanese type, Unified type I, and Unified type II are considered to determine the best type for the Inchon rainfall intensity. The root mean squared errors are computed to compare the accuracy from the derived formulas. It has been suggested that the probable rainfall intensities having Unified type I for the short term duration should be the most reliable formulas by considering the root mean squared errors and the difference between computed probable rainfall depth and estimated probable rainfall depth.

• Journal of Korean Academy of Nursing
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• v.36 no.5
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• pp.837-844
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• 2006

Purpose: This study was done to identify fat distribution and blood pressure according to anthropometric change patterns between NIDDM patients and control subjects. Methods: Cross-sectionally 167 NIDDM patients and 87 controls were studied. Previous maximal body weight and acute weight loss was obtained. Current height, body weight, BMI, waist-hip ratio(WHR), skinfold thicknesses(abdomen, subscapular & triceps), and blood pressure was measured. Three anthropometric change patterns were categorized by BMI changes from the maximum lifetim's BMI to the current time (obese-obese, obese-nonobese and nonobese-nonobese: obese: BMI$\geq$25kg/m$^2$, nonobese: BMI<25kg/m$^2$). The data was analyzed by $X^2$, t-test, age adjusted ANCOVA and Least Squares Means(LSM) for multiple comparison. Result: Acute body weight loss(p=0.01), anthropometric change types (p=0.001), WHR (p=0.05), and skinfold thickness (p=0.002) of NIDDM were significantly higher than those of the controls. The mean arterial pressure, WHR and skinfold thicknesses were greater in both obese-obese and obese-nonobese NIDDM and control subjects compared with both nonobese-nonobese NIDDM and control subjects. (all p's<0.05). Conclusion: NIDDM patients had more central and upper body adiposicity. Also both obese-obese and obese-nonobese NIDDM and control subjects had higher mean arterial pressures and central body obesity.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.1
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• pp.42-55
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• 2017

Since the phases and patterns of the climate adaptability of vegetation can greatly differ from region to region, an intensive pixel scale approach is required. In this study, Partial Least Squares (PLS) regression on satellite image-based vegetation index is conducted for to assess the effect of climate factors on vegetation productivity and to predict future productivity of forests vegetation in South Korea. The results indicate that the mean temperature of wettest quarter (Bio8), mean temperature of driest quarter (Bio9), and precipitation of driest month (Bio14) showed higher influence on vegetation productivity. The predicted 2050 EVI in future climate change scenario have declined on average, especially in high elevation zone. The results of this study can be used in productivity monitoring of climate-sensitive vegetation and estimation of changes in forest carbon storage under climate change.

• Asian-Australasian Journal of Animal Sciences
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• v.15 no.5
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• pp.732-739
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• 2002

Milk samples with different phenotype combination of $\{kappa}$-casein and ${\beta}$-lactoglobulin and different preheating temperatures of 30, 70, 75 and $80^{\circ}C$ were used for cheesemaking under laboratory conditions. For the 853 batches of cheese, mean composition was 59.64% total solids, 30.24% fat and 23.66% protein, and the whey contained 6.93% total solids, 0.30% fat and 0.87% protein. Least squares analysis of the data indicated that heating temperature of the milk and ${\kappa}$-CN/${\beta}$-LG phenotypes had significant effects on cheese and whey compositions. The total solids, fat and protein contents of cheese were negatively correlated with preheating temperatures of milk. Cheese from BB/BB phenotype milk had the highest and those from AA/AA phenotype milk had the lowest concentrations of total solids, fat and protein. Mean recoveries of milk components in the cheese were 53.71% of total solids, 87.15% of fat, and 80.32% of protein. For the 10 different types of milk, maximum recoveries of milk components in cheese occurred with preheating temperature of $70^{\circ}C$ or $75^{\circ}C$ and lowest recoveries occurred at $80^{\circ}C$. The whey averaged 6.94% total solids, 0.30% fat and 0.87% protein. Losses of milk components in the whey were lowest for milk preheated at $80^{\circ}C$ and for milk containing the BB/BB phenotype.

• Journal of Biosystems Engineering
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• v.37 no.6
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• pp.404-410
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• 2012

Purpose: The objective of this research was to select high quality cucumber (cucumis sativus) seed by classifying into viable or non-viable one using Raman spectroscopy. Method: Both transmission and back-scattering Raman spectra of viable and non-viable seeds in the range from $150cm^{-1}$ to $1890cm^{-1}$ were collected with a laser illumination. Results: The Raman spectra of cucumber seed showed Raman peaks with features of polyunsaturated fatty acids. The partial least squares-discriminant analysis (PLS-DA) to predict viable seeds was developed with measured transmission and backscattering spectra with Raman spectroscopy and germination test results. Various types of spectra pretreatment were investigated to develop the classification models. The results of developed PLS-DA models using the transmission spectra with mean normalization or range normalization, and back-scattering spectra with mean normalization treatment or baseline correction showed 100% discrimination accuracy. Conclusions: These results showed that Raman spectroscopy technologies can be used to select the high quality cucumber seeds.

• Nuclear Engineering and Technology
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• v.23 no.2
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• pp.200-209
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• 1991

A new semi-empirical average heat transfer correlation applicable for both laminar and turbulent film-wise condensation on a vertical surface has been presented. Re functional form of the present correlation is based on the representative existing correlations for laminar and turbulent film flows, whereas the numerical coefficients of the present correlation have been determined by the least squares method using experimental data obtained from the open literatures. In addition, the performance of the present as well as the seven existing correlations (four for laminar and three for turbulent film flow regimes) were evaluated for their accuracy and the range of application. The result shows that for laminar film filow regimes Zazuli's and the present correlations give the samllest values of mean error, whereas for turbulent film How regimes Kirkbride and Badger's and the present correlations produce the smallest values of mean error.

• Journal of the Korean Chemical Society
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• v.65 no.4
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• pp.254-259
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• 2021

The purpose of this work is the development of a method for an effective, less expensive, rapid, and simultaneous determination of three phenolic compounds (caffeic acid, gallic acid, and quercetin) widely present in food resources and known for their antioxidant powers. The method relies on partial least squares (PLS) calibration of UV-visible spectroscopic data. This model was applied to simultaneously determine, the concentrations of caffeic acid (CA), gallic acid (GA), and quercetin (Q) in six herb infusion extracts: basil, chive, laurel, mint, parsley, and thyme. A wavelength range (250-400) nm, and an experimental calibration matrix with 21 samples of ternary mixtures composed of CA (6.0-21.0 mg/L), GA (10.0-35.2 mg/L), and Q (6.4-17.5 mg/L) were chosen. Spectroscopic data were mean-centered before calibration. Two latent variables were determined using the contiguous block cross-validation procedure after calculating the root mean square error cross-validation RMSECV. Other statistic parameters: RMSEP, R², and Recovery (%) were used to determine the predictive ability of the model. The results obtained demonstrated that UV-visible spectrometry and PLS regression were successfully applied to simultaneously quantify the three phenolic compounds in synthetic ternary mixtures. Moreover, the concentrations of CA, GA and Q in herb infusion extracts were easily predicted and found to be 3.918-18.055, 9.014-23.825, and 9.040-13.350 mg/g of dry sample, respectively.