• Journal of the Korean Geographical Society
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• v.51 no.4
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• pp.509-523
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• 2016

The soil prediction can provide quantitative soil information for sustainable mountainous ecosystem management. Visible near infrared spectroscopy, one of soil prediction methods, has been applied to predict several soil properties with effective costs, rapid and nondesctructive analysis, and satisfactory accuracy. Spectral preprocessing is a essential procedure to correct noisy spectra for visible near infrared spectroscopy. However, there are no attempts to evaluate various spectral preprocessing methods. We tested 5 different pretreatments, namely continuum removal, Savitzky-Golay filter, discrete wavelet transform, 1st derivative, and 2nd derivative to predict soil carbon(C) and nitrogen(N). Partial least squares regression was used for the prediction method. The total of 153 soil samples was split into 122 samples for calibration and 31 samples for validation. In the all range, absorption was increased with increasing C contents. Specifically, the visible region (650nm and 700nm) showed high values of the correlation coefficient with soil C and N contents. For spectral preprocessing methods, continuum removal had the highest prediction accuracy(Root Mean Square Error) for C(9.53mg/g) and N(0.79mg/g). Therefore, continuum removal was selected as the best preprocessing method. Additionally, there were no distinct differences between Savitzky-Golay filter and discrete wavelet transform for visual assessment and the methods showed similar validation results. According to the results, we also recommended Savitzky-Golay filter that is a simple pre-treatment with continuum removal.

• Sleep Medicine and Psychophysiology
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• v.6 no.1
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• pp.52-60
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• 1999

Objectives: With the object of finding the appropriate conditions and algorithms for dimensional analysis of human EEG, we calculated correlation dimensions in the various condition of sampling rate and data aquisition time and improved the computation algorithm by taking advantage of bit operation instead of log operation. Methods: EEG signals from 13 scalp lead of a man were digitized with A-D converter under the condition of 12 bit resolution and 1000 Hertz of sampling rate during 32 seconds. From the original data, we made 15 time series data which have different sampling rate of 62.5, 125, 250, 500, 1000 hertz and data acqusition time of 10, 20, 30 second, respectively. New algorithm to shorten the calculation time using bit operation and the Least Trimmed Squares(LTS) estimator to get the optimal slope was applied to these data. Results: The values of the correlation dimension showed the increasing pattern as the data acquisition time becomes longer. The data with sampling rate of 62.5 Hz showed the highest value of correlation dimension regardless of sampling time but the correlation dimension at other sampling rates revealed similar values. The computation with bit operation instead of log operation had a statistically significant effect of shortening of calculation time and LTS method estimated more stably the slope of correlation dimension than the Least Squares estimator. Conclusion: The bit operation and LTS methods were successfully utilized to time-saving and efficient calculation of correlation dimension. In addition, time series of 20-sec length with sampling rate of 125 Hz was adequate to estimate the dimensional complexity of human EEG.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1121-1121
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• 2001

A previous study (Berzaghi et al., 2001) evaluated the performance of 3 calibration methods, modified partial least squares (MPLS), local PLS (LOCAL) and artificial neural networks (ANN) on the prediction of the chemical composition of forages, using a large NIR database. The study used forage samples (n=25,977) from Australia, Europe (Belgium, Germany, Italy and Sweden) and North America (Canada and U.S.A) with reference values for moisture, crude protein and neutral detergent fibre content. The spectra of the samples were collected using 10 different Foss NIR Systems instruments, only some of which had been standardized to one master instrument. The aim of the present study was to evaluate the behaviour of these different calibration methods when predicting the same samples measured on different instruments. Twenty-two sealed samples of different kind of forages were measured in duplicate on seven instruments (one master and six slaves). Three sets of near infrared spectra (1100 to 2500nm) were created. The first set consisted of the spectra in their original form (unstandardized); the second set was created using a single sample standardization (Clone1); the third was created using a multiple sample procedure (Clone6). WinISI software (Infrasoft International Inc., Port Mathilda, PA, USA) was used to perform both types of standardization, Clone1 is just a photometric offset between a “master” instrument and the “slave” instrument. Clone6 modifies both the X-axis through a wavelength adjustment and the Y-axis through a simple regression wavelength by wavelength. The Clone1 procedure used one sample spectrally close to the centre of the population. The six samples used in Clone 6 were selected to cover the range of spectral variation in the sample set. The remaining fifteen samples were used to evaluate the performances of the different models. The predicted values for dry matter, protein and neutral detergent fibre from the master Instrument were considered as “reference Y values” when computing the statistics RMSEP, SEPC, R, Bias, Slope, mean GH (global Mahalanobis distance) and mean NH (neighbourhood Mahalanobis distance) for the 6 slave instruments. From the results we conclude that i) all the calibration techniques gave satisfactory results after standardization. Without standardization the predicted data from the slaves would have required slope and bias correction to produce acceptable statistics. ii) Standardization reduced the errors for all calibration methods and parameters tested, reducing not only systematic biases but also random errors. iii) Standardization removed slope effects that were significantly different from 1.0 in most of the cases. iv) Clone1 and Clone6 gave similar results except for NDF where Clone6 gave better RMSEP values than Clone1. v) GH and NH were reduced by half even with very large data sets including unstandardized spectra.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.3 s.345
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• pp.49-58
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• 2006

In this paper, a curve-fitting channel estimation method is proposed for orthogonal frequency division multiplexing (OFDM) system in a time-varying frequency-selective fading channel. The method can greatly improve channel state information (CSI) estimation accuracy by performing smoothing and interpolation through consecutive curve-fitting processes in both time domain and frequency domain. It first evaluates least-squares (LS) estimates using pilot symbols and then the estimates are approximated to a polynomial with proper degree in the LS error sense, starting from one preferred domain in which pilots we densely distributed. Smoothing, interpolation, and prediction are performed subsequently to obtain CSI estimates for data transmission. The channel estimation processes are completed by smoothing and interpolating CSI estimates in the other domain once again using the channel estimates obtained in one domain. The performance of proposed method is influenced heavily on the time variation and frequency selectivity of channel and pilot arrangement. Hence, a proper degree of polynomial and an optimum approximation interval according to various system and channel conditions are required for curve-fitting. From extensive simulation results in various channel environments, we see that the proposed method performs better than the conventional methods including the optimal Wiener filtering method, in terms of the mean square error (MSE) and bit error rate (BER).

• Korean Journal of Community Nutrition
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• v.20 no.2
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• pp.129-140
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• 2015

Objectives: We examined the association between the adherence to dietary guidelines for breast cancer survivors and health-related quality of life in a cross-sectional study of Korean breast cancer survivors. Methods: A total of 157 women aged 21 to 79 years who had been diagnosed with stage I to III breast cancers according to the American Joint Committee on Cancer (AJCC) and had breast cancer surgery at least 6 months before the baseline were included. We used a Korean version of the Core 30 (C30) and Breast cancer 23 (BR23) module of the European Organization for Research and Treatment Cancer Quality of Life Questionnaire (EORTC-QLQ), both of which have been validated for Koreans. Participants were asked about their adherence to dietary guidelines for breast cancer survivors, suggested by the Korean breast cancer society, using a 5-point Likert scale. We summed dietary guideline adherence scores for each participant and calculated the least squares means of health-related quality of life according to dietary guideline adherence scores using the generalized linear model. Results: Breast cancer survivors who had higher adherence to dietary guidelines for breast cancer survivors had lower constipation scores than those with lower adherence (p for trend=0.01). When we stratified by the stage at diagnosis, this association was limited to those who had been diagnosed with stage II or III breast cancers. Also, sexual functioning scores increased significantly with increasing adherence scores of dietary guidelines among those with stage II or III breast cancers (p for trend < 0.001). However, among those who had been diagnosed with stage I, higher scores of dietary guidelines were associated with higher scores of pain (p for trend=0.03) and breast symptoms (p for trend=0.05). Conclusions: Our study suggested that the health-related quality of life levels of breast cancer survivors are associated with the adherence to dietary guidelines and may differ by the stage of the breast cancer.

• Journal of Energy Engineering
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• v.22 no.3
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• pp.245-249
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• 2013

This paper attempts to estimate the kerosene demand function in Korea over the period 1981-2012. As the kerosene demand function provides us information on the pattern of consumer's kerosene consumption, it can be usefully utilized in predicting the impact of policy variables such as kerosene price and forecasting the demand for kerosene. We apply least absolute deviations and least median squares estimation methods as a robust approach to estimating the parameters of the kerosene demand function. The results show that short-run price and income elasticities of the kerosene demand are estimated to be -0.468 and 0.409, respectively. They are statisitically significant at the 1% level. The short-run price and income elasticities portray that demand for kerosene is price- and income-inelastic. This implies that the kerosene is indispensable goods to human-being's life, thus the kerosene demand would not be promptly adjusted to responding to price and/or income change. However, long-run price and income elasticities reveal that the demand for kerosene is price- and income-elastic in the long-run.

• Journal of the Korean Chemical Society
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• v.29 no.2
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• pp.73-79
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• 1985

The crystal and molecular structure of acetone 4-benzylthiosemicarbazone, $C_{11}H_{15}N_3S$, has been determined by the single crystal X-ray diffraction methods. The crystals are monoclinic, space group $P2_1/c$ with unit cell dimensions, a = 10.249(7), b = 11.403(9), c = 10.149(7)TEX>${\AA}$, ${\beta}$ = 90.9$(1)^0$ and z = 4. The intensities were collected on an automatic four-circle diffractometer with graphite-monochromated Mo-$K_{\alpha}$ radiation. The structure was solved by direct methods and refined by full matrix least-squares methods. The final R was 0.045 for 1554 observed reflections. S-C(8)-N(2)-N(3)-C(9)-C(10) atoms make a zigzag planar chain. There are no unusual bond lengths and angles. There are two independent hydrogen bonds in the crystal structure. One is N-H${\cdots}$S intermolecular hydrogen bond with the length of 3.555${\AA}$ and makes dimer-like units. The other is N-H${\cdots}$N intramolecular hydrogen bond with the length of 2.568${\AA}$. The structure was compared with those of other thiosemicarbazone derivatives.

• Journal of Korean Society of Transportation
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• v.18 no.4
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• pp.117-126
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• 2000

Conventional methods for collecting origin-destination trips have been mainly relied on the surveys of home or roadside interview. However, the methods tend to be costly, labor intensive and time disruptive to the trip makers, thus the methods are not considered suitable for Planning applications such as routing guidance, arterial management and information Provision, as the parts of deployments in Intelligent Transport Systems Motivated by the problems, more economic ways to estimate origin-destination trip tables have been studied since the late 1970s. Some of them, which have been estimating O-D table from link traffic counts are generally Entropy maximizing, Maximum likelihood, Generalized least squares(GLS), and Bayesian inference estimation etc. In the Paper, with user equilibrium constraint we formulate GLS problem for estimating O-D trips and develop a solution a1gorithm by using Genetic Algorithm, which has been known as a g1oba1 searching technique. For the purpose of evaluating the method, we apply it to Seoul inner ringroad and compare it with gradient method proposed by Spiess(1990). From the resu1ts we fond that the method developed in the Paper is superior to other.

• Journal of the Korean association of regional geographers
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• v.22 no.1
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• pp.251-266
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• 2016

Intelligent interpolation methods such as dasymetric mapping are considered to be the best way to disaggregate zone-based population data by observing and utilizing the internal variation within each source zone. This research reviews the advantages and problems of the dasymetric mapping method, and presents a geographically weighted regression (GWR) based method to take into consideration the spatial heterogeneity of population density - land cover relationship. The locally adaptive intelligent interpolation method is able to make use of readily available ancillary information in the public domain without the need for additional data processing. In the case study, we use the preclassified National Land Cover Dataset 2011 to test the performance of the proposed method (i.e. the GWR-based multi-class dasymetric method) compared to four other popular population estimation methods (i.e. areal weighting interpolation, pycnophylactic interpolation, binary dasymetric method, and globally fitted ordinary least squares (OLS) based multi-class dasymetric method). The GWR-based multi-class dasymetric method outperforms all other methods. It is attributed to the fact that spatial heterogeneity is accounted for in the process of determining density parameters for land cover classes.

• Journal of Food Hygiene and Safety
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• v.39 no.1
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• pp.35-43
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• 2024

Numerous methods have been applied to assess the antibacterial effectiveness of hand hygiene products. However, the different results obtained through various evaluation methods have complicated our understanding of the real efficacy of the products. Few studies have compared test methods for assessing the efficacy of hand hygiene products. In particular, reports on ex vivo pig skin testing are limited. This study aimed to compare and characterize the methodologies applied for evaluating hand hygiene products, involving in vitro, ex vivo, and in vivo approaches, applicable to both leave-on sanitizers and wash-off products. Our further aim was to enhance the reliability of ex vivo test protocols by identifying influential factors. We performed an in vitro method (EN1276) and an in vivo test (EN1499 and ASTM2755) with at least 20 participants, against Serratia marcescens or Escherichia coli and Staphylococcus aureus. For the ex vivo experiment, we used pig skin squares prepared in the same way as those used in the in vivo test method and determined the optimal treated sample volumes for sanitizers and the amount of water required to wash off the product. The hand sanitizers showed at least a 5-log reduction in bacterial load in the in vitro test, while they showed little antibacterial activity in the in vivo and ex vivo tests, particularly those with a low alcohol content. For the hand wash products, the in vitro test was limited because of bubble formation or the high viscosity of the products and it showed low antibacterial activity of less than a 1-log reduction against E. coli. In contrast, significantly higher log reductions were observed in ex vivo and in vivo tests, consistently demonstrating these results across the two methods. Our findings revealed that the ex vivo and in vivo tests reflect the two different antibacterial mechanisms of leave-on and wash-off products. Our proposed optimized ex vivo test was more rapid and more precise than the in vitro test to evaluate antibacterial results.