• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.4101-4101
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• 2001

Information of body composition (fat and protein) in living animal is important to determine the nutrients requirement. Deuterium oxide (D2O) dilution techniques, as one of isotope dilution techniques have been useful for the prediction of body composition. However, the determination of D2O concentration is time consuming and complicated. Therefore this study was conducted to develop a new method to predict D2O concentration in plasma using near infrared spectroscopy technique (NIRS). Four dairy cows in early lactation were used. They were fed total mixed ration containing conr silage, timothy hay, and concentrates to make 17.0%CP and 14.0 MJDE/kgDM. Dosing D2O was at week 1,3 and 5 after parturition. After dosing D2O, the blood was collected from hour 0 to 72. Blood samples were then centrifuge at 3,000 rpm for 10 minutes to obtain plasma. D2O concentration was analyzed by gas chromatograph (deuterium oxide analyzable system, HK102, Shokotsusyou) after extracted from plasma by liophilization. Plasma sample was scanned by NIRS using Pacific Scientific (Neotec) model 6500 (Perstorp Analytical, Silver Spring, MD) in the range of wavelength from 1100 to 2500 nm. Calibration equation was developed using multiple linear regression. Sample from one animal (cow #550; n: 74) was used for developing the calibration while the rest three animals were used for validating the equation. The range, R and SEC of the calibration set samples were 135-925 ppm, 0.93 and 48.1 ppm, respectively. Validation of the calibration equation for three individual cows was done and the average of NIR predicted value of D2O at each collection time from three weeks injection showed a high correlation. The range, r and 53 of plasma from cow #474 were 322-840 ppm,0.93 and 53.1; cow #478 were 146-951 ppm,0.95 and 39.8; cow #942 were 313-885 ppm,0.95 and 37.2, respectively. Judgement of accuracy based on ratio of standard deviation and standard error in validation set samples (RPD) for cow #474, #478 and #942 were 2.2,4.3 and 3.4, respectively. The error in application due to the variation between individual was considered smaller than the bias from collection period, however, this prediction can be overcome with correction of standard zero-minute concentration of blood. The results of this preliminary study on the use of NIRS for determination of D2O in plasma showed very promising as shown by a convenient and satisfy accuracy. Further study on various physiological stage of animal should be done.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1032-1032
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• 2001

Artificial Neural Network (ANN) calibration techniques have been used commercially for agricultural applications since the mid-nineties. Global models, based on transmission data from 850 to 1050 nm, are used routinely to measure protein and moisture in wheat and barley and also moisture in triticale, rye, and oats. These models are currently used commercially in approx. 15 countries throughout the world. Results concerning earlier European ANN models are being published elsewhere. Some of the findings from that study will be discussed here. ANN models have also been developed for coarsely ground samples of compound feed and feed ingredients, again measured in transmission mode from 850 to 1050 nm. The performance of models for pig- and poultry feed will be discussed briefly. These models were developed from a very large data set (more than 20,000 records), and cover a very broad range of finished products. The prediction curves are linear over the entire range for protein, fat moisture, fibre, and starch (measured only on poultry feed), and accuracy is in line with the performance of smaller models based on Partial Least Squares (PLS). A simple bias adjustment is sufficient for calibration transfer across instruments. Recently, we have investigated the possible use of ANN for a different type of NIR spectrometer, based on reflectance data from 1100 to 2500 nm. In one study, based on data for protein, fat, and moisture measured on unground compound feed samples, dedicated ANN models for specific product classes (cattle feed, pig feed, broiler feed, and layers feed) gave moderately better Standard Errors of Prediction (SEP) compared to modified PLS (MPLS). However, if the four product classes were combined into one general calibration model, the performance of the ANN model deteriorated only slightly compared to the class-specific models, while the SEP values for the MPLS predictions doubled. Brix value in molasses is a measure of sugar content. Even with a huge dataset, PLS models were not sufficiently accurate for commercial use. In contrast an ANN model based on the same data improved the accuracy considerably and straightened out non-linearity in the prediction plot. The work of Mr. David Funk (GIPSA, U. S. Department of Agriculture) who has studied the influence of various types of spectral distortions on ANN- and PLS models, thereby providing comparative information on the robustness of these models towards instrument differences, will be discussed. This study was based on data from different classes of North American wheat measured in transmission from 850 to 1050 nm. The distortions studied included the effect of absorbance offset pathlength variation, presence of stray light bandwidth, and wavelength stretch and offset (either individually or combined). It was shown that a global ANN model was much less sensitive to most perturbations than class-specific GIPSA PLS calibrations. It is concluded that ANN models based on large data sets offer substantial advantages over PLS models with respect to accuracy, range of materials that can be handled by a single calibration, stability, transferability, and sensitivity to perturbations.

• Korean Journal of Agricultural and Forest Meteorology
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• 제5권4호
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• pp.247-254
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• 2003

This study was conducted to develop site index equations by main species grown in Gyunggi and Chungcheong provinces using environmental factors obtained from a digital forest site map. For this, 28 environmental factors were regressed on site index by species. Four to five environmental factors by species were selected as independent variables in the best site index equations (coefficients of determination greater than 0.91). For these site index equations, three evaluation statistics, mean difference, standard deviation of difference, and standard error of difference, were applied to the data set. Site index equations by species relationships developed in this study effectively estimate forest productivity in the study area. However, the site index equation of Larix leptolepis showed a larger than expected bias between the estimated and the measured site index. The reason is not clear in this situation, but might be because of the small sample set. It will be necessary, therefore, to conduct more studies to determine the exact reason. It is also expected that the site index equations with a few environmental factors as independent variables could provide valuable information about species well suited to given site conditions. Site index equations for other species should be developed to establish a rational policy about the selection of best species for site conditions.

• Journal of the Korean earth science society
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• 제40권6호
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• pp.599-605
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• 2019

Rice yield (kg 10a^-1) in South Korea was estimated by meteorological variables that are influential factors in crop growth. This study investigated the possibility of anticipating the rice yield variability using a simple but an efficient statistical method, a multiple linear regression analysis, on the basis of the annual variation of meteorological variables. Due to heterogeneous environmental conditions by region, the yearly rice yield was assessed and validated for each province in South Korea. The monthly mean meteorological data for the period 1986-2018 (33 years) from 61 weather stations provided by Korean Meteorological Administration was used as the independent variable in the regression analysis. An 11-fold (leave-three-out) cross-validation was performed to check the accuracy of this method estimating rice yield at each province. This result demonstrated that temporal variation of rice yield by province in South Korea can be properly estimated using such concise procedure in terms of correlation coefficient (0.7, not significant). Furthermore, the estimated rice yield well captured spatial features of observation with mean bias of 0.7 kg 10a^-1 (0.15%). This method may offer useful information on rice yield by province in advance as long as accurate agro-meteorological forecasts are timely obtained from climate models.

• The Journal of Internal Korean Medicine
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• 제39권3호
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• pp.372-388
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• 2018

Objective: This study evaluates the effectiveness and safety of moxibustion for benign prostatic hyperplasia (BPH). Methods: Using the keywords "benign prostatic hyperplasia", "benign prostatic hypertrophy", "benign prostatic enlargement", "prostatic hyperplasia", and "moxibustion", we searched papers in numerous databases, including National Discovery for Science Leaders (NDSL), Korean Traditional Knowledge Portal (KTKP), Oriental Medicine Advanced Searching Integrated System (OASIS), Research Information Sharing Service (RISS), PubMed, Embase, and CENTRAL. The search range included randomized controlled trials (RCTs). Papers not matched with inclusion criteria were excluded. The methodological quality of each RCT was assessed using the Cochrane risk-of-bias tool. Where appropriate, meta-analyses were performed. Results: Initially, 77 studies were found. Of these, 11 duplicate studies were removed and 27 were excluded following title and abstract screening. After the remaining 39 papers were scanned, 13 RCTs were selected and analyzed. Among these 13 RCTs, five compared moxibustion therapy and oral medication, seven compared moxibustion plus acupuncture therapy and oral medication, and one compared moxibustion plus acupuncture therapy and sham-moxibustion. The meta-analysis showed positive results for the use of moxibustion therapy in terms of International Prostate Symptom Score (IPSS), Quality Of Life (QOL), Maximum Flow Rate (Qmax), Prostate Volume (PV), and the efficacy rate. The meta-analysis showed positive results for the use of moxibustion plus acupuncture therapy in terms of IPSS, QOL, and the efficacy rate. Conclusions: This meta-analysis of clinical trials suggests that moxibustion is effective intreating BPH patients. The results of this study could be applied to clinical treatment of BPH. However, additional large-scale clinical researches should be conducted.

• Environmental and Resource Economics Review
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• 제15권2호
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• pp.147-175
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• 2006

This paper attempts to incorporate three important factors-perceptions, behavior and valuation-in analysing consumers' responses to health risks from environmental pollutants. Using a survey sample of 500 consumers in the Chonbuk province area, this paper empirically investigated determinants of risk perceptions from using tap water as drinking water. Most consumers were considerably concerned about health risks from drinking tap water. Moreover, those subjective concerns were not random, but were systematically related to individuals' demographic variables such as age, gender, and family size. Those subjective beliefs also influenced respondents' purchase intentions on safer water bottles, in response to a contingent behavior question of presenting two types of water bottles. The technical risk information provided in the survey had significant effects on purchase intentions only when it was interacted with respondents' actual averting practice. In addition, the sample selection effects were present by eliminating respondents who decided not to purchase either of two types of water bottles. The potential selection bias had impacts on the coefficients of the price difference variable, and subsequently the estimates of the price increments for health risk reductions.

• The Journal of the Korea Contents Association
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• 제12권4호
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• pp.485-494
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• 2012

The role of admissions officers in universities is to evaluate applicants from a comprehensive perspective on the basis of diverse bases and materials for evaluation that include not only quantitative, but also qualitative information about applicants. Therefore, the crucial key to ensuring the success of the admissions officer system is to ensure the fairness of admission-related decisions and the integrity of individual admissions officers by urging them to render impartial evaluations based on professionalism and avoidance of bias. This study selected the major realm of the ethical education for admission officers on the basis or experts' opinions, and documentary research, and tried to secure the validity of the composed educational contents through the in-depth interviews and discussions with the incumbent admissions officers. The program must handle subjects that are intimately related to the actual experience of many admissions officers, and must be capable of inducing voluntary compliance from the officers. Therefore, the program suggested by this study focuses on three core areas of ethics: that is, 'interaction with society,' 'ethics and responsibilities involved in admission,' and 'legal obligations and roles of admissions officers.' To this end, it provides twelve sub-topics and learning materials. Providing this kind of ethical education programs for admissions officers will help not only to enhance the professionalism and ethical commitments of admissions officers, but also broadly to establish a fairer and more reliable admissions officer system.

• Journal of KIISE
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• 제44권8호
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• pp.803-812
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• 2017

T-commerce is technology-fusion service on which the user can purchase using data broadcasting technology based on bi-directional digital TVs. To achieve the best revenue under a limited environment in regard to the channel number and the variety of sales goods, organizing broadcast programs to maximize the expected sales considering the selling power of each product at each time slot. For this, this paper proposes a method to predict the sales of goods when it is assigned to each time slot. The proposed method predicts the sales of product at a time slot given the week-in-year and weather of the target day. Additionally, it combines a statistical predict model applying SVD (Singular Value Decomposition) to mitigate the sparsity problem caused by the bias in sales record. In experiments on the sales data of W-shopping, a T-commerce company, the proposed method showed NMAE (Normalized Mean Absolute Error) of 0.12 between the prediction and the actual sales, which confirms the effectiveness of the proposed method. The proposed method is practically applied to the T-commerce system of W-shopping and used for broadcasting organization.

• Asian Pacific Journal of Cancer Prevention
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• 제15권12호
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• pp.5029-5034
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• 2014

This study aimed to summarize published epidemiological evidence for the relationship between pancreatitis and subsequent risk of pancreatic cancer (PC). We searched Medline and Embase for epidemiological studies published by February $5^{th}$, 2014 examining the risk of PC in pancreatitis patients using highly inclusive algorithms. Information about first author, year of publication, country of study, recruitment period, type of pancreatitis, study design, sample size, source of controls and attained age of subjects were extracted by two researchers and Stata 11.0 was used to perform the statistical analyses and examine publication bias. Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated with the random effects model. A total of 17 articles documenting 3 cohort and 14 case-control studies containing 14,667 PC cases and 17,587 pancreatitis cases were included in this study. The pooled OR between pancreatitis and PC risk was 7.05 (95%CI: 6.42-7.75). Howeever, the pooled ORs of case-control and cohort studies were 4.62 (95%CI: 4.08-5.22) and 16.3 (95%CI: 14.3-18.6) respectively. The risk of PC was the highest in patients with chronic pancreatitis (pooled OR=10.35; 95%CI: 9.13-11.75), followed by unspecified type of pancreatitis (pooled OR=6.41; 95%CI: 4.93-8.34), both acute and chronic pancreatitis (pooled OR=6.13; 95%CI: 5.00-7.52), and acute pancreatitis (pooled OR=2.12; 95%CI: 1.59-2.83). The pooled OR of PC in pancreatitis cases diagnosed within 1 year was the highest (pooled OR=23.3; 95%CI: 14.0-38.9); and the risk in subjects diagnosed with pancreatitis for no less than 2, 5 and 10 years were 3.03 (95%CI: 2.41-3.81), 2.82 (95%CI: 2.12-3.76) and 2.25 (95%CI: 1.59-3.19) respectively. Pancreatitis, especially chronic pancreatitis, was associated with a significantly increased risk of PC; and the risk decreased with increasing duration since diagnosis of pancreatitis.

• Journal of Korean Society for Atmospheric Environment
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• 제33권5호
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• pp.445-457
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• 2017

In this study, we developed an approach to better account for uncertainties in estimated contributions from fine particulate matter ($PM_{2.5}$) modeling. Our approach computes a Concentration Correction Factor (CCF) which is a ratio of observed concentrations to baseline model concentrations. We multiply modeled direct contribution estimates with CCF to obtain revised contributions. Overall, the modeling system showed reasonably good performance, correlation coefficient R of 0.82 and normalized mean bias of 2%, although the model underestimated some PM species concentrations. We also noticed that model biases vary seasonally. We compared contribution estimates of major source sectors before and after applying CCFs. We observed that different source sectors showed variable magnitudes of sensitivities to the CCF application. For example, the total primary $PM_{2.5}$ contribution was increased $2.4{\mu}g/m^3$ or 63% after the CCF application. Out of a $2.4{\mu}g/m^3$ increment, line sources and area source made up $1.3{\mu}g/m^3$ and $0.9{\mu}g/m^3$ which is 92% of the total contribution changes. We postulated two major reasons for variations in estimated contributions after the CCF application: (1) monthly variability of unadjusted contributions due to emission source characteristics and (2) physico-chemical differences in environmental conditions that emitted precursors undergo. Since emissions-to-$PM_{2.5}$ concentration conversion rate is an important piece of information to prioritize control strategy, we examined the effects of CCF application on the estimated conversion rates. We found that the application of CCFs can alter the rank of conversion efficiencies of source sectors. Finally, we discussed caveats of our current approach such as no consideration of ion neutralization which warrants further studies.