• Magazine of the Korean Society of Agricultural Engineers
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• v.43 no.4
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• pp.113-119
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• 2001

Ammonia emissions during composting of hog manure mixed with sawdust were studied in four runs comprising a total of 22 pilot-scale reactor vessels. These four runs extended previous work and both verified and extended the previous conclusions. The pilot-scale vessels were 205 L insulated stainless steel drums that were aerated either continuously (high/low thermostatically controlled fans) or intermittently (5 min high fan 55 min off). Temperature ammonia emissions air flow rates carbon dioxide production and oxygen utilization moisture and dry matter reduction initial and final chemical compositions were measured. Ammonia emissions from the intermittently aerated vessels were only about 50% as great as those from the continuously aerated ones but this was found to be a result more related to total air flow than to aeration technique. All of the data for total result more related to total air flow were fitted with a linear regression line y=0.139x+29.835 where y is ammonia expressed as g of N and x is air flow in kg with $R^2$=0.6808. this general trend indicates that about 50% reduction in ammonia emissions can be achieved with 75% reduction in air flow. For the aeration techniques used the minimum oxygen level in te exhaust gas from the vessels was 5% and this is probably a resonable lower limit constraining air flow reduction. However within this constraint lower air flow now appears to be a technique that can reduce odorous ammonia emissions.

• Journal of Distribution Science
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• v.20 no.5
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• pp.105-117
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• 2022

Purpose: This research investigates ready-to-drink (RTD) coffee. Although the RTD coffee market is growing competitively, few studies have examined behavioral re-intention or repurchase intention in the context of this industry. Therefore, the objective of this study was to explore factors affecting the behavioral re-intention to purchase RTD coffee. Research design, data and methodology: Using the theory of planned behavior (TPB) as the underpinning theoretical framework, this study hypothesized that behavioral re-intention to purchase RTD coffee is influenced by the variables of the TPB and additional variables. A mixed-method research design was applied, starting with qualitative in-depth interviews and followed by a quantitative method. Data were collected using an online survey of coffee lovers. Multiple linear regression (MLR) was used to assess the hypothesized relationships in the proposed conceptual framework. Results: The results reveal that content sensory attribute beliefs are the strongest positive predictor of behavioral re-intention in Thailand, followed by perceived utilitarian value. In contrast, price signaling was negatively related to behavioral re-intention. Conclusions: The findings can help food and beverage companies to develop new coffee product lines to gain more market share, create integrated marketing communications to build brand awareness, and manage distribution channels and the supply chain.

• Advances in materials Research
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• v.11 no.1
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• pp.75-90
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• 2022

In this paper, functionality of soft computing algorithms such as Group method of data handling (GMDH), Random forest (RF), Random tree (RT), Linear regression (LR), M5P, and artificial neural network (ANN) have been looked out to predict the compressive strength of concrete mixed with marble powder. Assessment of result suggests that, the overall performance of ANN based model gives preferable results over the different applied algorithms for the estimate of compressive strength of concrete. The results of coefficient of correlation were maximum in ANN model (0.9139) accompanied through RT with coefficient of correlation (CC) value 0.8241 and minimum root mean square error (RMSE) value of ANN (4.5611) followed by RT with RMSE (5.4246). Similarly, other evaluating parameters like, Willmott's index and Nash-sutcliffe coefficient value of ANN was 0.9458 and 0.7502 followed by RT model (0.8763 and 0.6628). The end result showed that, for both subsets i.e., training and testing subset, ANN has the potential to estimate the compressive strength of concrete. Also, the results of sensitivity suggest that the water-cement ratio has a massive impact in estimating the compressive strength of concrete with marble powder with ANN based model in evaluation with the different parameters for this data set.

• Land and Housing Review
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• v.11 no.3
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• pp.1-9
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• 2020

This study fulfills an empirical analysis how the physical factors affect the formation of housing price with the block unit. Block unit houses are a type of housing that pursues comfort and convenience in that the characteristics of individual houses and apartment houses are mixed. Existing studies have focused only on the physical characteristics of various planning elements such as block-type residential complexes. Nevertheless, it is not known whether the physical characteristics of block-type residential complexes reflect the preferences of actual consumers. In addition, there are no sufficient studies on how to evaluate them from the market side. In this study, block-level detached housing sites the target complexes with 10 or more households built between 2002 and 2019. The target areas for analysis are 163 complexes in Paju, Namyangju, Goyang, Suwon, Yongin, Ansan, Gimpo, Incheon, Seongnam, Hwaseong and Gwangju, Gyeonggi-do. The physical elements that make up the unit housing were classified through factor analysis. Finally, regression analysis was conducted to establish the basis determining the price-forming factors. As a result of the analysis, the factors that influenced the price were the site area and the number of community facilities. The variable with negative influence was the distance from Seoul. Based on the results of this study, it can be said that the influence on price formation in various areas was confirmed by presenting the relationship between the facility composition and price of a detached house.

• Nutrition Research and Practice
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• v.7 no.4
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• pp.330-335
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• 2013

Data are limited on the association between dietary patterns and screen time among Korean adolescents. The present study identified dietary patterns of 691 adolescents, aged 13-18 years, who had participated in the Third Korean National Health and Nutrition Examination Survey (KNHANES III) and analyzed their associations with screen time. Screen time was defined as the time spent watching TV, using a computer, or playing video games was calculated as a sum of all these times. Dietary patterns and their factor scores were derived from a food frequency questionnaire using the factor analysis method. To analyze the association between dietary patterns and screen time, we conducted multiple linear regression analysis. We also performed multiple logistic regression analysis to estimate odds ratios (OR) of excessive screen time (2 hours or longer per day) and 95% confidence intervals (CI). We identified 2 dietary patterns labeled "the Korean healthy dietary pattern" and "the Western diet and fast foods pattern". The former included mixed grains, legumes, potatoes, red meat, eggs, fish, dairy products, fruits, vegetables, seaweeds, and mushrooms, whereas the latter included noodles, bread, red meat, poultry, fast foods, snack, and soft drinks. After controlling for potential confounding factors, factor scores for the Korean healthy dietary pattern were inversely associated (P-value for trend < 0.01) and those for the Western diet and fast foods pattern were positively associated with the screen time (P-value for trend < 0.01). Adolescents in the top tertile of the scores for the Korean healthy dietary pattern had a multivariable-adjusted OR [95% CI] of 0.44 (0.25-0.75) for excessive screen time compared with those in the lowest tertile. On the basis of these findings, adolescents who have excessive screen time may need to be encouraged to consume a more healthy diet.

• Mass Spectrometry Letters
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• v.5 no.4
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• pp.104-109
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• 2014

Nonmedical use of prescription stimulants such as methylphenidate (MPH) and amphetamine (AP) by normal persons has been increased to improve cognitive functions. Due to high potential for their abuse, reliable analytical methods were required to detect these prescription stimulants in biological samples. A direct injection liquid chromatography-tandem mass spectrometric (LC-MS/MS) method was developed and implemented for simultaneous determination of MPH, AP and their metabolites ritalinic acid (RA) and 4-hydroxyamphetamine (HAP) in human urine. Urine sample was centrifuged and the upper layer ($100{\mu}L$) was mixed with $800{\mu}L$ of distilled water and $100{\mu}L$ of internal standards ($0.2{\mu}g/mL$ in methanol). The mixture was then directly injected into the LC-MS/MS system. The mobile phase was composed of 0.2% formic acid in distilled water (A) and acetonitrile (B). Chromatographic separation was performed by using a Capcell Pak MG-II C18 ($150mm{\times}2.0mm$ i.d., $5{\mu}m$, Shiseido) column and all analytes were eluted within 5 min. Linear least-squares regression with a 1/x weighting factor was used to generate a calibration curve and the assay was linear from 20 to 1500 ng/mL (HAP), 40-3000 ng/mL (AP and RA) and 2-150 ng/mL (MPH). The intra- and inter-day precisions were within 16.4%. The intra- and inter-day accuracies ranged from -15.6% to 10.8%. The limits of detection for all the analytes were less than 4.7 ng/mL. The suitability of the method was examined by analyzing urine samples from drug abusers.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.1044-1051
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• 2002

This paper proposes a two-phase mathematical programming approach by considering classification gap to solve the proposed credit scoring problem so as to complement any theoretical shortcomings. Specifically, by using the linear programming (LP) approach, phase 1 is to make the associated decisions such as issuing grant of credit or denial of credit to applicants. or to seek any additional information before making the final decision. Phase 2 is to find a cut-off value, which minimizes any misclassification penalty (cost) to be incurred due to granting credit to 'bad' loan applicant or denying credit to 'good' loan applicant by using the mixed-integer programming (MIP) approach. This approach is expected to and appropriate classification scores and a cut-off value with respect to deviation and misclassification cost, respectively. Statistical discriminant analysis methods have been commonly considered to deal with classification problems for credit scoring. In recent years, much theoretical research has focused on the application of mathematical programming techniques to the discriminant problems. It has been reported that mathematical programming techniques could outperform statistical discriminant techniques in some applications, while mathematical programming techniques may suffer from some theoretical shortcomings. The performance of the proposed two-phase approach is evaluated in this paper with line data and loan applicants data, by comparing with three other approaches including Fisher's linear discriminant function, logistic regression and some other existing mathematical programming approaches, which are considered as the performance benchmarks. The evaluation results show that the proposed two-phase mathematical programming approach outperforms the aforementioned statistical approaches. In some cases, two-phase mathematical programming approach marginally outperforms both the statistical approaches and the other existing mathematical programming approaches.

• Nutrition Research and Practice
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• v.15 no.6
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• pp.789-797
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• 2021

BACKGROUD/OBJECTIVES: Registered dietitian nutritionists (RDN) are providers of medical nutrition therapy (MNT) to address health and chronic disease. Traditionally, RDNs have provided care in healthcare facilities including hospitals and private care facilities. The purpose of this study was to determine how RDN individualized MNT in the home impacted nutrition, physical activity, and food security. SUBJECTS/METHODS: This is a secondary data analysis. The mean age of the participants (n = 1,007) was 51.6 years old with a mean body mass index (BMI) of 34.1 kg/m². Individualized MNT visits were delivered by an RDN in the home setting from January to December 2019. Participants were referred by healthcare professionals or self-referred. Participants had MNT benefits covered by their health insurance plan (43.3% Medicaid; 39.8% private insurance; 7.9% Medicare, 9% other). Health outcomes related to nutrition care were measured. Outcomes included self-reported consumption of nutrition factors and physical activity. Our secondary outcome focused on food security. The changes in weight, BMI, physical activity, and nutrition factors were analyzed by a linear regression model or linear mixed model, adjusting for age, sex, baseline value, and number of appointments. Food security was summarized in a 2 by 2 contingency table. RESULTS: Baseline values had significantly negative impacts for all changes and number of appointments was significant in the changes for weight and BMI. Increases in physical activity were significant for both female and male participants, 10.4 and 12.6 minutes per day, respectively, while the changes in weight and BMI were not. Regarding dietary factors, the consumption total servings per day of vegetables (0.13) and water (3.35) significantly increased, while the consumption of total servings of whole grain (-0.27), fruit (-0.32), dairy (-0.80) and fish (-0.81) significantly decreased. About 24% (of overall population) and 45% (of Medicaid population) reported improvements in food security. CONCLUSIONS: This study found that home visits were a useful setting for MNT delivered by RDNs. There is a strong need for individualized counseling to meet the participants' needs and personal goals.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.32 no.3
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• pp.221-230
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• 2022

Objectives: The aim of this study is to evaluate the association between shiftwork and skeletal muscle mass index in a single university health check-up. Methods: We used data from 98,227 workers who answered in a special interview on health check-up at a local university hospital from 2014 to 2020. Pearson correlation analysis was conducted for comparing the association between skeletal muscle mass index and demographic and hematological variables in shiftwork and non-shiftwork groups. Mixed linear model analysis after controlling demographic and hematological variables was used to analyze the difference of skeletal muscle mass index between groups at every visit for seven years. Results: In linear regression analysis, the variables most significantly correlated with skeletal muscle index in both groups were shiftwork(p=0.049), BMI(p<0.001), hypertension(p=0.024), platelet(p<0.001), total protein (p<0.001), AST(p=0.028), ALT(p=0.003), ALP(p<0.001), total cholesterol(p=0.002), triglyceride(p=0.019), BUN (p=0.001), creatinine(p<0.001), and uric acid(p=0.002). After the adjustment for demographic and hematologic variables, the skeletal muscle mass index at every visit was decreased both in the shiftwork group and non-shiftwork group. The slope of the shiftwork group was -0.240 and non-shiftwork group -0.149, showing a significant difference (p<0.001). Conclusions: In the shiftwork group, the skeletal muscle mass index showed a tendency to decrease markedly over time compared to the non-shiftwork group. It is presumed that shift workers' skeletal muscle health was adversely affected by changes in the biological clock due to changes in wake-up and sleep patterns, and changes in food intake.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.17
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• pp.7785-7788
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• 2015

Utilization of high energy photons (>10MV) with an optimal weight using a mixed energy technique is a practical way to generate a homogenous dose distribution while maintaining adequate target coverage in intact breast radiotherapy. This study represents a model for estimation of this optimal weight for day to day clinical usage. For this purpose, treatment planning computed tomography scans of thirty-three consecutive early stage breast cancer patients following breast conservation surgery were analyzed. After delineation of the breast clinical target volume (CTV) and placing opposed wedge paired isocenteric tangential portals, dosimeteric calculations were conducted and dose volume histograms (DVHs) were generated, first with pure 6MV photons and then these calculations were repeated ten times with incorporating 18MV photons (ten percent increase in weight per step) in each individual patient. For each calculation two indexes including maximum dose in the breast CTV ($D_{max}$) and the volume of CTV which covered with 95% Isodose line ($V_{CTV,95%IDL}$) were measured according to the DVH data and then normalized values were plotted in a graph. The optimal weight of 18MV photons was defined as the intersection point of $D_{max}$ and $V_{CTV,95%IDL}$ graphs. For creating a model to predict this optimal weight multiple linear regression analysis was used based on some of the breast and tangential field parameters. The best fitting model for prediction of 18MV photons optimal weight in breast radiotherapy using mixed energy technique, incorporated chest wall separation plus central lung distance (Adjusted R2=0.776). In conclusion, this study represents a model for the estimation of optimal beam weighting in breast radiotherapy using mixed photon energy technique for routine day to day clinical usage.