• Journal of Animal Science and Technology
• /
• v.46 no.3
• /
• pp.335-346
• /
• 2004

Factors associated with milk urea nitrogen on milk yield and milk composition were investigated in this study regarding feeding management and Physiological status of lactating cows. The data for 3 years between 1999 and 2002 for this study were collected from 129,645 cows by Korean Agricultural Cooperatives Federation. The objectives of this study were to describe the relationships between milk urea concentrations and seasonal factors, cow factors and production of milk, milk fat, protein and somatic cell score(SCS). Milk urea was highest in summer and it also showed a nonlinear association with milk yield. Milk yield was higher at milk urea concentrations of 21 ${\sim}$ 24mg/dl, however it decreased at higher level of milk urea concentrations than 24mg/dl. Milk urea was higher with increased parities of cows and in particular, at 3 to 4 parities. There was a negative association between milk urea and SCS in milk. SCS in milk was lowest at milk urea concentrations of 2l${\sim}$24mg/dl. Milk fat and milk protein were greatly affected by days in milk(DIM), year of birth, season and milk urea concentrations, respectively. While milk urea increased in summer, milk fat and protein were decreased. Milk protein decreased according to longer days in milk. With regard to the influences of parity, milk protein in overall was negatively correlated to milk urea in all lactations, however the extent of decrease of milk protein at high concentrations of milk urea was bigger at third lactation. The balanced supply of energy and protein to the animals might have greatly affected the urea concentrations and protein content of milk.

• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.51 no.5
• /
• pp.386-395
• /
• 2006

The core questions for determining nitrogen topdress rate (Npi) at panicle initiation stage (PIS) are 'how much nitrogen accumulation during the reproductive stage (PNup) is required for the target rice yield or protein content depending on the growth and nitrogen nutrition status at PIS?' and 'how can we diagnose the growth and nitrogen nutrition status easily at real time basis?'. To address these questions, two years experiments from 2001 to 2002 were done under various rates of basal, tillering, and panicle nitrogen fertilizer by employing a rice cultivar, Hwaseongbyeo. The response of grain yield and milled-rice protein content was quantified in relation to RVIgreen (green ratio vegetation index) and SPAD reading measured around PIS as indirect estimators for growth and nitrogen nutrition status, the regression models were formulated to predict PNup based on the growth and nitrogen nutrition status and Npi at PIS. Grain yield showed quadratic response to PNup, RVIgreen around PIS, and SPAD reading around PIS. The regression models to predict grain yield had a high determination coefficient of above 0.95. PNup for the maximum grain yield was estimated to be 9 to 13.5 kgN/10a within the range of RVIgreen around PIS of this experiment. decreasing with increasing RVIgreen and also to be 10 to 11 kgN/10a regardless of SPAD readings around PIS. At these PNup's the protein content of milled rice was estimated to rise above 9% that might degrade eating quality seriously Milled-rice protein content showed curve-linear increase with the increase of PNup, RVIgreen around PIS, and SPAD reading around PIS. The regression models to predict protein content had a high determination coefficient of above 0.91. PNup to control the milled-rice protein content below 7% was estimated as 6 to 8 kgN/10a within the range of RVIgreen and SPAD reading of this experiment, showing much lower values than those for the maximum grain yield. The recovery of the Npi applied at PIS ranged from 53 to 83%, increasing with the increased growth amount while decreasing with the increasing Npi. The natural nitrogen supply from PIS to harvest ranged from 2.5 to 4 kg/10a, showing quadratic relationship with the shoot dry weight or shoot nitrogen content at PIS. The regression models to estimate PNup was formulated using Npi and anyone of RVIgreen, shoot dry weight, and shoot nitrogen content at PIS as predictor variables. These models showed good fitness with determination coefficients of 0.86 to 0.95 The prescription method based on the above models predicting grain yield, protein content and PNup and its constraints were discussed.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.19 no.10
• /
• pp.243-253
• /
• 2018

This study aimed to investigate the effects of DCI on glucose control, quality of life(SF-36 Version 2.0, Korean) and SDSCA(Summary of Diabetes Self-Care Activities) in patients with type 2 diabetes mellitus. A randomized, double-blind, placebo-controlled study was performed on 46 patients with HbA1c 7.0% taking triple anti-diabetic drug regimen who visited the department of Endocrinology and Metabolism in Chungnam National University Hospital between March 2015 and May 2016. As a result, DCI treatment in the intervention group resulted in significantly reduced HbA1c levels $8.75{\pm}0.79%$(baseline), $8.36{\pm}1.03%$(after 12weeks), and $8.65{\pm}0.81%$(after 24weeks). However, patients in the control group did not show any significant change. Interestingly, both DCI treatment group and the control group significantly showed improvements in SDSCA. Participants in the intervention group showed a small yet significant improvement in their only fasting blood glucose test in SDSCA and revealed significant increase in the quantitative levels of quality of life, from $73.05{\pm}16.85$ to $82.74{\pm}10.68$. By using pathway analysis, improvement of SDSCA scores(${\beta}=-0.505$, t=-2.743) was the most influential factor to the fasting blood glucose. The quality of life of patients with type 2 diabetes mellitus was affected by changes of SDSCA scores(${\beta}=0.411$, t=2.024) and fasting c-peptide(${\beta}=-0.445$, t=-2.668) in DCI treatment group. In conclusion, treatment of DCI effectively improved glucose control in patients with type 2 DM(HbA1c level>7.0%) after 12 weeks of treatment, although it had no impact on glucose control after 24 weeks of treatment. Improved glucose control may encourage diabetic patients to conduct self-care activities and improve the quality of life. Based on the present study, we suggest that diabetes self-management, as well as consideration of comprehensive laboratory findings, may be important factor in regulating the quality of life in type 2 DM patients.

• Journal of Korean Tunnelling and Underground Space Association
• /
• v.20 no.3
• /
• pp.543-560
• /
• 2018

With the increased development in downtown underground space facilities that vertically cross under a railway at a shallow depth, the demand for non-open cut method is increasing. However, most construction sites still adopt the pipe roof method, where medium and large diameter steel pipes are pressed in to form a roof, enabling excavation of the inside space. Among the many factors that influence the loosening region and loads that occur while pressing in steel pipes, the size of the pipe has the largest impact, and this factor may correspond to the magnitude of load applied to the underground structure inside the steel pipe roof. The super equilibrium method (SEM) has been developed to minimize ground disturbance and loosening load, and uses small diameter pipes of approximately 114 mm instead of conventional medium and large diameter pipes. This small diameter steel pipe is called an SEM pile. After SEM piles are pressed in and the grouting reinforcement is constructed, a crossing structure is pressed in by using a hydraulic jack without ground subsidence or heaving. The SEM pile, which plays the role of timbering, is a fore-poling pile of approximately 5 m length that prevents ground collapse and supports surface load during excavation of toe part. The loosening region should be adequately calculated to estimate the spacing and construction length of the piles and stiffness of members. In this paper, we conducted a comparative analysis of calculations of loosening load that occurs during the press-in of SEM pile to obtain an optimal design of SEM. We analyzed the influence of factors in main theoretical and empirical formulas applied for calculating loosening regions, and carried out FEM analysis to see an appropriate loosening load to the SEM pile. In order to estimate the soil loosening caused by actual SEM-pile indentation and excavation, a steel pipe indentation reduction model test was conducted. Soil subsidence and soil loosening were investigated quantitatively according to soil/steel pipe (H/D).

• Journal of the Korea Organic Resources Recycling Association
• /
• v.23 no.2
• /
• pp.36-46
• /
• 2015

Integration of crop-livestock farming has been a problem-solving mode for abatement of environmental pollution and recovery of resources in recent years. The objectives of this study were 1) to suggest the customized integration of crop-livestock farming model reflecting the regional characteristics through in-depth analysis of case study and 2) to analyze the livestock nutrients flow in terms of three primary elements as nitrogen(N), phosphorous(P), and potassium(K). The personal interview and survey were carried out in 2012 for a total of 161 farms from four different regions(NS, NW, JJ, YC) in South Korea. The mass balance analysis was used to suggest and evaluate the models for two sites(JJ and YC). The results showed that NS and NW sites produced relatively more livestock manure than the sites of YC and JJ because of the regional differences in livestock numbers and urbanization. The models were suggested for the site JJ and site YC, and 'two track model(energy and resource recovery)' and 'dispersal type model' were assigned respectively. For the nutrient flows, the releasing P and K with new models had increased up to 7%, while N release had decreased down to 15% in both YC and JJ sites compared to the present treatment system. Estimated value showed that there was oversupply of N (719 ton/yr) and $P_2O_5$ (1,269 ton/yr) in YC and deficiency of N (671 ton/yr) and excessive $P_2O_5$ (32 ton/yr) in JJ respectively. Therefore, P runoff has to be considered an eutrophication occurs in rural small stream when an integration of crop-livestock farm system is applied into both sites.

• Journal of Digital Convergence
• /
• v.16 no.3
• /
• pp.249-259
• /
• 2018

This research had intended to find out regarding the present influences of the Smart Work on the intention to use continuously with the staff members working in the small- and medium-sized enterprises as the subject. And, finally, it had intended to find out about the Smart Work environments of the IT corporations and the non-IT corporations. For this research, the questionnaire survey data were collected from the staff members working at the small- and medium-sized enterprises. Through the questionnaire survey data that were collected, an empirical analysis was carried out. And, through the reliability analysis, the feasibility analysis, the discriminatory feasibility analysis, and the inspection of the degree of suitableness of the structural equation model, finally, the research model was verified and, finally, a difference analysis of the IT corporations and the non-IT corporations was carried out. Regarding the results of the analysis of the research, it appeared that the factors of the job efficiency and the job autonomy of the special characteristics of the job had the positive influences on the usefulness and the job satisfaction, which were the parameters and which were perceived. And it appeared that the time flexibility of the job form could not have any influences on the usefulness and the job satisfaction, which were the parameters and which were perceived. And it appeared that the spatial flexibility had the influences on the job satisfaction only. The perceived usefulness, which was a parameter, had the positive influences on the job satisfaction and the intention to use continuously. And, finally, the job satisfaction had the positive influences on the intention to use continuously. And it appeared that there were the differences, too, between the IT corporations and the non-IT corporations. It is thought that, through the results of this research and through the Smart Work environment, the positive influences on the workers and the organizations could be induced and that a better working environment than previously can be provided to the workers to fit the special characteristics of the corporations.

• Journal of dental hygiene science
• /
• v.14 no.2
• /
• pp.158-166
• /
• 2014

This study is trying to grasp the stress of the male high school students and the correlation between the stress according to the oral health important cognitive and self-rated oral health status and number of brushing, emphasizing the need for the education of oral health important, providing the basic data in order to accomplish correctly until the enhance of oral health-related quality of the oral health correct behavior. From May to July 2013, a self administered survey was conducted by the selected by convenience sampling from subjects of two high school located in Chungcheongnam-do 1, 2 grade. The SPSS PASW Statistics 18.0 and Amos 5.0 program had been used for the statistical data analysis. The study results were as follow: 1) Among five areas of stress, the stress of school life was the highest as 2.11 points and the stress of home problem was the lowest as 1.51 points; 2) The significance analysis results between the five areas of stress according to the stress of latent variable and the oral health-related quality of life all showed the significant difference (p<0.001). 3) Oral health-related quality of life was higher as oral health important and self-rated oral health status positive. Furthermore oral health-related quality of life was higher as number of brushing increased; 4) Fit Measures test result of stress, academic level, and family economic level model all showed more than 0.9 in goodness of fit index (GFI), adjusted GFI, normed fit index and root mean square residual and root mean square error of approximation values is all estimated less than 0.1, so it showed good model. From this study, it can be concluded that there is the correlation between stress and oral health-related quality of life.

• Journal of Intelligence and Information Systems
• /
• v.24 no.2
• /
• pp.1-19
• /
• 2018

Since stock movements forecasting is an important issue both academically and practically, studies related to stock price prediction have been actively conducted. The stock price forecasting research is classified into structured data and unstructured data, and it is divided into technical analysis, fundamental analysis and media effect analysis in detail. In the big data era, research on stock price prediction combining big data is actively underway. Based on a large number of data, stock prediction research mainly focuses on machine learning techniques. Especially, research methods that combine the effects of media are attracting attention recently, among which researches that analyze online news and utilize online news to forecast stock prices are becoming main. Previous studies predicting stock prices through online news are mostly sentiment analysis of news, making different corpus for each company, and making a dictionary that predicts stock prices by recording responses according to the past stock price. Therefore, existing studies have examined the impact of online news on individual companies. For example, stock movements of Samsung Electronics are predicted with only online news of Samsung Electronics. In addition, a method of considering influences among highly relevant companies has also been studied recently. For example, stock movements of Samsung Electronics are predicted with news of Samsung Electronics and a highly related company like LG Electronics.These previous studies examine the effects of news of industrial sector with homogeneity on the individual company. In the previous studies, homogeneous industries are classified according to the Global Industrial Classification Standard. In other words, the existing studies were analyzed under the assumption that industries divided into Global Industrial Classification Standard have homogeneity. However, existing studies have limitations in that they do not take into account influential companies with high relevance or reflect the existence of heterogeneity within the same Global Industrial Classification Standard sectors. As a result of our examining the various sectors, it can be seen that there are sectors that show the industrial sectors are not a homogeneous group. To overcome these limitations of existing studies that do not reflect heterogeneity, our study suggests a methodology that reflects the heterogeneous effects of the industrial sector that affect the stock price by applying k-means clustering. Multiple Kernel Learning is mainly used to integrate data with various characteristics. Multiple Kernel Learning has several kernels, each of which receives and predicts different data. To incorporate effects of target firm and its relevant firms simultaneously, we used Multiple Kernel Learning. Each kernel was assigned to predict stock prices with variables of financial news of the industrial group divided by the target firm, K-means cluster analysis. In order to prove that the suggested methodology is appropriate, experiments were conducted through three years of online news and stock prices. The results of this study are as follows. (1) We confirmed that the information of the industrial sectors related to target company also contains meaningful information to predict stock movements of target company and confirmed that machine learning algorithm has better predictive power when considering the news of the relevant companies and target company's news together. (2) It is important to predict stock movements with varying number of clusters according to the level of homogeneity in the industrial sector. In other words, when stock prices are homogeneous in industrial sectors, it is important to use relational effect at the level of industry group without analyzing clusters or to use it in small number of clusters. When the stock price is heterogeneous in industry group, it is important to cluster them into groups. This study has a contribution that we testified firms classified as Global Industrial Classification Standard have heterogeneity and suggested it is necessary to define the relevance through machine learning and statistical analysis methodology rather than simply defining it in the Global Industrial Classification Standard. It has also contribution that we proved the efficiency of the prediction model reflecting heterogeneity.

• Korean Chemical Engineering Research
• /
• v.55 no.3
• /
• pp.322-331
• /
• 2017

District heating was first introduced in Korea in 1985. As the service life of the underground thermal piping network has increased for more than 30 years, the maintenance of the underground thermal pipe has become an important issue. A variety of complex technologies are required for periodic inspection and operation management for the maintenance of the aged thermal piping network. Especially, it is required to develop a model that can be used for decision making in order to derive optimal maintenance and replacement point from the economic viewpoint in the field. In this study, the analysis was carried out based on the repair history and accident data at the operation of the thermal pipe network of five districts in the Korea District Heating Corporation. A failure probability model was developed by introducing statistical techniques of qualitative analysis and binomial logistic regression analysis. As a result of qualitative analysis of maintenance history and accident data, the most important cause of pipeline damage was construction erosion, corrosion of pipe and bad material accounted for about 82%. In the statistical model analysis, by setting the separation point of the classification to 0.25, the accuracy of the thermal pipe breakage and non-breakage classification improved to 73.5%. In order to establish the failure probability model, the fitness of the model was verified through the Hosmer and Lemeshow test, the independent test of the independent variables, and the Chi-Square test of the model. According to the results of analysis of the risk of thermal pipe network damage, the highest probability of failure was analyzed as the thermal pipeline constructed by the F construction company in the reducer pipe of less than 250mm, which is more than 10 years on the Seoul area motorway in winter. The results of this study can be used to prioritize maintenance, preventive inspection, and replacement of thermal piping systems. In addition, it will be possible to reduce the frequency of thermal pipeline damage and to use it more aggressively to manage thermal piping network by establishing and coping with accident prevention plan in advance such as inspection and maintenance.

• Korean Journal of Social Welfare
• /
• v.54
• /
• pp.5-33
• /
• 2003

This study is about the re-validation evaluation of the family Relationship Scale (FRS), developed to measure the family relationship in the social work practice. This study aims at re-validating the FRS, developed and validated in by Yang in 2001 for more general utilization. The sample was married mates and females residing in Seoul. For Face Validity, the content analysis was performed, and the FRS was re-validated in the dimensions of Love & Caring, Acceptance, and Recognition, positive affection, empathy, and autonomy and flexibility for each area. Internal reliability was .93, and internal consistency among three dimensions was 93%. For Empirical Validity, the Construct validity, the Criterion validity, and the Discriminant validity were performed. Construct Validity was validated through factor analyses. Commonalities for the factor analysis was 54%, and the factor loading for each factor was over .45. The confirmative factor analysis also confirmed the fitness of the scale. For Predictive Validity of Criterion Validity, regression analysis showed that the family stress scores became lower as the scores of the family relationship became higher; the discriminant analysis revealed that the family stress turned low ill tile group of high scores of family relationship. The Correlation analysis for Concurrent Validity was performed and the results showed the positive and significant relationship with a couple communication level (r=54) and a parent-child communication level (r=64). Life satisfaction and mental health level also revealed significantly positive correlation to prove Convergent Validity. Physical health level revealed a weak relationship with family relationship providing the evidence of Discriminant Validity. Discriminance was also proved by the analysis of variance with demographics. Thus, Cross Validation was confirmed the validation of the FRS through the various analyses with the married population. This study result improved the validity generalization of the Scale and verify the generalized usage of this sociometric scale in the field of social work practice.