• Journal of Korean Academy of Nursing
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• v.13 no.3
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• pp.61-74
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• 1983

The proportion of people who contacted pulmonary T.B. in Korea has drastically decreased as a result of the incessant effort of the Korean government which adopted a policy of“drive out T.B.”as its foremost health policy. However, the proportion still remains relatively high com-pared with that of developed countries. This study attempts to find some means for guiding and educating college students who have T.B. in their health care by (1) first determining the effect if their self-concept and health beliefs on their behavior in regard to their disease and (2) then predicting the level of compliance of the new patients to the treatment suggested by the health specialist, before the commencement of the treatment. The subjects of this study consisted of 88 mald and female students at Y University who were diagnosed as minimal pulmonary T.B. patients and registered at the health clinic of Y University during the period between September 1, 1981 and March 31, 1953. Data were collected from them by means of questionnaire and interview. The instruments used for this study were (1) a part of Junghoon Choi's“Perceptual Orientation ,Scale”for measuring self-perception of patients and (2) Rosenberg's questionnaire for measuring patients' evaluation of self-esteem, and (3) an instrument for measuring patients' health beliefs which was developed by this researcher utilizing information available from references. The collected data were analyzed using descriptive statistics, chisquare test, Pearson correlation coefficient and t-test. The findings were as follows: 3. Test of hypotheses 1) Hypothesis 1: Patients with high self-concept will be high in health beliefs. For testing this hypothesis a calculation of Pearson correlation coefficient (r) between the patients' self-concept and their health beliefs was carried out. The result of this test was -. 0756 which was not significant at α=.05 and hence hypothesis 1 was not supported. 2) Hypothesis 2: Patients with a high self-concept will tend to be high in compliance with the suggested treatment. Again a Pearson correlaton coefficient was calculated between the two variaibles in the hypothesis. The calculated coefficient r was .1558 which was not significant at α=.05. Hence hypothesis 2 was rejected. 3) Hypothesis 3: Patients with high susceptibility will have a high compliance level. The correlation coefficient between the two variables was -.1975, which was significant at α=.05 but due to the negative sign hypothesis 3 could not be accepted. 4) Hypothesis 4: Patients who take their disease seriously will have a higher compliance level. The calculated correlation coefficient between the variables in this hypothesis was .1642 which was not significant at α=.05 and hence hypothesis 4 was rejected. 5) Hypothesis 5: Patients with a high sense of the benefit of treatment will have a high level of compliance. The computed correlation coefficient was .3129 which was significant at α=.05 and hence hypothesis 5 was acepted. 2. Findings from the correlation analysis were as follows: 1) Patients' susceptibility and their compliance to treatment was negatively correlated (r= -. 1975) which was significant at α= .05. This implies that as the patients' level of susceptibility increases their compliance level decreases. 2) Patients' susceptibility and their self-concept were negatively correlated (r= -. 1790) which was again singnificant at α=.05. The implication of this is that as the patients’self concept increases their susceptibility to disease decreases. 3) Patients' self-concept and their sense of benefit derieved from the treatment was positively correlated (r=.1970) which was significant at α=.05. That is, patients with a high self-concept perceived a great sense of benefit from the treatment. To summarize, patients who are low in susceptibility have a high level of compliance and self-concept.

• Child Health Nursing Research
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• v.9 no.2
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• pp.206-220
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• 2003

Purpose: this study was intended to search the relationship between perception of the infant temperament in mother of infant at the age of 1～12 months and maternal confidence and satisfaction in performing maternal role, and to submit a basic data to establish a nursing intervention program which is helpful for determination of infant development and performing maternal role promotion by identify variables associated with infant temperament. Method: The subjects of this study were 300 mothers of infant at the age of 1～12 months who visited well baby clinic in 4 hospitals in Busan city and Kyoung-Nam province. Final analysis was performed in 293 cases. Seven cases was excluded in this study because of its inappropriate data collection. The data was collected from 1st July to 15th August 2002. The questionaries which were fill-up by mother were collected. Infant temperament was measured by using the tool of 'what my baby is like'(WBL) which was developed by Priham et. al.(1994) and translated by Bang(1999). The scale of postpartum self evaluation which was developed by Lederman et al(1981) and translated by Lee(1992) was used for the confidence and satisfaction of maternal role. All statistical analyses were performed using SPSS-PC for window, version 10.0: frequency, percentage, minimum, maximum, mean, SD, t-test, ANOVA, Post-hoc test(Scheffe's test), Pearson Correlation Coefficients. Result: The mean score of maternal perception of the infant temperament was 6.17±1.04, and mother recognized her infant as positive. The mean score of confidence of maternal role was 2.89± .41 and this revealed in an average level. The mean score of satisfaction of maternal role was 3.29± .51 and this revealed in a higher level. There was a weak significant positive correlation between the score of maternal perception of infant temperament and confidence of maternal role(r=0.176, P= .003), but there was no significant correlation between satisfaction of maternal role(P> .05). It revealed the more maternal perception of the infant temperament as positive, the higher confidence of maternal role. There was a moderate significant positive correlation between confidence of maternal role and satisfaction of maternal role(r=0.410, P= .000). It revealed the more confidence of maternal role, the higher satisfaction of maternal role. The variables related with the score of maternal perception of infant temperament were the type of delivery (t=-2.600, P= .010), experience of learning baby care(t=2.382, P= .018), maternal perception on baby's health status(F=3.467, P= .033), maternal perception on her health status(F=3.467, P= .027), baby's age(F=3.080, P= .028). Conclusion: Our result showed the confidence of maternal role was increased as the maternal perception of infant temperament was positive, and conformed that the confidence of maternal role was also related with satisfaction of maternal role. Prenatal education, type of delivery, baby's age were also related with the maternal perception of infant temperament. So, nursing intervention program of developmental stage maybe necessary in order to help maternal perception of infant temperament as positive, and it will be increased the confidence of maternal role and satisfaction of performing maternal role which was considered as real indicate of achievement of maternal role.

• Journal of the Korean Society of School Health
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• v.9 no.1
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• pp.55-67
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• 1996

This research has incorporated a postal survey from the principals, nurse-charging teachers and nurse-teachers of the fiftyfive elementary, middle and high school in Yang-pyeong county area where its supplementary rate of nurse-teachers is less than adequate. It is to analyse the current status of the school health service in the area and to come out with a plan to improve the school health program through the participations of the health related experts of the local community. The survey was done in the two months of period of April to May of 1994. The result of the survey follows. The student population in the Yang-pyeong county area is 13,998 and the school employee population is 904 which counts for about 19.2% of the whole population of the area. However, the supplementary rate of nurse-teachers is only 10.8% (4 in 55 schools) which is very low in terms of relativity. School health committee only exist in 17% of the whole number of schools in the area and 50 of school health committee answered that their activity do not meet the adequate level. Only 54. 3% of the whole school numbers has included the school health finance in their financial plans and the amount set for the school health finance is about 500,000 wons (100,000-1,600,000 wons). 64.9% of the schools in the Yang-pyeong county area have the permanent nursing room established in the school. But, often than the equipment for a simple physical examinations, their supply of the health related equipments are less than adequate. Particitations of school doctor in the school health service is at only 67.6% which pretty much include only the physical examinations. Nurse-charging teachers consider their utmost important role is to teach health education but, they answered that they spent most of their times and efforts on physical examinations & immunizations. The average number of students visition to the nursing room is 2.5 persons and complains for basic discomfort as headache, concussion, stomachache and indigestion problems and usual pills used are the analgesics and digestives. Physical examination is done in the most schools every year but, 51.4% of nurse-charging teachers answered the physical examination does not really help. About the emergency treatment ability, 75.7% reports that both manpower & equipment are short. The school food services are present in only 8 schools (21.6%) but, 89.2% of nurse-charging teachers answer that there is a definite need of the food service. The survey says that the utmost important environmental health and safety factors are the traffic accidents followed by improper heat system, lighting, the stools and desks that do not consider the student physical status The overall evaluation of school health program reports that there are adequate physical examination, immunization, environmental hygiene, and management of safety but, on the other hand, health education, health councelling & management of nursing room are not managed properly. The principals of the survey pool report shortage of public agency support, lack of understanding of school health, shortage of nursing equipments and school health finance as the barrier factors of school health. The nurse-charging teachers report on the same questions as their less than qualitifying expertise, extraload of work upon the nursing affairs, shortage of nursing equipments & school health finance. The head masters & nurse-charging teachers answered that they are desperate for the meetings of nurse-charging teachers, construction of school health councelling system & training education in order to improve school health and if these are available, they will actively participate in them. After the careful analysis of the survey result, it is apparent that through the relations of the manpowers, establishment of community-oriented school health is definitely in need in rural area where there is low supplementary rate of nurse-teachers and poor school health environment.

• Clean Technology
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• v.19 no.3
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• pp.264-271
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• 2013

In this study, we optimized the removal condition of contaminants attached on the scrap surface to recycle the scrap generated from the Zr alloy tube manufacturing process back to the nuclear grade. The main contaminant is remnant of watersoluble cooling lubricant that is used in the pilgering manufacture during the tube production, and it is assumed to be compressed and carbonized on the surface of tube. Zirlo alloy tube of ${\phi}9.50mm$, which has high occurrence frequency of scrap, was selected as the object to be cleaned, and cleaning abilities of reagents were evaluated by measuring the characteristics of contaminants remained and by analyzing the surface of the tube after cleaning process. For evaluation of each cleaning agent, we selected two types of sodium hydroxide series and three types of potassium hydroxide series. Furthermore, to confirm dependence on tempe-rature and ultrasonic intensities, cleaning at the room temperature, $40^{\circ}C$, and $60^{\circ}C$ was conducted, and results showed that higher the cleaning temperature and higher the ultrasonic intensity, better the cleaning effect. As a result of the bare-eye inspection, while the use of sodium hydroxide provided satisfactory condition on the tube surface, the use of potassium hydroxide series provided satisfactory condition on the tube surface only when the ultrasonic intensity was over 120 W. In the cleaning effect analysis using the gravimetric method, cleaning efficiency of sodium hydroxide series was as high as 97.6% ($60^{\circ}C$, 120 W), but since the tube surface condition was poor after the use of potassium hydroxide, the gravimetric method was not appropriate. In the analytical result of surface contaminants on the tube surface, C, O, Ca, and Zr were detected, and mainly C and O dominated the proportion of contaminants. It was also found that the degree of cleaning on the tube affected the componential ratio of C and O; if the degree of cleaning is high, or if cleaning is well-conducted, the proportion of C is decreased, and the proportion of O is increased. Based on these results, optimal cleaning for application in the industry can be expected by categorizing cleaning process into three steps of Alkali cleaning, Rinsing, and Drying and by adjusting cleaning parameters in each step.

• Journal of Korea Water Resources Association
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• v.45 no.8
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• pp.795-804
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• 2012

Recently, changes in rainfall intensity and patterns have been causing increasing soil loss worldwide. As a result, the water ecosystem becomes worse and crops yield are reduced with soil loss and nutrient loss with it. Many studies have been proposed to estimate runoff and soil loss to predict or decrease non-point source pollution. Although the USLE has been used for many years in estimating soil losses, the USLE cannot reflect effects on soil loss of changes in rainfall intensity and patterns. The WEPP, physically based model, is capable of predicting soil loss and runoff using various rainfall intensity. In this study, the WEPP model was simulated for sediment yield, runoff and peak runoff using data of 5, 10, 30, 60 minute term rainfall, Huff's method and design rainfall. In case of rainfall interval of 5 minutes and 60 minutes, the sediment and runoff values decreased by 24% and 19%, respectively. The peak rate runoff values decreased by 16% when rainfall interval changed from 5 minutes to 60 minutes, indicating the peak rate runoff values are affected by rainfall intensity to some degrees. As a result of simulating using Huff's method, all values (sediment yield, runoff, peak runoff) were found to be the greatest at third quartile. According to the analysis under various design rainfall conditions (2, 3, 5, 10, 20, 30, 50, 100, 200, 300 years frequency), sediment yield, runoff, and peak runoff of 906.2%, 249.4% and 183.9% were estimated using 2 year to 300 year frequency rainfall data.

• Asia pacific journal of information systems
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• v.19 no.2
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• pp.157-178
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• 2009

Corporate credit rating is a very important factor in the market for corporate debt. Information concerning corporate operations is often disseminated to market participants through the changes in credit ratings that are published by professional rating agencies, such as Standard and Poor's (S&P) and Moody's Investor Service. Since these agencies generally require a large fee for the service, and the periodically provided ratings sometimes do not reflect the default risk of the company at the time, it may be advantageous for bond-market participants to be able to classify credit ratings before the agencies actually publish them. As a result, it is very important for companies (especially, financial companies) to develop a proper model of credit rating. From a technical perspective, the credit rating constitutes a typical, multiclass, classification problem because rating agencies generally have ten or more categories of ratings. For example, S&P's ratings range from AAA for the highest-quality bonds to D for the lowest-quality bonds. The professional rating agencies emphasize the importance of analysts' subjective judgments in the determination of credit ratings. However, in practice, a mathematical model that uses the financial variables of companies plays an important role in determining credit ratings, since it is convenient to apply and cost efficient. These financial variables include the ratios that represent a company's leverage status, liquidity status, and profitability status. Several statistical and artificial intelligence (AI) techniques have been applied as tools for predicting credit ratings. Among them, artificial neural networks are most prevalent in the area of finance because of their broad applicability to many business problems and their preeminent ability to adapt. However, artificial neural networks also have many defects, including the difficulty in determining the values of the control parameters and the number of processing elements in the layer as well as the risk of over-fitting. Of late, because of their robustness and high accuracy, support vector machines (SVMs) have become popular as a solution for problems with generating accurate prediction. An SVM's solution may be globally optimal because SVMs seek to minimize structural risk. On the other hand, artificial neural network models may tend to find locally optimal solutions because they seek to minimize empirical risk. In addition, no parameters need to be tuned in SVMs, barring the upper bound for non-separable cases in linear SVMs. Since SVMs were originally devised for binary classification, however they are not intrinsically geared for multiclass classifications as in credit ratings. Thus, researchers have tried to extend the original SVM to multiclass classification. Hitherto, a variety of techniques to extend standard SVMs to multiclass SVMs (MSVMs) has been proposed in the literature Only a few types of MSVM are, however, tested using prior studies that apply MSVMs to credit ratings studies. In this study, we examined six different techniques of MSVMs: (1) One-Against-One, (2) One-Against-AIL (3) DAGSVM, (4) ECOC, (5) Method of Weston and Watkins, and (6) Method of Crammer and Singer. In addition, we examined the prediction accuracy of some modified version of conventional MSVM techniques. To find the most appropriate technique of MSVMs for corporate bond rating, we applied all the techniques of MSVMs to a real-world case of credit rating in Korea. The best application is in corporate bond rating, which is the most frequently studied area of credit rating for specific debt issues or other financial obligations. For our study the research data were collected from National Information and Credit Evaluation, Inc., a major bond-rating company in Korea. The data set is comprised of the bond-ratings for the year 2002 and various financial variables for 1,295 companies from the manufacturing industry in Korea. We compared the results of these techniques with one another, and with those of traditional methods for credit ratings, such as multiple discriminant analysis (MDA), multinomial logistic regression (MLOGIT), and artificial neural networks (ANNs). As a result, we found that DAGSVM with an ordered list was the best approach for the prediction of bond rating. In addition, we found that the modified version of ECOC approach can yield higher prediction accuracy for the cases showing clear patterns.

• Asia pacific journal of information systems
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• v.19 no.4
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• pp.77-100
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• 2009

Information Systems (IS) is an essential tool for any organizations. The last decade has seen an increasing body of knowledge on IS usage. Yet, IS often fails because of its misuse or non-use. In general, decisions regarding the selection of a system, which involve the evaluation of many IS vendors and an enormous initial investment, are made not through the consensus of employees but through the top-down decision making by top managers. In situations where the selected system does not satisfy the needs of the employees, the forced use of the selected IS will only result in their resistance to it. Many organizations have been either integrating dispersed legacy systems such as archipelago or adopting a new ERP (Enterprise Resource Planning) system to enhance employee efficiency. This study examines user resistance prior to the adoption of the selected IS or ERP system. As such, this study identifies the importance of managing organizational resistance that may appear in the pre-adoption context of an integrated IS or ERP system, explores key factors influencing user resistance, and investigates how prior experience with other integrated IS or ERP systems may change the relationship between the affecting factors and user resistance. This study focuses on organizational members' resistance and the affecting factors in the pre-adoption context of an integrated IS or ERP system rather than in the context of an ERP adoption itself or ERP post-adoption. Based on prior literature, this study proposes a research model that considers six key variables, including perceived benefit, system complexity, fitness with existing tasks, attitude toward change, the psychological reactance trait, and perceived IT competence. They are considered as independent variables affecting user resistance toward an integrated IS or ERP system. This study also introduces the concept of prior experience (i.e., whether a user has prior experience with an integrated IS or ERP system) as a moderating variable to examine the impact of perceived benefit and attitude toward change in user resistance. As such, we propose eight hypotheses with respect to the model. For the empirical validation of the hypotheses, we developed relevant instruments for each research variable based on prior literature and surveyed 95 professional researchers and the administrative staff of the Korea Photonics Technology Institute (KOPTI). We examined the organizational characteristics of KOPTI, the reasons behind their adoption of an ERP system, process changes caused by the introduction of the system, and employees' resistance/attitude toward the system at the time of the introduction. The results of the multiple regression analysis suggest that, among the six variables, perceived benefit, complexity, attitude toward change, and the psychological reactance trait significantly influence user resistance. These results further suggest that top management should manage the psychological states of their employees in order to minimize their resistance to the forced IS, even in the new system pre-adoption context. In addition, the moderating variable-prior experience was found to change the strength of the relationship between attitude toward change and system resistance. That is, the effect of attitude toward change in user resistance was significantly stronger in those with prior experience than those with no prior experience. This result implies that those with prior experience should be identified and provided with some type of attitude training or change management programs to minimize their resistance to the adoption of a system. This study contributes to the IS field by providing practical implications for IS practitioners. This study identifies system resistance stimuli of users, focusing on the pre-adoption context in a forced ERP system environment. We have empirically validated the proposed research model by examining several significant factors affecting user resistance against the adoption of an ERP system. In particular, we find a clear and significant role of the moderating variable, prior ERP usage experience, in the relationship between the affecting factors and user resistance. The results of the study suggest the importance of appropriately managing the factors that affect user resistance in organizations that plan to introduce a new ERP system or integrate legacy systems. Moreover, this study offers to practitioners several specific strategies (in particular, the categorization of users by their prior usage experience) for alleviating the resistant behaviors of users in the process of the ERP adoption before a system becomes available to them. Despite the valuable contributions of this study, there are also some limitations which will be discussed in this paper to make the study more complete and consistent.

• Progress in Medical Physics
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• v.23 no.2
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• pp.81-90
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• 2012

The effect of setup uncertainties on CTV dose and the correlation between setup uncertainties and setup margin were evaluated by Monte Carlo based numerical simulation. Patient specific information of IMRT treatment plan for rectal cancer designed on the VARIAN Eclipse planning system was utilized for the Monte Carlo simulation program including the planned dose distribution and tumor volume information of a rectal cancer patient. The simulation program was developed for the purpose of the study on Linux environment using open source packages, GNU C++ and ROOT data analysis framework. All misalignments of patient setup were assumed to follow the central limit theorem. Thus systematic and random errors were generated according to the gaussian statistics with a given standard deviation as simulation input parameter. After the setup error simulations, the change of dose in CTV volume was analyzed with the simulation result. In order to verify the conventional margin recipe, the correlation between setup error and setup margin was compared with the margin formula developed on three dimensional conformal radiation therapy. The simulation was performed total 2,000 times for each simulation input of systematic and random errors independently. The size of standard deviation for generating patient setup errors was changed from 1 mm to 10 mm with 1 mm step. In case for the systematic error the minimum dose on CTV $D_{min}^{stat{\cdot}}$ was decreased from 100.4 to 72.50% and the mean dose $\bar{D}_{syst{\cdot}}$ was decreased from 100.45% to 97.88%. However the standard deviation of dose distribution in CTV volume was increased from 0.02% to 3.33%. The effect of random error gave the same result of a reduction of mean and minimum dose to CTV volume. It was found that the minimum dose on CTV volume $D_{min}^{rand{\cdot}}$ was reduced from 100.45% to 94.80% and the mean dose to CTV $\bar{D}_{rand{\cdot}}$ was decreased from 100.46% to 97.87%. Like systematic error, the standard deviation of CTV dose ${\Delta}D_{rand}$ was increased from 0.01% to 0.63%. After calculating a size of margin for each systematic and random error the "population ratio" was introduced and applied to verify margin recipe. It was found that the conventional margin formula satisfy margin object on IMRT treatment for rectal cancer. It is considered that the developed Monte-carlo based simulation program might be useful to study for patient setup error and dose coverage in CTV volume due to variations of margin size and setup error.

• Korean Journal of Remote Sensing
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• v.35 no.6_1
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• pp.883-893
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• 2019

In this study, crop coefficients were calculated in two different methods and the results were evaluated. In the first method, appropriateness of GLDAS-based evapotranspiration was evaluated by comparing it with observed data of Cheongmi-cheon (CMC) Flux tower. Then, crop coefficient was calculated by dividing actual evapotranspiration with potential evapotranspiration that derived from GLDAS. In the second method, crop coefficient was determined by using MLR (Multiple Linear Regression) analysis with vegetation index (NDVI, EVI, LAI and SAVI) derived from MODIS and in-situ soil moisture data observed in CMC, In comparison of two crop coefficients over the entire period, for each crop coefficient GLDAS K_c and SM&VI K_c, shows the mean value of 0.412 and 0.378, the bias of 0.031 and -0.004, the RMSE of 0.092 and 0.069, and the Index of Agree (IOA) of 0.944 and 0.958. Overall, both methods showed similar patterns with observed evapotranspiration, but the SM&VI-based method showed better results. One step further, the statistical evaluation of GLDAS K_c and SM&VI K_c in specific period was performed according to the growth phase of the crop. The result shows that GLDAS K_c was better in the early and mid-phase of the crop growth, and SM&VI K_c was better in the latter phase. This result seems to be because of reduced accuracy of MODIS sensors due to yellow dust in spring and rain clouds in summer. If the observational accuracy of the MODIS sensor is improved in subsequent study, the accuracy of the SM&VI-based method will also be improved and this method will be applicable in determining the crop coefficient of unmeasured basin or predicting the crop coefficient of a certain area.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.3
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• pp.82-98
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• 2019

The importance of spatial information is rapidly rising. In particular, 3D spatial information construction and modeling for Real World Objects, such as smart cities and digital twins, has become an important core technology. The constructed 3D spatial information is used in various fields such as land management, landscape analysis, environment and welfare service. Three-dimensional modeling with image has the hig visibility and reality of objects by generating texturing. However, some texturing might have occlusion area inevitably generated due to physical deposits such as roadside trees, adjacent objects, vehicles, banners, etc. at the time of acquiring image Such occlusion area is a major cause of the deterioration of reality and accuracy of the constructed 3D modeling. Various studies have been conducted to solve the occlusion area. Recently the researches of deep learning algorithm have been conducted for detecting and resolving the occlusion area. For deep learning algorithm, sufficient training data is required, and the collected training data quality directly affects the performance and the result of the deep learning. Therefore, this study analyzed the ability of detecting the occlusion area of the image using various image quality to verify the performance and the result of deep learning according to the quality of the learning data. An image containing an object that causes occlusion is generated for each artificial and quantified image quality and applied to the implemented deep learning algorithm. The study found that the image quality for adjusting brightness was lower at 0.56 detection ratio for brighter images and that the image quality for pixel size and artificial noise control decreased rapidly from images adjusted from the main image to the middle level. In the F-measure performance evaluation method, the change in noise-controlled image resolution was the highest at 0.53 points. The ability to detect occlusion zones by image quality will be used as a valuable criterion for actual application of deep learning in the future. In the acquiring image, it is expected to contribute a lot to the practical application of deep learning by providing a certain level of image acquisition.