• Childhood Kidney Diseases
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• v.11 no.1
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• pp.74-82
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• 2007

Purpose : To analyze the clinical characteristics, spontaneous resolution rate and predictive factors of resolution in children with primary vesicoureteral reflux(VUR). Methods : Between October 1991 and July 2003, 149 children diagnosed with primary VUR at Chonbuk National University Hospital were reviewed retrospectively. All of the patients were maintained on low-dose antibiotic prophylaxis and underwent radionuclide cystograms at 1 year intervals over 3 years after the initial diagnosis of VUR by voiding cystourethrogram was made. Results : The median time to resolution of VUR was 24 months and the total 3 year-cumulative resolution rate of VUR was 61.7%. The following variables were associated with resolution of VUR according to univariate analysis-; age<1 year, male gender, mild grade of reflux, unilateral reflux, congenital hydronephrosis as clinical presentation at time of diagnosis of VUR, absence of focal defects in the renal scan at diagnosis, absence of recurrent UTI, renal scars and small kidney during follow-up. After adjustment by Cox regression model, five variables remained as independent predictors of VUR resolution; age<1 yew, relative risk 1.77(P<0.05), VUR grade I+II 2.98(P<0.05), absence of renal scars 2.23(P<0.05), and absence of small kidney 5.20(P<0.01) during follow-up. Conclusion : In this study, spontaneous resolution rate of VUR, even high grade reflux, is high in infants during medical management, and it was related to age, reflux grade at diagnosis, absence of renal scars and small kidney during follow-up. Therefore early surgical intervention should be avoided and reserved for the selected groups.

• Journal of Korean Public Health Nursing
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• v.10 no.1
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• pp.118-138
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• 1996

Because of accelerated urbanization public body visiting nursing project that started according as matter of health on urban class in the lower brackets of income was concentrated on Social interests has a unsatisfied points to propel project efficiently from the lack of rating materials. Therefore centering around written contents in documentary literature of citizen health by household in five years from starting year of project to now. visiting frequency by medical manpower was evaluated quantitatively and qualitatively in aspect of management hereupon. for the sake of giving a basic materials for public health project of this field. This research presents documentary literature of citizen health which become materials is that as one person's charged region of nurse in duty scale. district is Kang-Buck Gu. the object is resident in the lower brackets of income grounded livelihood protection law and who is admitted by the head of organ~chief of health care). and the number of material centering around the head of a household is 415 copy. The result of research is summarized. as follow. 1. Average visiting frequency examinated by medical manpower show difference according to valuables of supervision characteristics namely average visiting. Frequency of nurse has long term residence in case registration season is early and supervision season is the first year and is high incase a kind of house is unlicdnsed mountain town. Average visiting frequency with doctor is high incase supervision season is the first year and the medical insurance system is admitted by chief of health care. That shows that a man of discomfort behavior left alone are yet many in local society. The meaning of this result shows that the continuity of official relation about class in the lowest brackets of income of long term residence goes well between househole who is a user of visiting nursing service of the object according to midway income under management influences a given duty of nurse s and so causes quantitative decrease. 2. In case behavier and condition of health that nurse diagnoses are bad. as the type matter is a lack of health and the number of patient is large. the average visiting frequency of nurse is high. because average visiting frequency with doctor is high as the condition of health is bad and the number of patient is large. That is similar with that of nurse. CD Average visiting frequency of nurse s seen by matter of disease is very high only in apoplexy by 39.50 and is confined within limits from 7.63 to 11.36 in other disease. But average visiting frequency with doctor is double as many as that of nurse but defined in apoplexy hypertension and articulate. (1) Average visiting frequency of nurse by existence in inoculation of hepatitis is low by 6.73 in unidentified group and very high by 26.89 in group of non-inoculation and the case of the antigenic positive man of B type hepatitis or epileptic who can't be inoculated shows 13.00 and that even family nursing service is needed to them. That result shows that though one person nurse of local charge has a large scale of duty. as visting nursing service is given a class who has a large demand preferentially by respectively accurate nursing diagnosis. the number of diagnosis service is similar with it. 3. During five years. average visiting frequency of nurse is 10.84 and average visiting frequency with doctor is 76.50 seeing from the official scale of nurse. visiting by household is performed two more per year to the average. Seeing this by type of service. average visiting frequency of nurse is higher in indirectly nursing than in directly nursing and that suggests that at the time of visiting household nurse performs education of protection lively save patient but at the time of contrastedly visiting with doctor. directly nursing is more contents of service show no difference by man power and medication dressing by demand is 14.3 and 18.6 the aid of hardship term of doctor and nurse is high by 18.7 and 17.00 in the request of hospitalization when seeing by demands. 4. Action by turns exemplified 1994 is well in sequence of 2/4 turn. 3/4 turn. 1/4 turn. 4/4 turn. When seen by average visiting frequency of nurse but gradually is even. Without difference by turns. average visiting frequency of doctor is much higher in 1/4 turn than other turns. Type of service by turns is all even but directly nursing is inactive in 4/4 and indirectly nursing. Very increases in 4/4 and so. Nurse's quantity of duty is plentiful that shows that by evaluation of last turn and plan of project. Contents of service follows that medication and dressing is the highest by' 5.57 in 1/4turn. goes down gradually by turn. becomes 3.57 in 3/4 turn. and increases again by 4.83 in 4/4 turn. the rest service is higher in 2/4 turn than other turns. 5. Total visiting frequency of nurse is explained to total $37.5\%$ by six valuables of visiting frequency of doctor. nursing demand. demand of diagnosis. condition of behavior. year. Special terms and magnitude of influential power is the same as sequence of enumerated valuables. Namely. the higher the visiting frequency of doctor. the bigger nursing and demand of diagnosis is. the worse the condition of behavior is. the older the object is and the more the household of special terms is. the high total visiting frequency of nurse is.

• Journal of the Korea Society of Computer and Information
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• v.25 no.9
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• pp.37-44
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• 2020

AI technology has developed in the form of decision support technology in law, patent, finance and national defense and is applied to disease diagnosis and legal judgment. To search real-time information with Deep Learning, Big data Analysis and Deep Learning Algorithm are required. In this paper, we try to predict the entrance rate to high-ranking universities using a Deep Learning model, RNN(Recurrent Neural Network). First, we analyzed the current status of private academies in administrative districts and the number of students by age in administrative districts, and established a socially accepted hypothesis that students residing in areas with a high educational fever have a high rate of enrollment in high-ranking universities. This is to verify based on the data analyzed using the predicted hypothesis and the government's public data. The predictive model uses data from 2015 to 2017 to learn to predict the top enrollment rate, and the trained model predicts the top enrollment rate in 2018. A prediction experiment was performed using RNN, a Deep Learning model, for the high-ranking enrollment rate in the special education zone. In this paper, we define the correlation between the high-ranking enrollment rate by analyzing the household income and the participation rate of private education about the current status of private institutes in regions with high education fever and the effect on the number of students by age.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.5
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• pp.480-488
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• 2018

The development of information and communication technology has been carried out actively in the field of agriculture to generate valuable information from large amounts of data and apply big data technology to utilize it. Crops and their varieties are determined by the influence of the natural environment such as temperature, precipitation, and sunshine hours. This paper derives the climatic factors affecting the production of crops using the garlic growth process and daily meteorological variables. A prediction model was also developed for the production of garlic per unit area. A big data analysis technique considering the growth stage of garlic was used. In the exploratory data analysis process, various agricultural production data, such as the production volume, wholesale market load, and growth data were provided from the National Statistical Office, the Rural Development Administration, and Korea Rural Economic Institute. Various meteorological data, such as AWS, ASOS, and special status data, were collected and utilized from the Korea Meteorological Agency. The correlation analysis process was designed by comparing the prediction power of the models and fitness of models derived from the variable selection, candidate model derivation, model diagnosis, and scenario prediction. Numerous weather factor variables were selected as descriptive variables by factor analysis to reduce the dimensions. Using this method, it was possible to effectively control the multicollinearity and low degree of freedom that can occur in regression analysis and improve the fitness and predictive power of regression analysis.

• Nuclear Engineering and Technology
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• v.53 no.8
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• pp.2534-2546
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• 2021

Nuclear emergency preparedness and response is an essential part to ensure the safety of nuclear power plant (NPP). Key support technologies of nuclear emergency decision-making usually consist of accident diagnosis, source term estimation, accident consequence assessment, and protective action recommendation. Source term estimation is almost the most difficult part among them. For example, bad communication, incomplete information, as well as complicated accident scenario make it hard to determine the reactor status and estimate the source term timely in the Fukushima accident. Subsequently, it leads to the hard decision on how to take appropriate emergency response actions. Hence, this paper aims to develop a method for rapid source term estimation to support nuclear emergency decision making in pressurized water reactor NPP. The method aims to make our knowledge on NPP provide better support nuclear emergency. Firstly, this paper studies how to build a Bayesian network model for the NPP based on professional knowledge and engineering knowledge. This paper presents a method transforming the PRA model (event trees and fault trees) into a corresponding Bayesian network model. To solve the problem that some physical phenomena which are modeled as pivotal events in level 2 PRA, cannot find sensors associated directly with their occurrence, a weighted assignment approach based on expert assessment is proposed in this paper. Secondly, the monitoring data of NPP are provided to the Bayesian network model, the real-time status of pivotal events and initiating events can be determined based on the junction tree algorithm. Thirdly, since PRA knowledge can link the accident sequences to the possible release categories, the proposed method is capable to find the most likely release category for the candidate accidents scenarios, namely the source term. The probabilities of possible accident sequences and the source term are calculated. Finally, the prototype software is checked against several sets of accident scenario data which are generated by the simulator of AP1000-NPP, including large loss of coolant accident, loss of main feedwater, main steam line break, and steam generator tube rupture. The results show that the proposed method for rapid source term estimation under nuclear emergency decision making is promising.

• 재활복지
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• v.20 no.4
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• pp.135-156
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• 2016

The purpose of this study was to investigate item goodness-of-fit of Childhood Autism Rating Scale(CARS), Rasch rating scale model was applied to 15 items of the CARS in a sample of pervasive development disorder(n=238). An assumption to test Rasch Model, which is satisfaction of unidimensionality, is regarded through PCAR analysis, and jMetrik 4.03 program is used to test the goodness-of-fit of items. The results of this study were: First, 5-point rating scale was appropriate for the CARS rather than 7-point original rating scale. Second, the result of examining the CARS questions goodness-of-fit, there was a overfitting or misfitting items according to the classified groups. Only in particular Q11 item in diagnosis subject of integration population of autism has become inappropriate. Therefore, it is necessary to provide education for the CARS more systematically. Thirdly, the result of comparing the personal attributes score and difficulty of a CARS question, Q2, Q3, Q10, Q11 items are necessary to distinguish conceptually defined in more detail. Fourth, the results of investigating the difficulty of CARS question, it was found to exhibit a verbal communication is most serious problem for the population of autism.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.1
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• pp.184-192
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• 2022

Valve internal leakage is caused by damage to the internal parts of the valve, resulting in accidents and shutdowns of the piping system. This study investigated the possibility of a real-time leak detection method using the acoustic emission (AE) signal generated from the piping system during the internal leakage of a butterfly valve. Datasets of raw time-domain AE signals were collected and postprocessed for each operation mode of the valve in a systematic manner to develop a data-driven model for the detection and classification of internal leakage, by applying machine learning algorithms. The aim of this study was to determine whether it is possible to treat leak detection as a classification problem by applying two classification algorithms: support vector machine (SVM) and convolutional neural network (CNN). The results showed different performances for the algorithms and datasets used. The SVM-based binary classification models, based on feature extraction of data, achieved an overall accuracy of 83% to 90%, while in the case of a multiple classification model, the accuracy was reduced to 66%. By contrast, the CNN-based classification model achieved an accuracy of 99.85%, which is superior to those of any other models based on the SVM algorithm. The results revealed that the SVM classification model requires effective feature extraction of the AE signals to improve the accuracy of multi-class classification. Moreover, the CNN-based classification can be a promising approach to detect both leakage and valve opening as long as the performance of the processor does not degrade.

• The Korean Journal of Applied Statistics
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• v.37 no.2
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• pp.225-237
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• 2024

In the analysis of competing risks data, some of covariates may not be fully observed for some subjects. In such cases, excluding subjects with missing covariate values from the analysis may result in biased estimates and loss of efficiency. In this paper, we studied multiple imputation and the augmented inverse probability weighting method for regression parameter estimation in the cause-specific proportional hazards model with missing covariates. The performance of estimators obtained from multiple imputation and the augmented inverse probability weighting method is evaluated by simulation studies, which show that those methods perform well. Multiple imputation and the augmented inverse probability weighting method were applied to investigate significant risk factors for the risk of death from breast cancer and from other causes for breast cancer data with missing values for tumor size obtained from the Prostate, Lung, Colorectal, and Ovarian Cancer Screen Trial Study. Under the cause-specific proportional hazards model, the methods show that race, marital status, stage, grade, and tumor size are significant risk factors for breast cancer mortality, and stage has the greatest effect on increasing the risk of breast cancer death. Age at diagnosis and tumor size have significant effects on increasing the risk of other-cause death.

• Journal of Arbitration Studies
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• v.28 no.2
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• pp.3-43
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• 2018

The emergence of a multi-door courthouse is related with a couple of reasons as follows: First, a multi-door courthouse was originally initiated by the United States government that increasingly became impatient with the pace and cost of protracted litigation clogging the courts. Second, dockets of courts are overcrowded with legal suits, making it difficult for judges to handle those legal suits in time and causing delays in responding to citizens' complaints. Third, litigation is not suitable for the disputant that has an ongoing relationship with the other party. In this case, even if winning is achieved in the short run, it may not be all that was hoped for in the long run. Fourth, international organizations such as the World Bank, UNDP, and Asia Development Bank urge to provide an increased access to women, residents, and the poor in local communities. The generic model of a multi-door courthouse consists of three stages: The first stage includes a center offering intake services, along with an array of dispute resolution services under one roof. At the second stage, the screening unit at the center would diagnose citizen disputes, then refer the disputants to the appropriate door for handling the case. At the third stage, the multi-door courthouse provides diverse kinds of dispute resolution programs such as mediation, arbitration, mediation-arbitration (med-arb), litigation, and early neutral evaluation. This study suggests the extended model of multi-door courthouse comprised of five layers: intake process, diagnosis and door-selection process, neutral-selection process, implementation process of dispute resolution, and process of training and education. One of the major characteristics of extended multi-door courthouse model is the detailed specification of individual department corresponding to each process within a multi-door courthouse. The intake department takes care of the intake process. The screening department plays the role of screening disputes, diagnosing the nature of disputes, and determining a suitable door to handle disputes. The human resources department manages experts through the construction and management of the data base of mediators, arbitrators, and judges. The administration bureau manages the implementation of each process of dispute resolution. The education and training department builds long-term planning to procure neutrals and experts dealing with various kinds of disputes within a multi-door courthouse. For this purpose, it is necessary to establish networks among courts, law schools, and associations of scholars in order to facilitate the supply of manpower in ADR neutrals, as well as judges in the long run. This study also provides six case studies of multi-door courthouses across continents in order to grasp the worldwide picture and wide spread phenomena of multi-door courthouse. For this purpose, the United States and Latin American countries including Argentina and Brazil, Middle Eastern countries, and Southeast Asian countries (such as Malaysia and Myanmar), Australia, and Nigeria were chosen. It was found that three kinds of patterns are discernible during the evolution of a multi-door courthouse model. First, the federal courts of the United States, land and environment court in Australia, and Lagos multi-door courthouse in Nigeria may maintain the prototype of a multi-door courthouse model. Second, the judicial systems in Latin American countries tend to show heterogenous patterns in terms of the adaptation of a multi-door courthouse model to their own environments. Some court systems of Latin American countries including those of Argentina and Brazil resemble the generic model of a multi-door courthouse, while other countries show their distinctive pattern of judicial system and ADR systems. Third, it was found that legal pluralism is prevalent in Middle Eastern countries and Southeast Asian countries. For example, Middle Eastern countries such as Saudi Arabia have developed various kinds of dispute resolution methods, such as sulh (mediation), tahkim (arbitration), and med-arb for many centuries, since they have been situated at the state of tribe or clan instead of nation. Accordingly, they have no unified code within the territory. In case of Southeast Asian countries such as Myanmar and Malaysia, they have preserved a strong tradition of customary laws such as Dhammthat in Burma, and Shriah and the Islamic law in Malaysia for a long time. On the other hand, they incorporated a common law system into a secular judicial system in Myanmar and Malaysia during the colonial period. Finally, this article proposes a couple of factors to strengthen or weaken a multi-door courthouse model. The first factor to strengthen a multi-door courthouse model is the maintenance of flexibility and core value of alternative dispute resolution. We also find that fund raising is important to build and maintain the multi-door courthouse model, reflecting the fact that there has been a competition surrounding the allocation of funds within the judicial system.

• Journal of Chest Surgery
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• v.36 no.6
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• pp.379-383
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• 2003

Background: An accurate diagnosis of the severity of the rejection after a heart transplantation relies on endomyo-cardial biopsy, but because of its invasiveness and the need for repeated examination makes it is an inappropriate monitoring method. Therefore, we have tried to find a monitoring method that is continuous and less invasive. Material and Method: Heterotopic heart transplantation using Ono-Lindsey Method was done in 20 rats, and then $^{99m}$ Tc-Pyrophosphate (PYP) scan was done after a month, Uptake ratio of transplanted heart to vertebrae (H/V) was obtained to be compared with the biopsy result. Result: Rejection was defined when the H/V uptake ratio was higher than 0.09, and we compared the uptake ratio with the results of biopsy. The result was true positives was 3, true negatives 12, false negatives 2, andfalse positives 3. Therefore sensitivity was 60% and specificity was 80%, diagnostic value was 75%. Conclusion: $^{99m}$Tc-Pyrophosphate (PYP) scan was a useful method for the evaluation of the heart transplantation rejection and it will be helpful for monitoring rejection as an non-invasive and simple method.hod.