• The Korean Journal of Nuclear Medicine
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• v.38 no.6
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• pp.486-491
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• 2004

Purpose: factor analysis and independent component analysis (ICA) has been used for handling dynamic image sequences. Theoretical advantages of a newly suggested ICA method, ensemble ICA, leaded us to consider applying this method to the analysis of dynamic myocardial $H_2^{15}O$ PET data. In this study, we quantified patients' blood flow using the ensemble ICA method. Materials and Methods: Twenty subjects underwent $H_2^{15}O$ PET scans using ECAT EXACT 47 scanner and myocardial perfusion SPECT using Vertex scanner. After transmission scanning, dynamic emission scans were initiated simultaneously with the injection of $555{\sim}740$ MBq $H_2^{15}O$. Hidden independent components can be extracted from the observed mixed data (PET image) by means of ICA algorithms. Ensemble learning is a variational Bayesian method that provides an analytical approximation to the parameter posterior using a tractable distribution. Variational approximation forms a lower bound on the ensemble likelihood and the maximization of the lower bound is achieved through minimizing the Kullback-Leibler divergence between the true posterior and the variational posterior. In this study, posterior pdf was approximated by a rectified Gaussian distribution to incorporate non-negativity constraint, which is suitable to dynamic images in nuclear medicine. Blood flow was measured in 9 regions - apex, four areas in mid wall, and four areas in base wall. Myocardial perfusion SPECT score and angiography results were compared with the regional blood flow. Results: Major cardiac components were separated successfully by the ensemble ICA method and blood flow could be estimated in 15 among 20 patients. Mean myocardial blood flow was $1.2{\pm}0.40$ ml/min/g in rest, $1.85{\pm}1.12$ ml/min/g in stress state. Blood flow values obtained by an operator in two different occasion were highly correlated (r=0.99). In myocardium component image, the image contrast between left ventricle and myocardium was 1:2.7 in average. Perfusion reserve was significantly different between the regions with and without stenosis detected by the coronary angiography (P<0.01). In 66 segment with stenosis confirmed by angiography, the segments with reversible perfusion decrease in perfusion SPECT showed lower perfusion reserve values in $H_2^{15}O$ PET. Conclusions: Myocardial blood flow could be estimated using an ICA method with ensemble learning. We suggest that the ensemble ICA incorporating non-negative constraint is a feasible method to handle dynamic image sequence obtained by the nuclear medicine techniques.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.109-125
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• 2020

The Ministry of National Defense is pushing for the Defense Acquisition Program to build strong defense capabilities, and it spends more than 10 trillion won annually on defense improvement. As the Defense Acquisition Program is directly related to the security of the nation as well as the lives and property of the people, it must be carried out very transparently and efficiently by experts. However, the excessive diversification of laws and regulations related to the Defense Acquisition Program has made it challenging for many working-level officials to carry out the Defense Acquisition Program smoothly. It is even known that many people realize that there are related regulations that they were unaware of until they push ahead with their work. In addition, the statutory statements related to the Defense Acquisition Program have the tendency to cause serious issues even if only a single expression is wrong within the sentence. Despite this, efforts to establish a sentence comparison system to correct this issue in real time have been minimal. Therefore, this paper tries to propose a "Comparison System between the Statement of Military Reports and Related Laws" implementation plan that uses the Siamese Network-based artificial neural network, a model in the field of natural language processing (NLP), to observe the similarity between sentences that are likely to appear in the Defense Acquisition Program related documents and those from related statutory provisions to determine and classify the risk of illegality and to make users aware of the consequences. Various artificial neural network models (Bi-LSTM, Self-Attention, D_Bi-LSTM) were studied using 3,442 pairs of "Original Sentence"(described in actual statutes) and "Edited Sentence"(edited sentences derived from "Original Sentence"). Among many Defense Acquisition Program related statutes, DEFENSE ACQUISITION PROGRAM ACT, ENFORCEMENT RULE OF THE DEFENSE ACQUISITION PROGRAM ACT, and ENFORCEMENT DECREE OF THE DEFENSE ACQUISITION PROGRAM ACT were selected. Furthermore, "Original Sentence" has the 83 provisions that actually appear in the Act. "Original Sentence" has the main 83 clauses most accessible to working-level officials in their work. "Edited Sentence" is comprised of 30 to 50 similar sentences that are likely to appear modified in the county report for each clause("Original Sentence"). During the creation of the edited sentences, the original sentences were modified using 12 certain rules, and these sentences were produced in proportion to the number of such rules, as it was the case for the original sentences. After conducting 1 : 1 sentence similarity performance evaluation experiments, it was possible to classify each "Edited Sentence" as legal or illegal with considerable accuracy. In addition, the "Edited Sentence" dataset used to train the neural network models contains a variety of actual statutory statements("Original Sentence"), which are characterized by the 12 rules. On the other hand, the models are not able to effectively classify other sentences, which appear in actual military reports, when only the "Original Sentence" and "Edited Sentence" dataset have been fed to them. The dataset is not ample enough for the model to recognize other incoming new sentences. Hence, the performance of the model was reassessed by writing an additional 120 new sentences that have better resemblance to those in the actual military report and still have association with the original sentences. Thereafter, we were able to check that the models' performances surpassed a certain level even when they were trained merely with "Original Sentence" and "Edited Sentence" data. If sufficient model learning is achieved through the improvement and expansion of the full set of learning data with the addition of the actual report appearance sentences, the models will be able to better classify other sentences coming from military reports as legal or illegal. Based on the experimental results, this study confirms the possibility and value of building "Real-Time Automated Comparison System Between Military Documents and Related Laws". The research conducted in this experiment can verify which specific clause, of several that appear in related law clause is most similar to the sentence that appears in the Defense Acquisition Program-related military reports. This helps determine whether the contents in the military report sentences are at the risk of illegality when they are compared with those in the law clauses.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.111-126
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• 2020

Most industries have recently become aware of the importance of customer lifetime value as they are exposed to a competitive environment. As a result, preventing customers from churn is becoming a more important business issue than securing new customers. This is because maintaining churn customers is far more economical than securing new customers, and in fact, the acquisition cost of new customers is known to be five to six times higher than the maintenance cost of churn customers. Also, Companies that effectively prevent customer churn and improve customer retention rates are known to have a positive effect on not only increasing the company's profitability but also improving its brand image by improving customer satisfaction. Predicting customer churn, which had been conducted as a sub-research area for CRM, has recently become more important as a big data-based performance marketing theme due to the development of business machine learning technology. Until now, research on customer churn prediction has been carried out actively in such sectors as the mobile telecommunication industry, the financial industry, the distribution industry, and the game industry, which are highly competitive and urgent to manage churn. In addition, These churn prediction studies were focused on improving the performance of the churn prediction model itself, such as simply comparing the performance of various models, exploring features that are effective in forecasting departures, or developing new ensemble techniques, and were limited in terms of practical utilization because most studies considered the entire customer group as a group and developed a predictive model. As such, the main purpose of the existing related research was to improve the performance of the predictive model itself, and there was a relatively lack of research to improve the overall customer churn prediction process. In fact, customers in the business have different behavior characteristics due to heterogeneous transaction patterns, and the resulting churn rate is different, so it is unreasonable to assume the entire customer as a single customer group. Therefore, it is desirable to segment customers according to customer classification criteria, such as loyalty, and to operate an appropriate churn prediction model individually, in order to carry out effective customer churn predictions in heterogeneous industries. Of course, in some studies, there are studies in which customers are subdivided using clustering techniques and applied a churn prediction model for individual customer groups. Although this process of predicting churn can produce better predictions than a single predict model for the entire customer population, there is still room for improvement in that clustering is a mechanical, exploratory grouping technique that calculates distances based on inputs and does not reflect the strategic intent of an entity such as loyalties. This study proposes a segment-based customer departure prediction process (CCP/2DL: Customer Churn Prediction based on Two-Dimensional Loyalty segmentation) based on two-dimensional customer loyalty, assuming that successful customer churn management can be better done through improvements in the overall process than through the performance of the model itself. CCP/2DL is a series of churn prediction processes that segment two-way, quantitative and qualitative loyalty-based customer, conduct secondary grouping of customer segments according to churn patterns, and then independently apply heterogeneous churn prediction models for each churn pattern group. Performance comparisons were performed with the most commonly applied the General churn prediction process and the Clustering-based churn prediction process to assess the relative excellence of the proposed churn prediction process. The General churn prediction process used in this study refers to the process of predicting a single group of customers simply intended to be predicted as a machine learning model, using the most commonly used churn predicting method. And the Clustering-based churn prediction process is a method of first using clustering techniques to segment customers and implement a churn prediction model for each individual group. In cooperation with a global NGO, the proposed CCP/2DL performance showed better performance than other methodologies for predicting churn. This churn prediction process is not only effective in predicting churn, but can also be a strategic basis for obtaining a variety of customer observations and carrying out other related performance marketing activities.

• The Korean Nurse
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• v.34 no.3
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• pp.85-98
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• 1995

The purpose of this study is to provide basic data regarding effective learning opportunities in childbirth education classes. Also analysis of the data indicates the optimum conditions for the welfare and improvements in the promotion of health in childbearing mothers. The results of this study are as follows; 1) The average age of the subjects in this study was 30.6 years and the total number of subjects was 58 pregnant women. The average number of children was one and 84.5% of the subjects were unemployed even though 63.8% of them held over bachelor's degrees. It was found that 22.4% of the subjects were living in an extended family. Also 61.5% of them were living with parents-in-law. The number of pregnancies were calssified as one, two, or three to nine times with the percentages of 58.7%, 22.4% and 18.9%, respectively. Further, 72.4% of the subjects had no abortion experience and 15.5% had one aborion experience. While 89.7% of the subjects planned to feed their babies with breastmilk, mixed feeding were used by only 22.4% of the sample. These data were collected at about 6 months after delivery. Thus one can see that a low rate of breastfeeding was common. 2) The length of one period of childbirth education is four weeks. It was found that 36.2% of the subjects participated in childbirth education only once, where as 13.8% participated four times and 19% of the subjects participated in this class more than four times. pregnant at least once. Further, 75.9% of the participants were participated in this education through their own will. Their motivation for participation developed through information, advertisement and posters which contained information on childbirth education. Those with unplanned pregnancies 92.9% participated after a suggestion by the nurses. The number of participants in terms of percentage according to the childbirth education contents can be classified as following. The most active participation was shown in preparation of delivery(77.6%), postpartrm management(56.9%) fetal development(37.6%) and physiology of pregnancy(17.2%). It was found that 75.9% of the subjects were willing to participate again if they were given a chance. The reason can be summarized as following: The content of the education is very helpful(47.7%). Scientific knowledge can be obtained through this program(20.5%). Participation helps in achieving psychological stability(9.1%). Participation enables one to establish a friendly relationship with other participants(6.8%) of the sample. 24.1% of the participants did not want to participate again. The reasons can be as following: They do not want another baby(42.9%). The first paricipation in childbirth education gave enough knowledge about childbirth(21.4%). Another reason for not want to participate again was because they had a cesarean birth(14.3%). Only 7.1% of them responded with a negative view. A response that they do not need childbirth education after their operation can be traced back to the general belief that childbirth education is the place where one prepares for natural birth through the Lamaze breathing technique. Of the subjects, 91.4% suggested that this program could be recommended to other childbearing mothers, because this program gave educational content along with psychological stability for childbearing women. Of the subjects 41.4% did not see any efforts towards the welfare of the baby, where as 88.2% did. Among the subjects 58.6% made some effort to eliminate the discomfort of labor by breathing and imagination and breathing and walking. Further 41.7% of the 24 subjects did not do anything toward the welfare of the baby, because they did have a cesarean section so that they didn't have a chance even though they had been educated about childbirth. Also 33.3% of the subjects did not do anything toward the welfare of the baby, because they lacked a willingness. After leaving the hospital, only 75.9% of the subjects did some exercises. The subjects who tried participate this program with their husband accounted for 20.7% of the sample. Interviewing with the subjects solved some of the uneasiness and. fear of delivery, increased self-confidence in parenting and active coping in the delivery process.

• 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.

• The Korean Journal of Nuclear Medicine
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• v.37 no.2
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• pp.73-82
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• 2003

Objectives: A new software (Cardiac SPECT Analyzer: CSA) was developed for quantification of volumes and election fraction on gated myocardial SPECT. Volumes and ejection fraction by CSA were validated by comparing with those quantified by Quantitative Gated SPECT (QGS) software. Materials and Methods: Gated myocardial SPECT was peformed in 40 patients with ejection fraction from 15% to 85%. In 26 patients, gated myocardial SPECT was acquired again with the patients in situ. A cylinder model was used to eliminate noise semi-automatically and profile data was extracted using Gaussian fitting after smoothing. The boundary points of endo- and epicardium were found using an iterative learning algorithm. Enddiastolic (EDV) and endsystolic volumes (ESV) and election fraction (EF) were calculated. These values were compared with those calculated by QGS and the same gated SPECT data was repeatedly quantified by CSA and variation of the values on sequential measurements of the same patients on the repeated acquisition. Results: From the 40 patient data, EF, EDV and ESV by CSA were correlated with those by QGS with the correlation coefficients of 0.97, 0.92, 0.96. Two standard deviation (SD) of EF on Bland Altman plot was 10.1%. Repeated measurements of EF, EDV, and ESV by CSA were correlated with each other with the coefficients of 0.96, 0.99, and 0.99 for EF, EDV and ESV respectively. On repeated acquisition, reproducibility was also excellent with correlation coefficients of 0.89, 0.97, 0.98, and coefficient of variation of 8.2%, 5.4mL, 8.5mL and 2SD of 10.6%, 21.2mL, and 16.4mL on Bland Altman plot for EF, EDV and ESV. Conclusion: We developed the software of CSA for quantification of volumes and ejection fraction on gated myocardial SPECT. Volumes and ejection fraction quantified using this software was found valid for its correctness and precision.

• The Journal of Korean Academy of Sensory Integration
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• v.17 no.3
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• pp.26-45
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• 2019

Objective : The purpose of this study is to develop educational goals, training content, and training methods for the intervention course of the Korean Academy of Sensory Integration (KASI) and to conduct competency-based intervention courses based on the competency model for sensory integration intervention. Methods : This study was conducted on work therapists who participated in the 2019 intervention course of KASI. In the first phase, educational needs were analyzed to set goals for the interventional course. In the second phase, a meeting of researchers drafted the intervention course education program and the methods of education, and the intervention course was conducted. In the third phase, the changes in educational satisfaction and performance level pre- and post-intervention course for each competency index were investigated. Results : The educational goals of "learning and applying the clinical reasoning process of sensory integration intervention" and "intervention by applying the principle of sensory integration intervention" were set after reflecting on the results of the analysis of the educational requirements. The length of the competency-based intervention course was 42 hours. The average education satisfaction level of participants in the arbitration process was 4.48±0.73, and the average education satisfaction level of the supervisor was 3.92±0.71. In both groups, the most satisfying curriculums were the data-driven decision-making process and the intervention goal-setting lecture. But the satisfaction level of was the lowest. Before and after the intervention course, there were significant changes in the performance of the two behavioral indicators of the analytic skills in the expertise competency cluster of the competency model. Conclusion : This study is meaningful in that it conducted a survey of educational needs, the development and implementation of an educational curriculum, and an education satisfaction survey through systematic courses necessary for education development.

• Journal of Korean Home Economics Education Association
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• v.29 no.3
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• pp.15-32
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• 2017

This study investigated the effectiveness of home economics class on self-esteem and stress of middle school students. Data were collected from self-reported inventory of the middle school students in Y city of Gyeonggi province and 165 data copies were used for analyses. Data were analyzed for frequency, percentage, mean, standard deviation, Cronbach's ${\alpha}$, t-test, corelation and dependent t-test using SPSS/PC 18.0 program. The results were as follows. First, the average of positive self-esteem was 2.74 and that of negative self-esteem was 1.90 on a 4 Likert scale. The range of stress level was 1.88~2.48 on a 5 Likert scale. Life satisfaction was 3.90 and helpfulness of home economics class was 3.89 on a 5 point Likert scale, which means moderately high. Second, examining differences in variables according to gender, there were statistically significant differences in stress regarding family for both pre- and post-tests. Third, helpfulness of home economics class had positive correlation with positive self-esteem and life satisfaction and had negative correlation with negative self-esteem and stress, which means that home economics class enhance life satisfaction and positive self-esteem and lessen negative self-esteem and stress of middle students. Fourth, as a result of comparison of pre and post-tests, positive self-esteem, life satisfaction, and helpfulness of home economics class increased statistically after home economics classes, while stress regarding school life decreased statistically. Even though students' growth and changes resulting from learning other subjects were not controlled, it was meaningful that effectiveness of home economics class were examined and helpful information for enhancing perception of home economics education were provided.

• Journal of agricultural medicine and community health
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• v.43 no.4
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• pp.234-249
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• 2018

This study was performed to identify the impact of awareness and educational experiences on cardiopulmonary resuscitation in the ability to execute of cardiopulmonary resuscitation among Korean adults. This study used original data of 2014 Community Health Data Survey. 228,712 participants in this survey were resident in South Korea who is aged 19 or older on July 2014. Participants in this survey were sampled an average of 900 residents(target error ${\pm}3percent$) per community health center of Korea. Data were analyzed by using R 3.1.3 employing chi-squared test, fisher's exact analysis, and logistic regression analysis. Ability to execute CPR was significantly higher in males(3.34 time), higher the education level (1.61 times), the white color occupation (1.14 times), the higher the income level (1.07 times), the higher the education level (0.91 times), non-hypertensive patients (1.12 times), non-diabetic patients (1.16 times), non-dyslipidemic patients (0.86 times), non-stroke patients (0.30 times), CPR education experience group (3.25 times), CPR experience group with manikin-based training (4.30 times), higher subjective health status (1.08 times, 1.16 times) respectively. This study identified that awareness, educational experience, and mannequin-based learning experience of CPR impacted on the ability to execute CPR. Responding to education-related factors could contribute to reducing the rate of out-of-hospital acute cardiac arrest by improving the ability to execute CPR of the general public.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.3
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• pp.149-155
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• 2021

Early warning systems for weather risk management in the agricultural sector have been developed to predict potential wind damage to crops. These systems take into account the daily maximum wind speed to determine the critical wind speed that causes fruit drops and provide the weather risk information to farmers. In an effort to increase the accuracy of wind risk predictions, an artificial neural network for binary classification was implemented. In the present study, the daily wind speed and other weather data, which were measured at weather stations at sites of interest in Jeollabuk-do and Jeollanam-do as well as Gyeongsangbuk- do and part of Gyeongsangnam- do provinces in 2019, were used for training the neural network. These weather stations include 210 synoptic and automated weather stations operated by the Korean Meteorological Administration (KMA). The wind speed data collected at the same locations between January 1 and December 12, 2020 were used to validate the neural network model. The data collected from December 13, 2020 to February 18, 2021 were used to evaluate the wind risk prediction performance before and after the use of the artificial neural network. The critical wind speed of damage risk was determined to be 11 m/s, which is the wind speed reported to cause fruit drops and damages. Furthermore, the maximum wind speeds were expressed using Weibull distribution probability density function for warning of wind damage. It was found that the accuracy of wind damage risk prediction was improved from 65.36% to 93.62% after re-classification using the artificial neural network. Nevertheless, the error rate also increased from 13.46% to 37.64%, as well. It is likely that the machine learning approach used in the present study would benefit case studies where no prediction by risk warning systems becomes a relatively serious issue.