• Communications of Mathematical Education
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• v.24 no.3
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• pp.563-585
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• 2010

The major goals of this study are to find the factors that enhance self-directed math learning in college math classes and to provide the students with the opportunities to check and develop their self-directed math learning attitude. For these research goals, we prepared the questionnaires that asked about their learning motivations, basic learning ability, self-discipline strategies, and self-directed learning strategies. Another purpose of the questionnaires was to give them the chances to check and improve their attitude toward those learning strategies, motivation and ability. From the research results, we find that the important factors for self-directed learning are internal & external motivations, concentration ability, and the goal-setting and plan-making abilities. In addition, concentration ability, good habit, stress-control, recognition of math value, and self-directing ability are found to be necessary for the desirable learning environment. On the other hand, we find that the ability to perform note-taking, class preparation and review, time-control, and test-control is required for the selection and practice of self-fitting learning strategies. Finally, we provided our own self-directed math learning model. Our model, containing the necessary factors for self-directed math learning, is the revised and modified one of Knowles(1975)'s 5 stage self-directed learning model that comprises diagnosis of learning desire, setting learning goals, grasping human&material resources, selection and practice of proper learning strategies, and evaluation of learning results.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.1
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• pp.62-71
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• 2016

Food insecurity is associated with poor health outcomes. In particular, previous studies marked the adverse outcomes on mental health. This study examined the association of food insecurity and mental health in Korean adults using the data from the 2013 Korean National Health and Nutrition Examination Survey (KNHANES). The study population was 5,685 adults in Korea. Food insecurity was examined using 18-items. A diagnosis of depression was considered to be depression. Depressive symptoms were defined as more than 2 weeks of depression feelings. Multivariate logistic regression models examined the associations between food insecurity and depression and depressive symptom. The overall prevalence of depression was 3.8% in the participants. Food insecurity was associated significantly with depression and depressive symptom in the unadjusted and age and sex adjusted model. Food insecurity was associated with depression, depressive symptoms in the multivariate logistic regression model (OR:3.49, OR:3.70). Marginal food insecurity was not associated with depression in the multivariate logistic regression model. The results showed that food insecurity is associated with depression and depressive symptoms in adults. Multi-disciplinary interventions are needed including nutrition, health, health policy, and a healthy environment for the food insecurity group to achieve a better health outcome, especially mental health.

• Journal of Korean Society of Environmental Engineers
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• v.22 no.6
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• pp.1149-1158
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• 2000

A radioisotope tracer experiment was carried out in the submerged fixed bioreactor of a dye wastewater treatment facility to evaluate the flow behaviors in the 6 compartments of the reactor and to find any possible factors which may affect to the efficiency of the process. Approximately 20mCi of $^{131}I$ was injected into the system as a tracer and 8 radiation detectors were placed in the 6 compartments and at the inlet and the outlet of the system to measure the change of the tracer concentration with time. Using the Perfect Mixers in Series Model the measured data were analyzed to calculate the mean residence time and the characteristic parameters of the flow in the system. The mean residence time of the system was calculated as 17 hours which is 76% of the designed MRT(22.3hr). Among the 6 compartments, the first compartment doesn't show the characteristic of perfect mixer, whereas, the other 5 compartments are working as perfect mixers. The output response of the first compartment is fit well with the simulated output of a model which consists of a perfect mixer with an exchange volume. It indicates that a quarter of the tank volume is working as a dead volume or an exchange volume. From the measured residence time distributions in each compartment, the appropriate sampling times after the change of operational condition of the electron beam accelerator were evaluated.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.8
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• pp.570-578
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• 2019

In this era of big data, a variety of government organizations are trying to create new added value via Information Integration. Therefore, several projects related to government agencies' information sharing have activated system connection/integration. The risk factors of system operation, however, have increased as the volume of Information Integration System grows. The interference in information sharing is predicted to affect the operation of the agencies, and the issue will grow even worse with massive impact on civil society when the agency operation is interrupted due to system failures in terms of infrastructure, software, data quality, and security. Diverse studies related to the maintenance of Information System have been conducted, but there is currently no evaluation framework for the operational system of Information Integration between various government agencies. In this respect, this study distinguishes each of the Information System components, Data, IT, People, Process, systematizes with Plan-Do-See, and finally presents a maturity model for Information Integration. Nine derived processes were analyzed through interview and questionnaires from Information Integration System officials, further suggesting maturity stage applying CMMI. This model allows diagnosis of the maturity level of an Information Integration System, and is expected to be utilized as resource for improving organizational processes.

• The Journal of the Korea Contents Association
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• v.18 no.12
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• pp.25-34
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• 2018

With the higher competition of university environment, universities has been adapted Customer Satisfaction Index (CSI). However, the problem of CSI focuses on score and ranking announcement. In public sectors, PCSI model is used because of increasing its strategic utilization by providing diagnosis of the phenomenon and direction for future improvement through causal model analysis. The purpose of this research is to develop a measurements of university satisfaction using PCSI. This research demonstrates validity and reliability of PCSI using test-retest method using multi-group confirmatory factor analysis. The results of this research indicate that the reliability and validity of the PCSI model is verified. Service product quality, service delivery quality, environment quality and social quality have positive effects on customer satisfaction. In turn, customer satisfaction have positve effects on university performance and social performance. In conclusion, service quality, PCSI, and service performance are clarified to be appropriate components of the satisfaction survey. These results can be used to measure the satisfaction level of education at actual universities. It is expected that practical basic data can be obtained to improve the quality of university education.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.126-136
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• 2018

The purpose of this study was to develop a severity-adjustment model for predicting mortality in acute stroke patients using machine learning. Using the Korean National Hospital Discharge In-depth Injury Survey from 2006 to 2015, the study population with disease code I60-I63 (KCD 7) were extracted for further analysis. Three tools were used for the severity-adjustment of comorbidity: the Charlson Comorbidity Index (CCI), the Elixhauser comorbidity index (ECI), and the Clinical Classification Software (CCS). The severity-adjustment models for mortality prediction in patients with acute stroke were developed using logistic regression, decision tree, neural network, and support vector machine methods. The most common comorbid disease in stroke patients were hypertension, uncomplicated (43.8%) in the ECI, and essential hypertension (43.9%) in the CCS. Among the CCI, ECI, and CCS, CCS had the highest AUC value. CCS was confirmed as the best severity correction tool. In addition, the AUC values for variables of CCS including main diagnosis, gender, age, hospitalization route, and existence of surgery were 0.808 for the logistic regression analysis, 0.785 for the decision tree, 0.809 for the neural network and 0.830 for the support vector machine. Therefore, the best predictive power was achieved by the support vector machine technique. The results of this study can be used in the establishment of health policy in the future.

• Journal of the Korean Society for information Management
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• v.39 no.1
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• pp.91-117
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• 2022

The number of depressed patients in Korea and around the world is rapidly increasing every year. However, most of the mentally ill patients are not aware that they are suffering from the disease, so adequate treatment is not being performed. If depressive symptoms are neglected, it can lead to suicide, anxiety, and other psychological problems. Therefore, early detection and treatment of depression are very important in improving mental health. To improve this problem, this study presented a deep learning-based depression tendency model using Korean social media text. After collecting data from Naver KonwledgeiN, Naver Blog, Hidoc, and Twitter, DSM-5 major depressive disorder diagnosis criteria were used to classify and annotate classes according to the number of depressive symptoms. Afterwards, TF-IDF analysis and simultaneous word analysis were performed to examine the characteristics of each class of the corpus constructed. In addition, word embedding, dictionary-based sentiment analysis, and LDA topic modeling were performed to generate a depression tendency classification model using various text features. Through this, the embedded text, sentiment score, and topic number for each document were calculated and used as text features. As a result, it was confirmed that the highest accuracy rate of 83.28% was achieved when the depression tendency was classified based on the KorBERT algorithm by combining both the emotional score and the topic of the document with the embedded text. This study establishes a classification model for Korean depression trends with improved performance using various text features, and detects potential depressive patients early among Korean online community users, enabling rapid treatment and prevention, thereby enabling the mental health of Korean society. It is significant in that it can help in promotion.

• The Korean Journal of Franchise Management
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• v.5 no.1
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• pp.109-141
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• 2014

Recently, the interests of consumers in firms that implement the social commitment activities have been consistently growing. Consumers' evaluation about the level of corporate social responsibility(CSR) can affect the overall image for product or service of corporation. This recent changes make a marketer to have to consider direct and indirect effects of CSR efforts on the market performance. This phenomena is also found in the franchise industry. The importance of CSR is more critical rather than other industries since each franchisor should care franchisees as well as end users. Franchisors' execution of CSR could increase satisfaction of end user through consonance of activities provided by franchisees. However most franchisor stay in focusing on the traditional CSR activities. Therefore, this study aims to enhance the understanding the CSR in franchise and provide the phase model of CSR development for general firms including franchise. After diagnosis the firms with the proposed model, the study found many franchisors have huge gap between current CSR activities and higher level of CSR policies that franchisor have to make facing. This study call franchisors to reduce this gap by implementing new CSR efforts. If they answer for this calling, franchise industry could leap for making the best practice of creating shared value with other stakeholders.

• Journal of Service Research and Studies
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• v.11 no.2
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• pp.67-77
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• 2021

This study is a study on the methodology of establishing an innovation strategy centering on the customer experience, which is essential in order to transform the existing collection and preservation-centered mutual aid company service into a visitor-centered service. To this end, we conducted literature research on environmental changes in the funeral industry from the perspective of service science and the significance and value of customer experiences within them, good customer experiences and bad customer experiences from the perspective of customer experience management. A study was conducted to present and prove a specific model. The customer experience-oriented innovation strategy of the funeral industry means to search for various alternatives that can reach the target state from the present state, focusing on the customer, and select the most appropriate transformation plan among them. As an effect of application, it was found that it is a source of differentiation by generating positive emotions to customers, and that customer experience data is highly helpful in making important decisions for the actual resource input of the parent company. This innovation model was presented, and its value was firstly proved by analyzing the difference from the existing evaluation method. Finally, as a result of analyzing the causal relationship through regression analysis using the customer experience measurement procedure, customer experience diagnosis/evaluation, customer experience innovation strategy, and cooperative company's performance as variables, the relationship proved to be significant.

• Information Systems Review
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• v.23 no.1
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• pp.93-113
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• 2021

Service orientation and customer orientation are recognized as important success factors in service companies. However, these constructs are evaluated through self-diagnosis within the service company based on service delivery experience. For this reason, Fintech companies that provide financial services based on non-face-to-face channels such as mobile APP have limitations in evaluating their service orientation and customer orientation. Therefore, in this study, the perceived customer orientation is conceptualized so that service orientation and customer orientation can be evaluated through customer evaluation. In addition, the antecedents and consequences of the perceived customer orientation based on the technology acceptance model were demonstrated. As a result, it was confirmed the mediating effect of perceived customer orientation in the relationship between perceived ease of use and usefulness and customer's continuous use intention and word of mouth intention. This study laid the foundation for the Fintech companies that provide all financial services throughout non-face-to-face to measure their service orientation and customer orientation through customer evaluation and utilize them in establishing service operation strategies.