• Journal of Information Technology Services
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• v.18 no.5
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• pp.71-83
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• 2019

This study aimed to develop and pilot-test educational program prototypes of training health coaches to help cancer patients overcome crises and create positive growth. For this purpose, the educational contents and methods of the blended learning program prototypes were derived through learner needs and literature analysis. The prototypes, which consist of introducing of health management and health information and understanding and practice of basic coaching and health coaching, were developed to integrate with four sessions of face-to-face, off-line classes, training practices through 12 tele-classes, and use of online learning system. The prototypes were conducted and pilot-tested by a total of 35 students selected through the document screening and the interview. After participating in the blended learning program, learners expressed greater overall satisfaction with each session program (average score = 4.36, with 5 being most satisfied), satisfaction with learning contents (average score=4.42) satisfaction with course preparation (average score = 4.26) and satisfaction with lecture materials (average score = 4.19). The results of this study show that a systematic and integrative approach for designing a blended learning program can be useful for various educational needs in health and medical fields. In the future, empirical studies are expected to see how these curricula are actually implemented and assess whether the intended learning outcomes are achieved.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.34 no.2
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• pp.93-114
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• 2023

In accordance with the educational paradigm that values self-directed creative education, school libraries and public libraries emphasize self-directed learning support through curriculum-linked programs as their main tasks. For self-directed learning, it is essential to provide learner-centered educational knowledge information, and there should be abundant textbook-linked references that can deepen and expand the curriculum reflected in textbooks. This study established KDC-linked information related to unit and cross-curricular learning topics through the analysis of elementary school textbooks and curriculum-linked books, restructured KDC system based on major subjects in the elementary school curriculum, and established a curriculum-linked subject information. Libraries can strengthen support for self-directed creative learning for elementary school students in an online environment by linking library content targeted for each user with elementary school education content focusing on learning topics in the curriculum.

• International journal of advanced smart convergence
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• v.9 no.3
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• pp.183-191
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• 2020

Today, taking photos using smartphones has become an essential element of modern people. According to these social changes, modern people need a larger storage capacity, and the number of unnecessary photos has increased. To support the storage, cloud-based photo storage services from various platforms have appeared, and many people are using the services. As the number of photos increases, it is difficult for users to find the photos they want, and it takes a lot of time to organize. In this paper, we propose a cloud-based photo management service that facilitates photo management by classifying photos and recommending unnecessary photos using deep learning. The service provides the function of tagging photos by identifying what the subject is, the function of checking for wrongly taken photos, and the function of recommending similar photos. By using the proposed service, users can easily manage photos and use storage capacity efficiently.

• Journal of Information Technology Services
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• v.18 no.1
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• pp.173-186
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• 2019

Recently, as the amount of fine dust has risen rapidly, our interest is increasing day by day. It is virtually impossible to remove fine dust. However, it is best to predict the concentration of fine dust and minimize exposure to it. In this study, we developed a mathematical model that can predict the concentration of fine dust using various information related to the weather and air quality, which is provided in real time in 'Air Korea (http://www.airkorea.or.kr/)' and 'Weather Data Open Portal (https://data.kma.go.kr/).' In the mathematical model, various domestic seasonal variables and atmospheric state variables are extracted by multiple regression analysis. The parameters that have significant influence on the fine dust concentration are extracted, and using ANN (Artificial Neural Network) and SVM (Support Vector Machine), which are machine learning techniques, we proposed a prediction model. The proposed model can verify its effectiveness by using past dust and weather big data.

• The Korean Journal of Emergency Medical Services
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• v.15 no.2
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• pp.15-26
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• 2011

Purpose: The purpose of this study was to develop and implement the educational program of Life Safety Support for parent. Methods: This study was used to develop children life safety support education program. The education program was utilized as multimedia, practice and discussions to increase understanding and effectiveness of learning. The data for this study was collected from June to December, 2010. There were two forms of evaluations, pretest and posttest with an intervention of education program. The analysis of the collected data was analyzed by descriptive analysis, t-test and paired t-test using the SPSS 10.0 program. Results: 1. the experimental group, who was given an education program before the test, got higher marks on the Life Safety support knowledge than the control group. There was a significant difference in knowledge between experimental group and control group(t=6.678, p=.000). 2. the experimental group got higher marks on the action evaluation than the control group. There was a significant difference in the certainty of action(t=8.546, p=.000) between experimental group and control group. Conclusion: This study examined how Life Safety support education program increased effectiveness in the knowledge and action of children Life Safety support.

• The Journal of Information Systems
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• v.30 no.3
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• pp.65-91
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• 2021

Purpose In this study, we investigated the impact of perceived risk and switching costs on switching intention to cloud service based on PPM (Pull-Push-Mooring) model. Design/methodology/approach We focused on revealing the switching factors of the switching intention to the cloud services. The switching factors to the cloud services were defined as perceived risk consisting of performance risk, economic risk, and security risk, and switching costs consisting of financial and learning costs. On the PPM model, we defined the pull factors consisting of perceived usefulness and perceived ease of use, and the push factor as satisfaction of the legacy system, and the mooring factor as policy supports. Findings The results of this study as follows; (1) Among the perceived risk factors, performance risk has a negative effect on the ease of use of pull factors, and finally it was found to affect the switching intention to the cloud services. Therefore, cloud service providers need to improve trust in cloud services, service timeliness, and linkage to the legacy systems. And it was found that economic risk and security risk among the perceived risk factors did not affect the switching intention to the cloud services. (2) Of the perceived risk factors, financial cost and learning cost did not affect the satisfaction of the legacy system, which is a push factor. It indicates that the respondents are positively considering switching to cloud service in the future, despite the fact that the respondents are satisfied with the use of the legacy system and are aware of the switching cost to cloud service. (3) Policy support was found to improve the switching intention to cloud services by alleviating the financial and learning costs required for cloud service switching.

• Journal of the Korea Society of Computer and Information
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• v.23 no.7
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• pp.19-26
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• 2018

This paper presents a structuring process of unstructured social network service (SNS) messages on rail services. We crawl messages about rail services posted on SNS and extract keywords indicating date and time, rail operating company, station name, direction, and rail service types from each message. Among them, the rail service types are classified by machine learning according to predefined rail service types, and the rest are extracted by regular expressions. Words are converted into vector representations using Word2Vec and a conventional Convolutional Neural Network (CNN) is used for training and classification. For performance measurement, our experimental results show a comparison with a TF-IDF and Support Vector Machine (SVM) approach. This structured information in the database and can be easily used for services for railway users.

• Journal of Internet Computing and Services
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• v.22 no.5
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• pp.27-33
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• 2021

With the broad adoption of the Internet of Things (IoT) in a variety of scenarios and application services, management and orchestration entities require upgrading the traditional architecture and develop intelligent models with ultra-reliable methods. In a heterogeneous network environment, mission-critical IoT applications are significant to consider. With erroneous priorities and high failure rates, catastrophic losses in terms of human lives, great business assets, and privacy leakage will occur in emergent scenarios. In this paper, an efficient resource slicing scheme for optimizing federated learning in software-defined IoT (SDIoT) is proposed. The decentralized support vector regression (SVR) based controllers predict the IoT slices via packet inspection data during peak hour central congestion to achieve a time-sensitive condition. In off-peak hour intervals, a centralized deep neural networks (DNN) model is used within computation-intensive aspects on fine-grained slicing and remodified decentralized controller outputs. With known slice and prioritization, federated learning communications iteratively process through the adjusted resources by virtual network functions forwarding graph (VNFFG) descriptor set up in software-defined networking (SDN) and network functions virtualization (NFV) enabled architecture. To demonstrate the theoretical approach, Mininet emulator was conducted to evaluate between reference and proposed schemes by capturing the key Quality of Service (QoS) performance metrics.

• Journal of Information Technology Services
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• v.22 no.6
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• pp.71-86
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• 2023

The rapid change in industry and the technological gap give rise to social demand for upskilling and reskilling and spread of alternative education. Against this backdrop, digital certification and career management tools can be used to manage various types of learning activities comprehensively. Digital badges provide various kinds of history information related to individual learning, and the reliability and transparency of the issued information can be strengthened by applying blockchain technology. There have been various discussions about digital badges for a long time, but due to the lack of standards to support the issuance and distribution of digital badges, they have been partially used in some areas. However, interest in digital badges is increasing due to the development of related technologies, establishment of standards, paradigm changes in higher education, and government policies related to nurturing digital talent. This paper deals with the use of digital badges for efficient and transparent learning management and career management in an online learning environment. The researcher analyzes the technical characteristics and use cases of digital badges, and proposes a plan for use in online higher education based on them.

• Child Health Nursing Research
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• v.18 no.1
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• pp.19-28
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• 2012

Purpose: The study aimed to identity specific needs for services and programs to help childhood cancer survivors adjust and adapt to life after treatment. Methods: In-depth interviews were conducted with 31 childhood cancer survivors, diagnosed with cancer before the age of 18 and currently between 15 and 39 years of age. Each survivor had completed his/her cancer treatment. Results: The participating cancer survivors reported needs for services related to psychological counseling, schooling and learning, social skills, mentorship, integrated health management, self support activities, families of survivors, and public recognition and awareness. Conclusion: The results of the study indicate a need to better understand childhood cancer survivors, provides a basis for developing various services and programs to improve the quality of life among childhood cancer patients, survivors, and their families, and supports the importance of psychosocial adjustment.