• Journal of Korean Academy of Nursing
• /
• v.49 no.6
• /
• pp.677-689
• /
• 2019

Purpose: This qualitative study aimed to develop a substantive theory of the process of adaptation to motherhood in Central Asian-Korean immigrants to Korea. Methods: Individual, in-depth interviews were conducted from July to September 2017, with 18 women who emigrated of Korean ethnicity from Central Asia to Korea, and took care of their baby for at least a year after their first delivery in Korea. The interviews were audio-recorded and transcribed verbatim. Data from the transcriptions were analyzed through Strauss and Corbin's grounded theory method, and data analysis was conducted simultaneously with data collection. Results: As a result of categorizing the interview data through the process of open coding, 10 categories, with 31 subcategories and 102 concepts were drawn, and "growth as a Central Asian-Korean mother in an unfamiliar, historical hometown" was found to be the core category of the process of adaptation to motherhood in Central Asian-Korean immigrants to Korea. Conclusion: A characteristic of the process of adaptation to motherhood in Central Asian-Korean immigrants to Korea, drawn from this study, is that it differs according to the level of initiative to carry out interaction strategies, and the use of various supportive social resources. The findings indicate the need for Medicare eligibility adjustment for antenatal care, the extension of the visa renewal period during childbirth, the development of web- or mobile application-based educational programs in Russian language, and the establishment of integrated visiting healthcare services, community service resources, and policy support to enable these women to utilize various supportive social resources.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2017.05a
• /
• pp.482-484
• /
• 2017

Over the past 70 years, movies and television have revolutionized the way people communicate. However, even with this development, TV has been used only as a means of communication targeting an unspecified number of people due to the restriction of media such as radio waves and movies. However, the development of the Internet and online video has come to a time when 100 million people watch YouTube videos uploaded from the other side of the world by eliminating these restrictions. The message that you want to deliver now can be delivered to anyone, but making the image with these messages remains the last obstacle to communication. To solve these problems, we implemented a web application and a video production program through AWS. This system basically provides the administrator with the video production through the easy interface, the information management and the program on the server on the internet through AWS, the assigned lecture including the computer and the smart phone, the learning materials, And implemented to increase the efficiency of educational video production service.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.24 no.3
• /
• pp.499-505
• /
• 2014

According to the increasing use of smart devices such as smart phones and tablets, the service that targets mobile office, finance and e-government for convenience of usage and productivity has emerged significantly. As a result, important information is treated with the smart devices and also, the malicious activity that targets smart devices is increasing steadily. In particular, the damage case by harmful sites, malware distribution sites and phishing sites that targets smart devices has occurred steadily and it has emerged as a social issue. In the case of smart devices, the Android platform is occupied the 90% in Korea, 2013 therefore the method of device block level is required to resolve the social issues of smart devices. In this paper, we propose a method that can be effectively blocked when you try to access an illegal site to Web browser on the Android platform and develop the application and also analyze the wrong site block function.

• KIPS Transactions on Software and Data Engineering
• /
• v.5 no.6
• /
• pp.289-294
• /
• 2016

In recent times, as most people develop keen interest in health management, the importance of cultivating dietary habits to prevent various chronic diseases is emphasized. Subsequently, dietary management systems using a variety of mobile and web application interfaces have emerged. However, these systems are difficult to apply in real world and also do not provide personalized information reflective of the user's situation. Hence it is necessary to develop a personalized dietary management and recommendation method that considers user's body state information, food analysis and other essential statistics. In this paper, we analyze nutrition using self-organizing map (SOM) and prepare data about nutrition using clustering. We provide a substitute food recommendation method and also give feedback about the food that user wants to eat based on personalized criteria. The experiment results show that the distance between input food and recommended food of the proposed method is short compared to the recommended food results using general methods and proved that nutritional similar food is recommended.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2018.05a
• /
• pp.129-130
• /
• 2018

Big data analysis is a technique for effectively analyzing unstructured data such as the Internet, social network services, web documents generated in the mobile environment, e-mail, and social data, as well as well formed structured data in a database. The most big data analysis techniques are data mining, machine learning, natural language processing, and pattern recognition, which were used in existing statistics and computer science. Global research institutes have identified analysis of big data as the most noteworthy new technology since 2011. Therefore, companies in most industries are making efforts to create new value through the application of big data. In this study, we analyzed using the Social Matrics which a big data analysis tool of Daum communications. We analyzed public perceptions of "Artificial Intelligence" keyword, one month as of May 19, 2018. The results of the big data analysis are as follows. First, the 1st related search keyword of the keyword of the "Artificial Intelligence" has been found to be technology (4,122). This study suggests theoretical implications based on the results.

• Anxiety and mood
• /
• v.12 no.1
• /
• pp.13-20
• /
• 2016

Objective : The purpose of this study was to verify the differences of expressed character strengths graded as per the Korean Strength Scale, based on the type of work. Methods : A total of 2,444 conglomerate workers were classified into two groups: 1,356 office workers and 1,088 production workers. The subjects were examined through a web or mobile application based on the Korean Strength Scale. The Korean Strength Scale consists of a total of four top entries and 25 sub-items with appropriate validity. Results : The difference in the average score of sum of character strengths between the two groups was not significant. In the office worker group, character strengths such as love of learning, creativity, perspective, curiosity, facilitation, judgment and faith had significantly high scores. On the other hands, modesty, hope, gratitude, sincerity, magnanimity and self-regulation were high in the production worker group. The results remained unchanged in additional analysis of covariants as sex, age and education level, except for self-regulation and faith. Conclusion : Our results suggest significant differences in the character strengths between the two types of work; however, the average of sum of character strength score remains unchanged. These results may help to understand differences between work environments and thus help to establish a positive foundation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2017.10a
• /
• pp.146-147
• /
• 2017

Big data analysis is a technique for effectively analyzing unstructured data such as the Internet, social network services, web documents generated in the mobile environment, e-mail, and social data, as well as well formed structured data in a database. The most big data analysis techniques are data mining, machine learning, natural language processing, and pattern recognition, which were used in existing statistics and computer science. Global research institutes have identified analysis of big data as the most noteworthy new technology since 2011. Therefore, companies in most industries are making efforts to create new value through the application of big data. In this study, we analyzed using the Social Matrics which a big data analysis tool of Daum communications. We analyzed public perceptions of "Internet of things" keyword, one month as of october 8, 2017. The results of the big data analysis are as follows. First, the 1st related search keyword of the keyword of the "Internet of things" has been found to be technology (995). This study suggests theoretical implications based on the results.

• Journal of Convergence for Information Technology
• /
• v.8 no.6
• /
• pp.217-223
• /
• 2018

Real-time controllability has been a major challenge that should be addressed to ascertain the practical usage of the management systems. In this regards, for the first time, we proposed and implemented an IoT(Internet of Things)-based water tank system to improve convenience and efficiency. The reservoir can be effectively controlled by notifying the user if the condition of the reservoir is unstable. The proposed system consists of embedded H/W unit for sensor data measuring and controling, application S/W for deployment of management server via web and mobile app, and efficient database structure for managing and monitoring statistics. And machine learning algorithms can be applied for further improvements of efficiency in practice.

• The Journal of Korean Association of Computer Education
• /
• v.19 no.3
• /
• pp.21-34
• /
• 2016

This study aims to develop user experience based mathematical program for self-directed learning. To meet its aim this program is designed and developed according to the process and method of 'ADDIE', general design model of education program. The features of this program are as follows. First, teacher can set questions conveniently through intuitive system of web and learner can solve questions at anytime and anywhere through instant access to application. Second, learner can solve different types of questions based on powerful question database and teacher can provide instantaneous feedback on them. Third, learner's circulation learning can be possible by utilizing paper-video explanation and wrong answer note and teacher supports learner's active learning management though group achievement management.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.51 no.6
• /
• pp.162-168
• /
• 2014

'Personal Healthcare Records' (PHR) is a service for providing individual clinical data to patients. PHR service should be useful for the patient and healthcare service providers. This study has aimed at not only providing patients' clinical data but also developing optimized healthcare service for every patients. The research has been conducted as 3 phases: formal case analysis, caregivers interviews and patients interviews. The patients interviews were limited to cancer patients. As results, 3 key functions have been developed. First, it offers patient's clinical pathway as a personalized medical treatment scheduler. Second, it supplies Question & Answer board on online. Last, it supports patients to input their healthcare record. This Myongji PHR service has 3 months of pilot test on web and mobile application(android version). For further commercialized PHR service, the standardization for clinical pathway registration and user convenience need to be considered.