• Convergence Security Journal
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• v.15 no.2
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• pp.19-24
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• 2015

As the Internet usage such as Web3.0, future internet, and internet of things increases, the big data through information exchange between the users and web servers increases. Analyzing those web data, the commercial web sites use the analytic results for marketing and campaign, and non-commercial web sites also use the results to improve the user's services satisfaction. In this paper, the quantitative index is presented to analyze the web sites, and optimized web site design method is also presented through the correlation analysis of index and significance test. From the results for 138 web sites, it is observed that strong plus(+) correlation for visits-unique visitors and page views-average visit duration exists. We also observe the minus(-) correlation between bounce rate and page views per user(or ratio of new visits). In specific, to reduce the bounce rate for users, the strategy to increase the page views and ratio of new visits rather than visits and unique visitors is needed.

• Journal of Digital Contents Society
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• v.19 no.5
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• pp.845-852
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• 2018

This study has developed a preventive launcher from smartphone addiction for the digital generation and the contents recommendation based on machine learning which used multiple and collective intelligence. This could provide convenient digital nurturing experience for the parents who fear their children's over use of digital devices and also suggest individually adaptive digital learning methods that enhance the learning efficiency and pleasurable and safe learning environment for the children. Suggested application is a kind of gamification launcher that protects children from harmful contents and from smartphone addiction with time limit settings. For parents who find difficulty choosing from various kinds of contents and applications for education, this suggested system could provide a learning analytic report based on big data after collecting and analyzing the data of their children's learning and activities and recommend contents necessary for their kids using recommended algorithm by collective intelligence.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.220-222
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• 2019

Korean automobile industry has been slow down since 2016. The most fundamental solution for solving this problem is to develop competitive parts. There are two important factors for developing competitive parts. The most important is product design technology, and the second most important is production technology. Production technology is important because it requires lowering the production cost except for the material cost and continuously maintaining the quality. In this paper, an intelligent smart inspection system is proposed and designed to inspect automobile parts of company C. At present, the basic and detailed design of this system has been completed and it is in the development progress stage. If the system is successfully developed, it is expected that the quality inspection stage of company C will be automated and the defect rate will be reduced.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.787-793
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• 2022

After COVID-19, with the emergence of social distancing, non-face-to-face services, and home economics, visiting dining out is rapidly being replaced by non-face-to-face dining out. The purpose of this study is to find ways to create a safe dining culture centered on living quarantine in line with the changing trend of the restaurant industry after the outbreak of COVID-19, establish the direction of food culture improvement projects, and enhance the effectiveness of the project. This study used TEXTOM to collect and refine search frequency, perform TF-IDF analysis, and Ucinet6 programs to implement visualization using NetDraw from January 1, 2018 to October 31, 2019 and December 31, 2021, and identified the network between nodes of key keywords. Finally, clustering between them was performed through Concor analysis. As a result of the study, if you check the frequency of searches before and after COVID-19, it can be seen that the COVID-19 pandemic greatly affects the changes in the restaurant industry.

• Journal of Korean Society for Quality Management
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• v.45 no.4
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• pp.629-648
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• 2017

Purpose: The world faces a great turning point fundamentally rebuilding the future, and human lives, by embracing the 4th industrial revolution era. This paper aims to seek new and various business models in the 4th industrial revolution era, and to examine the evolution of quality management in the changing of the industrial ecosystem. Methods: This paper examines the various strategies of approaching the 4th industrial revolution in Germany, the USA, Japan, China, and Korea. This paper also draws detailed items by classifying the six major items of Malcolm Baldridge into large, medium, and small scale classifications, researches items from the technical perspective by applied fields, and the four major factor perspectives of quality management, as well as analyzes the relevant items in a multidimensional method. After a questionnaire survey targeting 200 quality experts was conducted, the important quality management factors were selected by applying the Analytic Hierarchy Process (AHP) method. Results: The importance of the general criteria was analyzed in the order of customers, MAKM (measurement, analysis, and knowledge management), workforce, strategy, operations, and leadership. As for the importance analysis results of the secondary subcriteria, the following items are highly analyzed: senior leadership, searching business model's innovation opportunity, customer satisfaction improvement, big data utilization, systematic management of workforce, and, planning and design quality. Conclusion: In the era of the Internet of everything, when complexity increases, this study presented a quality management direction suitable for new business methods challenging existing orders by drawing on quality management priorities.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.140-143
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• 2017

Lately, the three mobile telecom companies in Korea are competing for the launch of internet of things services for using home. Typical launched services are in the smart home related fields. However, internet of things as mobile telecom based are at an early stage, expected that various services will be started continuously. At this point, we have been planning to analyze the preference of Internet of things for objects based on the services already launched. In order to apply the AHP (analytic hierarchy process) analysis method, the first stage factors were designed as safety, security, health care, intelligence and home appliances. In addition, the second stage factors were organized into 18 detailed services presented in the conceptual model. Thus, we present the theoretical and practical implications of these results.

• Convergence Security Journal
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• v.22 no.5
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• pp.135-143
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• 2022

The defense environment is rapidly changing, such as nuclear and missile threats of North Korea, changes in war patterns, and a decrease in military service resources due to low birth rate. In order to actively respond to these changes, the Korean military is promoting Defense Innovation 4.0 and is trying to foster an army armed with high technology such as artificial intelligence (AI), big data analysis, etc. In this regard, we analyze the effectiveness of the radar-based AI scientific guard system applied by high technology for guard operations using Analytic Hierarchy Process (AHP). We first select evaluation factors that can assess the effectiveness of the scientific guard system, and analyze its relative importance. Each evaluation factor was selected by deriving a significant concept from operating principle and how they work, and by consulting experts on the correlation between each factor and effectiveness of the scientific guard system. We examine the relative effects of the radar-based AI scientific guard system and existing scientific guard system based on the importance of the evaluation factors.

• The Journal of Information Systems
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• v.31 no.3
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• pp.177-195
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• 2022

Purpose This paper aims to prepare a full operational readiness by establishing an optimal flight plan considering the weather conditions in order to effectively perform the mission and operation of military aircraft. This paper suggests a flight prediction model and rules by analyzing the correlation between flight implementation and cancellation according to weather conditions by using big data collected from historical flight information of military aircraft supplied by Korean manufacturers and meteorological information from the Korea Meteorological Administration. In addition, by deriving flight rules according to weather information, it was possible to discover an efficient flight schedule establishment method in consideration of weather information. Design/methodology/approach This study is an analytic study using data mining techniques based on flight historical data of 44,558 flights of military aircraft accumulated by the Republic of Korea Air Force for a total of 36 months from January 2013 to December 2015 and meteorological information provided by the Korea Meteorological Administration. Four steps were taken to develop optimal flight prediction models and to derive rules for flight implementation and cancellation. First, a total of 10 independent variables and one dependent variable were used to develop the optimal model for flight implementation according to weather condition. Second, optimal flight prediction models were derived using algorithms such as logistics regression, Adaboost, KNN, Random forest and LightGBM, which are data mining techniques. Third, we collected the opinions of military aircraft pilots who have more than 25 years experience and evaluated importance level about independent variables using Python heatmap to develop flight implementation and cancellation rules according to weather conditions. Finally, the decision tree model was constructed, and the flight rules were derived to see how the weather conditions at each airport affect the implementation and cancellation of the flight. Findings Based on historical flight information of military aircraft and weather information of flight zone. We developed flight prediction model using data mining techniques. As a result of optimal flight prediction model development for each airbase, it was confirmed that the LightGBM algorithm had the best prediction rate in terms of recall rate. Each flight rules were checked according to the weather condition, and it was confirmed that precipitation, humidity, and the total cloud had a significant effect on flight cancellation. Whereas, the effect of visibility was found to be relatively insignificant. When a flight schedule was established, the rules will provide some insight to decide flight training more systematically and effectively.

• Journal of Korean Academy of Nursing
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• v.21 no.1
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• pp.89-116
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• 1991

The purpose of this study was to describe mother -infant interacting behavior patterns related to newborn infant feeding and to explore the mother's cultural belief about their infant. The data collection was conducted by observation and interview. Twenty-five mothers and their newborn infants who were normally delivered and were also planned to breast feed were comprised as the subjects of this study. All subjects were interviewed and observed individuaily at 1 to 5 days after the delivery at the hospital, mid -wife's clinic, Maternal Child Health Center and their home throughout the country from remote area to big city, The observation data were recorded with symbolic letter on a recording sheet newly developed as a result of preliminary study. The interview data were taperecorded and then recorded in narrative form. Mother - infant interaction behaviors in early feeding period were analyzed based on 19 analytic sub-categories and their composing elements. Unit of analysis were mother, infant and mother -infant dyad. 8 analytic categories draw from the data. Each were preparation, instrument, interaction inducing, evaluation referred to mother's behavior, preparation, instrument, interaction inducing referred to infant's behavior and synchronic behaviors referred to mother - infant dyad. Frequencies of behavior items based on the categories were converted to percent. The result showed that in mother's preparation behavior, the breast condition of Korean mother can be an affecting factor for mother - infant interaction during feeding, and vocalization behavior was observed most frequently in interaction inducing behavior while the least frequent behavior observed was contacting. Subcultural characteristics of mother - infant interaction behaviors were analyzed for their relationships between groups of mothers who have lived in remote area vs urban area, and who were multipara vs primipara. Using a chi -square test, there were statistically significant relationships in the activity of psychological readiness in preparation behavior and the movement of extremities for the position of instrumental behavior in both groups. However, interaction inducing behaviors were not related with statistical significance in any set of groups. Accomplishment of marriage, bonding and emotional mediation of family members were the categories related to mother's cultural belief about the infant in aspect of functional values. Infant at birth is considered little more than a biological organism without social capabilities. Although the newborn infant is still be attached to his mother, he makes his mother extend her territoriality. The mother's interacting behavior toward her infant based on those beliefs appeared task oriented, separative behavioral series. On the other hand, it was seen that infant reacted independently to his mother's behavior by the in-nate perceptual abilities. Those independent behavioral series of mother and infant on the feeding situation were synchronized at any moment. Nurses are In a unique position to teach mothers about their infant's capabilities and help reducing some of uncertainty about infant's behaviors. Study results indicated that the informations infant's social capabilities and breast feeding should be given to the mothers. The results of this study have several implications for nursing. First, the study results will be used as fundamental resources for the development of the assessment tool about the early mother - infant interaction. Second, the results could be a relevant information in the fied. I of maternal child nursing education as real and useful data. Third, the behavioral patterns of early mother - infant interaction which were classified based on the qualitative analysis could be used for nursing theory development as very fundamental data.

• Journal of the Korea Convergence Society
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• v.6 no.1
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• pp.77-83
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• 2015

Though the SNA (social network analysis ; SNA) has been used for various fields, esp. social science field, ig. politics, journalism, and science of public administration as well as natural science field, there are few studies about the introduction of analysis tools. In order to perform the SNA, collecting data which are fit for the purpose, statistical values deduction and visualized results made by analysis tool are necessary, but the studies, which explain them systematically, are not sufficient yet. So, in this study, we are intended to introduce the analytic process, from the data input to the interpretation, with proven data. using the R program, which is free, in order to help researchers who have any plan to study using the SNA. The proven data in this study are quoted ones in the domestic scientific journals of food, which are those supplied citation index DB of Korean scientific journals. As a study methodology, the SNA is a new paradigm to substitute existing research methods as well as a complement of statistical analysis. Therefore, this study would contribute to vitalization of the SNA.