• The Korean Journal of Archival Studies
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• no.39
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• pp.101-138
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• 2014

This study examined the influence and meaning of SNS as the hot topic of our time from the archival perspective and also studied the 'SNS records management'. The many users mean a high accessibility and utilization of SNS, which increase the influence and value of SNS as a record. Politically, SNS is a tool that strengthens the communication among the voters, politicians and the public while economically, it is a window to accept the complaints of the customers and a marketing tool. In addition, the voices of social minorities are also recorded unlike in the traditional media, which makes the SNS record a method to gain the social variety and diversity. SNS is a place of formation of collective memory and collective memory itself. Furthermore, it can play the role of public sphere. It also is a place for generation of 'big data' in an archival sense. In addition, this study has classified the SNS records management into primary and secondary management that include record management entities, subjects, periods, methods, and causes. This study analyzed the history, status, and the meaning of SNS to assess the values and meanings as the preliminary study for the future SNS record management studies.

• Journal of Industrial Convergence
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• v.16 no.1
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• pp.21-26
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• 2018

The Seaborne Trade Volume accounts for 97% of the total. This means that the port operation management system can improve port efficiency, reducing operating costs, and the manager who manages all operations at the port needs to check and respond quickly when delays of work and equipment support is needed. Based on the real-time location information confirmation of yard automation equipment used the existing system GPS, the real-time location information confirmation system is a GPS system of the tablet, rather than a port operation system that monitors location information for the entered information, depending on the completion of the task or the start of the task. Network configurations also reduce container processing delays by using commercial LTE services that do not have shading due to containers in the yard also reduce container processing delays. Trough introduction of smart devices using Android or IOS and container processing scheduling utilizing artificial intelligence, we will build a minimum delay system with Smart Device usage of container processing applications and optimization of container processing schedule. The adoption of smart devices and the minimization of container processing delays utilizing artificial intelligence are expected to improve the quality of port services by confirming the processing containers in real time to consumers who are container information demanders.

• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.3201-3209
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• 2018

The purpose of this study was to explore the factors predicting increased usage hours of smartphone among adolescents. Secondary data was analyzed to be collected from a nationally representative sample of 2017 Korean adolescents. This study sample included 54,601 students in middle or high schools of Korea. The collected data were analyzed SPSS version 23.0 program for frequency, percentage, mean, standard deviation, t-test, ANOVA, Pearson's correlation coefficient and binary logistic regression analysis. In the results, the mean usage hour of smartphone among the adolescents was 28.42 (SD 23.30) per week. Analyses of the differences in usage hours of smartphone according to research variables were found that the groups of lower level of study (F=1361.067, p<.001) and sociality content type (F=761.549, p<.001) spent more time, as compared to the other groups. The logistic analysis showed the predictive factors for increased hour of using smartphone were smartphone usage for sociality (OR: 2.44, 95% CI: 2.26-2.64) and peer group counselor (OR: 1.49, 95% CI: 1.49). Conclusionally, the findings of this study suggests that it needs to understand cause or purpose of smartphone using of adolescent and to cope and educate on the cause.

• Journal of Convergence for Information Technology
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• v.11 no.4
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• pp.26-34
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• 2021

In the era of the Fourth Industrial Revolution, the future battlefield will carry out multi-area operations with hyper-connected, high-speed and mobile systems. In order to prepare for changes in the future, the Korean military intends to develop various weapons systems and form a multi-layer tactical network to support On The Move communication. However, current tactical networks are limited in support of On The Move communications. In other words, the operation of multi-beam antennas is necessary to efficiently construct a multi-layer tactical network in future warfare. Therefore, in this paper, we look at the need for multi-beam antennas through the operational scenario of a multi-layer tactical network. In addition, based on development consideration factors, features of rotary-wing and fixed-wing aircraft, we present the location and operation of airborne relay drone installations of multi-beam antennas.

• Science of Emotion and Sensibility
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• v.24 no.1
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• pp.91-104
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• 2021

This study explored users' emotional states identified from the wake-up words -"Hi, KIA!"- using a machine learning algorithm considering the user interface of passenger cars' voice. We targeted four emotional states, namely, excited, angry, desperate, and neutral, and created a total of 12 emotional scenarios in the context of car driving. Nine college students participated and recorded sentences as guided in the visualized scenario. The wake-up words were extracted from whole sentences, resulting in two data sets. We used the soundgen package and svmRadial method of caret package in open source-based R code to collect acoustic features of the recorded voices and performed machine learning-based analysis to determine the predictability of the modeled algorithm. We compared the accuracy of wake-up words (60.19%: 22%~81%) with that of whole sentences (41.51%) for all nine participants in relation to the four emotional categories. Accuracy and sensitivity performance of individual differences were noticeable, while the selected features were relatively constant. This study provides empirical evidence regarding the potential application of the wake-up words in the practice of emotion-driven user experience in communication between users and the artificial intelligence system.

• Journal of Convergence for Information Technology
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• v.10 no.12
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• pp.15-21
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• 2020

Although IoT systems are used in a variety of heterogeneous environments as cloud environments develop, all IoT devices are not provided with reliable protocols and services. This paper proposes an IoT data management technique that can extend the IoT cloud environment to an n-layer multi-level structure so that information collected from different heterogeneous IoT devices can be efficiently sorted and processed. The proposed technique aims to classify and process IoT information by transmitting routing information and weight information through wireless data link data collected from heterogeneous IoT devices. The proposed technique not only delivers information classified from IoT devices to the corresponding routing path but also improves the efficiency of IoT data processing by assigning priority according to weight information. The IoT devices used in the proposed technique use each other's reliable protocols, and queries for other IoT devices locally through a local cloud composed of hierarchical structures have features that ensure scalability because they maintain a certain cost.y channels of IoT information in order to make the most of the multiple antenna technology.

• Journal of the Korean Society of Radiology
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• v.14 no.7
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• pp.915-922
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• 2020

This study analyzed the content of use Tendency and addiction according to smartphone use of targeting radiological Technologist working in Gyeongnam area. The tool used as the data for the study is a survey. From April 21 to May 31, 2019, a total of 330 questionnaires were distributed to radiological Technologist working at medical institutions in Gyeongnam, and 300 copies suitable for the study were SPSS/PC Ver 18.0 program for Analysis was performed using. The factors of the study subject's tendency to use smartphone were communication, information, leisure, and convenience. As for the addiction factors, a total of 37 questions were analyzed, including daily living disorder, virtual world orientation, tolerance, and withdrawal. Smartphone-related characteristics were set as monthly average fee, usage time, and SNS usage time, and technical statistics, t-test, ANOVA, correlation and regression analysis were performed. The radiological Technologist tendency to use smartphones was 3.10±.55 points, which was average, and smartphone addiction was 2.34±.62 points, which was lower than the average. It was found that there was a significant correlation between the radiological Technologist Tendency to use smartphone and addiction. The effect of radiological Technologist tendency to use smartphone on addiction it was found to account for 10.8%. Through this study, it can be said that it is important to analyze the addiction factors according to the tendency use smartphone of radiological Technologist and to prepare a desirable plan for smartphone use.

• Journal of Convergence for Information Technology
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• v.11 no.6
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• pp.262-269
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• 2021

The Ministry of National Defense is re-establishing the role of the Army in accordance with the defense reform and is promoting the Warrior Platform, a next-generation individual combat system. The Warrior Platform project is divided into three stages and is being promoted. In the first stage, the quality and performance of individual items are improved, in the second stage, items between system development are integrated, and in the third stage, the combat capability is maximized by developing an integrated unit weapon system. In this paper, detailed sub-items for the five essential required competencies (survival, lethality, mobility, sustainability, Communication) that are considered for building an effective warrior platform are presented. We also present a plan that can be used to prepare a specific master plan for the Army's Warrior Platform project by using Analytic Hierarchy Process(AHP) and selecting the priority of the five required capabilities and detailed sub-items for different unit types. As a result of analyzing the priorities of the four types of units with different mission types, we find that there are differences for each unit. These results are expected to be used as useful reference materials for setting the future direction for the development of warrior platform.

• The Korean Journal of Applied Statistics
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• v.34 no.1
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• pp.115-126
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• 2021

Central banks communicate with the market through a statement on the direction of monetary policy while implementing monetary policy. The rapid contraction of the global economy due to the recent Covid-19 pandemic could be compared to the crisis situation during the 2008 global financial crisis. In this paper, we analyzed the text data from the monetary policy statements of the Bank of Korea and Fed reflecting monetary policy directions focusing on how they were affected in the face of a global crisis. For analysis, we collected the text data of the two countries' monetary policy direction reports published from October 1999 to September 2020. We examined the semantic features using word cloud and word embedding, and analyzed the trend of the similarity between two countries' documents through a piecewise regression tree model. The visualization result shows that both the Bank of Korea and the US Fed have published the statements with refined words of clear meaning for transparent and effective communication with the market. The analysis of the dissimilarity trend of documents in both countries also shows that there exists a sense of synchronization between them as the rapid changes in the global economic environment affect monetary policy.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.3
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• pp.73-86
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• 2021

The primary purpose of this paper is to explore the advanced models that predict entrepreneurial innovativeness most accurately. For the first time in the field of entrepreneurship research, it presents a model that predicts entrepreneurial innovativeness based on machine learning corresponding to data scientific approaches. It uses 22,099 the Global Entrepreneurship Monitor (GEM) data from 62 countries to build predictive models. Based on the data set consisting of 27 explanatory variables, it builds predictive models that are traditional statistical methods such as multiple regression analysis and machine learning models such as regression tree, random forest, XG boost, and artificial neural networks. Then, it compares the performance of each model. It uses indicators such as root mean square error (RMSE), mean analysis error (MAE) and correlation to evaluate the performance of the model. The analysis of result is that all five machine learning models perform better than traditional methods, while the best predictive performance model was XG boost. In predicting it through XG boost, the variables with high contribution are entrepreneurial opportunities and cross-term variables of market expansion, which indicates that the type of entrepreneur who wants to acquire opportunities in new markets exhibits high innovativeness.