• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.3
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• pp.669-678
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• 2018

This study developed information technology infrastructures for building a driving environment analysis platform using various big data, such as vehicle sensing data, public data, etc. First, a small platform server with a parallel structure for big data distribution processing was developed with H/W technology. Next, programs for big data collection/storage, processing/analysis, and information visualization were developed with S/W technology. The collection S/W was developed as a collection interface using Kafka, Flume, and Sqoop. The storage S/W was developed to be divided into a Hadoop distributed file system and Cassandra DB according to the utilization of data. Processing S/W was developed for spatial unit matching and time interval interpolation/aggregation of the collected data by applying the grid index method. An analysis S/W was developed as an analytical tool based on the Zeppelin notebook for the application and evaluation of a development algorithm. Finally, Information Visualization S/W was developed as a Web GIS engine program for providing various driving environment information and visualization. As a result of the performance evaluation, the number of executors, the optimal memory capacity, and number of cores for the development server were derived, and the computation performance was superior to that of the other cloud computing.

• The Journal of the Korea Contents Association
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• v.18 no.9
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• pp.149-155
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• 2018

Due to the rapid development of medical information, vast amounts of medical data are accumulating, and such medical data is highly likely to be used as an important data for solving the aging population and the rapid rise in medical cost. Especially in Korea, there are resident registration numbers and computerized usage data for all citizens, so it can be superior to other countries in terms of medical infrastructure that can utilize big data. The purpose of this study was to analyze the factors affecting the mortality and death rate of Gangwon using the Big Data and the National Statistical Office data centered on Kangwon province. As a result of analysis, major variables related to the mortality rate of Gangwon were hospital infrastructure utilization rate, income level, aging population and population density. Therefore, inequalities due to income disparities and insufficient local medical infrastructures were affecting the local mortality rate, and policy support was needed to improve the local hospital infrastructure and income level. The results of this study were meaningful in that medical big data were used to analyze the deaths of people in Gangwon, and the causes of the deaths were analyzed through various social indicators and correlation analysis.

• Journal of KIBIM
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• v.13 no.3
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• pp.39-47
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• 2023

This study aims to introduce a model for enhancing community well-being through the utilization of public open data. To objectively assess abstract notions of residential satisfaction, text data from complaints is analyzed. By leveraging accessible public data, costs related to data collection are minimized. Initially, relevant text data containing civic complaints is collected and refined by removing extraneous information. This processed data is then combined with meaningful datasets and subjected to topic modeling, a text mining technique. The insights derived are visualized using Geographic Information System (GIS) and Application Programming Interface (API) data. The efficacy of this analytical model was demonstrated in the Godeok/Gangil area. The proposed methodology allows for comprehensive analysis across time, space, and categories. This flexible approach involves incorporating specific public open data as needed, all within the overarching framework.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.28 no.4
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• pp.89-101
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• 2020

In order to enhance the safety of the international aviation industry, the International Civil Aviation Organization has recommended establishing an operational foundation for systematic and integrated collection, storage, analysis and sharing of aviation safety data. Accordingly, the Korea aviation industry also needs to comprehensively manage the safety data which generated and collected by various stakeholders related to aviation safety, and through this, it is necessary to previously identify and remove hazards that may cause accident. For more effective data management and utilization, a standard structure should be established to enable integrated management and sharing of safety data. Therefore, this study aims to propose the framework about how to manage and integrate the aviation safety data for big data-based aviation safety management and shared platform.

• Journal of Korean society of Dental Hygiene
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• v.11 no.5
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• pp.791-799
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• 2011

Objectives : This study aimed at examining the aspects of utilization of the dental services in some regions and analyzing the related factors with a view to helping the old solve the dental problems and overcome the difficulties. Methods : This investigation was intended for 422 old people living in Jeon-ju city and Jang-su county from July 18, 2006 to August 25 by direct interviewing posing questions. The survey data sets were analyzed by chi-square, correlation, multiple regression and logistic regression. Results : 1. The average number of the existing teeth per an old person was 13.6 and the 28.8% of the old who didn't use denture called for dentures. 2. The annual coefficient of utilization in dental services for an old person was 52.3% and the annual average visits to dental clinics were 3.12 days while 38.6% of the old experienced illegal dental treatments. 3. The affecting factors on the dental utilization for treatment were as follows: family income, dental clinics available, the number of existing teeth, the days of dental trouble, the recognition of the prevention of the dental disease, the knowledge for the dental treatment and the oral health judged by himself. 4. The major variables influencing the utilization of dental services were spouse presence, form of family, income, having a regular dental care, denture presence and the experience of inconvenience in living. Conclusions : To conclude, the following suggestions could be made. First, It was necessary that enforcement practice of free dental prosthesis service and application to the national health insurance in old people's prosthetic therapy for government support because the economic factor was barrier to utilization of the dental services. Second, Dental clinic was required to the health center because availability of common dental services was big impact in utilization of the dental services.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.1
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• pp.237-252
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• 2017

In recent years, data centers have become the core infrastructure to deal with big data processing. For these big data applications, network transmission has become one of the most important factors affecting the performance. In order to improve network utilization and reduce job completion time, in this paper, by real-time monitoring from the application layer, we propose job-aware priority scheduling. Our approach takes the correlations of flows in the same job into account, and flows in the same job are assigned the same priority. Therefore, we expect that flows in the same job finish their transmissions at about the same time, avoiding lagging flows. To achieve load balancing, two approaches (Flow-based and Spray) using ECMP (Equal-Cost multi-path routing) are presented. We implemented our scheme using NS-2 simulator. In our evaluations, we emulate real network environment by setting background traffic, scheduling delay and link failures. The experimental results show that our approach can enhance the Hadoop job execution efficiency of the shuffle stage, significantly reduce the network transmission time of the highest priority job.

• Journal of the Society of Disaster Information
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• v.18 no.1
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• pp.146-153
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• 2022

Purpose: In the case of domestic port facilities, port structures that have been in use for a long time have many problems in terms of safety performance and functionality due to the enlargement of ships, increased frequency of use, and the effects of natural disasters due to climate change. A big data analysis method was studied to develop an approximate model that can predict the aging pattern of a port facility based on the maintenance history data of the port facility. Method: In this study, member-level maintenance history data for caisson-type quay walls were collected, defined as big data, and based on the data, a predictive approximation model was derived to estimate the aging pattern and deterioration of the facility at the project level. A state-based aging pattern prediction model generated through Gaussian process (GP) and linear interpolation (SLPT) techniques was proposed, and models suitable for big data utilization were compared and proposed through validation. Result: As a result of examining the suitability of the proposed method, the SLPT method has RMSE of 0.9215 and 0.0648, and the predictive model applied with the SLPT method is considered suitable. Conclusion: Through this study, it is expected that the study of predicting performance degradation of big data-based facilities will become an important system in decision-making regarding maintenance.

• Journal of Digital Contents Society
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• v.18 no.6
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• pp.1175-1182
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• 2017

Recent trend in the manufacturing industry is focused on the convergence with IoT and Big Data, by emergence of the 4th Industrial Revolution. To realize a smart factory, the proposed system based on MTConnect technology collects and integrates various status information of machines from many production facilities including heterogeneous devices. Also it can distribute the acquisited status of heterogeneous manufacturing machines to the remote devices. As a key technology of a flexible automated production line, the proposed system can provide much possibility to manage important information such as error detection and processing state management in the unmanned automation line.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.4
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• pp.281-298
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• 2015

From the complexity system theory, City is dynamic system which has evolved through evolution and adaptation in initial conditions and different situation. So people's active should involve in decision-making processes in the urban planning. And this suggests that responding to the demands of its citizens are important factors influencing the process of urban planning. The implications of this study are following: using big data helps people understand current social phenomena. Specifically, it figured out latent needs of citizens that traditional survey methods could not before. we can make the most of new opportunities given by digital data and prevent potential dangers in advance. They are complementary and do not replace one another.

• Journal of the Korea Society of Computer and Information
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• v.27 no.12
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• pp.111-119
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• 2022

The purpose of this paper is to examine the change in perception of 3D virtual fashion before and after COVID-19 using big data analysis. The data collection period is from January 1, 2017, before the outbreak of COVID-19, to October 30, 2022, after the outbreak. Big data was collected for key words related to 3D virtual fashion extracted from social media such as Naver, Daum, Google, and YouTube using Textom. After the collected words were refined, word cloud, word frequency, connection centrality, network visualization, and CONCOR analysis were performed. As a result of extracting and analyzing 32,461 words with 3D virtual fashion as a keyword, the frequency and centrality of fashion, virtual, and technology appeared the highest, and the frequency of appearance of digital, design, clothing, utilization, and manufacturing was also high. Through this, it was found that 3D virtual fashion is being used throughout the industry along with the development of technology. In particular, the key words that stand out the most after COVID-19 are metaverse and 3D education, which are in high demand in the fashion industry.