• Journal of Digital Convergence
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• v.16 no.7
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• pp.107-116
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• 2018

One of the key mission is to develop and prompte the use National Competency Standards, which is defined to be the systemization of competencies(knowledge, skills and attitudes) required to perform duties at the workplace by the nation for each industrial sector and level. This provides the basis for the design of training and detailed specifications for workplace assessment. To promote the data-driven service improvement, the commercial product Splunk was introduced, and has grown to become an extremely useful platform because it enables the users to search, collect, and organize data in a far more comprehensive, far less labor-intensive way than traditional databases. Leveraging Splunk's built-in data visualization and analytical features, HRD Korea have built custom tools to gain new insight and operational intelligence that organizations have never had before. This paper analyzes the NCS homepage. Concretely, applying Splunk in creating visualizations, dashboards and performing various functional and statistical analysis and structure without Web development skills. We presented practical use and implications through case studies.

• Journal of Cadastre & Land InformatiX
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• v.49 no.2
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• pp.67-82
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• 2019

The purpose of this study is to analyze the issues and perceptions of smart cities. First, based on the big data analysis platform, big data analysis on smart cities were conducted to derive keywords by year, word cloud, and frequency of generation of smart city keywords by time. Second, trend and flow by area were analyzed by reclassifying major keywords by year based on meta-keywords. Third, emotional recognition flow for smart cities and major emotional keywords were derived. While U-City in the past is mostly centered on creating infrastructure for new towns, recent smart cities are focusing on sustainable urban construction led by citizens, according to the analysis. In addition, it was analyzed that while infrastructure, service, and technology were emphasized in the past, management and methodology were emphasized recently, and positive perception of smart cities was growing. The study could be used as basic data for the past, present and future of smart cities in Korea at a time when smart city services are being built across the country.

• Journal of Korea Entertainment Industry Association
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• v.14 no.5
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• pp.1-14
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• 2020

This study conducted a topic modeling and semantic network analysis of 'korean wave' and its meaning in Korean society from 2000 to 2019 by applying an agenda setting theory. For this purpose, a total of 197,992 newspaper articles which reported 'korean wave' issues were analyzed by applying topic modeling and semantic network analysis. As a result, first, the word 'korean wave' mainly appeared in korean-related regions in the korean press. culture and economy. second, a total of 9 topics related to korean wave issues appeared. This was followed by 'broadcast', 'export', 'domestic and foreign affairs', 'education', 'beauty and fashion', 'music and performance', 'tourism', 'media(platform)', and 'region'. Lastly, korean wave was mainly discussed at the cultural and economic ares. In addition, it was clustered into five characteristics: 'cultural hallyu', 'business hallyu', 'education', 'environment', and 'geography'.

• Knowledge Management Research
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• v.23 no.3
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• pp.285-311
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• 2022

In this study, based on the S-O-R framework, how individual's stimuli (i.e., video characteristics, YouTuber characteristics, real-time broadcasting characteristics of YouTube channel) form organisms (i.e., perceived usefulness, perceived pleasure, social presence), leading to viewers' responses (i.e., continuous watching intention, paid sponsorship intention) on real-time YouTube channels. For this purpose, a research model and hypotheses were constructed, and 369 questionnaire data collected from users of real-time broadcasting channel services on the YouTube platform were analyzed. Result findings confirmed that some video/YouTuber/real-time broadcasting characteristics significantly affect viewers' perceived usefulness/perceived pleasure/social presence, and further influence continuous watching/paid sponsorship intentions. Theoretical and practical implications of the findings are discussed in conclusion.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.1-10
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• 2021

This paper aimed to look at the awareness of foreign workers in social platforms by using text mining, one of the big data techniques and draw suggestions for foreign workers. To achieve this purpose, data collection was conducted with search keyword 'Foreign Worker' from Jan. 1, to Dec. 31, 2020, and frequency analysis, TF-IDF analysis, and degree centrality analysis and 100 parent keywords were drawn for comparison. Furthermore, Ucinet6.0 and Netdraw were used to analyze semantic networks, and through CONCOR analysis, data were clustered into the following eight groups: foreigner policy issue, regional community issue, business owner's perspective issue, employment issue, working environment issue, legal issue, immigration issue, and human rights issue. Based on such analyzed results, it identified national awareness of foreign workers and main issues and provided the basic data on policy proposals for foreign workers and related researches.

• Informatization Policy
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• v.30 no.4
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• pp.89-112
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• 2023

Traffic safety policies have been established and carried out every five years according to the Traffic Safety Act. In addition to policies that are planned and carried out in the long run, there are also policies established to prevent the recurrence of various social issues and accidents. Citizens' participation in administrative affairs has recently seized the spotlight, and has become an efficient means of realizing administrative democracy. Based on big data analysis, this study aims to present how the "Kim Min-sik Case," which recently brought to the fore a social issue of strengthening laws on child school zones, has realized administrative democracy and contributed to legislation due to the emergence of the online platform called "national petition." Policy changes according to the cycle of issues are divided according to time series classification and what contents are devised in each section through text mining analysis. In this regard, the results of this study are expected to provide useful theoretical and practical implications for researchers and policymakers by presenting policy implications that it is important to prepare practical and realistic alternatives in solving policy problems.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.10
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• pp.239-246
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• 2020

In the medical field where artificial intelligence technology is introduced, research related to clinical decision support system(CDSS) in relation to diagnosis and prediction is actively being conducted. In particular, medical imaging-based disease diagnosis area applied AI technologies at various products. However, medical imaging data consists of inconsistent data, and it is a reality that it takes considerable time to prepare and use it for research. This paper describes a one-stop AI learning platform for converting to medical image standard R_CDM(Radiology Common Data Model) and supporting AI algorithm development research based on the dataset. To this, the focus is on linking with the existing CDM(common data model) and model the system, including the schema of the medical imaging standard model and report information for multi-center research based on DICOM(Digital Imaging and Communications in Medicine) tag information. And also, we show the execution results based on generated datasets through the AI learning platform. As a proposed platform, it is expected to be used for various image-based artificial intelligence researches.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.5
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• pp.851-858
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• 2021

Due to the increase in renewable energy and distributed resources, not only traditional data but also various energy-related data are being generated in the new energy industry. In other words, there are various renewable energy facilities and power generation data, system operation data, metering and rate-related data, as well as weather and energy efficiency data necessary for new services and analysis. Energy big data processing technology can systematically analyze and diagnose data generated in the first half of the power production and consumption infrastructure, including distributed resources, systems, and AMI. Through this, it will be a technology that supports the creation of new businesses in convergence between the ICT industry and the energy industry. To this end, research on the data analysis system, such as itemized characteristic analysis of the collected data, correlation sampling, categorization of each feature, and element definition, is needed. In addition, research on data purification technology for data loss and abnormal state processing should be conducted. In addition, it is necessary to develop and structure NIFI, Spark, and HDFS systems so that energy data can be stored and managed in real time. In this study, the overall energy data processing technology and system for various power transactions as described above were proposed.

• Journal of Digital Contents Society
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• v.19 no.6
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• pp.1207-1212
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• 2018

The ultrasound image uses ultrasonic pulses to receive the reflected waves and construct an image necessary for diagnosis. At this time, when the signal becomes weak, noise is generated and a slight difference in brightness occurs. In addition, fluctuation of image due to breathing phenomenon, which is the characteristic of ultrasound image, and change of motion in real time occurs. Such a noise is difficult to recognize and diagnose visually in the analysis process. In this paper, morphological features are automatically extracted by using image processing technique on ultrasound acquired images. In this paper, we implemented a GPU - based fast filter using a cloud big data processing platform for image processing. In applying the GPU - based high - performance filter, the algorithm was run with performance 4.7 times faster than CPU - based and the PSNR was 37.2dB, which is very similar to the original.

• Spatial Information Research
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• v.22 no.5
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• pp.1-8
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• 2014

Globally, mobile, cloud computing or big data are the recent marketable key terms. These trend technologies or paradigm in the ICT (Information Communication Technology) fields exert large influence on the most application fields including geo-spatial applications. Among them, cloud computing, though the early stage in Korea now, plays a important role as a platform for other trend technologies uses. Especially, mobile cloud, an integrated platform with mobile device and cloud computing can be considered as a good solution to overcome well known limitations of mobile applications and to provide more information processing functionalities to mobile users. This work is a case study to design and implement the mobile application system for geo-spatial image filtering processing operated on mobile cloud platform built using OpenStack and various open sources. Filtering processing is carried out using R environment, recently being recognized as one of big data analysis technologies. This approach is expected to be an element linking geo-spatial information for new service model development and the geo-spatial analysis service development using R.