• Therapeutic Science for Rehabilitation
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• v.9 no.3
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• pp.63-75
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• 2020

Objective : The purpose of this study was to examine the changes in work performance and motor function of stroke patients in the Lee Silverman Voice Treatment-BIG (LSVT-BIG) program and to confirm its clinical applicability. Methods : Two stroke patients underwent the LSVT-BIG program for a total of 16 sessions (60 minutes per session and, four days a week for four weeks). To assess any changes between before and after the intervention, the Canadian Occupational Performance Measurement (COPM), Berg Balance Scale (BBS), Timed Up and Go (TUG), Functional Reaching Test (FRT), Manual Function Test (MFT) were used. Differences in scores between before and after the intervention were analyzed. Results : The performance and satisfaction of occupational performance increased after the intervention in both subjects. The performance time of the TUG decreased to 0.91, 8.42 seconds for each subject, increasing the walking speed. In FRT distance change, the subject increased in both the affected side and unaffected side. The BBS score increased by 3 points in one subject and by 6 points in the other, indicating improved balance. In addition, in the MFT score, subject A showed an improvement of 1 point on the unaffected side, and subject B showed an improvement of 1 point on the unaffected side and 3 points on the affected side. Conclusion : We confirmed the applicability of the LSVT-BIG program as a new intervention technique for stroke patients. Future, complementary research on the effects of the LSVT-BIG program on stroke patients will be needed.

• Journal of Information Technology Applications and Management
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• v.24 no.4
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• pp.197-214
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• 2017

This study sheds light on the source data quality in big data systems. Previous studies about big data success have called for future research and further examination of the quality factors and the importance of source data. This study extracted the quality factors of source data from the user's viewpoint and empirically tested the effects of source data quality on the usefulness and utilization of big data analytics results. Based on the previous researches and focus group evaluation, four quality factors have been established such as accuracy, completeness, timeliness and consistency. After setting up 11 hypotheses on how the quality of the source data contributes to the usefulness, utilization, and ongoing use of the big data analytics results, e-mail survey was conducted at a level of independent department using big data in domestic firms. The results of the hypothetical review identified the characteristics and impact of the source data quality in the big data systems and drew some meaningful findings about big data characteristics.

• Journal of the Korea Society of Computer and Information
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• v.22 no.1
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• pp.49-56
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• 2017

In this paper we propose the approach for big data integration so as to analyze, visualize and predict the future of the trend of the market, and that is to get the integration data model using the R language which is the future of the statistics and the Hadoop which is a parallel processing for the data. As four approaching methods using R and Hadoop, ff package in R, R and Streaming as Hadoop utility, and Rhipe and RHadoop as R and Hadoop interface packages are used, and the strength and weakness of four methods are described and analyzed, so Rhipe and RHadoop are proposed as a complete set of data integration model. The integration of R, which is popular for processing statistical algorithm and Hadoop contains Distributed File System and resource management platform and can implement the MapReduce programming model gives us a new environment where in R code can be written and deployed in Hadoop without any data movement. This model allows us to predictive analysis with high performance and deep understand over the big data.

• Land and Housing Review
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• v.7 no.1
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• pp.19-29
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• 2016

This study proposes the big data policy and case studies in Korea and the application of land and housing of spatial big data to excavate the future business and to propose the spatial big data based application for the government policy in advance. As a result, at first, the policy and cases of big data in Korea were evaluated. Centered on the Government 3.0 Committee, the information from each department of government is being established with the big-data-based system, and the Ministry of Land, Infrastructure, and Transport is establishing the spatial big data system from 2013 to support application of big data through the platform of national spatial information and job creation. Second, based on the information system established and administrated by LH, the status of national territory information and the application of land and housing were evaluated. First of all, the information system is categorized mainly into the support of public ministration, statistical view, real estate information, on-line petition, and national policy support, and as a basic direction of major application, the national territory information (DB), demand of application (scope of work), and profit creation (business model) were regarded. After the settings of such basic direction, as a result of evaluating an approach in terms of work scope and work procedure, the four application fields were extracted: selection of candidate land for regional development business, administration and operation of rental house, settings of priority for land preservation, and settings of priority for urban generation. Third, to implement the application system of spatial big data in the four fields extracted, the required data and application and analytic procedures for each application field were proposed, and to implement the application solution of spatial big data, the improvement and future direction of evaluation required from LH were proposed.

• Journal of the Korea Society of Computer and Information
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• v.22 no.12
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• pp.101-108
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• 2017

The study proposed a system that filters the data that is entered when analyzing big data such as SNS and BLOG. Personal information includes impersonal personal information, but there is also personal information that distinguishes it from personal information, such as religious institution, personal feelings, thoughts, or beliefs. Define these personally identifiable information as sensitive information. In order to prevent this, Article 23 of the Privacy Act has clauses on the collection and utilization of the information. The proposed system structure is divided into two stages, including Big Data Processing Processes and Sensitive Information Filtering Processes, and Big Data processing is analyzed and applied in Big Data collection in four stages. Big Data Processing Processes include data collection and storage, vocabulary analysis and parsing and semantics. Sensitive Information Filtering Processes includes sensitive information questionnaires, establishing sensitive information DB, qualifying information, filtering sensitive information, and reliability analysis. As a result, the number of Big Data performed in the experiment was carried out at 84.13%, until 7553 of 8978 was produced to create the Ontology Generation. There is considerable significan ce to the point that Performing a sensitive information cut phase was carried out by 98%.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.3
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• pp.42-49
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• 2021

As cyber attacks become more intelligent, there is difficulty in detecting advanced attacks in various fields such as industry, defense, and medical care. IPS (Intrusion Prevention System), etc., but the need for centralized integrated management of each security system is increasing. In this paper, we collect big data for intrusion detection and build an intrusion detection platform using deep learning and CNN (Convolutional Neural Networks). In this paper, we design an intelligent big data platform that collects data by observing and analyzing user visit logs and linking with big data. We want to collect big data for intrusion detection and build an intrusion detection platform based on CNN model. In this study, we evaluated the performance of the Intrusion Detection System (IDS) using the KDD99 dataset developed by DARPA in 1998, and the actual attack categories were tested with KDD99's DoS, U2R, and R2L using four probing methods.

• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.101-107
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• 2020

This paper aims to compare and analyze the major keywords according to the political orientation of progressive and conservative newspapers by utilizing the big data of the four major domestic daily newspapers related to COVID-19, which has entered a long-term war. To this end, 93,917 news reports from Jan. 20 to Sept. 15, 2020 were divided into four stages and the major keywords of the four newspapers were implemented and analyzed in WordCloud. According to the analysis, the conservative newspaper focused on the government's response, criticism, and China's responsibility by mentioning the keywords "government," "president," "state of affairs" and "mask" more than the progressive newspaper, while the progressive newspaper uses keywords that emphasize the seriousness of the disease and the occurrence of a dangerous situation. The Chosun Ilbo found that the use of various keywords during the massive outbreak of collective infections (2.18-5.15), and that the JoongAng Ilbo used keywords criticizing government policies in relation to reports of infectious diseases such as COVID-19, but also used keywords that emphasize the seriousness of diseases used by progressive newspapers and the occurrence of dangerous situations.

• Journal of Digital Convergence
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• v.12 no.9
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• pp.169-175
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• 2014

The ICT (information and communication technology) paradigm shift, including the burgeoning use of mobile, SNS, and smart devices, has resulted in an explosion of data along with lifestyle changes. We have thus arrived at the age of big data. In the meantime, a number of difficulties have arisen in terms of cost or on the technical side with respect to the use of large quantities of data. However, big data has begun to receive attention with the advent of efficient big data technologies such as Hadoop. In this paper, we discuss the patent analysis of big data platform technology research and development in major countries. Especially, we analyzed 2,568 patent applications and registered patents in four countries on December 2010.

• Knowledge Management Research
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• v.21 no.4
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• pp.243-263
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• 2020

The purpose of this study is to propose the performance measurement model for open big data platform. In order to develop the performance measurement model, we have integrated big data reference architecture(NIST 2018) with performance prism model(Neely et al. 2001) in the platform perspective of open big data. Our proposed model consists of five key building blocks for measuring performance of open data platform as follows: stakeholder contribution, big data governance capabilities, big data service capabilities, big data IT capabilities, and stakeholder satisfaction. In addition, our proposed model have twenty four evaluation indices and seventy five measurement items. We believe that our model could offer both research and practical implications for relevant research.

• Journal of People, Plants, and Environment
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• v.22 no.5
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• pp.455-466
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• 2019

This study was carried out to analyze trends in floral products and services through the big data analysis of various social networking services (SNSs) and then to provide objective marketing directions for the floricultural industry. To analyze the big data of SNSs, we used four analytical methods: Cotton Trend (Social Matrix), Naver Big Data Lab, Instagram Big Data Analysis, and YouTube Big Data Analysis. The results of the big data analysis showed that SNS users paid positive attention to flower one-day classes that can satisfy their needs for direct experiences. Consumers of floral products and services had their favorite designs in mind and purchased floral products very actively. The demand for flower items such as bouquets, wreaths, flower baskets, large bouquets, orchids, flower boxes, wedding bouquets, and potted plants was very high, and cut flowers such as roses, tulips, and freesia were most popular as of June 1, 2019. By gender of consumers, females (68%) purchased more flower products through SNSs than males (32%). Consumers preferred mobile devices (90%) for online access compared to personal computers (PCs; 10%) and frequently searched flower-related words from February to May for the past three years from 2016 to 2018. In the aspect of design, they preferred natural style to formal style. In conclusion, future marketing activities in the floricultural industry need to be focused on social networks based on the results of big data analysis of popular SNSs. Florists need to provide consumers with the floricultural products and services that meet the trends and to blend them with their own sensitivity. It is also needed to select SNS media suitable for each gender and age group and to apply effective marketing methods to each target.