• The Journal of Bigdata
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• v.1 no.2
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• pp.91-102
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• 2016

In traditional environments we have called the data life cycle DIKW, which represents data-information-knowledge-wisdom. In big data environments, on the other hand, we call it DIA, which represents data-insight-action. The difference between the two data life cycles results in new architecture of data resource management. In this paper, we study data resource management architecture for big data environments. Especially main components of the architecture are proposed in this paper.

• Journal of the Korean Society for information Management
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• v.37 no.3
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• pp.25-50
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• 2020

Since big data platform services for the public library began January 1, 2016, libraries have used big data to improve their work performance. This paper aims to examine the use cases of library big data and attempts to draw improvement plan to improve the effectiveness of library big data. For this purpose, first, we examine big data used while utilizing the library big data platform, the usage pattern of big data and services/policies drawn by big data analysis. Next, the limitations and advantages of the library big data platform are examined by comparing the data analysis of the integrated library management system (ILUS) currently used in public libraries and data analysis through the library big data platform. As a result of case analysis, big data usage patterns were found program planning and execution, collection, collection, and other types, and services/policies were summarized as customizing bookshelf themes for the book curation and reading promotion program, increasing collection utilization, and building a collection based on special topics. and disclosure of loan status data. As a result of the comparative analysis, ILUS is specialized in statistical analysis of library collection unit, and the big data platform enables selective and flexible analysis according to various attributes (age, gender, region, time of loan, etc.) reducing analysis time. Finally, the limitations revealed in case analysis and comparative analysis are summarized and suggestions for improvement are presented.

• Journal of Digital Convergence
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• v.11 no.11
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• pp.143-153
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• 2013

Big data is expected to bring forth enormous public good as well as economic opportunity. However there is ongoing concern about privacy not only from public authorities but also from private enterprises. Big data is suspected to aggravate the existing privacy battle ground by introducing new types of privacy risks such as privacy risk of behavioral pattern. On the other hand, big data is asserted to become a new way to by-pass tradition behavioral tracking such as cookies, DPIs, finger printing${\cdots}$ and etc. For it is not based on a targeted person. This paper is to find out if big data could contribute to catching out behavioral patterns of consumers without threatening or damaging their privacy. The difference between traditional behavioral tracking and big data analysis from the perspective of privacy will be discerned.

• 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 the Korean Society of Costume
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• v.57 no.6 s.115
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• pp.87-100
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• 2007

In the Joseon Dynasty, a Court Ladies' full dress was Slanted by the Ming Dynasty. Since the Ming Dynasty had declined, a Court Ladies' full dress, Jeok-ui began to be made by the Joseon Dynasty. It was based on the Chinese Court Ladies' full dress, Desam, but it became Joseon's own style, which was different from the Chinese one. The formula of Jeok-ui was completed in the time of King Yongjo. Since then, Jeok-ui for big ceremonies was called Bub-bok. It was recorded on the Regular rule of Sang-uiwon. The color of Jeok-ui was departmentalized for the wearer; red one for the Queen, bluish black one for the Crown Princess, and purple one for the Queen mother. There were some differences between Jeok-ui for feasts and for big ceremonies. In the case of Jeok-ui for big ceremonies, the pattern of Hyung-bae for the Queen was a dragon with five claws, and for the Crown Princess, a dragon with four claws. On the other hand, in the case of Jeok-ui for feasts, the pattern of Hyung-bae was phoenixes for the Queen, Crown Princess and the Queen mother. The number of embroidered round badges, which were attached to Jeok-ui, was 51 for big ceremonies, and 36 for feasts. The skirt for big ceremonies was a Jeonang-ut-chima with dragons pattern for the Queen, and phoenixes for the Crown Princess. The Queen's skirt for feasts was a Jeonang-ut-chima with phoenixes pattern, and the Queen mother's also. The Crown Princess' was a double skirt with phoenixes pattern. The pearls were not decorated on the shoes for big ceremonies, but shoes for feasts had six big pearls fer decoration. When the royal woman wore Jeok-ui for big ceremonies, it was prepared for Kyu, Pe-ok and belt with jade. But those were not necessary for Jeok-ui for feasts.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.406-412
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• 2022

Storing large amounts of data has always been a big problem from the beginning of computing history. Big Data has made huge advancements in improving business processes by finding the customers' needs using prediction models based on web and social media search. The main purpose of big data stream processing frameworks is to allow programmers to directly query the continuous stream without dealing with the lower-level mechanisms. In other words, programmers write the code to process streams using these runtime libraries (also called Stream Processing Engines). This is achieved by taking large volumes of data and analyzing them using Big Data frameworks. Streaming platforms are an emerging technology that deals with continuous streams of data. There are several streaming platforms of Big Data freely available on the Internet. However, selecting the most appropriate one is not easy for programmers. In this paper, we present a detailed description of two of the state-of-the-art and most popular streaming frameworks: Apache Ignite and Hazelcast. In addition, the performance of these frameworks is compared using selected attributes. Different types of databases are used in common to store the data. To process the data in real-time continuously, data streaming technologies are developed. With the development of today's large-scale distributed applications handling tons of data, these databases are not viable. Consequently, Big Data is introduced to store, process, and analyze data at a fast speed and also to deal with big users and data growth day by day.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.2
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• pp.207-215
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• 2016

The demand for spatial data service technologies is increasing lately with the development of realistic 3D spatial information services and ICT (Information and Communication Technology). Research is being conducted on the real-time provision of spatial data services through a variety of mobile and Web-based contents. Big data or cloud computing can be presented as alternatives to the construction of spatial data for the effective use of large volumes of data. In this paper, the process of building HLM (Hyper Live Map) using multi-source data to acquire stereo CCTV and other various data is presented and a big data service architecture design is proposed for the use of flexible and scalable cloud computing to handle big data created by users through such media as social network services and black boxes. The provision of spatial data services in real time using big data and cloud computing will enable us to implement navigation systems, vehicle augmented reality, real-time 3D spatial information, and single picture based positioning above the single GPS level using low-cost image-based position recognition technology in the future. Furthermore, Big Data and Cloud Computing are also used for data collection and provision in U-City and Smart-City environment as well, and the big data service architecture will provide users with information in real time.

• Journal of Digital Convergence
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• v.15 no.9
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• pp.167-178
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• 2017

Big Data is a key asset for the company and a key factor in boosting its competitiveness in the logistics sector. However, there is still a lack of research on how to collect, analyze and utilize Big Data in logistics. In this context, this study has developed a value model applicable to logistics companies based on the results of analysis and application of Big Data in the logistics of previous studies and DHL. The purpose of this study is to improve the operational efficiency and customer experience maximization level of logistics companies through utilization of big data analysis in logistics, to improve competitiveness of big data utilization and to develop new business opportunities. This study has a significance to newly create a value model for utilization of big data analysis in logistics sector and can provide implications for other industries as well as logistics sector in the future.

• Journal of Trauma and Injury
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• v.32 no.3
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• pp.187-193
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• 2019

Many techniques have been developed for reconstruction of the hand; however, less attention has been paid to foot reconstruction techniques. In particular, reconstruction of the forefoot and big toe has been considered a minor procedure despite the importance of these body parts for standing and walking. Most of the weight load on the foot is concentrated on the forefoot and big toe, whereas the other toes have a minor role in weight bearing. Moreover, the forefoot and big toe are important for maintaining balance and supporting the body when changing directions. Recently, attention has been focused on the aesthetic appearance and functional aspects of the body, which are important considerations in the field of reconstructive surgery. In patients for whom flap reconstruction in the forefoot and big toe is planned, clinicians should pay close attention to flap survival as well as functional and cosmetic outcomes of surgery. In particular, it is important to assess the ability of the flap to withstand functional weight bearing and maintain sufficient durability under shearing force. Recovery of protective sensation in the forefoot area can reduce the risk of flap loss and promote rapid rehabilitation and functional recovery. Here, we report our experience with two cases of successful reconstruction of the forefoot and big toe with a sensate anterolateral thigh flap, with a review of the relevant literature.

• East Asian Journal of Business Economics (EAJBE)
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• v.10 no.2
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• pp.105-113
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• 2022

Purpose - An increase in automation has been as a result of digital technologies. The data will be instrumental in the determination of the services that are more necessary so that more resources can be allocated for them. The purpose of the current research is to investigate how big data utilization will help increase the profitability in the industry 4.0 era. Research design, Data, and methodology - The present research has conducted the comprehensive literature content analysis. Quantitative approaches allow respondents to decide, but qualitative methods allow them to offer more information. In the next step, respondents are given data collection equipment, and information is collected. Result - The According to qualitative literature analysis, there are five ways in which big data utilization will help increase the profitability in the industry 4.0 era. The five solutions are (1) Better Customer Insight, (2) Increased Market Intelligence, (3) Smarter Recommendations and Audience Targeting, (4) Data-driven innovation, (5) Improved Business Operations. Conclusion - Modern companies have been seeking a competitive advantage so that they can have the edge over other companies in the same industries providing the same services and products. Big data is that technology that businesses have always wanted for an extended period of time to revolutionize their operations, making their businesses more profitable.