• Journal of The Korean Association For Science Education
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• v.33 no.5
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• pp.1041-1054
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• 2013

Big ideas are overarching principles that help students to build a holistic understanding of domain-specific knowledge and assimilate individual facts and theories. This study aims to design a standard-based integrated science curriculum framework based on Big Ideas. The core contents were extracted by analysing the 2009 National Science Standards curriculum of primary and middle schools. Four Big Ideas, 'diversity,' 'structure,' 'interaction,' and 'change,' were generated after the process of examination and categorization of core contents. The scientific facts, disciplinary concepts, and interdisciplinary concepts of every scientific domains included in each Big Idea are represented as a knowledge pyramid. Essential questions guiding the direction of curriculum design were proposed on each Big idea. Based on the framework, teaching modules for 'structure' were developed for grades 5~6.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2005.10a
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• pp.305-311
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• 2005

The die development of the high-strength steel sheet has big difference on the formability compared with the general panels. Especially, the springback after stamping of the high-strength steel sheets shows big problem. In this study, for the die development of the high-strength steel sheets, write about examples reducing the lead time and the expense of the die development after CAD modification with the result of the springback analysis after finding the best design planning as several times stamping analysis.

• Proceedings of the KOR-KST Conference
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• 1998.09a
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• pp.45-51
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• 1998

This paper is based on the science and technology development plan of Chinese railways, it has briefly described the big breakthrough achieved during the 'Ninth Five Year Plan' and has presented the outstanding symbol of science and technology level of Chinese railways by the year of 2000.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.196-203
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• 2020

In this study, we tried to explore the actual direction for the play culture by looking at the social perception of the change of play culture due to the Corona 19 using big data analysis. For this research, we used Textom, a website specializing in collecting big data, and collected 10,216 data using keywords of "Corona + Play," "Play Culture" and "Leisure" from January 19, 2020 to September 30, 2020, when the first confirmed case of Corona 19 occurred in Korea on various portal sites at home and abroad. The results of this paper showed that the social perception of the play culture in Corona 19 was 51.61%, not much different from the negative image of 48.15%. It is necessary to develop a play culture program that can identify people's various desires and emotions under the premise that situations similar to the current With Corona period and Corona19 can occur at any time, and find mental and physical stability and vitality in unstable situations. In addition, the results of this study can be used as basic data for the development of play culture policies or programs, with the significance that this study helped vitalize big data utilization research in the fields of play, leisure, and culture.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.6
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• pp.225-230
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• 2016

Recently, Web has arisen large amount of data that to the development of the network and the Internet. In order to process it appeared that Big Data technology. Big Data technologies have been studied aiming a multifaceted and accurate analysis using existing regular data and a variety of data social data. But social data does not have the expertise and objectivity. And such manipulation and concealment and distortion of information have been raised troubling. Thus, this paper proposes for trust big data platform and will be described in detail. The big data platform proposed in this paper consists of data refiner, Data Analyzer, co-truster, visualizer, searcher, etc.

• Fashion & Textile Research Journal
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• v.22 no.5
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• pp.639-649
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• 2020

This study investigates consumer opinions of clothing care and provides fundamental data to decision-making for oncoming development of clothing care system. Textom, a web-matrix program, was used to analyze big data collected from Naver and Daum with a keyword of "clothing care" from March 2019 to February 2020. A total of 22, 187 texts were shown from the big data collection. Collected big data were analyzed using text-mining, network, and CONCOR analysis. The results of this study were as follows. First, many keywords related to clothing care were shown from the result of frequency analysis such as style, Dryer, LG Electronics, Product, Customer, Clothing, and Styler. Consumers were well recognizing and having an interest in recent information related to the clothing care system. Second, various keywords such as product, function, brand, and performance, were linked to each other which were fundamentally related to the clothing care. The interest in products of the clothing care system were linked to product brands that were also naturally linked to consumer interest. Third, the keywords in the network showed similar attributes from the result of CONCOR analysis that were classified into 4 groups such as the characteristics of purchase, product, performance, and interest. Lastly, positive emotions including goodwill, interest, and joy on the clothing care system were strongly expressed from the result of the sentimental analysis.

• International Journal of Contents
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• v.15 no.4
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• pp.113-119
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• 2019

It has been reported that large amounts of information on agri-foods were delivered to consumers through television and social networks, and the information may influence consumers' behavior. The purpose of this paper was first to analyze relations of social network service and broadcasting program on paprika consumption in the aspect of amounts to purchase and identify potential factors that can promote paprika consumption; second, to develop prediction models of paprika consumption by using structured and unstructured big data. By using data 2010-2017, cross-correlation and time-series prediction algorithms (autoregressive exogenous model and vector error correction model), statistically significant correlations between paprika consumption and television programs/shows and blogs mentioning paprika and diet were identified with lagged times. When paprika and diet related data were added for prediction, these data improved the model predictability. This is the first report to predict paprika consumption by using structured and unstructured data.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.202-204
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• 2013

Nowadays, owing to the development of hardware, most of enterprises should operate and manage bigger amount of data than they used to do in the past. For this reason, the enterprises ceaselessly and urgently need systemized tools, platforms, and analysis methodologies in order to collect, store, and handle explosively increasing data. In this paper, we firstly understand key elements of Big Data, and secondly define critical factors for Big Data application with these elements. Thirdly, we research on various analysis techniques for Big Data analysis. Lastly, we propose an infrastructure to analyze bid data.

• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1516-1529
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• 2016

While global manufacturing is becoming more competitive due to variety of customer demand, increase in production cost and uncertainty in resource availability, the future ability of manufacturing industries depends upon the implementation of Smart Factory. With the convergence of new information and communication technology, Smart Factory enables manufacturers to respond quickly to customer demand and minimize resource usage while maximizing productivity performance. This paper presents the development of a big data analytics platform architecture for Smart Factory. As this platform represents a conceptual software structure needed to implement data-driven decision-making mechanism in shop floors, it enables the creation and use of diagnosis, prediction and optimization models through the use of data analytics and big data. The completion of implementing the platform will help manufacturers: 1) acquire an advanced technology towards manufacturing intelligence, 2) implement a cost-effective analytics environment through the use of standardized data interfaces and open-source solutions, 3) obtain a technical reference for time-efficiently implementing an analytics modeling environment, and 4) eventually improve productivity performance in manufacturing systems. This paper also presents a technical architecture for big data infrastructure, which we are implementing, and a case study to demonstrate energy-predictive analytics in a machine tool system.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.6
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• pp.567-580
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• 2016

In recent years, our society, because of the arrival of a new paradigm according to the rapid changes in ICT has entered into future smart society and the ubiquitous era. So it can be a notable turning point in the marine disaster prevention system with big data, aspects of the era change. Therefore, this study was to derive a desirable vision for the big data marine disaster prevention informatization in terms of ICT maritime disaster prevention system development as preparedness for the maritime disaster by applying 'scenario planning' as a foresight method. Soon this study derived a successful marine disaster prevention informatization strategy as preparedness for the maritime disaster like Ferry Sewol Disaster. It proposed the big data marine disaster prevention informatization system with the use of the administrative aspects of information with spatial informatization as big data information. Also this study explored the future leadership strategy of the big data marine disaster prevention informatization in smart society. Eventually in 2030 to around, In order to still remain our marine disaster prevention informatization as a leading ICT nation, this study suggested the following strategy. It is important to ready the advanced Big Data administrative spatial informatization system In terms of prevention of incidents like Ferry Sewol Disaster.