• Journal of Korean Library and Information Science Society
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• v.49 no.3
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• pp.331-359
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• 2018

The purpose of this study is to analyse the Big6 model and the Big6 modification model to find out the characteristics of the Big6 model and to derive implications for applying the Big6 model in the field. For this purpose, the information literacy standards of the AASL and the ACRL were compared with the Big6 model. The Big6 model, influenced by Bloom's taxonomy was analyzed alongside the Big6+3 model, the Big8 model and the modified Big6 model, provided by LG Science Land. As a result, the Big6 model could be used as an information problem-solving model, metacognitive activation strategy, and scaffolding to improve students' information literacy. In addition, it could be used as a model for constructivism, inquiry-based learning, the integration of curriculum, collaborative education, and ICT technology. How teacher-librarians or librarians apply the Big6 model is related to the improvement of critical thinking skills. Teacher-librarians and librarians need to plan situations, subjects, topics, and methods in a systematic and specific way when applying the Big6 model to the information literacy curriculum.

• Journal of the Korean Society for information Management
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• v.17 no.4
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• pp.7-26
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• 2000

This study is an attempt to analyze the individual merit of the INSTRAT model, which forms a cognitive process paradigm, and that of the Big6 model, which involves a functional approach, as tools for enhancing human information activities and aptitude. The former was examined through logical interpretations, while the latter was deduced from interviews using the Micro-Moment Time-Line method, a key methodology used in the Sense-Making Approaches. Results indicate that the application of the INSTRAT model is suitable for developing information systems that can assist users in the stage of defining information needs and search strategies, and that the application of the Big6 model is appropriate in information literacy education or information aptitude training. Of particular significance is the fact that the study proves for the first time that human information problem-solving behavior indeed follows the process delineated in the Big6 model.

• Journal of Korean Port Research
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• v.13 no.1
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• pp.101-112
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• 1999

Traffic accidents increase with the increase of the vehicles in operation on the street. Especially big traffic accidents composed of over 3 killed or 20 injured accidents with the property damage become one of the serious problems to be solved in most of the cities. The purpose of this study is to build the discrimination model on big traffic accidents using the Quantification II theory for establishing the countermeasures to reduce the big traffic accidents. The results are summarized as follows. 1)The existing traffic accident related model could not explain the phenomena of the current traffic accident appropriately. 2) Based on the big traffic accident types vehicle-vehicle, vehicle-alone, vehicle-pedestrian and vehicle-train accident rates 73%, 20.5% 5.6% and two cases respectively. Based on the law violation types safety driving non-fulfillment center line invasion excess speed and signal disobedience were 48.8%, 38.1% 2.8% and 2.8% respectively. 3) Based on the law violation types major factors in big traffic accidents were road and environment, human, and vehicle in order. Those factors were vehicle, road and environment, and human in order based on types of injured driver’s death. 4) Based on the law violation types total hitting and correlation rates of the model were 53.57% and 0.97853. Based on the types of injured driver’s death total hitting and correlation rates of the model were also 71.4% and 0.59583.

• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.2
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• pp.141-152
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• 2015

Our agriculture and rural villages have faced negative conditions in many reasons. To overcome this situation, a new change is needed by the 6th industrialization. Many agriculture and rural villages in Korea are pursuing the 6th industrialization through the convergence of the primary, secondary, and tertiary industries to vitalize agriculture and rural villages. But there are several problems with the 6th industrialization. There is a limit to the capacity building of the members of the rural organization and Korean agricultural base primary, secondary, and tertiary industries are weak all. In addition, it has been insufficient research for value chain management of the region as a whole; there has been no study of information sharing across the region for the 6th industrialization. This study is about value chain management model for successful the 6th industry with Quick Response System and the big data technology. In this study to provide the efficiency of 6th industry value chain management with customer's needs analysis using big data and research for the information share between the industries in the region through the information pipeline theory of the QR System. We hope that our study is helped to proceed successfully on the 6th industrialization in Korea.

• Journal of Korean Society of Archives and Records Management
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• v.15 no.1
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• pp.127-155
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• 2015

This study proposes the formation of education service models using presidential archives based on ubiquitous technology. To accomplish these, this study analyzed various education programs of presidential archives in Korea and other countries. The reason behind the use of ubiquitous technology is to allow interinstitution cooperation and create synergy effects. With this, this technology is grafted onto the modified BIG6 Model, which is developed for information literacy. This study can be useful and valuable in the aspects of education, contents development, and service development.

• Journal of Information Processing Systems
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• v.14 no.6
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• pp.1301-1306
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• 2018

Artificial intelligence is one of the key technologies of the Fourth Industrial Revolution. This paper introduces the diverse kinds of approaches to subjects that tackle diverse kinds of research fields such as model-based MS approach, deep neural network model, image edge detection approach, cross-layer optimization model, LSSVM approach, screen design approach, CPU-GPU hybrid approach and so on. The research on Superintelligence and superconnection for IoT and big data is also described such as 'superintelligence-based systems and infrastructures', 'superconnection-based IoT and big data systems', 'analysis of IoT-based data and big data', 'infrastructure design for IoT and big data', 'artificial intelligence applications', and 'superconnection-based IoT devices'.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.6
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• pp.15-23
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• 2020

While research activities in the agricultural field for climate change are being actively carried out, smart agriculture using information and communication technology has become a new trend in line with the Fourth Industrial Revolution. Accordingly, research is being conducted to identify and respond to signs of abnormal growth in advance by monitoring the stress of crops in various outdoor environments and soil conditions. There are also attempts to analyze data collected in real time through various sensors using artificial intelligence techniques or big data technologies. In this paper, we propose a big data model that is effective in analyzing the growth environment informations and biometric information of crops by using the existing relational database for big data analysis. The performance of the model was measured by the response time to a query according to the amount of data. As a result, it was confirmed that there is a maximum time reduction effect of 23.8%.

• Journal of Electrical Engineering and Technology
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• v.10 no.6
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• pp.2384-2392
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• 2015

The technical development and practical applications of big-data for health is one hot topic under the banner of big-data. Big-data medical image fusion is one of key problems. A new fusion approach with coding based on Spherical Coordinate Domain (SCD) in Wireless Sensor Network (WSN) for big-data medical image is proposed in this paper. In this approach, the three high-frequency coefficients in wavelet domain of medical image are pre-processed. This pre-processing strategy can reduce the redundant ratio of big-data medical image. Firstly, the high-frequency coefficients are transformed to the spherical coordinate domain to reduce the correlation in the same scale. Then, a multi-scale model product (MSMP) is used to control the shrinkage function so as to make the small wavelet coefficients and some noise removed. The high-frequency parts in spherical coordinate domain are coded by improved SPIHT algorithm. Finally, based on the multi-scale edge of medical image, it can be fused and reconstructed. Experimental results indicate the novel approach is effective and very useful for transmission of big-data medical image(especially, in the wireless environment).

• Journal of Fashion Business
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• v.22 no.6
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• pp.83-93
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• 2018

The purpose of this research is to investigate the characteristics of big data-based fashion shopping (BDFS) application, perceived usefulness, and expectation confirmation that influence the continuous usage intention of BDFS application users based on the expectation-confirmation model. A survey was conducted with female consumers in their 20s, who are living in Seoul and Incheon area and have used BDFS applications, A total of 182 responses were used for the data analysis. Five hypotheses were proposed, and regression analyses were conducted to test those hypotheses. The results indicated that the users' perceived usefulness increased with the increase of accuracy and personalization characteristics of the app and the expectation confirmation. The result suggested that it is essential to provide accurate information for users to feel useful and to develop the personalized offerings and services which can be the biggest strength of the big-data based mobile fashion store. It was also found that continuous usage intention increases with increased perceived usefulness and expectation confirmation. This result suggests that expectations can play a critical role in perceiving the usefulness of BDFS applications and the user's expectation confirmation also significantly affected the users' continuous usage intention.

• Journal of the Korean Ceramic Society
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• v.56 no.6
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• pp.596-600
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• 2019

Artificial intelligence with a sufficient amount of realistic big data in certain applications has been demonstrated to play an important role in designing new materials or in manufacturing high-quality products. To reduce cracks in ceramic products using machine learning, it is desirable to utilize big data in recently developed data-driven optimization schemes. However, there is insufficient big data for ceramic processes. Therefore, we developed a numerical algorithm to make "virtual" manufacturing data sets using indirect methods such as computer simulations and image processing. In this study, a numerical algorithm based on the random walk was demonstrated to generate images of cracks by adjusting the conditions of the random walk process such as the number of steps, changes in direction, and the number of cracks.