• Journal of Korean Library and Information Science Society
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• v.40 no.1
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• pp.471-492
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• 2009

Inquiry instruction is a dynamic process that uses questioning and answering to have students actively participate in their own learning. Inquiry instruction is a teaching technique in which teachers do not provide knowledge, but help students discover knowledge by themselves. However, Inquiry instruction currently has problems of lack of connection between inquiry process and school library, lack of collaboration between the media specialist and teacher, and lack of applicable models. Information literacy is the ability to access, evaluate and use information. Information literacy process is closely related to the inquiry process. Thus, this study suggested an elaborative model in inquiry instruction using information literacy process. This research derived the skills, strategies, activities of inquiry instruction model by comparing and analyzing Lippitt's inquiry process with information literacy process(Big6 Skills, Pathways to Knowledge, I-Search, 8Ws, Inquiry Process, Inquiry in the Research Process). Based on the results, this study designed an elaborative model in inquiry instruction using information literacy process.

• Journal of the Korea Convergence Society
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• v.11 no.9
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• pp.21-29
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• 2020

The Topic Modeling research, the methodology for deduction keyword within literature, has become active with the explosion of data from digital society transition. The research objective is to investigate research trends in D.N.A.(Data, Network, Artificial Intelligence) field using DTM(Dynamic Topic Model). DTM model was applied to the 1,519 of research projects with SW·A.I technology classifications among ICT(Information and Communication Technology) field projects between 6 years(2015~2020). As a result, technology keyword for D.N.A. field; Big data, Cloud, Artificial Intelligence, extended keyword; Unstructured, Edge Computing, Learning, Recognition was appeared every year, and accordingly that the above technology is being researched inclusively from other projects can be inferred. Finally, it is expected that the result from this paper become useful for future policy·R&D planning and corporation's technology·marketing strategy.

• Journal of Information Processing Systems
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• v.15 no.6
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• pp.1306-1325
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• 2019

As the world is moving towards digitization, data is generated from various sources at a faster rate. It is getting humungous and is termed as big data. The financial sector is one domain which needs to leverage the big data being generated to identify financial risks, fraudulent activities, and so on. The design of predictive models for such financial big data is imperative for maintaining the health of the country's economics. Financial data has many features such as transaction history, repayment data, purchase data, investment data, and so on. The main problem in predictive algorithm is finding the right subset of representative features from which the predictive model can be constructed for a particular task. This paper proposes a correlation-based method using submodular optimization for selecting the optimum number of features and thereby, reducing the dimensions of the data for faster and better prediction. The important proposition is that the optimal feature subset should contain features having high correlation with the class label, but should not correlate with each other in the subset. Experiments are conducted to understand the effect of the various subsets on different classification algorithms for loan data. The IBM Bluemix BigData platform is used for experimentation along with the Spark notebook. The results indicate that the proposed approach achieves considerable accuracy with optimal subsets in significantly less execution time. The algorithm is also compared with the existing feature selection and extraction algorithms.

• Mycobiology
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• v.49 no.6
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• pp.582-588
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• 2021

The interaction of mating pheromone and pheromone receptor from the B mating-type locus is the first step in the activation of the mushroom mating signal transduction pathway. The B mating-type locus of Lentinula edodes is composed of Bα and Bβ subloci, each of which contains genes for mating pheromone and pheromone receptor. Allelic variations in both subloci generate multiple B mating-types through which L. edodes maintains genetic diversity. In addition to the B mating-type locus, our genomic sequence analysis revealed the presence of a novel chromosomal locus 43.3 kb away from the B mating-type locus, containing genes for a pair of mating pheromones (PHBN1 and PHBN2) and a pheromone receptor (RCBN). The new locus (Bα-N) was homologous to the Bα sublocus, but unlike the multiallelic Bα sublocus, it was highly conserved across the wild and cultivated strains. The interactions of RcbN with various mating pheromones from the B and Bα-N mating-type loci were investigated using yeast model that replaced endogenous yeast mating pheromone receptor STE2 with RCBN. The yeast mating signal transduction pathway was only activated in the presence of PHBN1 or PHBN2 in the RcbN producing yeast, indicating that RcbN interacts with self-pheromones (PHBN1 and PHBN2), not with pheromones from the B mating-type locus. The biological function of the Bα-N locus was suggested to control the expression of A mating-type genes, as evidenced by the increased expression of two A-genes HD1 and HD2 upon the treatment of synthetic PHBN1 and PHBN2 peptides to the monokaryotic strain of L. edodes.

• Journal of the Korean Data and Information Science Society
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• v.26 no.6
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• pp.1259-1269
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• 2015

Recently, big data is positioning as a keyword in the academic circles. And usefulness of big data is carried into government, a local public body and enterprise as well as academic circles. Also they are endeavoring to obtain useful information in big data. This research mainly deals with analyses of box office success or failure of films using text mining. For data, it used a portal site 'D' and film review data, grade point average and the number of screens gained from the Korean Film Commission. The purpose of this paper is to propose a model to predict whether a film is success or not using these data. As a result of analysis, the correct classification rate by the prediction model method proposed in this paper is obtained 95.74%.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.6
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• pp.157-167
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• 2023

The use of big data for transportation often involves using data that includes personal information, such as the driver's driving routes and coordinates. This study explores the creation of a route choice prediction model using a large dataset from mobile navigation apps using federated learning. This privacy-focused method used distributed computing and individual device usage. This study established preprocessing and analysis methods for driver data that can be used in route choice modeling and compared the performance and characteristics of widely used learning methods with federated learning methods. The performance of the model through federated learning did not show significantly superior results compared to previous models, but there was no substantial difference in the prediction accuracy. In conclusion, federated learning-based prediction models can be utilized appropriately in areas sensitive to privacy without requiring relatively high predictive accuracy, such as a driver's preferred route choice.

• Korean Journal of Artificial Intelligence
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• v.6 no.1
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• pp.16-20
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• 2018

The development of modern information technology has increased the amount of big data about patients' information and diseases. In this study, we developed a prediction model of diabetes using the health examination data provided by the public data portal in 2016. In addition, we graphically visualized diabetes incidence by sex, age, residence area, and income level. As a result, the incidence of diabetes was different in each residence area and income level, and the probability of accurately predicting male and female was about 65%. In addition, it can be confirmed that the influence of X on male and Y on female is highly to affect diabetes. This predictive model can be used to predict the high-risk patients and low-risk patients of diabetes and to alarm the serious patients, thereby dramatically improving the re-admission rate. Ultimately it will be possible to contribute to improve public health and reduce chronic disease management cost by continuous target selection and management.

• Computers and Concrete
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• v.24 no.6
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• pp.571-578
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• 2019

This study aimed to investigate the permeable nature of pervious concretes (PC) through the moving particle simulation (MPS) method. In the simulation, the complex structure of a pervious concrete was virtually demonstrated as a lattice model (LM) of spherical beads, where the test of permeability was conducted. Results of the simulation were compared with the experimental ones for validation. As a result, MPS results showed the permeability index of the LM as almost twice as big as the actual PCs. A proposed virtual model was created to prevent the stuck of water flow in the MPS simulation of PC or LM. Successful simulation results were demonstrated with the model.

• The Bulletin of The Korean Astronomical Society
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• v.37 no.2
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• pp.111.2-111.2
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• 2012

We observed an Ellerman bomb(EB) and its associated surge using the Fast Imaging Solar Spectrograph(FISS) and the broadband TiO filter of the 1.6 meter New Solar Telescope at Big Bear Solar Observatory. As is well-known, the EB appears as a feature that is very bright at the far wings of the H alpha line. The lambdameter method applied to these wings indicates that the EB is blue-shifted up to 6km/s in velocity. In the photospheric level below the EB, we see rapidly growing "granule-like" feature. The transverse velocity of the dark lane at the edge of the "granule" increased with time as reached a peak of 6km/s, at the time of the EB's occurrence. The surge was seen in absorption and varied rapidly both in the H alpha and the Ca II 8542 line. It originated from the Ellerman bomb, and was impulsively accelerated to 20km/s toward us(blueshift). Then the velocity of the surge gradually changed from blueshift of 20km/s to redshift of 40km/s. By adopting the cloud model, we estimated the temperature of the surge material at about 27000K and the non-thermal velocity at about 10km/s. Our results shed light on the conventional idea that an EB results from the magnetic reconnection of an emerging flux tube and pre-existing field line.

• Smart Media Journal
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• v.6 no.4
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• pp.88-93
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• 2017

The story of "A Tale of the Conquest over a Big Enemy from an Underground Nation" is a story that is distributed all over the world. This familiar narrative structure can be accepted without great objection even in places with different cultures. In case of storytelling with the elements extracted from the narrative according to the previous research, storytelling of the picture book was carried out using the element and structure of the narrative. One of the ways to content the story is called a re-writing. In this paper, we divided the components of picture book into literary subjects, plots, characters, and backgrounds. "A Tale of the Conquest over a Big Enemy from an Underground Nation" is analyzed in the same way. And presented storytelling of the picture book.