• (The)Korea Educational Review
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• v.23 no.1
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• pp.231-260
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• 2017

The Fourth Industrial Revolution foreshadows radical changes in our lives. In the era of the fourth industrial revolution called the digital revolution, individualized learning based on ubiquitous learning is emphasized. The contents of learning will be centered on procedural knowledge rather than narrative knowledge, and fusion education in which boundaries between learning domains are broken down will be achieved. First of all, learners in the fourth industrial revolution era should have critical thinking and problem solving abilities. Metacognition based on self-control and cognitive flexibility is important for effective self-directed and active learning. Creativity-based collaborative activities, social vision skills, and social and emotional skills are also important competencies. Therefore, in order to provide individualized learning contents to learners in the fourth industrial revolution era, they should be transformed into learning paradigm based on personal characteristics such as learners' self-efficacy, interest, curiosity and creativity. In addition to this, evaluation forms should be diversified according to changing teaching and learning methods. In order to cultivate teachers to lead such educational innovation, it is necessary to reconsider the teaching capacity. Teachers should be able to construct creative lessons by skillfully exploiting technology in future learning environments. In addition to this, it should also have the ability to collaborate and cognitive flexibility to converge with other academic disciplines. Along with these discussions, we proposed the need for policy intervention along with changes in education.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.35 no.2
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• pp.83-91
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• 2022

Seismic design and analysis of nuclear power plant components are performed based on an decoupled model. However, this decoupled analysis has a limitation in that it generates inaccurate results compared to the coupled analysis because it cannot simulate actual phenomena such as the interaction between structures and components. Thus, this study performed seismic coupled and decoupled analysis on an existing nuclear containment structure and related components, considering the mass and natural frequency ratios. And based on these results, comparative analyses of responses of components were conducted. Consequently, the seismic coupled analysis result generally gave a smaller value than the decoupled analysis result. These results were similar to the analysis results for the simple coupled model, which was an existing study, but the difference in component responses was much more pronounced. Also, this was influenced by the installation location of the component rather than the influence of the input frequency of the input seismic motions. Finally, the difference between the decoupled and coupled seismic analysis occurred in the region where the mass ratio of the components was large, and the natural frequencies were almost similar due to the considerable dynamic interaction between the structure and the component in this realm.

• The Journal of the Convergence on Culture Technology
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• v.10 no.4
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• pp.509-516
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• 2024

We rethink human existence as a assemblage through intersectionality by comparing autopoiesis and sympoiesis systems with reference to science fiction protagonists such as Ghost in the Shell, Neuralink, Camille, a genetic hybrid, and San Ti against the background of neo-materialism. Our findings reveal that, first, radical sympoiesis is characterized by the dissolution of individuals and boundaries, and attempt to explain existence solely through heterogeneous linkage and fusion; second, by ignoring the capacity for autonomous thinking at the individual level, they are unable to fully recognize the destructive nature of hybrid co-production or to develop practical responses to it. Third, we suggest that if the very survival of humanity is threatened by heterogeneous linkage, we should pay more attention to our identity as autonomous members of a autopoietic system rather than to heterogeneous sympoietic networks and we should also pay attention to the role of individual units in stabilizing self-regulation. Through this study, we aimed to contribute to overcoming the limitations of neo-materialism by arguing that it is likely to fail to provide an adequate practical vision if it is limited to describing the hybrid connections that recur through the intersection of beings, and by urging us to define the identity of the human species from a new perspective by utilizing various SF stories that trigger the imagination of destructive interactions between beings, and to explore the autopoiesis in terms of symbiotic interactions based on a certain level of boundary and self-regulation.

• Korean Journal of Remote Sensing
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• v.36 no.5_4
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• pp.1209-1220
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• 2020

In the case of forest areas, the installation of ground control points (GCPs) and the selection of terrain features, which are one of the unmanned aerial photogrammetry work process, are limited compared to urban areas, and safety problems arise due to non-visible flight due to high forest. To compensate for this problem, the drone equipped with a real time kinematic (RTK) sensor that corrects the position of the drone in real time, and a 3D flight method that fly based on terrain information are being developed. This study suggests to present a method for investigating damage using drones in forest areas. Position accuracy evaluation was performed for three methods: 1) drone mapping through GCP measurement (normal mapping), 2) drone mapping based on topographic data (3D flight mapping), 3) drone mapping using RTK drone (RTK mapping), and all showed an accuracy within 2 cm in the horizontal and within 13 cm in the vertical position. After evaluating the position accuracy, the volume of the landslide area was calculated and the volume values were compared, and all showed similar values. Through this study, the possibility of utilizing 3D flight mapping and RTK mapping in forest areas was confirmed. In the future, it is expected that more effective damage investigations can be conducted if the three methods are appropriately used according to the conditions of area of the disaster.

• Journal of Digital Convergence
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• v.14 no.7
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• pp.339-345
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• 2016

While a game market has been growing consistently world widely, a market of arcade or video game has been detained. In this stagnation, the latest one in 2015, "Super Mario Maker" of Mario series that's been running in good for 30 years, the notable sale and growth of which are extraordinary. As for a study in customizing, a literature of game customizing and studies that are foregone were mostly handling contents about a game character. In the survey that's done in this thesis about knowledge and needs in customizinge game users have, it was shown they want to customize sides of a rule and a character. I analyzed what the main factors are in this game which uses a main concept of customizing and the reason for high profits and popularity. As a result of the analysis, four features, possibility to customize a game rule, share data among users, collaboration in marketing with NFC figure characters, offering updates with sustained and new customizing features were found out. I am certain a game customizing will be helping to meet users and be used for various industries without limit of existing character.

• Journal of KIISE
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• v.42 no.1
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• pp.54-67
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• 2015

Nowadays, studies on the fusion of Semantic Web technologies are being carried out to promote the interoperability and value of sensor data in an IoT environment. To accomplish this, the semantic translation of sensor data is essential for convergence with service domain knowledge. The existing semantic translation technique, however, involves translating from static metadata into semantic data(RDF), and cannot properly process real-time and large-scale features in an IoT environment. Therefore, in this paper, we propose a technique for translating large-scale streaming sensor data generated in an IoT environment into semantic data, using real-time and parallel processing. In this technique, we define rules for semantic translation and store them in the semantic repository. The sensor data is translated in real-time with parallel processing using these pre-defined rules and an ontology-based semantic model. To improve the performance, we use the Apache Storm, a real-time big data analysis framework for parallel processing. The proposed technique was subjected to performance testing with the AWS observation data of the Meteorological Administration, which are large-scale streaming sensor data for demonstration purposes.

• Journal of the Korean Vacuum Society
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• v.20 no.6
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• pp.422-429
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• 2011

Dependence of radical and ion density on electron density and temperature is numerically investigated for $Cl_2$/Ar, $CF_4$, $CF_4/O_2$, $CF_4/H_2$, $C_2F_6$, $C_4F_8$ and $SF_6$ discharges which are widely used for etching process. We derived a governing equation set for radical and ion densities as functions of the electron density and temperature, which are easier to measure relatively, from continuity equations by assuming steady state condition. Used rate coefficients of reactions in numerical calculations are directly produced from collisional cross sections or collected from various papers. If the rate coefficients have different values for a same reaction, calculation results were compared with experimental results. Then, we selected rate coefficients which show better agreement with the experimental results.

• Korean Journal of Remote Sensing
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• v.34 no.6_3
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• pp.1427-1443
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• 2018

Object-based image analysis (OBIA) allows higher computation efficiency and usability of information inherent in the image, as it reduces the complexity of the image while maintaining the image properties. Superpixel methods oversegment the image with a smaller image unit than an ordinary object segment and well preserve the edges of the image. SLIC (Simple linear iterative clustering) is known for outperforming the previous superpixel methods with high image segmentation quality. Although the input parameter for SLIC, number of superpixels has considerable influence on image segmentation results, impact analysis for SLIC parameter has not been investigated enough. In this study, we performed optimal parameter analysis and evaluation of change detection for SLIC-based superpixel techniques using KOMPSAT data. Forsuperpixel generation, three superpixel methods (SLIC; SLIC0, zero parameter version of SLIC; SNIC, simple non-iterative clustering) were used with superpixel sizes in ranges of $5{\times}5$ (pixels) to $50{\times}50$ (pixels). Then, the image segmentation results were analyzed for how well they preserve the edges of the change detection reference data. Based on the optimal parameter analysis, image segmentation boundaries were obtained from difference image of the bi-temporal images. Then, DBSCAN (Density-based spatial clustering of applications with noise) was applied to cluster the superpixels to a certain size of objects for change detection. The changes of features were detected for each superpixel and compared with reference data for evaluation. From the change detection results, it proved that better change detection can be achieved even with bigger superpixel size if the superpixels were generated with high regularity of size and shape.

• Journal of Digital Convergence
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• v.20 no.4
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• pp.575-584
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• 2022

The purpose of this study is to derive interaction types that appear variously in immersive contents through John Dewey's empirical theory, and to explore how the derived types are delivered in real cases. For this reason, two cases of the National Museum of Korea 'Immersive Digital Gallery' and 'Arte Museum Jeju' were analyzed through interaction types derived from the empirical theory. The interaction types derived based on the experience theory are the elements of 'multi-sensory', 'simultaneous experience' and 'sensory expansion'. In both cases, these types appear connected rather than grafted one by one in common. In one direction, 'multi-sensory' leads to 'sensory expansion', and in two directions, 'simultaneous experience' leads to 'sensory expansion'. As such, the core types of communication between technology and humans are not delivered one by one, but a cycle of interaction is formed in multiple ways. Therefore, it can be seen that the interaction type of immersive contents is expanded step by step by fusion of various senses and experiences in various fields, rather than a 1:1 partial delivery method. Based on this, it will be necessary to study how types are expanded and how viewers are affected when interaction is implemented in immersive contents in the future.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.1
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• pp.9-18
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• 2023

Predicting the compressive strength of high-performance concrete (HPC) is challenging because of the use of additional cementitious materials; thus, the development of improved predictive models is essential. The purpose of this study was to develop an HPC compressive-strength prediction model using an ensemble machine-learning method of combined bagging and stacking techniques. The result is a new ensemble technique that integrates the existing ensemble methods of bagging and stacking to solve the problems of a single machine-learning model and improve the prediction performance of the model. The nonlinear regression, support vector machine, artificial neural network, and Gaussian process regression approaches were used as single machine-learning methods and bagging and stacking techniques as ensemble machine-learning methods. As a result, the model of the proposed method showed improved accuracy results compared with single machine-learning models, an individual bagging technique model, and a stacking technique model. This was confirmed through a comparison of four representative performance indicators, verifying the effectiveness of the method.