• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.108-111
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• 2014

In this paper, we tried to identify implications of selecting gifted of information science & followed educational system via analyzing each of student's characteristics in each subjects they study within Science Education Institute for the Gifted. A study of the existing institutions do not have experience of the gifted students based on assessment through observation of the 1-year science, mathematics and information science education in the List of attribute analysis. Learners of Information Science became with analysis that Attitude Category was superior in mathematics to the subject of science and Problem Solving Category regardless of the subjects showed similar. As to, Attitude Category, Problem Solving Category and Mathematics Cognition Category was analyzed to be closed and we could confirm through the qualitative observation record. On this, the researcher concluded that the mathematics could know the effect fitness by a learner rather than the subject of science as to an attitude and problem resolution area.

• Convergence Security Journal
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• v.17 no.5
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• pp.63-69
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• 2017

In the early 1990s, IETF(Internet Engineering TaskForce) had started the discussion on new address protocol that can modify and supplement various drawbacks of existing IPv4 address protocol with the introduction of CIDR(Classless Inter-Domain Routing) which is a temporary solution for IPv4 address depletion, NAT, private IP address. While various standards related to new address protocol has been proposed, the SIPP(Simple Internet Protocol Plus) was adopted among them because it is regarded as the most promising solution. And this protocol has been developed into current IPv6. The new concepts are introduced with modifying a lot of deficiencies in the exisitng IPv4 such as real-time data processing, performance on QoS, security and the efficiency of routing. Since many security threats in IPv6 environment still exist, the necessity of stable data communication environment has been brought up continuously. This paper deveopled one-way communication algorithm in IPv6 based on the high possibility of protecting the system from uncertain and potential risk factors if the data is transmitted in one way. After the analysis of existing IPv6 and ICMPv6, this paper suggests one-way communication algorithm as a solution for existing IPv6 and ICMPv6 environment.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.21 no.6
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• pp.95-113
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• 2018

We studied the change of wetland vegetation structure to understand ecological restoration process of wetlands through the field survey of ecological restoration projects in Incheon, Iksan and Busan. We compared the vegetation plan at the time of planted with the results of the vegetation monitoring in 2018, and analyzed the changes in wetland vegetation structure. Based on results, we attempted to understand the restoration process of those wetlands and discuss the management measures for sustainable wetland restoration. As a result, in the Incheon Yeonhee restoration wetland, the number of plant species was increased, from 18 species in 2016 to 29 in 2018. The dominant species, Myriophyllum verticillatum, covered the wetland most and its occupied area was increased. On the other hand, the distribution area of the planted emergent hydrophytes was reduced. The area of open water decreased from 71.7% in 2016 to 48.8% in 2018. In Busan Igidae restoration wetland, the number of plant species was increased, from 6 species in 2014 to 31 in 2018. The dominant species was Myriophyllum verticillatum and its occupied area was increased. The area of floating plant communities that planned has decreased. The open water area decreased from 83.9% in 2014 to 31.8% in 2018. In Iksan Sorasan restoration wetland, the number of plant species was increased, from 13 species in 2016 to 36 in 2018. The dominant species was Phragmites communis Trin. and its occupied area was increased. The other planted species showed a tendency to be decreased by Phragmites communis Trin. and its terrestrialization. The open water area decreased from 86.6% in 2016 to 6.7% in 2018. These results suggest that wetlands should be managed by considering the change of vegetation structure and open water areas based on the following succession process, because it affects the habitat suitability of wetland organisms and biodiversity as well. Thus, the continuous monitoring for the ecological structure of restored wetland is important, and it could be possible step to develop sustainable wetland ecological restoration model.

• Journal of Life Science
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• v.31 no.2
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• pp.158-163
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• 2021

In the present study, we prepared hot water extracts of green apple (GAHW) and unripe apple (UAHW), and ethanol extract of green apple (GAE), and investigated their anti-inflammatory activities in LPS-activated RAW264.7 cells. All extracts dramatically suppressed nitric oxide (NO) production in a dose-dependent manner in LPS-stimulated RAW264.7 cells without affecting cell viability. In addition, all extracts decreased the expression of iNOS, whereas UAHW only reduced the expression of COX-2. All extracts suppressed the phosphorylation of MAPKs (p38, ERK, and JNK) indicating all extracts show their anti-inflammatory activities via regulating MAPK pathway. Furthermore, all extracts reduced the production of reactive oxygen species in a dose-dependent manner and they increased the expression of heme oxygenase-I (HO-I) whereas UAHW could not. We also investigated whether apple flavonoids phloretin and phloridzin can have their anti-inflammatory activities in same in vitro model. Phloretin dramatically decreased NO production in a dose dependent manner without affecting cell viability, whereas phloridzin have no effects. Phloretin also reduced the expression of iNOS as well as COX-2, whereas phloridzin could not. Overall, these results suggest that apple extracts have their anti-inflammatory activities via regulating MAPKs and HO-1 pathways, and apple flavonoid phloretin can be one of phytochemicals responsible for anti-inflammatory effect of apple.

• Journal of Internet of Things and Convergence
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• v.8 no.6
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• pp.21-26
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• 2022

This study aims to enhance the cultivation of SW·AI basic competencies of middle school students by forming and distributing SW·AI education programs for middle school students who form the basis of their lives. In addition, by planning SW·AI education programs in connection with the regular curriculum, it is intended to serve as a cornerstone for the public education of SW·AI education that will be implemented from 2025. To this end, the concept of SW and AI in middle school was first defined and a plan to link software/artificial intelligence learning factors to the regular curriculum was proposed, and based on this, SW·AI education programs for middle school students were prepared. Based on literature research, the understanding of artificial intelligence technology, the value of data, and the use of artificial intelligence technology in real life were set as SW·AI education contents, and educational programs were organized by linking them with the current middle school curriculum. All SW·AI education was organized in the form of practice rather than theory so that classes could be conducted centered on participants, and the purpose of the course was to cultivate the ability to use artificial intelligence technology in real life based on understanding artificial intelligence technology.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.763-769
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• 2021

In this study, ionic liquids were synthesized to remove carbon dioxide (CO2) on a laboratory scale. The vapor-liquid absorption equilibrium device (VLE) was used to investigate the carbon dioxide absorption capacity. In the regeneration study, the absorption capacity after regeneration was reduced by approximately 7% for all ionic liquids, in which the anion was sulfite-based, showing excellent regeneration. Ethyl sulfite showed the highest absorption capacity of CO2 among the ionic liquids based on the sulfite anion. In particular, the absorption capacity of [beim] ethyl sulfite was 1.1 mol CO2 / mol IL at an absorption equilibrium pressure of 22 bar. In the regeneration study, the absorption capacity after regeneration was reduced by approximately 7% for all ionic liquids, in which the anion was sulfite-based, from which regeneration is outstanding. After the absorption experiment, the viscosity of the sample tended to decrease by approximately 8% compared to that before the absorption experiment. On the other hand, the absorbent was synthesized in the first step. Moreover, the raw material used is also inexpensive and has excellent reproducibility and highly stable absorbent capacity.

• Korean Journal of Remote Sensing
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• v.38 no.2
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• pp.199-213
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• 2022

The unsupervised domain adaptation can solve the impractical issue of repeatedly collecting high-quality training data every year for annual crop classification. This study evaluates the applicability of deep learning-based unsupervised domain adaptation models for crop classification. Three unsupervised domain adaptation models including a deep adaptation network (DAN), a deep reconstruction-classification network, and a domain adversarial neural network (DANN) are quantitatively compared via a crop classification experiment using unmanned aerial vehicle images in Hapcheon-gun and Changnyeong-gun, the major garlic and onion cultivation areas in Korea. As source baseline and target baseline models, convolutional neural networks (CNNs) are additionally applied to evaluate the classification performance of the unsupervised domain adaptation models. The three unsupervised domain adaptation models outperformed the source baseline CNN, but the different classification performances were observed depending on the degree of inconsistency between data distributions in source and target images. The classification accuracy of DAN was higher than that of the other two models when the inconsistency between source and target images was low, whereas DANN has the best classification performance when the inconsistency between source and target images was high. Therefore, the extent to which data distributions of the source and target images match should be considered to select the best unsupervised domain adaptation model to generate reliable classification results.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1357-1369
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• 2022

Cloud removal is an essential image processing step for any task requiring time-series optical images, such as vegetation monitoring and change detection. This paper presents a two-stage cloud removal method that combines conditional generative adversarial networks (cGANs) with regression-based calibration to construct a cloud-free time-series optical image set. In the first stage, the cGANs generate initial prediction results using quantitative relationships between optical and synthetic aperture radar images. In the second stage, the relationships between the predicted results and the actual values in non-cloud areas are first quantified via random forest-based regression modeling and then used to calibrate the cGAN-based prediction results. The potential of the proposed method was evaluated from a cloud removal experiment using Sentinel-2 and COSMO-SkyMed images in the rice field cultivation area of Gimje. The cGAN model could effectively predict the reflectance values in the cloud-contaminated rice fields where severe changes in physical surface conditions happened. Moreover, the regression-based calibration in the second stage could improve the prediction accuracy, compared with a regression-based cloud removal method using a supplementary image that is temporally distant from the target image. These experimental results indicate that the proposed method can be effectively applied to restore cloud-contaminated areas when cloud-free optical images are unavailable for environmental monitoring.

• Journal of Internet of Things and Convergence
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• v.8 no.5
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• pp.93-98
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• 2022

With the development of new digital technologies, research on various learning tools is being actively conducted. These learning tools are also being developed so that they can be applied to various environments by applying the technology of artificial intelligence or using smart functions to which big data technology is applied. These smart learning tools are contributing a lot to increasing educational effectiveness and learning efficiency. Recently, various learning tools have been applied in universities, and solutions for smart learning from smart attendance are introduced to improve student learning efficiency. This study intends to propose a design for a smart learning tool that can increase the efficiency of project progress and increase the scalability of the results when conducting a company's customized project through such a university's smart learning tool. The proposed smart learning tool is expected to have the advantage of being able to easily adapt to the practical business project as the company-customized projects that can improve practical skills are smoothly used as a learning tool. The proposed project-based smart learning tool model is later built as a related LMS and applied to actual project progress to check its utility, and to revise and supplement the proposed smart learning tool model to provide a project-based smart learning function want to strengthen.

• Journal of Internet of Things and Convergence
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• v.8 no.5
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• pp.119-125
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• 2022

With the recent increase in dementia patients due to aging, measures to prevent their wandering behavior and disappearance are urgently needed. To solve this problem, various authentication methods and location detection techniques have been introduced, but the security problem of personal authentication and a system that can check indoor and outdoor overall was lacking. In order to solve this problem, various authentication methods and location detection techniques have been introduced, but it was difficult to find a system that can check the security problem of personal authentication and indoor/outdoor overall. In this study, we intend to propose a system that can identify personal authentication, basic health status, and overall location indoors and outdoors by using wristband-type wearable devices in a private blockchain environment. In this system, personal authentication uses ECG, which is difficult to forge and highly personally identifiable, Bluetooth beacon that is easy to use with low power, non-contact and automatic transmission and reception indoors, and DGPS that corrects the pseudorange error of GPS satellites outdoors. It is intended to detect wandering behavior and abnormal signs by locating the patient. Through this, it is intended to contribute to the prompt response and prevention of disappearance in case of wandering behavior and abnormal symptoms of dementia patients living at home or in nursing homes.