• The Korean Journal of Archival Studies
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• no.56
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• pp.147-182
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• 2018

Intangible cultural heritage is formless. It's of importance to preserve heritage in line with society drastically being transformed. It's passed down by human being. It is, on the other hand, impossible to preserve intangible cultural heritage solely based on memory, for it's changed in succession. Thus, it be archived to pass down. This study investigated on the state of affair related with Intangible cultural heritage documentations, examined the shortages thereupon. Furthermore, Training center should be in charge of documentation for a solution. This will provide an opportunity to overcome the limitations attributed to the top-down documentation system by central administrative organ, to open up the possibility of viewpoint of different successors, organizations. In addition to that, Intangible cultural heritage documents should be of different aspects of community history. Features of Intangible cultural heritages, which are convergent to the Regionality, tendency of variation, transmission, can be magnified when documentating. Finally, Training center is going to play a major role being vitalised. The record management of intangible cultural heritage, institutions and policies about Intangible cultural heritage have been highly complicated since National Intangible Heritage Center opened and the law on Intangible cultural heritage enacted with its recognition attracted. Therewith this study wishes to see a cornerstone of records on intangible cultural heritage by laying stress on training center in which educations and pass-down of intangible cultural heritage are lively achieved.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.9
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• pp.211-226
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• 2019

Pig CD45, the leukocyte common antigen, is encoded by the PTPRC gene and CD45 is a T cell-type specific tyrosine phosphatase with alternative splicing of its exons. The CD45 is a coordinated regulator of T cell antigen receptor (TCR) signal transduction achieved by dephosphorylating the phosphotyrosine of its substances, including $CD3{\zeta}$ chain of TCR, Lck, Fyn, and Zap-70 kinase. A dysregulation of CD45 is associated with a multitude of immune disease and has been a target for immuno-drug discovery. To characterize its key structural features with the effects of regulating TCR signaling, this study predicted the unknown structure of pig CD45RO (the smallest isoform) and the complex structure bound to the ITAM (REEpYDV) of $CD3{\zeta}$ chain via homology modeling and docking the peptide, based on the known human CD45 structures. These features were integrated into the structural plasticity of extracellular domains and functional KNRY and PTP signature motifs (the role of a narrow entrance into ITAM binding site) of the tyrosine phosphatase domains in a cytoplasmic region from pig CD45RO. This contributes to the selective recognition of phosphotyrosine from its substrates by adjusting the structural stability and binding affinity of the complex. The characterized features of pigCD45RO can be applied in virtual screening of the T-cell specific immunomodulator.

• Journal of Science Education
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• v.43 no.1
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• pp.119-135
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• 2019

The purpose of this study is to analyze components of conflicts and investigate causes of them between mentor teachers and mentee teachers, who participated in the collaborative mentoring program to improve beginning science teachers teaching practice. The most often occurring component of conflict for surveyed teams was class strategy on knowledge of teaching methods. Then, conflicts in understanding student characteristics as a component of understanding students and knowledge transfer of concepts in science as a component of teaching contents followed as main causes. Changes in conflicts showed that less frequency of conflict occurred with ongoing mentoring. Conflicts from class strategy decreased the most, which had been the most often occurring cause. This decrease was explained as mentees were changed gradually into the teacher's role recognition through continuous mentoring. This study suggests that education for mentor and mentee teachers be provided with consideration of causes of conflicts and reasons for those causes, which eventually lead sustainable and efficient mentoring program management.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.22 no.4
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• pp.15-34
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• 2019

Today, there is increasing recognition of the importance of urban regeneration for better public places. Urban parks as a public area play an important role in harnessing its positive impact on people's well-being: where the standards and funding of/for the parks are getting worse. There is however less a focus on policy approach to park regeneration in the country. Neverthless, a few UK's cases of such innovative park management(PM) has shown successful park regeneration based on policy support. Therefore, the aim of this research is to draw policy implications by exploring a case of successful park regeneration. To address the aim, this research conducts an in-depth case study of 'Manor Fields Park, UK', digging into its PM structure and PM body 'Green Estate Ltd' in relation to relevant policy. The data is mainly collected by interviews including a group interview. The analytical framework 'Place-keeping(PK)' and its six dimensions are employed to determine the characteristics of MFP's PM structure. Resultingly, there is a significant shift in the approach to PM which stresses the principle of long-term and self-sustaining structure led by a non-profit organisation and strong impacts of policy. In this context, PK highlights significant drivers for parks regeneration particularly in terms of policy implications: 1)providing policy support to encourage non-profit organisations in PM, 2)extending community involvement in decision-making processes, 3)promoting income generation by community groups, 4)shifting public awareness of shared responsibility for PM, 5)completing regular park maintenance assessment by community groups, and 6)delivering low-maintenance approaches to PM. To support these implications, PM structure for successful parks regeneration does meet a holistic and multi-dimensional approach of place-keeping underlined by understanding policy contexts and rethinking current status quo of PM. Addressing these implications will shed light on urban PM in an era of austerity and ultimately contribute to improving people's well-being.

• Journal of the Korean Society for Library and Information Science
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• v.53 no.2
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• pp.91-116
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• 2019

This study conducted a demand analysis for the operation and management of closed schools, the direction of future use of closed schools, and the utilization of closed schools, among local residents expected to play a key role in the successful use of closed libraries. According to the study, residents in areas where schools actually occur may actively consider the use of closed schools when they are lacking in the number of libraries in the region or when they hope to remodel their schools as libraries, given that they are positive about future use of closed schools and that remodeling them is more economical in terms of cost than building new libraries. The current awareness of the use and operation of closed schools remains at a normal level, so it is deemed necessary to improve the direction of the promotion, operation and recycling of closed schools in the order of promotion, operation and physical aspects by grouping obstacles to the operation and management of closed schools. In addition, the current status of cultural facilities and the demands of local residents are met in terms of the types of use of closed school facilities, and it means that closed schools can be used in a relatively easy-to-access location based on their location, while libraries can be used as a space for cultural facilities that are different from the existing public libraries, exhibition halls, and eco-friendly libraries.

• BMB Reports
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• v.54 no.2
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• pp.118-123
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• 2021

The bacterial effector protein RavZ from a pathogen can impair autophagy in the host by delipidating the mammalian autophagy-related gene 8 (mATG8)-phosphatidylethanolamine (PE) on autophagic membranes. In RavZ, the membrane-targeting (MT) domain is an essential function. However, the molecular mechanism of this domain in regulating the intracellular localization of RavZ in cells is unclear. In this study, we found that the fusion of the green fluorescent protein (GFP) to the MT domain of RavZ (GFP-MT) resulted in localization primarily to the cytosol and nucleus, whereas the GFP-fused duplicated-MT domain (GFP-2xMT) localized to Rab5- or Rab7-positive endosomes. Similarly, GFP fusion to the catalytic domain (CA) of RavZ (GFP-CA) resulted in localization primarily to the cytosol and nucleus, even in autophagy-induced cells. However, by adding the MT domain to GFP-CA (GFP-CA-MT), the cooperation of MT and CA led to localization on the Rab5-positive endosomal membranes in a wortmannin-sensitive manner under nutrient-rich conditions, and to autophagic membranes in autophagy-induced cells. In autophagic membranes, GFP-CA-MT delipidated overexpressed or endogenous mATG8-PE. Furthermore, GFP-CA△α3-MT, an α3 helix deletion within the CA domain, failed to localize to the endosomal or autophagic membranes and could not delipidate overexpressed mATG8-PE. Thus, the CA or MT domain alone is insufficient for stable membrane localization in cells, but the cooperation of MT and CA leads to localization to the endosomal and autophagic membranes. In autophagic membranes, the CA domain can delipidate mATG8-PE without requiring substrate recognition mediated by LC3-interacting region (LIR) motifs.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.6
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• pp.77-83
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• 2020

The heat treatment facility is in a situation where the scope of application of the remote IOT system is expanding due to the harsh environment caused by high heat and long working hours among the root industries. In this heat treatment process environment, the IOT middleware is required to play a pivotal role in interpreting, managing and controlling data information of IoT devices (sensors, etc.). Until now, the system controlled by the heat treatment remotely was operated with the command of the operator's batch system without overall monitoring of the site situation. However, for the safety and precise control of the heat treatment facility, it is necessary to control various sensors and recognize the surrounding work environment. As a solution to this, the heat treatment safety support system presented in this paper proposes a support system that can detect the access of the work manpower to the heat treatment furnace through thermal image detection and operate safely when ordering work from a remote location. In addition, an OPEN CV-based deterioration analysis system using DNN deep learning network was constructed for faster and more accurate recognition than general fixed hot spot monitoring-based thermal image analysis. Through this, we would like to propose a system that can be used universally in the heat treatment environment and support the safety management specialized in the heat treatment industry.

• Journal of Broadcast Engineering
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• v.25 no.6
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• pp.944-953
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• 2020

Object detection plays a crucial role in a self-driving system. With the advances of image recognition based on deep convolutional neural networks, researches on object detection have been actively explored. In this paper, we proposed a lightweight model of the mask R-CNN, which has been most widely used for object detection, to efficiently predict location and shape of various objects on the road environment. Furthermore, feature maps are adaptively re-calibrated to improve the detection performance by applying an attention module to the neural network layer that plays different roles within the mask R-CNN. Various experimental results for real driving scenes demonstrate that the proposed method is able to maintain the high detection performance with significantly reduced network parameters.

• The Journal of Korean Institute of Next Generation Computing
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• v.14 no.5
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• pp.19-30
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• 2018

Visual information understanding is known as one of the most difficult and challenging problems in the realization of machine intelligence. This paper proposes deriving visual verb and construction of ActionNet database as a video database for video semantic understanding. Even though development AI (artificial intelligence) algorithms have contributed to the large part of modern advances in AI technologies, huge amount of database for algorithm development and test plays a great role as well. As the performance of object recognition algorithms in still images are surpassing human's ability, research interests shifting to semantic understanding of video contents. This paper proposes candidates of visual verb requiring in the construction of ActionNet as a learning and test database for video understanding. In order to this, we first investigate verb taxonomy in linguistics, and then propose candidates of visual verb from video description database and frequency of verbs. Based on the derived visual verb candidates, we have defined and constructed ActionNet schema and database. According to expanding usability of ActionNet database on open environment, we expect to contribute in the development of video understanding technologies.

• Journal of the Korea Society for Simulation
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• v.30 no.2
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• pp.41-48
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• 2021

As the rural population continues to decline and aging, the improvement of agricultural productivity is becoming more important. Early prediction of crop quality can play an important role in improving agricultural productivity and profitability. Although many researches have been conducted recently to classify diseases and predict crop yield using CNN based deep learning and transfer learning technology, there are few studies which predict postharvest crop quality early in the planting stage. In this study, a early quality prediction model is proposed for sprout ginseng, which is drawing attention as a healthy functional foods. For this end, we took pictures of ginseng seedlings in the planting stage and cultivated them through hydroponic cultivation. After harvest, quality data were labeled by classifying the quality of ginseng sprout. With this data, we build early quality prediction models using several pre-trained CNN models through transfer learning technology. And we compare the prediction performance such as learning period and accuracy between each model. The results show more than 80% prediction accuracy in all proposed models, especially ResNet152V2 based model shows the highest accuracy. Through this study, it is expected that it will be able to contribute to production and profitability by automating the existing seedling screening works, which primarily rely on manpower.