• KIPS Transactions on Computer and Communication Systems
• /
• v.9 no.8
• /
• pp.171-180
• /
• 2020

Smart Factory consists of digital automation solutions throughout the production process, including design, development, manufacturing and distribution, and it is an intelligent factory that installs IoT in its internal facilities and machines to collect process data in real time and analyze them so that it can control itself. The smart factory's equipment works in a physical combination of numerous hardware, rather than a virtual character being driven by a single object, such as a game. In other words, for a specific common goal, multiple devices must perform individual actions simultaneously. By taking advantage of the smart factory, which can collect process data in real time, if reinforcement learning is used instead of general machine learning, behavior control can be performed without the required training data. However, in the real world, it is impossible to learn more than tens of millions of iterations due to physical wear and time. Thus, this paper uses simulators to develop grid sortation systems focusing on transport facilities, one of the complex environments in smart factory field, and design cooperative multi-agent-based reinforcement learning to demonstrate efficient behavior control.

• Bulletin of the Korean Chemical Society
• /
• v.31 no.1
• /
• pp.52-58
• /
• 2010

Human histamine H1 receptor (HHR1) is a G protein-coupled receptor and a primary target for antiallergic therapy. Here, the ligand-based three-dimensional pharmacophore models were built from a set of known HHR1 inverse agonists using HypoGen module of CATALYST software. All ten generated pharmacophore models consist of five essential features: hydrogen bond acceptor, ring aromatic, positive ionizable and two hydrophobic functions. Best model had a correlation coefficient of 0.854 for training set compounds and it was validated with an external test set with a high correlation value of 0.925. Using this model Maybridge database containing 60,000 compounds was screened for potential leads. A rigorous screening for drug-like compounds unveiled RH01692 and SPB00834, two novel molecules for HHR1 with good CATALYST fit and estimated activity values. The new lead molecules were docked into the active site of constructed HHR1 homology model based on recently crystallized squid rhodopsin as template. Both the hit compounds were found to have critical interactions with Glu177, Phe432 and other important amino acids. The interpretations of this study may effectively be deployed in designing of novel HHR1 inverse agonists.

• Bulletin of the Korean Chemical Society
• /
• v.32 no.1
• /
• pp.201-207
• /
• 2011

Peroxisome proliferator-activated receptors (PPARs) are members of nuclear receptors and their activation induces regulation of fatty acid storage and glucose metabolism. Therefore, the $PPAR\gamma$ is a major target for the treatment of type 2 diabetes mellitus. In order to generate pharmacophore model, 1080 known agonists database was constructed and a training set was selected. The Hypo7, selected from 10 hypotheses, contains four features: three hydrogen-bond acceptors (HBA) and one general hydrophobic (HY). This pharmacophore model was validated by using 862 test set compounds with a correlation coefficient of 0.903 between actual and estimated activity. Secondly, CatScramble method was used to verify the model. Hence, the validated Hypo7 was utilized for searching new lead compounds over 238,819 and 54,620 chemical structures in NCI and Maybridge database, respectively. Then the leads were selected by screening based on the pharmacophore model, predictive activity, and Lipinski's rules. Candidates were obtained and subsequently the binding affinities to $PPAR\gamma$ were investigated by the molecular docking simulations. Finally the best two compounds were presented and would be useful to treat type 2 diabetes.

• Journal of the Korean Institute of Traditional Landscape Architecture
• /
• v.37 no.1
• /
• pp.68-75
• /
• 2019

This study aims to look at the application methods of landscape architecture in response to the 4th Industrial Revolution. The results of the analysis of trends in the 4th Industrial Revolution and the subsequent search for application methods to the field of landscape architecture are as follows. First, the 4th Industrial Revolution means innovative change based on digital technology and seeks to create value based on intelligent information technology, and continuous growth is being made through innovation. This requires expertise to collect large amounts of information and creatively rework it, and a strategy to flexibly cope with changes in the times. Second, the status of technological use in response to the 4th Industrial Revolution in the field of landscape architecture is generalizing the establishment of precise analysis results such as survey technology and global mapping using drones, three-dimensional design simulation, and VR. In the field of traditional landscape architecture, efforts are made to obtain accurate fact-finding data on landscape site components. Third, the application methods in the field of landscape science according to the 4th Industrial Revolution in the future are required to supply precision technology and supply programs in the technology sector, and to provide a shared platform. In addition, a systemically standardized process will need to be established for this. In addition, educational efforts should be continued to professional manpower training and provide economic support for the development of technologies.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.19 no.6
• /
• pp.235-249
• /
• 2020

The Ministry of Land, Infrastructure and Transport established safety standards for Level 3 autonomous vehicles for the first time in the world in December 2019, and specified the safety standards for conditional autonomous driving systems. Accordingly, it is necessary to analyze the influence of various driving environments on take-over. In this study, using a driving simulator, we investigated how traffic conditions and weather conditions affect take-over time and stabilization time. The experimental procedure was conducted in the order of preliminary training, practice driving, and test driving, and the test driving was conducted by dividing into a traffic density and geometry experiment and a weather environment experiment. As a result of the experiment, it was analyzed that the traffic volume and weather environment did not affect the take-over time and take-over stabilization time, and only the curve radius affects take-over stabilization time.

• Journal of Korean Library and Information Science Society
• /
• v.52 no.4
• /
• pp.103-126
• /
• 2021

This study aims to propose a plan to restructure libraries as a complex space for education and culture for 19 public libraries belonging to the Chungcheongnam-do Office of Education. For the purpose of this, case surveys and user surveys of complex facilities of domestic and foreign public institutions were conducted. Based on the findings, a space restructuring strategy was suggested by dividing the library space into the following ways: a space to learn (a comprehensive data room, a theme data inquiry room, a future classroom, a blended learning center, a STEAM training room, and an online lecture learning room), a space to express (a foyer, a maker room, a digital media creation room and an online lecture production room), a space to share (a club room, a group study room, a well-being complex culture space, a convenient living space, rest area, and a browsing area), and a space to enjoy (a performance-thought playground, infant and child archives, a digital virtual experience room, a specialized alcove room, and an outdoor reading room). In addition, a restructuring model of public libraries belonging to the Office of Education was proposed, such as a leading model, a basic model, a joint model, and a minimum model, in consideration of the size of the building, the size of the library, and the level of service and space.

• Journal of the Korean Society of Earth Science Education
• /
• v.14 no.3
• /
• pp.248-256
• /
• 2021

The purpose of this study is to investigate the perception of pre-service elementary teachers on the educational approach to metaverse. Questions about metaverse were asked to 71 pre-service elementary teachers who were taking the course 'Study of Textbooks in Elementary Science II'. The results of analyzing the contents of the questions are as follows. The results and conclusions were presented through numerical analysis and static analysis based on the responses to questions presented using the university's LMS system. First, the level of understanding of the metaverse of pre-service elementary teachers is very high. Pre-service elementary teachers, as the MZ generation, are already living in a very fast IT environment that can be the basis of the metaverse, so it would have been helpful to understand the metaverse. Second, the need for the metaverse of pre-service elementary teachers is very high. There was a tendency to think that the perception of pre-service elementary teachers is because the metaverse has many factors that can provide higher quality education beyond the current educational environment. Third, in the question of applicability exploration in the 'Earth and Space' domain of Pre-service elementary teachers, there have been few cases in which instructional design was planned based on instructional design principles. Based on these results, if the possibility of metaverse application is proposed in the 'Earth and Space' domain, educational contents using virtual space that can transcend time and space will be very necessary. Based on these results, suggestions are made as follows. First, educational content incorporating the metaverse technique based on instructional design should be developed and utilized. Second, financial support should be provided so that the metaverse can be implemented in the educational environment. Third, it is necessary to provide training opportunities for teachers (including Pre-service elementary teachers) to give lectures on metaverse.

• Journal of Broadcast Engineering
• /
• v.27 no.5
• /
• pp.728-737
• /
• 2022

Metaverse is gaining worldwide interest, and related industries are developing rapidly. In the field of education, students' interest in metaverse is increasing, and education on metaverse-related technologies and services is required. However, since metaverse classes in universities mainly consist of theoretical education and domestic/overseas case analysis education, practical education that can apply metaverse technology to the real world is also necessary. In the cultural field, event contents such as entrance ceremonies and exhibitions are mainly produced for metaverse contents, and it is also necessary to study metaverse contents that can be sustained for a long time by people visiting regularly. In this study, educational contents that can link cultural participation in the real world with cultural participation in the metaverse were studied using the local cultural space as a medium to produce sustainable metaverse contents. The 'Metaverse Moonshin Art Museum commemorating the 100th anniversary of Moonshin's birth' program reinterpreted the real world of Changwon Moonshin Art Museum into a virtual world by collaborating with students on the Roblox. The 'Expanded Reality Moonshin Art Museum' program created an expanded Metaverse art museum that transcends time by augmenting the deceased Moonshin artist in the museum's exhibition space using HoloLens. For students studying culture-related majors, an educational program that combines metaverse education and practical training was conducted, and it is planned to be supplemented and used as a teaching plan.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.25 no.4
• /
• pp.63-80
• /
• 2022

As a technology to analyze and predict an issue has been developed by constructing real space into virtual space, it is becoming more important to acquire precise spatial information in complex cities. In this study, images were acquired using an unmanned aerial vehicle for urban area with complex landscapes, and land cover classification was performed object-based image analysis and semantic segmentation techniques, which were image classification technique suitable for high-resolution imagery. In addition, based on the imagery collected at the same time, the replicability of land cover classification of each artificial intelligence (AI) model was examined for areas that AI model did not learn. When the AI models are trained on the training site, the land cover classification accuracy is analyzed to be 89.3% for OBIA-RF, 85.0% for OBIA-DNN, and 95.3% for U-Net. When the AI models are applied to the replicability assessment site to evaluate replicability, the accuracy of OBIA-RF decreased by 7%, OBIA-DNN by 2.1% and U-Net by 2.3%. It is found that U-Net, which considers both morphological and spectroscopic characteristics, performs well in land cover classification accuracy and replicability evaluation. As precise spatial information becomes important, the results of this study are expected to contribute to urban environment research as a basic data generation method.

• KNOM Review
• /
• v.23 no.2
• /
• pp.18-28
• /
• 2020

With the development of the virtual community, the benefits that IT technology provides to people in fields such as healthcare, industry, communication, and culture are increasing, and the quality of life is also improving. Accordingly, there are various malicious attacks targeting the developed network environment. Firewalls and intrusion detection systems exist to detect these attacks in advance, but there is a limit to detecting malicious attacks that are evolving day by day. In order to solve this problem, intrusion detection research using machine learning is being actively conducted, but false positives and false negatives are occurring due to imbalance of the learning dataset. In this paper, a Random Oversampling method is used to solve the unbalance problem of the UNSW-NB15 dataset used for network intrusion detection. And through experiments, we compared and analyzed the accuracy, precision, recall, F1-score, training and prediction time, and hardware resource consumption of the models. Based on this study using the Random Oversampling method, we develop a more efficient network intrusion detection model study using other methods and high-performance models that can solve the unbalanced data problem.