• Journal of Creative Information Culture
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• v.7 no.4
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• pp.265-277
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• 2021

Data is the core of AI technology. With the development of technology, AI technology is also accelerating as the amount of data increases explosively than before. However, compared to the interest in AI education, research on data education with AI is still insufficient. According to the case analysis of exsisting AI data education, there were cases of educating the process and part of data science, but it was hard to find studies related to data collection. Cause physical computing tools have a positive effect on AI education for elementary school students, data collection cases using tools were studied, but researches related to data collection were rare. Therefore, in this study, an efficient data collection method using physical tools was designed. A structural diagram of a data collection program was created using COBL S, a modular physical computing teaching tool, and examples of program screens from the service side and the user side were configured. This study has limitations in that the establishment of an AI education platform that can be used in conjunction with future program production and programs should be prioritized as a proposal in terms of design.

• Journal of Creative Information Culture
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• v.6 no.3
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• pp.209-217
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• 2020

Recently, interest in data analysis has increased, and convergence research through data analysis has been actively conducted in various fields such as engineering, natural science, and social science. In the field of architecture, various studies using data analysis are being conducted, and in particular, efforts are being made to solve the problems in the field of architecture that have been quantitatively expanded through the urbanization process. In this study, data analysis on residential satisfaction of residents in residential environment improvement areas and similar neighborhoods through urban regeneration projects is performed. Through analysis using R for post-residential evaluation elements that are conducted after building construction and occupancy, important evaluation items that affect the satisfaction of the residential environment are identified by analyzing the association rules between each evaluation element and identifying the frequency of major requirements of residents. To grasp. Through this, we intend to conduct convergence research between IT and architecture fields, such as the development of a system that can recommend high-quality residential areas as well as providing data for securing high-quality residential spaces when constructing residential areas in the future.

• Journal of the Korean Chemical Society
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• v.66 no.5
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• pp.349-361
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• 2022

Because hydrotreating (HDT) of FCC gasoline is one of the important processes used to prepare such gasoline for blending, the development of a catalyst for this process is of great interest. Currently, the industrial HDT of FCC gasoline consists of two stages and the creation of a new catalyst for one-stage HDT will make this process more efficient. Recently, our group has developed the CoMo/Al₂O₃-ASA catalyst and studied the influence of Si/Al ratio on the target reactions of HDT process. Despite the high selectivity and activity, the catalyst with ASA is not applicable in industry because of its low strength. The present work moves forward to study the influence of the ASA content in the catalyst support and clarify the possibility to develop the catalyst that combines high activity and selectivity in HDT reactions with successful performance. Here we show that the CoMo catalyst with ASA/Al₂O₃ molar ratio 1/1 in the support is the best combination for FCC gasoline hydrotreatment due to exceptional properties of the catalyst composition.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.5
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• pp.55-61
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• 2022

With the rapid development of information technology, Metaverse and Non-Fungible Token (hereinafter referred to as NFT) technology will not only create new supply and demand markets for digital art creators, but also for existing art writers. As interest in and trading of virtual assets and coins increases, so does the demand for digital art trading in the NFT market. This study examines the theoretical content of NFTs, blockchains, and Metaverse, and analyzes various expressions of NFT art that are currently popular. As the case study, 100 projects were selected and analyzed in the overall OpenSea ranking, which included 2D graphics, 3D graphics and motion graphics works. Then, from the perspective of creators, the graphic styles of NFT digital art are divided into 4 types: 2D graphics, 3D graphics, 2D dynamic graphics, 3D dynamic graphics, and analyzed and studied. It is hoped that in the future, this study can suggest the direction of creating graphic styles to digital art NFT creators.

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.5
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• pp.95-102
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• 2022

Recently, there has been a growing interest in reducing greenhouse gases in all industrial fields. In the construction industry, studies have been conducted for the use of high-volume fly ash concrete to replace cement with fly ash. Quantitative measurements of cement hydration and fly ash reactivity enable a clear understanding of the strength development mechanism of high-volume fly ash concrete. It is very difficult to describe the reactivity in a simple way because the hydration and pozzolanic reactions of cement paste containing fly ash are very complex and the composition of the hydration product cannot be accurately determined. This study investigated the hydration and mechanical properties of high volume fly ash (HVFA) cement according to the substitution rate of fly ash (FA). The hydration degree of cement and the reactivity of FA were evaluated through the selective dissolution method and the non-evaporable water content of the paste according to age. In addition, compressive strength was measured using HVFA mortar specimens according to age. As a result of the experiment, as the substitution rate of fly ash increased, the hydration degree of cement increased, but the reactivity of FA decreased.

• Journal of the Microelectronics and Packaging Society
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• v.29 no.3
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• pp.13-23
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• 2022

Demand and interest in electric vehicles are increasing rapidly due to environmental issues. Improving the performance of electric vehicles requires the development of automotive batteries and battery joining technologies. Aluminum alloys are the most widely used metals in the electric vehicle industry, and aluminum bonding is used in all processes comprising automotive batteries. Therefore, in this paper, based on the characteristics of aluminum and aluminum alloys and knowledge of various aluminum joining technologies, the main and the next generation bonding technologies used in automotive battery are reviewed. It also explains the structure of automotive secondary battery cells and the integration order of 'cell-module-pack' where joining is used in the process, also various environmental conditions that must be considered when joining.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.73-82
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• 2022

Early detection continues to be the mainstay of breast cancer control as well as the improvement of its treatment. Even so, the absence of cancer symptoms at the onset has early detection quite challenging. Therefore, various researchers continue to focus on cancer as a topic of health to try and make improvements from the perspectives of diagnosis, prevention, and treatment. This research's chief goal is development of a system with deep learning for classification of the breast cancer as non-malignant and malignant using mammogram images. The following two distinct approaches: the first one with the utilization of patches of the Region of Interest (ROI), and the second one with the utilization of the overall images is used. The proposed system is composed of the following two distinct stages: the pre-processing stage and the Convolution Neural Network (CNN) building stage. Of late, the use of meta-heuristic optimization algorithms has accomplished a lot of progress in resolving these problems. Teaching-Learning Based Optimization algorithm (TIBO) meta-heuristic was originally employed for resolving problems of continuous optimization. This work has offered the proposals of novel methods for training the Residual Network (ResNet) as well as the CNN based on the TLBO and the Genetic Algorithm (GA). The classification of breast cancer can be enhanced with direct application of the hybrid TLBO- GA. For this hybrid algorithm, the TLBO, i.e., a core component, will combine the following three distinct operators of the GA: coding, crossover, and mutation. In the TLBO, there is a representation of the optimization solutions as students. On the other hand, the hybrid TLBO-GA will have further division of the students as follows: the top students, the ordinary students, and the poor students. The experiments demonstrated that the proposed hybrid TLBO-GA is more effective than TLBO and GA.

• Genomics & Informatics
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• v.19 no.4
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• pp.47.1-47.12
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• 2021

Kaposi's sarcoma-associated herpesvirus (KSHV) is one of the few human oncogenic viruses, which causes a variety of malignancies, including Kaposi's sarcoma, multicentric Castleman disease, and primary effusion lymphoma, particularly in human immunodeficiency virus patients. The currently available treatment options cannot always prevent the invasion and dissemination of this virus. In recent times, siRNA-based therapeutics are gaining prominence over conventional medications as siRNA can be designed to target almost any gene of interest. The ORF57 is a crucial regulatory protein for lytic gene expression of KSHV. Disruption of this gene translation will inevitably inhibit the replication of the virus in the host cell. Therefore, the ORF57 of KSHV could be a potential target for designing siRNA-based therapeutics. Considering both sequence preferences and target site accessibility, several online tools (i-SCORE Designer, Sfold web server) had been utilized to predict the siRNA guide strand against the ORF57. Subsequently, off-target filtration (BLAST), conservancy test (fuzznuc), and thermodynamics analysis (RNAcofold, RNAalifold, and RNA Structure web server) were also performed to select the most suitable siRNA sequences. Finally, two siRNAs were identified that passed all of the filtration phases and fulfilled the thermodynamic criteria. We hope that the siRNAs predicted in this study would be helpful for the development of new effective therapeutics against KSHV.

• Journal of Korean society of Dental Hygiene
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• v.21 no.6
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• pp.813-820
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• 2021

Objectives: This study was conducted to verify the effectiveness of the VR-applied head and neck anatomy class and to be used as basic data for the development of a teaching method using VR in the basic dental hygiene field. Methods: A convenience sample was extracted from 128 students and graduates who completed the head and neck anatomy class at the department of dental hygiene at a university in Gwangju. From June 1 to July 31, 2021, an online survey was conducted on class attitude and satisfaction, and statistical analysis was performed using frequency analysis and independent sample t-test. Results: Class attitude (3.79), interest (3.64), attention (3.88), learning motivation (3.80), and achievement motivation (3.84) were all high in the head and neck anatomy VR application group (p<0.01). Satisfaction (3.99), relevance of class content (4.06) and class achievement (3.96) were high in the head and neck anatomy VR application group (p<0.01). The suitability of class attitude (3.65) and class content (sub-item of class satisfaction) (4.13) was high in the group with the 4th industrial revolution education experience (p<0.05). Conclusions: The effect of VR application in the head and neck anatomy class was confirmed to increase students' class attitude and satisfaction. In the basic dental hygiene curriculum, it will be necessary to develop and utilize teaching methods related to the 4th industrial revolution and VR application classes.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.2
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• pp.61-69
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• 2022

The study intends to investigate a short-run and a long-run causality among money, income, and prices in the Keynesian and Monetarists framework. This study emphasizes the importance of unrecorded money, which exists alongside legal monetary assets and plays a dual function in determining economic prosperity. The underground economy, which is a hidden component of aggregate economic activity, is determined using Tanzi's monetary approach (Tanzi, 1980). This research uses a time series of annual data from 1990 to 2019 for this purpose. The data is extracted from the World Bank database for the monetary and development indicators. The study keeping in view the trending nature in data follows a unit root testing followed by the Autoregressive Distributive Lag Model (ARDL) to assess the long and short-run dynamics of causality among the variables. In both the pricing and income equations, the study finds a significant level link among the variables; however, there is no evidence of the presence of a level association in the money equation. The short-run causal relationship provides evidence of bi-directional causation between the supply of money and national income. The outcome of this study advise that though the view point of both the Monetarist and Keynesian school holds in both short and long run, however, in Pakistan only the Monetarists' role of money supply and income holds in Pakistan. This evidence would be of precise interest to the policy-makers.