• KIPS Transactions on Software and Data Engineering
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• v.10 no.3
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• pp.79-84
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• 2021

A feature extraction method capable of reflecting features well while mainaining the properties of data is required in order to process high-dimensional data. The principal component analysis method that converts high-level data into low-dimensional data and express high-dimensional data with fewer variables than the original data is a representative method for feature extraction of data. In this study, we propose a principal component analysis method based on adaptive correlation when selecting principal component variables in principal component analysis for data feature extraction when the data is high-dimensional. The proposed method analyzes the principal components of the data by adaptively reflecting the correlation based on the correlation between the input data. I want to exclude them from the candidate list. It is intended to analyze the principal component hierarchy by the eigen-vector coefficient value, to prevent the selection of the principal component with a low hierarchy, and to minimize the occurrence of data duplication inducing data bias through correlation analysis. Through this, we propose a method of selecting a well-presented principal component variable that represents the characteristics of actual data by reducing the influence of data bias when selecting the principal component variable.

• Journal of the Korea Society of Computer and Information
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• v.26 no.3
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• pp.9-17
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• 2021

In this paper, an autonomous multi-agent path planning using reinforcement learning for monitoring of infrastructures and resources in a computationally distributed system was proposed. Reinforcement-learning-based multi-agent exploratory system in a distributed node enable to evaluate a cumulative reward every action and to provide the optimized knowledge for next available action repeatedly by learning process according to a learning policy. Here, the proposed methods were presented by (a) approach of dynamics-based motion constraints multi-agent path-planning to reduce smaller agent steps toward the given destination(goal), where these agents are able to geographically explore on the environment with initial random-trials versus optimal-trials, (b) approach using agent sub-goal selection to provide more efficient agent exploration(path-planning) to reach the final destination(goal), and (c) approach of reinforcement learning schemes by using the proposed autonomous and asynchronous triggering of agent exploratory phases.

• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.211-217
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• 2020

This study is to find out the effectiveness by adult CPR method of a single rescuer. For patients with acute cardiac arrest, CPR is the only first aid, and chest compression is the most important of these techniques. The subjects of this study were freshman, 120 subjects who did not learn CPR, and for data analysis, the SPSS 22.0 Version was used. The accuracy of chest compression site selection was significantly higher in the upper part of the two fingers in the pit of the stomach(p<.001), and the ease was also high(p<.001). In the case of the general public, they select the chest compression area easily and quickly, it turns out that it is easier to designate the landmark toward the pit of the stomach. In the future, through various job groups, research to select the chest compression site is needed, and additional studies should be conducted to confirm the maintenance and accuracy during chest compression.

• Journal of dental hygiene science
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• v.21 no.1
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• pp.1-7
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• 2021

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is transmitted primarily through droplets, and dental practitioners are at risk of occupational exposure to SARS-CoV-2 infection owing to direct contact with the patient's mouth, aerosols from dental procedures, and saliva. Wearing a mask is believed to be the best method of protection against infection, and a systematic literature review was conducted on whether the dental masks used in dentistry are effective in preventing Coronavirus Infectious Disease-19 (COVID-19). Methods: We used PubMed, Google Scholar, DBpia, NDSL, and KISS databases for this study. Of the 917 documents narrowed down by the search terms "Coronavirus, COVID-19, and dental," 83 documents were collected and studied. Ultimately, 42 of these papers were selected for analysis after considering duplication from the flow chart of the literature selection process. Results: While dental masks are often used when treating patients with unknown COVID-19 status, the Ministry of Food and Drug Safety stated that the use of dental masks is insufficient in preventing cross-transmission of COVID-19; instead, it was recommended that N95 masks, which correspond to KF94 masks, should be worn daily. On the other hand, wearing a dental mask and following precautions such as hand hygiene may not pose a significantly higher risk of infection than wearing an N95 mask when treating COVID-19 patients. Conclusion: There is an ongoing discussion regarding the use of dental masks when treating dental patients, and many argue that different types of masks should be selected according to the degree of infection and the individual's respiratory condition. By considering the safety and efficacy of dental masks in preventing infection, improvements can be made in the management of COVID-19 and dental-related infections.

• Journal of Advanced Navigation Technology
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• v.25 no.1
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• pp.8-16
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• 2021

In this paper, locations of vertiports were selected and evaluated to operate urban air mobility (UAM) in the Seoul metropolitan area. Demand data were analyzed using the data from the survey of commuting population and were marked on a map using MATLAB. To cluster the data, the K-means algorithm function built in MATLAB was used to identify the center of the cluster to as the location of vertiports, and using the silhouette technique, the accuracy and reliability of the clustering were evaluated. The locations of the selected vertiports were also identified using satellite maps to ensure that the locations of the selected vertiports were suitable for the actual vertiport location, and, if the location was not appropriate, final vertiports were selected through the repositioning process.

• Journal of Animal Reproduction and Biotechnology
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• v.36 no.2
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• pp.91-98
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• 2021

The objective of this study was to establish a selection process for high quality sperm in bovine semen using sperm separation by magnetic activation (MACS). For this, semen from 21 Nellore bulls was collected using an artificial vagina. To guarantee the presence of pathologies in the ejaculate, animals previously declassified in four consecutive spermiogram were used. Semen was analyzed in five statuses: (1) fresh semen (fresh); (2) density gradient centrifugation (DGC), percoll column; (3) non-apoptotic fraction after separation by MACS (MAC); (4) apoptotic fraction from the separation (MACPOOR); and (5) MAC followed by DGC (MACDGC). Using a computerized analysis system (CASA), motility was measured. The sperm morphology was evaluated by phase contrast, and the supravital test was completed with eosin/nigrosin staining. For DGC, 20 × 10⁶ cells were used in a gradient of 90% and 45% percoll. MACS used 10 × 10⁶ cells with 20 μL of nanoparticles attached to annexin V, and filtered through the MiniMACS magnetic separation column. Membrane integrity was assessed with SYBR-14/IP and mitochondrial potential with JC-1 by flow cytometry. Processing sperm by MACDGC, was more effective in obtaining samples with high quality sperm, verified by the total of abnormalities in the samples: 35.04 ± 2.29%, 21.50 ± 1.47%, 17.30 ± 1.10%, 30.68 ± 1.94% and 10.50 ± 1.46%, respectively for fresh, DGC, MAC, MACPOOR, and MACDGC. The subpopulation of non-apoptotic sperm had a high number of live cells (82.65%), membrane integrity (56.60%) and mitochondrial potential (83.98%) (p < 0.05). These findings suggest that this nanotechnological method, that uses nanoparticles, is efficient in the production of high-quality semen samples for assisted reproduction procedures in cattle.

• Design & Manufacturing
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• v.15 no.4
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• pp.24-31
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• 2021

In this study, an artificial neural network model was constructed to convert CAE analysis data into similar experimental data. In the analysis and experiment, the injection molding data for 50 conditions were acquired through the design of experiment and random selection method. The injection molding conditions and the weight, height, and diameter of the product derived from CAE results were used as the input parameters for learning of the convert model. Also the product qualities of experimental results were used as the output parameters for learning of the convert model. The accuracy of the convert model showed RMSE values of 0.06g, 0.03mm, and 0.03mm in weight, height, and diameter, respectively. As the next step, additional randomly selected conditions were created and CAE analysis was performed. Then, the additional CAE analysis data were converted to similar experimental data through the conversion model. An artificial neural network model was constructed to predict the quality of injection molded product by using converted similar experimental data and injection molding experiment data. The injection molding conditions were used as input parameters for learning of the predicted model and weight, height, and diameter of the product were used as output parameters for learning. As a result of evaluating the performance of the prediction model, the predicted weight, height, and diameter showed RMSE values of 0.11g, 0.03mm, and 0.05mm and in terms of quality criteria of the target product, all of them showed accurate results satisfying the criteria range.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.65-75
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• 2021

This study explores multiple variables of an OTT service for discovering hidden relationship between rating and the other variables of each successful and failed content, respectively. In order to extract key variables that are strongly correlated to the rating across the contents, this work analyzes 170 Netflix original dramas and 419 movies. These contents are classified as success and failure by using the rating site IMDb, respectively. The correlation between the contents, which are classified via rating, and variables such as violence, lewdness and running time are analyzed to determine whether a certain variable appears or not in each successful and failure content. This study employs a regression analysis to discover correlations across the variables as a main analysis method. Since the correlation between independent variables should be low, check multicollinearity and select the variable. Cook's distance is used to detect and remove outliers. To improve the accuracy of the model, a variable selection based on AIC(Akaike Information Criterion) is performed. Finally, the basic assumptions of regression analysis are identified by residual diagnosis and Dubin Watson test. According to the whole analysis process, it is concluded that the more director awards exist and the less immatatable tend to be successful in movies. On the contrary, lower fear tend to be failure in movies. In case of dramas, there are close correlations between failure dramas and lower violence, higher fear, higher drugs.

• Education of Primary School Mathematics
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• v.25 no.2
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• pp.161-178
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• 2022

Korean uses a dual numeral system consisting of native and Chinese words. This dual numerical system is customarily selected in real life, mixed with two methods, or irregularly transformed. Therefore, the burden on both students and teachers is increased in the learning guidance process of numeral. This study recognized the need to improve the difficulty of learning guidance due to the dual numeral system. To this end, the context in which the numeral system method is selected, various modified cases, and related guidance contents of the current curriculum and textbooks were analyzed and organized. As a result of the analysis, there were characteristics of the selection and deformation of the numeral system method, which appears according to the actual situation using numerical. However, the criteria for characteristics were ambiguous and there were no specific guidance guidelines in the curriculum and textbooks. In this case, since the role of the teacher is more important, the teacher should be aware of the detailed characteristics of the actual situation related to the dual numeral system and let the student understand through experience and practice on various aspects of the use of the dual numeral system.

• Journal of Industrial Convergence
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• v.20 no.4
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• pp.1-6
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• 2022

In recent years, many global manufacturers such as Mercedes-Benz and BMW have been using augmented reality technology to spread it to various fields such as assembly process, after-sales service, sales stores, and consumer manuals. In this study, the application status of innovation in manufacturing using industrial augmented reality was identified, and the possibility of combining existing ERP and augmented reality was analyzed based on this. In addition, it was empirically analyzed that the selection of a dedicated content development engine is the most important factor in development productivity in the development of industrial augmented reality content. The same content developed with Unity3d was redeveloped with Vuforia Studio, and as a result of comparative analysis of development man-hours by field, the development lead time was shortened by 8 times. This study proves productivity by actually developing industrial augmented reality contents, and it is a study with a difference that is difficult to implement in practice.