• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.4
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• pp.184-193
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• 2021

The system for managing spatial data updates the existing information by extracting only the information that is different from the existing information for the newly obtained spatial information file to update the stored information. In order to extract only objects that have changed from existing information, it is necessary to compare whether there is any difference from existing information for all objects included in the newly obtained spatial information file. This study was conducted to improve this total inspection method in a situation where the amount of spatial information that is frequently updated increases and data update is required at the national level. In this study, before inspecting individual objects in a new acquisition space information file, a method of determining whether individual space objects have been changed only by the information in the file was considered. Spatial data files have structured data characteristics different from general image or text document files, so it is possible to determine whether to change the file unit in a simpler way compared to the existing method of creating and managing file hash. By reducing the number of target files that require full inspection, it is expected to improve the use of resources in the system by saving the overall data quality inspection time and saving data extraction time.

• Journal of the Korean Applied Science and Technology
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• v.38 no.6
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• pp.1445-1454
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• 2021

In this study, based on the expectation that beauty education based on VR experience of beauty majors will have on expertise and practical ability, it was attempted to develop VR-based beauty subjects and secure an educational environment. A total of 106 learners participated in the study, and the online questionnaire consisted of questions about the development of VR-based beauty subjects, recognition of expertisee and practical skills, and general characteristics. The collected data were verified at the significance level of .05 using the SPSS 21.0 statistical program. As a result of frequency analysis, factor analysis, correlation, and linear regression analysis, the higher the grade, the higher the perception of VR-based beauty subjects development (p<.01). The perception of VR-based beauty subject development was related to VR-based expertise and practical skills for each sub-factor of the recognition of expertise (r=.683, p<.001), practical skills (r=.676, p<.001), and industry-related awareness (r=.543, p<.001). It was found that there was a statistically significant positive (+) correlation with related perception. In addition, it was found that the higher the awareness of VR-based beauty subjects development, the higher the expectation that expertise, practical ability, and industry-related awareness would be improved. As a result, the necessity of developing VR-based beauty subjects and expectations for course operation of majors in the beauty subjects environment were confirmed. In follow-up studies, it is necessary to expand the scope of the sample.

• Journal of Environmental Health Sciences
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• v.48 no.2
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• pp.66-74
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• 2022

Background: The health effects of particulate matter (PM_2.5) bonded with various harmful chemicals differ based on their composition, so investigating and managing their concentrations and composition is vital for long-term management. As industrial complexes emit considerable quantities of pollutants, higher PM_2.5 concentrations and chemical component effects are expected than in other places. Objectives: We investigated the concentration distribution ratios of PM_2.5 chemical components to provide basic data to inform future major emissions control and PM_2.5 reduction measures in industrial complexes. Methods: We monitored five sites near the Ansan and Siheung industrial complexes from August 2020 to July 2021. Samples were collected and analyzed twice per week in spring/winter and once per week in summer/autumn according to the National Institute of Environmental Research in the Ministry of Environments' Air Pollution Monitoring Network Installation and Operation Guidelines. We investigated and compared composition ratios of 29 ions, carbon, and elemental components in PM_2.5. Results: The analysis of PM_2.5 components at the five sites revealed that ion components accounted for the greatest total mass at approximately 50% while carbon components and elemental components contributed 23~28% and 8~10%, respectively. Among the ionic components, NO₃^- occupies the greatest proportion. OC occupies the greatest proportion of the carbon components and sulphur occupies the greatest proportion of elemental components. Conclusions: This study investigated the concentration distribution ratios of PM_2.5 chemical components in industrial complexes. We believe these results provide basic chemical component concentration ratio data for establishing future air management policies and plans for the Ansan and Siheung industrial complexes.

• The Journal of the Korea Contents Association
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• v.22 no.4
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• pp.145-158
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• 2022

Although the rapid development of technology has led to a swift increase in the number of companies using social networking services (SNS), it will not be accurate to say that they have fully "utilized" the functionality of SNS simply by "using" these services. Therefore, this study aims to increase the convenience of using digital technology and help SNS users in extending the functionality of these services beyond their regular use and thus, revitalize the field by increasing the service providers' efficiency. In this study, the Facebook usage status of a graduate school newspaper from an undisclosed university in Seoul was analyzed from February to December, 2021 using the participant observation method. The results of the study revealed the following: First, it is necessary to diversify the subject and type of content to ensure a continuous supply of quality content; Second, there is a need to examine the user categories and characteristics by utilizing SNS functionalities such as, the target reports and insights, and based on this, supply content that meets the needs of the users; Third, to resolve the problem of low levels of user participation and an inactive Facebook account, it is necessary to mobilize new marketing tools like online events. The significance of this study is that it confronts the real problems faced by some companies that cannot keep pace with market changes in a digital environment, identifies failure factors, and proposes solutions to them.

• Journal of Navigation and Port Research
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• v.46 no.3
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• pp.269-279
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• 2022

With the development of artificial intelligence, artificial intelligence is being introduced to automate systems throughout the industry. In the maritime industry, artificial intelligence is being applied step by step, through the paradigm of autonomous ships. In line with this trend, ABS and DNV have published guidelines for autonomous vessels. However, there is a possibility that the risk of artificial intelligence has not been sufficiently considered, as the classification guidelines describe the requirements from the perspective of ship operation and marine service. Thus in this study, using the standards established by the ISO/ IEC JTC1/SC42 artificial intelligence division, classification requirements are classified as the causes of risk, and a measure that can evaluate risks through the combination of risk causes and artificial intelligence metrics want to use. Through the combination of the risk causes of artificial intelligence proposed in this study and the characteristics to evaluate them, it is thought that it will be beneficial in defining and identifying the risks arising from the introduction of artificial intelligence into the marine system. It is expected that it will enable the creation of more detailed and specific safety requirements for autonomous ships.

• Journal of Navigation and Port Research
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• v.46 no.3
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• pp.280-288
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• 2022

This study examined the diagnostics of abnormalities and faults of equipment, whose rotational speed changes even during regular operation. The purpose of this study was to suggest a procedure that can properly apply machine learning to the time series data, comprising non-stationary characteristics as the rotational speed changes. Anomaly and fault diagnosis was performed using machine learning: k-Nearest Neighbor (k-NN), Support Vector Machine (SVM), and Random Forest. To compare the diagnostic accuracy, an autoencoder was used for anomaly detection and a convolution based Conv1D was additionally used for fault diagnosis. Feature vectors comprising statistical and frequency attributes were extracted, and normalization & dimensional reduction were applied to the extracted feature vectors. Changes in the diagnostic accuracy of machine learning according to feature selection, normalization, and dimensional reduction are explained. The hyperparameter optimization process and the layered structure are also described for each algorithm. Finally, results show that machine learning can accurately diagnose the failure of a variable-rotation machine under the appropriate feature treatment, although the convolution algorithms have been widely applied to the considered problem.

• Journal of Korea Entertainment Industry Association
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• v.14 no.3
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• pp.15-26
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• 2020

This study examined the effects of a social tourism information platform on platform users' experiential value and e-loyalty and performed an empirical analysis with the aim to propose methods and implications regarding what strategies can enable practical application for sustainable growth in the operation of a social tourism information platform in the future tourism industry. The results of the analysis are as follows. First, the analysis supported the hypothesis that sub-factors of a social tourism information platform, such as interactivity, information reliability, and usefulness, have statistically significant positive effects on experiential value. Second, the analysis did not support the hypothesis that the sub-factors of a social tourism information platform, such as interactivity, information reliability, and usefulness, have statistically significant positive effects on e-loyalty. Third, the analysis supported the hypothesis that experiential value has a statistically significant positive effect on e-loyalty. Consequently, tourism companies should improve customers' experiential value by supplementing their existing platforms, considering the interactivity, information reliability, and usefulness of users based on these characteristics of social tourism information platforms. To increase e-loyalty to their social tourism information platforms, tourism companies should clearly and rapidly provide the information needed by users in addition to improving the visual design of such platforms. Moreover, to increase e-loyalty, the companies can incorporate their own killer content into platforms for users to have an enjoyable time, using platforms that stimulate their interest and give pleasure and fun, and this way, they can satisfy the users' needs for experiential value.

• Journal of Korea Entertainment Industry Association
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• v.15 no.4
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• pp.349-357
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• 2021

Recently, drones are rapidly becoming common and expanding. There is a great need for diversity in whether drone flight data can be used as entertainment technology analysis data. In particular, it is necessary to check whether it is possible to analyze and utilize the flight and operation process of entertainment drones, which are developing through autonomous and intelligent methods, through data analysis and machine learning. In this paper, it was confirmed whether it can be used as a machine learning technology by using FC data in the evaluation of drones for entertainment. As a result, FC data from DJI and Parrot such as Mavic2 and Anafi were unable to analyze machine learning for entertainment. It is because data is collected at intervals of 0.1 second or more, so that it is impossible to find correlation with other data with GCS. On the other hand, it was found that machine learning technologies can be applied in the case of Fixhawk, which used an ARM processor and operates with the Nuttx OS. In the future, it is necessary to develop technologies capable of analyzing the characteristics of entertainment by dividing fixed-wing and rotary-wing flight information. For this, a model shoud be developed, and systematic big data collection and research should be conducted.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.1
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• pp.51-58
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• 2022

Drivable area detection, one of the main functions of advanced driver assistance systems, means detecting an area where a vehicle can safely drive. The drivable area detection is closely related to the safety of the driver and it requires high accuracy with real-time operation. To satisfy these conditions, V-disparity-based method is widely used to detect a drivable area by calculating the road disparity value in each row of an image. However, the V-disparity-based method can falsely detect a non-road area as a road when the disparity value is not accurate or the disparity value of the object is equal to the disparity value of the road. In a road environment including vegetation, such as a highway and a country road, the vegetation area may be falsely detected as the drivable area because the disparity characteristics of the vegetation are similar to those of the road. Therefore, this paper proposes a drivable area detection method and hardware architecture with a high accuracy in road environments including vegetation areas by reducing the number of false detections caused by V-disparity characteristic. When 289 images provided by KITTI road dataset are used to evaluate the road detection performance of the proposed method, it shows an accuracy of 90.12% and a recall of 97.96%. In addition, when the proposed hardware architecture is implemented on the FPGA platform, it uses 8925 slice registers and 7066 slice LUTs.

• Journal of Convergence for Information Technology
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• v.12 no.5
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• pp.116-125
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• 2022

Recent aspects of terrorism varies in various ways according to means, targets, and regions. In particular, the 9/11 terrorist attacks in the United States in 2001 changed the paradigm of each country's terrorism, and the South Korea also participated in the enactment and enforcement of the Anti-Terrorism Act in 2016. Based on this, CBRN terrorism is included in general terrorism, and the National Police Agency plays the role of a control tower, and a system supported by related organizations such as the Ministry of Environment is being built and operated. However, restrictions were confirmed in the organizational system, manpower composition, and equipment and materials in operation in preparation for CBRN within the police. Based on the identified limitations, we proposed improvement plans to strengthen the capacity for CBRN terrorism: establishing a dedicated CBRN organization; creating research organization; and securing additional dedicated personnel. Based on this, as an improvement plan to strengthen the capability of CBRN, the establishment of an organization dedicated to CBRN and a research organization within the National Police Agency, and expansion of electronic equipment suitable for the characteristics of CBRN were proposed. It is expected that the police's on-site response capability system for CBRN terrorism will be strengthened via the proposed improvement measures to recover the various restrictions on the response to CBRN terrorism.