• Korean small business review
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• v.43 no.1
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• pp.51-83
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• 2021

This study empirically examined how the technology innovation competence of the 4th Industrial Revolution Enterprises affects management performance. It also analyzed whether there would be any difference in business performance between the 4th Industrial Revolution Enterprises and the non-4th Industrial Revolution Enterprises. The samples for analysis were analyzed using in-situ data of 2,543 enterprises classified as technical innovation enterprises and the 4th Industrial Revolution Enterprises through Korea Technology Finance Corporation's in-house technical evaluation. Variables for technology innovation competence were analyzed using variables such as the size of manpower of research and development, the level of research and development organizations, the number of intellectual property rights, the ratio of intangible assets, the amount of knowledge properties, the amount of research and development investment, and the intensiveness degree of research and development. In terms of the impact of the 4th Industrial Revolution Enterprises' technology innovation competence on business performance, all factors except for the level of research and development organizations were found to affect business performance, which supported the study hypothesis. In particular, it was confirmed that the amount of knowledge properties has had a relatively greater impact on business performance. In addition, the average comparative analysis between the 4th Industrial Revolution Enterprises and the non-4th Industrial Revolution Enterprises confirmed that the 4th Industrial Revolution Enterprises conducted higher values in the business performance.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.896-905
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• 2021

In the field of SIEM(Security information and event management), many studies try to use a feedback system to solve lack of completeness of training data and false positives of new attack events that occur in the actual operation. However, the current feedback system requires too much human inputs to improve the running model and even so, those feedback from inexperienced analysts can affect the model performance negatively. Therefore, we propose "active model improving feedback technology" to solve the shortage of security analyst manpower, increasing false positive rates and degrading model performance. First, we cluster similar predicted events during the operation, calculate feedback priorities for those clusters and select and provide representative events from those highly prioritized clusters using XAI (eXplainable AI)-based event visualization. Once these events are feedbacked, we exclude less analogous events and then propagate the feedback throughout the clusters. Finally, these events are incrementally trained by an existing model. To verify the effectiveness of our proposal, we compared three distinct scenarios using PKDD2007 and CSIC2012. As a result, our proposal confirmed a 30% higher performance in all indicators compared to that of the model with no feedback and the current feedback system.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.66-75
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• 2021

The research is centered towards analyzing the usage status of YouTube platform and the nature of content supplied to YouTube by selecting Korean two Traffic Broadcastings Based on TBS(Traffic Broadcasting System) and TBN(Traffic Broadcasting Network). TBS operates 'Citizen's Broadcasting', which has 1.1 million subscribers among 13 YouTube channels, as its main channel. TBN has only 15,000 subscribers to its main 'TBN Tong', and YouTube channels in 12 local networks. TBS which has a dedicated YouTube manpower, is far ahead of TBN in terms of YouTube channel management and content composition. Both broadcasters are passive about creating new media content due to job stability. For the development of the YouTube platform for these two broadcasters, organizational changes within traffic broadcasting and changes in the perception of members are required, and live broadcasting and discovery of star creators are required. In the changing media environment two traffic broadcastings need a program distribution strategy that can be included in various media platforms.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.1
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• pp.77-100
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• 2022

In the era of low growth, many provincial cities are experiencing population decline and aging. Population decline phenomena such as reduction of productive manpower, reduction of finances, deterioration of quality of life, and collapse of the community base are occurring in a chain and are being pushed to the brink of extinction of the cities. This study aims to propose a methodology to objectively estimate the employment creation centers and setting the basic unit of industrial-centered zoning by applying spatial statistical techniques and GIS for the application of the compact city plan as an efficient spatial management policy in a city with a declining population. In details, based on reviewing previous studies on compact city, 'employment complex index(ECI)' were defined considering the number of workers, the number of settlers, and the area of development land, the employment creation center was estimated by applying the 'Local Moran's I' and 'Getis-Ord's Hot-Spot Analysis'. As a case study, changes in the four years of 2013, 2015, 2017, and 2019 were compared and analyzed for Changwon City. As a result, it was confirmed that the employment creation center is becoming compacted and polycentric, which is a significant result that reflects the actual situation well. This results provide the basic data for functional and institutional territorial governance for the regional revitalization platform, and provide meaningful information necessary for spatial policy decision-making, such as population reduction, regional gross domestic product, and public facility arrangement that can respond to energy savings, transportation plans, and medical and health plans.

• Journal of the Korea Institute of Building Construction
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• v.22 no.6
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• pp.565-575
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• 2022

Thanks to the latest developments in digital architectural technologies, free-form designs that maximize the creativity of architects have rapidly increased. However, there are a lot of difficulties in forming various free-form curved surfaces. In panelizing to produce free forms, the methods of mesh, developable surface, tessellation and subdivision are applied. The process of applying such panelizing methods when producing free-form panels is complex, time-consuming and requires a vast amount of manpower when extracting production data. Therefore, algorithms are needed to quickly and systematically extract production data that are needed for panel production after a free-form building is designed. In this respect, the purpose of this study is to propose mathematical algorithms for the automatic generation of production data of free-form panels in consideration of the building model, performance of production equipment and pattern information. To accomplish this, mathematical algorithms were suggested upon panelizing, and production data for a CNC machine were extracted by mapping as free-form curved surfaces. The study's findings may contribute to improved productivity and reduced cost by realizing the automatic generation of data for production of free-form concrete panels.

• Journal of the Korean Geotechnical Society
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• v.38 no.11
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• pp.43-54
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• 2022

The settlement at the railroad foundation is often the leading cause of track irregularity and potential derailment. The control of such deformation is considered necessary in track maintenance practice. Nevertheless, the monitoring process performed by in situ surveying requires an excessive amount of manpower and cost. The InSAR, a remote sensing technique by RADAR satellite, is used to overcome such a burden. The PS-InSAR technique is preferred for a long-term precise monitoring method. However, this study aims to obtain relatively brief analysis results from only two satellite images using the D-InSAR technique, while a minimum of 25 images are required for PS-InSAR. This study verifies the precision of D-InSAR within a few millimeters by inspecting railroad facilities and land settlements in Korea Railroad Research Institute's test track with images from TerraSAR-X Satellite. Multiple corner reflectors were adopted and installed on an embankment and the building roof to raise the surface reflectivity. Those reflectors were slightly adjusted periodically to verify the detecting performance. The results revealed the optimum distance between corner reflectors. Further, the deformation of railway tracks, slopes, and concrete structures was analyzed successively. In conclusion, this study indicates that the D-InSAR technique effectively monitors the short-term deformation of a broad area such as railway structures.

• Journal of the Korean Society of Radiology
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• v.16 no.7
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• pp.985-993
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• 2022

This study was conducted to compare and evaluate the expectations and satisfaction of clinical practice for students who conducted practice at clinical practice institutions of various sizes before and after COVID-19, and to suggest future clinical practice guidance methods and operation directions. There was a significant difference in the evaluation of satisfaction with practice before and after COVID-19, especially after the evaluation of satisfaction with practice guidance, practice environment, and practice time. As a result of analyzing the decisive influencing factors related to practice satisfaction, students who conducted practice at university hospitals highly evaluated the institutional environmental factors, and students who conducted practice at small and medium-sized hospitals showed high satisfaction in participation-oriented practice. Therefore, it is thought that practice that utilizes the strengths and weaknesses of university hospitals and small and medium-sized hospitals will be more effective than clinical practice that relies only on university hospitals. However, in order to diversify the training institution to small and medium-sized hospitals, it is necessary to create a manual on standardized training courses, training methods, and evaluation methods suitable for the training goals and curriculum, and provide them to the institution. In addition, if it is operated through sufficient exchange of opinions and consultation with institutions, schools will be able to obtain opportunities to cultivate practical talents, and small and medium-sized hospitals with difficulties in expanding manpower will be able to secure excellent human resources first.

• Journal of Korean Society for Quality Management
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• v.50 no.4
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• pp.647-664
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• 2022

Purpose: The purpose of this study is to derive major policies that domestic small and medium-sized manufacturing companies should consider to maximize productivity and quality improvement by utilizing manufacturing data and AI, and to find priorities and implications. Methods: In this study, domestic and international issues and literature review by country were conducted to derive major considerations such as manufacturing AI technology, manufacturing AI talent, manufacturing AI data and manufacturing AI ecosystem. Additionally, the questionnaire survey targeting 46 experts of manufacturing data and AI industry were conducted. Finally, the major considerations and detailed factors importance were derived by applying the Analytic Hierarchy Process (AHP). Results: As a result of the study, it was found that 'manufacturing AI technology', 'manufacturing AI talent', 'manufacturing AI data', and 'manufacturing AI ecosystem' exist as key considerations for domestic manufacturing AI. After empirical analysis, the importance of the four key considerations was found to be 'manufacturing AI ecosystem (0.272)', 'manufacturing AI data (0.265)', 'manufacturing AI technology (0.233)', and 'manufacturing AI talent (0.230)'. The importance of the derived four viewpoints is maintained at a similar level. In addition, looking at the detailed variables with the highest importance for each of the four perspectives, 'Best Practice', 'manufacturing data quality management regime, 'manufacturing data collection infrastructure', and 'manufacturing AI manpower level of solution providers' were found. Conclusion: For the sustainable growth of the domestic manufacturing AI ecosystem, it should be possible to develop and promote manufacturing AI policies in a balanced way by considering all four derived viewpoints. This paper is expected to be used as an effective guideline when developing policies for upgrading manufacturing through domestic manufacturing data and AI in the future.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.4
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• pp.49-57
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• 2022

The government is making great efforts to prevent crimes such as missing children by using public CCTVs. However, there is a shortage of operating manpower, weakening of concentration due to long-term concentration, and difficulty in tracking. In addition, applying real-time object search, re-identification, and tracking through a deep learning algorithm showed a phenomenon of increased parameters and insufficient memory for speed reduction due to complex network analysis. In this paper, we designed the network to improve speed and save memory through the application of Yolo v4, which can recognize real-time objects, and the application of Batch and TensorRT technology. In this thesis, based on the research on these advanced algorithms, OSNet re-ranking and K-reciprocal nearest neighbor for re-identification, Jaccard distance dissimilarity measurement algorithm for correlation, etc. are developed and used in the solution of CCTV national safety identification and tracking system. As a result, we propose a solution that can track objects by recognizing and re-identification objects in real-time within situation of a Korean public multi-CCTV environment through a set of algorithm combinations.

• Journal of Space Technology and Applications
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• v.2 no.2
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• pp.81-103
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• 2022

In this paper, the contents of the design and development process of the 6U micro-satellite Snipe (SNIPE, national name Toyosat; small scale magnetospheric and Ionospheric plasma experiment ), which was developed to observe the near-global space environment through polarization flight for the first time in Korea, were described. Snipe performs transversal flight to observe the Earth's surrounding space environment in three dimensions, and aims to simultaneously observe the space plasma density and temperature in the ionosphere, as well as temporal changes in the solar magnetic field and electromagnetic waves. In this way, it was developed by dividing it into a test certification model (EQM) and a flight model (FM) to perform the actual mission for at least six months, away from developing a cube satellite for short-term space technology verification or manpower training. Currently, Snipe, which has completed the development of a total of four FM and completed all space environment tests, is scheduled to launch 2023. In this paper, we introduce the design contents and development process of the Snipe satellite body ahead of launch, and hope that it will be a useful reference for the development of 6U-class micro-satellite for full-scale mission in Korea.