• Korea Trade Review
• /
• v.47 no.3
• /
• pp.57-73
• /
• 2022

The process and change of convergence in the economy and industry with the development of digital technology and combining with new technologies is called Digital Transformation. Specifically, it refers to innovating existing businesses and services by utilizing information and communication technologies such as big data analysis, Internet of Things, cloud computing, and artificial intelligence. Digital transformation is changing the shape of business and has a wide impact on businesses and consumers in all industries. Among them, the big data and analytics market is emerging as one of the most important growth drivers of digital transformation. Integrating intelligent data into an existing business is one of the key tasks of digital transformation, and it is important to collect and monitor data and learn from the collected data in order to efficiently operate a data-based business. In developed countries overseas, research on new business models using various data accumulated at the level of government and private companies is being actively conducted. However, although the trade and import/export data collected in the domestic public sector is being accumulated in various types and ranges, the establishment of an analysis and utilization model is still in its infancy. Currently, we are living in an era of massive amounts of big data. We intend to discuss the value of trade big data possessed from the past to the present, and suggest a strategy to activate trade big data for trade digital transformation and a new direction for future trade big data research.

• Industry Promotion Research
• /
• v.8 no.4
• /
• pp.131-137
• /
• 2023

This study collected and analyzed articles related to military sex crimes covered in the news from February 2019 to May 28, 2022 in order to identify problems arising from sexual crimes in the military. In order to understand the current status of military sexual violence reported in the media, articles were collected using BIGKinds, a news big data analysis system, and using the Textom program, the study was conducted using frequency analysis by period, word cloud, and semantic network analysis techniques for keywords. The study was conducted using the technique. As a result of data analysis, first, it was confirmed that the public's attention was focused on the victims in reports related to sex crimes within the military. Second, the problem of the lukewarm system of the relevant authorities in responding to sex crimes was revealed. Third, there was a lack of support for victims of sex crimes.

• The Korean Journal of Applied Statistics
• /
• v.37 no.1
• /
• pp.87-102
• /
• 2024

Digital transformation refers to the process by which a company or organization changes or innovates its existing business model or sales activities using digital technology. This requires the use of various digital technologies - cloud computing, IoT, artificial intelligence, etc. - to strengthen competitiveness in the market, improve customer experience, and discover new businesses. In addition, in order to derive knowledge and insight about the market, customers, and production environment, it is necessary to select the right data, preprocess the data to an analyzable state, and establish the right process for systematic analysis suitable for the purpose. The usefulness of such digital data is determined by the importance of pre-processing and the correct application of exploratory data analysis (EDA), which is useful for information and hypothesis exploration and visualization of knowledge and insights. In this paper, we reexamine the philosophy and basic concepts of EDA and discuss key visualization information, information expression methods based on the grammar of graphics, and the ACCENT principle, which is the final visualization review standard, for effective visualization.

• Journal of Information Technology Services
• /
• v.23 no.1
• /
• pp.37-53
• /
• 2024

Recently, the application of microservice architecture has been increasing as information systems have shifted to cloud environments. The purpose of this paper was to analyze the case of applying microservice architecture to MES in the manufacturing field, summarize the results of how it was applied in practice, and find out the effects of the application. Based on the improvement project by applying microservice architecture to the existing steel manufacturing MES, 11 principles of microservice application were derived through literature research, and the implementation process and results were summarized according to these principles. In addition, through a comparison of systems in the service industry and the manufacturing industry, we investigated why the application of microservices was more active in the service industry and whether the application in the manufacturing industry can be expected to have the same effect. We also evaluated the results and changes in the overall system after implementation. In particular, we analyzed the SR (Service Request) processing status of users' requests for system changes and operators' requests to see how much the lead time was reduced. The results showed that 8 out of 11 microservice application principles were properly implemented according to the principles, but the remaining 3 were not applicable due to practical difficulties and organizational circumstances. Despite not following all of the principles, the project was able to be implemented without any problems, and the most noticeable change as a result of the microservices architecture was that the lead time was reduced by 9 days compared to the previous system. This proves that it is possible to quickly adapt to customer requirements, and it also proves that the system is more flexible and scalable than the existing monolithic system.

• International Journal of Internet, Broadcasting and Communication
• /
• v.16 no.2
• /
• pp.267-277
• /
• 2024

This paper explores the use of machine learning in game production to create goal-oriented, realistic animations for skeleton monsters. The purpose of this research is to enhance realism by implementing intelligent movements in monsters within game development. To achieve this, we designed and implemented a learning model for skeleton monsters using reinforcement learning algorithms. During the machine learning process, various reward conditions were established, including the monster's speed, direction, leg movements, and goal contact. The use of configurable joints introduced physical constraints. The experimental method validated performance through seven statistical graphs generated using machine learning methods. The results demonstrated that the developed model allows skeleton monsters to move to their target points efficiently and with natural animation. This paper has implemented a method for creating game monster animations using machine learning, which can be applied in various gaming environments in the future. The year 2024 is expected to bring expanded innovation in the gaming industry. Currently, advancements in technology such as virtual reality, AI, and cloud computing are redefining the sector, providing new experiences and various opportunities. Innovative content optimized for this period is needed to offer new gaming experiences. A high level of interaction and realism, along with the immersion and fun it induces, must be established as the foundation for the environment in which these can be implemented. Recent advancements in AI technology are significantly impacting the gaming industry. By applying many elements necessary for game development, AI can efficiently optimize the game production environment. Through this research, We demonstrate that the application of machine learning to Unity and game engines in game development can contribute to creating more dynamic and realistic game environments. To ensure that VR gaming does not end as a mere craze, we propose new methods in this study to enhance realism and immersion, thereby increasing enjoyment for continuous user engagement.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
• /
• v.37 no.5
• /
• pp.486-493
• /
• 2024

Lighting has been used for a long time as a medium to convey brightness from darkness, and through incandescent lamps and fluorescent lamps, LED light sources have now become the standard in the lighting industry. Recently, the lighting equipment industry has been undergoing rapid digital transformation, starting with smart lighting, and is evolving into smart lighting customized for individuals and spaces through the development of IoT technology, cloud-based services, and data analysis. However, the blue light emitted from digital devices (computers, smartphones, tablets, etc.) or LED lights stimulates the melanopsin in the optic ganglion cells in the retina of the eye, which in turn stimulates the secretion of melatonin through the pineal gland, which regulates the secretion of melatonin. This can reduce sleep quality or disrupt biological rhythms. This interaction between blue light and melatonin has such a significant impact on human sleep patterns and overall health that it is essential to reduce exposure to blue light, especially in the evening. Human-centered lighting refers to lighting that takes into account the effects of light on the physical and mental areas, such as human activity and awakening, improvement of sleep quality, and health management. Many research institutes study the effects in the visible area and the non-visible area. By studying the impact, it is expected to improve the quality of human life. In this study, we plan to study ways to implement human-centered lighting by collecting sunrise and sunset data and linking commercialized LED packages and control devices with open-source hardware.

• The KIPS Transactions:PartD
• /
• v.14D no.1 s.111
• /
• pp.121-130
• /
• 2007

in a software development, the design or architecture prior to implementing the software is essential for the success. This paper presents a case that we successfully designed a software architecture of radiation monitoring system (RMS) for HANARO research reactor currently operating in KAERI by applying the quality attribute-driven design method which is modified from the attribute-driven design (ADD) introduced by Bass[1]. The quality attribute-driven design method consists of following procedures: eliciting functionality and quality requirements of system as architecture drivers, selecting tactics to satisfy the drivers, determining architectures based on the tactics, and implementing and validating the architectures. The availability, maintainability, and interchangeability were elicited as duality requirements, hot-standby dual servers and weak-coupled modulization were selected as tactics, and client-server structure and object-oriented data processing structure were determined at architectures for the RMS. The architecture was implemented using Adroit which is a commercial off-the-shelf software tool and was validated based on performing the function-oriented testing. We found that the design method in this paper is an efficient method for a project which has constraints such as low budget and short period of development time. The architecture will be reused for the development of other RMS in KAERI. Further works are necessary to quantitatively evaluate the architecture.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.12 no.3
• /
• pp.1341-1349
• /
• 2011

This research is focused on an analysis on the structure of RAW image file and the development of a RAW image file viewer for an embedded device. Recently, several RAW image file formats are being used for saving and displaying the images created by various DSLR cameras, and the necessity of handing RAW images in mobile multimedia devices is increasing. For the development of RAW image decoding/encoding library applicable to WinCE-based embedded devices viewer, an analysis of RAW image file formats, such as CRW, CR2, PEF, NEF, MRW, have been performed because their formats are not released in public. By using the library, the analysis software which can extract RAW image data, 2~3 JPEG image files and other informations such as the specification of a camera and various photographic parameters from RAW image files, were developped and a RAW image file viewer which can run in WinCE-based embedded devices. The experimental result has shown that the viewer could encode and decode RAW image files successfully and it took approximately 10secs to load them to the screen in S3C6410 based embedded platform. The outcomes of this research cloud be a good information and solution to multimedia application developers.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.11
• /
• pp.672-682
• /
• 2020

The Korea Nowadays, which is research on digital twin technology for efficient operation in various industrial/manufacturing sites, is being actively conducted, and gradual depletion of fossil fuels and environmental pollution issues require new renewable/eco-friendly power generation methods, such as wave power plants. In wave power generation, however, which generates electricity from the energy of waves, it is very important to understand and predict the amount of power generation and operational efficiency factors, such as breakdown, because these are closely related by wave energy with high variability. Therefore, it is necessary to derive a meaningful correlation between highly volatile data, such as wave height data and sensor data in an oscillating water column (OWC) chamber. Secondly, the methodological study, which can predict the desired information, should be conducted by learning the prediction situation with the extracted data based on the derived correlation. This study designed a workflow-based training model using a machine learning framework to predict the pressure of the OWC. In addition, the validity of the pressure prediction analysis was verified through a verification and evaluation dataset using an IoT sensor data to enable smart operation and maintenance with the digital twin of the wave generation system.

• Journal of Digital Convergence
• /
• v.15 no.10
• /
• pp.455-465
• /
• 2017

This study focuses on design development and verification through virtual simulation based on 3D model data in the cloud platform as a method of utilization of engineering technology of design in the fourth industrial revolution era. The goal of research is to develop and examine a design for the needs of the target that has never been met before through virtual simulations that can be conducted in practice. As a research method, we analyzed secondary data to identify the needs of the target, and did literature research for the ergonomic data and target body development stages. In addition, the design development process of this study was shown meaningful result in design, structure, safety, material, durability through loop test of 7 virtual simulations. This study can be applied to the automated process system based on 3D model data in the 4th industrial revolution era and can be used as an element of the cyber physics system for the additional research.