• Journal of the Korean Society of Industry Convergence
• /
• v.20 no.2
• /
• pp.125-132
• /
• 2017

The slope of the road in the forest area has a characteristic of steep slope, so natural disasters such as slope collapse occur. The slope displacement observation technique according to landslide is being studied as a method to observe a wide area and a method to observe a small area. This is a study on high-precision digital map generation using ground LiDAR. It is possible to create a high - precision digital map by minimizing the US side using the 3D LiDAR in the steep slope area where the GPS and Total Station measurement are difficult in the maintenance of the danger slope area. It is difficult to objectively evaluate whether the contour lines generated by LiDAR are correct and it is considered necessary to construct a test bed for this purpose. Based on this study, if terrain changes such as landslides occur in the future, it will be useful for measuring slope displacement.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.19 no.3
• /
• pp.233-244
• /
• 2023

Although artificial intelligence and machine learning technologies have been used in various fields, problems with personal information protection have arisen based on centralized data collection and processing. Federated learning has been proposed to solve this problem. Federated learning is a process in which clients who own data in a distributed data environment learn a model using their own data and collectively create an artificial intelligence model by centrally collecting learning results. Unlike the centralized method, Federated learning has the advantage of not having to send the client's data to the central server. In this paper, we quantitatively present the performance improvement when federated learning is applied using the building change detection learning data. As a result, it has been confirmed that the performance when federated learning was applied was about 29% higher on average than the performance when it was not applied. As a future work, we plan to propose a method that can effectively reduce the number of federated learning rounds to improve the convergence time of federated learning.

• Journal of the Korean Society of Industry Convergence
• /
• v.25 no.3
• /
• pp.397-406
• /
• 2022

Recently, research and development to revitalize smart construction are being actively carried out. Accordingly, 3D mapping technology that digitizes construction site is drawing attention. To create a 3D digital map for construction site a point cloud generation method based on LiDAR(Light detection and ranging) using MMS(Mobile mapping system) is mainly used. The purpose of this study is to analyze the accuracy of MMS LiDAR-based point cloud data. As a result, accuracy of MMS point cloud data was analyzed as dx = 0.048m, dy = 0.018m, dz = 0.045m on average. In future studies, accuracy comparison of point cloud data produced via UAV(Unmanned aerial vegicle) photogrammetry and MMS LiDAR should be studied.

• Convergence Security Journal
• /
• v.22 no.4
• /
• pp.75-84
• /
• 2022

In the 4th industry, drones are being used while having a close relationship with our lives. The development and use of various drones suggests a new paradigm for the domestic industry in the future, and is expected to become more advanced and scientific. Meanwhile, in the field of defense, efforts are being made in various ways to overcome the social phenomenon of reduced service resources. It is concentrating its efforts on strengthening the national defense power by preparing an exit strategy to supplement the shortage of service resources and to maintain and improve combat power, and by combining various science and technology related to the 4th industry. The military is planning to reinforce its combat power in connection with future industries to effectively respond and perform missions in preparation for the future combat aspects that have been researched and planned, and is planning an unmanned combat system for the science and technology army by investing a separate budget. Therefore, we systematically introduce and utilize drones, which are the core of the unmanned combat system, to create more active combat power and seek countermeasures for the battle vacuum, It is expected to provide a new paradigm for the battlefield when using advanced technology developed in the private sector and grafting it to the military sector.

• Journal of Veterinary Science
• /
• v.25 no.1
• /
• pp.10.1-10.11
• /
• 2024

In livestock industry, there is growing interest in methods to increase the production efficiency of livestock to address food shortages, given the increasing global population. With the advancements in gene engineering technology, it is a valuable tool and has been intensively utilized in research specifically focused on human disease. In historically, this technology has been used with livestock to create human disease models or to produce recombinant proteins from their byproducts. However, in recent years, utilizing gene editing technology, cattle with identified genes related to productivity can be edited, thereby enhancing productivity in response to climate change or specific disease instead of producing recombinant proteins. Furthermore, with the advancement in the efficiency of gene editing, it has become possible to edit multiple genes simultaneously. This cattle breed improvement has been achieved by discovering the genes through the comprehensive analysis of the entire genome of cattle. The cattle industry has been able to address gene bottlenecks that were previously impossible through conventional breeding systems. This review concludes that gene editing is necessary to expand the cattle industry, improving productivity in the future. Additionally, the enhancement of cattle through gene editing is expected to contribute to addressing environmental challenges associated with the cattle industry. Further research and development in gene editing, coupled with genomic analysis technologies, will significantly contribute to solving issues that conventional breeding systems have not been able to address.

• International journal of advanced smart convergence
• /
• v.10 no.4
• /
• pp.84-97
• /
• 2021

Digital twins are one of the promising digital technologies used to facilitate digital transformation. Therefore, it needs to continually be developed remain relevant in industry and academia. Consolidation of research is required to create a common understanding of the topic and to ensure that future research is built upon a solid foundation. Based on a bibliometric review and a thematic analysis of 217 publications on digital twins from the past two decades, this paper creates and analyzes a visual knowledge map and proposes areas for further research. To comprehensively analyze the development trends and research trends of digital twins, we performed statistical analysis of the relevant literature on digital twins within the core collection database of Web of Science. Through our research, we have shown that the current situation, trends, and hotspots of digital twin research were analyzed via CiteSpace. This study demonstrates that research on digital twins is rapidly growing in popularity, that the output of the research depends largely on the core group of authors conducting it, and that digital twins warrant cross-domain and cross-disciplinary research pathways.

• Journal of Intelligence and Information Systems
• /
• v.21 no.1
• /
• pp.65-82
• /
• 2015

Recently, there has been a surge of interest in finding core issues and analyzing emerging trends for the future. This represents efforts to devise national strategies and policies based on the selection of promising areas that can create economic and social added value. The existing studies, including those dedicated to the discovery of future promising fields, have mostly been dependent on qualitative research methods such as literature review and expert judgement. Deriving results from large amounts of information under this approach is both costly and time consuming. Efforts have been made to make up for the weaknesses of the conventional qualitative analysis approach designed to select key promising areas through discovery of future core issues and emerging trend analysis in various areas of academic research. There needs to be a paradigm shift in toward implementing qualitative research methods along with quantitative research methods like text mining in a mutually complementary manner. The change is to ensure objective and practical emerging trend analysis results based on large amounts of data. However, even such studies have had shortcoming related to their dependence on simple keywords for analysis, which makes it difficult to derive meaning from data. Besides, no study has been carried out so far to develop core issues and analyze emerging trends in special domains like the aviation industry. The change used to implement recent studies is being witnessed in various areas such as the steel industry, the information and communications technology industry, the construction industry in architectural engineering and so on. This study focused on retrieving aviation-related core issues and emerging trends from overall research papers pertaining to aviation through text mining, which is one of the big data analysis techniques. In this manner, the promising future areas for the air transport industry are selected based on objective data from aviation-related research papers. In order to compensate for the difficulties in grasping the meaning of single words in emerging trend analysis at keyword levels, this study will adopt topic analysis, which is a technique used to find out general themes latent in text document sets. The analysis will lead to the extraction of topics, which represent keyword sets, thereby discovering core issues and conducting emerging trend analysis. Based on the issues, it identified aviation-related research trends and selected the promising areas for the future. Research on core issue retrieval and emerging trend analysis for the aviation industry based on big data analysis is still in its incipient stages. So, the analysis targets for this study are restricted to data from aviation-related research papers. However, it has significance in that it prepared a quantitative analysis model for continuously monitoring the derived core issues and presenting directions regarding the areas with good prospects for the future. In the future, the scope is slated to expand to cover relevant domestic or international news articles and bidding information as well, thus increasing the reliability of analysis results. On the basis of the topic analysis results, core issues for the aviation industry will be determined. Then, emerging trend analysis for the issues will be implemented by year in order to identify the changes they undergo in time series. Through these procedures, this study aims to prepare a system for developing key promising areas for the future aviation industry as well as for ensuring rapid response. Additionally, the promising areas selected based on the aforementioned results and the analysis of pertinent policy research reports will be compared with the areas in which the actual government investments are made. The results from this comparative analysis are expected to make useful reference materials for future policy development and budget establishment.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.42 no.1
• /
• pp.148-158
• /
• 2018

This study analyzes recent trends in fashion retailing instigated by the fourth industrial revolution and approaches the trends in terms of the convergence of big data and artificial intelligence. The findings are as below. First, companies like 'Edited' and 'Stylumia' offer solutions that support the strategic decisions of fashion brands and fashion retailers by analyzing big data using artificial intelligence. Second, the convergence of big data and artificial intelligence scales personalized service on the web as examples of 'Coded Couture', 'StitchFix', and 'Thread'. Third, the insights gained from artificial intelligence and big data help create new fashion retailing platforms such as 'Botshop' and 'Lyst'. Last, artificial intelligence and big data assist with design. 'Ivyrevel' designs digital fashion, assisted by a macroscopic perspective on fashion trends, market and consumers through the analysis of big data. The Fourth Industrial Revolution brings changes across all industries that will likely accelerate. The fashion industry is also undergoing many changes with advancements in scientific technology. The convergence of big data and artificial intelligence will play a key role in the future of fast-moving industry like fashion, where fickle tastes of consumers are the main drivers.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.27 no.1
• /
• pp.80-93
• /
• 2024

This study attempted to analyze the factors that influence the participation of beneficiary companies in the government's defense industry promotion support project. To this end, experimental data were analyzed by constructing a prediction model consisting of highly important variables in beneficiary company decisions among various company information using the decision tree model, one of the data mining techniques. In addition, various rules were derived to determine the beneficiary companies of the government's support project using the analysis results expressed as decision trees. Three policy measures were presented based on the important rules that repeatedly appear in different predictive models to increase the effect of the government's industrial development. Using the analysis methods presented in this study and the determinants of the beneficiary companies of the government support project will help create a sustainable future defense industry growth environment.

• The Research Journal of the Costume Culture
• /
• v.15 no.6
• /
• pp.952-964
• /
• 2007

This study is about the design for environment which is central social interest in recent days. This study focused on both experimental designs which convey meanings and practical designs which can be produced within the fashion industry and then influence on the wide range of consumer, human and surrounding environment. The purposes of this study are to categorize national and global fashion designs for environment, to analyze data based on the fashion pipeline from planning to discard, to suggest systematic actions, and to establish fashion design for environment model. Through these processes, this study helps in making fashion designs for environment more understandable, and demonstrates one future direction for using environment as fashion industry's innovative strategy. This study attempts to create business and at the same time suggests design actions based on social belief. The results of this study are following. Fashion designs for environment were categorized by organic fabric, new-to-the-world fabric, reduce, multi-function, reproduce, order-made, recycle, and reuse. The results show that fashion designs for environment have been implemented throughout the fashion pipeline, and applied the concepts of design for environment including green, sustainable slow, and natural design principles. Furthermore, labelling and service from supply side, green purchasing from demand side, and integration from both sides are suggested as company's and society's systematic actions.