• Journal of Korean Society of Industrial and Systems Engineering
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• v.25 no.3
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• pp.58-63
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• 2002

The Internet, as a commercial tool, presented a new market that connects producers with consumers through the E-commerce. Now, E-commerce spreads over almost all industries through the Internet excluding some. This research indicates the reason why the E-commerce is not activated in agricultural Industry, which is less developed than other industries. And it suggests a good example of E-commerce on the agricultural products combining on and off line markets. In addition, data-mining technique is suggested to analyze whole information in system.

• Geomechanics and Engineering
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• v.29 no.6
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• pp.627-643
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• 2022

Water-rock interactions have a significant influence on the mechanical behavior of rocks. In this study, uniaxial compression and tension tests on different water-treated sandstone samples were conducted. Acoustic emission (AE) monitoring and micro-pore structure detection were carried out. Water-rock interactions and their effects on rock mechanical behavior were discussed. The results indicate that water content significantly weakens rock mechanical strength. The sensitivity of the mechanical parameters to water treatment, from high to low, are Poisson ratio (𝜇), uniaxial tensile strength (UTS), uniaxial compressive strength (UCS), elastic modulus (E), and peak strain (𝜀). After water treatment, AE activities and the shear crack percentage are reduced, the angles between macro fractures and loading direction are minimized, the dynamic phenomenon during loading is weakened, and the failure mode changes from a mixed tensile-shear type to a tensile one. Due to the softening, lubrication, and water wedge effects in water-rock interactions, water content increases pore size, promotes crack development, and weakens micro-pore structures. Further damage of rocks in fractured and caved zones due to the water-rock interactions leads to an extra load on the adjoining coal and rock masses, which will increase the risk of dynamic disasters.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.1
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• pp.1-12
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• 2010

Recently, large amount of information in IDS(Intrusion Detection System) can be un manageable and also be mixed with false prediction error. In this paper, we propose a data mining methodology for IDS, which contains uncertainty based on training process and post-processing analysis additionally. Our system is trained to classify the existing attack for misuse detection, to detect the new attack pattern for anomaly detection, and to define border patter between attack and normal pattern. In experimental results show that our approach improve the performance against existing attacks and new attacks,from 0.62 to 0.84 about 35%.

• Tunnel and Underground Space
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• v.32 no.1
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• pp.78-92
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• 2022

In this study, we proposed a diagnostics and assessment model for mining sites that can evaluate the smart mining technology level in a systematic and structured way. For this, the maturity of the smart mining was defined, and detailed assessment items of the diagnostics and assessment model for smart mining were derived by considering the smart factory diagnostics and assessment model (KS X 9001-3) used in the manufacturing industry. While maintaining the existing system, the existing 46 detailed assessment items were modified to be suitable for mining. As a result, a total of 29 detailed assessment items were derived in the areas of promotion strategy, process, information system and automation, and performance. Based on this, a questionnaire was designed to diagnose the level of smart mining technology, and assessment was performed by applying it to domestic iron mines. The level of smart mining technology in the study area was found to be level 2, and it could be inferred that it was about 40% lower than the average smart level of the general manufacturing industry. In addition, by using the developed model, it was possible to recognize the weak points of the mine at each stage of the introduction, operation, and advancement of smart mining, and to suggest investment and improvement directions.

• The Journal of Information Systems
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• v.30 no.3
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• pp.21-45
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• 2021

Purpose This paper analyzed the impacts of domestic stock market by a global pandemic such as COVID-19. We investigated how the overall pattern of the stock market changed due to the impact of the COVID-19 pandemic. In particular, we analyzed in depth the pattern of stock price, as well, tried to find what factors affect on stock market index(KOSPI) in the healthcare industry due to the COVID-19 pandemic. Design/methodology/approach We built a data warehouse from the databases in various industrial and economic fields to analyze the changes in the KOSPI due to COVID-19, particularly, the changes in the healthcare industry centered on bio-medicine. We collected daily stock price data of the KOSPI centered on the KOSPI-200 about two years before and one year after the outbreak of COVID-19. In addition, we also collected various news related to COVID-19 from the stock market by applying text mining techniques. We designed four experimental data sets to develop decision tree-based prediction models. Findings All prediction models from the four data sets showed the significant predictive power with explainable decision tree models. In addition, we derived significant 10 to 14 decision rules for each prediction model. The experimental results showed that the decision rules were enough to explain the domestic healthcare stock market patterns for before and after COVID-19.

• Journal of Information Technology Services
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• v.15 no.3
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• pp.71-95
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• 2016

In recent years, text mining has been used to extract meaningful insights from the large volume of unstructured text data sets of various domains. As one of the most representative text mining applications, topic modeling has been widely used to extract main topics in the form of a set of keywords extracted from a large collection of documents. In general, topic modeling is performed according to the weighted frequency of words in a document corpus. However, general topic modeling cannot discover the relation between documents if the documents share only a few terms, although the documents are in fact strongly related from a particular perspective. For instance, a document about "sexual offense" and another document about "silver industry for aged persons" might not be classified into the same topic because they may not share many key terms. However, these two documents can be strongly related from the R&D perspective because some technologies, such as "RF Tag," "CCTV," and "Heart Rate Sensor," are core components of both "sexual offense" and "silver industry." Thus, in this study, we attempted to discover the differences between the results of general topic modeling and R&D perspective topic modeling. Furthermore, we package social issues from the R&D perspective and present a prototype system, which provides a package of news articles for each R&D issue. Finally, we analyze the quality of R&D perspective topic modeling and provide the results of inter- and intra-topic analysis.

• Tunnel and Underground Space
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• v.9 no.3
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• pp.230-237
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• 1999

Production of limestone for cement in Kangwon and Chungbuk areas reaches over 80 million tonnes per year. However, many regulatory activities for preservation of the environment against potential hazardous impacts from the open pit mining make it difficult for the industry. With recent improvement of the mining methods and working conditions, the regulations related to the quarrying of limestone may need to be revised. Methods for reducing environmental hazards are proposed in this paper, with some suggestions concerning the revision of related regulations. This study is expected to serve as a practical solution for the cement industry in balance of preservation and development.

• Journal of Korean Society for Quality Management
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• v.49 no.1
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• pp.97-112
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• 2021

Purpose: The purpose of this paper is to analyze the technology convergence and its characteristics, focusing on the defense technologies in South Korea. Methods: Patents applied by the Agency for Defense Development (ADD) during 1979~2019 were utilized in this paper. Information Entropy analysis has been conducted on the patents to analyze the usability and potential for development. To analyze the trend of technology convergence in defense technologies, Social Network Analysis(SNA) and Association Rule Mining Analysis were applied to the co-occurrence networks of International Patent Classification (IPC) codes. Results: The results show that sensor, communication, and aviation technologies played a key role in recent development of defense science and technology. The co-occurrence network analysis also showed that the convergence has gradually enhanced over time, and the convergence between different technology sectors largely emerged, showing that the convergence has been diversified. Conclusion: By analyzing the patents of the defense technologies during the last 30 years, this study presents the comprehensive perspectives on trends and characteristics of technology convergence in defense industry. The results of this study are expected to be used as a guideline for decision making in the government's R&D policies in defence industry.

• Fashion & Textile Research Journal
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• v.24 no.5
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• pp.545-556
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• 2022

To overcome the pandemic, a new strategy for innovation is in demand throughout the value chains of the fashion industry that emphasize the importance of fashion technology. Accordingly, as various viewpoints and fields of debate are unfolding to consider the direction of change led by fashion technology, it is necessary to make an active value judgment precedent by understanding the differences between various opinions. This study aims to derive keywords from fashion technology used during the pandemic, to infer the characteristics of each type of perspective and to understand their characteristics. For the research, this study combines text mining analysis and content analysis. Text mining analysis is used to find statistical patterns by collecting keywords from big data from online media, and content analysis is used to interpret the data qualitatively. After analyzing the results of this study, the following observations are made. First, the perspective of positive acceptance seeks to maximize the perception and sensory action of fashion through technology; this amplifies experience, an opportunity for innovation and efficiency. Second, critical vigilance highlights the side effects of radical changes in fashion technology, characterized by concerns about capital-centered polarization, threats to human rights, and infringement of creative thinking. Lastly, the perspective of gradual adoption is the gradual convergence of technologies, characterized by the pursuit of an appropriate balance.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.3
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• pp.291-298
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• 2014

Demand forecasting plays a key role in overall business activities such as production planning, distribution management, and inventory management. Especially, for a fast-changing environment of the clothing industry, logical forecasting techniques are required. In this study, we propose a procedure to predict product life cycle using data mining algorithms. The proposed procedure involves three steps : extracting key variables from profiles, clustering, and classification. The effectiveness and applicability of the proposed procedure were demonstrated through a real data from a leading clothing company in Korea.