• Geomechanics and Engineering
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• v.28 no.6
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• pp.613-624
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• 2022

A study of the evolution of overburden fractures under the solid-fluid coupling state was conducted based on the geological and mining characteristics of the coal seam depth, weak strata cementation, and high-intensity mining in the mining areas of West China. These mining characteristics are key to achieving water conservation during mining or establishing groundwater reservoirs in coal mines. Based on the engineering background of the Daliuta Coal Mine, a non-hydrophilic simulation material suitable for simulating the weakly cemented rock masses in this area was developed, and a physical simulation test was carried out using a water-sand gushing test system. The study explored the spatial distribution and dynamic evolution of the fractured zone in the mining overburden under the coupling of stress and seepage. The experimental results show that the mining overburden can be vertically divided into the overall migration zone, the fracture extension zone and the collapse zone; additionally, in the horizontal direction, the mining overburden can be divided into the primary fracture zone, periodic fracture zone, and stop-fracture zone. The scope of groundwater flow in the overburden gradually expands with the mining of coal seams. When a stable water inrush channel is formed, other areas no longer generate new channels, and the unstable water inrush channels gradually close. Finally, the primary fracture area becomes the main water inrush channel for coal mines. The numerical simulation results indicate that the overlying rock breaking above the middle of the mined-out area allows the formation of the water-conducting channel. The water body will flow into the fracture extension zone with the shortest path, resulting in the occurrence of water bursting accidents in the mining face. The experimental research results provide a theoretical basis for the implementation of water conservation mining or the establishment of groundwater reservoirs in western mining areas, and this theoretical basis has considerable application and promotion value.

• ETRI Journal
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• v.32 no.5
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• pp.676-686
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• 2010

Mining sequential patterns is an important research issue in data mining and knowledge discovery with broad applications. However, the existing sequential pattern mining approaches consider only binary frequency values of items in sequences and equal importance/significance values of distinct items. Therefore, they are not applicable to actually represent many real-world scenarios. In this paper, we propose a novel framework for mining high-utility sequential patterns for more real-life applicable information extraction from sequence databases with non-binary frequency values of items in sequences and different importance/significance values for distinct items. Moreover, for mining high-utility sequential patterns, we propose two new algorithms: UtilityLevel is a high-utility sequential pattern mining with a level-wise candidate generation approach, and UtilitySpan is a high-utility sequential pattern mining with a pattern growth approach. Extensive performance analyses show that our algorithms are very efficient and scalable for mining high-utility sequential patterns.

• Geomechanics and Engineering
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• v.18 no.2
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• pp.111-119
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• 2019

Due to certain geological characteristics (high thickness, rocky properties), some underground coal mines require the use of explosives. This paper explores the effects of fragmentation of different decks detonated simultaneously in a single borehole with the use of numerical analysis. ANSYS/LS-DYNA code was used for the implementation of the models. The models include an erosion criterion to simulate the cracks generated by the explosion. As expected, the near-borehole area was damaged by compression stresses, while far zones and the free surface of the boundary were subjected to tensile damage. With the increase of the number of decks in the borehole, different changes in the fracture pattern were observed, and the superposition effects of the stress wave became evident, affecting the fragmentation results. The superposition effect is more evident in close distances to the borehole, and its effect attenuates when the distance to the borehole increase.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.698-701
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• 2004

In many literatures, data mining has been used as a utilization of data warehouse and data collection. The biggest utilizations of data mining are for marketing and researches. This is solely because of the data available for this field is usually in large amount. The usability of the data mining is expandable also to the production process. While the object of research of the data mining in marketing is the customers and products, data mining in the production field is object to the so called 4MlE, man, machine, materials, method (recipe) and environment. All of the elements are important to the production process which determines the quality of the product. Because the final aim of the data mining in production field is the quality of the production, this data mining is commonly recognized as quality data mining. As the variables researched in quality data mining can be hundreds or more, it could take a long time to reveal the information from the data warehouse. Feature selection methodology is proposed to help the research take the best performance in a relatively short time. The usage of available simple statistical tools in this method can help the speed of the mining.

• Korean Journal of Cognitive Science
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• v.13 no.3
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• pp.33-46
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• 2002

Recently, unstructured random data such as website logs, texts and tables etc, have been flooding in the internet. Among these unstructured data there are potentially very useful data such as bulletin boards and e-mails that are used for customer services and the output from search engines. Various text mining tools have been introduced to deal with those data. But most of them lack accuracy compared to traditional data mining tools that deal with structured data. Hence, it has been sought to find a way to apply data mining techniques to these text data. In this paper, we propose a text mining system which can incooperate existing data mining methods. We use text mining as a preprocessing tool to generate formatted data to be used as input to the data mining system. The output of the data mining system is used as feedback data to the text mining to guide further categorization. This feedback cycle can enhance the performance of the text mining in terms of accuracy. We apply this method to categorize web sites containing adult contents as well as illegal contents. The result shows improvements in categorization performance for previously ambiguous data.

• Tunnel and Underground Space
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• v.32 no.3
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• pp.173-193
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• 2022

In this study, international standardization trend of smart mining technology was analyzed focusing on the guidelines developed by GMG (Global Mining Guidelines Group). GMG is a non-profit organization that unites the global mining community. It was established to promote mining safety, innovation and sustainability. Currently, GMG's working group consists of artificial intelligence, asset management, autonomous mining, cybersecurity, data access and usage/interoperability, the electric mine, mineral processing, underground mining, and sustainability. Guideline development projects related to smart mining technology are being conducted in artificial intelligence, autonomous mining, cybersecurity, data access and usage/interoperability, and underground mining. As of April 2022, eight types of smart mining-related guidelines have been published through pre-launch, launch, guideline definition, contents generation, technical editing/layout/final review, and voting process. It is judged that the GMG guidelines can be an important reference for the development of domestic smart mining technology standards.

• Journal of Korean Society for Quality Management
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• v.34 no.1
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• pp.13-19
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• 2006

Data mining is a useful tool for analyzing data from different perspectives and for summarizing them into useful information. Recently, the data mining methods are applied to solving quality problems of the manufacturing processes. This paper discusses the problems of construction of a quality mining system, which is based on the various data mining methods. The quality mining system includes recipe optimization, significant difference test, finding critical processes, forecasting the yield. The contents and system of this paper are focused on the TFT-LCD manufacturing process. We also provide some illustrative field examples of the quality mining system.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.95-97
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• 2007

The mining-related damages due to the mining operations such as ground subsidence, tailing, Acid Mine Drainage, and soil contamination have a significant effect on our social and economical environment. So, for the effective prevention and reclamation works of the hazards in the mining area, the systematic management of mine information and mining-related damages is urgently needed. In this study, we estimated the possibilities of GIS-based system development for the mining area and related database. We classified the steps of building GIS as mine itself, mining-related damages, rehabilitation works and additional functions for estimating damages and analyzed the essential database and functions for each step. GIS will be helpful to estimate the mining-related damages and to carry out the reclamation works effectively.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.11-19
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• 2022

Data mining has broad applications that reach beyond scholarly and scientific research and provide internet search engine services that are commonly used forms of Text and Data Mining('TDM') of websites. The exceptions and limitations for data mining provide a competitive advantage in the global race for policy innovation because it permits researchers to conduct computational analysis - TDM on any materials to which they have access. For this purpose, Japan and the EU added limitations on copyright to legalize some TDM research through amendments to copyright law, and the U.S. copyright law has allowed data mining by the fair use provision. On the other hand, there are no explicit exceptions and limitations for data mining under the Korean Copyright Act, and there are no cases considering data mining fair use. We review comparatively exceptions and limitations on copyright which will help to encourage AI-related business by using more data smoothly through the mining process and extracting more valuable information.

• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.381-389
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• 2022

With the collection of huge volumes of text, image, audio, video or combinations of these, in a word multimedia data, the need to explore them in order to discover possible new, unexpected and possibly valuable information for decision making was born. Starting from the already existing data mining, but not as its extension, multimedia mining appeared as a distinct field with increased complexity and many characteristic aspects. Later, the concept of big data was extended to multimedia, resulting in multimedia big data, which in turn attracted the multimedia big data mining process. This paper aims to survey multimedia data mining, starting from the general concept and following the transition from multimedia data mining to multimedia big data mining, through an up-to-date synthesis of works in the field, which is a novelty, from our best of knowledge.