• Proceedings of the Korean Society for Rock Mechanics Conference
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• 2008.10a
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• pp.17-29
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• 2008

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.597-599
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• 2003

Moving pattern is as a kind of sequential pattern, which can be extracted from the large volume of location history data. This sort of knowledge is very useful in supporting intelligence to the LBS or GIS. In this paper, we proposed the continuous moving pattern mining approach in LBS platform and LBS Miner. The location updates of moving objects affect the set of the rules maintained. In our approach, we use the validity thresholds that indicate the next time to invoke the incremental pattern mining. The mining system will play a major role in supporting the various LBS solutions.

• Geomechanics and Engineering
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• v.18 no.6
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• pp.585-594
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• 2019

In-situ leaching could be one of the promising mining methods to extract the minerals from deep fractured rock mass. Constrained by the low permeability at depth, however, the performance does not meet the expectation. In fact, the rock mass permeability mainly depends on the pre-existing natural fractures and therefore play a crucial role in in-situ leaching performance. More importantly, fractures have various characteristics, such as aperture, persistence, and density, which have diverse contributions to the promising method. Hence, it is necessary to study the variation of fluid rate versus fracture parameters to enhance in-situ leaching performance. Firstly, the subsurface fractures from the depth of 1500m to 2500m were mapped using the discrete fracture network (DFN) in this paper, and then the numerical model was calibrated at a particular case. On this basis, the fluid flow through fractured rock mass with various fracture characteristics was analyzed. The simulation results showed that with the increase of Fisher' K value, which determine the fracture orientation, the flow rate firstly decreased and then increased. Subsequently, as another critical factor affecting the fluid flow in natural fractures, the fracture transmissivity has a direct relationship with the flow rate. Sensitive study shows that natural fracture characteristics play a critical role in in-situ leaching performance.

• Journal of Information Technology Applications and Management
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• v.26 no.1
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• pp.65-75
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• 2019

As the use of semantic web based on XML increases in the field of data management, a lot of studies to extract useful information from the data stored in ontology have been tried based on association rule mining. Ontology data is advantageous in that data can be freely expressed because it has a flexible and scalable structure unlike a conventional database having a predefined structure. On the contrary, it is difficult to find frequent patterns in a uniformized analysis method. The goal of this study is to provide a basis for extracting useful knowledge from ontology by searching for frequently occurring subgraph patterns by applying transaction-based graph mining techniques to ontology schema graph data and instance graph data constituting ontology. In order to overcome the structural limitations of the existing ontology mining, the frequent pattern search methodology in this study uses the methodology used in graph mining to apply the frequent pattern in the graph data structure to the ontology by applying iterative node chunking method. Our suggested methodology will play an important role in knowledge extraction.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.6
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• pp.133-143
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• 2020

The purpose of this study is to investigate the economic potential of the regions from the mining sector of North Morowali, Central-Sulawesi, Indonesia, and the formulation of pro-business regional development management that aims to create synergy between the local government and mining sector entrepreneurs. This study uses a descriptive qualitative approach by taking data in the form of primary data from FGD and secondary data observations from statistical bureau data in the North Morowali, Indonesia. The analysis unit uses SWOT analysis to determine the economic potential of the North Morowali and Location Quotient (LQ) to analyze the economic potential of the mining sector. The research period covers one year (2018-2019) in North Morowali, Indonesia. All the mining products have considerable potential as a financing unit in North Morowali, while mining potential has not been maximally exploited. The absence of regulations, facilities such as road access, and optimal land and sea transportation are the causes of the difficulty of optimization and access to explore mining products comprehensively. As a new province at Central Sulawesi, more efforts and the role of government are needed to focus attention to North Morowali as an area with great potential in the mining sector.

• Journal for History of Mathematics
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• v.18 no.2
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• pp.95-106
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• 2005

This paper is investigated conception and methodology of data selection, cleaning, integration, transformation, reduction, selection and application of data mining techniques, and model evaluation during procedure of the knowledge discovery in database (KDD) based on Mathematics. Statistical role and methodology in KDD is studied as branch of Mathematics. Also, we investigate the history, mathematical background, important modeling techniques using statistics and information, practical applied field and entire examples of data mining. Also we study the differences between data mining and statistics.

• The Journal of Information Systems
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• v.15 no.4
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• pp.211-224
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• 2006

This study investigates the application of data mining techniques such as artificial neural networks, rough sets, and induction teaming to the intrusion detection systems. To maximize the effectiveness of data mining for intrusion detection systems, we introduced the asymmetric costs with false positive errors and false negative errors. And we present a method for intrusion detection systems to utilize the asymmetric costs of errors in data mining. The results of our empirical experiment show our intrusion detection model provides high accuracy in intrusion detection. In addition the approach using the asymmetric costs of errors in rough sets and neural networks is effective according to the change of threshold value. We found the threshold has most important role of intrusion detection model for decreasing the costs, which result from false negative errors.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.37-38
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• 2015

A number of documents containing important and useful knowledge have been generated over time in the construction industry. Such text-based knowledge plays an important role in the construction industry for decision-making and business strategy development by being used as best practice for upcoming projects, delivering lessons learned for better risk management and project control. Thus, practical and usable knowledge creation from construction documents is necessary to improve business efficiency. This study proposes a knowledge creating system from construction documents using text mining and the design comprises three main steps - text mining preprocessing, weight calculation of each term, and visualization. A system prototype was developed as a pilot study of the system design. This study is significant because it validates a knowledge creating system design based on text mining and visualization functionality through the developed system prototype. Automated visualization was found to significantly reduce unnecessary time consumption and energy for processing existing data and reading a range of documents to get to their core, and helped the system to provide an insight into the construction industry.

• Safety and Health at Work
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• v.12 no.2
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• pp.201-208
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• 2021

Background: In the mining industry, various methods of accident analysis have utilized official accident investigations to try and establish broader causation mechanisms. An emerging area of interest is identifying the extent to which cultural influences, such as safety culture, are acting as drivers in the reoccurrence of accidents. Thus, the overall objective of this study was to analyze occupational health and safety (OHS) reports in mining to investigate if/how safety culture has historically been framed in the mining industry, as it relates to accident causation. Methods: Using a computer-assisted qualitative data analysis software, 34 definitions of safety culture were analyzed to highlight key terms. Based on word count and contextual relevance, 26 key terms were captured. Ten OHS reports were then analyzed via an inductive thematic analysis, using the key terms. This analysis provided a concept map representing the 50-year data set and facilitated the use of text framing to highlight safety culture in the selected OHS mining reports. Results: Overall, 954 references and six themes, safety culture, attitude, competence, belief, patterns, and norms, were identified in the data set. Of the 26 key terms originally identified, 24 of them were captured within the text. The results made evident two distinct frames in which to interpret the data: the role of the individual and the role of the organization, in safety culture. Conclusion: Unless efforts are made to understand and alter cultural drivers and share these findings within and across industries, the same accidents are likely to continue to occur.

• Journal of Soil and Groundwater Environment
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• v.18 no.4
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• pp.40-49
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• 2013

In the beginning of $20^{th}$ century, the coal mining industry had an important role in Japan at which two-thirds of the coal product came from the Kitakyushu-Chikuho District (KCD). As a consequence of mining activities, land-use condition in this district showed notable changes. This paper presented a study of land-use changes in coal mining area by characterizing land-use pattern transition over the last 100 years. In order to carry out the rigorous analysis of land-use, a series of land-use maps over the last 100 years was developed using geographic information systems (GIS). The historic topographic map and another available old data were used to investigate the long-term changes of land-use associated with past mining within the GIS platform. The results showed that the utilization of a series of developed land-use maps successfully indicated the difference of land-use pattern in the KCD before and after the peak of mining activities. The general findings from land-use analysis described that forest and farm lands were lost and turned into abandoned sites in the last 100 years.