• Geomechanics and Engineering
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• v.14 no.5
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• pp.429-437
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• 2018

In order to reduce deformation of roadway floor heave in deep underground soft rockmass, four support design patterns were analyzed using the Fast Lagrangian Analysis of Continua (FLAC)3D, including the traditional bolting (Design 1), the bolting with the backbreak in floor (Design 2), the full anchorage bolting with the backbreak in floor (Design 3) and the full anchorage bolting with the bolt-grouting backbreak in floor (Design 4). Results show that the design pattern 4, the full anchorage bolting with the bolt-grouting backbreak in floor, was the best one to reduce the deformation and failure of the roadway, the floor deformation was reduced at 88.38% than the design 1, and these parameters, maximum vertical stress, maximum horizontal displacement and maximum horizontal stress, were greater than 1.69%, 5.96% and 9.97%. However, it was perfectly acceptable with the floor heave results. The optimized design pattern 4 provided a meaningful and reliable support for the roadway in deep underground coal mine.

• Korean Journal of Computational Design and Engineering
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• v.17 no.4
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• pp.294-302
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• 2012

Process mining is a useful methodology that can be used for extracting user patterns in log files in order to discover efficient or inefficient processes in organizations. In general, it is used to find and reduce differences between pre-defined processes and actually executed processes in an organization. In this paper, we propose a method to improve processes in PDM/PLM systems based on process mining. In order to improve and detect the inefficient processes, we gathered event logs from PDM/PLM systems and derived process models using several process mining techniques such as ${\alpha}$-algorithm mining, heuristics mining, and fuzzy miner. By comparing original process models with process mining results, it is possible to detect differences between predefined processes and real ones; thereby we can build improved process models for future application.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2011.06a
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• pp.919-920
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• 2011

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2124-2141
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• 2018

Recent studies have revealed the efficacy of incorporating delayed channel state information at transmit side (CSIT) in transmission scheme design. This paper focuses on transmit precoder design to maximize the ergodic sum-rate in a two-user Multiple-Input Single-Output (MISO) system with delayed and statistical CSIT. A new transmit strategy which precodes signals in all transmit slots is proposed in this paper, denoted as all time-slots precoding Alternative MAT (AAMAT). There is a common procedure in conventional delayed-CSIT based schemes, which is retransmitting the overheard interferences. Since the retransmitting signal is intended to both users, all previous schemes tend to use only one antenna. We however figure out an improvement in spectral efficiency could be realized if all antennas can be utilized. In this paper, we detail the design of the procoder which enabling all antennas and also we compute a lower bound of the ergodic sum-rate in an ideal condition. In addition, simulation results demonstrate the superiority of our proposed scheme.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.601-605
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• 2009

The objective of this research is to develop a knowledge discovery framework which can help project teams discover useful patterns to improve energy efficient building design. This paper utilizes the technology of data mining to automatically extract concepts, interrelationships and patterns of interest from a large dataset. By applying data mining technology to the analysis of energy efficient building designs one can identify valid, useful, and previously unknown patterns of energy simulation modeling.

• Geomechanics and Engineering
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• v.28 no.5
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• pp.463-475
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• 2022

In the mine exploitation stage; one of the critical issues is the stability assessment of post-pillars. The instability of post-pillars leads to serious safety hazards in mining operations. The focus of this study is to assess the stability of post-pillars in the 130# stope in the central ore body at Trepça hard rock mine by employing both conventional (i.e., critical span curve) and numerical methods (i.e., FLAC3D). Moreover, a new numerical based index (i.e., Pillar Yield Ratio-PYR) was proposed. The aim of PYR index is to determine a border line between stable, potentially unstable, and failure state of post-pillars at a specific mine site. The critical value of pillar width to height ratio is 2.5 for deep production stopes (e.g., > 800 m). Results showed that pillar size, mining height and mining depth significantly have affected the post-pillar stability. The reliability of numerical based index (i.e., PYR) is verified based on empirical underground pillar stability graph developed by Lunder, 1994. The proposed pillar yield ratio index and pillar stability graph can be used as a design tool in new mining areas at Trepça hard rock mine and for other situations with similar geotechnical conditions.

• Korean Journal of Computational Design and Engineering
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• v.14 no.6
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• pp.382-389
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• 2009

Recently, knowledge management has been required in companies as a tool of competitiveness. Companies have constructed Enterprise Resource Planning(ERP) system in order to manage huge knowledge. But, it is not easy to formalize knowledge in organization. We focused on data mining system by genetic programming(GP). Data mining system by genetic programming can be useful tools to derive and extract the necessary information and knowledge from the huge accumulated data. However when we don't have enough amounts of data to perform the learning process of genetic programming, we have to reduce input parameter(s) or increase number of learning or training data. In this study, an enhanced data mining method combining Genetic Programming with Self organizing map, that reduces the number of input parameters, is suggested. Experiment results through a prototype implementation are also discussed.

• 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.

• Archives of design research
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• v.15 no.4
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• pp.159-168
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• 2002

The world has rushed into knowledge information society. Information technology is one of the causes to show up knowledge management and one of the motives to accelerate knowledge management. And, these days information technology and internet have made staffing progress. Therefore, the objective of this study is to take out latent knowledge of customers through web data mining in a vast amount of data on the internet in rapidly developing digital environments, to develop the knowledge-based design paradigm applied to knowledge management framework, and finally to develop design which satisfies customers' needs. To reach the objective, knowledge management process and varied previous studies related to web data mining are reviewed on a theoretical basis, and then a new knowledge-based design paradigm (in this study, eCRM in a true sense which combines web data mining with knowledge management process is called knowledge-based design paradigm) combining knowledge management process with web data mining is suggested.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.30 no.2
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• pp.99-105
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• 2007

According to the automated manufacturing processes followed by the development of computer manufacturing technologies, products or quality characteristics produced on the processes have measured and recorded automatically. Much amount of data daily produced on the processes may not be efficiently analyzed by current statistical methodologies (i.e., statistical quality control and statistical process control methodologies) because of the dimensionality associated with many input and response variables. Although a number of statistical methods to handle this situation, there is room for improvement. In order to overcome this limitation, we integrated data mining and robust design approach in this research. We find efficiently the significant input variables that connected with the interesting response variables by using the data mining technique. And we find the optimum operating condition of process by using RSM and robust design approach.