• Safety and Health at Work
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• v.12 no.3
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• pp.317-323
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• 2021

Background: The surface mining industry has one of the highest fatality rates among private industries in the United States. Despite recent decreases in the fatality rates of comparable industries, the fatality rate in the surface mining industry has increased. Meanwhile, a lack of safety research in surface mining has hindered efforts to improve safety strategies in the surface mining workplace. Method: This study examined quarry workers' hazard identification skills by conducting a case study of a surface mining facility in the Mid-Atlantic region of the United States. Semistructured interviews were conducted with eight quarry workers who were employed at the mine facility. In addition to the interviews, data were collected through field notes, notes from an expert meeting with safety managers, and site photographs to explore quarry workers' safety behaviors in the workplace. Results: The results showed that quarry workers identified hazards and improved their safety performance by translating safety knowledge learned from training into practice, acquiring hands-on work experience, learning from coworkers, and sharing responsibilities among team members. Conclusion: This study contributes to understanding quarry workers' safe performance beyond what they have learned in safety training to include their interaction with other workers and hand-on experience in the workplace. This study informs practitioners in the surface mining industry to build a safe work environment as they design effective safety programs for employees.

• Journal of the Korea Safety Management & Science
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• v.24 no.4
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• pp.149-156
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• 2022

Manufacturing process mining performs various data analyzes of performance on event logs that record production. That is, it analyzes the event log data accumulated in the information system and extracts useful information necessary for business execution. Process data analysis by process mining analyzes actual data extracted from manufacturing execution systems (MES) to enable accurate manufacturing process analysis. In order to continuously manage and improve manufacturing and manufacturing processes, there is a need to structure, monitor and analyze the processes, but there is a lack of suitable technology to use. The purpose of this research is to propose a manufacturing process analysis method using process mining and to establish a manufacturing process mining system by analyzing empirical data. In this research, the manufacturing process was analyzed by process mining technology using transaction data extracted from MES. A relationship model of the manufacturing process and equipment was derived, and various performance analyzes were performed on the derived process model from the viewpoint of work, equipment, and time. The results of this analysis are highly effective in shortening process lead times (bottleneck analysis, time analysis), improving productivity (throughput analysis), and reducing costs (equipment analysis).

• Annual Conference of KIPS
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• 2008.11a
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• pp.275-278
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• 2008

Recently, there are many research of datamining. On the transaction dataset, association rules is made by finding of interesting patterns. A part of mining, sub-structure mining is increased in interest of and applied to many high technology. But graph mining has more computing time then itemset mining. Therefore, that need efficient way for avoid duplication. GASTON is best algorithm of duplication free. This paper analyze GASTON and expect the future work.

• Journal of Digital Contents Society
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• v.13 no.1
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• pp.21-29
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• 2012

In ubiquitous computing environment, rising large scale data exchange through sensor network with sharply growing the internet, the processing of the continuous stream data is required. Therefore there are some mining researches related to the extracting of frequent structures and the efficient query processing of XML stream data. In this paper, we propose a mining method to extract frequent structures of XML stream data in recent window based on the active window sliding using trigger rule. The proposed method is a basic research to control the stream data flow for data mining and continuous query by trigger rules.

• Journal of Power Electronics
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• v.14 no.2
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• pp.315-323
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• 2014

An optimized space vector pulse width modulation (SVPWM) method with common mode voltage elimination and neutral point potential balancing is proposed for an open-end winding induction motor. The motor is fed from both of the ends with two neutral point clamped (NPC) three-level inverters. In order to eliminate the common mode voltage of the motor ends and balance the neutral point potential of the DC link, only zero common mode voltage vectors are used and a balancing control factor is gained from calculation in the strategy. In order to improve the harmonic characteristics of the output voltages and currents, the balancing control factor is regulated properly and the theoretical analysis is provided. Simulation and experimental results show that by adopting the proposed method, the common mode voltage can be completely eliminated, the neutral point potential can be accurately balanced and the harmonic performance for the output voltages and currents can be effectively improved.

• The Korean Journal of Applied Statistics
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• v.13 no.2
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• pp.489-503
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• 2000

Data mining means data analysis and model selection using various types of data in order to explore useful information and knowledge for making decisions. Examples of data mining include scoring for credit analysis of a new customer and scoring for churn management, where the customers with high scores are given special attention. In this paper, scoring is interpreted as a modeling process of the conditional probability and polyclass scoring method is described. German credit data, a PC communication company data and a mobile communication company data are used to compare the performance of polyclass scoring method with that of the scoring method based on a tree model.

• Journal of Power Electronics
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• v.13 no.5
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• pp.896-908
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• 2013

Under high grid impedance conditions, it is difficult to guarantee the stability of grid-connected inverters with an LCL filter designed based on ideal grid conditions. In this paper, the theoretical basis for output impedance calculation is introduced. Based on the small-signal model, the d-d channel closed-loop output impedance models adopting the converter-side current control method and the grid-side current control method are derived, respectively. Specifically, this paper shows how to simplify the stability analysis which is usually complemented based on the generalized Nyquist stability criterion (GNC). The stability of each current-controlled grid-connected system is analyzed via the proposed simplified method. Moreover, the influence of the LCL parameters on the stability margin of grid-connected inverter controlled with converter-side current is studied. It is shown that the stability of grid-connected systems is fully determined by the d-d channel output admittance of the grid-connected inverter and the inductive component of the grid impedance. Experimental results validate the proposed theoretical stability analysis.

• Geomechanics and Engineering
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• v.23 no.5
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• pp.405-418
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• 2020

Deep excavation may have impact on the adjacent tunnels. It is obvious that the excavation will adversely affect and even damage the existing tunnels if the induced deformation exceeds the capacity of tunnel structures. It hence creates a high necessity to predict tunnel displacement induced by nearby excavation to ensure the safety of tunnel. In this paper, a simplified method to evaluate the heave of the underlying tunnel induced by adjacent excavation is presented and verified by field measurement results. In the proposed model, the tunnel is represented by a series of short beams connected by tensile springs, compressional springs and shear springs, so that the rotational effect and shearing effect of the joints between lining rings can be captured. The proposed method is compared with the previous modelling methods (e.g., Euler-Bernoulli beam, a series of short beams connected only by shear springs) based on a field measured longitudinal deformation of subway tunnels. Results of these case studies show a reasonable agreement between the predictions and observations.

• Journal of Digital Contents Society
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• v.17 no.5
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• pp.359-366
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• 2016

In order to provide useful services for user in ubiquitous environment, a technique that can get the helpful information considering user activity and preference is needed and also user's interest actually changes as time passes. Therefore, the discovering method which reflects the concern degree of service information is needed. In this paper, we present the finding method of frequent pattern with dynamic weight on individual item based on service ontology we design. Our method can be applied to provide interested service information for user depending on context.

• Journal of Digital Contents Society
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• v.15 no.5
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• pp.569-577
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• 2014

The various services are required to user in time and space. It is important to provide suitable service to user according to user's circumstance. Therefore it is need to provide services to user through mining by latest information of user activity and service history. In this paper we propose a mining method to search association rule using service history based on spatiotemporal information and service ontology. In this method, we find the associative service pattern using level-cross tree on service ontology. The proposed method is to be a basic research to find the service pattern to provide high quality service to user according to season, location and age under the same context.