• Journal of Power Electronics
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• v.18 no.5
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• pp.1555-1566
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• 2018

Proportional capacitor-current-feedback active damping (AD) is a common damping method for the resonance of LCL-type grid-connected inverters. Proportional capacitor-current-feedback AD behaves as a virtual resistor in parallel with the capacitor. However, the existence of delay in the actual control system causes impedance in the virtual resistor. Impedance is manifested as negative resistance when the resonance frequency exceeds one-sixth of the sampling frequency ($f_s/6$). As a result, the damping effect disappears. To extend the system damping region, this study proposes a virtual resistor-inductor-capacitor (RLC) AD method. The method is implemented by feeding the filter capacitor current passing through a band-pass filter, which functions as a virtual RLC in parallel with the filter capacitor to achieve positive resistance in a wide resonance frequency range. A combination of Nyquist theory and system close-loop pole-zero diagrams is used for damping parameter design to obtain optimal damping parameters. An experiment is performed with a 10 kW grid-connected inverter. The effectiveness of the proposed AD method and the system's robustness against grid impedance variation are demonstrated.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.3
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• pp.383-393
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• 2013

Data stream mining is a technique to obtain the useful information by analyzing the data generated in real time. In data stream mining technology, frequent itemset mining is a method to find the frequent itemset while data is transmitting, and these itemsets are used for the purpose of pattern analyze and marketing in various fields. Existing techniques of finding frequent itemset mining are having problems when a malicious attacker sniffing the data, it reveals data provider's real-time information. These problems can be solved by using a method of inserting dummy data. By using this method, a attacker cannot distinguish the original data from the transmitting data. In this paper, we propose a method for privacy preserving frequent itemset mining by using the technique of inserting dummy data. In addition, the proposed method is effective in terms of calculation because it does not require encryption technology or other mathematical operations.

• Journal of Power Electronics
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• v.18 no.2
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• pp.511-521
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• 2018

Proportional capacitor current feedback active damping (CCFAD) has a limited valid damping region in the discrete time domain as (0, $f_s/6$. However, the resonance frequency ($f_r$) of an LCL-type filter is usually designed to be less than half the sampling frequency ($f_s$) with the symmetry regular sampling method. Therefore, ($f_s/6$, $f_s/2$) becomes an invalid damping region. This paper proposes an improved CCFAD method to extend the valid damping region from (0, $f_s/6$ to (0, $f_s/2$), which covers all of the possible resonance frequencies in the design procedure. The full-valid damping region is obtained and the stability margin of the system is analyzed in the discrete time domain with the Nyquist criterion. Results show that the system can operate stably with the proposed CCFAD method when the resonance frequency is in the region (0, $f_s/2$). The performances at the steady and dynamic state are enhanced by the selected feedback coefficient H and controller gain $K_p$. Finally, the feasibility and effectiveness of the proposed CCFAD method are verified by simulation and experimental results.

• Journal of the Korean Data and Information Science Society
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• v.17 no.2
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• pp.335-344
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• 2006

The purpose of this paper is to apply data mining method for the inbound call center optimization. Data mining analysis is come to be used in order to predict the degree of difficulty on the consultation. It is the method of maximal efficiency for the call center that uses of the predicted degree of difficulty and customer grade as routing which hits to the skill of the consultation unit. This method is to get the possibility of efficiency for the call center with the maximum efficiency.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.8
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• pp.1325-1335
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• 2002

Workflow systems, automated business processing, have been generalized. In this paper, we propose a method to mine workflow specification on workflow logs. The method detects workflow specification considering cycle, AND and OR control flow between tasks. Also, we provide dynamic mining method to detect workflow specification in which log is generated.

• International Journal of Contents
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• v.3 no.2
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• pp.18-24
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• 2007

Biological sequences such as DNA and amino acid sequences typically contain a large number of items. They have contiguous sequences that ordinarily consist of more than hundreds of frequent items. In biological sequences analysis(BSA), a frequent contiguous sequence search is one of the most important operations. Many studies have been done for mining sequential patterns efficiently. Most of the existing methods for mining sequential patterns are based on the Apriori algorithm. In particular, the prefixSpan algorithm is one of the most efficient sequential pattern mining schemes based on the Apriori algorithm. However, since the algorithm expands the sequential patterns from frequent patterns with length-1, it is not suitable for biological datasets with long frequent contiguous sequences. In recent years, the MacosVSpan algorithm was proposed based on the idea of the prefixSpan algorithm to significantly reduce its recursive process. However, the algorithm is still inefficient for mining frequent contiguous sequences from long biological data sequences. In this paper, we propose an efficient method to mine maximal frequent contiguous sequences in large biological data sequences by constructing the spanning tree with a fixed length. To verify the superiority of the proposed method, we perform experiments in various environments. The experiments show that the proposed method is much more efficient than MacosVSpan in terms of retrieval performance.

• Journal of Power Electronics
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• v.16 no.5
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• pp.1763-1772
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• 2016

To reduce system complexity and implementation costs, fully-controlled H-bridge (FHB) modules and diode H-bridge PFC (DHB) modules are cascaded to form a hybrid cascaded H-bridge rectifier (HCHR). In this paper, the advantages of such a HCHR over other cascaded rectifiers are analyzed depending on the numbers of FHB modules and DHB modules. Therefore, to assign proper numbers to these two kinds of modules for the HCHR, a configuration determination method is investigated under balanced and imbalanced loads. Three principles are also presented to guide the configuration determination for the HCHR. In addition, the constraints for selecting the step-up ratio and filter inductance are derived based on a phasor diagram analysis. The proposed configuration determination method is validated by simulations under three different conditions in the PSIM environment. Finally, experiments are carried out on a scaled-down prototype where the configuration can be easily adjusted. The feasibility of the proposed theory is then verified by experimental results.

• Journal of Digital Contents Society
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• v.17 no.2
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• pp.81-88
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• 2016

The general frequent pattern mining considers frequency and support of items. To extract useful information, it is necessary to consider frequency and weight of items that reflects the changing of user interest as time passes. The suitable services considering time or location is requested by user so that the weighted mining method is necessary. We propose a method of weighted frequent pattern mining based on service ontology. The weight considering time and location is given to service items and it is applied to association rule mining method. The extracted rule is combined with stored service rule and it is based on timely service to offer for user.

• Journal of the Korea Society of Computer and Information
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• v.14 no.10
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• pp.251-258
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• 2009

Data mining is a method that extract useful knowledges from huge size of data. Recently, a focussing research part of data mining is to find interesting patterns in graph databases. More efficient methods have been proposed in graph mining. However, graph analysis methods are in NP-hard problem. Graph pattern mining based on pattern growth method is to find complete set of patterns satisfying certain property through extending graph pattern edge by edge with avoiding generation of duplicated patterns. This paper suggests an efficient approach of reducing computing time of pattern growth method through pattern growth's property that similar patterns cause similar tasks. we suggest pruning methods which reduce search space. Based on extensive performance study, we discuss the results and the future works.

• Geomechanics and Engineering
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• v.19 no.5
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• pp.383-392
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• 2019

How to safely and economically dispose mining tailings is a challenge to mine operators. This paper presents an alternative upstream method for tailings dam construction, termed as the template construction method (TCM), which has been successfully implemented at Zhelamuqing tailings impoundment since 2004. By the beginning of 2015, the tailings dam wall had reached 95 m in height for the 46 upstream raises, with the total height of the dam including the starter dyke being 128 m. The proposed TCM is relatively simple and cost-effective and provides a good way for constructing rapidly raising tailings dam based on this case.