• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.359-360
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• 2006

Magnetic Flux Leakage (MFL) methods are widely employed for the non-destructive testing of gas pipelines. In the application of MFL pipeline inspection technology, corrosion anomalies are detected and identified via their leakage filed due to changes in wall thickness. This paper presents discrete cosine transform (DCT) based MFL signal analysis for defect feature extraction of natural gas pipelines. The original MFL signals are transformed into new ones based on the analysis. The usefulness of the approach has been shown by the experimental results.

• The Transactions of the Korean Institute of Power Electronics
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• v.17 no.1
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• pp.8-13
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• 2012

DSTATCOM is active filter that reduces nonlinear and unbalanced currents. Researches about DSTATCOM are mainly divided two parts, one is the reference value calculation of compensation current depending on the calculation of the load-side average active power and dc-link capacitor average voltage, the other part is actual current control depending on the reference value of compensation current. This paper proposes a calculation of dc-link capacitor average voltage ripple voltage extraction instead of conventional method using LPF. The utility of the proposed algorithm is verified through the theoretical analysis and the experiment under unbalance loads and non-linear load.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.6
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• pp.62-70
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• 2007

In this study, the natural flaws in welding parts are classified using the signal pattern classification method. The storage digital oscilloscope including FFT function and enveloped waveform generator is used and the signal pattern recognition procedure is made up the digital signal processing, feature extraction, feature selection and classifier design. It is composed with and discussed using the distance classifier that is based on euclidean distance the empirical Bayesian classifier. Feature extraction is performed using the class-mean scatter criteria. The signal pattern classification method is applied to the signal pattern recognition of natural flaws.

• Korean Journal of Pharmacognosy
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• v.43 no.1
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• pp.54-58
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• 2012

To increase the extraction yield and biological effect of antler by fermentation, probiotics fermenting antler were screened from rice shells. Of screened Bacillus species, the most potently antler-degrading probiotics was Bacillus KH-07. The supernatant yield of fermented antler is highest. Bacillus KH-07 may belong to Bacillus licheniformis by biochemical and 16S rDNA sequencing analyses. The KH-07-fermented antler (50 mg/kg) increased the anti-fatigue effect 2.3-fold compared to that of non-treated antler. Furthermore, the KH-07-fermented antler improved $CCl_4$-induced liver injury in mice. Based on these findings, the extraction yield and biological effect of antler can be increased by KH-07 fermentation.

• Journal of Institute of Convergence Technology
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• v.3 no.2
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• pp.1-6
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• 2013

The ionic liquids are known to potential alternative solvents capable of replacing the commercial solvents in various processes including those in nuclear fuel cycle. As to the material, a number of studies have already reviewed the interesting results and addressed the spectroscopic as well as electrochemical behaviors of metal elements included in spent nuclear fuels. It has found that the important properties of metal ions in TBP dissolved ILs have led the development of alternative technologies to traditional solvent extraction processes. On the other hand, the electrochemical deposition of metal ions in ILs have been investigated for the application of the solvents to aqueous as well as to non-aqueous processes. In this work, a review on the application of ILs in nuclear fuel cycle is briefly presented to understand the notable researches on ILs focusing on aqueous processes.

• Environmental and Resource Economics Review
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• v.27 no.4
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• pp.639-666
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• 2018

This paper analyses the investment options of groundwater development project under water price uncertainty. The optimal investment threshold price which trigger the investment are calibrated base on monopolistic real options model. Stochastic dynamic model is set to reflect the uncertainty of water price which follows the GBM (Geometric Brownian Motion) process. Our finding from non-cooperative investment decision model is that uncertainty of water price could deter the groundwater investment by considering the existence of option values. For policy markers, it is easy to manage 'charges for utilization of groundwater' rather than 'performance guarantee ratio' when managing groundwater investment with pricing policy. And it is necessary to make comprehensive and well-designed policies considering the characteristics of regional groundwater reservoir and groundwater developers.

• Nuclear Engineering and Technology
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• v.55 no.2
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• pp.391-407
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• 2023

This article provides a survey of wet (aqueous) methods for recovery, separation, and purification of uranium from fission products in carbonate solutions during the reprocessing of spent nuclear fuel and methods for removal of radionuclides from alkaline radioactive waste. The main methods such as selective direct precipitation, ion exchange, and solvent extraction are considered. These methods were compared and evaluated for reprocessing of spent nuclear fuel in carbonate media according to novel alternative non-acidic methods and for treatment processes of alkaline radioactive waste.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.07a
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• pp.540-543
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• 2020

기존의 초해상도 딥러닝 기법은 모델의 깊이가 깊어지면서, 좋은 성능을 내지만 점점 더 복잡해지고 있고, 실제로 사용하는데 있어 많은 시간을 요구한다. 이를 해결하기 위해, 우리는 딥러닝 모델의 가중치를 양자화 하여 추론시간을 줄이고자 한다. 초해상도 모델은 feature extraction, non-linear mapping, reconstruction 세 부분으로 나누어져 있으며, 레이어 사이에 많은 skip-connection 이 존재하는 특징이 있다. 따라서 양자화 시 최종 성능 하락에 미치는 영향력이 레이어 별로 다르며, 이를 감안하여 강화학습으로 레이어 별 최적 bit 를 찾아 성능 하락을 최소화한다. 본 논문에서는 Skip-connection 이 많이 존재하는 MSRN 을 사용하였으며, 결과에서 feature extraction, reconstruction 부분과 블록 내 특정 위치의 레이어가 항상 높은 bit 를 가짐을 알 수 있다. 기존에 영상 분류에 한정되어 사용되었던 혼합 bit 양자화를 사용하여 초해상도 딥러닝 기법의 모델 사이즈를 줄인 최초의 논문이며, 제안 방법은 모바일 등 제한된 환경에 적용 가능할 것으로 생각된다.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.6
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• pp.20-26
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• 2003

This study proposes the construction of attractor quadrant method for high-precision cutting characteristics evaluation of non-ferrous metals. Also this paper aims to find the optimal cutting conditions of diamond turning machine by measuring surface form and roughness to perform the cutting experiment of non-ferrous metals, which are aluminum, with diamond tool. As well, according to change cutting conditions such as feed rate, using diamond turning machine to Perform cutting Processing, by measuring cutting force and surface roughness and according to cutting conditions the aluminum about cutting properties. Trajectory changes in the attractor indicated a substantial difference in fractal characteristics and attractor quadrant characteristics. In quantitative quadrant feature extraction, 1,309 point in the case of A17075 (one quadrant) and 1,406 point (one quadrant) in the case of brass were proposed on the basis of attractor reconstruction. Proposed attractor quadrant method can be used for high-precision cutting characteristics evaluation of non-ferrous metals.

• Journal of Distribution Science
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• v.20 no.6
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• pp.99-108
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• 2022

Purpose: This study aims to provide a further research challenge in digital marketing distribution and co-creation from relevant literature. The concept of digital marketing and co-creation has been known to impact the business sector positively, but it has not been utilized much in the government sector. Therefore, further research is needed to identify the role of digital marketing distribution and co-creation in increasing non-tax state revenue services of government institutions in Indonesia. Research design, data, and methodology: This study is based on a systematic literature review. The stages are (1) research scope review, (2) article extraction from journals, (3) article quality assessment, (4) article analysis, and (5) comprehensive report. Fifty articles published from 2011 to 2021 were collected from the Google Scholar website. Result: This study provides a proposed model that depicts all of the potential connections between digital marketing, co-creation, and non-tax state revenue. In addition, we also identify that the customer experience influences non-tax state revenue. Conclusions: This study attributes the use of the digital marketing distribution and co-creation concept in the government sector and its benefits for state organizations, which have not been investigated in previous studies.