• Journal of the Korean Wood Science and Technology
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• 제42권2호
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• pp.172-182
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• 2014

Extraction is a necessary element in the bioconversion of lignocellulosics to fuels and chemicals. Although various forms of chemical pretreatment of cellulosic materials have been proposed, their effectiveness varies depending on the treatment conditions and substrate. In this study, mixed hardwood (MH) and loblolly pine (LP) were pretreated with dilute acid in a 100 mL accelerated solvent extraction (ASE) at the predetermined optimal conditions: temperature: $170^{\circ}C$, acid concentration: 0.5% (w/v), and reaction time: 2~64 min. This method was highly effective for extracting the hemicellulose fraction. Total xmg (defined as the sum of xylose, mannose, and galactose) can be extracted from milled MH and LP through pressurized dilute acid treatment in maximum yields of 12.6 g/L and 15.3 g/L, respectively, representing 60.5% and 70.4% of the maximum possible yields, respectively. The crystallinity index increased upon pretreatment, reflecting the removal of the amorphous portion of biomass. The crystalline structure of the cellulose in the biomass, however, was not changed by the ASE extraction process.

• Elastomers and Composites
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• 제33권3호
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• pp.201-209
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• 1998

고무배합물의 충진제로 사용되는 알루미나 분말의 제조에 있어서 재래식 및 마이크로파 에너지원에 의하여 황산용액중의 카올린으로 부터 알루미나를 얻는다. 이때 카올린으로부터 알루미나 분말의 최대 추출율은 각각 재래식의 경우는 $80^{\circ}C$, 1M 황산, 180분에서 72.8%이고, 마이크로파 추출 공정의 경우는 $90^{\circ}C$, 1m 황산, 60분에서 $99\%$였다. 또한 추출된 시료는 TG/DTA, XRD, SEM, Atomic Emission Spectroscopy 및 BET법에 의하여 분석하였다..

• Journal of Information Processing Systems
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• 제14권4호
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• pp.824-836
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• 2018

The automatic extraction of temporal information from written texts is a key component of question answering and summarization systems and its efficacy in those systems is very decisive if a temporal expression (TE) is successfully extracted. In this paper, three different approaches for TE extraction in Uyghur are developed and analyzed. A novel approach which uses lexical semantics as an additional information is also presented to extend classical approaches which are mainly based on morphology and syntax. We used a manually annotated news dataset labeled with TIMEX3 tags and generated three models with different feature combinations. The experimental results show that the best run achieved 0.87 for Precision, 0.89 for Recall, and 0.88 for F1-Measure in Uyghur TE extraction. From the analysis of the results, we concluded that the application of semantic knowledge resolves ambiguity problem at shallower language analysis and significantly aids the development of more efficient Uyghur TE extraction system.

• 한국염색가공학회지
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• 제24권4호
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• pp.253-259
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• 2012

In this work, the natural indigo production process from Polygonum tinctorium was balanced based on the traditional Niram method in Korea. A standard procedure was determined considering the conditions of indican extraction from plant material, the amount of alkali for precipitation, storage of extract, etc. The effect of experimental conditions on the yield of crude dye was investigated. The contents of indigo and indirubin of the crude dyes were analyzed by HPLC. Increase of the amount of crude dye was observed within 1-2.5 days of extraction time. Longer extraction beyond 2.5 days resulted in a slight decrease in the amount of crude dye. There was no consistency in terms of indigo content depending on extraction pH. We found that the storage of extract or harvested plants affected adversely to dye yield and dye quality. Based on the lab scale extraction, large scale extraction was performed for 2-2.5 days in water and 2.0-2.5 g/L of $Ca(OH)_2$ was applied for precipitation of indigo dye. We obtained natural indigo dye containing about 15% of pure indigo in scale-up production using whole plant except root.

• Journal of Electrical Engineering and Technology
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• 제12권2호
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• pp.586-593
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• 2017

Modeling busbar distribution system as a transmission line is an important subject of power line communication in the smart grid concept. This requires extraction of busbar RLGC parameters, accurately. In this study, a comparison is made between conventional and modified method for the aspect of optimum RLGC parameters extraction in the 1 MHz to 50 MHz frequency band. The usefulness of these methods is shown both in time and frequency-domain analysis. The frequency-domain analyzes show that the inherent power of modified method can eliminate the errors especially due to the discontinuities arise in conventional method. This makes the modeling approach of modified method more advantageous for the busbars due to its robustness against disturbances in the S-parameters measurements which cannot be eliminated with the calibration procedure. On the other hand, time-domain simulations show that the transmission line representation of the modified method is closer to physical reality by handling causality issues.

• 한국작물학회지
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• 제51권spc1호
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• pp.269-273
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• 2006

The study of molecular markers to improve crops largely depends on the availability of rapid and of efficient DNA extraction methods. Here we developed a cheap and convenient method to isolate genomic DNA from rice grains suitable for large-scale microsatellite analysis. We confirmed that the isolated rice DNA is suitable for PCR analysis with STS marker and SNP marker, as well as microsatellite marker. Further, we established high-throughput DNA extraction system in a 96-well plate format which make it possible high-throughput analysis of microsatellite markers with rice grains. This implies that the new method could be a useful tool for other types of marker analysis in large scale.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2001년도 The Pacific Aisan Confrence On Intelligent Systems 2001
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• pp.128-132
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• 2001

In this paper, we evaluate and contrast four neural network rule extraction approaches for credit scoring. Experiments are carried our on three real life credit scoring data sets. Both the continuous and the discretised versions of all data sets are analysed The rule extraction algorithms, Neurolonear, Neurorule. Trepan and Nefclass, have different characteristics, with respect to their perception of the neural network and their way of representing the generated rules or knowledge. It is shown that Neurolinear, Neurorule and Trepan are able to extract very concise rule sets or trees with a high predictive accuracy when compared to classical decision tree(rule) induction algorithms like C4.5(rules). Especially Neurorule extracted easy to understand and powerful propositional if -then rules for all discretised data sets. Hence, the Neurorule algorithm may offer a viable alternative for rule generation and knowledge discovery in the domain of credit scoring.

• 한국방재학회 논문집
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• 제8권4호
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• pp.53-59
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• 2008

지하철터널에서 화재가 발생하면, 열차는 가장 가까운 정거장으로 대피하여 승객들을 하차시켜야 한다. 실제로 대구지하철 화재사고가 이러한 방식으로 대응 하였으나 큰 인명 피해를 초래하였다. 지하철 정거장의 화재배연시스템은 열차화재에 대응할 수 있도록 설계되어 있지 않기 때문에 화재열차의 정거장 진입시 예상치 못한 피해를 유발할 수 있으며 피해방지를 위한 정거장 선로부의 배연계획 수립이 필요하다. 본 연구의 목적은 정거장 선로부의 열차화재시 효율적인 배연방식을 연구하고 승객의 피난 동선 확보를 위해 상층부로의 역류 방지대책을 축소모형실험에 의하여 수립하는 것이다.

• 디지털융복합연구
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• 제11권6호
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• pp.137-142
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• 2013

음성 인식 시스템은 부정확한 음성 신호의 입력으로 특징을 추출하여 인식할 경우 오인식의 결과가 나타나거나 유사한 음소로 인식된다. 따라서 본 논문에서는 음소가 갖는 특징을 기반으로 음소 유사율과 신뢰도 측정을 이용한 음성 인식 오류 보정 방법을 제안하였다. 음소 유사율은 학습 모델의 음소에 MFCC와 LPC 특징 추출 방법을 이용하여 구하였으며 신뢰도로 측정하였다. 음소 유사율과 신뢰도를 측정하여 오인식되는 오류를 최소화하였으며 음성 인식 과정에서 오류로 판명된 음성에 대하여 오류 보정을 수행하였다. 본 논문에서 제안한 시스템을 적용한 결과 98.3%의 인식률과 95.5%의 오류 보정율을 나타내었다.

• 제어로봇시스템학회논문지
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• 제16권10호
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• pp.957-962
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• 2010

If we want to recognize the human's emotion via the facial image, first of all, we need to extract the emotional features from the facial image by using a feature extraction algorithm. And we need to classify the emotional status by using pattern classification method. The AAM (Active Appearance Model) is a well-known method that can represent a non-rigid object, such as face, facial expression. The Bayesian Network is a probability based classifier that can represent the probabilistic relationships between a set of facial features. In this paper, our approach to facial feature extraction lies in the proposed feature extraction method based on combining AAM with FACS (Facial Action Coding System) for automatically modeling and extracting the facial emotional features. To recognize the facial emotion, we use the DBNs (Dynamic Bayesian Networks) for modeling and understanding the temporal phases of facial expressions in image sequences. The result of emotion recognition can be used to rehabilitate based on biofeedback for emotional disabled.