• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2005.11a
• /
• pp.127-130
• /
• 2005

There are many methods in feature extraction have been developed. Recently, principal components analysis (PCA) and independent components analysis (ICA) is introduced for doing feature extraction. PCA and ICA linearly transform the original input into new uncorrelated and independent features space respectively In this paper, the feasibility of using nonlinear feature extraction will be studied. This method will employ the PCA and ICA procedure and adopt the kernel trick to nonlinearly map the data into a feature space. The goal of this study is to seek effectively useful feature for faults classification.

• Bulletin of the Korean Chemical Society
• /
• v.21 no.11
• /
• pp.1101-1105
• /
• 2000

A simultaneous determination method of BTEX (benzene, toluene, ethylbenzene, o,m.p-xylene) and TPH (kerosene, diesel, jet fuel and bunker C) in soil with gas chromatography/flame ionization detection (GC-FID) was described. The effects of extracti on method, extraction solvent, solvent volume and extraction time on the extraction performance were studied. A sonication method was simpler and more efficient than Soxhlet or shaking methods. Sonication with 10 mL of acetone/methylene chloride (1 : 1, v/v) for 10 min was found to be optimal extraction conditions for 20 g of soil. Peak shapes and quantification of BTEX and TPH were excellent, with linear calibration curves over a wide range of 1-500 mg/L for BTEX and 10-5000 mg/L for TPH. Good reproducibilities by sonication were obtained, with the RSD values below 10%. By using about 20 g of soil, detection limits were 0.8 mg/L for BTEX and 10 mg/L for TPH. The advantages of this procedure are the use of simple and common equipment, reduced volumes of organic solvents, rapid extraction periods of less than 20 min, and simultaneous analysis of volatile and semivolatile compounds.

• Food Science and Preservation
• /
• v.4 no.1
• /
• pp.45-51
• /
• 1997

In our studies on the role of $\beta$-galactosidase in fruit softening, significant difficulty, was encountered in our attempts to extract RNA from persimmon(Diospyros kaki L. cv. Fuyu) fruit due to astringency and tannin content. Initial, unsuccessful RNA extractions involved methods using guanidinium isothiocyanate/CsCl with and without polyvinylpyrrolidone(PVP), phenol/sodium lauryl sulfate(SDS), guanidinium hydrochloride, as well as polysomal RNA purification method that used 0.2 M Tris-HCI (pH 9.0) containing KCI, Mg-acetate, EDTA, $\beta$-mercaptoethanol, and sucrose. A method was devised which employed treatment of fruit with CO2 gas to diminish astringency prior to RNA extraction, followed by extraction of tissue powders with Proteinase K extraction buffer containing PVP and ascorbate at an alkaline pH. This procedure resulted in the removal of tannins and other polyphenolics and extraction of relatively large amount of high-quality RNA suitable for cDNA library construction and polymerase chain reaction(PCR). Futhermore, the procedure does not use the toxic and corrosive chemical guanidinium isothiocyanate or require ultracentrifugation.

• Journal of Advanced Information Technology and Convergence
• /
• v.10 no.1
• /
• pp.45-56
• /
• 2020

Despite extensive research, performance enhancement of keyphrase (KP) extraction remains a challenging problem in modern informatics. Recently, deep learning-based supervised approaches have exhibited state-of-the-art accuracies with respect to this problem, and several of the previously proposed methods utilize Bidirectional Encoder Representations from Transformers (BERT)-based language models. However, few studies have investigated the effective application of BERT-based fine-tuning techniques to the problem of KP extraction. In this paper, we consider the aforementioned problem in the context of scientific articles by investigating the fine-tuning characteristics of two distinct BERT models - BERT (i.e., base BERT model by Google) and SciBERT (i.e., a BERT model trained on scientific text). Three different datasets (WWW, KDD, and Inspec) comprising data obtained from the computer science domain are used to compare the results obtained by fine-tuning BERT and SciBERT in terms of KP extraction.

• Natural Product Sciences
• /
• v.28 no.2
• /
• pp.89-92
• /
• 2022

In Asia, the roots of Paeonia lactiflora and Astragalus membranaceus have been used as therapeutic agents for thousands of years. Once the medicinal plants are harvested, they are dried and their ingredients are extracted by heat-mediated reflux extraction. However, the condensed structure of organic products (especially roots) limits the extraction of bioactive components. In this study, we assessed the effect of the puffing method (using high temperature and pressure) before the extraction process in relation to the profile and antioxidant capacity of active ingredients. We demonstrated that the additional puffing process before extraction methods improves the yield of polyphenol concentrations and antioxidant activities from the roots of P. lactiflora and A. membranaceus.

• Journal of Pharmacopuncture
• /
• v.21 no.2
• /
• pp.48-60
• /
• 2018

Objective: The aim of this study is to optimize the extraction of beneficial substance from Cudrania tricuspidata leaves grown at Jirisan Mountain in South Korea by three different solvents depending on extraction time and at different temperature. Methods: The total phenolic contents were determined by the method reported by $S{\acute{a}}nchez$-Moreno et al. The total flavonoid contents were analyzed by Slinkard and Singleton. The DPPH radical scavenging activity was determined according to the method reported by Blois Results: The extraction yield for each solvent is 9.05-14.1%, 2.17-5.67%, and 2.3-3.9% for D.W., ethanol, and hexane, respectively. The overall results were maximized for the extract obtained with D.W. for 5 min at $100^{\circ}C$. The average phenol contents were 77.11, 45.64, and 0.343 mg/g at $100^{\circ}C$ in water, $78^{\circ}C$ in ethanol, and $68^{\circ}C$ in hexane, respectively. The flavonoid contents were the highest in the materials extracted with D.W., and were increased with increasing temperature, regardless of the extraction solvents, whether water (green), polar organic ethanol, or nonpolar organic hexane. In the ethanol extract, the flavonoid contents are increased gradually from 5.66 mg/g to 7.73 mg/g. The total flavonoid contents were proportional to the concentrations of the water extracts, ranging from 4.14 mg/g to 48.89 mg/g. The antioxidative activities of the water-extracted compounds are generally increased with increasing temperature from 42.5% to 85.5%. Those of the hexane extracts are increased slowly from 3.79% to 8.8%, while those of ethanol extracts are increased from 29.8% to 47.4%. Conclusion: The extraction yields were dependent upon solvents for extraction as well as extraction time and the temperature. The optimal extraction time was 5 min and the extraction yields were increased with increasing temperature excepted hexane. Of the three tested extraction solvents, the greenest solvent of water shows excellent results, suggesting that water is among the most effective solvents for natural sample extractions for general medicinal, pharmaceutical, and food applications.

• Herbal Formula Science
• /
• v.22 no.2
• /
• pp.15-24
• /
• 2014

Objectives : Gwakhyangjeonggi-san (GJS) which consists of 13 herbal medicines has been used to treat gastrointestinal disorders caused by common cold. This study was performed to compare GJS decoctions produced using different pressure levels for various extraction times. Methods : Decoctions were prepared by the pressure levels of $0kgf/cm^2$ (non-pressurized) or $1kgf/cm^2$ (pressurized) for 30-180 min. The extraction yield, total soluble solid content (TSSC), and hydrogen ion concentration (pH) were measured, and the contents of the nine marker compounds were determined using high performance liquid chromatography. Results : The higher pressure and longer extraction time significantly increased TSSC value, while decreased the pH value. However, only extraction time affected the extraction yield of pressurized decoction. Variation of the amounts of chemical compounds was shown in pressurized and non-pressurized decoctions during extraction time. The result of regression analysis showed that pressure and extraction time can influence to extraction yield, TSSC, pH, and the content of chemical compounds. Conclusions : This study suggests that the pressure and extraction time can significantly affect the extraction efficiency of components from GJS decoctions.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2013.05a
• /
• pp.903-904
• /
• 2013

• ETRI Journal
• /
• v.35 no.1
• /
• pp.100-108
• /
• 2013

In this paper, a feature extraction (FE) method is proposed that is comparable to the traditional FE methods used in automatic speech recognition systems. Unlike the conventional spectral-based FE methods, the proposed method evaluates the similarities between an embedded speech signal and a set of predefined speech attractor models in the reconstructed phase space (RPS) domain. In the first step, a set of Gaussian mixture models is trained to represent the speech attractors in the RPS. Next, for a new input speech frame, a posterior-probability-based feature vector is evaluated, which represents the similarity between the embedded frame and the learned speech attractors. We conduct experiments for a speech recognition task utilizing a toolkit based on hidden Markov models, over FARSDAT, a well-known Persian speech corpus. Through the proposed FE method, we gain 3.11% absolute phoneme error rate improvement in comparison to the baseline system, which exploits the mel-frequency cepstral coefficient FE method.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.49 no.12
• /
• pp.651-658
• /
• 2000

This paper presents a new method to extract traffic information such as number of passing vehicles and average speed by a pair of stereo road images. The whole process consists of the extraction of vehicles and the tracking of the extracted vehicles. For the extraction of vehicles, the outline of each vehicle is obtained by using binary region growing technique applied to disparity map based on multi-resolution stereo matching. The Kalman filter tracking algorithm is applied to the extracted vehicle outlines to determine the flow of vehicles. Experimental results show that the proposed method significantly improved recognition rate of vehicles over the conventional methods-frame difference and background elimination methods.