• 한국IT서비스학회지
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• 제18권2호
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• pp.143-159
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• 2019

Machine learning (ML) is a method of fitting given data to a mathematical model to derive insights or to predict. In the age of big data, where the amount of available data increases exponentially due to the development of information technology and smart devices, ML shows high prediction performance due to pattern detection without bias. The feature engineering that generates the features that can explain the problem to be solved in the ML process has a great influence on the performance and its importance is continuously emphasized. Despite this importance, however, it is still considered a difficult task as it requires a thorough understanding of the domain characteristics as well as an understanding of source data and the iterative procedure. Therefore, we propose methods to apply deep learning for solving the complexity and difficulty of feature extraction and improving the performance of ML model. Unlike other techniques, the most common reason for the superior performance of deep learning techniques in complex unstructured data processing is that it is possible to extract features from the source data itself. In order to apply these advantages to the business problems, we propose deep learning based methods that can automatically extract features from transaction data or directly predict and classify target variables. In particular, we applied techniques that show high performance in existing text processing based on the structural similarity between transaction data and text data. And we also verified the suitability of each method according to the characteristics of transaction data. Through our study, it is possible not only to search for the possibility of automated feature extraction but also to obtain a benchmark model that shows a certain level of performance before performing the feature extraction task by a human. In addition, it is expected that it will be able to provide guidelines for choosing a suitable deep learning model based on the business problem and the data characteristics.

• 음성과학
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• 제4권2호
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• pp.55-68
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• 1998

In this paper, a novel method of noise reduction of speech based on a complex adaptive noise canceler and method of optimal feature extraction are proposed. This complex adaptive noise canceler needs simply the noise detection, and LMS algorithm used to calculate the adaptive filter coefficient. The method of optimal feature extraction requires the variance of noise. The experimental results have shown that the proposed method effectively reduced noise in noisy speech. Optimal feature extraction has shown similar characteristics in noise-free speech.

• Biotechnology and Bioprocess Engineering:BBE
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• 제9권3호
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• pp.207-211
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• 2004

Predispersed solvent extraction (PDSE) of succinic acid with Tri-n-octylamine (TOA) dissolved in 1-octanol from aqueous solutions of 50 g/L succinic acid was examined. It was found that the equilibrium data in PDSE was equal to that in conventional solvent extraction in spite of the lack of mechanical mixing in PDSE. The influence of salts on succinic acid extraction and the stability of colloidal liquid aphrons (CLAs) were also investigated. Results indicated that in the presence of sodium chloride, less succinic acid was extracted by CLAs and the stability of CLAs decreased. However, the stability of CLAs was sufficient to make PDSE practically applicable to real fermentation broth, considering the concentration range of salts in the fermentation process for succinic acid.

• 한국정보기술학회 영문논문지
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• 제10권1호
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• pp.45-56
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• 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.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 추계종합학술대회 논문집(2)
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• pp.47-50
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• 2000

DC Gummel-Poon SPICE model parameter extraction program has been implemented. This program extracts the parameters from measured data using Levenberg-Marquardt algorithm. Measured data consist of forward and reverse Gummel plot, forward and reverse output characteristics and RE and RC measurements.

• Elastomers and Composites
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• 제48권4호
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• pp.288-293
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• 2013

무수말레산-그래프트 EPDM (MAH-g-EPDM)/산화아연 복합체를 디클로로아세트산(DCA)/톨루엔 공용매로 처리하고 추출 온도에 따른 무게 감소와 가교밀도 측정을 이용하여 가교 특성을 조사하였다. 감쇠전반-후리에변환 적외선분광법(ATR-FTIR)을 이용하여 화학적 변화를 분석하였다. 상온 추출보다 고온($90^{\circ}C$) 추출에 의한 무게 감소가 월등히 높았으며, DCA/톨루엔 공용매 추출에 의한 무게 감소는 톨루엔 추출에 의한 무게 감소보다 5배 이상 높았다. 용매 추출 후 가교밀도를 측정하였으며, 1차 가교밀도보다 2차 가교밀도가 높았다. 1차 가교밀도는 추출온도가 높은 경우 더 낮았고 DCA/톨루엔 공용매로 추출한 것이 톨루엔으로 추출한 것보다 훨씬 낮았다. 2차 가교밀도는 DCA/톨루엔 공용매로 추출한 것이 톨루엔으로 추출한 것보다 높았다. 고온에서 DCA/톨루엔 공용매로 추출하면 강한 가교 그물망만 남는 반면, 상온에서 톨루엔으로 추출하면 미가교 고분자 사슬이 추출되는 등 추출 용매와 온도에 따라 추출되는 성분이 달랐다. 따라서 추출 용매와 온도에 따른 추출 성분의 비교와 연속 가교밀도 측정에 의해 MAH-g-EPDM/산화아연 복합체의 가교 특성을 분석할 수 있다.

• 한국조리학회지
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• 제20권3호
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• pp.13-21
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• 2014

본 연구에서는 순환형 감압건조 및 초고압 추출공정을 이용하여 전통적인 기존 추출공정과 비교함으로써 복합 추출공정에 의한 감귤의 항산화 활성 증진을 확인하고자 연구를 수행하였다. 건조공정을 거친 후 초고압 처리 추출물의 수율이 20.41~28.19%로 높은 추출 수율을 나타내어 건조전 열수추출공정(17.21%)과 비교하여 약 1.6배의 높은 추출수율을 나타내었다. 순환형 감압건조와 초고압 공정을 병행하였을 시 총 폴리페놀과 플라보노이드 함량이 순환형 감압건조공정을 거치지 않은 것보다 다소 증가되는 것으로 보아 활성성분의 용출이 증진된 것으로 보인다. DPPH radical 소거 활성은 15분 초고압 처리한 추출물이 48.21%로 높은 활성을 나타내었다. 전처리 공정에 따른 감귤 시료의 주사전자현미경(SEM)을 통해 순환형 감압건조 후 초고압 추출이 감귤 내부 조직까지 영향을 주어 세포벽이 깨어지면서 조직 및 구조가 변화한 것으로 판단되며, 이를 통해 수율 및 활성 성분의 용출 증가가 이루어 진 것으로 사료된다. 따라서, 감귤의 건조 및 초고압 추출공정의 최적화를 통한 활성물질의 추출 극대화를 통해 추출수율을 향상시킬 것으로 판단된다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2008년도 International Symposium on Remote Sensing
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• pp.147-150
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• 2008

This study refers to develop a semi-automatic extraction of agricultural land use and vegetation information using high resolution satellite images. Data of IKONOS satellite image (May 25 of 2001) and QuickBird satellite image (May 1 of 2006) which resembles with the spatial resolution and spectral characteristics of KOMPSAT3. The precise agricultural land use classification was tried using ISODATA unsupervised classification technique and the result was compared with on-screen digitizing land use accompanying with field investigation. For the extraction of vegetation information, three crops of paddy, com and red pepper were selected and the spectral characteristics were collected during each growing period using ground spectroradiometer. The vegetation indices viz. RVI, NDVI, ARVI, and SAVI for the crops were evaluated. The evaluation process is under development using the ERDAS IMAGINE Spatial Modeler Tool.

• 설비공학논문집
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• 제14권6호
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• pp.503-511
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• 2002

Heat flow characteristics during hot water extraction process was studied experimentally. Data were taken at various outlet port type for the fixed inlet port type, inlet-outlet temperature differences and mass flow rates. In this study, the temperature distribution in a storage tank and an outlet temperature were measured to predict a degree of stratification in the storage tank, and a useful rate of hot water was analysed with respect to the variables dominating a extraction process. Experimental results show that the degree of stratification and useful rate of hot water are all high in a low flow rate in case of using modified distributor I (MDI) as the outlet port type.

• ETRI Journal
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• 제33권4호
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• pp.547-557
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• 2011

This study presents an approach for extracting boundaries of various buildings, which have concave boundaries, inner yards, non-right-angled corners, and nonlinear edges. The approach comprises four steps: building point segmentation, boundary tracing, boundary grouping, and regularization. In the second and third steps, conventional algorithms are improved for more accurate boundary extraction, and in the final step, a new algorithm is presented to extract nonlinear edges. The unique characteristics of airborne light detection and ranging (LIDAR) data are considered in some steps. The performance and practicality of the presented algorithm were evaluated for buildings of various shapes, and the average omission and commission error of building polygon areas were 0.038 and 0.033, respectively.