• Journal of Information Management
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• v.40 no.4
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• pp.1-22
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• 2009

Large-scaled information extraction plays an important role in advanced information retrieval as well as question answering and summarization. Information extraction can be defined as a process of converting unstructured documents into formalized, tabular information, which consists of named-entity recognition, terminology extraction, coreference resolution and relation extraction. Since all the elementary technologies have been studied independently so far, it is not trivial to integrate all the necessary processes of information extraction due to the diversity of their input/output formation approaches and operating environments. As a result, it is difficult to handle scientific documents to extract both named-entities and technical terms at once. In this study, we define scientific as a set of 10 types of named entities and technical terminologies in a biomedical domain. in order to automatically extract these entities from scientific documents at once, we develop a framework for scientific core entity extraction which embraces all the pivotal language processors, named-entity recognizer, co-reference resolver and terminology extractor. Each module of the integrated system has been evaluated with various corpus as well as KEEC 2009. The system will be utilized for various information service areas such as information retrieval, question-answering(Q&A), document indexing, dictionary construction, and so on.

• Journal of Pharmaceutical Investigation
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• v.40 no.3
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• pp.155-160
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• 2010

A gas chromatographic-mass spectrometric (GC-MS) method was developed for the simultaneous determination of valproic acid (VPA) and its toxic metabolites, 4-ene-VPA and 2,4-diene-VPA in rat plasma. Extraction was performed in weak acidic condition (pH 5.2) to avoid degradation of 4-ene-VPA and 2,4-diene-VPA. The recoveries for 4-ene-VPA and 2,4-diene-VPA were more than 70% and that for VPA was 33-42%. R value for each compounds exceeded 0.998 in calibration curve during all the analysis. Accuracy and precision ranged from 88.3 to 113.2% and from 2.16 to 14.2%, respectively The method was successfully applied to monitor plasma concentrations of VPA, 4-ene-VPA and 2,4-diene-VPA after intravenous administration of VPA at the dose of 100 mg/kg, suggesting that these toxic metabolites may involved in the hepatotoxicity induced by VPA.

• Genomics & Informatics
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• v.18 no.1
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• pp.7.1-7.7
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• 2020

In this paper, we present few technical notes about the distance distribution paradigm for Mosaab-metric using 1, 2, and 3 grams feature extraction techniques to analyze composite data points in high dimensional feature spaces. This technical analysis will help the specialist in bioinformatics and biotechnology to deeply explore the biodiversity of influenza virus genome as a composite data point. Various technical examples are presented in this paper, in addition, the integrated statistical learning pipeline to process segmented genomes of influenza virus is illustrated as sequential-parallel computational pipeline.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07b
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• pp.43-45
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• 2005

XML 스키마의 수가 급증함에 따라 동일한 도메인에 속하는 유사한 스키마를 통합하는 방법에 대한 관심이 증가하고 있다. 일반적으로 XML 스키마 통합 과정은 스키마 클러스터링과 통합 스키마 추출의 두 단계로 구성된다. 본 논문에서는 통합 스키마의 추출을 위한 효율적인 방법을 제안한다. 제안된 방법은 공통 구조 추출, 스키마 통합, 그리고 최적화의 세 단계로 이루어진다. 실험결과, 제안된 방법은 처리시간 및 정확도 측면에서 우수란 결과를 보였다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.4
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• pp.438-445
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• 2017

Tanzania has abundant copper deposits, but copper-metal extraction remains low there, owing to the lack of suitable copper recovery processes and insufficient funds for developing mining technologies. Accordingly, leaching and solvent extraction methods for the extraction of copper from copper ore were studied with a particular emphasis on developing a simple processing method for small-scale copper mining. Chrysocolla ore was used as the copper-bearing mineral and sulfuric acid was used as the leaching reagent. A maximum copper recovery of 95.1% was obtained when the particles in the sample were smaller than $53{\mu}m$, the concentration of 98%(w/w) sulfuric acid in the leaching solution was 5.0 g/L and the stirring rate was between 60 and 80 rpm. The highest selectivity of $Cu^2+$ in the solvent extraction was obtained using 15% LIX-70 in kerosene. In the pH range from 0.5 to 3.0, the efficiency of $Cu^2+$ extraction increased with increasing pH. However, at pH values higher than 3.0, other metal ions were extracted into the organic phase more readily than $Cu^2+$. The highest solvent extraction rate obtained was 96.5% at pH values of 2.0 and 3.0 using 15% LIX-70.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.9
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• pp.259-269
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• 2012

With the lower supply voltage and the higher operating frequency in integrated circuits, the analysis of the power distribution network (PDN) including on-chip inductances becomes more important. In this paper, an effective inductance extraction method for a regular on-chip power grid structure is proposed. The loop inductance model applicable to chip layout is proposed and the inductance extraction tool using the proposed inductance model based on post layout RC circuits is developed. The accuracy of the proposed loop model and the developed tool is verified by comparing the test circuit simulation results with those from the partial element equivalent circuit (PEEC) model. The voltage fluctuation from the RLC circuits extracted by the developed tool was examined for the analysis of on-chip inductance effects. The significance of on-chip power grid inductance was investigated by the co-simulation of chip-package-PCB.

• Journal of Soil and Groundwater Environment
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• v.23 no.4
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• pp.48-59
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• 2018

Beryllium (Be), cobalt (Co), thallium (Tl) and vanadium (V) are candidates of 21 priority soil pollutants in Korea. The distribution of their concentration in soils from three contamination sources including industrial, roadside and mining areas was investigated. Concentrations of the metals were evaluated quantitatively using pollution indices and the fractionation of metals was conducted using modified SM&T (Standards Measurements and Testing programme) sequential extraction. Concentrations of the metals for all samples from industrial and roadside soils were within the range of natural background levels, while some of Be in soils from abandoned mines exceeded that the range. Enrichment Factor (EF) and Nemerow Integrated Pollution Index (NIPI) for Be, Co, Tl and V showed that there are effects or possibilities of anthropogenic activities. Pollution Load Index (PLI) analyses indicated all investigated sites needed further monitoring. The results of sequential extractions indicated mobile fractions (F1+F2) of Be, Tl and V were below 30% except some of Co in soil, which implies their low mobility to neighboring environment media. Variable tools like sequential extraction, comparison with background/actual concentration and pollution indices, as well as aqua regia extraction should be considered when evaluating Be, Co, Tl, V in soil.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.5
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• pp.379-387
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• 2001

We proposed an enhanced extraction method of vehicle plate, in which both the brightness variation of gray and the Hue value of HSI color model were used. For the extraction of the vehicle plate from a vehicle image, first of all, candidate regions for the vehicle plate were extracted from the image by using the property of brightness variation of the image. A real place region was determined among candidate regions by the density of pixels with the Hue value of green and white. For- extracting the feature area containing characters from the extracted vehicle plate, we used the histogram-based approach of individual characters. And we proposed and applied for the recognition of characters the enhanced ART2 algorithm which support the dynamical establishment of the vigilance threshold with the genera]iced union operator of Yager. In addition, we propose an enhanced SOSL algorithm which is integrated both enhanced ART2 and supervised learning methods. The performance evaluation was performed using 100's real vehicle images and the evaluation results demonstrated that the extraction rates of tole proposed extraction method were improved, compared with that of previous methods based un brightness variation, RGB and HSI individually . Furthermore, the recognition rates of the proposed algorithms were improved much more than that of the conventional ART2 and BP algorithms.

• Journal of Energy Engineering
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• v.10 no.3
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• pp.188-194
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• 2001

The process simulations are made on the IGCC power plant using heavy residue oil from refinery process. In order to model combined power block of IGCC, the present study employs the gas turbine of MS7001FA model integrated with ASU (Air Separation Unit), and considers the air extraction from gas turbine and the combustor dilution by returned nitrogen from ASU. The exhaust gas energy of gas turbine is recovered through the bottoming cycle with triple pressure HRSG (Heat Recovery Steam Generator). Clean syngas fuel of the gas turbine is assumed to be produced through Shell gasification of Visbreaker residue oil and Sulfinol-SCOT-Claus gas cleanup processes. The process optimization results show that the best efficiency of IGCC plant is achieved at 20% air extraction condition in the case without nitrogen dilution of gas turbine combustor find at the 40% with nitrogen dilution. Nitrogen dilution of combustor has very favorable and remarkable effect in reducing NOx emission level, while shifting the operation point of gas turbine to near surge point.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.8
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• pp.371-380
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• 2023

Relation extraction is to extract relationships between named entities from text. Traditionally, relation extraction methods only extract relations between predetermined subject and object entities. However, in end-to-end relation extraction, all possible relations must be extracted by considering the positions of the subject and object for each pair of entities, and so this method uses time and resources inefficiently. To alleviate this problem, this paper proposes a method that sets directions based on the positions of the subject and object, and extracts relations according to the directions. The proposed method utilizes existing relation extraction data to generate direction labels indicating the direction in which the subject points to the object in the sentence, adds entity position tokens and entity type to sentences to predict the directions using a pre-trained language model (KLUE-RoBERTa-base, RoBERTa-base), and generates representations of subject and object entities through probabilistic crossover operation. Then, we make use of these representations to extract relations. Experimental results show that the proposed model performs about 3 ~ 4%p better than a method for predicting integrated labels. In addition, when learning Korean and English data using the proposed model, the performance was 1.7%p higher in English than in Korean due to the number of data and language disorder and the values of the parameters that produce the best performance were different. By excluding the number of directional cases, the proposed model can reduce the waste of resources in end-to-end relation extraction.