• Microbiology and Biotechnology Letters
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• v.46 no.3
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• pp.300-312
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• 2018

Whole-genome sequencing of the wood-rotting fungus, Flammulina fennae, was carried out to identify carbohydrate-active enzymes (CAZymes). De novo genome assembly (31 kmer) of short reads by next-generation sequencing revealed a total genome length of 32,423,623 base pairs (39% GC). A total of 11,591 gene models in the assembled genome sequence of F. fennae were predicted by ab initio gene prediction using the AUGUSTUS tool. In a genome-wide comparison, 6,715 orthologous groups shared at least one gene with F. fennae and 10,667 (92%) of 11,591 genes for F. fennae proteins had orthologs among the Dikarya. Additionally, F. fennae contained 23 species-specific genes, of which 16 were paralogous. CAZyme identification and annotation revealed 513 CAZymes, including 82 auxiliary activities, 220 glycoside hydrolases, 85 glycosyltransferases, 20 polysaccharide lyases, 57 carbohydrate esterases, and 45 carbohydrate binding-modules in the F. fennae genome. The genome information of F. fennae increases the understanding of this basidiomycete fungus. CAZyme gene information will be useful for detailed studies of lignocellulosic biomass degradation for biotechnological and industrial applications.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.1615-1617
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• 2015

웹을 통한 데이터 공유에 대한 관심의 증가로 RDF 트리플 형태의 데이터가 폭발적으로 증가하고 있다. 대용량 RDF 데이터를 저장하고 빠른 SPARQL 질의 처리를 지원하는 트리플 저장소의 개발이 중요하다. 아파치 프로젝트 중 하나인 Jena-TDB는 가장 잘 알려진 오픈소스 트리플 저장소 중 하나로서 Jena 프레임워크 기반으로 구현됐다. 하지만 Jena-TDB 의 경우 단일 컴퓨터에서 작동하기 때문에 대용량 RDF 데이터를 다룰 수 없다는 문제점이 있다. 본 논문에서는 MongoDB를 활용한 Jena 프레임워크 기반의 트리플 저장소인 Jena-MongoDB를 제안한다. Jena 프레임워크를 사용했기 때문에 기존 Jena-TDB와 동일한 인터페이스로 사용할 수 있고 최신 표준 SPARQL 문법도 지원한다. 또한 MongoDB를 사용했기 때문에 분산환경에서도 작동할 수 있다. 대용량 LUBM 데이터셋에 대한 SPARQL 질의 처리 실험결과 Jena-MongoDB가 Jena-TDB 보다 빠른 질의 응답 속도를 보여줬다.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.11a
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• pp.112-113
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• 2008

유방암은 유럽과 미국을 비롯해 전 세계적으로 증가하고 있으며 최근 우리나라에서도 가장 급속하게 늘고 있는 여성암중에 하나이다. 본 연구에서는 먼저 grey level co-occurrence matrix(GLCM)을 적용하여 유방영역을 분할한 후, median filter 를 적용하여 잡음을 제거하였다. 전처리 수행 후, 2차미분 행렬을 이용할여 미소석회화 부분을 강조한 후, 가우시안 정규분포도를 적용하여 미소석회화 후보군을 검출하였다. 검출된 후보군은 8 개의 feature 들을 적용하여 미소석회화를 최종 결정하였다. 본 연구를 통해서 조기 유방암 진단을 위한 발전된 미소석회화 검출 방법을 제안하였다.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.05
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• pp.240-242
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• 1996

In this paper, we proposed a method of a hearing aid suitable for the sensorineural hearing impaired. Generally as the sensorineural hearing impaired have narrow audible ranges between threshold and discomfortable level, the speech spectrum may easily go beyond their audible range. Therefore speech spectrum must be optimally amplified and compressed into the impaired's audible range. The level and frequency of input speech signal are varied continuously. So we have to make compensation input signal for frequency-gain loss of the impaired, specially in the frequency band which includes much information. The input sigaal is divided into short time block and spectrum within the block is calculated. The frequency-gain characteristic is determined using the calculated spectrum. The number of frequency band and the target gain which will be added input signal are estimated. The input signal within the block is processed by a single digital filter with the calculated frequency-gain characteristics. From the results of monosyllabic speech tests to evaluate the performance of the proposed algorithm, the scores of test were improved.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.11
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• pp.111-113
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• 1996

The impaired person and the elderly who has hearing loss have been continuously increased and these people's desire for participating society as a producer has been increased also. So they strongly request the aid device which can compensate their handicap. The healing aid telephone is one of the basic aid devices that helps the hearing impaired to communicate with other people and to acquire useful information. We design the new model of the hearing aid telephone and test it's efficiency in three fields - electrical, speech perception, user test. From the result of the test we certify that the new model is better for the hearing impaired to understand the meaning of telephone speech than the old general models. We expect that the advanced healing aid telephone can be developed by the research about speech perception characteristics of the hearing impaired in engineering and clinical side.

• The Korean Journal of Health Service Management
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• v.6 no.4
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• pp.37-48
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• 2012

This study sought to provide basic for the establishment of desirable sense of ethics values by analyzing the consciousness of biomedical ethics of freshmen nursing students. The subjects of the study were 420 freshmen nursing students. The period of data collection was from April 1 to 6, 2012 and collected data were analyzed on SPSS/PC 19.0 program. The results is followed; First, the mean score of the consciousness of biomedical ethics was $2.39{\pm}0.25$. While the mostly high ranked category of biomedical ethics was the right to life of newborn($2.76{\pm}0.39$), the category with the lowest score was the artificial abortion($2.13{\pm}0.39$). Second, with respect to the characteristics of participants there were statistically significant difference in total score according to age, religion, and participation in religious activity, experience of hearing for biomedical ethics, sources of information for biomedical ethics, ethical values for biomedical ethics, and in intention to attend biomedical ethics in subjects. As a result, an arbitration program that could promote either changeable or controllable ethical values must be considered with attention to the significant variables that can promote the consciousness of biomedical ethics of freshmen nursing students.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.10
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• pp.1830-1840
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• 2011

CDISC (Clinical Data Interchanging Standards Consortium) standards are to support the acquisition, exchange, submission and archival of clinical trial and research data. SDTM (Study Data Tabulation Model) for Case Report Forms (CRFs) was recommended for U.S. Food and Drug Administration (FDA) regulatory submissions since 2004. Although the SDTM Implementation Guide gives a standardized and predefined collection of submission metadata 'domains' containing extensive variable collections, transforming CRFs to SDTM files for FDA submission is still a very hard and time-consuming task. For addressing this issue, we developed metadata based SDTM mapping rules. Using these mapping rules, we also developed a semi-automatic tool, named CDISC Transformer, for transforming clinical trial data to CDISC standard compliant data. The performance of CDISC Transformer with or without MDR support was evaluated using CDISC blank CRF as the 'gold standard'. Both MDR and user inquiry-supported transformation substantially improved the accuracy of our transformation rules. CDISC Transformer will greatly reduce the workloads and enhance standardized data entry and integration for clinical trial and research in various healthcare domains.

• Journal of Information Processing Systems
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• v.8 no.4
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• pp.575-588
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• 2012

Exploiting unlabeled text data with a relatively small labeled corpus has been an active and challenging research topic in text mining, due to the recent growth of the amount of biomedical literature. Biomedical named-entity recognition is an essential prerequisite task before effective text mining of biomedical literature can begin. This paper proposes an Active Co-Training (ACT) algorithm for biomedical named-entity recognition. ACT is a semi-supervised learning method in which two classifiers based on two different feature sets iteratively learn from informative examples that have been queried from the unlabeled data. We design a new classification problem to measure the informativeness of an example in unlabeled data. In this classification problem, the examples are classified based on a joint view of a feature set to be informative/non-informative to both classifiers. To form the training data for the classification problem, we adopt a query-by-committee method. Therefore, in the ACT, both classifiers are considered to be one committee, which is used on the labeled data to give the informativeness label to each example. The ACT method outperforms the traditional co-training algorithm in terms of f-measure as well as the number of training iterations performed to build a good classification model. The proposed method tends to efficiently exploit a large amount of unlabeled data by selecting a small number of examples having not only useful information but also a comprehensive pattern.

• Proceedings of the KOSOMBE Conference
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• v.1995 no.11
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• pp.269-272
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• 1995

• Proceedings of the KSMRM Conference
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• 1999.11a
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• pp.114-114
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• 1999