• 대한음성학회:학술대회논문집
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• 대한음성학회 2003년도 10월 학술대회지
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• pp.37-40
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• 2003

This paper presents the preliminary result of the automatic pronunciation scoring for non-native English speakers, and shows the developmental process for an English speech recognizer for the educational and evaluational purposes. The proposed speech recognizer, featuring two refined acoustic model sets, implements the noise-robust data compensation, phonetic alignment, highly reliable rejection, key-word and phrase detection, easy-to-use language modeling toolkit, etc., The developed speech recognizer achieves 0.725 as the average correlation between the human raters and the machine scores, based on the speech database YOUTH for training and K-SEC for test.

• 디지털산업정보학회논문지
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• 제7권2호
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• pp.19-27
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• 2011

Recent development of information technologies produces a lot of community services. Social Network Service is one of the community services on the world wide webs. In the Social Network Service, a user can register other users as friends and enjoy communication through a virtual message. Previous researches show a few social service methods using manually generated tagging. However, the manual social tagging is not widely used in many social network services. Moreover, they do not consider ubiquitous computing environment. We propose a recommendation method for social service using contexts in ubiquitous environment. Our method scores documents based on context tags and social network services. Our social scoring model is computed by both a tagging score of a document and a tagging score of a document that was tagged by a user's friends.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2016년도 춘계학술발표대회
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• pp.821-823
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• 2016

본 논문은 다차원 정서모델 기반 영상, 음성, 뇌파를 이용한 멀티모달 복합 감정인식 시스템을 제안한다. 사용자의 얼굴 영상, 목소리 및 뇌파를 기반으로 각각 추출된 특징을 심리학 및 인지과학 분야에서 인간의 감정을 구성하는 정서적 감응요소로 알려진 다차원 정서모델(Arousal, Valence, Dominance)에 대한 명시적 감응 정도 데이터로 대응하여 스코어링(Scoring)을 수행한다. 이후, 스코어링을 통해 나온 결과 값을 이용하여 다차원으로 구성되는 3차원 감정 모델에 매핑하여 인간의 감정(단일감정, 복합감정)뿐만 아니라 감정의 세기까지 인식한다.

• Journal of Information Processing Systems
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• 제16권4호
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• pp.820-831
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• 2020

Extractive document summarization aims to select a few sentences while preserving its main information on a given document, but the current extractive methods do not consider the sentence-information repeat problem especially for news document summarization. In view of the importance and redundancy of news text information, in this paper, we propose a neural extractive summarization approach with joint sentence semantic clipping and selection, which can effectively solve the problem of news text summary sentence repetition. Specifically, a hierarchical selective encoding network is constructed for both sentence-level and document-level document representations, and data containing important information is extracted on news text; a sentence extractor strategy is then adopted for joint scoring and redundant information clipping. This way, our model strikes a balance between important information extraction and redundant information filtering. Experimental results on both CNN/Daily Mail dataset and Court Public Opinion News dataset we built are presented to show the effectiveness of our proposed approach in terms of ROUGE metrics, especially for redundant information filtering.

• 산업경영시스템학회지
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• 제14권23호
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• pp.57-64
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• 1991

The preliminary, advanced and final evaluation of R&D project is essential in order to reduce loss of resource and opportunity and to minimize uncertainty resulting from optimal selection and efficient progress of R&D project. This thesis examined characteristics of deterministic evaluation, economical evaluation, and OR-approach evaluation as theoretical methodology of evaluation of R&D project applicable to food industry in Korea by using scoring method, one of deterministic evaluations. In addition, this thesis divided the evaluation factors for preliminary evaluation of R&D project into 5 groups and 30 factors on basis of the environment of domestic companies and set up the standard of each evaluation factors and contains marking-selecting way. But, generally, the evaluation model by this thesis, as the conditions of the business company environment are different to each other, contents to be set up evaluation factors, evaluation standard and decision method conforming to each the environment of the business companies with referring to as one standard of evaluation project for selecting R&D project.

• 한국정보과학회 언어공학연구회:학술대회논문집(한글 및 한국어 정보처리)
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• 한국정보과학회언어공학연구회 2022년도 제34회 한글 및 한국어 정보처리 학술대회
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• pp.354-359
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• 2022

에세이 자동 평가는 주어진 에세이를 읽고 자동으로 평가하는 작업이다. 본 논문에서는 효과적인 에세이 자동 평가 모델을 위해 Argument Mining 작업을 사용하여 에세이의 논증 구조가 반영된 에세이 표현을 만들고, 에세이의 평가 항목별 표현을 학습하는 방법을 제안한다. 실험을 통해 제안하는 에세이 표현이 사전 학습 언어 모델로 얻은 표현보다 우수함을 입증했으며, 에세이 평가를 위해 평가 항목별로 다른 표현을 학습하는 것이 보다 효과적임을 보였다. 최종 제안 모델의 성능은 QWK 기준으로 0.543에서 0.627까지 향상되어 사람의 평가와 상당히 일치한다.

• 한국정보과학회 언어공학연구회:학술대회논문집(한글 및 한국어 정보처리)
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• 한국정보과학회언어공학연구회 2023년도 제35회 한글 및 한국어 정보처리 학술대회
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• pp.327-332
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• 2023

데이터의 품질과 다양성은 모델 성능에 지대한 영향을 끼친다. 본 연구에서는 Topic을 활용한 데이터 전처리와 BERT 기반 MLM, T5, Random Masking을 이용한 증강으로 데이터의 품질과 다양성을 높이고자 했으며, 이를 KoBERT 기반 에세이 자동 평가 모델에 적용했다. 데이터 전처리만 진행했을 때, Quadratic Weighted Kappa Score(QWK)를 기준으로 모델이 에세이의 모든 평가 항목에 대해 베이스라인보다 더욱 높은 일치도를 보였으며 평가항목별 일치도의 평균을 기준으로 0.5368029에서 0.5483064(+0.0115035)로 상승했다. 여기에 제안하는 증강 방식을 추가 할 경우 MLM, T5, Random Masking 모두 성능 향상 효과를 보였다. 특히, MLM 데이터 증강 방식을 추가로 적용하였을 때 최종적으로 0.5483064에서 0.55151645(+0.00321005)으로 상승해 가장 높은 일치도를 보였으며, 에세이 총점으로 QWK를 기준으로 성능을 평가하면 베이스라인 대비 0.4110809에서 0.4380132(+0.0269323)로의 성능 개선이 있었다.

• Journal of Korean Biological Nursing Science
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• 제16권3호
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• pp.219-225
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• 2014

Purpose: This study was aimed to evaluate the effect of blending oils on atopic dermatitis (AD) model of NC/Nga mice. Methods: Adult NC/Nga mice were assigned to 1 of 3 groups: control group (C, n=8), experimental group [AD-induced group, blending oil-treated group (E=8, 8)]. Mice in the E group were given a treatment of blending oils such as Lavender, Rosemary and Lemon Balm (LRL) for 2 sessions (every day) for 6 days. Results: The AD-induced mice with LRL blending oils treatment showed a significant decrease in epidermal thickness, number of mast cells and degranulation, expression of TNF-${\alpha}$ and scoring of sensual assessment. Conclusion: LRL blending oils may be a putative resource for the cure of or treatment of AD by the diminution of AD-pathological factors such as the epidermal thickness, the number of mast cells and degranulation as well as the expression of TNF-${\alpha}$.

• 품질경영학회지
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• 제32권4호
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• pp.92-102
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• 2004

In this era of intense competition, TQM has become the key program in organizations as they strive for a competitive advantage. It has been applied to manufacturing and service sector since BNQA model was established in 1987. TQM literature for manufacturing sector abounds with empirical studies on the critical dimensions of TQM, but there is few empirical studies on the TQM evaluation for service sector. In this paper, two methodologies are applied to evaluate the TQM activities of service companies comparatively One of them is the traditional scoring system(TSS) by analytic hierarchy process(AHP). The other is the efficiency measuring system(EMS) by data envelopment analysis(DEA). DEA outperformed other alternative methods to measure the efficiency and it can be applied to evaluate the TQM activities. The objective of this paper is to evaluate TQM activities of domestic service companies by applying TAE(Total quality management Activities Evaluation) model to them. The result of this study is that TSS scores are not significantly correlated with EMS scores. It means that service organizations must not only make efforts to get the higher scores in terms of TSS but also take necessary steps to enhance their efficiencies.

• 융합보안논문지
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• 제15권5호
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• pp.77-86
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• 2015

조직은 고객 정보 유출과 관련된 비즈니스 위험을 최소화하고, 자발적인 사전 검사를 통해 정보 보안 활동을 강화하고 부주의 방치 사고에 의한 개인 정보의 누출을 검출하는 방법을 발견해야 한다. 최근 많은 기업들이 정보유출방지솔루션을 도입하였으나, 업무산 필요에 의한 허용된 권한을 가진 내부 사용자에 의한 유출가능성이 존재한다. 이에 정보취급행위 및 활동에 대한 정보를 수집하여 분석할 수 있는 환경이 필요하다. 본 연구에서는 내부자의 활동 수준을 평가하기 위해서 RFM 모델을 응용한 SFI 분석기법을 활용, 실제 기업에 적용하여 사례 연구를 수행하였다.