• Child Health Nursing Research
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• v.22 no.2
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• pp.97-106
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• 2016

Purpose: The purpose of this study was to identify the relationship between mother child-rearing attitude, language control styles and preschool child's social competence, and also, to provide a basis for development of a program to promote preschool child's social competence. Methods: The present study was a descriptive research. Participants in this study were a convenience sample of 300 preschool children and their mothers. For the final analysis 264 questionnaires were used after eliminating questionnaires with incomplete responses. Data were analyzed using the SPSS 18.0 program. Results: The mean score for mother's child-rearing attitude was $3.31{\pm}0.25$ out of 5 points, for hierarchical language control styles ($2.76{\pm}0.62$), commanding ($1.95{\pm}0.58$), and humanistic ($2.48{\pm}0.62$) out of 5 points, and for child's social competence, $3.50{\pm}0.34$ out of 5 points. Negative correlations were found between commanding language control styles and child's social competence (r=-.34, p<.001), and between commanding language control style and mother's child-rearing attitude (r=-.50, p<.001). Conclusion: The results demonstrate the importance of the quality of mother's child-rearing attitude and language control styles for child's social competence. It is suggested that promotion programs to enhance preschool child's social competence should be developed in conjunction with the parenting related environment.

• Journal of information and communication convergence engineering
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• v.15 no.3
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• pp.170-174
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• 2017

Nowadays, people share and discuss scientific papers on social media such as the Web 2.0, big data, online forums, blogs, Twitter, Facebook and scholar community, etc. In addition to a variety of metrics such as numbers of citation, download, recommendation, etc., paper review text is also one of the effective resources for the study of scientific impact. The social media tools improve the research process: recording a series online scholarly behaviors. This paper aims to research the huge amount of paper reviews which have generated in the social media platforms to explore the implicit information about research papers. We implemented and shown the result of text mining on review texts using R language. And we found that Zika virus was the research hotspot and association research methods were widely used in 2016. We also mined the news review about one paper and derived the public opinion.

• International Journal of Contents
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• v.8 no.3
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• pp.26-33
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• 2012

The animal naming test (ANT) is known to be influenced not only by age, gender, and education but only by ethnicity, culture, and language. Thus, population-specific norm considering these variables needs to be developed for Korean-speaking elderly. We evaluated 185 healthy elderly people with five measures. Education was the single statistically independent correlate of the total number of words ($R^2$ = .312, p = .038). After adjusting for education, there was slightly significant negative correlation (r = -.215, p = .049) between age and total number of words. Mean number of words produced was $13.71{\pm}3.09$. The production frequency was negatively correlated with the typicality rating (r = -0.41, p < .05). The concrete and exact scoring rule could be set up in the comparison of naming performance between a normal and patient with neuro-linguistic disorder and its data could be utilized in a differential diagnosis for patients with neurological disorders.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.9
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• pp.281-290
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• 2020

The Vision-and-Language Navigation(VLN) task is a complex intelligence problem that requires both visual and language comprehension skills. In this paper, we propose a new learning model for visual-language navigation agents. The model adopts a hybrid learning that combines imitation learning based on demo data and reinforcement learning based on action reward. Therefore, this model can meet both problems of imitation learning that can be biased to the demo data and reinforcement learning with relatively low data efficiency. In addition, the proposed model uses a novel path-based reward function designed to solve the problem of existing goal-based reward functions. In this paper, we demonstrate the high performance of the proposed model through various experiments using both Matterport3D simulation environment and R2R benchmark dataset.

• Journal of Korean Society for Quality Management
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• v.47 no.4
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• pp.713-723
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• 2019

Purpose: The purpose of this study is to develop a statistical program for capability analysis of measuring system and measurement process based upon KS Q ISO 22514-7. Methods: R is a powerful open source functional programming language that provides high level graphics and interfaces to other languages. Therefore, in this study, we will develop the statistical program using R language. Results: The R program developed in this study consists of the following five modules. ① Measuring system capability analysis with Type 1 study data: MSCA_Type1.R ② Measuring system capability analysis with Linearity study(Type 4 study) data: MSCA_Type4.R ③ Measurement process capability analysis with Type 1 study & Gage R&R study data: MPCA_T1GRR.R ④ Measurement process capability analysis with Type 4 study & Gage R&R study data: MPCA_T4GRR.R ⑤ Attribute measurement processes capability analysis : AttributeMP.R Conclusion: KS Q ISO 22514-7 evaluates measuring systems and measurement processes on the basis of the measurement uncertainty that was determined according to the GUM(KS Q ISO/IEC Guide 98-3). KS Q ISO 22514-7 offers precise procedures, however, computations are more intensive. The R program of this study will help to evaluate the measurement process.

• Communications for Statistical Applications and Methods
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• v.15 no.1
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• pp.51-64
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• 2008

In general, R is useful for small size data. We study how to access a large data set in a database by R-language. We provide real examples to access data sets stored in database servers MySQL, Oracle or PostgreSQL.

• Annual Conference on Human and Language Technology
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• 2021.10a
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• pp.112-117
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• 2021

기계 학습을 활용하여 요약문을 생성했을 경우, 해당 요약문의 정확도를 측정할 수 있는 도구는 필수적이다. 원문에 대한 요약문의 사실관계 일관성의 파악을 위해 개체명 유사도, 기계 독해를 이용한 질문-답변 생성을 활용한 방법이 시도되었으나, 충분한 데이터 확보가 필요하거나 정확도가 부족하였다. 본 논문은 딥러닝 모델을 기반한 개체명 인식기와 질문-답변쌍 정확도 측정기를 활용하여 생성, 필터링한 질문-답변 쌍에 대해 일치도를 점수화하는 방법을 제안하였다. 이러한 기계적 사실관계 확인 점수와 사람의 평가 점수의 분포를 비교하여 방법의 타당성을 입증하였다.

• Proceedings of the Korean Society for Language and Information Conference
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• 2002.02a
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• pp.433-446
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• 2002

No Abstract(See Full Text)

• Annual Conference on Human and Language Technology
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• 1999.10d
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• pp.167-172
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• 1999

한국어 형태소 분석기는 한국어를 분석하여 여러 다른 응용프로그램에 적용할 수 있는 기본적인 도구이다. 형태소 분석기를 응용하여 맞춤법 검사기나 정보검색, 기계번역, 음성인식 등에 적용할 수 있다. 본 논문에서는 형태소 분석기를 이용하여 여러 응용프로그램에 다목적으로 적용할 수 있도록 COM(Component Object Model)으로 인터페이스를 설계하고, 일례로 명사를 추출하는 응용프로그램을 구현하였다.

• Annual Conference on Human and Language Technology
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• 2016.10a
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• pp.201-204
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• 2016

본 논문에서는 문서의 공기관계를 통해 추출된 문서의 특징을 이용하여 유사 보고서를 판별하는 시스템을 제안한다. 국가 R&D 보고서의 XML형식 파일에서 텍스트를 추출 후, 문장 단위로 나누어 각 문장의 공기 관계를 추출한다. 그 후 공기관계의 노드와 엣지를 문서에 추가하고, 노드로 사용된 단어만 남기고 나머지 단어는 제외한다. 그리고 이것을 문서의 특징으로 삼고 유사도 계산을 한다. 이 때, 유사도 계산은 코사인 유사도를 사용한다. 실험결과, 국가 R&D문서 유사도 계산에서 제안된 방법이 기존의 방법보다 높은 분류율을 보여주었다.