• Korean Journal of Child Studies
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• v.27 no.3
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• pp.135-148
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• 2006

The Foreign Language Classroom Anxiety Scale(Horwitz et al., 1986) and the Classroom Environment Scale(Moos & Tricket, 1974) were administered to 434 middle school students in Daegu. Data were analyzed by Cronbach's $\alpha$, t-test, and Pearson's correlation using the SPSS program. Results on anxiety showed no gender differences between male and female students but $9^{th}$ graders reported more anxiety than $7^{th}$ graders. Two of the nine classroom environment subscales showed differences between perceptions of male and female students, and there were significant differences between $7^{th}$ and $9^{th}$ graders. Foreign language anxiety was correlated with perceived classroom environment. This finding suggests the importance of the psychological environment between the English teacher and students for successful language education.

• Annual Conference on Human and Language Technology
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• 2023.10a
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• pp.56-60
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• 2023

기존의 음성인식은 청장년 층에 초점이 맞추어져 있었으나, 최근 고령화가 가속되면서 노인 음성에 대한 연구 필요성이 증대되고 있다. 그러나 노인 음성 데이터셋은 청장년 음성 데이터셋에 비해서는 아직까지 충분히 확보되지 못하고 있다. 본 연구에서는 부족한 노인 음성 데이터셋 확보에 기여하고자 희소한 노인 데이터셋을 증강할 수 있는 방법론에 대해 연구하였다. 이를 위해 노인 음성 특징(feature)을 분석하였으며, '주파수'와 '발화 속도' 특징을 일반 성인 음성에 합성하여 데이터를 증강하였다. 이후 Whisper small 모델을 파인 튜닝한 뒤 노인 음성에 대한 CER(Character Error Rate)를 구하였고, 기존 노인 데이터셋에 증강한 데이터셋을 함께 사용하는 것이 가장 효과적임을 밝혀내었다.

• International Journal of Advanced Culture Technology
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• v.11 no.4
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• pp.112-122
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• 2023

This study was conducted as part of a summer Korean language and culture program at a university in Korea, aimed at examining the changes in intercultural sensitivity among American students who participated in the program, as well as the Korean students who served as their language partners. The research utilized a mixed-method approach combining qualitative and quantitative analysis. To derive research findings, pre- and post-program Intercultural Sensitivity Scale surveys were administered to participating students and semi-structured interview data were collected from a randomly selected group of six students. The research findings indicated that among a total of twenty-seven students including both American and Korean students, significant changes in intercultural sensitivity were observed in the domain of Interaction Engagement. Furthermore, fourteen American students showed significant changes in their Interaction Confidence, while the Korean students who participated as language partners did not exhibit significant changes in the five subdomains of intercultural sensitivity.

• ETRI Journal
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• v.46 no.1
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• pp.96-105
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• 2024

We propose a method to automatically predict Alzheimer's disease from speech data using the ChatGPT large language model. Alzheimer's disease patients often exhibit distinctive characteristics when describing images, such as difficulties in recalling words, grammar errors, repetitive language, and incoherent narratives. For prediction, we initially employ a speech recognition system to transcribe participants' speech into text. We then gather opinions by inputting the transcribed text into ChatGPT as well as a prompt designed to solicit fluency evaluations. Subsequently, we extract embeddings from the speech, text, and opinions by the pretrained models. Finally, we use a classifier consisting of transformer blocks and linear layers to identify participants with this type of dementia. Experiments are conducted using the extensively used ADReSSo dataset. The results yield a maximum accuracy of 87.3% when speech, text, and opinions are used in conjunction. This finding suggests the potential of leveraging evaluation feedback from language models to address challenges in Alzheimer's disease recognition.

• Journal of Practical Engineering Education
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• v.12 no.2
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• pp.265-273
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• 2020

In this paper, to design a basic data science practice curriculum as a liberal arts subject for non-majors, we proposed an educational method using an Excel(spreadsheet) data analysis tool. Tools for data collection, data processing, and data analysis include Excel, R, Python, and Structured Query Language (SQL). When it comes to practicing data science, R, Python and SQL need to understand programming languages and data structures together. On the other hand, the Excel tool is a data analysis tool familiar to the general public, and it does not have the burden of learning a programming language. And if you practice basic data science practice with Excel, you have the advantage of being able to concentrate on acquiring data science content. In this paper, a basic data science practice curriculum for one semester and weekly Excel practice contents were proposed. And, to demonstrate the substance of the educational content, examples of Linear Regression Analysis were presented using Excel data analysis tools.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.164-167
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• 2022

In table Machine comprehension, the knowledge required for language models or the structural form of tables changes depending on the domain, showing a greater performance degradation compared to text data. In this paper, we propose a pre-learning data construction method and an adversarial learning method through meaningful tabular data selection for constructing a pre-learning table language model robust to these domain changes in table machine reading. In order to detect tabular data sed for decoration of web documents without structural information from the extracted table data, a rule through heuristic was defined to identify head data and select table data was applied. An adversarial learning method between tabular data and infobax data with knowledge information about entities was applied. When the data was refined compared to when it was trained with the existing unrefined data, F1 3.45 and EM 4.14 increased in the KorQuAD table data, and F1 19.38, EM 4.22 compared to when the data was not refined in the Spec table QA data showed increased performance.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.627-630
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• 2001

XML is suitable to integrate various forms of engineering design data since it possesses the characteristics of both documents and data. In this research a web-based design system has been developed, which integrates various gear design data in the form of XML. The system generates XML document containing gear design data and transforms gear design data in the relational database into XML document form automatically. The XML documents are transmitted to gear modeler agent through SOAP, and then the agent is automatically executed and generates CAD model files and VRML files. The designer can check the generated VRML model of gear immediately in the web service.

• Journal of Fisheries and Marine Sciences Education
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• v.17 no.3
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• pp.427-433
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• 2005

The study of Web GUI(Graphic User Information) system for Virtual Reality System is mainly performed on effective methodology which transform real world data to computing world data. MGIS(Marine Geographic Information System) has its own target on reliable data service by acquisition of geometric information using accurate measurement and graphical visualization. This type of raw data visualization can be built without software tools, yet is incredibly useful for interpreting and communicating data. Even simple visualizations can aid in the interpretation of complex 3D relationships that are frequently encountered in the geosciences. The Virtual Reality Modeling Language provides an easy way for geoscientists to construct complex visualizations that can be viewed with free software. This study propose a three dimensional Web GUI system using MGIS-based three dimensional data models and virtual imaging system. Finally, we design a Web GUI system integrating above data models.

• Annual Conference on Human and Language Technology
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• 1997.10a
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• pp.277-282
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• 1997

최근 들어 웹 상의 문서를 번역해 주는 번역 시스템이 상용화되고 있다. 일반 문서와 달리 웹 문서는 HTML 태그를 포함하고 있어 번역 시스템에서 문장 단위로 분리하는데 어려움이 있다. 또한 그 대상 영역이 제한되지 않으므로 미등록어 및 구문 분석 실패에 대한 대처 기능이 필요하다. 따라서 웹 문서의 번역 품질이 일반 문서 번역에 비해 현저히 떨어지게 된다. 이 논문에서는 HTML 태그를 보유한 영어 웹 문서를 대상으로 하는 번역 시스템인 "에서로-웹/EK"에 대해 기술한다. 에서로-웹/EK는 HTML 문서의 특성을 고려하여 태그를 분리, 복원하는 태그 관리자를 별도로 가진다. 또한 태그를 유지하면서 영어에서 한국어로 변환되는 과정에서 발생하는 어휘 분리, 어휘 통합, 어순 변환 둥의 다양한 변환 현상을 처리한다. 이 시스템은 변환 방식에 기반한 번역 시스템으로서 영어 해석, 영한 변환, 한국어 생성의 단계를 거친다. 구현된 시스템은 Netscape와 DDE(Dynamic Data Exchange) 방식으로 연동하여 HTML 문서를 번역한다.

• Journal of Families and Better Life
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• v.32 no.6
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• pp.47-58
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• 2014

The purpose of this study was to examine the effects of mothers' parenting behavior, preschool children's language ability and emotion regulation on peer competence and aggressive behavior. The subjects were 100 preschool children (49 girls and 51 boys; mean age, 70.30 months), their mothers and teachers, recruited from five daycare centers located in Gyeonggi-do area. Each child's language ability was assessed individually with the standardized measure, the Preschool Receptive-Expressive Language Scale and their teachers reported on the children's peer competence and aggressive behavior. Their mothers also reported on parenting behavior and their child's emotion regulation by questionnaire. The collected data was analyzed by correlation analysis and hierarchical regression. The main results of this study were as follows. First, preschool children's peer competence was positively related to maternal warmth and children's language ability. Their aggressive behavior was positively related to harsh maternal parenting but negatively related to emotion regulation. Second, hierarchical regression analyses revealed that children's language ability and maternal warmth predicted peer competence. Third, children's gender, emotion regulation, and harsh maternal parenting predicted aggressive behavior. These findings could provide basic information for programs and services to promote peer competence in preschool children.