• The Journal of the Convergence on Culture Technology
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• v.7 no.2
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• pp.427-436
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• 2021

The purpose of this study is to implement a machine learning language model that learns literary texts. Literary texts have an important characteristic that pairs of question-and-answer are not frequently clearly distinguished. Also, literary texts consist of pronouns, figurative expressions, soliloquies, etc. They hinder the necessity of machine learning using literary texts by making it difficult to learn algorithms. Algorithms that learn literary texts can show more human-friendly interactions than algorithms that learn general sentences. For this goal, this paper proposes three text correction tasks that must be preceded in researches using literary texts for machine learning language model: pronoun processing, dialogue pair expansion, and data amplification. Learning data for artificial intelligence should have clear meanings to facilitate machine learning and to ensure high effectiveness. The introduction of special genres of texts such as literature into natural language processing research is expected not only to expand the learning area of machine learning, but to show a new language learning method.

• Korean Journal of Construction Engineering and Management
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• v.21 no.6
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• pp.125-134
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• 2020

Natural language encountered in construction documents largely deviates from those that are recommended by the authorities. Such practice that is lacking in coherence will discourage integrated research with automation, and it will hurt the productivity in the industry for the long run. This research aims to compare multiple string similarity (string matching) algorithms to compare each algorithm's performance in recognizing the same task name written in multiple different ways. We also aim to start a debate on how prevalent the aforementioned deviation is. Finally, we composed a small dataset that associates construction task names found in practice with the corresponding task names that are less cluttered w.r.t their formatting. We expect that this dataset can be used to validate future natural language processing approaches.

• Journal of Convergence for Information Technology
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• v.7 no.1
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• pp.87-92
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• 2017

This paper discusses the possibility of enhancing the efficiency in Second Language Learning with the help of an educational information and content search system that utilizes a Cloud system based Big Data. The proposed system plays a role in tracing the exact information that user request considering the interest, level, and aptitude of each individual. Also, the system screen outs unnecessary learning materials if they do not correspond to the user level which in result is one of the key factor in the proposed system. Since it requires multiple steps of verification in providing the extracted results finding out a way to reduce the steps to shorten the time of process.

• Journal of Convergence for Information Technology
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• v.10 no.10
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• pp.318-324
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• 2020

The present study was conducted to investigate the influences of emotion priming and the number of negation words on the task of sentential predicate reasoning in groups with or without anxiety symptoms. 3 types of primed emotions and 2 types of stimulus and 3 conditions of negation words were used as a within-subject variable. The subjects were instructed to make facial expressions that match the directions, and were asked to choose the correct answer from the given examples. Mixed repeated measured ANOVA analyses on reaction time first showed main effects for the variables of emotion, stimulus, number of negation words and anxiety level, and the interaction effects for the negation words x anxiety combination. These results are presumably suggested to reflect that externally intervening emotion works on language comprehension in a way that anxiety could delay task processing speed regardless of the emotion and stimulus type, meanwhile the number of negation words can slower language processing only in a anxiety group. Implications and limitations were discussed for the future work.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.4
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• pp.309-314
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• 2011

As a system becomes more complex, a design relies more heavily on a methodology based on high-level abstraction and functional verification. SystemVerilog includes characteristics of hardware design language and verification language in the form of extensions to the Verilog HDL. However, the OOP of System Veri log does not allow multiple inheritance. In this paper, we propose adoption of SystemC to introduce multiple inheritance. After being created, a SystemC unit is combined with a SystemVerilog-based verification environment using SystemVerilog DPI and ModelSim macro. Employing multiple inheritance of SystemC makes a design of a verification environment simple and easy through source code reuse. Moreover, a verification environment including SysemC unit has a benefit of reconfigurability due to OOP.

• Journal of Convergence for Information Technology
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• v.11 no.11
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• pp.312-326
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• 2021

Building on the framework of language socialization [10] in language learning and use, the present study examines the environmental factors involved in four college students' English learning in the situated place of the home during the COVID-19 pandemic. Using narrative inquiry, this study implements a time-series analysis to investigate undergraduates' online English learning in a rural area of northwest China. The data were collected via oral and written narration, semi-structured interviews, and class documents. Leveraging the field-habitus theories, the findings reveal that each of the students had a different habitus in the family field that influenced their English learning at home between March to July of 2020. Ultimately, all four students felt that their habitus made their online English learning ineffective and expressed that they did not wish to continue learning at home. The findings imply that it is important for rural parents to pay more attention to building college students' learning environments and helping students cultivate a strong learning habitus in the family field in northwest China.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.391-396
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• 2024

This study proposes a novel reverse N-Gram approach to overcome the limitations of traditional N-Gram methods and enhance performance in building an entity dictionary specialized for the healthcare sector. The proposed reverse N-Gram technique allows for more precise analysis and processing of the complex linguistic features of healthcare-related big data. To verify the efficiency of the proposed method, big data on healthcare and digital health announced during the Consumer Electronics Show (CES) held each January was collected. Using the Python programming language, 2,185 news titles and summaries mentioned from January 1 to 31 in 2010 and from January 1 to 31 in 2024 were preprocessed with the new reverse N-Gram method. This resulted in the stable construction of a dictionary for natural language processing in the healthcare field.

• The Journal of the Convergence on Culture Technology
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• v.10 no.4
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• pp.201-207
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• 2024

In this study, we investigated the current status of written discourse mediation in a more general and in-depth manner, including the training completion experience and knowledge of written discourse mediation among Speech-Language Pathologists in Korea, and the Speech-Language Pathologists' perceptions of written discourse mediation. We wanted to look into the requirements. Research results were derived through a questionnaire answered by 110 Speech-Language Pathologists. As a result, although most Speech-Language Pathologists learned about written discourse intervention in the curriculum, their application of written discourse intervention in clinical settings is insufficient and they have difficulty with written discourse intervention due to lack of systematic and professional knowledge of this intervention. I could tell that I was feeling it. Looking at the status of written discourse intervention, only 46.4% of the Speech-Language Pathologists who responded in clinical settings showed that they had experience with written discourse intervention. In other words, it was analyzed that 53.6% of respondents had no experience with writing discourse mediation. As a result of Speech-Language Pathologists' perception and demand for written discourse intervention, 76.4% of SpeechLanguage Pathologists responded that they thought written discourse intervention was an important area of speech therapy. In addition, 62.8% of respondents responded that a curriculum for discourse mediation is necessary, more than 90% said that continuous research on written discourse mediation is necessary, and 89.1% thought that the development of textbooks and teaching aids was necessary.This study is significant in that it investigated the experiences and perceptions of Speech-Language Pathologists in written discourse intervention and analyzed the results in that it provided direction on how education and various processes related to written discourse intervention should be conducted.

• 한국어정보학회:학술대회논문집
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• 2017.10a
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• pp.194-196
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• 2017

기존의 단어 기반 접근법을 이용한 개체 연결은 단어의 변형, 신조어 등이 빈번하게 나타나는 비정형 문장에 대해서는 좋은 성능을 기대하기 어렵다. 본 논문에서는 문서 임베딩과 선형 변환을 이용하여 단어 기반 접근법의 단점을 해소하는 개체 연결을 제안한다. 문서 임베딩은 하나의 문서 전체를 벡터 공간에 표현하여 문서 간 의미적 유사도를 계산할 수 있다. 본 논문에서는 또한 비교적 정형 문장인 위키백과 문장과 비정형 문장인 소셜 미디어 문장 사이에 선형 변환을 수행하여 두 문형 사이의 표현 격차를 해소하였다. 제안하는 개체 연결 방법은 대표적인 소셜 미디어인 트위터 환경 문장에서 단어 기반 접근법과 비교하여 높은 성능 향상을 보였다.

• Proceedings of the Korean Information Science Society Conference
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• 2005.11b
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• pp.703-705
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• 2005

지능형 에이전트란 환경상태를 인지하고 상태정보에 따른 적절한 행위를 자동적으로 수행하는 소프트웨어 객체를 말한다. 본 논문에서는 시맨틱 웹 등장에 따른 시맨틱 서비스를 지능적이고 자동적으로 수행하는 에이전트의 개발에 대해 제안한다. 본 논문에서는 제안하는 시맨틱 서비스 에이전트는 다음과 같은 핵심 요소 기술의 특징을 갖는다. 첫째, 시맨틱 웹 환경의 온톨로지와 메타데이터 및 사용자 프로파일을 자원으로 사용하여 상태정보를 인지하고 행동한다. 둘째, SWRL(Semantic Web Rule Language)기반의 추론엔진을 바탕으로 추론을 통한 지능적인 행동을 수행한다. 셋째, 시맨틱 웹 환경의 확장을 통한 에이전트의 활동 범위를 증가시키기 위해서 메타데이터의 저작기능을 갖는다. 넷째, 시맨틱 서비스 에이전트는 온톨로지 서버 및 시맨틱 미들웨어를 통한 시맨틱 웹 인프라 시스템의 프레임워크를 갖는다. 본 논문에서는 시맨틱 서비스 에이전트의 실제 구현을 통해서 시맨틱 웹 환경이 제공하는 자원을 적극 이용하고 이를 사용자에게 지능적이고 자동적인 서비스로 제공하는 에이전트를 제안한다.