• Journal of the Korea Society for Simulation
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• v.8 no.1
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• pp.113-138
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• 1999

Driven by the explosive expansion and acceptance of the Internet and its multimedia front-end, the Web, a new generation of the modeling and simulation tools have come up with the name of Web-Based Simulation (WBS). Most of WBS libraries inherit its powerful advantages from Java. However, there are cases where explicit specification of models or interface objects is more desirable than the black-box programs. This paper presents an XML-based DEVS (Discrete Event System Specification) markup language for sharing simulation models on the Web. DEVS provides a system-theoretic formalism for the language while XML supports platform-independent data access. This paper focuses on the design of such a language.

• English Language & Literature Teaching
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• v.15 no.2
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• pp.71-92
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• 2009

Europass was established in 2005 by the European Parliament and the Council of Europe as a single framework for language qualifications and competences, helping citizens to gain accreditation throughout the European Community. In addition, the 1996 Common European Framework of Reference for Languages: Learning, Teaching, Assessment (CEFR) provides a common basis for language syllabi, curriculum guidelines, examination, and textbooks in Europe. This framework describes the required knowledge and skills, the cultural context, and the levels of proficiency that learners should achieve. In combination, Europass and the CEFR provide employers and educational institutes with internationally recognized standards. This paper proposes that current trends such as globalization and international mobility require a similar approach to accreditation in Asia. As jobs and workers become independent of national boundaries and restrictions, it becomes necessary to educate students as multilingual world citizens, using standards that are accepted around the world. It is suggested, therefore, that assessment models such as Europass and the CEFR, along with successful language teaching models in Europe and Canada, present opportunities of adaptation for the Korean education system. Finally, rigorous teacher training to internationally recognized levels is recommended, if Korea is to produce a workforce of highly-skilled, plurilingual world citizens.

• Annual Conference on Human and Language Technology
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• 2023.10a
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• pp.196-202
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• 2023

Large Language Models (LLM)의 출현은 자연어 처리 분야의 연구 패러다임을 전환시켰다. LLM의 핵심적인 성능향상은 지시어 튜닝(instruction-tuning) 기법의 결과로 알려져 있다. 그러나, 현재 대부분의 연구가 영어 중심으로 진행되고 있어, 다양한 언어에 대한 접근이 필요하다. 본 연구는 한국어 지시어(instruction-following) 모델의 개발 및 최적화 방법을 제시한다. 본 연구에서는 한국어 지시어 데이터셋을 활용하여 LLM 모델을 튜닝하며, 다양한 데이터셋 조합의 효과에 대한 성능 분석을 수행한다. 최종 결과로 개발된 한국어 지시어 모델을 오픈소스로 제공하여 한국어 LLM 연구의 발전에 기여하고자 한다.

• 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.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.4
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• pp.193-202
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• 2023

In recent years, the outstanding performance of large language models (LLMs) trained on extensive datasets has become a hot topic. Since studies on LLMs are available on open-source approaches, the ecosystem is expanding rapidly. Models that are task-specific, lightweight, and high-performing are being actively disseminated using additional training techniques using pre-trained LLMs as foundation models. On the other hand, the performance of LLMs for Korean is subpar because English comprises a significant proportion of the training dataset of existing LLMs. Therefore, research is being carried out on Korean-specific LLMs that allow for further learning with Korean language data. This paper identifies trends of open source based LLMs and introduces research on Korean specific large language models; moreover, the applications and limitations of large language models are described.

• Journal of Information Processing Systems
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• v.17 no.3
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• pp.537-555
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• 2021

Many researchers have carried out studies related to programming languages since the beginning of computer science. Besides programming with traditional programming languages (i.e., procedural, object-oriented, functional programming language, etc.), a new paradigm of programming is being carried out. It is programming with natural language. By programming with natural language, we expect that it will free our expressiveness in contrast to programming languages which have strong constraints in syntax. This paper surveys the approaches that generate source code automatically from a natural language description. We also categorize the approaches by their forms of input and output. Finally, we analyze the current trend of approaches and suggest the future direction of this research domain to improve automatic code generation with natural language. From the analysis, we state that researchers should work on customizing language models in the domain of source code and explore better representations of source code such as embedding techniques and pre-trained models which have been proved to work well on natural language processing tasks.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2011.11a
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• pp.12-14
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• 2011

Crop growth simulation models have been developed as research and management tools. When these models are needed to incorporate new knowledge on phenology and physiology of crops, programming languages have been used for development and documentation of these models. However, researchers may have limited skill in programming languages. Furthermore, software developer may find it challenging to improve the crop models because documentation of the models are rarely available. The Unified Modeling Language (UML) can provide a simple approach for development and documentation of model. A template for implementation of the model can be obtained using the UML, which would facilitate code re-use and model improvement.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.5
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• pp.41-49
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• 2004

As a means of overcoming the linguistic barrier between different languages in the Internet cyberspace, a sign-language communication system has been proposed. However, the system supports avatars having the same model structure so that it is difficult to communicate between different avatar models. Therefore, in this paper, we propose a new gesture communication system in which different avatars models can communicate with each other by using a FBML (Facial Body Markup Language). Using the FBML, we define a standard document format that contains the messages to be transferred between models, where the document includes the action units of facial expression and the joint angles of gesture animation. The proposed system is implemented with Visual C++ and Open Inventor on Windows platforms. The experimental results demonstrate a possibility that the method could be used as an efficient means to overcome the linguistic problem.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.3
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• pp.51-65
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• 2024

Accurate electrical load forecasting is important to the effective operation of power systems in smart grids. With the recent development in machine learning, artificial intelligence-based models for predicting power demand are being actively researched. However, since existing models get input variables as numerical features, the accuracy of the forecasting model may decrease because they do not reflect the semantic relationship between these features. In this paper, we propose a scheme for short-term load forecasting by using features extracted through the large language models for input data. We firstly convert input variables into a sentence-like prompt format. Then, we use the large language model with frozen weights to derive the embedding vectors that represent the features of the prompt. These vectors are used to train the forecasting model. Experimental results show that the proposed scheme outperformed models based on numerical data, and by visualizing the attention weights in the large language models on the prompts, we identified the information that significantly influences predictions.

• Journal of The Korean Association of Information Education
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• v.7 no.3
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• pp.331-339
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• 2003

This study is the content about the development of ICT(Information and Communication Technology) teaching-learning model to support the korean language learning. Firstly, we proposed 3 types on developing models for ICT teaching-learning in korean language learning, we developed 4 ICT teaching-learning models based on analysing the curriculum of korean language course and studying the preceding works. Moreover we offered the strategies for applying ICT teaching-learning models with korean language learning. The developed 4 ICT teaching-learning models in this study are expected that ICT will use to design ICT teaching-learning model in another courses and teachers take advantage of the 4 models in korean lesson effectively.