• Journal of Sericultural and Entomological Science
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• v.29 no.2
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• pp.38-43
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• 1987

The just molted larvae of the fifth instar were fed on with cadmium trated mulberry leaf and on the third day of the fifth instar the daily change of the total protein, activities of GOT and GPT in larvae haemoymph were sexually analyzed. The result obtained are summarized as follows : 1. The total haemolymph was decreased by cadmium treatment. A decreasing ratio of the total haemolymph protein was higher at the later development stage of the male fifth instar than the female fifth instar. 2. There seemed a slight difference in albumin content of the female blood along with the fifth larvae development between control and cadmium treatment where 7% decrease of blood albumin took place with cadmium treatment comparing to that of cotrol. Contrarily a decrease of blood globulin was made on both sexes. 3. The activities of GOT and GPT were inhibited by cadmium treatment.

• The Journal of Internal Korean Medicine
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• v.30 no.4
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• pp.685-695
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• 2009

Objectives : In this study, the author tried to investigate whether Geonpye-tang(GPT) significantly affects PMA-, EGF- or TNF-alpha-induced MUC5AC mucin production and gene expression from human airway epithelial cells. Materials and Methods : Effects of the agent on PMA-, EGF- or TNF-alpha-induced MUC5AC mucin production and gene expression from human airway epithelial cells (NCI-H292) were investigated. Confluent NCI-H292 cells were pretreated for 30 min in the presence of GPT and treated with PMA (10ng/ml) or EGF (25ng/ml) or TNF-alpha (0.2nM), to assess both effect of the agent on PMA- or EGF- or TNF-alpha-induced MUC5AC mucin production by enzyme-linked immunosorbent assay (ELISA) and gene expression by reverse transcription-polymerase chain reaction (RT-PCR). Possible cytotoxicity of the agent was assessed by examining the rate of survival and proliferation of NCI-H292 cells after treatment with the agent over 72 hrs (SRB assay). Results : (1) GPT significantly inhibited PMA-induced and EGF-induced MUC5AC mucin production from NCI-H292 cells. However, GPT did not affect TNF-alpha-induced MUC5AC mucin production. (2) GPT significantly inhibited the expression levels of PMA-, EGF- or TNF-alpha-induced MUC5AC genes in NCI-H292 cells (3) GPT did not show significant cytotoxicity to NCI-H292 cells. Conclusion : This result suggests that GPT can affect the production and gene expression of respiratory mucin observed in diverse respiratory diseases accompanied by mucus hypersecretion. This can explain the traditional use of GPT in oriental medicine. Effects of GPT with their components should be further investigated using animal experimental models that reflect pathophysiology of airway diseases through future studies.

• Communications of Mathematical Education
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• v.37 no.3
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• pp.545-567
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• 2023

This study investigates effective ChatGPT prompts for solving mathematical problems, focusing on the chapters of quadratic equations and quadratic functions. A structured prompt was designed, following a sequence of 'Role-Rule-Example Solution-Problem-Process'. In this study, an artificial intelligence model combining GPT-4, Wolfram plugin, and Advanced Data Analysis was utilized. Wolfram was used as the primary tool for calculations to reduce computational errors. When using the structured prompt, the accuracy rate for problems from nine high school mathematics textbooks on quadratic equations and quadratic functions was 91%, showing higher performance compared to zero-shot prompts. This confirmed the effectiveness of the structured prompts in solving mathematical problems. The structured prompts designed in this study can contribute to the development of intelligent information systems for personalized and customized education.

• Journal of the Korea Society of Computer and Information
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• v.29 no.2
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• pp.43-50
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• 2024

This paper evaluates the Korean sentiment analysis performance of large language models like GPT-3.5 and GPT-4 using a zero-shot approach facilitated by the ChatGPT API, comparing them to pre-trained Korean models such as KoBERT. Through experiments utilizing various Korean sentiment analysis datasets in fields like movies, gaming, and shopping, the efficiency of these models is validated. The results reveal that the LMKor-ELECTRA model displayed the highest performance based on F1-score, while GPT-4 particularly achieved high accuracy and F1-scores in movie and shopping datasets. This indicates that large language models can perform effectively in Korean sentiment analysis without prior training on specific datasets, suggesting their potential in zero-shot learning. However, relatively lower performance in some datasets highlights the limitations of the zero-shot based methodology. This study explores the feasibility of using large language models for Korean sentiment analysis, providing significant implications for future research in this area.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.33 no.4
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• pp.412-418
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• 2023

As advances in artificial intelligence (AI) increasingly approach areas once relegated to the realm of science fiction, there is growing public interest in using these technologies for practical everyday tasks in both the home and the workplace. This paper explores the applications of and implications for of using ChatGPT, a conversational AI model based on GPT-3.5 and GPT-4.0, in the field of occupational health and safety. After gaining over one million users within five days of its launch, ChatGPT has shown promise in addressing issues ranging from emergency response to chemical exposure to recommending personal protective equipment. However, despite its potential usefulness, the integration of AI into scientific work and professional settings raises several concerns. These concerns include the ethical dimensions of recognizing AI as a co-author in academic publications, the limitations and biases inherent in the data used to train these models, legal responsibilities in professional contexts, and potential shifts in employment following technological advances. This paper aims to provide a comprehensive overview of these issues and to contribute to the ongoing dialogue on the responsible use of AI in occupational health and safety.

• Annual Conference on Human and Language Technology
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• 2023.10a
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• pp.228-233
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• 2023

인간의 수동 평가 시 시간과 비용의 소모, 주석자 간의 의견 불일치, 평가 결과의 품질 등 불가피한 한계가 발생한다. 본 논문에서는 맥락을 고려하고 긴 문장 입출력이 가능한 ChatGPT를 활용한 한국어 요약문 평가가 인간 평가를 대체하거나 보조하는 것이 가능한가에 대해 살펴보았다. 이를 위해 ChatGPT가 생성한 요약문에 정량적 평가와 정성적 평가를 진행하였으며 정량적 지표로 BERTScore, 정성적 지표로는 일관성, 관련성, 문법성, 유창성을 사용하였다. 평가 결과 ChatGPT4의 경우 인간 수동 평가를 보조할 수 있는 가능성이 있음을 확인하였다. ChatGPT가 영어 기반으로 학습된 모델임을 고려하여 오류 발견 성능을 검증하고자 한국어 오류 요약문으로 추가 평가를 진행하였다. 그 결과 ChatGPT3.5와 ChatGPT4의 오류 요약 평가 성능은 불안정하여 인간을 보조하기에는 아직 어려움이 있음을 확인하였다.

• Journal of the Korean Society of Clothing and Textiles
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• v.47 no.6
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• pp.1038-1056
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• 2023

This study investigates the effects of ChatGPT's quality characteristics (service and information) on purchase intention and word of mouth intention. We distributed questionnaires among domestic men and women aged in their 20s and 30s who had experience of using ChatGPT. A total of 222 responses were subjected to frequency analysis, factor analysis, correlation analysis, and multiple linear regression analysis using the IBM SPSS statistical program version 26. The major findings were as follows: (1) The factors of service quality were categorized as Tangibility, Reliability, Empathy, and Assurance, while the factors of information quality were categorized as Recency, Accuracy, and Usefulness. (2) Among the service quality factors of ChatGPT, two factors (Reliability and Empathy) significantly impacted purchase intention, and three factors (Tangibility, Reliability, and Empathy) significantly affected word of mouth intention. (3) Among ChatGPT's information quality factors, two factors (Usefulness and Recency) had a significant effect on purchase intention, and two factors (Usefulness and Accuracy) exerted a significant influence on word of mouth intention. (4) Purchase intention had a significant effect on word of mouth intention.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.503-504
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• 2022

최근 자연어 처리 분야에서 언어 모델을 활용하여 문장 생성에 관한 연구가 이루어지고 있다. 기존 언어 모델을 활용하여 생성된 시나리오는 텍스트를 학습하여 활용하는 것 외에는 작가의 의도를 반영하는 것에 한계가 존재했고 문맥에 일관성 없는 모습을 보여주었다. 시나리오를 작성하는 것은 작가가 흐름을 주도하며 작업해야 하는 내용이다. 본 논문에서는 GPT-3 기반 언어 모델을 기반으로 다양한 시나리오 문장을 생성하여 작가가 선택하거나 원하는 문장을 직접 입력하는 등 작가의 의도에 부합하는 시나리오를 생성하는 보조 시스템을 제안한다. 본 연구를 통해 시나리오 생성을 포함한 문장 생성 분야의 보조 도구로 활용하여 작가의 의도를 반영하는 결과물을 생성하는 것을 목표로 한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.367-368
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• 2023

최근 챗봇 시스템은 급격한 발전과 함께 사용자와 자연스러운 대화를 할 수 있는 인공지능 기술의 필요성이 대두되고 있다. 기존의 챗봇 시스템은 대화 상황을 충분히 이해하지 못하거나, 학습된 데이터를 벗어나는 문장에 대한 일관성 있는 응답을 제공하지 못하는 한계가 있다. 본 논문에서는 GPT-3와 KoBERT를 활용하여 사용자의 감정 상태를 파악하고 해당 감정을 고려한 일관성 있는 대화를 제공하는 감정 분석 기반 챗봇 시스템을 제안한다. 이를 바탕으로 긍정적인 대화를 이어 나가는데 초점을 두어 자연스러운 대화가 가능할 것으로 기대된다.

• Journal of the Korea Society of Computer and Information
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• v.29 no.3
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• pp.21-41
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• 2024

This study explores the relationship between users' attachment styles and their interactions with ChatGPT (Chat Generative Pre-trained Transformer), an advanced language model developed by OpenAI. As artificial intelligence (AI) becomes increasingly integrated into everyday life, it is essential to understand how individuals with different attachment styles engage with AI chatbots in order to build a better user experience that meets specific user needs and interacts with users in the most ideal way. Grounded in attachment theory from psychology, we are exploring the influence of attachment style on users' interaction with ChatGPT, bridging a significant gap in understanding human-AI interaction. Contrary to expectations, attachment styles did not have a significant impact on ChatGPT usage or reasons for engagement. Regardless of their attachment styles, hesitated to fully trust ChatGPT with critical information, emphasizing the need to address trust issues in AI systems. Additionally, this study uncovers complex patterns of attachment styles, demonstrating their influence on interaction patterns between users and ChatGPT. By focusing on the distinctive dynamics between users and ChatGPT, our aim is to uncover how attachment styles influence these interactions, guiding the development of AI chatbots for personalized user experiences. The introduction of the Perceived Partner Responsiveness Scale serves as a valuable tool to evaluate users' perceptions of ChatGPT's role, shedding light on the anthropomorphism of AI. This study contributes to the wider discussion on human-AI relationships, emphasizing the significance of incorporating emotional intelligence into AI systems for a user-centered future.