• Proceedings of the Korea Information Processing Society Conference
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• 2024.05a
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• pp.873-874
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• 2024

본 논문은 GPT-3.5 모델을 활용하여 우울증 환자의 일기에 대한 정서적 공감과 위로의 질을 향상 하는 프롬프트 엔지니어링 기법을 제안하고 실험적으로 검증한다. 제안 방법은 GPT-3.5모델에게 감정에 섬세하게 반응하고 적절한 위로의 답변을 생성하는 3가지 접근 방식을 사용한다. 위로 방법 구체적 제시, 페르소나 부여 및 감정 호소 명령서 제시를 통해 감정 일기 응답을 개선한다. 실험 결과, 조언 중심의 기존 답변 대신 감정을 중심으로 공감하는 응답이 생성됨을 확인할 수 있었다. 이는 우울증 환자에 대한 인문학적 접근과 제안 프롬프트 엔지니어링 기법을 통합하여, 인공지능 모델의 정서적 공감 능력을 향상할 수 있다는 것을 실험적으로 검증하였다.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.3
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• pp.53-68
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• 2024

Generative AI is receiving a lot of attention around the world, and ways to effectively utilize it in the business environment are being explored. In particular, since the public release of the ChatGPT service, which applies the GPT-3.5 model, a large language model developed by OpenAI, it has attracted more attention and has had a significant impact on the entire industry. This study focuses on the emergence of Generative AI, especially ChatGPT, which applies OpenAI's GPT-3.5 model, to investigate its impact on the startup industry and compare the changes that occurred before and after its emergence. This study aims to shed light on the actual application and impact of generative AI in the business environment by examining in detail how generative AI is being used in the startup industry and analyzing the impact of ChatGPT's emergence on the industry. To this end, we collected company information of generative AI-related startups that appeared before and after the ChatGPT announcement and analyzed changes in industry, business content, and investment information. Through keyword analysis, topic modeling, and network analysis, we identified trends in the startup industry and how the introduction of generative AI has revolutionized the startup industry. As a result of the study, we found that the number of startups related to Generative AI has increased since the emergence of ChatGPT, and in particular, the total and average amount of funding for Generative AI-related startups has increased significantly. We also found that various industries are attempting to apply Generative AI technology, and the development of services and products such as enterprise applications and SaaS using Generative AI has been actively promoted, influencing the emergence of new business models. The findings of this study confirm the impact of Generative AI on the startup industry and contribute to our understanding of how the emergence of this innovative new technology can change the business ecosystem.

• Fisheries and Aquatic Sciences
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• v.5 no.4
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• pp.308-310
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• 2002

Effect of 4-nonylphenol (4-NP), endocrine disrupting compounds (EDCs), on glutamate oxaloacetate transaminase (GOT) and glutamate pyruvate transaminase (GPT) were investigated in the plasma of juvenile rockfish, Sebastes schlegeli. Fish were injected with 4­NP (10, 50, 100 and 200 mg/kg body weight) in $70\%$ ethanol twice at 3-day intervals and plasma sampling were extracted at 7 days after the last injection. Controls received solvent only. 4-NP significant increased GOT in a dose-dependent manner. GPT was markedly elevated to $61\%$ (P<0.05) and $82\%$ (P<0.01) than that of the control at the 4-NP doses of 100 and 200mg, respectively. These results suggest that the estrogenic activity of 4-NP increase plasma GOT and GPT by toxic effect on hepatocyte.

• 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.

• International Journal of Advanced Culture Technology
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• v.11 no.4
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• pp.378-384
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• 2023

In this study, we explore social awareness, interest, and acceptance of generative AI, including chatGPT, which has revolutionized web search, 30 years after web search was released. For this purpose, we performed a machine learning-based topic modeling analysis based on Korean news big data collected from November 30, 2022, when chatGPT was released, to August 31, 2023. As a result of our research, we have identified seven topics related to chatGPT and generative AI; (1)growth of the high-performance hardware market, (2)service contents using generative AI, (3)technology development competition, (4)human resource development, (5)instructions for use, (6)revitalizing the domestic ecosystem, (7)expectations and concerns. We also explored monthly frequency changes in topics to explore social interest related to chatGPT and Generative AI. Based on our exploration results, we discussed the high social interest and issues regarding generative AI. We expect that the results of this study can be used as a precursor to research that analyzes and predicts the diffusion of innovation in generative AI.

• Korean Journal of Soil Science and Fertilizer
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• v.3 no.1
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• pp.43-48
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• 1970

In order to investigate the inter-relation with the growth of the barley root and GOT and GPT activities the growth of root and GOT, GPT activities were measured those which have been supplied various nitrogen compounds ($NO_3-N$, $NH_4-N$, Urea, and Amino acid). The results obtained are summarized as follows: 1. Growth of barley root supplied with $NH_4-N$ is generally increased in length and weight compared with that of the root fertilized by $NH_4-N$. 2. The above-mentioned root with $NH_4-N$ is not only decreased in its weight and length but also is apt to inhibited its growth, in compared with the root provided with $NO_3-N$. 3. The activities of GOT and GPT for the root fertilized by $NH_4-N$, the badly grown root is generally increased, while of the root supplied with $NO_3-N$ is decreased compared with that of the root fertilized by $NH_4-N$. 4. The activities of GOT and GPT for the root provided with amino acid known as the considerable growth inhibiting compound for rice is generally decreased, while that of the badly known-grown root is increased. 5. The activities of GOT and GPT in the supernatant fraction of the barley is for the most part, high and low in the mitocondrial fraction.

• YAKHAK HOEJI
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• v.43 no.4
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• pp.516-525
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• 1999

Hedera rhombea (HR) has been used for treatments of hemorrage, chronic catarrh, jaundice, lithisis and convulsion. This study was done to isolate active compounds that have protective effect on liver damage. BuOH and EtOAc fractions of HR recovered serum glutamic pyruvic transaminase (GPT), glutamic oxaloacetic transaminase (GOT) and ${\gamma}-glutamyltranspeptidase$ (${\gamma}-GTP$) activities in CCl4 treated rats. We isolated 7 phenolic compounds from BuOH and EtOAc fractions, which were identified as 3-caffeoyl quinic acid, 3,4-di-O-caffeoyl quinic acid, 3,5-di-O-caffeoyl quinic acid, 4,5-di-O-caffeoyl quinic acid, caffeic acid, methyl 3,4-di-O-caffeoyl quinic acid and methyl 3,5-di-O-caffeoyl quinic acid by chemical and spectral analysis. These compounds reduced significantly serum GOT and GPT elevated by CCl4 treatment in rats, and 3-caffeoyl quinic acid, 3,5-di-O-caffeoyl quinic acid and caffeic acid also showed mild inhibitory activity against human immunodeficiency virus.

• The Mathematical Education
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• v.63 no.3
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• pp.467-484
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• 2024

The rapid advancement of generative AI has ushered in an era where anyone can create and freely utilize personalized chatbots without the need for programming expertise. This study aimed to develop a customized chatbot based on OpenAI's GPTs for the purpose of pre-service teacher education and to analyze its educational performance in mathematics as assessed by educators guiding pre-service teachers. Responses to identical questions from a general-purpose chatbot (ChatGPT), a customized GPTs-based chatbot, and an elementary mathematics education expert were compared. The expert's responses received an average score of 4.52, while the customized GPTs-based chatbot received an average score of 3.73, indicating that the latter's performance did not reach the expert level. However, the customized GPTs-based chatbot's score, which was close to "adequate" on a 5-point scale, suggests its potential educational utility. On the other hand, the general-purpose chatbot, ChatGPT, received a lower average score of 2.86, with feedback indicating that its responses were not systematic and remained at a general level, making it less suitable for use in mathematics education. Despite the proven educational effectiveness of conventional customized chatbots, the time and cost associated with their development have been significant barriers. However, with the advent of GPTs services, anyone can now easily create chatbots tailored to both educators and learners, with responses that achieve a certain level of mathematics educational validity, thereby offering effective utilization across various aspects of mathematics education.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.4
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• pp.275-287
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• 2024

Research on the integration of Knowledge Graphs (KGs) and Language Models (LMs) has been consistently explored over the years. However, studies focusing on the automatic generation of text using the structured knowledge from KGs have not been as widely developed. In this study, we propose a methodology for automatically generating specific domain-related research items (Related Work) at a level comparable to existing papers. This methodology involves: 1) selecting optimal prompts, 2) extracting triples through a four-step refinement process, 3) constructing a knowledge graph, and 4) automatically generating related research. The proposed approach utilizes GPT-4, one of the large language models (LLMs), and is desigend to automatically generate related research by applying the four-step refinement process. The model demonstrated performance metrics of 17.3, 14.1, and 4.2 in Triple extraction across #Supp, #Cont, and Fluency, respectively. According to the GPT-4 automatic evaluation criteria, the model's performamce improved from 88.5 points vefore refinement to 96.5 points agter refinement out of 100, indicating a significant capability to automatically generate related research at a level similar to that of existing papers.

• Journal of the East Asian Society of Dietary Life
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• v.7 no.2
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• pp.181-198
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• 1997

The purpose of this study was to investigated relationship between heath status and food preference of male and fermale adults who live in Iksan City, Cheonbuk, Korea. The subjects consisted of 96 male and 93 fermale adults were aged 20 to 70 years old. Each subject was interviewed to get information of food preference. Blood samples were taken concentration of serum in hemoglobin, glucose, total cholesterol, GOT(glutamic oxaloacetic transaminase), GPT(glutamic pyruvic transaminase) were measured. The results obtained were as follows: Among the food preference were like, dislike and ordinary answered to male and fermale adults the normal average of serum concentration with hemoglobin level showed 15.4, 14.2, 15.5, 12.9, 15.8 and 13.2g/dl, glucose level showed 85.8, 86.1, 87.5, 88.1, 87.9 and 86.1mg/dl, total cholesterol level showed 183.1, 185.0, 172.4, 193.5, 181.2 and 184.0mg/dl, GOT level showed 4.8, 23.4, 24.8, 23.9, 24.9 and 21.7ppm, GPT level showed 22.7, 20.2, 26.3, 18.5, 22.5 and 18.4ppm respectively. The abnormal average of serum concentration with hemoglobin level showed 11.1, 10.8, 12.2, 11.3, 12.5 and 11.0g/dl, abnormal glucose level showed 155.7 168.5, 166.2, 134.1, 124.1, 130.1, abnormal total cholesterol level showed 260.3, 273.7, 255.2, 286.5, 255.9 and 251.8mg/dl, abnormal GOT level showed 58.8, 66.8, 51.8, 50.3, 51.2 and 51.0ppm abnormal GPT level showed 54.3, 48.6, 51.3, 50.2, 53.2 and 45.5ppm respectively.