• 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.

• 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.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.967-971
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• 2023

Recently, a variety of AI-based platform services are available, and one of them is ChatGPT that processes a large quantity of data in the natural language and generates an answer after self-learning. ChatGPT can perform various tasks including software programming in the IT sector. Particularly, it may help generate a simple program and correct errors using C Language, which is a major programming language. Accordingly, it is expected that ChatGPT is capable of effectively using Verilog HDL, which is a hardware language created in C Language. Verilog HDL synthesis, however, is to generate imperative sentences in a logical circuit form and thus it needs to be verified whether the products are executed properly. In this paper, we aim to select small-scale logical circuits for ease of experimentation and to verify the results of circuits generated by ChatGPT and human-designed circuits. As to experimental environments, Xilinx ISE 14.7 was used for module modeling, and the xc3s1000 FPGA chip was used for module embodiment. Comparative analysis was performed on the use area and processing time of FPGA to compare the performance of ChatGPT products and Verilog HDL products.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.3
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• pp.160-165
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• 2023

In this study, we propose an SNS sentence writing assistance system that utilizes YOLO and GPT to assist users in writing texts with images, such as SNS. We utilize the YOLO model to extract objects from images inserted during writing, and also extract meta-information such as GPS information and creation time information, and use them as prompt values for GPT. To use the YOLO model, we trained it on form image data, and the mAP score of the model is about 0.25 on average. GPT was trained on 1,000 blog text data with the topic of 'restaurant reviews', and the model trained in this study was used to generate sentences with two types of keywords extracted from the images. A survey was conducted to evaluate the practicality of the generated sentences, and a closed-ended survey was conducted to clearly analyze the survey results. There were three evaluation items for the questionnaire by providing the inserted image and keyword sentences. The results showed that the keywords in the images generated meaningful sentences. Through this study, we found that the accuracy of image-based sentence generation depends on the relationship between image keywords and GPT learning contents.

• 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.