• Journal of Digital Policy
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• v.2 no.4
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• pp.1-10
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• 2023

This study conducted preliminary study to identify effective ways to use ChatGPT in traffic policing by analyzing ChatGPT's responses to the driver's license test and the road traffic accident appraiser test. I collected ChatGPT responses for the driver's license test item pool and the road traffic accident appraiser test using the OpenAI API with Python code for 30 iterative experiments, and analyzed the percentage of correct answers by test, year, section, and consistency. First, the average correct answer rate for the driver's license test and the for road traffic accident appraisers test was 44.60% and 35.45%, respectively, which was lower than the pass criteria, and the correct answer rate after 2022 was lower than the average correct answer rate. Second, the percentage of correct answers by section ranged from 29.69% to 56.80%, showing a significant difference. Third, it consistently produced the same response more than 95% of the time when the answer was correct. To effectively utilize ChatGPT, it is necessary to have user expertise, evaluation data and analysis methods, design a quality traffic law corpus and periodic learning.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.79-90
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• 2024

This study focused on user trust in ChatGPT, a generative AI technology, and explored the factors that affect usage status and intention to continue using, and whether the influence of trust varies depending on the purpose. For this purpose, the survey was conducted targeting people in their 20s and 30s who use ChatGPT the most. The statistical analysis deploying IBM SPSS 27 and SmartPLS 4.0. A structural equation model was formulated on the foundation of Bhattacherjee's Expectation-Confirmation Model (ECM), employing path analysis and Multi-Group Analysis (MGA) for hypothesis validation. The main findings are as follows: Firstly, ChatGPT is mainly used for specific needs or objectives rather than as a daily tool. The majority of users are cognizant of its hallucination effects; however, this did not hinder its use. Secondly, the hypothesis testing indicated that independent variables such as expectation- confirmation, perceived usefulness, and user satisfaction all exert a positive influence on the dependent variable, the intention for continuance intention. Thirdly, the influence of trust varied depending on the user's purpose in utilizing ChatGPT. trust was significant when ChatGPT is used for information retrieval but not for creative purposes. This study will be used to solve reliability problems in the process of introducing generative AI in society and companies in the future and to establish policies and derive improvement measures for successful employment.

• Korean Journal of Radiology
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• v.25 no.4
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• pp.403-406
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• 2024

• 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.

• The Mathematical Education
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• v.63 no.3
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• pp.549-571
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• 2024

As digital·AI-based teaching and learning is emphasized, discussions on the educational use of generative AI are becoming more active. This study analyzed the mathematical performance of ChatGPT 4, Claude 3 Opus, and Gemini Advanced on solving examples and problems from five first-year high school math textbooks. As a result of examining the overall correct answer rate and characteristics of each skill for a total of 1,317 questions, ChatGPT 4 had the highest overall correct answer rate of 0.85, followed by Claude 3 Opus at 0.67, and Gemini Advanced at 0.42. By skills, all three models showed high correct answer rates in 'Find functions' and 'Prove', while relatively low correct answer rates in 'Explain' and 'Draw graphs'. In particular, in 'Count', ChatGPT 4 and Claude 3 Opus had a correct answer rate of 1.00, while Gemini Advanced was low at 0.56. Additionally, all models had difficulty in explaining using Venn diagrams and creating images. Based on the research results, teachers should identify the strengths and limitations of each AI model and use them appropriately in class. This study is significant in that it suggested the possibility of use in actual classes by analyzing the mathematical performance of generative AI. It also provided important implications for redefining the role of teachers in mathematics education in the era of artificial intelligence. Further research is needed to develop a cooperative educational model between generative AI and teachers and to study individualized learning plans using AI.

• Korean Journal of Pharmacognosy
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• v.25 no.4 s.99
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• pp.388-394
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• 1994

80% Methanol extracts of 44 traditional drugs used for the treatment of liver diseases or tonic effects were screened for anti-hepatotoxic activity by in vitro assay using $CCl_4-induced$ cytotoxicity in primary cultured rat hepatocytes. $CCl_4-induced$ cytotoxicity was evaluated by determination of LDH, GOT or GPT activity in the medium. Rehmaniae Radix Preparata and Gelantina nigra inhibited the release of LDH, GOT or GPT from $CCl_4-treated$ hepatocytes. Gibotii Rhizoma and Eucommiae Cortex showed inhibitory effect on release of LDH from normal hepatocytes as well as $CCl_4-treated$ hepatocytes. Eucommiae Cortex and Lili Bulbus decreased release of GOT and LDH from normal hepatocytes, respectively. Astragali Radix inhibited release of GPT in $CCl_4-treated$ hepatocytes. Phlomidis Radix, Imperatae Rhizoma, Cistanchis Herba, Broussonetiae Fructus, Asparagi Tuber, Trigonellae Semen and Polgonati Rhizoma inhibited release of LDH from $CCl_4-treated$ hepatocytes. Among 44 traditional drugs, most of them released LDH, GOT or GPT at the dose of 1 mg/ml in normal hepatocytes, and Drynariae Rhizoma, Acanthopanacis Cortex, Longanae Arillus, Atratylodis Rhizoma and Ecliptae Herba increased $CCl_4-induced$ cytotoxicity.

• 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.

• 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.

• YAKHAK HOEJI
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• v.40 no.1
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• pp.52-58
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• 1996

Solvent fractions were prepared from traditional herbal drugs which of methanol extracts inhibited $CCl_4$-induced cytotoxicity in primary cultured rat hepatocytes and c ontinuously assayed their effects. Ethylacetate and n-buthanol fractions from Cibotii Rhizoma and chloroform fraction from Gelatina Nigra inhibited the release of LDH and GPT from $CCl_4$-treated hepatocytes, respectively. Water fraction (WAR) among solvent fractions from Astragali Radix showed the most potent inhibitory effect on the release of GOT or GPT by treatment with $CCl_4$. All of solvent fractions prepared from Eucommiae Cortex had no effect on $CCl_4$-induced cytotoxicity. Chloroform and ethylacetate fractions from Rehmanniae Radix Preparata increased the release of GPT from $CCl_4$-treated hepatocytes. n-Hexan, chloroform or ethylacetate fraction from 5 herbal drugs increased the release of LDH, GOT or GPT from normal hepatocytes at the dose of 1.Omg/ml. Administration of WAR suppressed the elevation of GOT, ALP activities and MDA contents in the serum as well as in the liver tissue of $CCl_4$-intoxicated rats. Based on these results, isolation of antihepatotoxic substances from WAR is under the process.

• Journal of Information Technology Applications and Management
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• v.31 no.4
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• pp.121-137
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• 2024

This research studies NPCs applied by Generative Pre-trained Transformer (GPT) Technology. This study set three independent variables as characteristics of the NPCs applied GPT. User immersion is set as a mediator variable, while user game satisfaction and loyalty are chosen as dependent variables. The Stimulus-Organism-Response (SOR) theory is employed to study user attitude changes, and immersion is examined through the Flow Theory. The study found that interactions between NPCs and users directly and indirectly influence user satisfaction and loyalty. This suggests that NPCs capable of providing users with desired information, rather than merely following predetermined protocols, can enhance the user's affinity for the game. Furthermore, the intelligence and human-likeness of NPCs were found to indirectly influence satisfaction and loyalty through immersion. These findings underscore the importance of GPT-applied NPCs in the gaming industry, with potential implications for the future development and enhancement of such NPCs within games.