• Proceedings of the Korea Information Processing Society Conference
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• 2024.05a
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• pp.646-647
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• 2024

사이버 범죄가 증가함에 따라 익명성을 보장하는 암시장인 다크웹 내 불법적인 활동에 대한 모니터링의 중요성이 커졌다. 최근 다양한 분야에서 ChatGPT 의 쓰임이 주목받고 있듯이 다크웹에서도 전용 GPT 가 등장하였으며, 다크웹 생태계를 분석하고 정보를 수집하는데 이러한 다크웹 전용 생성형 인공지능 모델을 활용할 수 있다. 본 연구에서는 다크웹 GPT 에서 불법 행위와 관련된 질의를 통해 정보를 수집하고 해당 정보가 표면웹과 다크웹 상에서 다르게 쓰이고 있음을 확인함으로써 수사를 위한 다크웹 전용 GPT 활용 가능성 및 프롬프트 엔지니어링의 필요성을 탐구한다.

• The Journal of Bigdata
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• v.9 no.1
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• pp.17-30
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• 2024

This study categorizes the factors that affect the intention to continue using ChatGPT into positive motivational factors (personalization, social influence) and negative motivational factors (privacy concern, perceived risk) and investigates whether they affect the intention to continue using ChatGPT through information trust, performance expectancy, and effort expectancy. To this end, a survey was conducted among 265 adults in their 20s and above who have used ChatGPT service. The results showed that personalization and social influence had a defining effect on information trust, performance expectancy, and effort expectancy. For privacy concern, we found a negative effect of wealth on performance expectations, but not on effort expectations. Perceived risk had a negative effect on performance expectancy and effort expectancy. In addition, information trust, performance expectancy, and effort expectancy have a defining effect on continuance intention. This study extends the scope of existing research that focuses on positive factors, deepens our the understanding of ChatGPT. It also provides useful suggestions for continued use of ChatGPT.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.4
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• pp.503-508
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• 2012

Among the high distribution voltage consumers, high-capacity consumers are often applying the grounding resistance method in order to overcome demerits such as erroneous operation of the ground reply or potential increase in the battery at the accident of the isolated neutral system. In this paper, to prevent damage to CLR and GPT in the delay to block the breakdown in the resistance grounded neutral system, this study aims to provide a proper suggestion for continuous rating capacity of GPT to check the appropriateness of CLR size and reduce GPT burden. Thereupon, this study comparatively analyzes CLR current applied in general GPT and the current gained when CLR demanded in the system is used and analyzes the simulated system through simulation using PSCAD/EMTDC in order to suggest GPT's proper continuous rating capacity.

• Asia pacific journal of information systems
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• v.33 no.4
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• pp.957-976
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• 2023

ChatGPT has had a significant impact on society, business, and academia by influencing individuals and organizations through knowledge generation and supporting users in locating conversational inquiries and answers. It can transform how people seek answers by combining human-like conversational skills with AI. By eradicating the cumbersome process of selecting from multiple options, users can conduct preliminary research or create optimized solutions. The purpose of this research is to investigate how consumers use ChatGPT and digital transformation, specifically in terms of knowledge development, searching and recommending, and optimizing accessible possibilities. Using many linked theories, we address the potential implications and insights that can be gained from ChatGPT's early stages and its integration with other applications such as robotics, service automation, and the metaverse. Finally, the application of ChatGPT has practical, theoretical, and phenomenological impacts, in addition to improving users' experiences.

• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.259-260
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• 2024

졸음운전으로 인한 교통사고는 매년 꾸준하게 일어나 이에 대한 다방면의 해결책이 요구되고 있다. 본 논문에서는 위 문제를 개선하고자 ChatGPT와 영상처리를 이용한 졸음 감지 시스템을 구현하였다. 이 시스템은 운전자의 얼굴 부분을 영상처리로 인식하여 눈동자의 종횡비를 구해 PERCLOS 공식에 따른 운전자의 졸음을 판별시키고, 경고와 동시에 ChatGPT가 운전자에게 특정 주제를 키워드로 TTS와 STT를 통해 대화한다. 운전자의 졸음을 판별하기 위해 임베디드 보드에서 연결된 캠을 통해 졸음 판별을 하고, ChatGPT도 마찬가지로 보드에서 연결한 스피커, 마이크를 통해 운전자와 대화한다. 이를 활용하여 운전자의 졸음 자각을 통한 안전운전 및 사고 발생률의 감소를 기대할 수 있다.

• Korean Journal of Community Nutrition
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• v.3 no.4
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• pp.574-582
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• 1998

This study was carried out to discover the effects of eating habits and health-related life style on blood pressure, $\gamma$-Glutamic acid Peptide Transferase($\gamma$-GPT), blood glucose and High Density Lipoprotein-Cholesterol(HDL-C). 185 subjects(85 male, 100 female) were selected, who were living in the Cheonju area aged 40#s to 60#s. The mean systollic blood pressure(SBP), diastollic blood pressure (DBP), $\gamma$-GPT, fasting blood sugar(FBS) and HDL-C for all the subjects were 118mmHg, 77mmHg, 281U/l, 90mg/dl and 45mg/dl, respectively. The SBP and DBP for subuects over 60 years old were 126mmHg and 81mmHg and were significantly higher than subjects in their 40#s and 50#s(p<0.001, p<0.005). The HDL-C of the group that rarely ate breakfast was 57mg/dl and that was significantly higher than the 44mg/dl scored by those who ate breakfast everyday(p<0.05). The SBP for subjects having a snack 2-3 times/week was 125mmHg and that was significantly higher than the 114mmHg of those having a snack everyday(p<0.05). The $\gamma$-GPT for subjects consuming alcohol everyday was 44IU/L and that was significantly higher than 18IU/I of the non-drinking group(p<0.001). The $\gamma$-GPT of light smokers was 53IU/I and that was significantly higher than the 22IU/I for non-smoking participants(p<0.001). The DBP, SBP, $\gamma$-GPT, FBS and HDL-C related to exercise not significantly different. The SBP(p<0.001) and DBP(p-0.01) between age group was positively correlated. The $\gamma$-GPT between drinking frequency(p<0.001), drinking quantity(p<0.05), and smoking(p<0.05) was also positively correlated. The FBS between exercises had a negative correlation(p<0.05), and the HDL-C between breakfast had a negative correlation(p<0.05). These results indicate that decreasing drinking and smoking, when combined with appropriate exercise, will decrease the $\gamma$-GPT and fasting blood sugar level, and help preventing adult diseases.

• 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.

• 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.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.2
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• pp.135-145
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• 2023

ChatGPT is an artificial intelligence-based conversation agent developed by OpenAI using natural language processing technology. In this study, an empirical study was conducted on incumbent teachers on the intention to use the newly emerged Chat GPT. First, we studied how accuracy, entertainment, system accessibility, perceived usefulness, and perceived ease of use affect ChatGPT's acceptance intention. In addition, we analyzed whether perceived usefulness and perceived ease of use differ in the intention to accept depending on the digital technology of teachers. As a result of the study, the suitability of the structural equation model was generally good. Accuracy and entertainment were found to have a significant effect on perceived usefulness, and system accessibility was found to have a significant effect on perceived ease of use. In the analysis of teachers' digital technology control effects, it was found that perceived usefulness and perceived ease of use had a control effect between acceptance intentions. It was found that the group with high digital skills of teachers was strongly intended to accept the service regardless of perceived usefulness and ease of use. In the group with low digital skills of teachers, it is thought that ChatGPT's service shows the acceptance intention only when the perceived usefulness and ease of use are high. Therefore, in the group with low digital technology, it is necessary to seek teaching activities such as the development of instructional models using ChatGPT.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.309-328
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• 2022

This study empirically analyzed a Korean pre-trained language models (PLMs) designed for natural language generation. The performance of two PLMs - BART and GPT - at the task of abstractive text summarization was compared. To investigate how performance depends on the characteristics of the inference data, ten different document types, containing six types of informational content and creation content, were considered. It was found that BART (which can both generate and understand natural language) performed better than GPT (which can only generate). Upon more detailed examination of the effect of inference data characteristics, the performance of GPT was found to be proportional to the length of the input text. However, even for the longest documents (with optimal GPT performance), BART still out-performed GPT, suggesting that the greatest influence on downstream performance is not the size of the training data or PLMs parameters but the structural suitability of the PLMs for the applied downstream task. The performance of different PLMs was also compared through analyzing parts of speech (POS) shares. BART's performance was inversely related to the proportion of prefixes, adjectives, adverbs and verbs but positively related to that of nouns. This result emphasizes the importance of taking the inference data's characteristics into account when fine-tuning a PLMs for its intended downstream task.