• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.19-24
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• 2024

The future military combat environment is rapidly expanding the role and importance of artificial intelligence (AI) in defense, aligning with the current trends of declining military populations and evolving dynamics. Particularly, in the civilian sector, AI development has surged into new domains based on foundation models, such as OpenAI's Chat-GPT, categorized as Super-Giant AI or Hyperscale AI. The U.S. Department of Defense has organized Task Force Lima under the Chief Digital and AI Office (CDAO) to conduct research on the application of Large Language Models (LLM) and generative AI. Advanced military nations like China and Israel are also actively researching the integration of Super-Giant AI into their military capabilities. Consequently, there is a growing need for research within our military regarding the potential applications and fields of application for Super-Giant AI in weapon systems. In this paper, we compare the characteristics and pros and cons of specialized AI and Super-Giant AI (Foundation Models) and explore new application areas for Super-Giant AI in weapon systems. Anticipating future application areas and potential challenges, this research aims to provide insights into effectively integrating Super-Giant Artificial Intelligence into defense operations. It is expected to contribute to the development of military capabilities, policy formulation, and international security strategies in the era of advanced artificial intelligence.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1797-1808
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• 2021

Artificial intelligence is considered one of the core technologies leading the 4th industrial revolution. It is adopted in various fields bringing about a huge paradigm shift throughout our society. The field of biotechnology is no exception. It is undergoing innovative development by converging with other disciplines such as computers, electricity, electronics, and so on. In drug discovery and development, big data-based AI technology has a great potential of improving the efficiency and quality of drug development, rapidly advancing to overcome the limitations in the existing drug development process. AI technology is to be specialized and developed for the purpose including clinical efficacy and safety-related end points based on the multidisciplinary knowledge such as biology, chemistry, toxicology, pharmacokinetics, etc. In this paper, we review the current status of AI technology applied for drug discovery and consider its limitations and future direction.

• The Journal of Society for e-Business Studies
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• v.26 no.4
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• pp.95-118
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• 2021

As the AI speaker business has risen significantly in recent years, the potential for numerous uses of AI speakers has gotten a lot of attention. Consumers have created an environment in which they can express and share their experiences with products through various channels, resulting in a large number of reviews that leave consumers with a variety of candid opinions about their experiences, which can be said to be very useful in analyzing consumers' thoughts. Using this review data, this study aimed to examine the factors driving the continued use of AI speakers. Above all, it was determined whether the seven characteristics associated with the intention to adopt AI identified in prior studies appear in consumer reviews. Based on customer review data on Amazon.com, text mining and social network analysis were utilized to examine Amazon eco-products. CONCOR analysis was used to classify words with similar connectivity locations, and Connection centrality analysis was used to classify the factors influencing the continuous use of AI speakers, focusing on the connectivity between words derived by classifying review data into positive and negative reviews. Consumers regarded personality and closeness as the most essential characteristics impacting the continued usage of AI speakers as a result of the favorable review survey. These two parameters had a strong correlation with other variables, and connectedness, in addition to the components established from prior studies, was a significant factor. Furthermore, additional negative review research revealed that recognition failures and compatibility are important problems that deter consumers from utilizing AI speakers. This study will give specific solutions for consumers to continue to utilize Amazon eco products based on the findings of the research.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.2
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• pp.111-118
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• 2016

Artificial intelligence (AI) is making computer systems intelligent to do right thing. The AI is used today in a variety of fields, such as journalism, medical, industry as well as entertainment. The impact of AI is becoming larger day after day. In general, the AI system has to lead the optimal decision under uncertainty. But it is difficult for the AI system can derive the best conclusion. In addition, we have a trouble to represent the intelligent capacity of AI in numeric values. Statistics has the ability to quantify the uncertainty by two approaches of frequentist and Bayesian. So in this paper, we propose a methodology of the connection between statistics and AI efficiently. We compute a fixed value for estimating the population parameter using the frequentist learning. Also we find a probability distribution to estimate the parameter of conceptual population using Bayesian learning. To show how our proposed research could be applied to practical domain, we collect the patent big data related to Apple company, and we make the AI more intelligent to understand Apple's technology.

• 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.

• Journal of Industrial Convergence
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• v.20 no.5
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• pp.39-59
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• 2022

We analyze the perceptions and requirements of early childhood teachers for artificial intelligence(AI) education to develop an AI education program for 5-year-olds. As for the research methodology, we conducted a survey and an in-depth interview to extract the AI educational elements centering on the analysis stage, the first stage of the ADDIE model. The research result is that first, it is necessary to design a curriculum that combines the contents of early childhood education and AI education to be naturally accepted as AI education for 5-year-olds. Second, an evaluation tool for AI education that can showcase the teacher's reflection should be developed systematically. Third, it is necessary to support a play-centered AI education support and environment for early childhood teachers. Lastly, it is essential to establish a system that can be continuously operated in the field of early childhood education in consideration of AI education in the non-curricular curriculum. It is expected that in the future, a play-oriented AI education program for 5-year-olds will be developed to spread awareness of AI education for infants and present an AI education approach for each age and stage of learners.

• Journal of Embryo Transfer
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• v.26 no.4
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• pp.277-282
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• 2011

The present research was carried out to evaluate the possibility of increasing female offspring production ratios using artificial insemination buffer (AIB) before artificial insemination (AI). In this experiment, we optimized AIB composition, made an AIB gun and analyze factors affecting AI non-return rate after AIB treatment. The AIB was made with the base of Tris-buffer supplemented with L-arginine and several other chemicals that might reduce the motility of male sperm compared to the female counterpart, therefore, increasing the possibility of fertilization by female sperm. AIB must be deposited into $2^{nd}$ to $4^{th}$ cervix by AIB gun. After 15 min of AIB deposition, frozen semen was deposited into the same place. A total of 348 cattle were inseminated with AIB insemination, and there were no significant differences between AIB and traditional AI non-return rates (56.8% vs. 55.7%). The AI non-return rate in AIB group, however, differed significantly among 7 Hanwoo farms. The parturition numbers ($1^{st}$ to $7^{th}$) of cows did not affect AIB AI rate. The proportion of AIB AI success rates was significantly higher in Hanwoo cows than in dairy cows (61.0% vs. 48.7%), but the average AI success rate did not differ significantly between AIB and conventional AI (56.8% vs. 55.7%). The female offspring production rate in $2^{nd}$ to $4^{th}$ cervix deposition place was significantly higher than that in the uterus body (77.7% vs. 59.6%, p<0.05). The injection volume of AIB in 5 and 10 ml was significantly higher than that in 2 ml (77.7%, 78.7% vs. 51.8%, p<0.05), but there were no differences in AIB injection volume between 5 and 10 ml. The best exposure time of AIB in the cervix was 10 to 15 min rather than 5 min (79.2%, 77.2% vs. 52.6%, p<0.05). AIB therefore needs to have an exposure time of at least over 10 min for a higher production rate of female offspring. In conclusion, AIB could be used in AI industry to increase the female offspring ratio and AIB AI can increase the AI success rate.

• Animal cells and systems
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• v.16 no.2
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• pp.127-134
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• 2012

We investigated the effects of fadrozol, an aromatase inhibitor (AI), and $17{\alpha}$-methyltestosterone (MT) on the induction of sex change in juvenile longtooth grouper $Epinephelus$ $bruneus$, via histological observation of gonads. Changes in the mRNA expression of GtH subunits (FSH-${\beta}$ and LH-${\beta}$) in the pituitary, and estradiol-$17{\beta}$ (E2) and 11-ketotestosterone (11-KT) levels in the blood were also surveyed after AI and MT treatment. Juvenile longtooth groupers ($113{\pm}17g\;body\;weight$; $16.2{\pm}1.2cm\;body\;length$) received intramuscular injections of AI at 3 (3-AI) and 5 (5-AI) mg/kg BWdoses and MT at a 5 mg/kg BW (5-MT) dose. At week 7 post-injection, 3-AI and 5-MT oocytes were degenerated, and gonads of the 5-AI group initiated spermatogenesis. At week 21 post-injection, 3-AI- and 5-MT-treated gonads contained spermatogonia and spermatocytes, while 5-AI treatment induced advanced stages of spermatogenesis. The serum E2 level showed no significant differences throughout the experimental period, whereas that of 11-KT was significantly elevated in the 5-AI group at weeks 7 and 21 post-injection. A significant increase in the expression of FSH-${\beta}$ mRNA was evident in the 5-AI group at week 21 post-injection. In contrast, LH-${\beta}$ mRNA expression did not significantly differ among groups during the experimental period. These results imply that sex change has two stages in the longtooth grouper. In the first stage, oocytes are degenerated by the stimulation by 11-KT, and in the second stage spermatogenesis occurs, owing to the co-effects of 11-KT and FSH-${\beta}$.

• Journal of the korean academy of Pediatric Dentistry
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• v.48 no.4
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• pp.376-383
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• 2021

The aim of this study was to determine the prevalence and incidence and evaluate the current status of dental treatment of Amelogenesis imperfecta (AI) and Dentinogenesis imperfecta (DI) in South Korea. The data was based on National Health Insurance Service (NHIS)-National Sample Cohort Database (2002 - 2015) and Jeonbuk National University (JBNU) Dental Hospital (2011 - 2020). The NHIS data analysis showed prevalence of AI and DI were 11.6 and 2.4 per 100,000 people, respectively. The annual incidence of AI and DI for 2013 - 2015 were 2.2 and 0.5 per 100,000. There were no statistically significant differences regarding the number of visits, the reimbursable cost among AI, DI patients and others. In the patient analysis of the JBNU dental hospital, proportion of the reimbursable and non-reimbursable cost for AI patients were 12.1% and 87.9%, while DI patients accounted for 18.6% and 81.4%.

• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.193-206
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• 2021

Artificial Intelligence (AI) has been inserted into people's lives through Intelligent Virtual Assistants (IVA), like Alexa. Moreover, intelligent systems have expanded to design studios. This research delves into designers' perspectives on developing AI-based practices and examines the challenges of adopting future intelligent design assistants. We surveyed UX/UI professionals in Brazil to understand how they use IVAs and AI design tools. We also explored a scenario featuring the use of Alexa Sensei, a hypothetical voice-controlled AI-based design assistant mixing Alexa and Adobe Sensei characteristics. The findings indicate respondents have had limited opportunities to work with AI, but they expect intelligent systems to improve the efficiency of the design process. Further, majority of the respondents predicted that they would be able to collaborate creatively with AI design systems. Although designers anticipated challenges in natural language interaction, those who already adopted IVAs were less resistant to the idea of working with Alexa Sensei as an AI design assistant.