• The Journal of the Convergence on Culture Technology
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• v.10 no.5
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• pp.803-808
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• 2024

As a service that creates graphic work images with AI, DALL-E2, Midjourney, Stable Diffusion, BING image generator, and Playground AI are widely used. It is that graphic also enables learner-led customized education. With this, it is worth studying detailed design customized learning materials and methods for designing efficient design in future 2D graphic work, and it is necessary to explore the areas of application. The current situation is that it is necessary to develop a design education system that can indicate the lack of AI technology through text security and questions. In this study, a successful proposal for a process that is produced through a process of creating AI design work through proxy work can be presented as a conclusion. Design, advertisement, and visual content companies are already using and adapting, and the trend is to reflect the AI graphic utilization ability and results in the portfolio along with interviews when hiring new employees. In line with this, detailed consideration and research on visual and design production methods for AI convergence between instructors and learners are currently needed. In this paper, proposals and methods for image quality production were considered in the main body and conclusions, and conclusive directions were proposed for five alternatives and methods for future applications.

• Journal of Christian Education in Korea
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• v.72
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• pp.183-203
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• 2022

The purpose of this study is to construct factors of AI education utilization competency. AI education utilization competency is used as basic data for education to enhance the AI education competency of pre-service early childhood teachers. To this end, 7 studies related to competency factors and models were selected by searching for previous studies. Seven preceding studies were analyzed. As a result, 18 competency factors were extracted, including understanding of artificial intelligence. The extracted competency elements were divided into six areas, which are divided into understanding subject knowledge through coding, class preparation, class management, class result feedback, class guidance, and self-development. And 15 factors were constructed. The draft formed through coding was improved through review by three early childhood education experts. Factors improved through expert review were structured by classifying them into knowledge, skills, and attitudes to organize the curriculum. The validity of the structured competency factor was verified through expert Delphi. As a result of the Delphi verification, all factors were converged in the first survey. Through this, 6 competency areas, 11 competency factors, and 19 competency factors were composed of knowledge, 10 skills, and 5 attitudes. The implication is that the competency factors presented as a result of this study can be used as basic data for organizing a curriculum to improve the ability of pre-service early childhood teachers to use artificial intelligence education.

• The Journal of the Convergence on Culture Technology
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• v.10 no.5
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• pp.397-406
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• 2024

Today, in the field of contemporary fashion design, AI is being actively utilized as a new design tool, leading to a new paradigm of collaboration between designers and AI. This study is about a method for developing integrated fashion design through collaboration between human designers and AI. The purpose of this study is to analyze the visual and formative characteristics and changes of fashion design images generated using the AI generation program Midjourney, thereby expanding the understanding and utilization methods of AI image generation programs in fashion design development. The results of this study are as follows. First, Midjourney has the characteristic of relying more on the characteristics of the existing image used rather than the command when creating the image. It also creates new images by distributing and applying the design through an eclectic interaction between the costume and the image background. By excluding the names of fashion items from the commands, you can generate images that can give you more diverse ideas. Second, Midjourney initially expressed clothing colors using colors used in fashion schematics in color creation, and gradually expanded to various color series. Third, there is a kind of compromise between color and design when Midjourney creates an image, and accordingly, by specifying and limiting the image background and clothing colors, more diverse and advanced fashion design images can be created.

• Smart Media Journal
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• v.7 no.4
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• pp.30-36
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• 2018

Single domain model like DataLake framework is in spotlight because it can improve data efficiency and process data smarter in big data environment, where large scaled business system generates huge amount of data. In particular, efficient operation of network, storage, and computing resources in logical single domain model is very important for physically partitioned multi-site data process. Based on the advantages of Data Lake framework, we define and extend the concept of Connected Data Architecture and functions of DataLake framework for integrating multiple sites in various domains and managing the lifecycle of data. Also, we propose the design of CDA-based AI service and utilization scenarios in various application domain.

• Korean Journal of Clinical Pharmacy
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• v.34 no.2
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• pp.134-139
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• 2024

Background: Increasing numbers of studies and research about artificial intelligence (AI) and machine learning (ML) have led to their application in clinical trials. The purpose of this study is to analyze computer-based new technologies (AI/ML) applied on clinical trials registered on ClinicalTrials.gov to elucidate current usage of these technologies. Methods: As of March 1st, 2023, protocols listed on ClinicalTrials.gov that claimed to use AI/ML and included at least one of the following interventions-Drug, Biological, Dietary Supplement, or Combination Product-were selected. The selected protocols were classified according to their context of use: 1) drug discovery; 2) toxicity prediction; 3) enrichment; 4) risk stratification/management; 5) dose selection/optimization; 6) adherence; 7) synthetic control; 8) endpoint assessment; 9) postmarketing surveillance; and 10) drug selection. Results: The applications of AI/ML were explored in 131 clinical trial protocols. The areas where AI/ML was most frequently utilized in clinical trials included endpoint assessment (n=80), followed by dose selection/optimization (n=15), risk stratification/management (n=13), drug discovery (n=4), adherence (n=4), drug selection (n=1) and enrichment (n=1). Conclusion: The most frequent application of AI/ML in clinical trials is in the fields of endpoint assessment, where the utilization is primarily focuses on the diagnosis of disease by imaging or video analyses. The number of clinical trials using artificial intelligence will increase as the technology continues to develop rapidly, making it necessary for regulatory associates to establish proper regulations for these clinical trials.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.4
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• pp.65-76
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• 2023

In the field of technology entrepreneurship and startups, the development of Artificial Intelligence(AI) has emerged as a key topic for business model innovation. As a result, venture firms are making various efforts centered on AI to secure competitiveness(Kim & Geum, 2023). The purpose of this study is to analyze the relationship between the development of GenAI technology and the startup ecosystem by analyzing domestic news articles to identify trends in the technology startup field. Using BIG Kinds, this study examined the changes in GenAI-related news articles, major issues, and trends in Korean news articles from 1990 to August 10, 2023, focusing on the emergence of ChatGPT before and after, and visualized the relevance through network analysis and keyword visualization. The results of the study showed that the mention of GenAI gradually increased in the articles from 2017 to 2023. In particular, OpenAI's ChatGPT service based on GPT-3.5 was highlighted as a major issue, indicating the popularization of language model-based GenAI technologies such as OpenAI's DALL-E, Google's MusicLM, and VoyagerX's Vrew. This proves the usefulness of GenAI in various fields, and since the launch of ChatGPT, Korean companies have been actively developing Korean language models. Startups such as Ritten Technologies are also utilizing GenAI to expand their scope in the technology startup field. This study confirms the connection between GenAI technology and startup entrepreneurship activities, which suggests that it can support the construction of innovative business strategies, and is expected to continue to shape the development of GenAI technology and the growth of the startup ecosystem. Further research is needed to explore international trends, the utilization of various analysis methods, and the possibility of applying GenAI in the real world. These efforts are expected to contribute to the development of GenAI technology and the growth of the startup ecosystem.

• Convergence Security Journal
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• v.19 no.5
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• pp.63-73
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• 2019

In the 4th Industrial Revolution, information is collected and analyzed from people and objects through the rapid development of ICT. It is possible to create value. However, there are many legal and institutional restrictions on the collection of information aimed at people.Therefore, in-depth research on the protection and use of personal information in the rapidly changing cyber security environment is needed. The purpose of this study is to protect and utilize personal information for the operation of AI (Artificial Intelligence) and big data during the 4th Industrial Revolution. It is to seek a paradigm shift. The organization of the research for this is: Chapter 1 examines the meaning of personal information during the 4th Industrial Revolution, Chapter 2 presents the framework for the review and analysis of prior research. In Chapter 3, after analyzing policies for the protection and utilization of personal information in major countries, Chapter 4 looks at the paradigm shift in personal information protection during the 4th Industrial Revolution and how to respond. Chapter 5 made some policy suggestions for the protection and utilization of personal information.

• The Journal of Society for e-Business Studies
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• v.21 no.4
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• pp.29-40
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• 2016

Voice User Interface (VUI) is the most familiar and comfortable interface to human. Recently, with the development of cloud and AI technologies VUI has been applied to various products. The aim of this study was to identify the problems of the current VUI and to find the direction of future study by investigating the utilization status and user perception of the VUI of smartphones. A survey was conducted with 163 college students using Google Forms. The results showed that the level of recognition of VUI is high but the rate of usage is very low, and many users feel uncomfortable about the voice recognition rate, reaction speed and operation method. Most of the survey participants tried VUI out of curiosity, but only a small portion of them found it useful to continue to use it. Many participants disliked talking to machines and also did not want others to listen. The study results will guide future research efforts for improving the utilization of VUI.

• BMB Reports
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• v.46 no.1
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• pp.31-36
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• 2013

Heat shock proteins play an important role in plant stress tolerance and are mainly regulated by heat shock transcription factors (Hsfs). In this study, we generated transgenic rice over-expressing OsHsfA7 and carried out morphological observation and stress tolerance assays. Transgenic plants exhibited less, shorter lateral roots and root hair. Under salt treatment, over-expressing OsHsfA7 rice showed alleviative appearance of damage symptoms and higher survival rate, leaf electrical conductivity and malondialdehyde content of transgenic plants were lower than those of wild type plants. Meanwhile, transgenic rice seedlings restored normal growth but wild type plants could not be rescued after drought and re-watering treatment. These findings indicate that over-expression of OsHsfA7 gene can increase tolerance to salt and drought stresses in rice seedlings.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.4
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• pp.21-35
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• 2023

Expectations surrounding generative AI technology and its profound ramifications are sweeping across various industrial domains. Given the anticipated pivotal role of the startup ecosystem in the utilization and advancement of generative AI technology, it is imperative to cultivate a deeper comprehension of the present state and distinctive attributes characterizing venture capital (VC) investments within this domain. The current investigation delves into South Korea's landscape of VC investment deals and prognosticates the projected VC investments by juxtaposing these against the United States, the frontrunner in the generative AI industry and its associated ecosystem. For analytical purposes, a compilation of 286 investment deals originating from 117 U.S. generative AI startups spanning the period from 2008 to 2023, as well as 144 investment deals from 42 South Korean generative AI startups covering the years 2011 to 2023, was amassed to construct new datasets. The outcomes of this endeavor reveal an upward trajectory in the count of VC investment deals within both the U.S. and South Korea during recent years. Predominantly, these deals have been concentrated within the early-stage investment realm. Noteworthy disparities between the two nations have also come to light. Specifically, in the U.S., in contrast to South Korea, the quantum of recent VC deals has escalated, marking an augmentation ranging from 285% to 488% in the corresponding developmental stage. While the interval between disparate investment stages demonstrated a slight elongation in South Korea relative to the U.S., this discrepancy did not achieve statistical significance. Furthermore, the proportion of VC investments channeled into generative AI enterprises, relative to the aggregate number of deals, exhibited a higher quotient in South Korea compared to the U.S. Upon a comprehensive sectoral breakdown of generative AI, it was discerned that within the U.S., 59.2% of total deals were concentrated in the text and model sectors, whereas in South Korea, 61.9% of deals centered around the video, image, and chat sectors. Through forecasting, the anticipated VC investments in South Korea from 2023 to 2029 were derived via four distinct models, culminating in an estimated average requirement of 3.4 trillion Korean won (ranging from at least 2.408 trillion won to a maximum of 5.919 trillion won). This research bears pragmatic significance as it methodically dissects VC investments within the generative AI domain across both the U.S. and South Korea, culminating in the presentation of an estimated VC investment projection for the latter. Furthermore, its academic significance lies in laying the groundwork for prospective scholarly inquiries by dissecting the current landscape of generative AI VC investments, a sphere that has hitherto remained void of rigorous academic investigation supported by empirical data. Additionally, the study introduces two innovative methodologies for the prediction of VC investment sums. Upon broader integration, application, and refinement of these methodologies within diverse academic explorations, they stand poised to enhance the prognosticative capacity pertaining to VC investment costs.