• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.8
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• pp.1111-1120
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• 2022

Image Capturing is a matter of viewing images and describing images in language. The problem is an important problem that can be solved by keeping, understanding, and bringing together two areas of image processing and natural language processing. In addition, by automatically recognizing and describing images in text, images can be converted into text and then into speech for visually impaired people to help them understand their surroundings, and important issues such as image search, art therapy, sports commentary, and real-time traffic information commentary. So far, the image captioning research approach focuses solely on recognizing and texturing images. However, various environments in reality must be considered for practical use, as well as being able to provide image descriptions for the intended purpose. In this work, we limit the universally available Korean and English image captioning models and text generation techniques for the purpose of image captioning.

• Journal of Practical Engineering Education
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• v.14 no.1
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• pp.11-18
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• 2022

As the need for software development manpower increases, various educational programs appear and the popularity of bootcamp style education program for software development increases. However, despite the operations and forms of bootcamp education programs are completely different from the existing software development education programs, there is a lack of research in understanding bootcamp as a software education program. Therefore, this study tried to derive the core elements of the education program through a case study on bootcamp software developer education program. After conducting interviews of 7 members who have completed a series of bootcamp software developer education program X, seven characteristics of bootcamp-type software development education program were derived: intensive theory education, sense of growth and achievement, team project-based learning, community characteristics, peer pressure, stress and fatigue due to short-term learning, and contact-free specialty. Based on the derived characteristics, the advantages and improvements of bootcamp-type education were described, and the direction of the bootcamp-type education program for software developer was discussed.

• Journal of Information Technology Applications and Management
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• v.28 no.6
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• pp.145-161
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• 2021

Recently, as personal information utilization devices such as IoT, artificial intelligence, and wearable devices that focus on the individual have spread, privacy violations are also increasing. However, the privacy paradox of providing personal information to enjoy services while worrying is getting stronger. However, there are still preliminary studies on this. In this study, an intelligent home camera based on IoT technology was selected as a research object, and whether privacy paradox exists in the IoT environment, including smart home camera, was studied. To this end, the effect of perceived usefulness, a benefit factor of smart home camera use, and privacy concern, a risk factor, on intention to use was verified. In addition, it was investigated whether the relationship between privacy concerns and intention to use differs according to the presence or absence of use experience. In order to verify the research model, a survey was conducted with people with and without experience in using smart home cameras, and a total of 298 data samples were used for statistical analysis. As a result of the analysis, it was found that both perceived usefulness and privacy concerns had a positive effect on the intention to use, proving that privacy paradox exists in the IoT-based smart home camera environment. In addition, by analyzing the fact that privacy concerns have different effects on usage intentions depending on the user experience, it was verified that those with experience have a strong privacy paradox and those without experience have a weak privacy paradox. This study is meaningful because it seeks strategic implications to improve service and business performance by understanding the relationship between privacy attitudes and behaviors of IoT service providers, including smart home cameras.

• Journal of Fashion Business
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• v.27 no.4
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• pp.141-162
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• 2023

With the prospect that integrating creative AI in the fashion design field will become more visible, this study considered the case of creative fashion design development through Human-AI Co-creation (HAIC). Methodologically, this research encompasses a literature review and empirical investigations. In the literature review, the fashion design and creative HAIC processes, and the possibilities of integrating AI in fashion design were considered. In the empirical study, based on the case analysis of generating fashion design through HAIC, the HAIC type according to the role and interaction method, and characteristics of humans and AI was considered, and the HAIC process for fashion design was derived. The results of this study are summarized as follows. First, HAIC types in fashion design are divided into four types: AI-driven passive HAIC, human-driven passive HAIC, flexible interaction-based HAIC, and integrated interaction-based value creation HAIC. Second, the stages of the HAIC process for creative fashion design can be broadly divided into semantic data integration, visual ideation, design creation and expansion, design presentation, and design/manufacturing solution and UX platform creation. Third, in fashion design, HAIC contributes to human ability, enhancement of creativity, achievement of efficient workflow, and creation of new values. This research suggests that HAIC has the potential to revolutionize the fashion design industry by facilitating collaboration between humans and AI; consequently, enhancing creativity, and improving the efficiency of the design process. It also offers a framework for understanding the different types of HAIC and the stages involved in the creative fashion design process.

• International Journal of Computer Science & Network Security
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• v.23 no.3
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• pp.110-122
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• 2023

Over the last few decades, various innovative technologies have emerged that have significantly contributed to making life easier for humans. Various information and communication technologies (ITCs) have emerged as a result of the global technological revolution, including big data, IoT, 4G and 5G networks, cloud computing, mobile computing, and artificial intelligence. These technologies have been adopted in urban planning and development, which gave rise to the concept of smart cities in the 1990s. A smart city is a type of city that uses ITCs to exchange and share information to enhance the quality of services for its citizens. With the global population increasing at unprecedented levels, cities are overwhelmed with a myriad of challenges, such as the energy crisis, environmental pollution, sanitation and sewage challenges, and water quality issues, and therefore, have become a convergence point of economic, social, and environmental risks. The concept of a smart city is a multidisciplinary, unified approach that has been adopted by governments and municipalities worldwide to overcome these challenges. Though challenging, this transformation is essential for cities with differing technological and social features, which all have the potential to determine the success or failure of the digital transformation of cities into smart cities. In recent years, researchers, businesses, and the government have all turned their attention to the emerging field of smart cities. Accordingly, this paper aims to represent a thorough understanding of the movement toward smart cities. The key themes identified are smart city definitions and concepts, smart city dimensions, and smart city architecture of different layers. Furthermore, this article discusses the challenges and some examples of smart cities.

• Korean Journal of Materials Research
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• v.33 no.5
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• pp.175-188
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• 2023

Water electrolysis holds great potential as a method for producing renewable hydrogen fuel at large-scale, and to replace the fossil fuels responsible for greenhouse gases emissions and global climate change. To reduce the cost of hydrogen and make it competitive against fossil fuels, the efficiency of green hydrogen production should be maximized. This requires superior electrocatalysts to reduce the reaction energy barriers. The development of catalytic materials has mostly relied on empirical, trial-and-error methods because of the complicated, multidimensional, and dynamic nature of catalysis, requiring significant time and effort to find optimized multicomponent catalysts under a variety of reaction conditions. The ultimate goal for all researchers in the materials science and engineering field is the rational and efficient design of materials with desired performance. Discovering and understanding new catalysts with desired properties is at the heart of materials science research. This process can benefit from machine learning (ML), given the complex nature of catalytic reactions and vast range of candidate materials. This review summarizes recent achievements in catalysts discovery for the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER). The basic concepts of ML algorithms and practical guides for materials scientists are also demonstrated. The challenges and strategies of applying ML are discussed, which should be collaboratively addressed by materials scientists and ML communities. The ultimate integration of ML in catalyst development is expected to accelerate the design, discovery, optimization, and interpretation of superior electrocatalysts, to realize a carbon-free ecosystem based on green hydrogen.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.59-67
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• 2021

The development of AI technology has brought about a big change in our lives. As AI's influence grows from life to society to the economy, the importance of education on AI and data is also growing. In particular, the OECD Education Research Report and various domestic information and curriculum studies address data literacy and present it as an essential competency. Looking at domestic and international studies, one can see that the definition of data literacy differs in its specific content and scope from researchers to researchers. Thus, the definition of major research related to data literacy was analyzed from various angles and derived from various angles. In key studies, Word2vec natural language processing methods, along with word frequency analysis used to define data literacy, are used to analyze semantic similarities and nominate them based on content elements of curriculum research to derive the definition of 'understanding and using data to process information'. Based on the definition of data literacy derived from this study, we hope that the contents will be revised and supplemented, and more research will be conducted to provide a good foundation for educational research that develops students' future capabilities.

• The Journal of Information Systems
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• v.32 no.1
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• pp.109-146
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• 2023

Purpose With Intelligent public service (IPS), it is possible to automate the quality of civil affairs, provide customized services for citizens, and provide timely public services. However, empirical studies on factors for the successful use of IPS are still insufficient. Hence, the purpose of this study is to empirically analyze the factors that affect the success of IPS with classification function. ISSM (Information System Success Model) is considered as the underlying research model, and how the algorithm quality, data quality, and environmental quality of the discrimination system affect the relationship between utilization intentions is analyzed. Design/methodology/approach In this study, a survey was conducted targeting users using IPS. After giving them a preliminary explanation of the intelligent public service centered on the discrimination system, they briefly experienced two types of IPS currently being used in the public sector. Structural model analysis was conducted using Smart-PLS 4.0 with a total of 415 valid samples. Findings First, it was confirmed that algorithm quality and data quality had a significant positive (+) effect on information quality and system quality. Second, it was confirmed that information quality, system quality, and environmental quality had a positive (+) effect on the use of IPS. Thirdly, it was confirmed that the use of IPS had a positive (+) effect on the net profit for the use of IPS. In addition, the moderating effect of the degree of knowledge on AI, the perceived accuracy of discriminative experience and IPS, and the user was analyzed. The results suggest that ISSM and TOE framework can expand the understanding of the success of IPS.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.81-83
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• 2022

Understanding research trends is necessary to select research topics and explore related works. Most researchers search representative keywords of interesting domains or technologies to understand research trends. However some conferences in artificial intelligence or data mining fields recently publish hundreds to thousands of papers for each year. It makes difficult for researchers to understand research trend of interesting domains. In our paper, we propose an automatic technology keyphrase extraction method to support researcher to understand research trend for each conference or journal. Keyphrase extraction that extracts important terms or phrases from a text, is a fundamental technology for a natural language processing such as summarization or searching, etc. Previous keyphrase extraction technologies based on pretrained language model extract keyphrases from long texts so performances are degraded in short texts like titles of papers. In this paper, we propose a techonolgy keyphrase extraction model that is robust in short text and considers the importance of the word.

• Communications of Mathematical Education
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• v.37 no.4
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• pp.591-614
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• 2023

For a long time, mathematics education institutions such as NCTM(National Council of Teachers of Mathematics) have emphasized the essential role of writing, and recent surveys by the Ministry of Education report a decline in foundational academic skills in the post-COVID19 period. The purpose of this study is to redefine the significance of mathematics writing in mathematics education, focusing on competencies highlighted in the field, particularly in the areas of problem-solving, communication, and reasoning. The research findings indicate that writing in problem-solving enhances cognitive organization, fostering the ability to grasp concepts and methods. Writing in communication builds confidence through the meta-cognitive process, and writing in inference allows self-awareness of step-by-step identification of areas lacking understanding. Particularly in the future society where artificial intelligence(AI) is utilized, changes in the learning environment necessitate research for the establishment of authenticity judgment through writing and the cultivation of a proper writing culture.