• International conference on construction engineering and project management
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• 2022.06a
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• pp.1222-1222
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• 2022

• Electronics and Telecommunications Trends
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• v.38 no.4
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• pp.70-80
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• 2023

In recent years, our society has shifted from an information society to an intelligent information society, in which computing has become a key factor in shaping and driving social development. In this new era of digital civilization powered by the Internet of Things, traditional data-based computing is no longer sufficient to meet the growing demand for higher levels of intelligence. Therefore, intelligent computing has emerged, reshaping traditional computing and forming new computing paradigms to promote the digital revolution in the era of the Internet of Things, big data, and artificial intelligence. Intelligent computing has greatly expanded the scope of computing through new computing theories, architectures, methodologies, systems, and applications, and it is expanding into diverse computing paradigms such as perceptual intelligence, cognitive intelligence, autonomous intelligence, and human-computer fusion intelligence. This paper introduces the concept and main features of intelligent computing and describes trends in standardization for intelligent computing within the ISO/IEC JTC 1, focusing on the technical trend report on intelligent computing that is currently under development within ISO/ IEC JTC 1/AG 2.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.10
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• pp.1435-1440
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• 2021

With the advent of the low interest rate era, many investors are flocking to the stock market. In the past stock market, people invested in stocks labor-intensively through company analysis and their own investment techniques. However, in recent years, stock investment using artificial intelligence and data has been widely used. The success rate of stock prediction through artificial intelligence is currently not high, so various artificial intelligence models are trying to increase the stock prediction rate. In this study, we will look at various artificial intelligence models and examine the pros and cons and prediction rates between each model. This study investigated as stock prediction programs using artificial intelligence artificial neural network (ANN), deep learning or hierarchical learning (DNN), k-nearest neighbor algorithm(k-NN), convolutional neural network (CNN), recurrent neural network (RNN), and LSTMs.

• Journal of Korean Society for Quality Management
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• v.47 no.4
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• pp.837-846
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• 2019

Purpose: The purpose of this study is to define various concepts, features, and scopes by examining various previous studies on AI services that are completely different from existing services. It also examines the limitations of existing service quality evaluation methods and studies the characteristics by combining them with various cases of new AI services. And this is to derive and propose quality evaluation attributes of AI service. Methods: The concept and characteristics of artificial intelligence were derived through research and analysis of various previous studies related to artificial intelligence. The key characteristics and quality evaluation items were derived through the KJ method and matching based on the keywords and characteristics derived from previous studies and various cases. Results: Based on the review of various previous studies on the quality of artificial intelligence services, this study presents the main characteristics and quality evaluation items of new artificial intelligence services, which are completely different from existing service quality evaluations. Conclusion: The quality measurement model of AI service is very useful when planning and developing AI-based new products or services because it can accurately evaluate the requirements of consumers using the services of the new AI era. In addition, consumers can be recommended a customized service according to the situation or taste, and can be provided with a customized service based on this.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.3
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• pp.124-129
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• 2021

As the 4th industrial era is in full swing, the public's interest in related technologies such as artificial intelligence, big data, and block chain is increasing. As artificial intelligence technology is used in various industrial fields, the need for research methods incorporating artificial intelligence technology in related fields is also increasing. Evidence collection among digital forensic investigation techniques is a very important procedure in the investigation process that needs to prove a specific person's suspicions. However, there may be cases in which evidence is damaged due to intentional damage to evidence or other physical reasons, and there is a limit to the collection of evidence in this situation. Therefore, this paper we intends to propose an artificial intelligence-based evidence collection system that analyzes numerous image files reported by citizens in real time to visually check the location, user information, and shooting time of the image files. When this system is applied, it is expected that the evidence expected data collected in real time can be actually used as evidence, and it is also expected that the risk area analysis will be possible through big data analysis.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.182-190
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• 2024

Various artificial intelligence neural network models that have emerged since 2014 enable the creation of new content beyond the existing level of information discrimination and withdrawal, and the recent generative artificial intelligences such as ChatGPT and Gall-E2 create and present new information similar to actual data, enabling natural interaction because they create and provide verbal expressions similar to humans, unlike existing chatbots that simply present input content or search results. This study aims to present a model that can improve the ChatGPT communication skills of university students through curriculum research on ChatGPT, which can be participated by students from all departments, including engineering, humanities, society, health, welfare, art, tourism, management, and liberal arts. It is intended to design a way to strengthen competitiveness to embody the practical ability to solve problems through ethical attitudes, AI-related technologies, data management, and composition processes as knowledge necessary to perform tasks in the artificial intelligence era, away from simple use capabilities. It is believed that through creative education methods, it is possible to improve university awareness in companies and to seek industry-academia self-reliant courses.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.801-806
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• 2022

In the modern era, the necessity of color capability in the digital era is the demand of the era, and research on improving color practice on the subdivided digital four areas that are not in the existing practice is needed. For digital majors who are difficult to solve in existing paint color practice, classes in digital color practice in four more specialized areas are needed, and the use of efficient artificial intelligence was studied for classes in digitized color and color sense. In this paper, we tried to show the expansion of the color practice area by suggesting digital color practice and color matching method based on Photoshop artificial intelligence and big data technology that existing color and color matching were practice that only CMYK could do. In addition, based on the color quantification data of individual users provided by the latest Adobe Sceney program artificial intelligence, the purpose of the practice was to improve learners' predictions of actual color combinations and random colors using filter effects. In conclusion, it is a study on the use of programs that eliminate ambiguity in the mixing process of existing paint practice, secure digital color details, and propose a practical method that can provide effective learning methods for beginners and intermediates to develop their senses through artificial intelligence support. The Adobe program practice method necessary for coloration and main color through theoretical consideration and improvement of teaching skills that are better than existing paint practice were presented.

• Journal of The Korean Association of Information Education
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• v.24 no.4
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• pp.391-400
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• 2020

While artificial intelligence (AI) is attracting attention as a core technology in the era of the 4th industrial revolution, needs for artificial intelligence education to cultivate AI literacy is emerging. In this regard, we developed and applied a project-based AI education program for elementary and middle school students, and analyzed its effects. Participants were assigned into teams with three members, and each team engaged in a project-based AI education program for two nights and three days. In the project, they selected an real-world problem they wanted and devised an AI-enabled artifact to solve it. The effectiveness of the program was investigated with the changes in attitude and efficacy of learners toward artificial intelligence. The results showed that the AI project learning positively changed both attitudes and efficacy toward artificial intelligence at a statistically significant level. This change was more pronounced as the level of perceived programming skills increased, and the level of interest in the project learning increased.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.159-166
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• 2022

Artificial Intelligence has stimulated every aspect of today's life. Human thinking quality is trying to be involved through digital tools in all research areas of the modern era. The education industry is also leveraging artificial intelligence magical power. Uses of digital technologies in pedagogical paradigms are being observed from the last century. The widespread involvement of artificial intelligence starts reshaping the educational landscape. Adaptive learning is an emerging pedagogical technique that uses computer-based algorithms, tools, and technologies for the learning process. These intelligent practices help at each learning curve stage, from content development to student's exam evaluation. The quality of information technology students and professionals training has also improved drastically with the involvement of artificial intelligence systems. In this paper, we will investigate adopted digital methods in the education sector so far. We will focus on intelligent techniques adopted for information technology students and professionals. Our literature review works on our proposed framework that entails four categories. These categories are communication between teacher and student, improved content design for computing course, evaluation of student's performance and intelligent agent. Our research will present the role of artificial intelligence in reshaping the educational process.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.275-281
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• 2021

Much of our lives are closely related to artificial intelligence, and society is changing more rapidly. Reflecting this era, the need for artificial intelligence education has emerged and various learning methods have been proposed, but guidance on artificial intelligence teaching and learning activities for lower grades elementary school students is insufficient. Therefore, in this study, the data collection education program for the lower grades of elementary school was developed based on the contents standards of the Korea Foundation for the Advancement of Science & Creativity. Focusing on the principles of artificial intelligence and the detailed data area of the utilization area, the focus was on expressing numbers and letters in various ways, such as colors and pictures, and finding various types of data in life to learn the principles of artificial intelligence. Through this program, it is expected that lower-grade elementary school students will be able to understand the importance of data collection in artificial intelligence through the process of knowing about data and collecting sound, picture, and text data.