• Electronics and Telecommunications Trends
• /
• v.37 no.1
• /
• pp.21-31
• /
• 2022

Human behavior and emotions are influenced by experiences accumulated through the past and present. To realize artificial intelligence technology that understands and sympathizes with humans, cognitive computing technology that automatically analyzes human behaviors, habits, and emotions associated with specific situations and uses past data and domain knowledge is required. In this study, we examine the latest research trends on human-understanding cognitive computing technology that recognizes human behavior and emotions, stores them as experience data, and provides services by analyzing the stored data. Further, we introduce high-quality data collection research in real-life and services for improving physical and mental health. We also review key issues essential for developing these technologies.

• Journal of The Korean Association of Information Education
• /
• v.24 no.6
• /
• pp.633-641
• /
• 2020

The development of intelligent information technology based on intelligence and data and network technology implemented by artificial intelligence has instigated innovation in society as a whole and has shown wide social and economic impact. Therefore, not only overseas but also in Korea, AI education is in a hurry to cultivate talents who will lead the upcoming society. Data is an important part of artificial intelligence, and data literacy, which can collect, process, and analyze data, to make data-based decisions, can be seen as an important competency to be developed along with AI literacy. Therefore, in this study, an AI data science education program that can increase data literacy of elementary school students was developed and applied to the experimental group, and its effectiveness was verified through a pre- and post response sample t-test. As a result, all of the four detailed competencies of data literacy, data understanding, collection, analysis, and expression, showed statistically significant improvement, indicating that the AI data science education program was effective in improving students' data literacy.

• Journal of Intelligence and Information Systems
• /
• v.29 no.4
• /
• pp.287-308
• /
• 2023

After launching its service in November 2022, ChatGPT has rapidly increased the number of users and is having a significant impact on all aspects of society, bringing a major turning point in the history of artificial intelligence. In particular, the inference ability of large language models such as ChatGPT is improving at a rapid pace through prompt engineering techniques. This reasoning ability can be considered as an important factor for companies that want to adopt artificial intelligence into their workflows or for individuals looking to utilize it. In this paper, we begin with an understanding of in-context learning that enables inference in large language models, explain the concept of prompt engineering, inference with in-context learning, and benchmark data. Moreover, we investigate the prompt engineering techniques that have rapidly improved the inference performance of large language models, and the relationship between the techniques.

• The Journal of Korea Robotics Society
• /
• v.14 no.1
• /
• pp.22-30
• /
• 2019

For effective human-robot interaction, robots need to understand the current situation context well, but also the robots need to transfer its understanding to the human participant in efficient way. The most convenient way to deliver robot's understanding to the human participant is that the robot expresses its understanding using voice and natural language. Recently, the artificial intelligence for video understanding and natural language process has been developed very rapidly especially based on deep learning. Thus, this paper proposes robot vision to audio description method using deep learning. The applied deep learning model is a pipeline of two deep learning models for generating natural language sentence from robot vision and generating voice from the generated natural language sentence. Also, we conduct the real robot experiment to show the effectiveness of our method in human-robot interaction.

• International Journal of Computer Science & Network Security
• /
• v.21 no.12
• /
• pp.29-34
• /
• 2021

The Qur'an is regarded as the holy book by Islam followers; they assert that God wants humankind to understand its meanings and implement best practices. Numerous individuals have attempted to understand the meaning of its verses and explore its Extraordinary Vocabulary; however, few people successfully studied and researched the different meanings of that holy text. Only a limited segment of the society comprising scholars, students, and intellectuals have grasped the teachings of the Qur'an. A majority of the general population, specifically youngsters, spend ample time using mobile phones. In this context, many innovative educational platforms have recently been launched to attract the general public to learn and use knowledge. Research has provided the positive impact of such smart platforms. This concept is about an innovative smartphone platform to help users understand and reason the Qur'an by helping with the book vocabulary explained by expert scholars. This work proposes creating an engaging digital format using innovative technologies. This idea is inspired by youngsters who demonstrate an immense interest in online learning. Qur'an vocabulary is the prerequisite to building a better understanding that allows users to get precise meaning.

• Journal of Distribution Science
• /
• v.22 no.2
• /
• pp.103-113
• /
• 2024

Purpose: With the popularity of artificial intelligence (AI) in the service industry and occurrence ofservice failures in AI-based services, understanding human-robot interaction issues in service failure situations is especially important. Some issues which deserve further empirical investigation are whether consumers can develop the same tolerance for chatbots after service failure as they have for human agents, and the relationship between agent type and tolerance is mediated by the mechanisms of perceived warmth and perceived competence. Research Design, Data, and Methodology: This research experimentally collected and analyzed data from 119 university students who had experienced chatbots service failures. Differences in tolerance towards human agents and chatbots after experiencing service failures were explored, with a further examination of the mediating pathways between this relationship via perceived warmth and perceived competence. Results: Consumers are more tolerant ofservice failure with chatbots compared to service failure with human agents. Significant mediation of the relationship between service agent and service failure tolerance by perceived competence, while perceived warmth has no significant mediating effect. Conclusions: This research enhances our understanding of AI-assisted services, human-computer interaction, improves the service functionality of existing smart devices, and deepens the understanding of the relationship between consumer responses and behaviors.

• The Journal of Korean Institute of Next Generation Computing
• /
• v.14 no.5
• /
• pp.19-30
• /
• 2018

Visual information understanding is known as one of the most difficult and challenging problems in the realization of machine intelligence. This paper proposes deriving visual verb and construction of ActionNet database as a video database for video semantic understanding. Even though development AI (artificial intelligence) algorithms have contributed to the large part of modern advances in AI technologies, huge amount of database for algorithm development and test plays a great role as well. As the performance of object recognition algorithms in still images are surpassing human's ability, research interests shifting to semantic understanding of video contents. This paper proposes candidates of visual verb requiring in the construction of ActionNet as a learning and test database for video understanding. In order to this, we first investigate verb taxonomy in linguistics, and then propose candidates of visual verb from video description database and frequency of verbs. Based on the derived visual verb candidates, we have defined and constructed ActionNet schema and database. According to expanding usability of ActionNet database on open environment, we expect to contribute in the development of video understanding technologies.

• Journal of the Korean Society of Systems Engineering
• /
• v.20 no.1
• /
• pp.64-75
• /
• 2024

With the development of the Internet, the information in our lives has become fast and diverse. Especially in the field of defense, articles and information are pouring in from various sources every day, and fast information selection, understanding, and decision-making are required in the ever-changing situation. It is very cumbersome to go from platform to platform and read articles one by one to get the information you need. To solve this problem, this research aims to save time and provide quick access to the latest information by allowing you to quickly grasp key information from summarized content without having to read the entire article. This can improve efficiency by allowing defense professionals to focus more on important tasks rather than extensive information search and analysis.

• Journal of Convergence for Information Technology
• /
• v.12 no.5
• /
• pp.139-149
• /
• 2022

The purpose of this study is to develop and analyze the effects of an educational program that can cultivate artificial intelligence(AI) convergence education competency for future education and enhance students' understanding of pre-service teachers. For this end, an AI convergence education program using Machine Learning for Kids and Scratch 3 was developed for 15 weeks under the theme of classifying the state of matter. The developed program were treated by K University pre-service teachers who participated voluntarily. As a result, pre-service teachers were able to metaphorically understand the learning process of students through understanding of machine learning training process. In addition, the pre-post t-test result of AI teaching efficacy showed a statistically significant improvement with t=-7.137 (p<.000). Therefore, it is suggested that the AI convergence education program developed in this study can help to increase the understanding of the pre-service teacher's students in an indirect way other than practice teaching, and can contribute to foster AI education competency.

• Journal of the Korea Society of Computer and Information
• /
• v.25 no.3
• /
• pp.109-115
• /
• 2020

In this paper, we propose an artificial intelligence(AI) technology analysis using partial least square(PLS) regression model. AI technology is now affecting most areas of our society. So, it is necessary to understand this technology. To analyze the AI technology, we collect the patent documents related to AI from the patent databases in the world. We extract AI technology keywords from the patent documents by text mining techniques. In addition, we analyze the AI keyword data by PLS regression model. This regression model is based on the technique of partial least squares used in the advanced analyses such as bioinformatics, social science, and engineering. To show the performance of our proposed method, we make experiments using AI patent documents, and we illustrate how our research can be applied to real problems. This paper is applicable not only to AI technology but also to other technological fields. This also contributes to understanding other various technologies by PLS regression analysis.