• Journal of Korean Elementary Science Education
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• v.43 no.1
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• pp.148-157
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• 2024

The purpose of this study was to develop an artificial intelligence-based marine ecological education program to improve the ecological sensitivity of elementary school students. The program was taught 11 times within 4 weeks, and an ecological sensitivity test was conducted before and after the program. The statistical results of the tests showed that the developed program improved the ecological sensitivity of elementary school students. Through in-depth interviews, improvements were found in all the areas, such as empathy for the living things, interest in nature, enjoyment of nature, and wonder about nature. Through the marine ecological classes, which used artificial intelligence and virtual reality, the students were able to get closer to nature, and the student participation activities showed a positive effect on their ecological sensitivity. This indicates that experience-oriented education methods are more effective than simple explanatory classes to improve the students' ecological sensitivity, and artificial intelligence technology proved effective in increasing the students' immersion in the class.

• Journal of Platform Technology
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• v.11 no.5
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• pp.97-103
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• 2023

Unlike GPS, which is an outdoor positioning technology that is universally and uniformly used all over the world, various technologies are still being developed in the field of indoor positioning technology. In order to acquire accurate indoor location information, a standard of representative indoor positioning technology is required. Recently, indoor positioning technology is expanding into the Real Time Location Service (RTLS) area based on high-precision location data. Accordingly, a new type of indoor positioning technology is being proposed. Thanks to the development of artificial intelligence, artificial intelligence-based indoor positioning technology using wireless signal data of a smartphone is rapidly developing. At this time, in the process of collecting data necessary for artificial intelligence learning, data that is distorted or inappropriate for learning may be included, resulting in lower indoor positioning accuracy. In this study, we propose a data preprocessing technology for artificial intelligence learning to obtain improved indoor positioning results through the refinement process of the collected data.

• The Journal of the Korea Contents Association
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• v.20 no.9
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• pp.475-485
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• 2020

The purpose of this study is to examine factors influencing the digital divide between the baby boomer and elderly generation. Under this relationship, we investigated the age, education, family type, income, using attitude, using motivation, using outcome, cognition of intelligence information society, anxiety of intelligence information society, life satisfaction, social support. Research data were Using the data of 2017 Digital Divide Survey conducted by the National Information Society Agency(NIA), The final sample were 2300 who fully responded. As a result of factor, age, education, using attitude, using object, cognition of intelligence information society, life satisfaction significantly effected directly in baby boomer. Also, family types, cognition of information intelligence society, life satisfaction in elderly. Based on the results of this study, the implications and future studies of the baby boomer and elderly are suggested.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.11
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• pp.4869-4874
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• 2011

In this paper, we defined constructivism and ontology theory and associate it in Location Based Service ubiquitous learning. And this paper aims to provide a clear vision about location based service (LBS) ubiquitous learning. The typical ubiquitous learning involving the Context Aware Intelligent system was presented. Also the Architecture for learning environment including the key idea and technical concept is being presented in this paper. Guided with these principles and with the advancement of information and communication technology the context-awareness based on Artificial intelligence for Location based Service for ubiquitous Learning was conceptualized. U-learning for Location Based Service is presented here and the concept behind this new learning paradigm. The learning environment architecture which comprises the entire component is illustrated here.

• Journal of Digital Contents Society
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• v.12 no.2
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• pp.217-223
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• 2011

AI(Artificial Intelligence) refers to the area of computer engineering and IT technology that focuses on the methodology and creation of intelligent agents. The Othello game is often produced with AI, since it is played with relatively simple rules on a board and on a limited space of 8 rows and 8 columns. Previous algorithms take longer time than desirable and often fail to face new circumstances, as they search for all the possible cases and rules. In order to solve this crucial weakness, we propose that a CBR algorithm be applied to Orthello. Case-Based Reasoning(CBR), is the process of solving new problems based on the solutions of the past similar problems. We can apply this process to Othello and expedite the process of computer reasoning for a solution to new cases based on the data from accumulated past cases. Then, these new solutions are dynamically added to the set of past cases so that it becomes harder for players(users) to be able to read the pattern. The proposed system in which a CBR algorithm is applied to the Othello game makes the computation process faster and the game harder to play.

• Journal of the Korea Convergence Society
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• v.8 no.2
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• pp.35-42
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• 2017

The purpose of the present study was to explore the features of Emotional Intelligence(EI) in psychiatric patients in terms of the ability model. EI scores of patients, measured by performance-based test and self-report inventory, was compared. The scores of performance-based test(Emotional Literacy Test) and self-report inventory(Trait Meta-Mmood Scale) of patients(30 with psychotic symptoms, 32 without psychotic symptoms) who had a appropriate literacy were analyzed by means of independent t-test. There was a no significant difference of IQ between two groups. Our results indicated that psychotic group had significantly lower EI in performance-based test than non-psychotic group. In contrast, non-psychotic group showed lower EI in self-report inventory than psychotic group. This inconsistent results might be attributable to the differences in method of measurement. Thus, these results suggested that it may be important to adopt a convergent using of both performance-based test and self-report inventory while assessing EI of patients with psychopathology.

• Journal of the Korea Society of Computer and Information
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• v.28 no.1
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• pp.39-47
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• 2023

In this paper, we propose a method to measure the similarity between golf swings in videos. As it is known that deep learning-based artificial intelligence technology is effective in the field of computer vision, attempts to utilize artificial intelligence in video-based sports data analysis are increasing. In this study, the joint coordinates of a person in a golf swing video were obtained using a deep learning-based pose estimation model, and based on this, the similarity of each swing segment was measured. For the evaluation of the proposed method, driver swing videos from the GolfDB dataset were used. As a result of measuring swing similarity by pairing swing videos of a total of 36 players, 26 players evaluated that their other swing sequence was the most similar, and the average ranking of similarity was confirmed to be about 5th. This ensured that the similarity could be measured in detail even when the motion was performed similarly.

• Journal of the Korean Society of Radiology
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• v.85 no.4
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• pp.693-704
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• 2024

Artificial intelligence (AI) technology is actively being applied for the interpretation of medical imaging, such as chest X-rays. AI-based software medical devices, which automatically detect various types of abnormal findings in chest X-ray images to assist physicians in their interpretation, are actively being commercialized and clinically implemented in Korea. Several important issues need to be considered for AI-based detection assistant tools to be applied in clinical practice: the evaluation of performance and efficacy prior to implementation; the determination of the target application, range, and method of delivering results; and monitoring after implementation and legal liability issues. Appropriate decision making regarding these devices based on the situation in each institution is necessary. Radiologists must be engaged as medical assessment experts using the software for these devices as well as in medical image interpretation to ensure the safe and efficient implementation and operation of AI-based detection assistant tools.

• The Mathematical Education
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• v.47 no.4
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• pp.405-419
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• 2008

The purpose of this study is to find oui the effects of teaching mathematical concepts by designing and applying teaching and learning programs that takes into consideration the students' strong intelligence, through the teaching and learning strategies based on the multiple intelligences theory. For this study, developmental and experimental research was conducted. In the developmental research part of the study, teaching and learning programs for teaching the concept of multiplication were designed and the activities based on the multiple intelligences were chosen. On the other hand, in the experimental research part, the data acquired from the application of nonequivalent control group pretest-posttest design in the actual classes was processed and analyzed. The results above indicate that the teaching and learning program based on the multiple intelligences theory improved the students' overall understanding of mathematical concepts by providing various types of activities. In addition, this program helped students to increase their confidence and generate a positive attitude towards learning math.

• Journal of Information Processing Systems
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• v.15 no.4
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• pp.717-723
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• 2019

Smart systems and services aim to facilitate growing urban populations and their prospects of virtual-real social behaviors, gig economies, factory automation, knowledge-based workforce, integrated societies, modern living, among many more. To satisfy these objectives, smart systems and services must comprises of a complex set of features such as security, ease of use and user friendliness, manageability, scalability, adaptivity, intelligent behavior, and personalization. Recently, artificial intelligence (AI) is realized as a data-driven technology to provide an efficient knowledge representation, semantic modeling, and can support a cognitive behavior aspect of the system. In this paper, an integration of AI with the smart systems and services is presented to mitigate the existing challenges. Several novel researches work in terms of frameworks, architectures, paradigms, and algorithms are discussed to provide possible solutions against the existing challenges in the AI-based smart systems and services. Such novel research works involve efficient shape image retrieval, speech signal processing, dynamic thermal rating, advanced persistent threat tactics, user authentication, and so on.