• Journal of Information Technology Services
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• v.16 no.4
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• pp.137-148
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• 2017

Researches on the Artificial Intelligence has been explosively activated in various fields since the advent of AlphaGo. Particularly, researchers on the application of multi-layer neural network such as deep learning, and various machine learning algorithms are being focused actively. In this paper, we described a development of an artificial intelligence Janggi game based on reinforcement learning algorithm and MCTS (Monte Carlo Tree Search) algorithm with accumulated game data. The previous artificial intelligence games are mostly developed based on mini-max algorithm, which depends only on the results of the tree search algorithms. They cannot use of the real data from the games experts, nor cannot enhance the performance by learning. In this paper, we suggest our approach to overcome those limitations as follows. First, we collects Janggi expert's game data, which can reflect abundant real game results. Second, we create a graph structure by using the game data, which can remove redundant movement. And third, we apply the reinforcement learning algorithm and MCTS algorithm to select the best next move. In addition, the learned graph is stored by object serialization method to provide continuity of the game. The experiment of this study is done with two different types as follows. First, our system is confronted with other AI based system that is currently being served on the internet. Second, our system confronted with some Janggi experts who have winning records of more than 50%. Experimental results show that the rate of our system is significantly higher.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.2-5
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• 2022

With the advent of deep learning and the rapid development of ICT (Information and Communication Technology), research using artificial intelligence is being actively conducted in various fields of society such as politics, economy, and culture and so on. Deep learning-based artificial intelligence technology is subdivided into various domains such as natural language processing, image processing, speech processing, and recommendation system. In particular, as the industry is advanced, the need for a recommendation system that analyzes market trends and individual characteristics and recommends them to consumers is increasingly required. In line with these technological developments, this paper extracts and classifies attribute information from structured or unstructured text and image big data through deep learning-based technology development of 'language processing intelligence' and 'image processing intelligence', and We propose an artificial intelligence-based 'customized fashion advisor' service integration system that analyzes trends and new materials, discovers 'market-consumer' insights through consumer taste analysis, and can recommend style, virtual fitting, and design support.

• Journal of the Korea Convergence Society
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• v.9 no.7
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• pp.163-175
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• 2018

The age of the $4^{th}$ Industrial revolution characterized with artificial intelligence leads to increased interest in emotional aspects representing humanity as counterpart competence to the digital literacy, As the educational model to foster emotional intelligence, noticed is 'maker education based on design thinking process,' since it cultivates the spirits of empathy, intuitive thinking, collaboration, communication, sharing, and openness. In this context, this study aimed to examine relationship between the educational model and emotional intelligence. For this purpose, a case study has been conducted with 37 undergraduate students in an University general education class, and the results of data collection and analysis confirmed positive influences of the program in enhancing most components of the emotional intelligence.

• Journal of the Korea Convergence Society
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• v.11 no.7
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• pp.239-249
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• 2020

The purpose of this study was to verify whether the endorser effect similar to humans can be created in advertising campaigns based on the artificial intelligence endorser. In particular, considering the characteristics of artificial intelligence, a research model was presented by convergence of consumer innovativeness and anthropomorphism. The results of the online survey of 244 respondents showed that expertise of the artificial intelligence endorser has a positive effect on both brand attitude and purchase intention, but not for trustworthiness while it has a positive effect on brand attitude. Also, the effect of consumer innovativeness and anthropomorphism on brand attitude and purchase intention for artificial intelligence was found. The endorser effect was expanded to artificial intelligence, which is an intangible object, and the existing theory and research results were combined to re-verify it. Theoretical and practical implications for artificial intelligence-based products and services were presented.

• Journal of Internet Computing and Services
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• v.20 no.6
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• pp.167-177
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• 2019

The enhancement of national competitiveness in future society is the discovery and training of excellent SW convergence gifted. In order to cultivate these SW convergence gifted, reinforcing competence of teachers in charge should be made first. Therefore, in this paper, artificial intelligence education contents, one of the core technologies of the 4th Industrial Revolution era, were developed to reinforcing competence of SW convergence gifted teachers. After setting the direction of artificial intelligence education content, we constructed educational content suitable for secondary SW convergence gifted education, and designed and developed it in detail. The composition of artificial intelligence education content consists of machine learning and tensor flow understanding, linear regression machine learning implementation for numerical prediction, and multiple linear regression-based price prediction machine learning implementations. The developed educational contents were verified by experts with qualitative aspects. In the future, we expect that the educational content of artificial intelligence proposed in this paper will be useful for strengthening the ability of SW convergence gifted teachers.

• Journal of the Korea Convergence Society
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• v.10 no.6
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• pp.33-39
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• 2019

As cyber attack methods are becoming more intelligent, incidents such as security breaches and international crimes are increasing. In order to predict and respond to these cyber attacks, the characteristics, methods, and types of attack techniques should be identified. To this end, many security companies are publishing security intelligence reports to quickly identify various attack patterns and prevent further damage. However, the reports that each company distributes are not structured, yet, the number of published intelligence reports are ever-increasing. In this paper, we propose a method to extract structured data from unstructured security intelligence reports. We also propose an automatic intelligence report analysis system that divides a large volume of reports into sub-groups based on their topics, making the report analysis process more effective and efficient.

• Journal of Information Technology Applications and Management
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• v.21 no.3
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• pp.65-77
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• 2014

Ubiquitous learning has aroused great interest and is becoming a new way for foreign language education in today's society. However, how to increase the learners' initiative and their community cohesion is still an issue that deserves more profound research and studies. Emotional intelligence can help to detect the learner's emotional reactions online, and therefore stimulate his interest and the willingness to participate by adjusting teaching skills and creating fun experiences in learning. This is, actually the new concept of smart education. Based on the previous research, this paper concluded a neural mechanism model for analyzing the learners' emotional characteristics in ubiquitous environment, and discussed the intelligent monitoring and automatic recognition of emotions from the learners' speech signals as well as their behavior data by multi-agent system. Finally, a framework of emotional intelligence system was proposed concerning the smart foreign language education in ubiquitous learning.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.528-529
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• 2023

Due to vast points and irregular structure, labeling full points in large-scale point clouds is highly tedious and time-consuming. To resolve this issue, we propose a novel point-based transformer network in weakly-supervised semantic segmentation, which only needs 0.1% point annotations. Our network introduces general local features, representing global factors from different neighborhoods based on their order positions. Then, we share query point weights to local features through point attention to reinforce impacts, which are essential in determining sparse point labels. Geometric encoding is introduced to balance query point impact and remind point position during training. As a result, one point in specific local areas can obtain global features from corresponding ones in other neighborhoods and reinforce from its query points. Experimental results on benchmark large-scale point clouds demonstrate our proposed network's state-of-the-art performance.

• Journal of Convergence for Information Technology
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• v.10 no.1
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• pp.120-127
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• 2020

The purpose of this study was to examine related variables that improve learning outcomes in collaborative learning. Based on literature reviews, emotional intelligence was used as a variable of personal character, communication ability and collective intelligence were used as variables in learning process, and learning satisfaction, and persistence were used as variables of learning outcomes. Data were collected from 3,475 students at A university, and were analyzed using structural equation modeling. The results of this study are as follows: First, it turned out that emotional intelligence had a significant and positive impact on communication ability, collective intelligence, learning satisfaction, and persistence. Second, communication ability influenced collective intelligence and persistence positively. Third, collective intelligence influenced learning satisfaction and persistence positively. Fourth, learning satisfaction had a significant and positive impact on persistence. These findings offer basic data for collaborative learning by revealing the structural relationships among related variables that improve learning outcomes in collaborative learning of college students.

• Journal of Korean Academy of Nursing
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• v.54 no.3
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• pp.459-474
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• 2024

Purpose: The purpose of this study was to conduct a concept analysis of social intelligence in nurses so that applying social intelligence to the nursing field. Methods: In this study, we followed the hybrid model procedure, involving the following steps: First, in the theoretical stage, the attributes and definitions of the concept of social intelligence were determined through literature review. Second, the concepts' reality was confirmed during fieldwork. In the final analysis stage, the results confirmed in the theoretical and fieldwork stages were compared and analyzed to confirm the properties and definition of the concept. Results: Nurses' social intelligence consists of three dimensions: social cognitive nursing competency, human-centered social evolution, and skills for solving complex nursing situations. Nurses' social intelligence is a professional nursing competency that flexibly coordinates complex nursing situations, developed through accumulating experiences of continuous reflection and relationship expansion based on receptive listening and social sensitivity in clinical interpersonal relationships. Conclusion: Nurses' social intelligence is widely used in clinical practice and is shown to have a significant direct and indirect impact on clinical nursing. To effectively apply social intelligence in the clinical context, individual and organizational efforts are required to share and transfer knowledge and capacity-building methods through collective intelligence and education.