• Journal of Korea Game Society
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• v.2 no.2
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• pp.37-45
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• 2002

Computer games could be regarded as simulation of the real world. Control problems of software agents have long been studied in the field of Artificial Intelligence (AI), resulting in giving a birth to the behavior-based approach. three main approaches might be categorized out of the history of AI study. First, Cognitivists propose that intelligence could be represented and manipulated in terms of symbols. Second, Connectionists claim that symbols could not be isolated but they are embedded in the body structure. Third, the behavior-based approach is an approach to AI which suggests that intelligence is dynamic property that exists nowhere but emerges in the relationship of an agent and the world including observers while the agent performs behavior. This paper explains and compares the three approaches to AI, then discusses the plausibility of the behavior-based approach and problems. Finally, this paper proposes application of behavior-based approach to computer games in terms of agent control.

• Journal of the Korea Society of Computer and Information
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• v.28 no.1
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• pp.189-199
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• 2023

This study aimed to identify the development direction of Arduino-based boards relating to artificial intelligence based on social awareness identified using big data analytical methods. For the purpose, big data were extracted through the Textom website, focusing on keywords that included 'Arduino + artificial intelligence' and 'Arduino + AI', and these data were refined and analyzed using the Textom website and the UNICET program. In this study, big data analyses, including frequency analysis, TF-IDF analysis, Degree Centrality analysis, N-gram analysis, and CONCOR analysis, were performed. The analyses' results confirmed that keywords relating to education and coding education, keywords relating to making and experience based on Arduino, and keywords relating to programs were the main keywords used in Arduino- and artificial intelligence-related Internet documents, and clusters were formed based on these keywords confirmed. The social awareness of Arduino and artificial intelligence was evaluated, and the direction of board development was identified based on this social awareness. This study is meaningful in that it identified various factors of board development based on the general public's social awareness, which was evaluated using a big data analysis method. This study may serve as a point of reference for future researchers or developers wishing to understand user needs using big data analysis methods.

• Journal of Internet Computing and Services
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• v.13 no.2
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• pp.109-118
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• 2012

This paper theoretically derives an algorithm to discover a new type of workflow-based knowledge from workflow models, which is termed workflow-based affiliation network knowledge. In general, workflow intelligence (or business process intelligence) technology consists of four types of techniques that discover, analyze, monitor and control, and predict a series of workflow-based knowledge from workflow models and their execution histories. So, this paper proposes a knowledge discovery algorithm which is able to discover workflow-based affiliation networks that represent the association and participation relationships between activities and performers defined in ICN-based workflow models. In order particularly to prove the correctness and feasibility of the proposed algorithm, this paper tries to apply the algorithm to a specific workflow model and to show that it is able to derive its corresponding workflow-based affiliation network knowledge.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.203-214
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• 2024

This study seeks to provide implications for domestic-related policies through exploratory analysis research to support AI-based policy decision-making. The following should be considered when establishing an AI-based decision-making model in Korea. First, we need to understand the impact that the use of AI will have on policy and the service sector. The positive and negative impacts of AI use need to be better understood, guided by a public value perspective, and take into account the existence of different levels of governance and interests across public policy and service sectors. Second, reliability is essential for implementing innovative AI systems. In most organizations today, comprehensive AI model frameworks to enable and operationalize trust, accountability, and transparency are often insufficient or absent, with limited access to effective guidance, key practices, or government regulations. Third, the AI system is accountable. The OECD AI Principles set out five value-based principles for responsible management of trustworthy AI: inclusive growth, sustainable development and wellbeing, human-centered values and fairness values and fairness, transparency and explainability, robustness, security and safety, and accountability. Based on this, we need to build an AI-based decision-making system in Korea, and efforts should be made to build a system that can support policies by reflecting this. The limiting factor of this study is that it is an exploratory study of existing research data, and we would like to suggest future research plans by collecting opinions from experts in related fields. The expected effect of this study is analytical research on artificial intelligence-based decision-making systems, which will contribute to policy establishment and research in related fields.

• Journal of Korean society of Dental Hygiene
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• v.18 no.3
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• pp.385-397
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• 2018

Objectives: The study was a cross-sectional research to examine dental hygiene students' multi-cultural experiences, emotional intelligence and cultural competency and to understand the correlations among them. Methods: The study was conducted from September $1^{st}$ to October $31^{st}$ 2016, based on the survey of 449 students in the department of dental hygiene at 7 Universities. The questionnaire consisted of 57 questions including general characteristics (n=7), multi-cultural experiences (n=7), emotional intelligence (n=16) and cultural competency (n=27). Results: Each score of students' emotional intelligence and cultural competency is 3.43 and 3.01 respectively in 5-point scale. An analysis of correlations between emotional intelligence and cultural competency shows that the higher the emotional intelligence, the higher the cultural competency (r=0.342). The factors affecting the cultural competency include use of emotions (${\beta}=0.327$, p<0.001), control of emotions (${\beta}=0.254$, p=0.001), frequency of multi-cultural media (${\beta}=0.221$, p<0.001) and experience of multi-cultural class (${\beta}=0.221$, p=0.002). The modified explanatory power in this model is 28.2% (F=10.856, p<0.001). Conclusions: There was a positive correlation between emotional intelligence and cultural competency, and the contacts with multi-culture and experience of class are identified as the affecting factors. Dental hygiene students should acquire theoretical experiences regarding the multi-culture through curriculum or continuous educations and it is necessary to promote such educations in order to develop and apply the programs for the enhancement of emotional intelligence.

• Journal of Digital Convergence
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• v.19 no.3
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• pp.81-88
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• 2021

Modern society is exposed to various types of crises. In particular, since the September 11 attacks, each country has been increasingly responsible for managing non-military crises. Therefore, the purpose of this study is to consider ways to utilize artificial intelligence(AI) for national crisis management in the era of the fourth industrial revolution. To this end, we analyzed the effectiveness of artificial intelligence(AI) operated and under research and development(R&D) to support human decision-making and examined the possibility of using artificial intelligence(AI) to national crisis management. As a result of the study, artificial intelligence(AI) provides objective judgment of the data-based situation and optimal countermeasures to policymakers, enabling them to make decisions in urgent crisis situations, indicating that it is efficient to use artificial intelligence(AI) for national crisis. These findings suggest the possibility of using artificial intelligence(AI) to respond quickly and efficiently to the national crisis.

• Journal of Korea Multimedia Society
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• v.20 no.2
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• pp.279-288
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• 2017

Nowadays, nations cyber security capabilities play an important role in a nation's defense. Security-critical infrastructures such as national defenses, public services, and financial services are now exposed to Advanced Persistent Threats (APT) and their resistance to such attacks effects the nations stability. Currently Cyber Threat Intelligence (CTI) is widely used by organizations to mitigate and deter APT for its ability to proactively protect their assets by using evidence-based knowledge. The evidence-based knowledge information can be exchanged among organizations and used by the receiving party to strengthen their cyber security management. This paper will discuss on the business process reengineering of the CTI information exchange management for a nationwide scaled control and governance by the government to better protect their national information security assets.

• Proceedings of the Korean Society for Language and Information Conference
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• 2007.11a
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• pp.481-488
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• 2007

In this paper, we propose a method to classify movie review documents into positive or negative opinions. There are several approaches to classify documents. The previous studies, however, used only a single classifier for the classification task. We describe a multiple classifier for the review document classification task. The method consists of three classifiers based on SVMs, ME and score calculation. We apply two voting methods and SVMs to the integration process of single classifiers. The integrated methods improved the accuracy as compared with the three single classifiers. The experimental results show the effectiveness of our method.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.818-821
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• 2020

The artificial intelligence software market is developing in various fields world widely. In particular, there is a wide variety of applications for image recognition technology using deep learning. This study intends to apply image recognition technology to the 'Home Gardening' market growing rapidly due to COVID-19, and aims to build a small-scale smart farm in the house using artificial intelligence and IoT technology for convenient crop cultivation for busy people living in cities. This intelligent farm system includes an automatic image recognition function and recommendation function based on temperature and humidity sensor-based indoor environment analysis.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.262-264
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• 2023

Internet of Things (IoT) networks currently employ an increased number of users and applications, raising their susceptibility to cyberattacks and data breaches, and endangering our security and privacy. Intrusion detection, which includes monitoring and analyzing incoming and outgoing traffic to detect and prohibit the hostile activity, is critical to ensure cybersecurity. Conventional intrusion detection systems (IDS) are centralized, making them susceptible to cyberattacks and other relevant privacy issues because all the data is gathered and processed inside a single entity. This research aims to create a blockchain-based architecture to support federated learning and improve cybersecurity and intrusion detection in IoT networks. In order to assess the effectiveness of the suggested approach, we have utilized well-known cybersecurity datasets along with centralized and federated machine learning models.