• 정보처리학회논문지B
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• 제15B권3호
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• pp.253-258
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• 2008

최근의 게임 플레이어들은 단순한 반복적인 조작을 벗어나 복잡한 환경 하에서 다양한 전략과 전술을 구사하여야 하는 게임을 요구하고 있다. 이러한 환경에서 게임 캐릭터를 학습시키기 위해 다양한 인공지능 기법들이 제안되었으며, 최근에는 신경망과 유전 알고리즘을 이용한 학습 방법이 연구되고 있다. 본 논문에서는 게임이론에서 널리 사용되는 추격-회피 전략의 학습을 위해 유전 프로그래밍(GP)을 사용하였다. 제안된 유전 프로그래밍은 신경망과 같은 기존의 방법에 비해 수행 속도가 빠르고, 학습의 결과를 직관적으로 이해할 수 있으며, 진화된 염색체를 추론 규칙으로 변환 가능하므로 호환성이 높다는 장점을 가지고 있다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2015년도 추계학술발표대회
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• pp.1281-1284
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• 2015

Multi-day trip itinerary planning is complex and time consuming task, from selecting a list of worth visiting POIs to arranging them into an itinerary with various constraints and requirements. In this paper, we present CYTRIP, a multi-day trip itinerary planning system that engages human computation (i.e. crowd recommendation) to collaboratively recommend POIs by providing a shared workspace. CYTRIP takes input the collective intelligence of crowd (i.e. recommended POIs) to build a multi-day trip itinerary taking into account user's preferences, various time constraints and locations. Furthermore, we explain how we engage crowd in our system. The planning problem and domain are formulated as AI planning using PDDL3. The preliminary empirical experiments show that our domain formulation is applicable to both single-day and multi-day trip planning.

• 한국컴퓨터정보학회논문지
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• 제25권1호
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• pp.55-61
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• 2020

딥 러닝 기술의 발전과 컴퓨팅 파워 등의 개선으로 인해 비디오 기반 연구는 최근 많은 관심을 얻고 있다. 비디오 데이터가 이미지 데이터와 비교하여 가장 큰 차이는 비디오 데이터에는 많은 양의 시간적, 공간적 정보가 포함되어 있다는 점이다. 이처럼 비디오에 포함된 많은 양의 데이터로 인해 컴퓨터 비전 연구에 있어서 행동 인식은 중요한 연구 과제 중 하나이지만, 비디오와 같이 움직임이 있는 환경에서 인간의 행동 인식은 매우 복잡하고 도전적인 과제이다. 인간에 대한 여러 연구를 바탕으로 인공지능에서는 인간과 유사한 주의(attention)메커니즘이 효율적인 인식 모델이라는 것을 알게 되었다. 이 효율적인 모델은 이미지 정보와 복잡한 연속 비디오 정보를 처리하는 데 이상적이다. 본 논문에서는 이러한 연구배경을 기반으로, 비디오에서 인간의 행동을 효율적으로 인식하기 위해 먼저 인간의 행동에 주목한 후 비디오 행동 인식에 주의메커니즘을 도입하고자 한다. 논문의 주요내용은 두 가지 주의 메카니즘을 기반으로 컨볼루션 신경망을 이용한 새로운 3D 잔류 주의 네트워크를 제안함으로써 비디오에서 인간의 행동을 식별하고자 한다. 제안 모델의 평가 결과 최대 90.7%정도의 정확도를 보였다.

• Journal of Information Processing Systems
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• 제20권2호
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• pp.200-214
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• 2024

Amid the flood of data, social network analysis is beneficial in searching for its hidden context and verifying several pieces of information. This can be used for detecting the spread model of infectious diseases, methods of preventing infectious diseases, mining of small groups and so forth. In addition, community detection is the most studied topic in social network analysis using graph analysis methods. The objective of this study is to examine signed attributed social networks and identify the maximal balanced cliques that are both absolute and fair. In the same vein, the purpose is to ensure fairness in complex networks, overcome the "information cocoon" bottleneck, and reduce the occurrence of "group polarization" in social networks. Meanwhile, an empirical study is presented in the experimental section, which uses the personal information of 77 employees of a research company and the trust relationships at the professional level between employees to mine some small groups with the possibility of "group polarization." Finally, the study provides suggestions for managers of the company to align and group new work teams in an organization.

• International Journal of Heart Failure
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• 제6권1호
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• pp.11-19
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• 2024

The prevalence of heart failure (HF) is increasing, necessitating accurate diagnosis and tailored treatment. The accumulation of clinical information from patients with HF generates big data, which poses challenges for traditional analytical methods. To address this, big data approaches and artificial intelligence (AI) have been developed that can effectively predict future observations and outcomes, enabling precise diagnoses and personalized treatments of patients with HF. Machine learning (ML) is a subfield of AI that allows computers to analyze data, find patterns, and make predictions without explicit instructions. ML can be supervised, unsupervised, or semi-supervised. Deep learning is a branch of ML that uses artificial neural networks with multiple layers to find complex patterns. These AI technologies have shown significant potential in various aspects of HF research, including diagnosis, outcome prediction, classification of HF phenotypes, and optimization of treatment strategies. In addition, integrating multiple data sources, such as electrocardiography, electronic health records, and imaging data, can enhance the diagnostic accuracy of AI algorithms. Currently, wearable devices and remote monitoring aided by AI enable the earlier detection of HF and improved patient care. This review focuses on the rationale behind utilizing AI in HF and explores its various applications.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권5호
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• pp.1273-1300
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• 2024

In the complex virtual environment of cyberspace, comprised of digital and communication networks, ensuring the security of information is being recognized as an ongoing challenge. The importance of 'Cyber Situation Awareness (CSA)' is being emphasized in response to this. CSA is understood as a vital capability to identify, understand, and respond to various cyber threats and is positioned at the heart of cyber security strategies from a defensive perspective. Critical industries such as finance, healthcare, manufacturing, telecommunications, transportation, and energy can be subjected to not just economic and societal losses from cyber threats but, in severe cases, national losses. Consequently, the importance of CSA is being accentuated and research activities are being vigorously undertaken. A systematic five-step approach to CSA is introduced against this backdrop, and a deep analysis of recent research trends, techniques, challenges, and future directions since 2019 is provided. The approach encompasses current situation and identification awareness, the impact of attacks and vulnerability assessment, the evolution of situations and tracking of actor behaviors, root cause and forensic analysis, and future scenarios and threat predictions. Through this survey, readers will be deepened in their understanding of the fundamental importance and practical applications of CSA, and their insights into research and applications in this field will be enhanced. This survey is expected to serve as a useful guide and reference for researchers and experts particularly interested in CSA research and applications.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2001년도 The Pacific Aisan Confrence On Intelligent Systems 2001
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• pp.50-58
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• 2001

Modern day networks are increasingly moving towards peer to peer architecture where routing tasks will not be limited to some dedicated routers, but instead all computers in a network will take part in some routing task. Since there are no specialized routers, each node performs some routing tasks and information passes from one neighbouring node to another, not in the form of dumb data, but as intelligent virtual agents or active code that performs some tasks by executing at intermediate nodes in its itinerary. The mobile agents can run, and they are free to d other tasks as the agent will take care of the routing tasks. The mobile agents because of their inherent 'intelligence'are better able to execute complex routing tasks and handle unexpected situations as compared to traditional routing techniques. In a modern day dynamic network users get connected frequently, change neighbours and disconnect at a rapid pace. There can be unexpected link failure as well. The mobile agent based routing system should be able to react to these situations in a fact and efficient manner so that information regarding change in topology propagates quickly and at the same time the network should not get burdened with traffic. We intend to build such a system.

• Journal of Multimedia Information System
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• 제7권1호
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• pp.11-16
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• 2020

Deep Learning has become the most important technology in the field of artificial intelligence machine learning, with its high performance overwhelming existing methods in various applications. In this paper, an interactive window service based on object recognition technology is proposed. The main goal is to implement an object recognition technology using this deep learning technology to remove the existing eye tracking technology, which requires users to wear eye tracking devices themselves, and to implement an eye tracking technology that uses only usual cameras to track users' eye. We design an interactive system based on efficient eye detection and pupil tracking method that can verify the user's eye movement. To estimate the view-direction of user's eye, we initialize to make the reference (origin) coordinate. Then the view direction is estimated from the extracted eye pupils from the origin coordinate. Also, we propose a blink detection technique based on the eye apply ratio (EAR). With the extracted view direction and eye action, we provide some augmented information of interest without the existing complex and expensive eye-tracking systems with various service topics and situations. For verification, the user guiding service is implemented as a proto-type model with the school map to inform the location information of the desired location or building.

• 수산해양교육연구
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• 제25권1호
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• pp.260-273
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• 2013

This study aims to reflect experts' opinions in analyzing a design thinking as foundation of multidisciplinary education. For this purpose, a delphi survey was conducted with 20 experts in three sessions from May 1 to June 25, 2012. To analyze the collected data, descriptive statistics, including frequency, percentage, the mean, and standard deviation were implemented, and internal reliability test on the survey instrument was carried out for statistical processing. The main results are as follows : First, the delphi analysis on intuitive thinking of design thinking suggested 7 items(to pursue the possibility of outside, to pursue the possibility of applying new forms of technology, content planning, facing a complex real-world phenomena etc.). Second, the delphi analysis on logical thinking of design thinking suggested 7 items(executed repeatedly, reasoning and verification, artificial intelligence, a decision support system etc.) Third, the delphi analysis on subjective thinking of design thinking suggested 9 items(user experience measuring, user satisfaction ratings, user requirements analysis, user interface design, behavioral responses of the human etc.). Fourth, the delphi analysis on objective information of design thinking suggested 8 items(information management system, simulation, production process, information exchange and sharing etc.). According to the results of the delphi analysis, design thinking can be seen as the foundation of multidisciplinary education. Suggestions were made for discussion about the main results and further researches.

• 디지털산업정보학회논문지
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• 제17권1호
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• pp.15-23
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• 2021

The 4th industrial revolution technology has brought many changes not only in human life but also in the industrial field. ICT such as 5G and artificial intelligence and convergence/complex systems such as drones and robots are convenient for humans, and automation of all processes in the industrial field. However, these advanced information and communication technologies also have adverse functions. As advanced ICT was incorporated into military and terrorist weapon systems, more powerful and highly destructive weapon systems began to be developed. In particular, by applying advanced ICT to the production and use of terrorist tools, the terrorist method became more sophisticated and caused more damage. In this paper, we derive advanced ICT that can be abused according to the terror patterns in the 4th industrial revolution era, and present a method that is applied from preparation to execution of terrorism. The abuse of advanced ICT makes terrorism more stealthy and subtle, and increases its destructive power.