• Journal of the Korea Society of Computer and Information
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• v.25 no.1
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• pp.55-61
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• 2020

With the development of deep learning technology and advances in computing power, video-based research is now gaining more and more attention. Video data contains a large amount of temporal and spatial information, which is the biggest difference compared with image data. It has a larger amount of data. It has attracted intense attention in computer vision. Among them, motion recognition is one of the research focuses. However, the action recognition of human in the video is extremely complex and challenging subject. Based on many research in human beings, we have found that artificial intelligence-like attention mechanisms are an efficient model for cognition. This efficient model is ideal for processing image information and complex continuous video information. We introduce this attention mechanism into video action recognition, paying attention to human actions in video and effectively improving recognition efficiency. In this paper, we propose a new 3D residual attention network using convolutional neural network based on two attention models to identify human action behavior in the video. An evaluation result of our model showed up to 90.7% accuracy.

• Journal of Information Processing Systems
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• v.20 no.2
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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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.5
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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.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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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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• v.7 no.1
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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.

• Journal of Fisheries and Marine Sciences Education
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• v.25 no.1
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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.

• Journal of Korea Society of Digital Industry and Information Management
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• v.17 no.1
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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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.6
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• pp.2895-2921
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• 2018

Security has become one of the major concerns in mobile adhoc networks (MANETs). Data and voice communication amongst roaming battlefield entities (such as platoon of soldiers, inter-battlefield tanks and military aircrafts) served by MANETs throw several challenges. It requires complex securing strategy to address threats such as unauthorized network access, man in the middle attacks, denial of service etc., to provide highly reliable communication amongst the nodes. Intrusion Detection and Prevention System (IDPS) undoubtedly is a crucial ingredient to address these threats. IDPS in MANET is managed by Command Control Communication and Intelligence (C3I) system. It consists of networked computers in the tactical battle area that facilitates comprehensive situation awareness by the commanders for timely and optimum decision-making. Key issue in such IDPS mechanism is lack of Smart Learning Engine. We propose a novel behavioral based "Smart Multi-Instance Multi-Label Intrusion Detection and Prevention System (MIML-IDPS)" that follows a distributed and centralized architecture to support a Robust C3I System. This protocol is deployed in a virtually clustered non-uniform network topology with dynamic election of several virtual head nodes acting as a client Intrusion Detection agent connected to a centralized server IDPS located at Command and Control Center. Distributed virtual client nodes serve as the intelligent decision processing unit and centralized IDPS server act as a Smart MIML decision making unit. Simulation and experimental analysis shows the proposed protocol exhibits computational intelligence with counter attacks, efficient memory utilization, classification accuracy and decision convergence in securing C3I System in a Tactical Battlefield environment.

• Journal of Information Technology Application
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• v.1
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• pp.173-211
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• 1999

The task of classification permeates all walks of life, from business and economics to science and public policy. In this context, nonlinear techniques from artificial intelligence have often proven to be more effective than the methods of classical statistics. The objective of knowledge discovery and data mining is to support decision making through the effective use of information. The automated approach to knowledge discovery is especially useful when dealing with large data sets or complex relationships. For many applications, automated software may find subtle patterns which escape the notice of manual analysis, or whose complexity exceeds the cognitive capabilities of humans. This paper explores the utility of a collaborative learning approach involving integrated models in the preprocessing and postprocessing stages. For instance, a genetic algorithm effects feature-weight optimization in a preprocessing module. Moreover, an inductive tree, artificial neural network (ANN), and k-nearest neighbor (kNN) techniques serve as postprocessing modules. More specifically, the postprocessors act as second0order classifiers which determine the best first-order classifier on a case-by-case basis. In addition to the second-order models, a voting scheme is investigated as a simple, but efficient, postprocessing model. The first-order models consist of statistical and machine learning models such as logistic regression (logit), multivariate discriminant analysis (MDA), ANN, and kNN. The genetic algorithm, inductive decision tree, and voting scheme act as kernel modules for collaborative learning. These ideas are explored against the background of a practical application relating to financial fraud management which exemplifies a binary classification problem.

• Journal of Intelligence and Information Systems
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• v.9 no.2
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• pp.155-169
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• 2003

A multi-agent technology has emerged as new paradigms that can flexibly and promptly cope with various environmental changes and complex problems. Accordingly, many studies have been carried out to establish multi-agent systems in an effort to solve dynamic problems in many fields. However, most previous research on the multi-agent frameworks aimed at, on the behalf of a user, exchanging and sharing information among agents, reusing agents, and suggesting job cooperation in order to integrate and assimilate heterogeneous agents. That is, their frameworks mainly focused on the basic functions of general multi-agents. Therefore, they are not suitable to the development of the proper system for a specific field such as a negotiation. The goal of this research is to design a multi-agent framework for the negotiation system that supports the evaluation of the negotiation messages, management of the negotiation messages, and message exchanges among the negotiation agents.