• International Journal of Contents
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• v.12 no.1
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• pp.25-43
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• 2016

An agent-centric event planning method is proposed for providing pedagogical experiences in an immersed environment. Two-level planning is required at in a macro-level (i.e., inter-event level) and an intra-event level to provide realistic experiences with the objective of learning declarative knowledge. The inter-event (horizontal) planning is based on search, while intra-event (vertical) planning is based on hierarchical decomposition. The horizontal search is dictated by several realistic types of association between events besides the conventional causality. The resulting schematic plan is further augmented by conditions associated with those agents cast into the roles of the events identified in the plan. Rather than following a main story plot, all the events potentially relevant to accomplishing an initial goal are derived in the final result of our planning. These derived events may progress concurrently or digress toward a new main goal replacing the current goal or event, and the plan could be merged or fragmented according to their respective lead agents' intentions and other conditions. The macro-level coherence across interconnected events is established via their common background world existing a priori. As the pivotal source of event concurrency and intricacy, agents are modeled to not only be autonomous but also independent, i.e., entities with their own beliefs and goals (and subsequent plans) in their respective parts of the world. Additional problems our method addresses for augmenting pedagogical experiences include casting of agents into roles based on their availability, subcontracting of subsidiary events, and failure of multi-agent event entailing fragmentation of a plan. The described planning method was demonstrated by monitoring implementation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.521-524
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• 2009

Everyone can easily acquire learning materials on web environment that rapidly develops. Because the importance of English education has been emphasized day by day, many English education systems are introduced. However, previous most English education systems support only single user mode, and cannot deal with a newly coined word such as 'WIKIPEDIA'. In order to lead a user's learning ability with interest and enjoyment, this paper propose an online English word game system implementing a 'scrabble' board game. The proposed English word game system has the following characteristics. First, the proposed system supports both single user mode and multi user mode with a virtual user based on artificial intelligence. Second, the proposed system can recognize newly coined words such as 'WIKIPEDIA' by using NEVER Open API dictionary. Third, the proposed system offers familiar user interface so that a user can play the game without any manual. Therefore, it is expected that the proposed system can help users to learn English words with interest and enjoyment.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.262-269
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• 2020

Recently, many attempts have been made to reduce the time required for payment in various shopping environments. In addition, for the Fourth Industrial Revolution era, artificial intelligence is advancing, and Internet of Things (IoT) devices are becoming more compact and cheaper. So, by integrating these two technologies, access to building an unmanned environment to save people time has become easier. In this paper, we propose a smart shopping cart system based on low-cost IoT equipment and deep-learning object-detection technology. The proposed smart cart system consists of a camera for real-time product detection, an ultrasonic sensor that acts as a trigger, a weight sensor to determine whether a product is put into or taken out of the shopping cart, an application for smartphones that provides a user interface for a virtual shopping cart, and a deep learning server where learned product data are stored. Communication between each module is through Transmission Control Protocol/Internet Protocol, a Hypertext Transmission Protocol network, a You Only Look Once darknet library, and an object detection system used by the server to recognize products. The user can check a list of items put into the smart cart via the smartphone app, and can automatically pay for them. The smart cart system proposed in this paper can be applied to unmanned stores with high cost-effectiveness.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.2
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• pp.48-55
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• 2022

The color image of the brand comes first and is an important visual element that leads consumers to the consumption of the product. To express more effectively what the brand wants to convey through design, the printing market is striving to print accurate colors that match the intention. In 'offset printing' mainly used in printing, colors are often printed in CMYK (Cyan, Magenta, Yellow, Key) colors. However, it is possible to print more accurate colors by making ink of the desired color instead of dotting CMYK colors. The resulting ink is called 'spot color' ink. Spot color ink is manufactured by repeating the process of mixing the existing inks. In this repetition of trial and error, the manufacturing cost of ink increases, resulting in economic loss, and environmental pollution is caused by wasted inks. In this study, a deep learning algorithm to predict printed spot colors was designed to solve this problem. The algorithm uses a single DNN (Deep Neural Network) model to predict printed spot colors based on the information of the paper and the proportions of inks to mix. More than 8,000 spot color ink data were used for learning, and all color was quantified by dividing the visible light wavelength range into 31 sections and the reflectance for each section. The proposed algorithm predicted more than 80% of spot color inks as very similar colors. The average value of the calculated difference between the actual color and the predicted color through 'Delta E' provided by CIE is 5.29. It is known that when Delta E is less than 10, it is difficult to distinguish the difference in printed color with the naked eye. The algorithm of this study has a more accurate prediction ability than previous studies, and it can be added flexibly even when new inks are added. This can be usefully used in real industrial sites, and it will reduce the attempts of the operator by checking the color of ink in a virtual environment. This will reduce the manufacturing cost of spot color inks and lead to improved working conditions for workers. In addition, it is expected to contribute to solving the environmental pollution problem by reducing unnecessarily wasted ink.

• Journal of Digital Contents Society
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• v.18 no.3
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• pp.607-612
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• 2017

The use of RaspberryPi in building an embedded system may be difficult for users in understanding the circuit and the hardware cost. This paper proposes a solution that can test the systems virtually. The solution consists of three elements; (i) editor, (ii) interpreter and (iii) simulator and provides nine full modules and also allows the users to configure/run/test their own circuits like real environment. The task of abstraction for modules through the actual circuit test was carried out on the basis of the data sheet and the specification provided by the manufacturer. If we can improve the level of quality of our solution, it can be useful in terms of cost reduction and easy learning. To achieve this end, the electrical physics engine, the level of interpreter that can be ported to the actual board, and a generalization of the simulation logic are required.

• The KIPS Transactions:PartB
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• v.15B no.5
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• pp.421-434
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• 2008

As computer graphics, virtual reality and augmented reality technologies have been developed, in many application areas based on those techniques, interaction for 3D space is required such as selection and manipulation of an 3D object. In this paper, we propose a framework for a vision-based 3D interaction which enables to simulate functions of an expensive 3D mouse for a desktop environment. The proposed framework includes a specially manufactured interaction device using three-color LEDs. By recognizing position and color of the LED from video sequences, various events of the mouse and 6 DOF interactions are supported. Since the proposed device is more intuitive and easier than an existing 3D mouse which is expensive and requires skilled manipulation, it can be used without additional learning or training. In this paper, we explain methods for making a pointing device using three-color LEDs which is one of the components of the proposed framework, calculating 3D position and orientation of the pointer and analyzing color of the LED from video sequences. We verify accuracy and usefulness of the proposed device by showing a measurement result of an error of the 3D position and orientation.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.2
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• pp.194-205
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• 2006

The purpose of this study is to develop a pedestrian multi-agent model and simulation system using multi-agent theory, which may be utilized as a planning support system for building a comfort and safe environment of pedestrian street. Differing from existing pedestrian models, however, every single pedestrian was regarded as an individual agent in the model. Multiple agents like multiple pedestrians in the street then maintain their own characteristics and respond to surrounding environment. In addition their moving behavior are made by their own decision rules that they have or had acquired through the interactive communications or learning between agents like real world. After verifying the model validation, as the $R^2$ between the predicted value and observed value was up to 0.781, the developed model was applied to Gazwa district within Gyeongsang university village. The simulation system was developed by Flash MX action scripts and the physical environment of the streets was configured with the digital map and ArcGis within computer virtual space. The attribute data of buildings such as type and size of commercial business were collected through the field survey and combined with physical features. Then the effect of the variation of building attractiveness and the occurrence of street events to pedestrian environment were simulated. Through the experiments this study could make suggestions to improve pedestrian environment.

• Journal of the Korea Society of Computer and Information
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• v.24 no.11
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• pp.61-69
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• 2019

In this paper, we propose a multisensory(i.e., visual-auditory-tactile) based AR system for the education of cultural heritage. The proposed system provides a multisensory interaction by designing a user to experience with a 3D printed artifact which is mapped by a virtual 3D content of digital heritage. Compared with the existing systems of cultural heritage education based on augmented reality(AR) technology, this system focused on not only providing learning experience via a sense of visual and auditory, but also a sense of tactile. Furthermore, since this systems mainly provided the direct interactions using a 3D printed model, it gives a higher degree of realism than existing system that use touch or click motions on a 2D display of mobile phones and tablets. According to a result of user testing, we concluded that the proposed system delivered the excellent presence and learning flow to users. Particularly, from the usability evaluation, a 3D printed target artifact which is similar in shape to original heritage artifact, achieved the highest scores among the various tested targets.

• Journal of The Korean Association of Information Education
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• v.26 no.3
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• pp.187-195
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• 2022

Recently, with interest in metaverse, attempts are being made to utilize the metaverse platform in various forms. In this paper, we focused on the educational application potential of metaverse, and developed and applied a metaverse STEAM program to provide an effective learning experience to learners in non-face-to-face educational situations. The developed program utilizes Minecraft and ZEPETO, familiar to students, as metaverse learning platforms, and consists of a total of 16 lessons of 5 modules in the form of modules so that alternative classes can take place in the educational field. Through this, the learner's change in STEAM attitude and learning satisfaction were measured, and through the developed STEAM program, the learner's interest, consideration, communication, usefulness, self-concept, self-efficacy, and career choice areas significantly increased. In addition, positive results were confirmed in all areas of the learner satisfaction test related to satisfaction, interest, and overall class. In the future, considering the characteristics of the metaverse, it is necessary to break free from the constraints of time and space to communicate anew, and various learner-centered educational approaches based on a high degree of freedom and immersion should be implemented.

• KNOM Review
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• v.23 no.2
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• pp.18-28
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• 2020

With the development of the virtual community, the benefits that IT technology provides to people in fields such as healthcare, industry, communication, and culture are increasing, and the quality of life is also improving. Accordingly, there are various malicious attacks targeting the developed network environment. Firewalls and intrusion detection systems exist to detect these attacks in advance, but there is a limit to detecting malicious attacks that are evolving day by day. In order to solve this problem, intrusion detection research using machine learning is being actively conducted, but false positives and false negatives are occurring due to imbalance of the learning dataset. In this paper, a Random Oversampling method is used to solve the unbalance problem of the UNSW-NB15 dataset used for network intrusion detection. And through experiments, we compared and analyzed the accuracy, precision, recall, F1-score, training and prediction time, and hardware resource consumption of the models. Based on this study using the Random Oversampling method, we develop a more efficient network intrusion detection model study using other methods and high-performance models that can solve the unbalanced data problem.