• Journal of Astronomy and Space Sciences
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• v.32 no.2
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• pp.151-159
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• 2015

The fundamental conception in physics of the propagation of the electromagnetic wave polarization in matter is newly understood as the cardinal keyword in free-space quantum communication technology and cosmology in astrophysics. Interactive visualization of the propagation mechanism of polarized electromagnetism in a medium with its helicity has accordingly received attention from scientists exploiting the protocol of quantum key distribution (QKD) to guarantee unconditional security in cryptography communication. We have provided a dynamic polarization platform for presenting the polarization modes of a transverse electromagnetic wave, converting the state of polarization through the arrangement of optical elements, using Jones vectors calculations in Methematica. The platform graphically simulates the mechanism of production and propagation of the polarized waves in a medium while satisfying Maxwell's equations.

• ETRI Journal
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• v.42 no.3
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• pp.366-375
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• 2020

The network traffic prediction of a smart substation is key in strengthening its system security protection. To improve the performance of its traffic prediction, in this paper, we propose an improved gravitational search algorithm (IGSA), then introduce the IGSA into a wavelet neural network (WNN), iteratively optimize the initial connection weighting, scalability factor, and shift factor, and establish a smart substation network traffic prediction model based on the IGSA-WNN. A comparative analysis of the experimental results shows that the performance of the IGSA-WNN-based prediction model further improves the convergence velocity and prediction accuracy, and that the proposed model solves the deficiency issues of the original WNN, such as slow convergence velocity and ease of falling into a locally optimal solution; thus, it is a better smart substation network traffic prediction model.

• Korean Journal of Computational Design and Engineering
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• v.12 no.3
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• pp.171-181
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• 2007

Ubiquitous computing is a vision of our future computing lifestyle in which computer systems seamlessly integrate into our everyday lives, providing services and information in anywhere and anytime fashion. Augmented reality (AR) can naturally complement ubiquitous computing by providing an intuitive and collaborative visualization and simulation interface to a three-dimensional information space embedded within physical reality. This paper presents a service framework and its applications for providing context-aware u-car maintenance services using augmented reality, which can support a rich set of ubiquitous services and collaboration. It realizes bi-augmentation between physical and virtual spaces using augmented reality. It also offers a context processing module to acquire, interpret and disseminate context information. In particular, the context processing module considers user's preferences and security profile for providing private and customer-oriented services. The prototype system has been implemented to support 3D animation, TTS (Text-to-Speech), augmented manual, annotation, and pre- and post-augmentation services in ubiquitous car service environments.

• The Journal of Korea Robotics Society
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• v.13 no.4
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• pp.220-229
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• 2018

In the midst of disaster, such as an earthquake or a nuclear radiation exposure area, there are huge risks to send human crews. Many robotic researchers have studied to send UGVs in order to replace human crews at dangerous environments. So far, two-dimensional camera information has been widely used for teleoperation of UGVs. Recently, three-dimensional information based teleoperations are attempted to compensate the limitations of camera information based teleoperation. In this paper, the 3D map information of indoor and outdoor environments reconstructed in real-time is utilized in the UGV teleoperation. Further, we apply the LTE communication technology to endure the stability of the teleoperation even under the deteriorate environment. The proposed teleoperation system is performed at explosive disposal missions and their feasibilities could be verified through completion of that missions using the UGV with the Explosive Ordnance Disposal (EOD) team of Busan Port Security Corporation.

• Journal of the Semiconductor & Display Technology
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• v.21 no.1
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• pp.136-141
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• 2022

In this paper, we designed, implemented, and verified the SLAM system that can be used on mobile devices. Mobile SLAM is composed of a stand-alone type that directly performs SLAM operation on a mobile device, and a mapping server type that additionally configures a mapping server based on FastAPI to perform SLAM operation on the server and transmits data for map visualization to a mobile device. The mobile SLAM system proposed in this paper is to mix the two types in order to make SLAM operation and map generation more efficient. The stand-alone type SLAM system was configured as an Android app by porting the OpenVSLAM library to the Unity engine, and the map generation and performance were evaluated on desktop PCs and mobile devices. The mobile SLAM system in this paper is an open source project, so it is expected to help develop AR contents based on SLAM in a mobile environment.

• Journal of the Semiconductor & Display Technology
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• v.22 no.3
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• pp.125-129
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• 2023

In this paper, we propose a method to design and implement a smart pipeline information management system that can provide visualization information linked to GIS and roadmap based on the construction of precise pipeline buried information. The smart pipeline information management system consists of a positioning device for high-precision pipeline location measurement and surround view image data recording, a database for data storage and management, and a mobile app for remote monitoring and management. It connects surrounding image data and location data with GIS and roadmap. Convenience and accessibility of management can be improved.

• The Journal of the Korea Contents Association
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• v.18 no.9
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• pp.240-247
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• 2018

In this paper, we implement a digital content that visualizes 33 Avalokitesvara-Bodhisattva according to the wishes of the public. The 33 Avalokitesvara-Bodhisattva is described in the Avalokitesvara-Bodhisattva tale that is found in the ancient literature "Memorabilia of the Three Kingdoms" as Tangible Cultural Heritage. Also, it is easily found in a wall painting of traditional Buddhist temples. The 33 Avalokitesvara-Bodhisattva is the saint of mercy that transforms into 33 various forms according to the wishes of the public. The Avalokitesvara-Bodhisattva tales deal with differences in the types of wishes of the public, and the tales have been speeded like wildfire among the people. So, in this paper, we classify them into 4 groups by the wishes (healing, security, academic achievement, disaster relief) of the public, and then analyze its symbolism and activity of the 33 Avalokitesvara-Bodhisattva. Also, we implement a 2D digital content that represents visually it according to the wishes of the public. Applications of the implemented visual content are as follows; development of character, game, and digital storytelling associated with traditional culture, education service for Buddhist doctrines, etc.

• Journal of the Korea Society for Simulation
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• v.23 no.4
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• pp.211-218
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• 2014

The Test and Evaluation (T&E) system became more important due to its advancement and complexity of the weapon system. Time and cost saving T&E related studies are in progress mainly with advanced countries. By utilizing the Modeling and Simulation (M&S) technology recently, we may save time and money. Also, overcome security and safety limitations. There are many M&S based research activities in South Korea but it is way behind of the system that some countries already have developed. i.e.; United States. This area of study requires new way of developing strategies in the T&E system of Korea. This study is to design the Operational T&E system for weapon systems based on modeling of processes. And we modeled the processes of operational performance evaluation through utilizing resources and performance modules of weapon systems and combined it with the simulation engine for 3D visualization. Through this, we propose the Operational T&E system for weapon systems based on modeling of processes that represent operational performances visually.

• Journal of Internet Computing and Services
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• v.23 no.5
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• pp.135-143
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• 2022

As the world has implemented social distancing and telecommuting due to the spread of COVID-19, real-time streaming sessions based on routing protocols have increased dependence on the Internet due to the activation of video and voice-related content services and cloud computing. BGP is the most widely used routing protocol, and although many studies continue to improve security, there is a lack of visual analysis to determine the real-time nature of analysis and the mis-detection of algorithms. In this paper, we analyze BGP data, which are powdered as normal and abnormal, on a real-world basis, using an anomaly detection algorithm that combines statistical and post-processing statistical techniques with Rule-based techniques. In addition, we present an interactive spatio-temporal analysis plan as an intuitive visualization plan and analysis result of the algorithm with a map and Sankey Chart-based visualization technique.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.4
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• pp.847-857
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• 2018

As the number of malicious code increases steeply, cyber attack victims targeting corporations, public institutions, financial institutions, hospitals are also increasing. Accordingly, academia and security industry are conducting various researches on malicious code detection. In recent years, there have been a lot of researches using machine learning techniques including deep learning. In the case of research using Convolutional Neural Network, ResNet, etc. for classification of malicious code, it can be confirmed that the performance improvement is higher than the existing classification method. However, one of the characteristics of the target attack is that it is custom malicious code that makes it operate only for a specific company, so it is not a form spreading widely to a large number of users. Since there are not many malicious codes of this kind, it is difficult to apply the previously studied machine learning or deep learning techniques. In this paper, we propose a method to classify malicious codes when the amount of samples is insufficient such as targeting type malicious code. As a result of the study, we confirmed that the accuracy of 97% can be achieved even with a small amount of data by applying the Memory Augmented Neural Networks model.