• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.356-359
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• 2017

According to the plan of operation of the Ministry of Education, IWB (Interactive White Board) was distributed to one or two classrooms per school. Therefore, instead of the overhead projector (OHP) and the screen, the visual presenter and the IWB replaced the role. However, the development speed of the imaging device and the display device could not keep up, and the utilization was often lowered. In this study, we study to obtain a high resolution image using the camera of smartphone. It uses WiGig(Wireless Gigabit) technology to transmit the acquired high-resolution images to IWB or large-screen TV without delay in wireless communication. In addition, while the smartphone camera is equipped with a lens of a wide field of view(FOV), the microscope lens can be used to magnify and magnify a specific portion of a smartphone 400 times. As s result of this study it will be used as active material for real-time 400 times magnification in education and research field.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.4
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• pp.729-738
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• 2019

In this paper, we propose two-way authentication protocol between unmanned systems in tactical wireless networks in which long distance communications are not guaranteed due to a poor channel conditions. It is assumed that every unmanned systems have same random data set before they put into combat. The proposed protocol generates authentication code(AC) using random data that causes hash collision. The requester for authentication encrypts the materials such as their identifier, time-stamp, authentication code with the secret key. After then the requester transmits the encrypted message to the receiver. The receiver authenticates the requester by verifying the authentication code included in the request message. The performance analysis of the proposed protocol shows that it guarantees the security for various attack scenarios and efficiency in terms of communication overhead and computational cost. Furthermore, we analyzed the effect of the parameter values of the proposed protocol on the performance and suggest appropriate parameter value selection guide according to the level of security requirement.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.5
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• pp.115-121
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• 2019

In this paper, we propose MSAG-SCS-MMA-I adaptive blind equalization with double step size with very small residual ISI and MSE at steady-state while significantly improving the convergence speed of the traditional SCS-MMA-I algorithm in 256-QAM system. And we evaluate the equalization performance for this algorithm. Different step sizes according to the absolute value of decision-directed error instead of a fixed step-size are applied to the tap update equation of MSAG-SCS-MMA-I, which is controlled by binary flags of '1' or '0' obtained from SCS-MMA-I and decision-directed algorithms. This makes for excellent equalization performance. As a result of computer simulation, we confirmed that the proposed algorithm has more better performance than the MMA, SCS-MMA-I, and MSAG-SCS-MMA-I algorithms in terms of the performance index such as residual ISI, MSE, and MD.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.6
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• pp.729-735
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• 2020

A college campus tour is a great opportunity to promote the school environment, facilities and history to visitors or prospective students. Along with the population of smart phones and the advancement of information and communication technologies, many universities have recently provided mobile applications for campus tour, and some are starting to utilize augmented reality technology. However, most of the existing campus tour augmented reality systems tended to present a description-oriented campus tour guide. Their main focus is simply to provide information about the campus's main buildings or symbols. This study focuses on self-guided tours of the campus through games making new students and visitors to get familiar with the campus in a more natural and intuitive way. In this paper we present the design and development of a location-based mobile augmented reality treasure hunt game to enhance the user experience.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.3
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• pp.7-14
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• 2021

The emergence of the automated smart grid has become an essential device for responding to these problems and is bringing progress toward a smart grid-based society. Smart grid is a new paradigm that enables two-way communication between electricity suppliers and consumers. Smart grids have emerged due to engineers' initiatives to make the power grid more stable, reliable, efficient and safe. Smart grids create opportunities for electricity consumers to play a greater role in electricity use and motivate them to use electricity wisely and efficiently. Therefore, this study focuses on power demand management through machine learning. In relation to demand forecasting using machine learning, various machine learning models are currently introduced and applied, and a systematic approach is required. In particular, the GP learning model has advantages over other learning models in terms of general consumption prediction and data visualization, but is strongly influenced by data independence when it comes to prediction of smart meter data.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.11 no.5
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• pp.3-16
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• 2001

With the development of Internet, it is widely spreaded to a Intranet based on Internet technology. Intranet is a private, unique network to share the information of organization such as incorporate, research institute and university. With the increase of Intranet using, Intranet environment is developing into Extranet environment which is connected many Intranet. Currently such Intranet and Extranet environments, above all, it is important to solve security problems which can appear through use of information between domains. Thus, in this paper, we propose SSO(Single Sign-on System) model with authorization management and single sign-on operation, and we extend it to enable mutual authentication through inter-working based on PKI(Public Key Infrastructure) in Extranet environments.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.6
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• pp.987-994
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• 2020

In this paper, we studied the effect of kernel size of CNN layer on performance in acoustic noise attenuators. This system uses a deep learning algorithm using a neural network adaptive prediction filter instead of using the existing adaptive filter. Speech is estimated from a single input speech signal containing noise using a 100-neuron, 16-filter CNN filter and an error back propagation algorithm. This is to use the quasi-periodic property in the voiced sound section of the voice signal. In this study, a simulation program using Tensorflow and Keras libraries was written and a simulation was performed to verify the performance of the noise attenuator for the kernel size. As a result of the simulation, when the kernel size is about 16, the MSE and MAE values are the smallest, and when the size is smaller or larger than 16, the MSE and MAE values increase. It can be seen that in the case of an speech signal, the features can be best captured when the kernel size is about 16.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.4
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• pp.625-632
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• 2021

This paper studies the effect of the number of filters in the CNN (Convolutional Neural Network) layer on the performance of a noise attenuator. Speech is estimated from a noised speech signal using a 64-neuron, 16-kernel CNN filter and an error back-propagation algorithm. In this study, in order to verify the performance of the noise attenuator with respect to the number of filters, a program using Keras library was written and simulation was performed. As a result of simulation, it can be seen that this system has the smallest MSE (Mean Squared Error) and MAE (Mean Absolute Error) values when the number of filters is 16, and the performance is the lowest when there are 4 filters. And when there are more than 8 filters, it was shown that the MSE and MAE values do not differ significantly depending on the number of filters. From these results, it can be seen that about 8 or more filters must be used to express the characteristics of the speech signal.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.3
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• pp.409-416
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• 2022

This paper relates to the blind noise separation method of time-delayed convolutive mixed signals. Since the mixed model of acoustic signals in a closed space is multi-channel, a convolutive blind signal separation method is applied and time-delayed data samples of the two microphone input signals is used. For signal separation, the mixing coefficient is calculated using an inverse model rather than directly calculating the separation coefficient, and the coefficient update is performed by repeated calculations based on secondary statistical properties to estimate the speech signal. Many simulations were performed to verify the performance of the proposed blind signal separation. As a result of the simulation, noise separation using this method operates safely regardless of convolutive mixing, and PESQ is improved by 0.3 points compared to the general adaptive FIR filter structure.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.1
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• pp.71-76
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• 2023

This paper studied a method of attenuating nonlinear noise using a Wiener filter of a neural network structure in an acoustic noise attenuator. This system improves nonlinear noise attenuation performance with a deep learning algorithm using a neural network Wiener filter instead of using a conventional adaptive filter. A voice is estimated from a single input voice signal containing nonlinear noise using a 128-neuron, 8-neuron hidden layer and an error back propagation algorithm. In this study, a simulation program using the Keras library was written and a simulation was performed to verify the attenuation performance for nonlinear noise. As a result of the simulation, it can be seen that the noise attenuation performance of this system is significantly improved when the FNN filter is used instead of the Wiener filter even when nonlinear noise is included. This is because the complex structure of the FNN filter expresses any type of nonlinear characteristics well.