• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.3
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• pp.137-143
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• 2009

Through the development of techniques, robots are becomes smaller, and many of robots needed for application are greater and greater. Method of coordinating large number of autonomous robots through local interactions has becoming an important research issue in robot community. Swarm Robot System is a system that independent autonomous robots in the restricted environment infer their status from preassigned conditions and operate their jobs through the coorperation with each other. Within the SRS,a robot contains sensor part to percept the situation around them, communication part to exchange information, and actuator part to do a work. Specially, in order to cooperate with other robots, communicating with other robot is one of the essential elements. In such as Bluetooth has many adventages such as low power consumption, small size module package, and various standard procotols, it is rated as one of the efficent communcating system for autonomous robot is developed in this paper. and How to construct and what kind of procedure to develop the communicatry system for group behavior of the SRS under intelligent space is discussed in this paper.

• Journal of the Korea Convergence Society
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• v.7 no.2
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• pp.53-59
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• 2016

Epilepsy is a neurological disease characterized by recurrent seizures. Though the exact causes for epilepsy are unknown, genetic mutations, especially altered gene functions, have been implicated as key causative components of epilepsy. We recently identified a causing gene for the Miles-Carpenter syndrome (MCS). MCS patients have intellectual disability and epilepsy. MCS knockout (KO) zebrafish also show a seizure-like phenotype with hyperactivity of pectoral fin and jaw movement, resulting from loss of GABAergic interneurons. To evaluate MCS KO zebrafish as an epilepsy model, we tested the effects of retigabine, an anticonvulsant drug, on the movement of MCS KO zebrafish.

• Journal of the Korean Data and Information Science Society
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• v.27 no.4
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• pp.887-898
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• 2016

The purpose of this study is to improve the learning ability of probability/statistics for H/W majors. Firstly, we developed a teaching method coupling probability/statistics with programming and multimedia signal processing courses that are opened in the H/W major curriculum. By use of its teaching-learning, we tried to verify the effectiveness on the improvement of learner's academic achievement and then analyze its educational efficiency through the regression analysis. Secondly, by analyzing the surveys and the statistical results of the education cases, we proposed a management plan on efficient teaching-learning in order to cultivate the learning ability of probability/statistics at a future time. Lastly, we concluded that probability/statistics is a required course of learners so as to contribute for the advanced technical development and the enhanced competitiveness in the field of the H/W.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.12C
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• pp.1181-1185
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• 2005

A combining of MIMO signal processing with OFDM is regarded as a promising solution of enhancing the performance of next generation wireless system. Therefore, in this paper, an OFDM-based wireless system employing layered space-time architecture is considered for a high-rate transmission. In the MIMO-OFDM system, we evaluate the PAR performance using the SLM approaches. The investigated SLM scheme for MIMO-OFDM signals selects the transmitted sequence with lowest average PAR over all transmitting antennas and retrieves the side information very accurately at the expense of a slight degradation of the PAR performance. The low probability of false side information can improve the overall detection performance of the MIMO-OFDM system with erroneous side information compared to the ordinary SLM approache, respectively. Also, we provide closed form of the average BER performance in MIMO-OFDM system using analytic approach.

• Journal of Digital Contents Society
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• v.19 no.1
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• pp.165-171
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• 2018

Shadow is a physical phenomenon observed in natural scenes and has a negative effect on various image processing systems such as intelligent video surveillance, traffic surveillance and aerial imagery analysis. Therefore, shadow detection should be considered as a preprocessing process in all areas of computer vision. In this paper, we define and analyze various feature elements for shadow detection in a single natural image that does not require a reference image. The shadow elements describe the intensity, chromaticity, illuminant-invariant, color invariance, and entropy image, which indicate the uncertainty of the information. The results show that the chromaticity and illuminant-invariant images are effective for shadow detection. In the future, we will define a fusion map of various shadow feature elements, and continue to study shadow detection that can adapt to various lighting levels, and shadow removal using chromaticity and illuminance invariant images.

• Journal of Convergence for Information Technology
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• v.7 no.5
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• pp.177-182
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• 2017

As major ICT technologies such as IoT, cloud computing, and Big Data are being applied to manufacturing, smart factories are beginning to be built. The key of smart factory implementation is the ability to acquire and analyze data of the factory. Therefore, the need for a big data analysis platform is increasing. The purpose of this study is to construct a platform for big data analysis of manufacturing process and propose integrated method for analysis. The proposed platform is a RHadoop-based structure that integrates analysis tool R and Hadoop to distribute a large amount of datasets. It can store and analyze big data collected in the unit process and factory in the automation system directly in HBase, and it has overcome the limitations of RDB - based analysis. Such a platform should be developed in consideration of the unit process suitability for smart factories, and it is expected to be a guide to building IoT platforms for SMEs that intend to introduce smart factories into the manufacturing process.

• Journal of IKEEE
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• v.16 no.4
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• pp.349-355
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• 2012

Information technology improves convenience, safety, and performance of automobiles. Recently, a lot of algorithms are studied to provide safety and environment information for driving, and lane detection algorithm is one of them. In this paper, we propose a lane detection algorithm that reduces the amount of calculation by reducing region of interest (ROI) after preprocessing. The proposed algorithm reduces the area of ROI a lot by determining the candidate regions near lane boundaries as V-ROI so that the amount of calculation is reduced. In addition, the amount of calculation can be maintained almost the same regardless of the resolutions of the input images by compressing the images since the lane detection algorithm does not require high resolution. The proposed algorithm is implemented using C++ and OpenCV library and is verified to work at 30 fps for realtime operation.

• Journal of Digital Contents Society
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• v.5 no.1
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• pp.87-94
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• 2004

In this paper, the digital watermarking algorithm is proposed using CDMA technique for protection of the mobile contents in the mobile environment. The digital watermarking was designed to robust the errors in the mobile environment where pathloss, multipath fading, interference, and noise exist. In case of the multimedia content service in the mobile environment, the construction method of the watermark, the algorithm of insertion and detection are also proposed. The watermark consists of the information of the mobile user. Invisibility and robustness required in watermarking are etimated. It is observed that PSNR of the mobile content inserted the watermark is 90.31 dB, and the signal processing and noise attack are also robust. Especially, because random noise occurs in wireless transmission can overcome, the proposed watermarking algorithm is adequate for protection of the multimedia contents in the mobile environment.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.6
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• pp.621-628
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• 2015

This paper describes an algorithm for detecting vehicles detection in real time. The proposed algorithm has the technique based on computer vision and image processing. In real, complex environment such as one with road traffic, many algorithms have great difficulty such as low detection rate and increasing computational time due to complex backgrounds and rapid changes. To overcome this problem in this paper, the proposed algorithm consists of the following methods. First, to effectively separate the candidate regions, we use vertical and horizontal edge information, and shadow values from input image sequences. Second, we extracts features by using HOG from the selected candidate regions. Finally, this paper uses the OS fuzzy-ELM based on SLFN to classify the extracted features. The experimental results show that the proposed method perform well for detecting vehicles and improves the accuracy and the computational time of detecting.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.6C
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• pp.535-543
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• 2002

In order to overcome disadvantages of existing centralized network management systems that use simple objects, dynamic object platforms are proposed as alternative systems. So the distributed network management systems are implemented using various distributed platform such as CORBA and Java-RMI. Subsequently mobile agent-based platforms are proposed. The mobile agent-based platform can additionally provide flexibility and scalability to network management system that CORBA or Java-RMI based platforms do not support. In this paper, we address an architecture to solve the problem of the occurrence of additional traffic by using mobile agent and to save resources of network element. Our proposal in this paper is an efficient network management architecture using motile agents. And we make use of mobile agents for minimizing of traffic that can happen when mobile agents moves. Also we design agents using information architecture of TMN for efficient resource management of network element and improvement of operation performance.