• Journal of Korea Society of Industrial Information Systems
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• v.9 no.3
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• pp.46-54
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• 2004

As a consequence of expansion in information technology, various services continually have been provided us through the internet in these days. Since the beginning of the mobile service, contents for its service actively have been developing now; there fore, the existing internet service system is gradually changing into the wireless mobile service system. However, mobile service now in use is mostly for entertainment such as bell sound, game and so on. The existing contents are very insufficient to satisfy the education. In this thesis, we have developed new mobile contents that are combined with Item Pool System. Students can connect to the learning contents by using the mobile device in anywhere and anytime in order to promote the efficiency of study.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.7
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• pp.1457-1464
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• 2011

In this paper, we go one step further in that the number of competitive layers is not determined by experience but can be determined by fuzzy control rules based on input pattern information. In our method, we design a set of membership functions and corresponding rules and used Max-Min reasoning proposed by Mamdani. Also, we use centroid method as a defuzzification. In experiment that has various patterns of English inputs, this new method works beautifully to determine the number of competitive layers and also efficient in overall accuracy as a result.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1373-1392
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• 2017

WiFi Direct (WD) is a state of the art technology for a Device-to-Device (D2D) communication in 802.11 networks. The performance of the WD system can be significantly affected by some key factors such as the type of application, specifications of MAC and PHY layer parameters, and surrounding environment etc. It is, therefore, important to develop a system model that takes these factors into account. In this paper, we focus on investigating the design parameters of the PHY layer that could maximize the efficiency of the WD 802.11 system. For this purpose, a basic theoretical model is formulated for a WD network under a 2x2 Multiple In Multiple Out (MIMO) TGn channel B model. The design level parameters such as input symbol rate and antenna spacing, as well as the effects of the environment, are thoroughly examined in terms of path gain, spectral density, outage probability and Packet Error Rate (PER). Thereafter, a novel adaptive algorithm is proposed to choose optimal parameters in accordance with the Quality of Experience (QoE) for a targeted application. The simulation results show that the proposed method outperforms the standard method thereby achieving an optimal performance in an adaptive manner.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.11
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• pp.2486-2491
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• 2013

There are invisible defects by naked eyes in ceramic material images such as internal stomata, cracks and foreign substances. In this paper we propose a method to detect and extract such defects from ceramic pipe weld zone by applying ART2 learning. In pre-processing, we apply Ends-in Search Stretching to enhance the intensity and then perform fuzzy binarization with triangle type membership function followed by enhanced ART2 that interacts with random input patterns to extract such invisible defects. The experiment verifies that this proposed method is sufficiently effective.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.5
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• pp.634-642
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• 1993

In this paper a new trajectory control method is proposed for a robot manipulator using a time delay neural network(TDNN) as a feedforward controller with an algorithm to learn inverse dynamics of the manipulator. The TDNN structure has so favorable characteristics that neurons can extract more dynamic information from both present and past input signals and perform more efficient learning. The TDNN neural network receives two normalized inputs, one of which is the reference trajectory signal and the other of which is the error signals from the PD controller. It is proved that the normalized inputs to the TDNN neural network can enhance the learning efficiency of the neural network. The proposed scheme was investigated for the planar robot manipulator with two joints by computer simulation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.4A
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• pp.371-382
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• 2002

A camera model with optical axes parallel has been widely used for stereo vision applications. A pair of input ages are obtained from a convergent-looking stereo camera model based on the human visual system in this per, and each image is divided into quadrant regions with respect to the fixation point. The reasoning of quadrant partitions is based on the human visual system and is proven by a geometrical method. Image patches : constructed from the right and left stereo images. A modified cepstrum filter is applied to the patches and disparity vectors are determined by peak detection algorithm. The three-dimensional information for synthetic ages is obtained from the measured disparity and the convergent stereo camera model. It is shown that the experimental results of the proposed method for various stereo images are accurate around the fixation point like the human visual system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.9
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• pp.3515-3538
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• 2015

Data accuracy can be increased by detecting and removing the incorrect data generated in wireless sensor networks. By increasing the data accuracy, network lifetime can be increased parallel. Network lifetime or operational time is the time during which WSN is able to fulfill its tasks by using microcontroller with on-chip memory radio transceivers, albeit distributed sensor nodes send summary of their data to their cluster heads, which reduce energy consumption gradually. In this paper a powerful algorithm using proactive fuzzy system is proposed and it is a mixture of fuzzy logic with comparative correlation techniques that ensure high data accuracy by detecting incorrect data in distributed wireless sensor networks. This proposed system is implemented in two phases there, the first phase creates input space partitioning by using robust fuzzy c means clustering and the second phase detects incorrect data and removes it completely. Experimental result makes transparent of combined correlated fuzzy system (CCFS) which detects faulty readings with greater accuracy (99.21%) than the existing one (98.33%) along with low false alarm rate.

• Journal of KIISE:Software and Applications
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• v.32 no.6
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• pp.523-531
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• 2005

Existing methods for color image segmentation using diffusion can't preserve contour information, or noises with high gradients become more salient as the number of times of the diffusion increases, resulting in over-segmentation when applied to watershed. This paper proposes a method for color image segmentation by applying morphological operations together with nonlinear diffusion For an input image, transformed into LUV color space, closing by reconstruction and nonlinear diffusion are applied to obtain a simplified image which preserves contour information with noises removed. With gradients computed from this simplified image, watershed algorithm is applied. Experiments show that color images are segmented very effectively without over-segmentation.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.28 no.4
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• pp.109-115
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• 2005

In the study, Methods for operating measures in equipment security to find out dangerousness timely in the system and to need for the prevention and measures. The method for analyzing and reconstructing the causes of accident of equipment in site, and try to save the information of site in real-time and to analyze the state of equipment to look for the factors of accidents. By this analysis, one plan for efficiency of production, Equipment Fault Diagnosis Management and security is integrating and building module of using the Fuzzy Inference based on fuzzy theory. The case study is applied to the industrial electric motors that are necessarily used to all manufacturing equipment. Using the sensor for temperature is attached to gain the site information in real time and to design the hardware module for signal processing. In software, realize the system supervising and automatically saving to management data base by the algorithm based in fuzzy theory from the existing manual input system

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.623-625
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• 2018

As the issue of particulate matter spreads, services for providing particulate matter information in real time are increasing. However, when a sensor node for collecting particulate matter is defective, a corresponding service may not be provided. To solve these problems, it is necessary to predict and deduce particulate matter. In this paper, a particulate matter prediction model is designed using artificial neural network algorithm based on past particulate matter and meteorological data to predict particulate matter. Also, the prediction results are compared by learning the input data of the model in the design stage.