• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.2
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• pp.28-36
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• 2018

Islands are supplied with power from diesel generation or from photovoltaic power generation, and problems with offshore environmental impacts (age deterioration, salt pollution), environmental pollution (exhaust gas, noise, dust) and power generation costs (installation, maintenance) have increasingly emerged. In 2016, the cost recovery rate was only 27%, and deficits reached 73% on 65 islands managed by KEPCO. In terms of deficits, the costs incurred in the power generation sector accounted for 91%, with the ratio of fixed costs at about 60%. Analysis suggests that operating costs can be reduced with an optimal power supply system that improves power generation efficiency and makes operating systems more efficient. Therefore, it is possible to simplify fuel transportation and facility maintenance, because one island integrates the power plants of remote islands, and offshore cable is used to supply power to the other islands. From the economic evaluations in this paper, an algorithm deciding offshore cable layout validity for an integrated power supply between adjacent islands is presented. Simulation results based on the proposed algorithm confirmed that an integrated power supply is economical for existing stand-alone operations on islands having diesel generation, low peak power, and near distances.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.7
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• pp.493-503
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• 2018

Recently, as living standards have improved, many people are becoming more interested in health, and self-training is increasing through exercise to prevent and manage pre-illness. In general, an imbalance of muscles causes asymmetry of posture, which can cause various diseases by accompanying an adjustment force, circulation action, displacement of internal organs, etc.. In this study, the development of fitness software that can be self - training among smart wears has attracted considerable attention in recent years. In this study, a technology was proposed for the commercialization of self - trainer fitness wear by a simulation through Android - based applications. Self - trainer fitness software was developed by combining a conductive polymer, fashion design, sewing, and electric and electronic technology to monitor the unbalance of the muscles during exercise and make smart wear that can calibrate the asymmetry by oneself. In particular, a polymer sensor was fabricated by deriving the optimal MWCNT concentration, and the electrode signal was collected by attaching the electrode to the optimal position, where the electrode signal line using the conductive fiber was designed and attached to collect the signal. A signal module that converts the bio-signals collected through electrical signal conversion and transmits them using Bluetooth communication was designed and manufactured. Self-trainer fitness software that can be commercialized was developed by combining noise cancellation with Android-based self-training application using a software algorithm method.

• Journal of Advanced Navigation Technology
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• v.6 no.1
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• pp.17-26
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• 2002

In this paper, we have analyzed the BER (Bit Error Rate) performance of multi-user detectors employing SIC(Successive Interference Cancellation) and PIC (Parallel Interference Cancellation) which are the representative schemes in the subtractive interference cancellation. We have considered the MUD structure employing HIC (Hybrid Interference Cancellation) which combines SIC with PIC scheme, and then analyzed the BER performance. We have evaluated the BER performance of SIC and HIC schemes which execute the soft decision to generate the tentative data bit for the purpose of the interference cancellation in MAI and noise environments. Through the numerical analysis and computer simulation, it is shown that HIC can remove the effect of MAI more efficiently than the others, that improve the BER performance and increase the capacity of DS-CDMA systems regardless of the power control conditions. The reason is that the SIC scheme in front of HIC can solve the near-far problem caused by the imperfect power control and PIC scheme in the rear of it can improve the performance much more.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.1
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• pp.696-701
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• 2017

This paper proposes an improved de-interlacing method that converts interlaced images into progressive images from one field. First, it calculates inter-pixel values applying third-order spline interpolation for the horizontal direction from four upper lower pixel values of missing pixels. From inter-pixel values obtained from spline interpolation and upper lower pixels with value, the proposed method makes an accurate estimate of the direction by applying the correlation between upper and lower pixels. The correlation between upper and lower pixels is calculated in nine directions of a missing pixel by using values obtained from spline interpolation and pixels with value. The direction of an edge is determined as the direction in which the correlation between upper and lower pixels is at its minimum. Thus, a missing pixel is calculated by taking the average of upper lower pixels obtained from the predicted direction of an edge. From the simulation results, there are problems in that it takes a bit more time for processing, but it is expected that the time problem will be improved by increasing CPU processing speed. As for image quality, it is shown that the proposed method improves both subjective and objective image quality and quantitatively improves picture signal-to-noise ratio (PSNR) in the range between 0.1 dB to 0.5 dB, as compared with previously presented de-interlacing methods.

• Journal of the Korea Computer Industry Society
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• v.3 no.9
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• pp.1145-1156
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• 2002

A method to measure the speed and distance of moving object is proposed using the stereo vision system. One of the most important factors for measuring the speed and distance of moving object is the accuracy of object tracking. Accordingly, the background image algorithm is adopted to track the rapidly moving object and the local opening operator algorithm is used to remove the shadow and noise of object. The extraction efficiency of moving object is improved by using the adaptive threshold algorithm independent to variation of brightness. Since the left and right central points are compensated, the more exact speed and distance of object can be measured. Using the background image algorithm and local opening operator algorithm, the computational processes are reduced and it is possible to achieve the real-time processing of the speed and distance of moving object. The simulation results show that background image algorithm can track the moving object more rapidly than any other algorithm. The application of adaptive threshold algorithm improved the extraction efficiency of the target by reducing the candidate areas. Since the central point of the target is compensated by using the binocular parallax, the error of measurement for the speed and distance of moving object is reduced. The error rate of measurement for the distance from the stereo camera to moving object and for the speed of moving object are 2.68% and 3.32%, respectively.

• Journal of KIISE:Software and Applications
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• v.30 no.3_4
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• pp.326-338
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• 2003

The objective of a neural network design and model selection is to construct an optimal network with a good generalization performance. However, training data include noises, and the number of training data is not sufficient, which results in the difference between the true probability distribution and the empirical one. The difference makes the teaming parameters to over-fit only to training data and to deviate from the true distribution of data, which is called the overfitting phenomenon. The overfilled neural network shows good approximations for the training data, but gives bad predictions to untrained new data. As the complexity of the neural network increases, this overfitting phenomenon also becomes more severe. In this paper, by taking statistical viewpoint, we proposed an integrative process for neural network design and model selection method in order to improve generalization performance. At first, by using the natural gradient learning with adaptive regularization, we try to obtain optimal parameters that are not overfilled to training data with fast convergence. By adopting the natural pruning to the obtained optimal parameters, we generate several candidates of network model with different sizes. Finally, we select an optimal model among candidate models based on the Bayesian Information Criteria. Through the computer simulation on benchmark problems, we confirm the generalization and structure optimization performance of the proposed integrative process of teaming and model selection.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.4
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• pp.395-403
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• 2016

This paper introduces a multi-cell search method for heterogeneous networks (HetNet), in which user equipments need to search multiple cells in its vicinity simultaneously. Due to the difficulty of acquiring channel informations for multiple cells, a non-coherent approach is preferred. In this paper, a non-coherent single-cell search scheme using a weighted vector is proposed, and the successive interference cancellation based multi-cell search algorithm is devised. In order to improve cell search performance, the weighted vector is designed in a way to exploit the general characteristic of wireless channel. Based on the fact that the performance of the proposed single-cell search scheme deviates slowly from the one using the optimal weighted vector, a universal weighted vector is also proposed, which shows the performance close to the optimal ones for various channel environments and signal-to-noise ratio regimes. Simulation results confirm that the proposed multi-cell search algorithm is capable of identifying cells more accurately with the help of the proposed single-cell search scheme, and can detect the remaining cells more effectively by removing the signals of the identified cells from the received signal.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.5A
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• pp.490-496
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• 2007

This paper describes the design and implementation of an integrated LTCC front-end module for the IEEE802.11a WLAN applications by performing the behavioral-level simulation using measurement-based behavioral model. To meet the IEEE802.11a WLAN standard, a system transmitting 1024 symbols through 64-QAM process at the rate of 54Mbps should be implemented and nonlinear properties are confirmed by simulations of ACPR and EVM in this circumstance. The right offsets of ACPR which are 30MHz, 20MHz, and 11MHz distant from the center frequency of 5.8GHz are 49.36dBc, 36.90dBc, and 24.58dBc, respectively. The left offsets are 50.14dBc, 30.04dBc, and 28.85dBc, respectively and EVM is 2.94%. The size of the module implemented with LTCC five-layer substrates is $13.4mm{\times}14.2mm$. The measured characteristics of the transmitter show P1dB of 16.2dBm and power gain of 16.73dB. Those of the receiver exhibit the small signal gain of 16.24dB and noise figure of 7.83dB.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2430-2434
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• 2005

Automatic FPC punching instrument for the improvement of working condition and cost saving is introduced in this paper. FPC(flexible printed circuit) is used to detect the contact position of K/B and button like a cellular phone. Depending on the quality of the printed ink and position of reference punching point to the FPC, the resistance and current are varied to the malfunctioning values. The size of reference punching point is 2mm and the above. Because the punching operation is done manually, the accuracy of the punching degree is varied with operator's condition. Recently, The punching accuracy has deteriorated severely to the 2mm punching reference hall so that assembly of the K/B has hardly done. To improve this manual punching operation to the FPC, automatic FPC punching system is introduced. Precise mechanical parts like a 5-step stepping motor and ball screw mechanism are designed and tested and low cost PC camera is used for the sake of cost down instead of using high quality vision systems for the FA. 3D Mechanical design tool(Pro/E) is used to manage the exact tolerance circumstances and avoid design failures. Simulation is performed to make the complete vision based punching machine before assembly, and this procedure led to the manufacturing cost saving. As the image processing algorithms, dilation, erosion, and threshold calculation is applied to obtain an exact center position from the FPC print marks. These image processing algorithms made the original images having various noises have clean binary pixels which is easy to calculate the center position of print marks. Moment and Least square method are used to calculate the center position of objects. In this development circumstance, Moment method was superior to the Least square one at the calculation of speed and against noise. Main control panel is programmed by Visual C++ and graphical Active X for the whole management of vision based automatic punching machine. Operating modes like manual, calibration, and automatic mode are added to the main control panel for the compensation of bad FPC print conditions and mechanical tolerance occurring in the case of punch and die reassembly. Test algorithms and programs showed good results to the designed automatic punching system and led to the increase of productivity and huge cost down to law material like FPC by avoiding bad quality.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.3
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• pp.62-70
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• 2011

Nowadays image sensor is an essential component in many multimedia devices, and it is covered by a color filter array to filter out specific color components at each pixel. We need a certain algorithm to combine those color components reconstructed a full color image from incomplete color samples output from an image sensor, which is called a demosaicking process. Most existing demosaicking algorithms are developed for ideal image sensors, but they do not work well for the practical cases because of dissimilar characteristics of each sensor. In this paper, we propose a new demosaicking algorithm in which the color filter characteristics are fully utilized to generate a good image. To demonstrate significance of our algorithm, we used a commerically available sensor, CBN385B, which is a sort of Honeycomb-style CFA(Color Filter Array) CCD image sensor. As a performance metric of the algorithm, PSNR(Peak Signal to Noise Ratio) and RGB distribution of the output image are used. We first implemented our algorithm in C-language for simulation on various input images. As a result, we could obtain much enhanced images whose PSNR was improved by 4~8 dB compared to the commonly idealized approaches, and we also could remove the inclined red property which was an unique characteristics of the image sensor(CBN385B).Then we implemented it in hardware to overcome its problem of computational complexity which made it operate slow in software. The hardware was verified on Spartan-3E FPGA(Field Programable Gate Array) to give almost the same performance as software, but in much faster execution time. The total logic gate count is 45K, and it handles 25 image frmaes per second.