• Journal of Korean Vacuum Science & Technology
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• v.6 no.1
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• pp.8-11
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• 2002

Ni, Si and $SiO_2$ films were implanted by 350 keV B $i_{+}$ ions at room temperature with fluences of 1$\times$10$^{16}$ and 2$\times$10$^{16}$ ions/c $m^2$ The depth distributions of implanted B $i^{+}$ ions in Ni, Si and $SiO_2$ films were by investigated by Rutherford backscattering. The results show that the depth distributions of implanted B $i^{+}$ ions into Ni, Si and $SiO_2$ films have obeyed nearly Gaussian distributions. The maximum difference between experimental and calculated values is less than 18 % for mean projected range. Experimental range straggling deviated significantly from calculated value. The possible reasons are discussed.sed.d.

• Honam Mathematical Journal
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• v.30 no.3
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• pp.581-587
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• 2008

In this paper, to have a better a posteriori error bound of the average case error between the true value of I(f) and the Trapezoidal rule on subintervals using zero mean-Gaussian, we prove that a new average error between the difference of the true value of I(f) from the composite Trapezoidal rule and that of the composite Trapezoidal rule from the simple Trapezoidal rule is bounded by $c_rH^{2r+3}$ through direct computation of constants $c_r$ for r ${\leq}$ 2 under the assumption that we have subintervals (for simplicity equal length h) partitioning [0, 1].

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.882-885
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• 2011

This paper presents testing and self-calibration of RF circuits using MEMS switches to identify process-related defects and out of specification circuits. We have developed a novel multi-tone dither test technique where the test stimulus is generated by modulating the RF carrier signal with a multi-tone signal generated using an Arbitrary Waveform Generator (AWG) with additive white Gaussian noise. This test stimulus is provided as input to the RF circuit and peak-to-average ratio (PAR) is measured at the output. For a faulty circuit, a significant difference is observed in the value of PAR as compared to a fault-free circuit. Simulation is performed for various circuit conditions such as fault-free as well as fault-induced and their corresponding PARs are stored in the look-up table. This testing and self-calibration technique is exhaustive and efficient for present-day communication systems.

• Journal of Information Processing Systems
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• v.15 no.2
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• pp.271-287
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• 2019

The synchronization scheme based on moving average is robust and suitable for the same rule to be adopted in embedding watermark and synchronization code, but the imperceptibility and search efficiency is seldom reported. The study aims to improve the original scheme for robust audio watermarking. Firstly, the survival of the algorithm from desynchronization attacks is improved. Secondly, the scheme is improved in inaudibility. Objective difference grade (ODG) of the marked audio is significantly changed. Thirdly, the imperceptibility of the scheme is analyzed and the derived result is close to experimental result. Fourthly, the selection of parameters is optimized based on experimental data. Fifthly, the search efficiency of the scheme is compared with those of other synchronization code schemes. The experimental results show that the proposed watermarking scheme allows the high audio quality and is robust to common attacks such as additive white Gaussian noise, requantization, resampling, low-pass filtering, random cropping, MP3 compression, jitter attack, and time scale modification. Moreover, the algorithm has the high search efficiency and low false alarm rate.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.6
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• pp.1293-1299
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• 2012

In this paper, a real-time vehicle detection and tracking algorithms is proposed. The vehicle detection could be processed using GMM (Gaussian Mixture Model) algorithm and mathematical morphological processing with HD CCTV camera images. The vehicle tracking based on separated vehicle object was performed using Euclidean distance between detected object. In more detail, background could be estimated using GMM from CCTV input image signal and then object could be separated from difference image of the input image and background image. At the next stage, candidated objects were reformed by using mathematical morphological processing. Finally, vehicle object could be detected using vehicle size informations dependent on distance and vehicle type in tunnel. The vehicle tracking performed using Euclidean distance between the objects in the video frames. Through computer simulation using recoded real video signal in tunnel, it is shown that the proposed system works well.

• Journal of Integrative Natural Science
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• v.12 no.4
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• pp.105-115
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• 2019

In this paper, a prediction system is proposed to control the brightness of smart street lamps by predicting the moving path through the reduction of consumption power and information of pedestrian's past moving direction while meeting the function of existing smart street lamps. The brightness of smart street lamps is adjusted by utilizing the walk tracking vector and soft hand-off characteristics obtained through the motion sensing sensor of smart street lamps. In addition, the motion vector is used to analyze and predict the pedestrian path, and the GPU is used for high-speed computation. Pedestrians were detected using adaptive Gaussian mixing, weighted difference imaging, and motion vectors, and motions of pedestrians were analyzed using the extracted motion vectors. The preprocessing process using linear interpolation is performed to improve the performance of the proposed prediction system. Fuzzy prediction system and neural network prediction system are designed in parallel to improve efficiency and rough set is used for error correction.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.1
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• pp.120-126
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• 1995

The diffusion neural network can be cfficiently applied to the Gaussian processing. For example, a difference of two Gaussians(DOG) is performed by this network with ease. In this paper, we model a neural network to perform the function /t(.del.${\Delta}^{2}$G) by using the diffusion neural network. This model is used to detect the edges of moving target in image. By this model not only moving target is separated from stationary background but also their trajectories are obtained using accumulated past information in the diffusion neural network. Furthermore this model needs a small number of connections per cell and the connection weights are fixed-valued. Therefore its hardware can be easily implemented with simple structure.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.54-56
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• 2009

We propose an image change detection algorithm implemented on sensor nodes of the ubiquitous sensor network(USN). The proposed algorithm was designed for the robust detection of image changes regardless of the continuously changing ambient illumination environment. Morphological lowpass filter was used for estimating the illumination component in order to reduce computational burden instead of the existing Gaussian lowpass filter. The decision of the change detection is based on the result of threshold of difference image between two consecutive images. We also propose a new thresholding method using precalculated histogram information. The proposed algorithm was implemented on the MSP430 16bit microprocessor.

• The Journal of Korea Robotics Society
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• v.5 no.1
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• pp.70-76
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• 2010

This paper addresses a design issue of "model complexity and performance trade-off" in the application of bandwidth extension (BWE) methods to the intra-frame predictivevector quantization problem of wideband speech. It discusses model-based linear and non-linear prediction methods and presents a comparative study of them in terms of prediction gain. Through experimentation, the general trend of saturation in performance (with the increase in model complexity) is observed. However, specifically, it is also observed that there is no significant difference between HMM and GMM-based BWE functions.

• Journal of information and communication convergence engineering
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• v.6 no.1
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• pp.80-85
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• 2008

Images are often corrupted by noises during signal acquisition and transmission. Among those noises, additive white Gaussian noise (AWGN) and impulse noise are most representative. For different types of noise have different characters, how to remove them separately from degraded image is one of the most fundamental problems. Thus, a modified image restoration algorithm is proposed in this paper, which can not only remove impulse noise of random values, but also remove the AWGN selectively. The noise detection step is by calculating the intensity difference and the spatial distance between pixels in a mask. To divide two different noises, the method is based on three weighted parameters. And the weighted parameters in the filtering mask depend on spatial distances, positions of impulse noise and standard deviation of AWGN. We also use the peak signal-to-noise ratio (PSNR) to evaluate restoration performance, and simulation results demonstrate that the proposed method performs better than conventional median-type filters, in preserving edge details.