• Journal of the Optical Society of Korea
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• v.18 no.2
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• pp.124-128
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• 2014

We derive joint probability density functions (JPDFs) for two adjacent data from direct-detection optical receivers in dense wavelength-division multiplexing systems. We show that the decision using two data per bit can increase the receiver sensitivity compared with the conventional decision. Our JPDFs can be used for software-defined optical receivers enhancing the receiver sensitivities for intensity-modulated channels.

• Journal of Korea Society of Industrial Information Systems
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• v.20 no.2
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• pp.73-83
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• 2015

This paper proposes a TFT-LCD defect blob detection algorithm using the sequential defect detection method. First, for every pixel, a defect possibility is determined by the intensity difference and the defect candidates are detected according to the sequential defect detection method. For detected candidate pixels, the defect probability that indicates a potential included in the defect according to the each step. By applying the morphological operation, blobs are comprised of the detected candidates and the defect blobs are detected using the defect possibility of blobs. The validity of the proposed method was demonstrated a simulated image and also then it was tested a real TFT-LCD image. By the experimental results, the proposed method is very effective in TFT-LCD detect detection.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.49.1-49
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• 2001

The skin color model is a very important concept in face detection, face recognition and face tracking. Usually, this model is obtained by estimating a probability density function of skin color distribution. In many cases, it is assumed that the underlying density function follows a Gaussian distribution. In this paper, a new method for non-parametric estimation of the probability density function, by using feed-forward neural network, is used to estimate the underlying skin color model. By using this method, the resulting skin color model is better than the Gaussian estimation and substantially approaches the real distribution. Applications to face detection and face ...

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.2
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• pp.287-293
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• 2013

Cognitive radio has been recently proposed to dynamically access unused-spectrum. The CR users can share the same frequency band with the primary user without interference to each other. Usually each CR user needs to determine spectrum availability by itself depending only on its local observations. But uncertainty communication environment effects can be mitigated so that the detection probability is improved in a heavily shadowed environment. Soft detection is a primary user detection method of cooperative cognitive radio networks. In our research, we will improve system detection probability by using optimal cooperative node selection algorithm. New algorithm can find optimal number of cooperative sensing nodes for cooperative soft detection by using maximum ratio combining (MRC) method. Through analysis, proposed cooperative node selection algorithm can select optimal node for cooperative sensing according to the system requirement and improve the system detection probability.

• Journal of Korean Society for Quality Management
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• v.25 no.3
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• pp.74-85
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• 1997

In this paper we calculate the subgroup size necessary for detecting the change of percent defective with several detection probabilities for orginal population fraction nonconforming p, changed population fraction nonconforming $p^*$, and the ratio k=$p^*$/p in the usage of p control charts. From our calculation we can know the error level of normal a, pp.oximation in detection probability calculation and recommend the subgroup size with lower error levels of normal a, pp.oximation, and then we show the reasonable subgroup size necessary for p, $p^*$, k, and the detection probability of the change of fraction nonconforming in a process. The information that we here show in tables will be useful when p control chart users decide the subgroup size in the p control chart users decide the subgroup size in the p control chart.

• Journal of Communications and Networks
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• v.16 no.6
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• pp.600-612
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• 2014

In this paper, we consider the problem of spectrum sensing for advanced television systems committee (ATSC) digital television (DTV) signal detection. To exploit the cyclostationarity of the ATSC DTV signals, we employ spectral correlation density (SCD) as the decision statistic and propose an optimal detection algorithm. The major difficulty is in obtaining the probability distribution functions of the SCD. To overcome the difficulty, we probabilistically model the pilot frequency location and employ Gaussian approximation for the SCD distribution. Then, we obtain a practically implementable detection algorithm that outperforms the industry leading systems by 2-3 dB. We also propose various techniques that greatly reduce the system complexity with performance degradation by only a few tenths of decibels. Finally, we show how robust the system is to the estimation errors of the noise power spectral density level and the probability distribution of the pilot frequency location.

• Journal of Korea Multimedia Society
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• v.22 no.6
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• pp.684-694
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• 2019

Information spread in networks is universal in many real-world phenomena such as propagation of infectious diseases, diffusion of a new technology, computer virus/spam infection in the internet, and tweeting and retweeting of popular topics. The problem of finding the information source is to pick out the true source if information spread. It is of practical importance because harmful diffusion can be mitigated or even blocked e.g., by vaccinating human or installing security updates. This problem has been much studied, where it has been shown that the detection probability cannot be beyond 31% even for regular trees if the number of infected nodes is sufficiently large. In this paper, we study the impact of an anti-information spreading on the original information source detection. We consider an active defender in the network who spreads the anti-information against to the original information simultaneously and propose an inverse Voronoi partition based inference approach, called Voronoi Inference to find the source. We perform various simulations for the proposed method and obtain the detection probability that outperforms to the existing prior work.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.890-895
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• 2004

This paper describes constant alarm rates process of millimeter wave radar that exits on non-stationary target detection schemes in the ground clutter conditions. The comparison of various CFAR processes such as CA(Cell-Average)-CFAR, GO(Greatest Of)/SO(Smallest Of)-CFAR and OS(Order Statistics)-CFAR performance are applied. Using matlab software, we show the performance and loss between detection probability and signal to noise ratio. When rang bins increase, this results show the OS-CFAR process performance is better than any others and satisfies the optimal detection probability without loss of detection in the homogeneous clutter.

• Journal of the Korea Society of Computer and Information
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• v.9 no.2
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• pp.89-96
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• 2004

In this paper, an improved method is proposed by supplementing multi-path gain for detection. This method is proposed to complement the shortcomings of the conventional detection method which is used for multiuser detection in STBC(Space-Time Block Code) CDMA system. We analyzed the improved method in bit error probability viewpoint and compared the result with that of the conventional method. From this result, we showed that bit error probability of the improved method is superior to that of the conventional method when the parameters such as delay, number of user and SNR are increased.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.2
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• pp.417-422
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• 2010

When memory devices are exposed to space environments, they suffer various effects such as SEU(Single Event Upset). Memory systems for space applications are generally equipped with error detection and correction(EDAC) logics against SEUs. In this paper, several error detection and correction codes - RS(10,8) code, (7,4) Hamming code and (16,8) code - are analyzed and compared with each other. Each code is implemented using VHDL and its performances(encoding/decoding speed, required memory size) are compared. Also the failure probability equation of each EDAC code is derived, and the probability value is analyzed for various occurrence rates of SEUs which the STSAT-3 possibly suffers. Finally, the EDAC algorithm for STSAT-3 is determined based on the comparison results.