• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.2
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• pp.67-74
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• 2008

This paper proposes two peak-windowing algorithms for peak-to-average power reduction(PAPR) of orthogonal frequency division multiple access(OFDMA) downlink systems. The Proposed algorithms mitigate the effect of excessive suppression due to successive peaks or relatively high peaks of the signal. First, multi-stage peak windowing algorithm is proposed, which exploits multiple threshold of target PAPR in order to step down the peaks gradually. Secondary, variable-length peak windowing algorithm is proposed, which adapts the window length with respect to the existence of successive peaks within a half of window length. Therefore, the proposed method reduces the distortion of signal amplitude caused by window overlapping. The proposed algorithms outperform the conventional peak windowing with the aid of window-length adaptation or sequential peak power reduction. Simulation results show the efficiency of the proposed algorithms over OFDMA downlink systems, especially WiBro systems.

• IEMEK Journal of Embedded Systems and Applications
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• v.7 no.4
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• pp.163-172
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• 2012

A driver assistance system is critical to improve a convenience and stability of vehicle driving. Several systems have been already commercialized such as adaptive cruise control system and forward collision warning system. Efficient vehicle detection is very important to improve such driver assistance systems. Most existing vehicle detection systems are based on a radar system, which measures distance between a host and leading (or oncoming) vehicles under various weather conditions. However, it requires high deployment cost and complexity overload when there are many vehicles. A camera based vehicle detection technique is also good alternative method because of low cost and simple implementation. In general, night time vehicle detection is more complicated than day time vehicle detection, because it is much more difficult to distinguish the vehicle's features such as outline and color under the dim environment. This paper proposes a method to detect vehicles at night time using analysis of a captured color space with reduction of reflection and other light sources in images. Four colors spaces, namely RGB, YCbCr, normalized RGB and Ruta-RGB, are compared each other and evaluated. A suboptimal threshold value is determined by Otsu algorithm and applied to extract candidates of taillights of leading vehicles. Statistical features such as mean, variance, skewness, kurtosis, and entropy are extracted from the candidate regions and used as feature vector for SVM(Support Vector Machine) classifier. According to our simulation results, the proposed statistical feature based SVM provides relatively high performances of leading vehicle detection with various distances in variable nighttime environments.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.7
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• pp.1564-1570
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• 2013

In this paper, we propose a robust pupil detection method using rank order filter and cross-correlation. Potential pupil candidates are detected using rank order filter. Eye region is binarized using variable threshold to find eyebrow, and pupil candidates at the eyebrow are removed. The positions of pupil candidates are corrected, the pupil candidates are grouped into pairs based on geometric constraints. A similarity measure is obtained for two eye of each pair using cross-correlation, we select a pair with the largest similarity measure as a final pupil. The experiments have been performed for 500 images of the BioID face database. The results show that it achieves the high detection rate of 96.8% and improves about 11.6% than existing method.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.6
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• pp.629-635
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• 2019

In Deep Learning models derivative is implemented by error back-propagation which enables the model to learn the error and update parameters. It can find the global (or local) optimal points of parameters even in the complex models taking advantage of a huge improvement in computing power. However, deliberately generated data points can 'fool' models and degrade the performance such as prediction accuracy. Not only these adversarial examples reduce the performance but also these examples are not easily detectable with human's eyes. In this work, we propose the method to detect adversarial datasets with random noise addition. We exploit the fact that when random noise is added, prediction accuracy of non-adversarial dataset remains almost unchanged, but that of adversarial dataset changes. We set attack methods (FGSM, Saliency Map) and noise level (0-19 with max pixel value 255) as independent variables and difference of prediction accuracy when noise was added as dependent variable in a simulation experiment. We have succeeded in extracting the threshold that separates non-adversarial and adversarial dataset. We detected the adversarial dataset using this threshold.

• Journal of Embryo Transfer
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• v.24 no.3
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• pp.225-230
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• 2009

Sex-sorting of sperm is an assisted reproductive technology (ART) used by the livestock industry for the mass production of animals of a desired sex. The standard method for sorting sperm is the detection of DNA content differences between X and Y chromosome-bearing sperm by flow cytometry. However, this method has variable efficiency and therefore requires verification by a second method. We have developed a sex determination method based on quantitative real-time polymerase chain reaction (qPCR) of the porcine amelogenin (AMEL) gene. The AMEL gene is present on both the X and the Y chromosome, but the length and sequence of its noncoding regions differ between the X and Y chromosomes. By measuring the threshold cycle (Ct) of qPCR, we were able to calculate the relative frequency of X chromosome. Two sets of AMEL primers were used in these studies. One set (AME) targeted AMEL gene sequences present in both X and Y chromosome, but produced PCR products of different lengths for each chromosome. The other set (AXR) bound to AMEL gene sequences present on the X chromosome but absent esholthe Y-chromosome. Relative product levels were calculated by normalizing the AXR fluorescence to the AME fluorescence. The AMEL method accurately predicted the sex ratios of boar sperm, demonstrating that it has potential value as a sex determination method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.8A
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• pp.1160-1168
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• 2000

This paper presents a real-time integrated traffic management (RITM) scheme that can effectively manage variable bit rate (VBR) and available bit rate (ABR) traffics having unpredictable characteristics in asynchronous transfer mode (ATM) networks. An unique feature of this scheme is that it has a special ATM cell control block which makes it possible to monitor bursty traffics in real-time so that the delay incurred to measure cell arrival rate is minimized. Additionally, the proposed scheme intends to dynamically reassign the leftover network resources to VBR/ABR connections without any deterioration in quality of service (QoS) of the existing connections. The RITM scheme has been verified to reliably monitor incoming traffics and to efficiently manage network resources by computer simulations. The capability of managing the incoming ATM traffics in real-time helps determine an optimal acceptable number of user connections for a given network condition. We can use this value as a threshold to protect the network from being congested and to find out a cost-effective buffer design method.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.1
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• pp.78-88
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• 2006

This paper is to apply Geographical Information System (GIS) supported Geomorphoclimatic Instantaneous Unit Hydrograph (GCIUH) approach for the calculated flash flood trigger rainfall of the mountainous area. GIS techniques was applied in geography data construction such as average slope, drainage area, channel characteristics. Especially, decided stream order using GIS at stream order decision that is important for input variable of GCIUH. We compared the GCIUH peak discharge with the existing report using the design storm at Chundong basin($14.58km^2$). The results showed that derived the GCIUH was a very proper method in the calculation of mountaunous discharge. At the Chundong basin, flash flood trigger rainfall was 12.57mm in the first 20 minutes when the threshold discharge was $11.42m^3/sec$.

• The Korean Journal of Applied Statistics
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• v.24 no.2
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• pp.269-278
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• 2011

There are many researches that have considered the distribution functions and appropriate covariates corresponding to the scores in order to improve the accuracy of a diagnostic test, including the ROC curve that is represented with the relations of the sensitivity and the specificity. The ROC analysis was used by the regression model including some covariates under the assumptions that its distribution function is known or estimable. In this work, we consider a general situation that both the distribution function and the elects of covariates are unknown. For the ROC analysis, the mixtures of normal distributions are used to estimate the distribution function fitted to the credit evaluation data that is consisted of the score random variable and two sub-populations of parameters. The AUC measure is explored to compare with the nonparametric and empirical ROC curve. We conclude that the method using normal mixtures is fitted to the classical one better than other methods.

• The Journal of the Acoustical Society of Korea
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• v.18 no.2
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• pp.3-10
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• 1999

This paper describes the development and evaluation of a Korean address input system employing automatic speech recognition technique as user interface for input Korean address. Address consists of cities, provinces and counties. The system works on a window 95 environment of personal computer with built-in soundcard. In the speech recognition part, the Continuous density Hidden Markov Model(CHMM) for making phoneme like units(PLUs) and One Pass Dynamic Programming(OPDP) algorithm is used for recognition. For address recognition, Finite State Automata(FSA) suitable for Korean address structure is constructed. To achieve an acceptable performance against the variation of speakers, microphones, and environmental noises, Maximum a posteriori(MAP) estimation is implemented in adaptation. And to improve the recognition speed, fast search method using variable pruning threshold is newly proposed. In the evaluation tests conducted for the 100 connected words uttered by 3 males the system showed above average 96.0% of recognition accuracy for connected words after adaption and recognition speed within 2 seconds, showing the effectiveness of the system.

• Journal of the Korean Data and Information Science Society
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• v.21 no.5
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• pp.891-899
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• 2010

Association rule is the technique to represent the relationship between two or more items by numerical representing for the relevance of each item in vast amounts of databases, and is most being used in data mining. The basic thresholds for association rule are support, confidence, and lift. these are used to generate the association rules. We need standardization of lift because the range of lift value is different from that of support and confidence. And also we need standardization of support and confidence to compare objectively association level of antecedent variables for one descendant variable. In this paper we propose a method for standardization of association thresholds considering marginal probability for each item to grasp objectively and exactly association level, check the conditions for association criteria and then compare association thresholds with standardized association thresholds using some concrete examples.