• Title/Summary/Keyword: threshold methods

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Traffic Seasonality aware Threshold Adjustment for Effective Source-side DoS Attack Detection

  • Nguyen, Giang-Truong;Nguyen, Van-Quyet;Nguyen, Sinh-Ngoc;Kim, Kyungbaek
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.5
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    • pp.2651-2673
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    • 2019
  • In order to detect Denial of Service (DoS) attacks, victim-side detection methods are used popularly such as static threshold-based method and machine learning-based method. However, as DoS attacking methods become more sophisticated, these methods reveal some natural disadvantages such as the late detection and the difficulty of tracing back attackers. Recently, in order to mitigate these drawbacks, source-side DoS detection methods have been researched. But, the source-side DoS detection methods have limitations if the volume of attack traffic is relatively very small and it is blended into legitimate traffic. Especially, with the subtle attack traffic, DoS detection methods may suffer from high false positive, considering legitimate traffic as attack traffic. In this paper, we propose an effective source-side DoS detection method with traffic seasonality aware adaptive threshold. The threshold of detecting DoS attack is adjusted adaptively to the fluctuated legitimate traffic in order to detect subtle attack traffic. Moreover, by understanding the seasonality of legitimate traffic, the threshold can be updated more carefully even though subtle attack happens and it helps to achieve low false positive. The extensive evaluation with the real traffic logs presents that the proposed method achieves very high detection rate over 90% with low false positive rate down to 5%.

X-ray fluorescence spectrum of the block algorithm to apply the interval threshold method using DWT (DWT를 이용한 형광 X-선 스펙트럼의 interval Threshold를 적용하기 위한 블록화 알고리즘)

  • Yang, Sang-Hoon;Lee, Jae-Hwan;Park, Dong-Sun
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.13 no.5
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    • pp.2291-2297
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    • 2012
  • X-ray fluorescence sprectrum signal include the continuum. XRF analysis the components of material by the amplitude of peaks. XRF remove the noise and background. To remove the noise, we apply the smoothing filter. And background removal methods applied such as SNIP, Morphology, Threshold methods. In this paper, we applied Threshold using DWT. Interval threshold method divide the some blocks in particular levels. We propose the method that is divided the particular level.

A Study on Denoising Methods using Wavelet in AWGN environment (AWGN 환경에서 웨이브렛을 이용한 잡음 제거 방법에 관한 연구)

  • 배상범;김남호
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.5 no.5
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    • pp.853-860
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    • 2001
  • This paper presents the new two denoising methods using wavelet. One is new spatially selective noise filtration(NSSNF) using spatial correlation and the other is undecimated discrete wavelet transform (UDWT) threshold-based. NSSNF got the flexible gain special property of SNR adding new parameter at the existing SSNF and UDWT had superior denosing effect than orthogonal wavelet transform(OWT) applied soft-threshold by applied hard-threshold. We selected additive white gaussian noise(AWGN) in this test environment. Also we analyzed and compared ousting denoising method using SNR as standard of judgement of improvemental effect.

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Blur Detection through Multinomial Logistic Regression based Adaptive Threshold

  • Mahmood, Muhammad Tariq;Siddiqui, Shahbaz Ahmed;Choi, Young Kyu
    • Journal of the Semiconductor & Display Technology
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    • v.18 no.4
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    • pp.110-115
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    • 2019
  • Blur detection and segmentation play vital role in many computer vision applications. Among various methods, local binary pattern based methods provide reasonable blur detection results. However, in conventional local binary pattern based methods, the blur map is computed by using a fixed threshold irrespective of the type and level of blur. It may not be suitable for images with variations in imaging conditions and blur. In this paper we propose an effective method based on local binary pattern with adaptive threshold for blur detection. The adaptive threshold is computed based on the model learned through the multinomial logistic regression. The performance of the proposed method is evaluated using different datasets. The comparative analysis not only demonstrates the effectiveness of the proposed method but also exhibits it superiority over the existing methods.

Comparison of a hearing threshold level using a headphone (헤드폰을 이용한 가청역치레벨의 측정 방법 비교)

  • Kim, Deuk-Seong;Jang, Seol-Il;Kim, Dong-Jun;Lee, Yeon-Su
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2007.11a
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    • pp.796-801
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    • 2007
  • This research presents a laboratory study about a comparison between two methods that measure a hearing threshold of the Subjects who participated in an experiment of the Jury test. The Subjects heard a signal by a headphone. The Subjects of total 63 persons (man=42, woman=21 persons) participated in an experiment. A test of hearing was divided into two (Top-Down, Bottom-Up) methods. Total time of hearing test was about 80 minute(40min/day). As a results of the hearing test, a hearing threshold of the Subjects who used to wear a headphone was higher than that of the Subjects who not used to wear a headphone. A hearing threshold of a man was higher than that of a woman. The result of hearing test was showed that ISO's hearing threshold(MAF) was lower than a result that get from an experiment.

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Local Binary Pattern Based Defocus Blur Detection Using Adaptive Threshold

  • Mahmood, Muhammad Tariq;Choi, Young Kyu
    • Journal of the Semiconductor & Display Technology
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    • v.19 no.3
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    • pp.7-11
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    • 2020
  • Enormous methods have been proposed for the detection and segmentation of blur and non-blur regions of the images. Due to the limited available information about the blur type, scenario and the level of blurriness, detection and segmentation is a challenging task. Hence, the performance of the blur measure operators is an essential factor and needs improvement to attain perfection. In this paper, we propose an effective blur measure based on the local binary pattern (LBP) with the adaptive threshold for blur detection. The sharpness metric developed based on LBP uses a fixed threshold irrespective of the blur type and level which may not be suitable for images with large variations in imaging conditions and blur type and level. Contradictory, the proposed measure uses an adaptive threshold for each image based on the image and the blur properties to generate an improved sharpness metric. The adaptive threshold is computed based on the model learned through the support vector machine (SVM). The performance of the proposed method is evaluated using a well-known dataset and compared with five state-of-the-art methods. The comparative analysis reveals that the proposed method performs significantly better qualitatively and quantitatively against all the methods.

An Application of the Clustering Threshold Gradient Descent Regularization Method for Selecting Genes in Predicting the Survival Time of Lung Carcinomas

  • Lee, Seung-Yeoun;Kim, Young-Chul
    • Genomics & Informatics
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    • v.5 no.3
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    • pp.95-101
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    • 2007
  • In this paper, we consider the variable selection methods in the Cox model when a large number of gene expression levels are involved with survival time. Deciding which genes are associated with survival time has been a challenging problem because of the large number of genes and relatively small sample size (n<

Performance Analysis of Pulse Positioning Using Adaptive Threshold Detector (ATD)

  • Chang, Jae Won;Lee, Sang Jeong
    • Journal of Positioning, Navigation, and Timing
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    • v.7 no.1
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    • pp.25-35
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    • 2018
  • This paper describes the measurement of pulse positioning (input time) to calculate a time of arrival (TOA) that takes from transmitting a signal from the target of multilateration (MLAT) system to receiving the signal at the receiver. In this regard, this paper analyzes performances of simple threshold method and level adjust system (LAS) method, which is one of the adaptive threshold detector (ATD) methods, among many methods to calculate pulse positioning of signal received at the receiver. To this end, Cramer-rao lower bound (CRLB) with regard to pulse positioning, which was measured when signals transmitted from a transponder mounted at the target were received at the receiver, was induced and then deviation sizes with regard to pulse positioning, which was measured with simple threshold and LAS methods through MATLAB simulations, were compared. Next, problems occurring according to a difference in amplitude of signals inputted to each receiver are described when pulse positioning is measured at multiple receivers located at a different distance from the target as is the case in the MLAT system. Furthermore, LAS method to resolve the problems is explained. Lastly, this study analyzes whether a pulse positioning error occurring due to the signal noise satisfies the requirement (6 nsec. or lower) recommended for the MLAT system when using these two methods.

Comparison of Echogram Analysis Methods for Evaluating the Sound-scattering Layer (음향산란층의 식별을 위한 에코그램 분석 방법의 비교)

  • Choi, Seok-Gwan;Yoon, Eun-A;Han, Inwoo;Oh, Wooseok
    • Korean Journal of Fisheries and Aquatic Sciences
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    • v.49 no.6
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    • pp.856-861
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    • 2016
  • This study compared the density of fish determined using three different echogram methods: the frequency-difference, time variable, and threshold modification methods. An acoustic survey was conducted off the coast of Jeju Island after sunset. Data at 38 and 120 kHz frequencies were collected using a commercial fishing vessel. As a reference point, the value of ${\Delta}MVBS_{120-38kHz}$ that distinguished fish from zooplankton using the 38 and 120 kHz frequencies was set at < 2 dB. The estimated density of fish along the survey line was 0.1-30.4, 0.1-64.3, and $0.1-51.7m^2/nmi^2$ using the frequency difference, time variable threshold, and threshold modification methods, respectively. The results of this study constitute basic research for estimating fish densities.

THRESHOLD MODELING FOR BIFURCATING AUTOREGRESSION AND LARGE SAMPLE ESTIMATION

  • Hwang, S.Y.;Lee, Sung-Duck
    • Journal of the Korean Statistical Society
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    • v.35 no.4
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    • pp.409-417
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    • 2006
  • This article is concerned with threshold modeling of the bifurcating autoregressive model (BAR) originally suggested by Cowan and Staudte (1986) for tree structured data of cell lineage study where each individual $(X_t)$ gives rise to two off-spring $(X_{2t},\;X_{2t+1})$ in the next generation. The triplet $(X_t,\;X_{2t},\;X_{2t+1})$ refers to mother-daughter relationship. In this paper we propose a threshold model incorporating the difference of 'fertility' of the mother for the first and second off-springs, and thereby extending BAR to threshold-BAR (TBAR, for short). We derive a sufficient condition of stationarity for the suggested TBAR model. Also various inferential methods such as least squares (LS), maximum likelihood (ML) and quasi-likelihood (QL) methods are discussed and relevant limiting distributions are obtained.