• Title/Summary/Keyword: threshold methods

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Modeling Extreme Values of Ground-Level Ozone Based on Threshold Methods for Markov Chains

  • Seokhoon Yun
    • Communications for Statistical Applications and Methods
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    • v.3 no.2
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    • pp.249-273
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    • 1996
  • This paper reviews and develops several statistical models for extreme values, based on threshold methodology. Extreme values of a time series are modeled in terms of tails which are defined as truncated forms of original variables, and Markov property is imposed on the tails. Tails of the generalized extreme value distribution and a multivariate extreme value distributively, of the tails of the series. These models are then applied to real ozone data series collected in the Chicago area. A major concern is given to detecting any possible trend in the extreme values.

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Improving the Gumbel analysis by using M-th highest extremes

  • Cook, Nicholas J.
    • Wind and Structures
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    • v.1 no.1
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    • pp.25-42
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    • 1998
  • Improvements to the Gumbel method of extreme value analysis of wind data made over the last two decades are reviewed and illustrated using sample data for Jersey. A new procedure for extending the Gumbel method to include M-th highest annual extremes is shown to be less effective than the standard method, but leads to a method for calibrating peak-over-threshold methods against the standard Gumbel approach. Peak-over-threshold methods that include at least the 3rd highest annual extremes, specifically the modified Jensen and Franck method and the "Method of independent storms" are shown to give the best estimates of extremes from observations.

Algorithm Development and Experimental Verification of Acoustic Emission First-arrival-time Determination for the Source Location (정확한 미소파괴음의 발생위치 분석을 위한 신호 도달시간 결정 알고리즘 연구 및 실험적 검증)

  • Jang, Hyun-Sic;Choi, Jun-Young;Jang, Bo-An
    • The Journal of Engineering Geology
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    • v.25 no.4
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    • pp.587-598
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    • 2015
  • We examined various existing threshold methods for the determination of the first arrival time of acoustic emission (AE), and developed a new variable threshold method that could determine the first arrival time of AE more accurately and more quickly than existing methods. The new method, a modification of an existing threshold method, does not fix the threshold, but applies variable thresholds for the AE signals according to noise analysis. Two- and three-dimensional models were established to test the effectiveness of the new method. It could determine source locations of AE in a two-dimensional model 38.3% more accurately than the pre-existing threshold methods. Its accuracy improvement over the existing methods in a three-dimensional model was about 15.2%. A practical test involved measuring the source locations of AE during three-point bending tests of granite cores. The new method placed the sources closer to the fracture plane than did the pre-existing methods, indicating its superior (and quicker) ability to determine the source locations of AE.

Securing Mobile Ad Hoc Networks Using Enhanced Identity-Based Cryptography

  • Mehr, Kamal Adli;Niya, Javad Musevi
    • ETRI Journal
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    • v.37 no.3
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    • pp.512-522
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    • 2015
  • Recent developments in identity-based cryptography (IBC) have provided new solutions to problems related to the security of mobile ad hoc networks (MANETs). Although many proposals to solve problems related to the security of MANETs are suggested by the research community, there is no one solution that fits all. The interdependency cycle between secure routing and security services makes the use of IBC in MANETs very challenging. In this paper, two novel methods are proposed to eliminate the need for this cycle. One of these methods utilizes a key pool to secure routes for the distribution of cryptographic materials, while the other adopts a pairing-based key agreement method. Furthermore, our proposed methods utilize threshold cryptography for shared secret and private key generation to eliminate the "single point of failure" and distribute cryptographic services among network nodes. These characteristics guarantee high levels of availability and scalability for the proposed methods. To illustrate the effectiveness and capabilities of the proposed methods, they are simulated and compared against the performance of existing methods.

Adaptive Shot Change Detection using Mean of Feature Value on Variable Reference Blocks and Implementation on PMP

  • Kim, Jong-Nam;Kim, Won-Hee
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2009.01a
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    • pp.229-232
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    • 2009
  • Shot change detection is an important technique for effective management of video data, so detection scheme requires adaptive detection techniques to be used actually in various video. In this paper, we propose an adaptive shot change detection algorithm using the mean of feature value on variable reference blocks. Our algorithm determines shot change detection by defining adaptive threshold values with the feature value extracted from video frames and comparing the feature value and the threshold value. We obtained better detection ratio than the conventional methods maximally by 15% in the experiment with the same test sequence. We also had good detection ratio for other several methods of feature extraction and could see real-time operation of shot change detection in the hardware platform with low performance was possible by implementing it in TVUS model of HOMECAST Company. Thus, our algorithm in the paper can be useful in PMP or other portable players.

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Threshold Selection Method Based on the Distribution of Gray Levels (그레이 레벨의 분포에 기반한 임계값 결정법)

  • Kwon, Soon-H.;Son, Seo-H.;Bae, Jong-I.
    • Journal of the Korean Institute of Intelligent Systems
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    • v.13 no.6
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    • pp.649-654
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    • 2003
  • Most of the conventional image thresholding methods are based on the histogram function of the gray values. In this paper, we present a simple but effective example showing that the histogram-based thresholding methods do not perform well. To overcome the difficulty, the authors propose a new gray level threshold selection method based on the distribution of gray levels in images. Finally, we provide simulation results showing the effectiveness of the proposed threshold selection method through several examples.

Quantitative vibratory sense measurement systems of a diabetic neuropathy (당뇨병성 신경병증의 정량적 진동 감각 측정 시스템)

  • Ryu, Bong-Jo;Kim, Youngshik;Koo, Kyung-Wan
    • Journal of Digital Contents Society
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    • v.19 no.4
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    • pp.615-620
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    • 2018
  • Evaluation of clinical usefulness of current perception threshold test and vibration sense perception threshold test in diagnosing the diabetic poly-neuropathy patients is one of the diagnosis methods for diabetic poly-neuropathy. Up to the present, some diagnostic methods were used for diabetic poly neuropathy patients. For example, there are neuropathy impairment score test of lower limbs, nerve conduction test, cooling detection threshold test, heat-pain threshold test and so on. However, most of the above tests require very expensive cost and take a lot of time in test. In this paper, a new apparatus estimating vibration sense ability is introduced. For this purpose, the VCM(voice coil motor) stimulating patient's peripheral nerve and current amplifier were manufactured. Also, softwares sensing and driving the vibration detection threshold test in order to measure the quantitative vibration sensory levels in diabetic poly-neuropathy patients were developed.

Fish Injured Rate Measurement Using Color Image Segmentation Method Based on K-Means Clustering Algorithm and Otsu's Threshold Algorithm

  • Sheng, Dong-Bo;Kim, Sang-Bong;Nguyen, Trong-Hai;Kim, Dae-Hwan;Gao, Tian-Shui;Kim, Hak-Kyeong
    • Journal of Power System Engineering
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    • v.20 no.4
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    • pp.32-37
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    • 2016
  • This paper proposes two measurement methods for injured rate of fish surface using color image segmentation method based on K-means clustering algorithm and Otsu's threshold algorithm. To do this task, the following steps are done. Firstly, an RGB color image of the fish is obtained by the CCD color camera and then converted from RGB to HSI. Secondly, the S channel is extracted from HSI color space. Thirdly, by applying the K-means clustering algorithm to the HSI color space and applying the Otsu's threshold algorithm to the S channel of HSI color space, the binary images are obtained. Fourthly, morphological processes such as dilation and erosion, etc. are applied to the binary image. Fifthly, to count the number of pixels, the connected-component labeling is adopted and the defined injured rate is gotten by calculating the pixels on the labeled images. Finally, to compare the performances of the proposed two measurement methods based on the K-means clustering algorithm and the Otsu's threshold algorithm, the edge detection of the final binary image after morphological processing is done and matched with the gray image of the original RGB image obtained by CCD camera. The results show that the detected edge of injured part by the K-means clustering algorithm is more close to real injured edge than that by the Otsu' threshold algorithm.

Evaluation of DEM-based Channel Network Delineation Methods on Watershed Drainage System (DEM을 이용한 수로망 산정 기법에 따른 유역의 배수구조 평가)

  • Lee, Gi Ha;Yoon, Eui Hyeok;Kim, Joo Cheol;Jung, Kwan Sue
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.31 no.1B
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    • pp.1-11
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    • 2011
  • Channel network delineation from DEM (Digital Elevation Model) is a fundamental pre-process for hydrologic model application since it determines the drainage system in a watershed. This study aims to propose an effective and efficient channel network delineation process and assess the effects of DEM-based channel networks on the watershed drainage system. For these objectives, we applied two methods to generate the channel networks of the Jinan-cheon catchment with $18.28km^2$ from the 20 m resolution DEM: a widely-used area-threshold method and a slope-area threshold method based on the relationship between contributing areas and local slopes. The results showed that the area-threshold method led to unreliable drainage system, which did not satisfy geomorphological laws with respect to drainage density and source area representation whereas the slope-area threshold method provided acceptable results under the geomorphological laws. Our suggestions in this study can give valuable pre-processing information in DEM-based hydrologic modeling.

Anomaly Detection in Livestock Environmental Time Series Data Using LSTM Autoencoders: A Comparison of Performance Based on Threshold Settings (LSTM 오토인코더를 활용한 축산 환경 시계열 데이터의 이상치 탐지: 경계값 설정에 따른 성능 비교)

  • Se Yeon Chung;Sang Cheol Kim
    • Smart Media Journal
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    • v.13 no.4
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    • pp.48-56
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    • 2024
  • In the livestock industry, detecting environmental outliers and predicting data are crucial tasks. Outliers in livestock environment data, typically gathered through time-series methods, can signal rapid changes in the environment and potential unexpected epidemics. Prompt detection and response to these outliers are essential to minimize stress in livestock and reduce economic losses for farmers by early detection of epidemic conditions. This study employs two methods to experiment and compare performances in setting thresholds that define outliers in livestock environment data outlier detection. The first method is an outlier detection using Mean Squared Error (MSE), and the second is an outlier detection using a Dynamic Threshold, which analyzes variability against the average value of previous data to identify outliers. The MSE-based method demonstrated a 94.98% accuracy rate, while the Dynamic Threshold method, which uses standard deviation, showed superior performance with 99.66% accuracy.