• 제목/요약/키워드: Performance-based Statistics

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영상에서 선형순위검정법을 이용한 에지검출 비교 (Comparison of Edge Detection using Linear Rank Tests in Images)

  • 임동훈
    • 한국컴퓨터정보학회논문지
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    • 제10권6호
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    • pp.17-26
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    • 2005
  • 본 논문에서는 통계학의 선형순위통계량(linear rank statistics)에 기초한 3가지 비모수 검정법 즉. Wilcoxon 검정법, Median 검정법 그리고 Van der Waerden 검정법을 이용하여 에지를 검출하고자 한다. 5$\times$5 윈도우상에서 중심픽셀의 에지여부는 에지-높이 모수(edge-height parameter)를 사용한 모형 하에서 두 영역간의 유의한 차이가 있는지를 검정함으로서 결정한다. 영상실험에서 통계적 방법들 간의 에지검출 성능은 에지맵(edge map)을 통한 정성적인 비교와 객관적인 척도 하에서 정량적인 비교를 통하여 분석하였다.

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Long-Term Forecasting by Wavelet-Based Filter Bank Selections and Its Application

  • Lee, Jeong-Ran;Lee, You-Lim;Oh, Hee-Seok
    • 응용통계연구
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    • 제23권2호
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    • pp.249-261
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    • 2010
  • Long-term forecasting of seasonal time series is critical in many applications such as planning business strategies and resolving possible problems of a business company. Unlike the traditional approach that depends solely on dynamic models, Li and Hinich (2002) introduced a combination of stochastic dynamic modeling with filter bank approach for forecasting seasonal patterns using highly coherent(High-C) waveforms. We modify the filter selection and forecasting procedure on wavelet domain to be more feasible and compare the resulting predictor with one that obtained from the wavelet variance estimation method. An improvement over other seasonal pattern extraction and forecasting methods based on such as wavelet scalogram, Holt-Winters, and seasonal autoregressive integrated moving average(SARIMA) is shown in terms of the prediction error. The performance of the proposed method is illustrated by a simulation study and an application to the real stock price data.

New approach for analysis of progressive Type-II censored data from the Pareto distribution

  • Seo, Jung-In;Kang, Suk-Bok;Kim, Ho-Yong
    • Communications for Statistical Applications and Methods
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    • 제25권5호
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    • pp.569-575
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    • 2018
  • Pareto distribution is important to analyze data in actuarial sciences, reliability, finance, and climatology. In general, unknown parameters of the Pareto distribution are estimated based on the maximum likelihood method that may yield inadequate inference results for small sample sizes and high percent censored data. In this paper, a new approach based on the regression framework is proposed to estimate unknown parameters of the Pareto distribution under the progressive Type-II censoring scheme. The proposed method provides a new regression type estimator that employs the spacings of exponential progressive Type-II censored samples. In addition, the provided estimator is a consistent estimator with superior performance compared to maximum likelihood estimators in terms of the mean squared error and bias. The validity of the proposed method is assessed through Monte Carlo simulations and real data analysis.

새로운 이미지 거리를 통한 이미지 검색 방안 연구 (Study of the New Distance for Image Retrieval)

  • 이성임;임요한;조영민
    • 대한산업공학회지
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    • 제40권4호
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    • pp.382-387
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    • 2014
  • Image retrieval is a procedure to find images based on the resemblance between query image and all images. In retrieving images, the crucial step that arises is how to define the similarity between images. In this paper, we propose a new similarity measure which is based on distribution of color. We apply the new measure to retrieving two different types of images, wallpaper images and the logo of automobiles, and compare its performance to other existing similarity measures.

Improving Security in Ciphertext-Policy Attribute-Based Encryption with Hidden Access Policy and Testing

  • Yin, Hongjian;Zhang, Leyou;Cui, Yilei
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제13권5호
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    • pp.2768-2780
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    • 2019
  • Ciphertext-policy attribute-based encryption (CP-ABE) is one of the practical technologies to share data over cloud since it can protect data confidentiality and support fine-grained access control on the encrypted data. However, most of the previous schemes only focus on data confidentiality without considering data receiver privacy preserving. Recently, Li et al.(in TIIS, 10(7), 2016.7) proposed a CP-ABE with hidden access policy and testing, where they declare their scheme achieves privacy preserving for the encryptor and decryptor, and also has high decryption efficiency. Unfortunately, in this paper, we show that their scheme fails to achieve hidden access policy at first. It means that any adversary can obtain access policy information by a simple decisional Diffie-Hellman test (DDH-test) attack. Then we give a method to overcome this shortcoming. Security and performance analyses show that the proposed scheme not only achieves the privacy protection for users, but also has higher efficiency than the original one.

Monitoring the asymmetry parameter of a skew-normal distribution

  • Hyun Jun Kim;Jaeheon Lee
    • Communications for Statistical Applications and Methods
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    • 제31권1호
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    • pp.129-142
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    • 2024
  • In various industries, especially manufacturing and chemical industries, it is often observed that the distribution of a specific process, initially having followed a normal distribution, becomes skewed as a result of unexpected causes. That is, a process deviates from a normal distribution and becomes a skewed distribution. The skew-normal (SN) distribution is one of the most employed models to characterize such processes. The shape of this distribution is determined by the asymmetry parameter. When this parameter is set to zero, the distribution is equal to the normal distribution. Moreover, when there is a shift in the asymmetry parameter, the mean and variance of a SN distribution shift accordingly. In this paper, we propose procedures for monitoring the asymmetry parameter, based on the statistic derived from the noncentral t-distribution. After applying the statistic to Shewhart and the exponentially weighted moving average (EWMA) charts, we evaluate the performance of the proposed procedures and compare it with previously studied procedures based on other skewness statistics.

대안적인 분류기준: 오분류율곱 (Alternative Optimal Threshold Criteria: MFR)

  • 홍종선;김효민;김동규
    • 응용통계연구
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    • 제27권5호
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    • pp.773-786
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    • 2014
  • 본 연구는 ROC 곡선에서 형성되는 면적 형태로 나타나는 분류정확도기준인 오분류율곱(multiplication of false rates; MFR)를 제안한다. MFR 기준과 다른 기준로부터 구한 최적분류점의 분류성과에 대하여 비교 분석한다. 다양한 분포함수에 대하여 최적분류점을 구하고 이에 대응하는 FNR과 FPR을 비교하면서 MFR의 특징과 장점을 유도한다. 일반적인 비용함수를 바탕으로 분류점에 대한 비용비율을 다양한 분류기준을 이용하여 구한다. 비용곡선에 대한 비용비율의 관계를 정리하여 MFR 기준의 장점을 탐색한다. MFR 기준의 정의를 다차원 ROC 분석으로 확장하고 다차원의 다른 분류기준과의 관계를 설명하면서 토론한다.

디지털영상 국부정규화처리의 영역분할 구도 (Region-Segmental Scheme in Local Normalization Process of Digital Image)

  • 황중원;황재호
    • 대한전자공학회논문지SP
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    • 제44권4호통권316호
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    • pp.78-85
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    • 2007
  • 영역들로 구성된 영상의 국부정규화처리 알고리즘에 내재된 분할 구도를 소개한다. 이동창에서 산출되는 국부통계치에 근거한 정규화적 접근은 선형 또는 비선형함수를 발생시켜 잡음 오염된 영역들의 화소분포와 근접유사 유형을 변형한다. 현재와 정규화된 영상신호 사이의 최근접 화소 이격거리에 대하여 평균과 표준편차를 조정하고 국부통계치와 파리미터 변동을 연계하여 영역간 분할 상태를 변화시킨다. 이러한 특성에 대하여 기존의 정규화 기법들과 본 연구에서 새로 고안한 국부정규화 기법이 비교 고찰된다. 그리고 실험결과는 국부정규화처리 실현에 의한 영역분할 성능을 보였다.

파라미터 설계에 대한 최적화 대체방안 (Alternative Optimization Procedure to Parameter Design)

  • 권용만;장덕준
    • Journal of the Korean Data and Information Science Society
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    • 제12권1호
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    • pp.11-18
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    • 2001
  • 다구찌가 제안한 파라미터 설계는 제품설계나 공정설계 단계에서 품질특성치의 수행변동(performance variation)을 줄이는데 있다. 파라미터 설계에서 품질평균 근처에서 품질의 변동을 줄일 수 있는 최적조건을 찾는데 있어서 신호대 잡음비(Signal-to-noise ratio; SN비)라는 수행측도(performance measure)를 사용하였다. 그러나 많은 통계학자들은 SN비를 이용한 다구찌 분석 기법을 비판한다. 본 논문에서는 파라미터 설계를 위한 최적조건을 찾는데 있어서 SN비를 사용하지 않는 보다 실질적인 최적방안을 제안한다.

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An Empirical Study on Dimension Reduction

  • Suh, Changhee;Lee, Hakbae
    • Journal of the Korean Data Analysis Society
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    • 제20권6호
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    • pp.2733-2746
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    • 2018
  • The two inverse regression estimation methods, SIR and SAVE to estimate the central space are computationally easy and are widely used. However, SIR and SAVE may have poor performance in finite samples and need strong assumptions (linearity and/or constant covariance conditions) on predictors. The two non-parametric estimation methods, MAVE and dMAVE have much better performance for finite samples than SIR and SAVE. MAVE and dMAVE need no strong requirements on predictors or on the response variable. MAVE is focused on estimating the central mean subspace, but dMAVE is to estimate the central space. This paper explores and compares four methods to explain the dimension reduction. Each algorithm of these four methods is reviewed. Empirical study for simulated data shows that MAVE and dMAVE has relatively better performance than SIR and SAVE, regardless of not only different models but also different distributional assumptions of predictors. However, real data example with the binary response demonstrates that SAVE is better than other methods.