• 제목/요약/키워드: total variation metrics

검색결과 6건 처리시간 0.017초

SECOND ORDER REGULAR VARIATION AND ITS APPLICATIONS TO RATES OF CONVERGENCE IN EXTREME-VALUE DISTRIBUTION

  • Lin, Fuming;Peng, Zuoxiang;Nadarajah, Saralees
    • 대한수학회보
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    • 제45권1호
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    • pp.75-93
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    • 2008
  • The rate of convergence of the distribution of order statistics to the corresponding extreme-value distribution may be characterized by the uniform and total variation metrics. de Haan and Resnick [4] derived the convergence rate when the second order generalized regularly varying function has second order derivatives. In this paper, based on the properties of the generalized regular variation and the second order generalized variation and characterized by uniform and total variation metrics, the convergence rates of the distribution of the largest order statistic are obtained under weaker conditions.

A Comparison of the Rudin-Osher-Fatemi Total Variation model and the Nonlocal Means Algorithm

  • ;최흥국
    • 한국멀티미디어학회:학술대회논문집
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    • 한국멀티미디어학회 2012년도 춘계학술발표대회논문집
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    • pp.6-9
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    • 2012
  • In this study, we compare two image denoising methods which are the Rudin-Osher-Fatemi total variation (TV) model and the nonlocal means (NLM) algorithm on medical images. To evaluate those methods, we used two well known measuring metrics. The methods are tested with a CT image, one X-Ray image, and three MRI images. Experimental result shows that the NML algorithm can give better results than the ROF TV model, but computational complexity is high.

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6 시그마의 적용에 대한 연구 (An Application Study of Six Sigma in Clinical Chemistry)

  • 장상우;김남용;최호성;박용원;추경복;윤근영
    • 대한임상검사과학회지
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    • 제36권2호
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    • pp.121-126
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    • 2004
  • The primary goal of six sigma is to improve patient satisfaction, and thereby profitability, by reducing and eliminating defects. Defects may be related to any aspect of customer satisfaction: high product quality, schedule adherence, cost minimization, process capability indices, defects per unit, and yield. Many six sigma metrics can be mathematically related to the others. Literally, six means six standard deviations from the mean or median value. As applied to quality metrics, the term indicates that failures are at least six standard deviations from the mean or norm. This would mean about 3.4 failures per million opportunities for failure. The objective of six sigma quality is to reduce process output variation so that on a long term basis, which is the customer's aggregate experience with our process over time, this will result in no more than 3.4 defect Parts Per Million(PPM) opportunities (or 3.4 Defects Per Million Opportunities. For a process with only one specification limit (upper or lower), this results in six process standard deviations between the mean of the process and the customer's specification limit (hence, 6 Sigma). The results of applicative six sigma experiment studied on 18 items TP, ALB, T.B, ALP, AST, ALT, CL, CK, LD, K, Na, CRE, BUN, T.C, GLU, AML, CA tests in clinical chemistry were follows. Assessment of process performance fits within six sigma tolerance limits were TP, ALB, T.B, ALP, AST, ALT, CL, CK, LD, K, Na, CRE, BUN, T.C, GLU, AML, CA with 72.2%, items that fit within five sigma limits were total bilirubin, chloride and sodium were 3 sigma. We were sure that the goal of six sigma would reduce test variation in the process.

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6 시그마와 총 오차 허용범위의 개발에 대한 연구 (A Study of Six Sigma and Total Error Allowable in Chematology Laboratory)

  • 장상우;김남용;최호성;김영환;추경복;정혜진;박병옥
    • 대한임상검사과학회지
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    • 제37권2호
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    • pp.65-70
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    • 2005
  • Those specifications of the CLIA analytical tolerance limits are consistent with the performance goals in Six Sigma Quality Management. Six sigma analysis determines performance quality from bias and precision statistics. It also shows if the method meets the criteria for the six sigma performance. Performance standards calculates allowable total error from several different criteria. Six sigma means six standard deviations from the target value or mean value and about 3.4 failures per million opportunities for failure. Sigma Quality Level is an indicator of process centering and process variation total error allowable. Tolerance specification is replaced by a Total Error specification, which is a common form of a quality specification for a laboratory test. The CLIA criteria for acceptable performance in proficiency testing events are given in the form of an allowable total error, TEa. Thus there is a published list of TEa specifications for regulated analytes. In terms of TEa, Six Sigma Quality Management sets a precision goal of TEa/6 and an accuracy goal of 1.5 (TEa/6). This concept is based on the proficiency testing specification of target value +/-3s, TEa from reference intervals, biological variation, and peer group median mean surveys. We have found rules to calculate as a fraction of a reference interval and peer group median mean surveys. We studied to develop total error allowable from peer group survey results and CLIA 88 rules in US on 19 items TP, ALB, T.B, ALP, AST, ALT, CL, LD, K, Na, CRE, BUN, T.C, GLU, GGT, CA, phosphorus, UA, TG tests in chematology were follows. Sigma level versus TEa from peer group median mean CV of each item by group mean were assessed by process performance, fitting within six sigma tolerance limits were TP ($6.1{\delta}$/9.3%), ALB ($6.9{\delta}$/11.3%), T.B ($3.4{\delta}$/25.6%), ALP ($6.8{\delta}$/31.5%), AST ($4.5{\delta}$/16.8%), ALT ($1.6{\delta}$/19.3%), CL ($4.6{\delta}$/8.4%), LD ($11.5{\delta}$/20.07%), K ($2.5{\delta}$/0.39mmol/L), Na ($3.6{\delta}$/6.87mmol/L), CRE ($9.9{\delta}$/21.8%), BUN ($4.3{\delta}$/13.3%), UA ($5.9{\delta}$/11.5%), T.C ($2.2{\delta}$/10.7%), GLU ($4.8{\delta}$/10.2%), GGT ($7.5{\delta}$/27.3%), CA ($5.5{\delta}$/0.87mmol/L), IP ($8.5{\delta}$/13.17%), TG ($9.6{\delta}$/17.7%). Peer group survey median CV in Korean External Assessment greater than CLIA criteria were CL (8.45%/5%), BUN (13.3%/9%), CRE (21.8%/15%), T.B (25.6%/20%), and Na (6.87mmol/L/4mmol/L). Peer group survey median CV less than it were as TP (9.3%/10%), AST (16.8%/20%), ALT (19.3%/20%), K (0.39mmol/L/0.5mmol/L), UA (11.5%/17%), Ca (0.87mg/dL1mg/L), TG (17.7%/25%). TEa in 17 items were same one in 14 items with 82.35%. We found out the truth on increasing sigma level due to increased total error allowable, and were sure that the goal of setting total error allowable would affect the evaluation of sigma metrics in the process, if sustaining the same process.

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An Analytic solution for the Hadoop Configuration Combinatorial Puzzle based on General Factorial Design

  • Priya, R. Sathia;Prakash, A. John;Uthariaraj, V. Rhymend
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제16권11호
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    • pp.3619-3637
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    • 2022
  • Big data analytics offers endless opportunities for operational enhancement by extracting valuable insights from complex voluminous data. Hadoop is a comprehensive technological suite which offers solutions for the large scale storage and computing needs of Big data. The performance of Hadoop is closely tied with its configuration settings which depends on the cluster capacity and the application profile. Since Hadoop has over 190 configuration parameters, tuning them to gain optimal application performance is a daunting challenge. Our approach is to extract a subset of impactful parameters from which the performance enhancing sub-optimal configuration is then narrowed down. This paper presents a statistical model to analyze the significance of the effect of Hadoop parameters on a variety of performance metrics. Our model decomposes the total observed performance variation and ascribes them to the main parameters, their interaction effects and noise factors. The method clearly segregates impactful parameters from the rest. The configuration setting determined by our methodology has reduced the Job completion time by 22%, resource utilization in terms of memory and CPU by 15% and 12% respectively, the number of killed Maps by 50% and Disk spillage by 23%. The proposed technique can be leveraged to ease the configuration tuning task of any Hadoop cluster despite the differences in the underlying infrastructure and the application running on it.

남양호에서 다변수 메트릭 모델 적용 및 평가 (Applications and Assessments of a Multimetric Model to Namyang Reservoir)

  • 한정호;안광국
    • 생태와환경
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    • 제41권2호
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    • pp.228-236
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    • 2008
  • 본 연구에서는 어류 메트릭 속성을 이용한 우리나라의 정수생태계 건강성평가 모델을 적용하기 위하여 국내 인공호인 남양호를 대상으로 2005년 10월과 2006년 5월 2차례에 걸쳐 생태 건강성 평가를 실시하였다. LEHA 모델은 생물학적 변수, 물리적 변수, 화학적 변수를 포함한 총 11개의 메트릭으로 구성되어 있다. 상기 변수의 시공간적인 분석을 위해 남양호의 상류부에서 하류부까지 6개의 지점을 선정하였다. 남양호의 생태 건강성 평가 결과 내성종($M_3$)이 80%로 나타났으며, 잡식종($M_4$)이 92%로 나타나 섭식구조의 단순화로 인하여 내성종과 잡식종의 우점현상을 보였으며, 특히 외래종의 상대 풍부도($M_7$)가 8%로 나타나 생태계가 교란되어 생태건강성이 크게 악화된 것으로 나타났다. 상기 LEHA 다변수 모델을 이용한 남양호의 생태 건강성 평가 결과, 생태 건강성 지수의 평균값은 24.3(n=12)으로서 안과 한(2007)의 등급에 의거하였을 때 "악화상태"로 나타났다. 지점별 LEHA 모델값은 $21{\sim}26$의 변이를 보여 낮은 건강성을 갖는 것으로 나타났으며, 장마철 집중강우에 의하여 시간적인 변이가 발생되었다. 전기전도도와 엽록소-$\alpha$를 이용한 부영양화지수(TSI)는 장마 후보다 장마 전에 더 높게 나타났다.