• Title/Summary/Keyword: weighted sum

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Complete convergence for weighted sums of AANA random variables

  • Kim, Tae-Sung;Ko, Mi-Hwa
    • Proceedings of the Korean Statistical Society Conference
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    • 2002.11a
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    • pp.209-213
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    • 2002
  • We study maximal second moment inequality and derive complete convergence for weighted sums of asymptotically almost negatively associated(AANA) random variables by applying this inequality. 2000 Mathematics Subject Classification : 60F05

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Inference Network-Based Retrieval Model for Web Search Environment (웹 검색 환경에 적용할 추론 망 기반 검색모델)

  • 최익규;김민구
    • Proceedings of the Korean Information Science Society Conference
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    • 2001.10b
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    • pp.19-21
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    • 2001
  • 대다수의 사용자는 웹 검색에서 자신이 찾고자 하는 것을 표현할 때, 평균 2, 3개의 단어를 사용하고 있다. 벡터 모델이나 추론 망 모델에서 이런 질의 정보를 이용하여 좋은 결과를 얻기에는 몇 가지 어려움이 있다. 특히 추론 망 모델에서 많이 사용되는 유사도 계산식인 weighted-sum방법은 질의에 나타나는 단어의 수가 적고 많은 문서들이 이 단어들을 모두 가지고 있을 경우에 좋지 않은 검색결과를 보여주고 있다. 본 논문은 추론 망 모델에 적용되는 유사도 계산식인 weighted-sum방법을 개선하였고, 이를 기반으로 Web Trec 9의 자료를 검색하여 좋은 결과를 얻었다.

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Cumulative Weighted Score Control Schemes for Controlling the Mean of a Continuous Production Process

  • Park, Byoung-Chul;Park, Sung H.
    • Journal of the Korean Statistical Society
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    • v.18 no.2
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    • pp.135-148
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    • 1989
  • Cumulative sum schemes based on a weighted score are considered for controlling the mean of a continuous production process; in which both the one-sided and two-sided schemes are proposed. The average run lengths and the run length distributions for the proposed schemes are obtained by the Markov chain approach. Comparisons by the average run length show that the proposed schemes perform nearly as well as the standard cumulative sum schemes in detecting changes in the process mean. Comparisons of the one-sided schemes by the run length distribution are also presented.

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Scheduling with regard to start lag in process group (공정 그룹별 Start lag을 고려한 스케쥴링)

  • 전태준;박성호
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 1996.10a
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    • pp.299-302
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    • 1996
  • The purpose of this study is developing scheduling logic and program for machining scheduling of automobile part production line with unbalanced processing time. Three rules are developed to minimize slack and effect on other job. Fourth rule is suggested which considered weighted sum of three factors. schedule is generated totally 1, 000 times and then optimal weight parameter is selected. The program is developed to schedule situation to compare with the performance measure, total finish time of machine and total tardiness of part. As a result, the rule which considered weighted sum of three factors is effective for both measure.

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COMPLETE CONVERGENCE FOR ARRAYS OF ROWWISE ASYMPTOTICALLY NEGATIVELY ASSOCIATED RANDOM VARIABLES

  • Kim, Hyun-Chull
    • Journal of the Chungcheong Mathematical Society
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    • v.30 no.4
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    • pp.411-422
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    • 2017
  • Let {$X_{ni}$, $i{\geq}1$, $n{\geq}1$} be an array of rowwise asymptotically negatively associated random variables and {$a_{ni}$, $i{\geq}1$, $n{\geq}1$} an array of constants. Some results concerning complete convergence of weighted sums ${\sum}_{i=1}^{n}a_{ni}X_{ni}$ are obtained. They generalize some previous known results for arrays of rowwise negatively associated random variables to the asymptotically negative association case.

Searching Algorithms for Protein Sequences and Weighted Strings (단백질 시퀀스와 가중치 스트링에 대한 탐색 알고리즘)

  • Kim, Sung-Kwon
    • Journal of KIISE:Computer Systems and Theory
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    • v.29 no.8
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    • pp.456-462
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    • 2002
  • We are developing searching algorithms for weighted strings such as protein sequences. Let${\sum}$ be an alphabet and for each $a{\in}{\sum}$ its weight ${\mu}(a)$ is given. Given a string $A=a_1a_2…a_n\; with each ai{\in}{\sum}$, a substring<$A(i.j)=a_ia_{i+1}…a_j$ has weight ${\in}(A(i.j))={\in}(a_i)+{\in}(a_i+1)+…+{\in}(a_j)$.The problem we are dealing with is to preprocess A to build a searching structure, and later, given a query weight M, the structure is used to answer the question of whether there is a substring A(i,j) such that$M={\in}(A(i,j))$.In this paper an algorithm that improves over the previous result will be presented. The previously best known algorithm answers a query in $0(\frac{nlog\;logn}{log\; n})$time using a searching structure that requires O(n) amount of memory. Our algorithm reduces the memory requirement to $0(\frac{n}{log\; n})$ while achieving the same query answer time.

Weighted Least Absolute Error Estimation of Regression Parameters

  • Song, Moon-Sup
    • Journal of the Korean Statistical Society
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    • v.8 no.1
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    • pp.23-36
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    • 1979
  • In the multiple linear regression model a class of weighted least absolute error estimaters, which minimize the sum of weighted absolute residuals, is proposed. It is shown that the weighted least absolute error estimators with Wilcoxon scores are equivalent to the Koul's Wilcoxon type estimator. Therefore, the asymptotic efficiency of the proposed estimator with Wilcoxon scores relative to the least squares estimator is the same as the Pitman efficiency of the Wilcoxon test relative to the Student's t-test. To find the estimates the iterative weighted least squares method suggested by Schlossmacher is applicable.

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Fall Recognition Algorithm Using Gravity-Weighted 3-Axis Accelerometer Data (3축 가속도 센서 데이터에 중력 방향 가중치를 사용한 낙상 인식 알고리듬)

  • Kim, Nam Ho;Yu, Yun Seop
    • Journal of the Institute of Electronics and Information Engineers
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    • v.50 no.6
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    • pp.254-259
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    • 2013
  • A newly developed fall recognition algorithm using gravity weighted 3-axis accelerometer data as the input of HMM (Hidden Markov Model) is introduced. Five types of fall feature parameters including the sum vector magnitude(SVM) and a newly-defined gravity-weighted sum vector magnitude(GSVM) are applied to a HMM to evaluate the accuracy of fall recognition. A GSVM parameter shows the best accuracy of falls which is 100% of sensitivity and 97.96% of specificity, and comparing with SVM, the results archive more improved recognition rate, 5.2% of sensitivity and 4.5% of specificity. GSVM shows higher recognition rate than SVM due to expressing falls characteristics well, whereas SVM expresses the only momentum.

Iterative Weighted MMSE Beamforming for Downlink multiuser MISO System (하향링크 다중사용자 다중안테나 시스템을 지원하는 반복 가중치 최소평균자승오류 빔형성 기법)

  • Choi, Ilgyu;Hwang, Youngsoo;Lee, Chungyong
    • Journal of the Institute of Electronics and Information Engineers
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    • v.50 no.3
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    • pp.3-8
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    • 2013
  • Conventional MMSE beamforming scheme shows better performance than ZF or MF beamforming, but it does not aim increase of sum rate. This paper proposes sum rate maximizing scheme by representing sum rate as a function of weighted MSE. Proposed scheme increases sum rate iteratively by updating weights and beam whose initial form is conventional MMSE beam. Simulation result shows sum rate of proposed scheme is higher than those of conventional schemes and increases as the number of users increases.