CHAPTER 18 Management of WAITING LINES KEY IDEAS 1. Waiting lines are an important consideration in capacity planning. Waiting lines tie up additional resources (waiting space‚ time‚ etc.); they decrease the level of customer service: and they require additional capacity to reduce them. 2. Waiting lines occur whenever demand for service exceeds capacity (supply). Even in systems that are underloaded‚ waiting lines tend to form if arrival and service patterns are highly variable because
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arrive at an average interval of 2 minutes. The unloading time is distributed exponentially and the arrival rate follows a Poisson distribution. a. What is the average number of trucks and the average time per truck in the system? b. What is the probability that more than 3 trucks are in the system? c. The farmers use the storage bin only for 2 weeks per year. They estimate that enlarging the storage bin would speed up the unloading process. The estimated unloading time is 80 seconds on average
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Fast and Robust Fixed-Point Algorithms for Independent Component Analysis Aapo Hyvärinen Helsinki University of Technology Laboratory of Computer and Information Science P.O. Box 5400‚ FIN-02015 HUT‚ Finland Email: aapo.hyvarinen@@hut.fi IEEE Trans. on Neural Networks‚ 10(3):626-634‚ 1999. Abstract Independent component analysis (ICA) is a statistical method for transforming an observed multidimensional random vector into components that are statistically as independent from each other as possible
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campus have. Additionally‚ some MBA students may have longer classes than the typical undergad student‚ especially on weekends. The MBA students may be more inclined to buy more food to save and snack on during class sessions. The retention probability through a certain time “r” is expected to be higher for undergrad students who live on or closer to campus and can easily walk to the sandwich shop. MBA students still have a high retention rate‚ but following the completion of their MBA program
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Psychology Theories of Personality 7th Edition Feist−Feist =>? McGraw-Hill McGraw−Hill Primis ISBN−10: 0−39−043533−3 ISBN−13: 978−0−39−043533−0 Text: Theories of Personality‚ Seventh Edition Feist−Feist This book was printed on recycled paper. Psychology http://www.primisonline.com Copyright ©2008 by The McGraw−Hill Companies‚ Inc. All rights reserved. Printed in the United States of America. Except as permitted under the United States Copyright Act of 1976‚ no part of
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ECE 4110: Random Signals in Communications and Signal Processing ECE department‚ Cornell University‚ Fall 2013 Homework 2 Due September 20 at 5:00 p.m. 1. (Chebyshev Inequality) Let X1 ‚ . . .‚ X be independent Geometric random variables with parameters p1 ‚ . . . ‚ p respectively (i.e.‚ P (Xi = k) = pi (1 − pi )k−1 ‚ k = 1‚ 2‚ . . .). Let random variable X to be X= i=1 Xi . (a) Find µX = E[X]. (b) Apply the Chebyshev inequality to upper bound P (|X − µX | > a). Evaluate your upper bound
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References: Lindeberg‚ J.W. (1922). “Eine neue Herleitung des Exponentialgesetzes in der Wahrscheinlichkeitsrechnung.” Mathemat. Z.‚ 15‚ 211-225. Thomasian‚ A. (1969). The Structure of Probability Theory with Applications. Mc Graw Hill‚ New York. (pp. 483-493) 8
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nEp (X1 ) + (n2 − n)Ep (X1 X2 ) = np + (n2 − n)p2 . 1≤i̸=j≤n Hence Ep (θ) = p2 + p(1 − p)/n ̸= p2 ‚ i.e θ is a biased estimator for θ with bias p(1 − p)/n. ∗ ∗ (d) We draw bootstrap sample X1 ‚ · · · ‚ Xn from Bernoulli distribution with probability p. Define the ∗ ∗ ∗ 2 bootstrap estimator θ = (X1 + · · · + Xn ) /n2 . The bootstrap estimator for the bias of θ is Bias∗ ≡ Ep (θ∗ ) − θ. In practice‚ Ep (θ∗ ) may be estimated via repeated bootstrap samplings. Note. For this simple example
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Theories and Hypotheses: The Differences and Similarities Abstract This paper is an examination of theories and hypotheses‚ their differences and similarities. The four major types of theories studied are Deductive‚ Inductive‚ Grounded and Axiomatic. Each type of theories is introduced and explained. Additionally‚ a hypothesis is defined in relation to a theory‚ and the key differences between the two explained. The variables which exist between the theories
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Summary of Forecasting Profitability and Earnings In the competitive environment‚ there is a strong prediction in economic theory that profitability is mean reversion both within and across industries. For instance‚ under competition‚ firms will leave relatively profitless industries and turn into relatively high profitable industries. Some companies introduce new products and technologies that bring more profitability for an entrepreneur. Otherwise‚ the expectation of failure which makes companies
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