w c mckern and the midwestern taxonomic method

university alabama press w c mckern and the midwestern taxonomic method nov 2002

university alabama press w c mckern and the midwestern taxonomic method nov 2002

... W C McKern and the Midwestern Taxonomic Method Classics in Southeastern Archaeology Stephen Williams, Series Editor W C McKern and the Midwestern Taxonomic Method R Lee Lyman and Michael ... Preface and Acknowledgments xi PART I: W C McKern and the Midwestern Taxonomic Method Introduction Taxonomic Classi¤cation and Biological Taxonomy 13 Developing the Midwestern Taxonomic Method, ... Application of the Midwestern Taxonomic Method W C McKern (1940) 262 17 Taxonomy and the Direct Historical Approach W C McKern (1942) 267 18 Regarding Midwestern Archaeological Taxonomy W C McKern (1943)...

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Pro c# 2010 and the  NET 4 platform, troelsen, 5ed, apress, 2010

Pro c# 2010 and the NET 4 platform, troelsen, 5ed, apress, 2010

... programmers can avoid the need to work with raw sockets, RPC calls, and other low-level details when building a distributed application For example, consider the following VB6 COM client code: ' The MyCOMClass ... only way NET and COM types can interact with each other is using the interoperability layer Introducing the Building Blocks of the NET Platform (the CLR, CTS, and CLS) Now that you know some of the ... MyCOMClass class could have be written in ' any COM-aware language, and may be located anywhere ' on the network (including your local machine) Dim obj as MyCOMClass Set obj = New MyCOMClass ' Location...

Ngày tải lên: 04/10/2013, 14:07

1,8K 682 1
Tài liệu Báo cáo khoa học: Adaptive changes in the expression of nuclear and mitochondrial encoded subunits of cytochrome c oxidase and the catalytic activity during hypoxia pptx

Tài liệu Báo cáo khoa học: Adaptive changes in the expression of nuclear and mitochondrial encoded subunits of cytochrome c oxidase and the catalytic activity during hypoxia pptx

... genes CytOX5a and CytOX5b, coding for the two isofoms Va and Vb, parallels that of genes CYC1 and CYC7, which encode iso-1 and iso-2 of yeast cytochrome c, respectively CytOX 5a and CYC1 are coexpressed ... of h Collection of cells and fractionation At the end of the culture period, the cells were rapidly chilled on ice and were rinsed twice with ice cold NaCl/Pi to remove any residual, media, and ... nonspeci c and toxic effects in animals To ascertain that the effects of these agents, on the catalytic activity and subunit composition of CytOX were related to their hypoxia-speci c effects, we have...

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Báo cáo " A combination of the identification algorithm and the modal superposition method for feedback active control of incomplete measured systems " doc

Báo cáo " A combination of the identification algorithm and the modal superposition method for feedback active control of incomplete measured systems " doc

... measuring the displacement of a certain point of the beam Because the velocity can be calculated from the displacement, the measurement vector contains components: the displacement and the velocity ... xck ] ( t ) = Λ c xck ] ( t ) + uck ] ( t ) + f c[ k ] ( t ) Using (10), we have [ [ [ f c[ k ] ( t ) = Cc−1 y[k ] ( t ) − Cc−1Cr xrk ] ( t ) − Λ c Cc−1 y[k ] ( t ) + Λ c Cc−1Cr xrk ] ( t ) − uck ... The effects of the time delay and the location of sensor are considered Acknowledgements The paper is based on the talk given at the Conference on Mathematics, Mechanics, and Informatics, Hanoi,...

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Báo cáo " A combination of the identification algorithm and the modal superposition method for feedback active control of incomplete measured systems" doc

Báo cáo " A combination of the identification algorithm and the modal superposition method for feedback active control of incomplete measured systems" doc

... measuring the displacement of a certain point of the beam Because the velocity can be calculated from the displacement, the measurement vector contains components: the displacement and the velocity ... xck ] ( t ) = Λ c xck ] ( t ) + uck ] ( t ) + f c[ k ] ( t ) Using (10), we have [ [ [ f c[ k ] ( t ) = Cc−1 y[k ] ( t ) − Cc−1Cr xrk ] ( t ) − Λ c Cc−1 y[k ] ( t ) + Λ c Cc−1Cr xrk ] ( t ) − uck ... The effects of the time delay and the location of sensor are considered Acknowledgements The paper is based on the talk given at the Conference on Mathematics, Mechanics, and Informatics, Hanoi,...

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8 417 0
partial differential equations and the finite element method - pave1 solin

partial differential equations and the finite element method - pave1 solin

... (Czech Technical University and Academy of Sciences of the Czech Republic), who is a theoretical electrical engineer with lively interest in computational mathematics, for providing me over the ... piecewise-affine FEM and h p - E M 450 B.3 Efficiency comparison of the piecewise-affine FEM and hp-FEM 454 B.4 Efficiency comparison of the piecewise-affine FEM and hp-FEM 458 B.5 Efficiency comparison ... RK method 182 5.2 Coefficients of the Dormand-Prince RK5(4) method 183 xxiii xxiv CONTENTS B.l Efficiency comparison of the piecewise-affine FEM and hp-FEM 447 B.2 Efficiency comparison of the...

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499 547 0
pro c# 2005 and the .net 2.0 platform

pro c# 2005 and the .net 2.0 platform

... illustrate the usefulness of each of these topics, the chapter concludes with the construction of an extendable Windows Forms application Chapter 13: Processes, AppDomains, Contexts, and CLR Hosts Now ... 3: C# Language Fundamentals This chapter examines the core constructs of the C# programming language Here you will come to understand basic class construction techniques, the distinction between ... syntactical constructs introduced with NET 2.0 As well, Part exposes you to each member of the CTS (classes, interfaces, structures, enumerations, and delegates) and the construction of generic types Chapter...

Ngày tải lên: 01/06/2014, 11:39

1K 472 0
Simulation and the Monte Carlo Method Second Edition potx

Simulation and the Monte Carlo Method Second Edition potx

... of the variance and covariance The proofs follow directly from the definitions of covariance and variance and the properties of the expectation Table 1.4 Properties of variance and covariance ... first see how the expectation vector and covariance matrix are transformed Theorem 1.7.1 IfX has an expectation vector px and covariance matrix EX, then the expectation vector and covariance matrix ... science, engineering, and mathematics We show how these problems can be viewed as particular instances of estimation problems and thus can be solved efficiently via Monte Carlo techniques, such...

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377 696 0
SIMULATION AND THE MONTE CARL0 METHODS econd Edition pptx

SIMULATION AND THE MONTE CARL0 METHODS econd Edition pptx

... of the variance and covariance The proofs follow directly from the definitions of covariance and variance and the properties of the expectation Table 1.4 Properties of variance and covariance ... first see how the expectation vector and covariance matrix are transformed Theorem 1.7.1 IfX has an expectation vector px and covariance matrix EX, then the expectation vector and covariance matrix ... science, engineering, and mathematics We show how these problems can be viewed as particular instances of estimation problems and thus can be solved efficiently via Monte Carlo techniques, such...

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377 569 0
SIMULATION AND THE MONTE CARLO METHOD Episode 2 pdf

SIMULATION AND THE MONTE CARLO METHOD Episode 2 pdf

... first see how the expectation vector and covariance matrix are transformed Theorem 1.7.1 IfX has an expectation vector px and covariance matrix EX, then the expectation vector and covariance matrix ... related to the cross-entropy concept, which follows 1.14.2 Kullback-Leibler Cross-Entropy Let g and h be two densities on X Kullback-Leibler cross-entropy between g and h The (compare with (1 S ... (1.65) - The random vector S(0) = S(0; X) with X f ( ; 0) is called the (eficient) score The expected score is always equal to the zero vector, that is where the interchange of differentiation and...

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SIMULATION AND THE MONTE CARLO METHOD Episode 3 potx

SIMULATION AND THE MONTE CARLO METHOD Episode 3 potx

... inverse-transform method, the alias method, the composition method, and the acceptance-rejection method 2.3.1 Inverse-Transform Method Let X be a random variable with cdf F Since F is a nondecreasing function, ... illustrative, since the inverse-transform method handles it efficiently As a consequence of (2.14), the efficiency of the modified acceptance-rejection method is again determined by the acceptanceprobabilityp ... etc.) CfX E G , accept Z = X as the random vector uniformly distributed over G; otherwise, return to Step I Figure 2.7 The vector acceptance-rejection method c, < As a special case, let G be the...

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SIMULATION AND THE MONTE CARLO METHOD Episode 4 potx

SIMULATION AND THE MONTE CARLO METHOD Episode 4 potx

... that uses the acceptance-rejection method with an Exp(X) proposal distribution c) Find the efficiency of the acceptance-rejection method for the cases a = 1, and a approaching zero and infinity ... research and management science, statistics, mathematics, physics, economics, biology, medicine, engineering, chemistry, and the social sciences Through computer simulation, one can study the behavior ... types by 1.2, and 3, respectively We can now implement the event list simply as a x matrix, where each row contains the event time and the event type After each advance of the clock, the current event...

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SIMULATION AND THE MONTE CARLO METHOD Episode 5 ppsx

SIMULATION AND THE MONTE CARLO METHOD Episode 5 ppsx

... than We can view Ri as the reward (or, alternatively, the cost) accrued during the i-th cycle ' Let =12 be the length of the first regeneration cycle and let R = R1 be the first reward The following ... variance reduction are importance sampling and conditional Monte Carlo Other well-known techniques that can provide moderate variance reduction include the use of common and antithetic variables, control ... advantage, the efficiency measure (5.10) reduces to (5.1 1) where the covariance is negative and can be estimated via the corresponding sample covariance The use of common/antithetic random variables...

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SIMULATION AND THE MONTE CARLO METHOD Episode 6 doc

SIMULATION AND THE MONTE CARLO METHOD Episode 6 doc

... parameterized by the vector u.We can write the density of X as m From the discussion at the beginning of this section we know that the optimal CE and VM parameters coincide, since we optimize over ... quite accurate We shall implement screening for both CE and VM methods Recall that for the C E method the parameter vector G (and G B ) can often be updated analytically, in particular when the ... available, the function v(v)becomes a deterministic one Since in typical applications both functions V(v) and ( v ) are convex and differentiable with respect to v, and since one can typically interchange...

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SIMULATION AND THE MONTE CARLO METHOD Episode 7 potx

SIMULATION AND THE MONTE CARLO METHOD Episode 7 potx

... statistical mechanics, while Section 6.6 deals with applications of MCMC in Bayesian statistics In Section 6.7 we show that both the Metropolis-Hastings and Gibbs samplers can be viewed as special cases ... i < j) for which yij > can be gathered into clusters, and within each such cluster the sites have identical colors Moreover, given y ,the colors within the clusters are independent and uniformly ... bidirectional walk by generating two independent nearest neighbor random walks in 9thatstart at X t andend when they step out o f One random walk is called the forward walk and the other is called...

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SIMULATION AND THE MONTE CARLO METHOD Episode 8 doc

SIMULATION AND THE MONTE CARLO METHOD Episode 8 doc

... and the stochastic counterpart method we refer to [ 101 and [ 181, respectively The following two subsections deal separately with the stochastic approximation and the stochastic counterpart methods ... e(u)with respect to u Estimates and 95% confidence intervals indicate that the minimum is attained between and To find u,*via the stochastic counterpart method, we can proceed as follows First, the ... computing machines Journal o Chemical Physics, 21 :1087-1092, f 1953 18 G Propp and D B Wilson Exact sampling with coupled Markov chains and applications to statistical mechanics Random Structures...

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SIMULATION AND THE MONTE CARLO METHOD Episode 9 doc

SIMULATION AND THE MONTE CARLO METHOD Episode 9 doc

... under case ( ) are W1 1 = = 8/5, Wz1 = =1 , W3 1 = W g = and W4 1 = W a = PZl while in case (1) they are all PZZ Next, we derive the score functions (in the first cycle) with respect to pl and p ... distribution is discrete and C( U) is piecewise linear and convex, then w. p the stochastic counterpart method (also called the sample path method) provides an exact optimal solution For a recent survey ... V!(u*)(V!(u*))' , exists Then the random vector N1f2(G u') converges in distribution to a normal random vector with zero mean and covariance matrix B-' C B-' (7.53) The asymptotic efficiency of the estimator...

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SIMULATION AND THE MONTE CARLO METHOD Episode 10 pot

SIMULATION AND THE MONTE CARLO METHOD Episode 10 pot

... Hamiltonian cycle is a special case of the TSP in which the distances between adjacent nodes are , and other distances are 0, and the objective is to find the longest tour The self-avoiding walk problem ... numerically the efficiency of the C E method and its fast convergence for several case studies For additional applications of CE see [311 and the list of references at the end of this chapter 8.4 THE ... thejnalpartition vector: Construct thepartition { Vl(X), Vz(X)} o V and calculate theperformance S(X) f according to (8.28) We take the updating formula for the reference vector p exactly the same as...

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SIMULATION AND THE MONTE CARLO METHOD Episode 11 pps

SIMULATION AND THE MONTE CARLO METHOD Episode 11 pps

... a way that no two adjacent nodes have the same color? If so, how many such colorings are there? Figure 9.1 color? Can the graph be colored with two colors so that no two adjacent nodes have the ... approaches for constructing such low-variance pdfs Among them are the standard CE, exponential change of measure (ECM), and the celebrated MinxEnt method [ 171 Here we shall us a particular modification ... that the clause contains x3,a - 1means that the clause contains the negation Tj; a means that the clause and does not contain either of them Let us call the corresponding matrix A = (atj) the clause...

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SIMULATION AND THE MONTE CARLO METHOD Episode 12 pptx

SIMULATION AND THE MONTE CARLO METHOD Episode 12 pptx

... &-optimalsolution of the true problem with probability at least - a In other words, solving the stochastic counterpart problem with accuracy b guarantees solving the true problem with accuracy E with probability ... ABBREVIATIONS AND ACRONYMS cdf cumulative distribution function CE cross-entropy CMC crude Monte Carlo CNF conjunctive normal form DEDS discrete-event dynamical system DESS discrete-event statical system ... q and h and matrices T and W, which are assumed to be random If we assume that the random data vector X = (q ,W , T, h) takes K different values (calledscenarios) {Xk, = , , K } , with respective...

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