Image registration with iterated local search

This contribution is devoted to the application of iterated local search to image registration, a very complex, real-world problem in the field of image processing. To do so, we first re-define this parameter estimation problem as a combinatorial optimization problem, then analyze the use of image-specific information to guide the search in the form of an heuristic function, and finally propose its solution by iterated local search. Our algorithm is tested by comparing its performance to that of two different baseline algorithms: iterative closest point, a well-known, image registration technique, a hybrid algorithm including the latter technique within a simulated annealing approach, a multi-start local search procedure, that allows us to check the influence of the search scheme considered in the problem solving, and a real coded genetic algorithm. Four different problem instances are tackled in the experimental study, resulting from two images and two transformations applied on them. Three parameter settings are analyzed in our approach in order to check three heuristic information scenarios where the heuristic is not used at all, is partially used or almost completely guides the search process, as well as two different number of iterations in the algorithms outer-inner loops. This work was partially supported by the Spanish Ministerio de Ciencia y Tecnología under project TIC2003-00877 (including FEDER fundings) and under Network HEUR TIC2002-10866-E.     

On the sensitivity of the one-sided test to covariance misspecification

Sensitivity analysis stands in contrast to diagnostic testing in that sensitivity analysis aims to answer the question of whether it matters that a nuisance parameter is non-zero, whereas a diagnostic test ascertains explicitly if the nuisance parameter is different from zero. In this paper, we introduce and derive the finite sample properties of a sensitivity statistic measuring the sensitivity of the t statistic to covariance misspecification. Unlike the earlier work by Banerjee and Magnus [A. Banerjee, J.R. Magnus, On the sensitivity of the usual t- and F-tests to covariance misspecification, Journal of Econometrics 95 (2000) 157–176] on the sensitivity of the F statistic, the theorems derived in the current paper hold under both the null and alternative hypotheses. Also, in contrast to Banerjee and Magnus’ [see the above cited reference] results on the F test, we find that the decision to accept the null using the OLS based one-sided t test is not necessarily robust against covariance misspecification and depends much on the underlying data matrix. Our results also indicate that autocorrelation does not necessarily weaken the power of the OLS based t test.     

Comparative studies of the globally convergent convexification algorithm with application to imaging of antipersonnel land mines

A comparative study of various aspects on the globally convergent convexification algorithm for coefficient inverse problems is described. Numerical results of the algorithm with application to detection of antipersonnel land mines are presented. The aspects studied include initial guess and layer size for the layer stripping approach, dimensions of the basis for spatial and pseudo-frequency approximations, the lower limit of the integrals with respect to pseudo-frequency κ, the stopping criteria of steepest descent method in the least squares minimization, the tails to compensate the truncated integration with respect to κ, the parameter λ associated with the Carleman weight function, and adding different noise levels to the input data for the coefficient inverse problems. With our new implementation, the convexification algorithm is very efficient and feasible to be applied in real time to detect antipersonnel land mines in the field.     

On a Multiparameter Version of Tukey's Linear Sensitivity Measure and its Properties

A multiparameter version of Tukey's (1965, Proc. Nat. Acad. Sci. U.S.A., 53, 127–134) linear sensitivity measure, as a measure of informativeness in the joint distribution of a given set of random variables, is proposed. The proposed sensitivity measure, under some conditions, is a matrix which is non-negative definite, weakly additive, monotone and convex. Its relation to Fisher information matrix and the best linear unbiased estimator (BLUE) are investigated. The results are applied to the location-scale model and it is observed that the dispersion matrix of the BLUE of the vector location-scale parameter is the inverse of the sensitivity measure. A similar property was established by Nagaraja (1994, Ann. Inst. Statist. Math., 46, 757–768) for the single parameter case when applied to the location and scale models. Two illustrative examples are included.     

Numerical study of forced and free convective boundary layer flow of a magnetic fluid over a flat plate under the action of a localized magnetic field

The two-dimensional, steady, laminar, forced and free convective boundary layer flow of a magnetic fluid over a semi-infinite vertical plate, under the action of a localized magnetic field, is numerically studied. The magnetic fluid is considered to be water-based with temperature dependent viscosity and thermal conductivity. The study of the boundary layer is separated into two cases. In case I the boundary layer is studied near the leading edge, where it is dominated by the large viscous forces, whereas in case II the boundary layer is studied far from the leading edge of the plate where the effects of buoyancy forces increase. The numerical solution, for these two different cases, is obtained by an efficient numerical technique based on the common finite difference method. Numerical calculations are carried out for the value of Prandl number Pr =  49.832 (water-based magnetic fluid) and for different values of the dimensionless parameters entering into the problem and especially for the magnetic parameter Mn, the viscosity/temperature parameter Θ _r and the thermal/conductivity parameter S*. The analysis of the obtained results show that the flow field is influenced by the application of the magnetic field as well as by the variation of the viscosity and the thermal conductivity of the fluid with temperature. It is hoped that they could be interesting for engineering applications.     

Smoothed penalty algorithms for optimization of nonlinear models

We introduce an algorithm for solving nonlinear optimization problems with general equality and box constraints. The proposed algorithm is based on smoothing of the exact l ₁-penalty function and solving the resulting problem by any box-constraint optimization method. We introduce a general algorithm and present theoretical results for updating the penalty and smoothing parameter. We apply the algorithm to optimization problems for nonlinear traffic network models and report on numerical results for a variety of network problems and different solvers for the subproblems.     

Seizure warning algorithm based on optimization and nonlinear dynamics

There is growing evidence that temporal lobe seizures are preceded by a preictal transition, characterized by a gradual dynamical change from asymptomatic interictal state to seizure. We herein report the first prospective analysis of the online automated algorithm for detecting the preictal transition in ongoing EEG signals. Such, the algorithm constitutes a seizure warning system. The algorithm estimates STL_max, a measure of the order or disorder of the signal, of EEG signals recorded from individual electrode sites. The optimization techniques were employed to select critical brain electrode sites that exhibit the preictal transition for the warning of epileptic seizures. Specifically, a quadratically constrained quadratic 0-1 programming problem is formulated to identify critical electrode sites. The automated seizure warning algorithm was tested in continuous, long-term EEG recordings obtained from 5 patients with temporal lobe epilepsy. For individual patient, we use the first half of seizures to train the parameter settings, which is evaluated by ROC (Receiver Operating Characteristic) curve analysis. With the best parameter setting, the algorithm applied to all cases predicted an average of 91.7% of seizures with an average false prediction rate of 0.196 per hour. These results indicate that it may be possible to develop automated seizure warning devices for diagnostic and therapeutic purposes.Mathematics Subject Classification (1991):20E28, 20G40, 20C20     

QoS commitment between vertically integrated autonomous systems

Vertically integrated autonomous systems bargain to provide quality of service guarantees and revenue sharing. Depending on the perceived quality of service and access price, consumers determine whether they subscribe to the access provider’s service. Four types of contracts are compared: (i) best effort, (ii) bilateral bargaining, (iii) cascade negotiations and (iv) grand coalition cooperation; the impact of the consumers’ QoS sensitivity parameter and power relation are tested for each contract. Assuming that the consumers’ quality of service sensitivity parameter is unknown and might evolve dynamically due to error judgement, word-of-mouth effect or competition pressure, a learning algorithm is detailed and implemented by each integrated autonomous systems under asymmetrical information. Its convergence and the influence of bias introduction by the most informed autonomous system is analyzed.     

Spline-based sieve maximum likelihood estimation in the partly linear model under monotonicity constraints

We study a spline-based likelihood method for the partly linear model with monotonicity constraints. We use monotone B-splines to approximate the monotone nonparametric function and apply the generalized Rosen algorithm to compute the estimators jointly. We show that the spline estimator of the nonparametric component achieves the possible optimal rate of convergence under the smooth assumption and that the estimator of the regression parameter is asymptotically normal and efficient. Moreover, a spline-based semiparametric likelihood ratio test is established to make inference of the regression parameter. Also an observed profile information method to consistently estimate the standard error of the spline estimator of the regression parameter is proposed. A simulation study is conducted to evaluate the finite sample performance of the proposed method. The method is illustrated by an air pollution study.     

Categorical data clustering with automatic selection of cluster number

In this paper, we investigate the problem of determining the number of clusters in the k-modes based categorical data clustering process. We propose a new categorical data clustering algorithm with automatic selection of k. The new algorithm extends the k-modes clustering algorithm by introducing a penalty term to the objective function to make more clusters compete for objects. In the new objective function, we employ a regularization parameter to control the number of clusters in a clustering process. Instead of finding k directly, we choose a suitable value of regularization parameter such that the corresponding clustering result is the most stable one among all the generated clustering results. Experimental results on synthetic data sets and the real data sets are used to demonstrate the effectiveness of the proposed algorithm.     

An algorithm for large scale 0–1 integer programming with application to airline crew scheduling

We present an approximation algorithm for solving large 0–1 integer programming problems whereA is 0–1 and whereb is integer. The method can be viewed as a dual coordinate search for solving the LP-relaxation, reformulated as an unconstrained nonlinear problem, and an approximation scheme working together with this method. The approximation scheme works by adjusting the costs as little as possible so that the new problem has an integer solution. The degree of approximation is determined by a parameter, and for different levels of approximation the resulting algorithm can be interpreted in terms of linear programming, dynamic programming, and as a greedy algorithm. The algorithm is used in the CARMEN system for airline crew scheduling used by several major airlines, and we show that the algorithm performs well for large set covering problems, in comparison to the CPLEX system, in terms of both time and quality. We also present results on some well known difficult set covering problems that have appeared in the literature.     

Structure optimization of linear resonance accelerators by sensitivity functions

An algorithm is proposed for optimizing linear accelerator structure parameters using sensitivity functions and practical stability methods. This approach takes into account the actual perturbations of particle trajectories as a function of the computational parameters, analyzes the distribution of system parameter tolerances, and performs optimization with allowance for these factors. Numerical results for specific optimization problems of beam dynamics at the outlet are reported.Translated from Vychislitel'naya i Prikladnaya Matematika, No. 58, pp. 100–106, 1986.     

Formulation of linear problems and solution by a universal machine

Using the predicate language for ordered fields a class of problems referred to aslinear problems is defined. This class contains, for example, all systems of linear equations and inequalities, all linear programming problems, all integer programming problems with bounded variables, all linear complementarity problems, the testing of whether sets that are defined by linear inequalities are semilattices, all satisfiability problems in sentenial logic, the rank-computation of matrices, the computation of row-reduced echelon forms of matrices, and all quadratic programming problems with bounded variables. A single, one, algorithm, to which we refer as theUniversal Linear Machine, is described. It solves any instance of any linear problem. The Universal Linear Machine runs in two phases. Given a linear problem, in the first phase a Compiler running on a Turing Machine generates alinear algorithm for the problem. Then, given an instance of the linear problem, in the second phase the linear algorithm solves the particular instance of the linear problem. The linear algorithm is finite, deterministic, loopless and executes only the five ordered field operations — additions, multiplications, subtractions, divisions and comparisons. Conversely, we show that for each linear algorithm there is a linear problem which the linear algorithm solves uniquely. Finally, it is shown that with a linear algorithm for a linear problem, one can solve certain parametric instances of the linear problem.Research was supported in part by the National Science Foundation Grant DMS 92-07409, by the Department of Energy Grant DE-FG03-87-ER-25028, by the United States—Israel Binational Science Foundation Grant 90-00434 and by ONR Grant N00014-92-J1142.Corresponding author.     

Rotation-Symmetric Referencebodys For Energy Efficient Flow Around Bodies

Topology optimization is used to optimize problems of flow around bodies and problems of guided flow. Within the context of research, optimization criteria are developed to increase the energy efficiency of these problems [1] [2] [3] [4] [5]. In order to evaluate the new criteria in respect to the increasing of energy efficiency, reference bodies for different Reynolds numbers in combination with given design space limitations are needed. Therefore, an optimal body at Reynolds number against 0 was analytically determined by Bourot [6]. At higher Reynolds numbers, in the range of laminar and turbulent flows, no analytical solution is known. Accordingly, reference bodies are calculated by CFD calculations at three technical relevant Reynolds numbers (1.000, 32.000, 100.000) in combination with parameter optimization. The cross section of the bodies is described by a parameterized model. To get the optimal body, a parameter optimization based on a “brute force”; algorithm is used to optimize with regard to the friction loss and pressure loss in order to minimize the total loss (c_d-value). The result is an optimal parameter constellation, depending on the Reynolds number. Within the results, it is possible to develop the optimal geometries. The identified characteristics of the flow field around these bodies are used as base for new optimization criteria. (© 2012 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Analytical approach to heat and mass transfer in MHD free convection from amoving permeable vertical surface

An analytical study is performed on heat and mass transfer in MHD‐free convection from a moving permeable vertical surface and the results are compared with previous works on this phenomenon to test the validity. The coupled equations of boundary layer are transformed from their non‐linear form to ordinary form using similarity transformation and then are solved by a newly developed method, homotopy analysis method. Having different base functions, homotopy analysis method provides us with great freedom in choosing the solution of a nonlinear problem. Solving the boundry layer equations, the effects of different parameters such as magnetic field strength parameter (M), Prandtl number (Pr), Schmidt number (Sc), buoyancy ratio and suction/blowing parameter (f_w) on velocity, temperature, and concentration profiles are taken into consideration. Obtained results show that increment of magnetic field strength parameter (M) leads to decrease in velocity profile. Copyright © 2011 John Wiley & Sons, Ltd.     

Summary and comparison of gradient-restoration algorithms for optimal control problems

This paper considers the problem of minimizing a functionalI which depends on the statex(t), the controlu(t), and the parameter . Here,I is a scalar,x ann-vector,u anm-vector, and ap-vector. At the initial point, the state is prescribed. At the final point, the state and the parameter are required to satisfyq scalar relations. Along the interval of integration, the state, the control, and the parameter are required to satisfyn scalar differential equations.Four types of gradient-restoration algorithms are considered, and their relative efficiency (in terms of number of iterations for convergence) is evaluated. The algorithms being considered are as follows: sequential gradient-restoration algorithm, complete restoration (SGRA-CR), sequential gradient-restoration algorithm, incomplete restoration (SGRA-IR), combined gradient-restoration algorithm, no restoration (CGRA-NR), and combined gradient-restoration algorithm, incomplete restoration (CGRA-IR).Evaluation of these algorithms is accomplished through six numerical examples. The results indicate that (i) the inclusion of a restoration phase is necessary for rapid convergence and (ii) while SGRA-CR is the most desirable algorithm if feasibility of the suboptimal solutions is required, rapidity of convergence to the optimal solution can be increased if one employs algorithms with incomplete restoration, in particular, CGRA-IR.This research was supported by the Office of Scientific Research, Office of Aerospace Research, United States Air Force, Grant No. AF-AFOSR-72-2185.     

On the choice of parameters for power-series interior point algorithms in linear programming

In this paper we study higher-order interior point algorithms, especially power-series algorithms, for solving linear programming problems. Since higher-order differentials are not parameter-invariant, it is important to choose a suitable parameter for a power-series algorithm. We propose a parameter transformation to obtain a good choice of parameter, called ak-parameter, for general truncated powerseries approximations. We give a method to find ak-parameter. This method is applied to two powerseries interior point algorithms, which are built on a primal—dual algorithm and a dual algorithm, respectively. Computational results indicate that these higher-order power-series algorithms accelerate convergence compared to first-order algorithms by reducing the number of iterations. Also they demonstrate the efficiency of thek-parameter transformation to amend an unsuitable parameter in power-series algorithms.Work supported in part by the DFG Schwerpunktprogramm Anwendungsbezogene Optimierung und Steuerung.     

Sensitivity analysis for parametric control problems with control-state constraints

Parametric nonlinear control problems subject to vector-valued mixed control-state constraints are investigated. The model perturbations are implemented by a parameter p of a Banach-space P. We prove solution differentiability in the sense that the optimal solution and the associated adjoint multiplier function are differentiable functions of the parameter. The main assumptions for solution differentiability are composed by regularity conditions and recently developed second-order sufficient conditions (SSC). The analysis generalizes the approach in [16, 20] and establishes a link between (1) shooting techniques for solving the associated boundary value problem (BVP) and (2) SSC. We shall make use of sensitivity results from finite-dimensional parametric programming and exploit the relationships between the variational system associated to BVP and its corresponding Riccati equation.Solution differentiability is the theoretical backbone for any numerical sensitivity analysis. A numerical example with a vector-valued control is presented that illustrates sensitivity analysis in detail.     

基于信息压缩矩阵特征值映射的时变系统UD分解辨识算法

在系统辨识领域遗忘因子UD分解算法(一种通过对系统数据矩阵进行UD分解的在线辨识算法)具有对时变系统阶次和参数同步估计的优异性能,但传统的遗忘策略不能从根本上解决信息压缩矩阵数据过饱和问题,为了拓展现有UD分解算法在时变系统的适用范围,同时针对数据空间分布不均匀性,提出一种基于信息压缩矩阵特征值映射的UD分解辨识算法....     

The inverse problem for an acoustic equation in a weakly horizontally inhomogeneous medium

The inverse problem of reconstructing the coefficients A and B in the equation {fx379-01} in the half-plane z > 0 is considered. It is assumed that an instantaneous point source at z = 0 generates a wave field U(t, z, x), which is known on the boundary. It is also known that the coefficients A and B can be represented in the form {fx379-02}. Here ε is a small parameter. An algorithm for determinating the coefficients A₀, B₀, A₁, and B₁ with accuracy O(ε²) is constructed. Bibliography: 5 titles. __________ Translated from Zapiski Nauchnykh Seminarov POMI, Vol. 354, 2008, pp. 81–99.