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First Kind (first + kind)
Selected AbstractsPERSPECTIVE: EVOLUTION AND DETECTION OF GENETIC ROBUSTNESSEVOLUTION, Issue 9 2003J. Arjan G. M. de Visser Abstract Robustness is the invariance of phenotypes in the face of perturbation. The robustness of phenotypes appears at various levels of biological organization, including gene expression, protein folding, metabolic flux, physiological homeostasis, development, and even organismal fitness. The mechanisms underlying robustness are diverse, ranging from thermodynamic stability at the RNA and protein level to behavior at the organismal level. Phenotypes can be robust either against heritable perturbations (e.g., mutations) or nonheritable perturbations (e.g., the weather). Here we primarily focus on the first kind of robustness,genetic robustness,and survey three growing avenues of research: (1) measuring genetic robustness in nature and in the laboratory; (2) understanding the evolution of genetic robustness; and (3) exploring the implications of genetic robustness for future evolution. [source] Iterative generalized cross-validation for fusing heteroscedastic data of inverse ill-posed problemsGEOPHYSICAL JOURNAL INTERNATIONAL, Issue 1 2009Peiliang Xu SUMMARY The method of generalized cross-validation (GCV) has been widely used to determine the regularization parameter, because the criterion minimizes the average predicted residuals of measured data and depends solely on data. The data-driven advantage is valid only if the variance,covariance matrix of the data can be represented as the product of a given positive definite matrix and a scalar unknown noise variance. In practice, important geophysical inverse ill-posed problems have often been solved by combining different types of data. The stochastic model of measurements in this case contains a number of different unknown variance components. Although the weighting factors, or equivalently the variance components, have been shown to significantly affect joint inversion results of geophysical ill-posed problems, they have been either assumed to be known or empirically chosen. No solid statistical foundation is available yet to correctly determine the weighting factors of different types of data in joint geophysical inversion. We extend the GCV method to accommodate both the regularization parameter and the variance components. The extended version of GCV essentially consists of two steps, one to estimate the variance components by fixing the regularization parameter and the other to determine the regularization parameter by using the GCV method and by fixing the variance components. We simulate two examples: a purely mathematical integral equation of the first kind modified from the first example of Phillips (1962) and a typical geophysical example of downward continuation to recover the gravity anomalies on the surface of the Earth from satellite measurements. Based on the two simulated examples, we extensively compare the iterative GCV method with existing methods, which have shown that the method works well to correctly recover the unknown variance components and determine the regularization parameter. In other words, our method lets data speak for themselves, decide the correct weighting factors of different types of geophysical data, and determine the regularization parameter. In addition, we derive an unbiased estimator of the noise variance by correcting the biases of the regularized residuals. A simplified formula to save the time of computation is also given. The two new estimators of the noise variance are compared with six existing methods through numerical simulations. The simulation results have shown that the two new estimators perform as well as Wahba's estimator for highly ill-posed problems and outperform any existing methods for moderately ill-posed problems. [source] Analytical approach with Laplace transform to the inverse problem of one-dimensional heat conduction transfer: Application to second and third boundary conditionsHEAT TRANSFER - ASIAN RESEARCH (FORMERLY HEAT TRANSFER-JAPANESE RESEARCH), Issue 1 2003Masanori Monde Abstract An analytical method using Laplace transformation has been developed for one-dimensional heat conduction. This method succeeded in explicitly deriving the analytical solution by which the surface temperature for the first kind of boundary condition can be well predicted. The analytical solutions for the surface temperature and heat flux are applied to the second and third of the boundary conditions. These solutions are also found to estimate the corresponding surface conditions with a high degree of accuracy when the surface conditions smoothly change. On the other hand, when these conditions erratically change such as the first derivative of temperature with time, the accuracy of the estimation becomes slightly less than that for a smooth condition. This trend in the estimation is similar irrespective of any kind of boundary condition. © 2002 Wiley Periodicals, Inc. Heat Trans Asian Res, 32(1): 29,41, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/htj.10069 [source] Meshless Galerkin analysis of Stokes slip flow with boundary integral equationsINTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN FLUIDS, Issue 11 2009Xiaolin Li Abstract This paper presents a novel meshless Galerkin scheme for modeling incompressible slip Stokes flows in 2D. The boundary value problem is reformulated as boundary integral equations of the first kind which is then converted into an equivalent variational problem with constraint. We introduce a Lagrangian multiplier to incorporate the constraint and apply the moving least-squares approximations to generate trial and test functions. In this boundary-type meshless method, boundary conditions can be implemented exactly and system matrices are symmetric. Unlike the domain-type method, this Galerkin scheme requires only a nodal structure on the bounding surface of a body for approximation of boundary unknowns. The convergence and abstract error estimates of this new approach are given. Numerical examples are also presented to show the efficiency of the method. Copyright © 2009 John Wiley & Sons, Ltd. [source] Transient thermal modelling of heat recovery steam generators in combined cycle power plantsINTERNATIONAL JOURNAL OF ENERGY RESEARCH, Issue 11 2007Sepehr Sanaye Abstract Heat recovery steam generator (HRSG) is a major component of a combined cycle power plant (CCPP). This equipment is particularly subject to severe thermal stress especially during cold start-up period. Hence, it is important to predict the operational parameters of HRSGs such as temperature of steam, water, hot gas and tube metal of heating elements as well as pressure change in drums during transient and steady-state operation. These parameters may be used for estimating thermal and mechanical stresses which are important in HRSG design and operation. In this paper, the results of a developed thermal model for predicting the working conditions of HRSG elements during transient and steady-state operations are reported. The model is capable of analysing arbitrary number of pressure levels and any number of elements such as superheater, evaporator, economizer, deaerator, desuperheater, reheater, as well as duct burners. To assess the correct performance of the developed model two kinds of data verification were performed. In the first kind of data verification, the program output was compared with the measured data collected from a cold start-up of an HRSG at Tehran CCPP. The variations of gas, water/steam and metal temperatures at various sections of HRSG, and pressure in drums were among the studied parameters. Mean differences of about 3.8% for temperature and about 9.2% for pressure were observed in this data comparison. In the second kind of data verification, the steady-state numerical output of the model was checked with the output of the well-known commercial software. An average difference of about 1.5% was found between the two latter groups of data. Copyright © 2007 John Wiley & Sons, Ltd. [source] Properties and performance of orthogonal neural network in function approximationINTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, Issue 12 2001Chieh F. Sher Backpropagation neural network has been applied successfully to solving uncertain problems in many fields. However, unsolved drawbacks still exist such as the problems of local minimum, slow convergence speed, and the determination of initial weights and the number of processing elements. In this paper, we introduce a single-layer orthogonal neural network (ONN) that is developed based on orthogonal functions. Since the processing elements are orthogonal to one another and there is no local minimum of the error function, the orthogonal neural network is able to avoid the above problems. Among the five existing orthogonal functions, Legendre polynomials and Chebyshev polynomials of the first kind have the properties of recursion and completeness. They are the most suitable to generate the neural network. Some typical examples are given to show their performance in function approximation. The results show that ONN has excellent convergence performance. Moreover, ONN is capable of approximating the mathematic model of backpropagation neural network. Therefore, it should be able to be applied to various applications that backpropagation neural network is suitable to solve. © 2001 John Wiley & Sons, Inc. [source] Active force closure for multiple objectsJOURNAL OF FIELD ROBOTICS (FORMERLY JOURNAL OF ROBOTIC SYSTEMS), Issue 3 2002Kensuke Harada This article discusses active force closure (AFC) for the manipulation of multiple objects. AFC for multiple objects is defined in such a way that the finger can generate an arbitrary acceleration onto a certain point of multiple objects. We define two kinds of AFC: in the first, an arbitrary acceleration can be generated onto each of the objects; in the second, an arbitrary acceleration can be generated onto the center of mass of multiple objects without changing the relative position of the objects. We show that the grasped object cannot always be manipulated arbitrarily even if the first kind of AFC is satisfied. We also show that the grasped objects are manipulated like a single rigid body if the second kind of AFC is satisfied. To explain these features of AFCs, numerical examples for the grasp of three objects are shown. © 2002 Wiley Periodicals, Inc. [source] Generalized MRI reconstruction including elastic physiological motion and coil sensitivity encodingMAGNETIC RESONANCE IN MEDICINE, Issue 6 2008Freddy Odille Abstract This article describes a general framework for multiple coil MRI reconstruction in the presence of elastic physiological motion. On the assumption that motion is known or can be predicted, it is shown that the reconstruction problem is equivalent to solving an integral equation,known in the literature as a Fredholm equation of the first kind,with a generalized kernel comprising Fourier and coil sensitivity encoding, modified by physiological motion information. Numerical solutions are found using an iterative linear system solver. The different steps in the numerical resolution are discussed, in particular it is shown how over-determination can be used to improve the conditioning of the generalized encoding operator. Practical implementation requires prior knowledge of displacement fields, so a model of patient motion is described which allows elastic displacements to be predicted from various input signals (e.g., respiratory belts, ECG, navigator echoes), after a free-breathing calibration scan. Practical implementation was demonstrated with a moving phantom setup and in two free-breathing healthy subjects, with images from the thoracic-abdominal region. Results show that the method effectively suppresses the motion blurring/ghosting artifacts, and that scan repetitions can be used as a source of over-determination to improve the reconstruction. Magn Reson Med, 2008. © 2008 Wiley-Liss, Inc. [source] A regularization procedure for the auto-correlation equationMATHEMATICAL METHODS IN THE APPLIED SCIENCES, Issue 14 2001L. Von Wolfersdorf The paper deals with the auto-correlation equation and its regularization by means of a Lavrent'ev regularization procedure in L2. The solution of this quadratic integral equation of the first kind and of the regularized equation of the second kind are obtained by reduction to a boundary value problem for the Fourier transform of the solution. We prove convergence of the approximate solution to the exact solution and derive a stability estimate for the error. Copyright © John Wiley & Sons, Ltd. [source] Source-group method to speed up the reconstruction of objects from radar data by using the FBTS methodMICROWAVE AND OPTICAL TECHNOLOGY LETTERS, Issue 1 2006Dongling Qiu Abstract We have proposed a time-domain forward-backward time-stepping (FBTS) method for reconstructing 3D structures in highly absorptive media. The reconstruction speed is greatly dependent on the number of transmitters. In this paper, we propose a source-group method to speed up the reconstruction. In the source-group method, multiple transmitters arranged at different positions are excited simultaneously, and receivers collect the wave fields. To compare the reconstruction results, three kinds of reconstructions from 16 conventional single transmitter-multiple receiver data sets, four source-group multiple-receiver data sets, and four conventional single-transmitter multiple-receiver data sets are carried out. Reconstruction by the source-group method is several times faster than (and the reconstructed results are almost the same as) those of the first kind of reconstruction, and they are much better than those of the third kind. © Wiley Periodicals, Inc. Microwave Opt Technol Lett 48: 67,71, 2006; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.21263 [source] Imperfection Sensitivity or Insensitivity of Zero-stiffness Postbuckling , that is the QuestionPROCEEDINGS IN APPLIED MATHEMATICS & MECHANICS, Issue 1 2009Xin Jia Zero-stiffness postbuckling of a structure is characterized by a secondary load-displacement path along which the load remains constant. In sensitivity analysis of the (initial) postbuckling path it is usually considered as a borderline case between imperfection sensitivity and imperfection insensitivity. However, it is unclear whether zero-stiffness postbuckling as such is imperfection sensitive or insensitive. In this paper, Koiter's initial postbuckling analysis is used as a tool for sensitivity analysis. Distinction between two kinds of imperfections is made on the basis of the behavior of the equilibrium path of the imperfect structure. New definitions of imperfection insensitivity of the postbuckling behavior are provided according to the classification of imperfections. A structure with two degrees of freedom with a zero-stiffness postbuckling path is studied, considering four different imperfections. The results from this example show that zero-stiffness postbuckling is a case of transition from imperfection sensitivity to imperfection insensitivity for imperfections of the first kind and that it is imperfection insensitive for imperfections of the second kind. (© 2009 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim) [source] Determination of depth-dependent diffraction data: a new approachACTA CRYSTALLOGRAPHICA SECTION A, Issue 1 2005A. Broadhurst A direct method for determining powder diffraction data at specific depths from angle-dependent diffraction data is described. The method is non-destructive and only traditional data collections, where the angle of incidence is varied, are required. These angle-dependent spectra are transformed to give diffraction data arising from different depths, which may then be exploited using any conventional method. This is a novel approach as traditional methods are forced to tolerate the inherent depth averaging of grazing-angle diffraction, or only examine specific structural characteristics. In order to obtain depth-dependent X-ray diffraction data, a Fredholm integral equation of the first kind is solved using regularization techniques. The method has been validated by the generation of pseudo-experimental data having known depth profiles and solving the Fredholm integral equation to recover the solution. The method has also been applied to experimental data from a number of thin film systems. [source] |