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Materias / palabras clave: computer science, materials science, metallurgy, materials reaserch, computational modeling; Science: Mathematics: Instruments and machines: Electronic computers. Computer science; Medicine: Medicine (General): Computer ...

Materias / palabras clave: Social sciences; Statistical methods; Data processing; R (Computer program language); Ciencias sociales; Métodos estadísticos; R (Lenguaje de programación)

Materias / palabras clave: Programación orientada al objeto (Informática); Java (Lenguaje de programación); UML (Informática); Object-oriented methods (Computer science); UML (Computer science); Java (Computer program language)

Materias / palabras clave: Presentation graphics software; Software gráfico; Business presentations; Graphic methods; Computer programs; Presentacion de negocios; Métodos gráficos; Programas informáticos; Computer graphics; Gráficos de comput...

BACKGROUND: There is a growing recognition of the value of synthesising qualitative research in the evidence base in order to facilitate effective and appropriate health care. In response to this, methods for undertaking...

W. R. Tobler, A Computer Movie Simulating Urban Growth in the Detroit Region, Economic Geography, Vol. 46, Supplement: Proceedings. International Geographical Union. Commission on Quantitative Methods (Jun., 1970), pp. 2...

A basic problem in computer vision is to understand the structure of a real world scene given several images of it. Techniques for solving this problem are taken from projective geometry and photogrammetry. Here, the aut...

Convolutional networks are at the core of most state of-the-art computer vision solutions for a wide variety of tasks. Since 2014 very deep convolutional networks started to become mainstream, yielding substantial gains ...

Computer vision applications have come to rely increasingly on superpixels in recent years, but it is not always clear what constitutes a good superpixel algorithm. In an effort to understand the benefits and drawbacks o...

This article provides researchers with a guide to properly construe and conduct analyses of conditional indirect effects, commonly known as moderated mediation effects. We disentangle conflicting definitions of moderated...

Non-biological experimental variation or "batch effects" are commonly observed across multiple batches of microarray experiments, often rendering the task of combining data from these batches difficult. The ability to co...

Business Research Methods contains new and revised chapters on quantitative methods and visual research, while cutting-edge material on inclusivity and bias in research, feminist perspectives, and decolonial and indigeno...

Collinearity refers to the non independence of predictor variables, usually in a regression‐type analysis. It is a common feature of any descriptive ecological data set and can be a problem for parameter estimation bec...

Preface 1. Background in linear algebra 2. Discretization of partial differential equations 3. Sparse matrices 4. Basic iterative methods 5. Projection methods 6. Krylov subspace methods Part I 7. Krylov subspace methods...

The purposes of this article are to position mixed methods research ( mixed research is a synonym) as the natural complement to traditional qualitative and quantitative research, to present pragmatism as offering an attr...

Prediction of species’ distributions is central to diverse applications in ecology, evolution and conservation science. There is increasing electronic access to vast sets of occurrence records in museums and herbaria, ...

Phylogenies are extremely useful tools, not only for establishing genealogical relationships among a group of organisms or their parts (e.g. genes), but also for a variety of research once the phylogenies are estimated. ...

SIR 97 is the integration of two programs, SIR 92 and CAOS , the first devoted to the solution of crystal structures by direct methods, the second to refinement via least-squares–Fourier procedures. Several new feature...

The increase in the number of large data sets and the complexity of current probabilistic sequence evolution models necessitates fast and reliable phylogeny reconstruction methods. We describe a new approach, based on th...

Deep convolutional neural networks have performed remarkably well on many Computer Vision tasks. However, these networks are heavily reliant on big data to avoid overfitting. Overfitting refers to the phenomenon when a n...

Previous article Next article An Algorithm for Least-Squares Estimation of Nonlinear ParametersDonald W. MarquardtDonald W. Marquardthttps://doi.org/10.1137/0111030PDFPDF PLUSBibTexSections ToolsAdd to favoritesExport Ci...

Genetic algorithms have been used in science and engineering as adaptive algorithms for solving practical problems and as computational models of natural evolutionary systems. This brief, accessible introduction describe...

Today, visual recognition systems are still rarely employed in robotics applications. Perhaps one of the main reasons for this is the lack of demanding benchmarks that mimic such scenarios. In this paper, we take advanta...

First-principles simulation, meaning density-functional theory calculations with plane waves and pseudopotentials, has become a prized technique in condensed-matter theory. Here I look at the basics of the suject, give a...