Repulsive Curves

Um trabalho muito interessante e com muito código sobre os melhores algoritmos para construir curvas que não se sobrepõem

Curves play a fundamental role across computer graphics, physical simulation, and mathematical visualization, yet most tools for curve design do nothing to prevent crossings or self-intersections. This paper develops efficient algorithms for (self-)repulsion of plane and space curves that are well-suited to problems in computational design. Our starting point is the so-called tangent-point energy, which provides an infinite barrier to self-intersection. In contrast to local collision detection strategies used in, e.g., physical simulation, this energy considers interactions between all pairs of points, and is hence useful for global shape optimization: local minima tend to be aesthetically pleasing, physically valid, and nicely distributed in space. A reformulation of gradient descent, based on a Sobolev-Slobodeckij inner product enables us to make rapid progress toward local minima—independent of curve resolution. We also develop a hierarchical multigrid scheme that significantly reduces the per-step cost of optimization. The energy is easily integrated with a variety of constraints and penalties (e.g., inextensibility, or obstacle avoidance), which we use for applications including curve packing, knot untangling, graph embedding, non-crossing spline interpolation, flow visualization, and robotic path planning.

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Journal of Physics: Conference Series

longa lista de artigos resultantes de conferências de Matemática e Física

The open access Journal of Physics: Conference Series (JPCS) provides a fast, versatile and cost-effective proceedings publication service. 


Electronic Statistics Textbook: StatSoft

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Uma referência muito completa sobre métodos estatísticos e de data mining.

Proper citation:

  • (Electronic Version): StatSoft, Inc. (2013). Electronic Statistics Textbook. Tulsa, OK: StatSoft. WEB:
  • (Printed Version): Hill, T. & Lewicki, P. (2007). STATISTICS: Methods and Applications. StatSoft, Tulsa, OK.

Overview of Elementary Concepts in Statistics. In this introduction, we will briefly discuss those elementary statistical concepts that provide the necessary foundations for more specialized expertise in any area of statistical data analysis. The selected topics illustrate the basic assumptions of most statistical methods and/or have been demonstrated in research to be necessary components of one’s general understanding of the “quantitative nature” of reality (Nisbet, et al., 1987). Because of space limitations, we will focus mostly on the functional aspects of the concepts discussed and the presentation will be very short.

Further information on each of those concepts can be found in the Introductory Overview and Examples sections of this manual and in statistical textbooks. Recommended introductory textbooks are: Kachigan (1986), and Runyon and Haber (1976); for a more advanced discussion of elementary theory and assumptions of statistics, see the classic books by Hays (1988), and Kendall and Stuart (1979).

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JStor – pesquisa de livros e artigos

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um site com muitos livros e revistas com temas variados.




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Uma alternativa à weekepedia com suposta melhor qualidade.

Welcome to Scholarpedia

the peer-reviewed open-access encyclopedia,
where knowledge is curated by communities of experts

Disseminate: share your expertise with a global audience

Pioneer: write the first persistent online review in your area of specialization

Steward: supervise the development of articles in your field

Collaborate: work with expert scientists and scholars from around the world

Learn: gain experience with scholarly writing and editing

Publish: transform your writing into a peer-reviewed article


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Docear – The Academic Literature Suite

Excelente software de gestão documental para escrever teses \ artigos

Excelente software de gestão documental para escrever teses \ artigos

Docear is a unique solution to academic literature management, i.e. it helps you organizing, creating, and discovering academic literature. Among others, Docear offers:

  1. A single-section user-interface that allows the most comprehensive organization of your literature. With Docear, you can sort documents into categories; you can sort annotations (comments, bookmarks, and highlighted text from PDFs) into categories; you can sort annotations within PDFs; and you can view multiple annotations of multiple documents, in multiple categories – at once.
  2. A ‘literature suite concept‘ that combines several tools in a single application (pdf management, reference management, mind mapping, …). This allows you to draft your own papers, assignments, thesis, etc. directly in Docear and copy annotations and references from your collection directly into your draft.
  3. recommender system that helps you to discover new literature: Docear recommends papers which are free, in full-text, instantly to download, and tailored to your information needs.

And did we mention that Docear is free, open source, available for Windows, Linux, and Mac OS X, and not evil?

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