2,196,756 research outputs found
Bringing trees to the I-205 multi-use path
Full text linkThis archived document is maintained by the Oregon State Library as part of the Oregon Documents Depository Program. It is for informational purposes and may not be suitable for legal purposes.Title from PDF caption (viewed on May 10, 2016).Logos: Friends of Trees; Metro; Oregon Department of Transportation."Friends of Trees and their Green Space Initiative program are planting thousands of native trees and shrubs along the I-205 Multi-Use Path, from the Columbia River south to Gladstone"--Page 1.Mode of access: Internet from the Oregon Government Publications Collection.Text in English
Thought Experiments in Graphic Design Education
No full textWhat happens when we look at graphic design education as a ‘thought experiment’?
Thought Experiments in Graphic Design Education documents an international mix of experimental, reflexive and speculative projects made by students, educators and practitioners who continue to question how and why graphic design is studied and practiced.
Over 50 pages of full-colour photographs are presented alongside new perspectives on enduring debates, including: education vs. industry; culture vs. commerce; art vs. design; specialism vs. generalism; structure vs. freedom; self-study vs. training; collaboration vs. competition; analogue vs. digital, concept vs. craft; and much more.
Using the book’s ‘time jump’ feature, readers can toggle back and forth between
concurrent activities encompassing dialogues, papers, manifestos, exhibitions, assignments, workshops, presentations, publications, commissions and self-initiated works.
Contributors: Bart de Baets, Stuart Bailey, Delphine Bedel, Victor Boullet, Lionel Bovier, Dante Carlos, James Corazzo, Daniel Eatock, Bianca Elzenbaumer, Kenneth Fitzgerald, Fabio Franz, John Hammersley, Harrisson, Ken Hollings, Brockett Horne, Scott King, Ken Kirton, Jono Lewarne, Alexander Lis, Yvan Martinez, Armand Mevis, Rens Muis, Silas Munro, Sebastian Pataki, Stuart Price, Darren Raven, Alexander Shoukas, Rebecca Stephany, Jon Sueda, Joshua Trees, and many more.
Schools represented: After School Club; Art Center College of Design; CalArts; California College of the Arts; Central Saint Martins; ERG, Belgium; Geneva University of Art and Design; Gerrit Rietveld Academie;
The Institute of Social Hypocrisy; KABK, The Hague; London College of Communication; Lost in the Forest Institute; Merz Academie, Stuttgart; MIT; North Carolina State University; Parsons, The New School for Design; Royal College of Art; San Francisco Art Institute; Stockport College; IAUV, Venice, Italy; The University of the West of England; and Werkplaats Typografie
Edition of 500
Riso printed
330 pages
Publisher: Booksfromthefuture
Editors: Yvan Martinez and Joshua Trees
Design: Pont
Alternating model trees
No full textModel tree induction is a popular method for tackling regression problems requiring interpretable models. Model trees are decision trees with multiple linear regression models at the leaf nodes. In this paper, we propose a method for growing alternating model trees, a form of option tree for regression problems. The motivation is that alternating decision trees achieve high accuracy in classification problems because they represent an ensemble classifier as a single tree structure. As in alternating decision trees for classifi-cation, our alternating model trees for regression contain splitter and prediction nodes, but we use simple linear regression functions as opposed to constant predictors at the prediction nodes. Moreover, additive regression using forward stagewise modeling is applied to grow the tree rather than a boosting algorithm. The size of the tree is determined using cross-validation. Our empirical results show that alternating model trees achieve significantly lower squared error than standard model trees on several regression datasets
The Integral Trees with Spectral Radius 3
Full text linkThere are eleven integral trees with largest eigenvalue 3.Integral graphs;graph spectra;trees
What do they like about trees?: Adding local voices to urban forest design and planning
Full text linkLocal preferences and priorities for trees and greenspaces are important considerations when planning and designing a community's urban forest. Local residents can provide insight into place-specific contexts such as local aesthetic preferences, social systems, cultures, and attitudes to inform appropriate design responses. Residents also inform researchers of key local issues that may impact urban forest configurations, and may differ from expert opinions. This paper reports on a case study from a suburban community in Canada that used a combination of methods to reveal new, place-based information to inform more contextual design for a community's future urban forest. Results reveal that the current urban forest in the community does not reflect the participants’ preferences and differs from experts’ priorities. The findings suggest issues that should be considered in future urban forest design and planning processes
A Generic Translation from Case Trees to Eliminators
No full textDependently-typed languages allow one to guarantee correctness of a program by providing formal proofs. The type checkers of such languages elaborate the user-friendly high-level surface language to a small and fully explicit core language. A lot of trust is put into this elaboration process, even though it is rarely verified. One such elaboration is elaborating dependent pattern matching to the low-level construction of eliminators. This elaboration is done in two steps. First, the function defined by dependent pattern matching is translated into a case tree, which can then be further translated to eliminators. We present a generic, well-typed implementation of this second step in Agda, without the use of metaprogramming and unsafe transformations, by providing a type-safe, correct-by construction, generic definition of case trees and an evaluation function that, given an interpretation of such a case tree and an interpretation of the telescope of function arguments, evaluates the output term of the function using only eliminators. We only allow case splits on variables from a fixed universe of data type descriptions, for which we use techniques like basic analysis and specialization by unification.https://github.com/klieverse/case-trees-to-eliminators Formalization of this thesis in Agda.Computer Scienc
Efficient implementation of lazy suffix trees
Full text linkGiegerich R, Kurtz S, Stoye J. Efficient implementation of lazy suffix trees. SOFTWARE-PRACTICE & EXPERIENCE. 2003;33(11):1035-1049.We present an efficient implementation of a write-only top-down construction for suffix trees. Our implementation is based on a new, space-efficient representation of suffix trees that requires only 12 bytes per input character in the worst case, and 8.5 bytes per input character on average for a collection of files of different type. We show how to efficiently implement the lazy evaluation of suffix trees such that a subtree is evaluated only when it is traversed for the first time. Our experiments show that for the problem of searching many exact patterns in a fixed input string, the lazy top-down construction is often faster and more space efficient than other methods. Copyright (C) 2003 John Wiley Sons, Ltd
Logistic model trees
No full textTree induction methods and linear models are popular techniques for supervised learning tasks, both for the prediction of nominal classes and numeric values. For predicting numeric quantities, there has been work on combining these two schemes into `model trees', i.e. trees that contain linear regression functions at the leaves. In this paper, we present an algorithm that adapts this idea for classification problems, using logistic regression instead of linear regression. We use a stagewise fitting process to construct the logistic regression models that can select relevant attributes in the data in a natural way, and show how this approach can be used to build the logistic regression models at the leaves by incrementally refining those constructed at higher levels in the tree. We compare the performance of our algorithm to several other state-of-the-art learning schemes on 36 benchmark UCI datasets, and show that it produces accurate and compact classifiers
Famous and Historical Trees of Iowa,1996.
No full textThis booklet takes a look at the role trees and woodlands play in the development of Iowa's history. It identifies the individual and groups of trees that have historical significance in the state
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