998 resultados para Shaker architecture--Maine--Alfred--Maps.
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Shows buildings pictorially.
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Addressed to Elder Otis Sawyer; concerning legal rights and obligations of trustee or agent for the Shaker community.
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Red and black pencil on blueprint. Duncan Chandler, architect. Residence, drive, walks in pencil over topo plan. Unsigned. 105 cm. x 88 cm. Scale: 1"=8' [from photographic copy by Lance Burgharrdt]
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Blueprint with pencil notations. Roads, residence, some contour lines. Duncan Chandler, architect. Unsigned. 94 cm. x 83 cm. No scale [from photographic copy by Lance Burgharrdt]
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Blueprint with notations. Note: Suggested treatment for living hall windows and living room arbor. Duncan Chandler, architect. Unsigned. 78 cm. x 30 cm. Scale: 1/8"=1' [from photographic copy by Lance Burgharrdt]
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Blueprint with pencil annotations. Markings on portions of grounds. Duncan Chandler, architect. Unsigned. 77 cm. x 70 cm. Scale: 3/32"=1' [from photographic copy by Lance Burgharrdt]
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Ink on linen. Location, type of plantings, notes. At lower left: number 2 in ink. Signed. 82 cm. x 44 cm. Scale: 1"=5' [from photographic copy by Lance Burgharrdt]
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Ink and pencil on linen. Plan and several section elevations. At lower right: number 4 in pencil. Unsigned [from photographic copy by Lance Burgharrdt]
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Ink on linen. Location of ledges, trees, boulders, paths, walls. Dimensions of cottage. Note under title: Made by hand level. At lower right: numnber 5 in pencil. Unsigned. 63 cm. x 36 cm. Scale: 1"=10' [from photographic copy by Lance Burgharrdt]
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Ink on linen. Location, type of plantings. At lower right: number 7 in pencil. Signed. 61 cm. x 36 cm. Scale: 1"=10' [from photographic copy by Lance Burgharrdt]
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A new neural network architecture is introduced for incremental supervised learning of recognition categories and multidimensional maps in response to arbitrary sequences of analog or binary input vectors. The architecture, called Fuzzy ARTMAP, achieves a synthesis of fuzzy logic and Adaptive Resonance Theory (ART) neural networks by exploiting a close formal similarity between the computations of fuzzy subsethood and ART category choice, resonance, and learning. Fuzzy ARTMAP also realizes a new Minimax Learning Rule that conjointly minimizes predictive error and maximizes code compression, or generalization. This is achieved by a match tracking process that increases the ART vigilance parameter by the minimum amount needed to correct a predictive error. As a result, the system automatically learns a minimal number of recognition categories, or "hidden units", to met accuracy criteria. Category proliferation is prevented by normalizing input vectors at a preprocessing stage. A normalization procedure called complement coding leads to a symmetric theory in which the MIN operator (Λ) and the MAX operator (v) of fuzzy logic play complementary roles. Complement coding uses on-cells and off-cells to represent the input pattern, and preserves individual feature amplitudes while normalizing the total on-cell/off-cell vector. Learning is stable because all adaptive weights can only decrease in time. Decreasing weights correspond to increasing sizes of category "boxes". Smaller vigilance values lead to larger category boxes. Improved prediction is achieved by training the system several times using different orderings of the input set. This voting strategy can also be used to assign probability estimates to competing predictions given small, noisy, or incomplete training sets. Four classes of simulations illustrate Fuzzy ARTMAP performance as compared to benchmark back propagation and genetic algorithm systems. These simulations include (i) finding points inside vs. outside a circle; (ii) learning to tell two spirals apart; (iii) incremental approximation of a piecewise continuous function; and (iv) a letter recognition database. The Fuzzy ARTMAP system is also compared to Salzberg's NGE system and to Simpson's FMMC system.
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Mode of access: Internet.
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Urban maps discusses new ways and tools to read and navigate the contemporary city. Each chapter investigates a possible approach to unravel the complexity of contemporary urban forms. Each tool is first defined, introducing its philosophical background, and is then discussed with case studies, showing its relevance for the navigation of the built environment. Urbanism classics such as the work of Lynch, Jacobs, Venuti and Scott-Brown, Lefebrve and Walter Benjamin are fundamental in setting the framework of the volume. In the introduction cities and mapping are first discussed, the former are illustrated as ‘a composite of invisible networks devoid of landmarks and overrun by nodes’ (p. 3), and ‘a series of unbounded spaces where mass production and mass consumption reproduce a standardised quasi-global culture’ (p. 6).
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We extended genetic linkage analysis - an analysis widely used in quantitative genetics - to 3D images to analyze single gene effects on brain fiber architecture. We collected 4 Tesla diffusion tensor images (DTI) and genotype data from 258 healthy adult twins and their non-twin siblings. After high-dimensional fluid registration, at each voxel we estimated the genetic linkage between the single nucleotide polymorphism (SNP), Val66Met (dbSNP number rs6265), of the BDNF gene (brain-derived neurotrophic factor) with fractional anisotropy (FA) derived from each subject's DTI scan, by fitting structural equation models (SEM) from quantitative genetics. We also examined how image filtering affects the effect sizes for genetic linkage by examining how the overall significance of voxelwise effects varied with respect to full width at half maximum (FWHM) of the Gaussian smoothing applied to the FA images. Raw FA maps with no smoothing yielded the greatest sensitivity to detect gene effects, when corrected for multiple comparisons using the false discovery rate (FDR) procedure. The BDNF polymorphism significantly contributed to the variation in FA in the posterior cingulate gyrus, where it accounted for around 90-95% of the total variance in FA. Our study generated the first maps to visualize the effect of the BDNF gene on brain fiber integrity, suggesting that common genetic variants may strongly determine white matter integrity.