Results 241 to 250 of about 32,845 (295)
Autoregulation of Woven Fabric Structure: Image-Based and Regression Analysis of Structural Homogeneity Under Varying Weaving Parameters. [PDF]
Owczarek M.
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Evaluating Dermoscopic Features of Nail Unit Squamous Cell Carcinoma: A Systematic Review and Sub-Analysis. [PDF]
Tordjman L +3 more
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3D-printed concrete with in-process embedded fiber-reinforced polymer grid reinforcement. [PDF]
Sun HQ, Xie SS, Zeng JJ, Zhuge Y.
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The Effect of CO2 Laser Treatment on the Composition of Cotton/Polyester/Metal Fabric. [PDF]
Skromulis A +9 more
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Structure and air permeability of polyamide and polyester parachute fabrics. [PDF]
Křemenáková D +2 more
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Regional adaptation to mosquito vectors shapes Plasmodium falciparum populations
Loesbanluechai D +17 more
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The relation between Sen's decomposition of the weak axiom of revealed preferences (WARP), and WARP directional decomposition introduced in Nosratabadi (2017) is investigated. It is argued that the latter generalizes the former. A pairwise transitive WARP decomposition consistent with Sen's property a is given.
Nosratabadi, Hassan, Hassan Nosratabadi
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IEEE Transactions on Visualization and Computer Graphics, 2005
The task of computer-based free-form shape design is fraught with practical and conceptual difficulties. Incorporating elements of traditional clay sculpting has long been recognized as a means of shielding the user from these complexities. We present warp sculpting, a variant of spatial deformation, which allows deformations to be initiated by the ...
James E. Gain, Patrick C. Marais
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The task of computer-based free-form shape design is fraught with practical and conceptual difficulties. Incorporating elements of traditional clay sculpting has long been recognized as a means of shielding the user from these complexities. We present warp sculpting, a variant of spatial deformation, which allows deformations to be initiated by the ...
James E. Gain, Patrick C. Marais
openaire +2 more sources
WARP: Time Warping for Periodicity Detection
Fifth IEEE International Conference on Data Mining (ICDM'05), 2006Periodicity mining is used for predicting trends in time series data. Periodicity detection is an essential process in periodicity mining to discover potential periodicity rates. Existing periodicity detection algorithms do not take into account the presence of noise, which is inevitable in almost every real-world time series data.
Mohamed G. Elfeky +2 more
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