Learning about stem by building a geodesic houseboat mrw 070714Michael R Weekes
In 2013, I built a geodesic houseboat right in the Buffalo Ship Canal, in just five weeks, for less than $2,000. We had our won little waterfront get-away.
Never being satisfied, that led to a book, Building a New and Useful Buffalo, which introduces the idea of a new interconnection framework to accelerate my community's quality of life and economy.
It also led to my development of a class on building domes (thanks to the HILA Road series / youtube) and now it compliments the desire to inspire STEM careers by making something fun.
I presented this at Alfred State SUNY in Alfred, NY to PhD's and teachers loved it. I was humbled by the experience. I am a 30 yr. engineering veteran experiencing the joy of education as a second life.
I wish to share with you and solicit your input on what content you would recommend for a new National STEM
If you would like to help build a 32' dia. geodesic greenhouse this summer in Downtown Buffalo, adjacent to the Buffalo Niagara Medical Campus, contact the author at michaellovesbuffalo@gmail.com
Thank you, enjoy and SHARE this!
This document contains terms related to Earth and geography such as extraterrestrial, geocentric, geodesic, geography, geology, geometry, internment, Mediterranean, subterranean, terrace, terra firma, terrain, and territory.
This document discusses consistent approximation of geodesics, or shortest paths, on graphs representing surfaces. It presents three key ideas:
1) Sampling the surface at sufficient density and ensuring local connectivity in the graph is necessary for consistent geodesic approximation.
2) Surface properties like minimum curvature radius and branch separation must be sufficiently large relative to the sampling distance for consistency.
3) Both sufficient sampling density and bounds on edge lengths are needed, as insufficient density or excessively long edges can lead to inconsistent approximations.
This document discusses geodesic data processing on Riemannian manifolds. It defines geodesic distances as the shortest path between two points on the manifold according to the Riemannian metric. Methods are presented for computing geodesic distances and curves, including iterative schemes and fast marching. Applications discussed include shape recognition using geodesic statistics and geodesic meshing.
Tony TUNG @ Matsuyama Lab., Kyoto University 2007-2014Tony Tung
Dynamic Surface Modeling & Applications
Dr. Tony TUNG,
Assistant Professor, Kyoto University
Matsuyama Laboratory, Graduate School of Informatics
2007-2014
Geodesic Method in Computer Vision and GraphicsGabriel Peyré
This document discusses geodesic methods in computer vision and graphics. It begins with an overview of topics including Riemannian data modelling, numerical computations of geodesics, geodesic image segmentation, geodesic shape representation, geodesic meshing, and inverse problems with geodesic fidelity. It then provides details on parametric surfaces, Riemannian manifolds, anisotropy and geodesics, the eikonal equation and viscosity solution, discretization methods, and numerical schemes for solving the fixed point equation.
This document provides an introduction to manifold learning. It defines what a manifold is and discusses how data lies on low-dimensional manifolds even when represented in high-dimensional space. It introduces several linear and nonlinear manifold learning algorithms, including Principal Components Analysis, Multidimensional Scaling, Isomap, Locally Linear Embedding, and Laplacian Eigenmaps. For each algorithm, it provides a brief overview of the motivation, key steps, and examples of applications like super-resolution imaging.
Learning about stem by building a geodesic houseboat mrw 070714Michael R Weekes
In 2013, I built a geodesic houseboat right in the Buffalo Ship Canal, in just five weeks, for less than $2,000. We had our won little waterfront get-away.
Never being satisfied, that led to a book, Building a New and Useful Buffalo, which introduces the idea of a new interconnection framework to accelerate my community's quality of life and economy.
It also led to my development of a class on building domes (thanks to the HILA Road series / youtube) and now it compliments the desire to inspire STEM careers by making something fun.
I presented this at Alfred State SUNY in Alfred, NY to PhD's and teachers loved it. I was humbled by the experience. I am a 30 yr. engineering veteran experiencing the joy of education as a second life.
I wish to share with you and solicit your input on what content you would recommend for a new National STEM
If you would like to help build a 32' dia. geodesic greenhouse this summer in Downtown Buffalo, adjacent to the Buffalo Niagara Medical Campus, contact the author at michaellovesbuffalo@gmail.com
Thank you, enjoy and SHARE this!
This document contains terms related to Earth and geography such as extraterrestrial, geocentric, geodesic, geography, geology, geometry, internment, Mediterranean, subterranean, terrace, terra firma, terrain, and territory.
This document discusses consistent approximation of geodesics, or shortest paths, on graphs representing surfaces. It presents three key ideas:
1) Sampling the surface at sufficient density and ensuring local connectivity in the graph is necessary for consistent geodesic approximation.
2) Surface properties like minimum curvature radius and branch separation must be sufficiently large relative to the sampling distance for consistency.
3) Both sufficient sampling density and bounds on edge lengths are needed, as insufficient density or excessively long edges can lead to inconsistent approximations.
This document discusses geodesic data processing on Riemannian manifolds. It defines geodesic distances as the shortest path between two points on the manifold according to the Riemannian metric. Methods are presented for computing geodesic distances and curves, including iterative schemes and fast marching. Applications discussed include shape recognition using geodesic statistics and geodesic meshing.
Tony TUNG @ Matsuyama Lab., Kyoto University 2007-2014Tony Tung
Dynamic Surface Modeling & Applications
Dr. Tony TUNG,
Assistant Professor, Kyoto University
Matsuyama Laboratory, Graduate School of Informatics
2007-2014
Geodesic Method in Computer Vision and GraphicsGabriel Peyré
This document discusses geodesic methods in computer vision and graphics. It begins with an overview of topics including Riemannian data modelling, numerical computations of geodesics, geodesic image segmentation, geodesic shape representation, geodesic meshing, and inverse problems with geodesic fidelity. It then provides details on parametric surfaces, Riemannian manifolds, anisotropy and geodesics, the eikonal equation and viscosity solution, discretization methods, and numerical schemes for solving the fixed point equation.
This document provides an introduction to manifold learning. It defines what a manifold is and discusses how data lies on low-dimensional manifolds even when represented in high-dimensional space. It introduces several linear and nonlinear manifold learning algorithms, including Principal Components Analysis, Multidimensional Scaling, Isomap, Locally Linear Embedding, and Laplacian Eigenmaps. For each algorithm, it provides a brief overview of the motivation, key steps, and examples of applications like super-resolution imaging.
Animals monstruosos is a Spanish language document about monstrous animals. It discusses several legendary creatures that were thought to exist such as dragons and griffins. The document suggests that while these animals were once believed to be real, they are now understood to likely be mythical creatures without factual existence.
Animals monstruosos is a Spanish language document about monstrous animals. It discusses several legendary creatures that were thought to exist such as dragons and griffins. The document suggests that while these animals were once believed to be real, they are now understood to likely be mythical creatures without factual existence.