Influence of pre-defined non-dimensional ratios and affine mapping on ship properties

2015 ◽  
pp. 503-512
Keyword(s):  
Affine Mapping

scholarly journals On the Affine Image of a Rational Surface of Revolution

Mathematics ◽  
2020 ◽  
Vol 8 (11) ◽  
pp. 2061
Author(s):  
Juan G. Alcázar
Keyword(s):  
Differential Geometry ◽  
Affine Transformation ◽  
Rational Surface ◽  
Affine Differential Geometry ◽  
Affine Mapping ◽  
Surfaces Of Revolution ◽  
Surface Of Revolution ◽  
Affine Image ◽  
Fixed Line ◽  
The Given

We study the properties of the image of a rational surface of revolution under a nonsingular affine mapping. We prove that this image has a notable property, namely that all the affine normal lines, a concept that appears in the context of affine differential geometry, created by Blaschke in the first decades of the 20th century, intersect a fixed line. Given a rational surface with this property, which can be algorithmically checked, we provide an algorithmic method to find a surface of revolution, if it exists, whose image under an affine mapping is the given surface; the algorithm also finds the affine transformation mapping one surface onto the other. Finally, we also prove that the only rational affine surfaces of rotation, a generalization of surfaces of revolution that arises in the context of affine differential geometry, and which includes surfaces of revolution as a subtype, affinely transforming into a surface of revolution are the surfaces of revolution, and that in that case the affine mapping must be a similarity.

SELECTING AFFINE MAPPINGS BASED ON PERFORMANCE ESTIMATION

1994 ◽  
Vol 04 (03) ◽  
pp. 205-219 ◽  
Author(s):  
WAYNE KELLY ◽  
WILLIAM PUGH
Keyword(s):  
Lower Bound ◽  
Performance Estimation ◽  
Affine Mapping ◽  
Affine Mappings ◽  
Iteration Space ◽  
Do So ◽  
Loop Skewing

In previous work, we presented a framework for unifying iteration reordering transformations such as loop interchange, loop distribution, loop skewing and statement reordering. The framework provides a uniform way to represent and reason about transformations. However, it does not provide a way to decide which transformation(s) should be applied to a given program. This paper describes a way to make such decisions within the context of the framework. The framework is based on the idea that a transformation can be represented as an affine mapping from the original iteration space to a new iteration space. We show how we can estimate the performance of a program by considering only the mapping from which it was produced. We also show how to produce a lower bound on performance given only a partially specified mapping. Our ability to estimate performance directly from mappings and to do so even for partially specified mappings allows us to efficiently find mappings which will produce good code.

On idempotent affine mappings

1983 ◽  
Vol 93 (3-4) ◽  
pp. 345-348 ◽  
Author(s):  
R. J. H. Dawlings
Keyword(s):  
Vector Space ◽  
Product Space ◽  
Inner Product Space ◽  
Inner Product ◽  
Affine Mapping ◽  
Affine Mappings

SynopsisLet V be a vector space and End (V) the semigroup of endomorphisms of V. An affine mapping of V is a map A: V → V given by xA = xα + a, where a belongs to End (V) and a is some element of V. Let (V) be the semigroup of affine mappings of V.Let E' denote the non-injective idempotents of End (V) and let ℰ denote the idempotents of (V). In this paper 〈ℰ〉 is determined in terms of 〈E′〉 when End (V) consists of all endomorphisms of V and when End (V) only contains the continuous endomorphisms (in which case we restrict V to being an inner product space).

scholarly journals Robust Stabilised Visual Tracker for Vehicle Tracking

2018 ◽  
Vol 68 (3) ◽  
pp. 307 ◽  
Author(s):  
Kamlesh Verma ◽  
Avnish Kumar ◽  
Debashis Ghosh
Keyword(s):  
Sparse Representation ◽  
Target Tracking ◽  
Visual Tracking ◽  
Vehicle Tracking ◽  
Affine Mapping ◽  
Linear Combinations ◽  
Target Template ◽  
Target Templates ◽  
Previous Frame ◽  
Novel Algorithm

<p>Visual tracking is performed in a stabilised video. If the input video to the tracker algorithm is itself destabilised, incorrect motion vectors will cause a serious drift in tracking. Therefore video stabilisation is must before tracking. A novel algorithm is developed which simultaneously takes care of video stabilisation and target tracking. Target templates in just previous frame are stored in positive and negative repositories followed by Affine mapping. Then optimised affine parameters are used to stabilise the video. Target of interest in the next frame is approximated using linear combinations of previous target templates. Proposed modified L1 minimisation method is used to solve sparse representation of target in the target template subspace. Occlusion problem is minimised using the inherent energy of coefficients. Accurate tracking results have been obtained in destabilised videos.</p>

scholarly journals 3-D from 2-D Using Warping Transformations .

2014 ◽  
Vol 13 (4) ◽  
pp. 4430-4455 ◽  
Author(s):  
M. A. Ashabrawy ◽  
E. E. Elbehadi
Keyword(s):  
Similarity Transformation ◽  
Image Warping ◽  
Affine Mapping ◽  
Single Image ◽  
Projective Mapping ◽  
Still Image ◽  
Bilinear Mapping ◽  
The Third ◽  
The Subject ◽  
Third Dimension

Shown in this paper are methods on how to find the third dimension of a single image or from the two views of the image taking in a different angle using the method more accurate and faster to get to the third dimension in the following cases: One image of the same scene. Two views of the same scene from two different perspectives. Pictures of parts of the same scene. Set of pictures for different views of the work of the subject Panorama. This method is known Image Warping, which falls below a set of transfers such as (Affine - Bilinear - Projective - Mosaic – Similarity transformation) was compared to the work of transfers between the previous and this will be applied to more pictures. The idea is based on building code software is built on the programming language Visual C + + with the library for drawing an OpenGL program Matlab, which way can build a model of the following conversions, which fall under the so-called image warping of the conversion linear Bilinear Mapping and conversion Affine Mapping and conversion imagery Projective Mapping . shown in this paper are methods on how to correct camera exposure changes and how to blend the stitching line between the images. We will show panorama photos generated from both still image.

scholarly journals The stability of a generalized affine functional equation in fuzzy normed spaces

2016 ◽  
Vol 100 (114) ◽  
pp. 163-181 ◽  
Author(s):  
M. Mursaleen ◽  
Khursheed Ansari
Keyword(s):  
Functional Equation ◽  
Fixed Point ◽  
General Solution ◽  
Affine Mapping ◽  
Normed Spaces ◽  
Alternative Method ◽  
The Stability ◽  
Rassias Stability

We obtain the general solution of the following functional equation f(kx1+x2+???+xk)+f(x1+kx2+???+xk)+???+f(x1+x2+???+kxk)+f(x1)+ f(x2)+???+ f(xk)= 2kf(x1+ x2+???+xk), k ? 2. We establish the Hyers-Ulam-Rassias stability of the above functional equation in the fuzzy normed spaces. More precisely, we show under suitable conditions that a fuzzy q-almost affine mapping can be approximated by an affine mapping. Further, we determine the stability of same functional equation by using fixed point alternative method in fuzzy normed spaces.

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