Spot identification in two-dimensional patterns by a least-squares template matching.

1984 ◽  
Vol 30 (12) ◽  
pp. 1985-1988 ◽  
Author(s):  
I Pardowitz ◽  
H G Zimmer ◽  
V Neuhoff

Abstract The coordinates of the center of measured spots are nonlinearly transformed to get an optimal match between the transformed coordinates and the given coordinates of a reference pattern. The parameters of the transformation are determined by the minimum of a function of squared distances between all spots of the sample and of the reference pattern. The algorithm requires a priori defined correspondences between some pivot points in the sample and the reference and treats their distances differently from the others. The parameters of the transformation are the solutions of a system of nonlinear equations; their numerical values are obtained by iteration.

2017 ◽  
Vol 24 (12) ◽  
pp. 2494-2511 ◽  
Author(s):  
Mahmoud Behroozifar ◽  
Neda Habibi

The purpose of this study is to introduce a novel approach based on the operational matrix of a Riemann–Liouville fractional integral of Bernoulli polynomials, in order to numerically solve a class of fractional optimal control problems that arise in engineering. The method is computationally consistent and moreover, it has good flexibility in satisfying the initial and boundary conditions. The fractional derivative in the dynamic system is considered in the Caputo sense. The upper bound of the error for function approximation by a Bernoulli polynomial is also given. In order to numerically solve the given problem, the problem is transformed into a functional integral equation that is equivalent to the given problem. Then, the new integral equation is approximated by utilizing the Gauss quadrature formula. Afterwards, a system of nonlinear equations is yielded from the Lagrange multipliers method. Finally, the resultant system of nonlinear equations is solved by Newton’s iterative method. Some illustrative examples are included to demonstrate the applicability of the new technique.


2021 ◽  
pp. 80-85
Author(s):  
А.А. Лопухов ◽  
Ю.Н. Осипов ◽  
Е.В. Павлов ◽  
В.И. Ершов

Рассмотрен один из возможных подходов к математическому моделированию загрузки робототехнического комплекса (РТК) тяжелого класса на гусеничном шасси с независимой торсионной подвеской в транспортный самолет. Данный подход представляет собой часть обоснованной оценки авиатранспортабельности специальных РТК. Он базируется на построении и решении системы линейных уравнений, в результате чего определяются параметры, по которым оценивается факт «вписывания» конструкции образца РТК в размеры грузовой кабины самолета. Актуальность статьи обусловливается, во-первых, потребностью в создании специальных РТК тяжелого класса для применения при тушении пожаров на особо опасных объектах, во-вторых, значительным вкладом оценки возможностей по загрузке в самолеты РТК в априорную аналитическую оценку авиатранспортабельности специальных РТК как до создания опытных образцов, так и в ходе оперативной подготовки к перебазированию в районы чрезвычайных ситуаций и, в третьих, определенной сложностью графоаналитического моделирования рассматриваемой загрузки. The threat of man-made danger with such sources as accidents at radiation, chemical and explosive objects exists at present time. That’s why it is advisable to create heavy-class fire robotic complexes on a tracked chassis, as the most effective means of extinguishing fires in these conditions. The consequences of emergencies depend on a quick and timely response. Therefore, when creating the new promising fire equipment, one of the most important issues to be addressed is to ensure its air transportability. At the stage of development of advanced heavy-class fire-fighting robotic systems on a tracked chassis with the planned possibility of their air transportability, it is very important to perform an a priori assessment of this property before creating a prototype. Modeling of loading involves solving a variety of problems, the main and most complex of which is the calculation of the spatial position of the structure of a particular robotic complex model with a tracked chassis relative to the internal contours of the cargo cabin of the aircraft. There are several types of structures for springing support rollers of tracked chassis. This article discusses tracked chassis with independent torsion bar suspension widely used in modern military equipment. It is advisable to focus the development of heavy-class fire robotics on the use of torsion bar suspension. The calculation of parameters that form the basis of mathematical modeling consists in solving a system of nonlinear equations (including algebraic and trigonometric operations). One of the equations describes the condition of the equilibrium of forces, the second - the equilibrium of moments, the rest (according to the number of support rollers minus one) describe the conditions for the location of the torsion axes on a given construction axis. The proposed calculation method provides for the transformation of this system into a system of linear algebraic equations which ensure an approximate solution, and the organization of an iterative process that ensures the convergence of a sequence of approximate solutions to the solution of the original system of nonlinear equations. The approach presented in the article can be used as the basis for modeling the loading of a special robotic complex on a tracked chassis with an independent torsion suspension into the cargo cabin of a transport aircraft. In turn, this modeling allows us to perform the reasonable a priori assessment of the air transportability of the robotic complex, carried out both at the stage of layout of the sample during its creation and during operation.


1996 ◽  
Vol 8 (3) ◽  
pp. 133-144 ◽  
Author(s):  
María del Mar del Pozo Andrés ◽  
Jacques F A Braster

In this article we propose two research techniques that can bridge the gap between quantitative and qualitative historical research. These are: (1) a multiple regression approach that gives information about general patterns between numerical variables and the selection of outliers for qualitative analysis; (2) a homogeneity analysis with alternating least squares that results in a two-dimensional picture in which the relationships between categorical variables are graphically presented.


2019 ◽  
Vol 10 (4) ◽  
pp. 877-886 ◽  
Author(s):  
Chhavi Mangla ◽  
Musheer Ahmad ◽  
Moin Uddin

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Camilo Broc ◽  
Therese Truong ◽  
Benoit Liquet

Abstract Background The increasing number of genome-wide association studies (GWAS) has revealed several loci that are associated to multiple distinct phenotypes, suggesting the existence of pleiotropic effects. Highlighting these cross-phenotype genetic associations could help to identify and understand common biological mechanisms underlying some diseases. Common approaches test the association between genetic variants and multiple traits at the SNP level. In this paper, we propose a novel gene- and a pathway-level approach in the case where several independent GWAS on independent traits are available. The method is based on a generalization of the sparse group Partial Least Squares (sgPLS) to take into account groups of variables, and a Lasso penalization that links all independent data sets. This method, called joint-sgPLS, is able to convincingly detect signal at the variable level and at the group level. Results Our method has the advantage to propose a global readable model while coping with the architecture of data. It can outperform traditional methods and provides a wider insight in terms of a priori information. We compared the performance of the proposed method to other benchmark methods on simulated data and gave an example of application on real data with the aim to highlight common susceptibility variants to breast and thyroid cancers. Conclusion The joint-sgPLS shows interesting properties for detecting a signal. As an extension of the PLS, the method is suited for data with a large number of variables. The choice of Lasso penalization copes with architectures of groups of variables and observations sets. Furthermore, although the method has been applied to a genetic study, its formulation is adapted to any data with high number of variables and an exposed a priori architecture in other application fields.


2013 ◽  
Vol 694-697 ◽  
pp. 2545-2549 ◽  
Author(s):  
Qian Wen Cheng ◽  
Lu Ben Zhang ◽  
Hong Hua Chen

The key point researched by many scholars in the field of surveying and mapping is how to use the given geodetic height H measured by GPS to obtain the normal height. Although many commonly-used fitting methods have solved many problems, they all value the pending parameters as the nonrandom variables. Figuring out the best valuations, according to the traditional least square principle, only considers its trend or randomness, which is theoretically incomprehensive and have limitations in practice. Therefore, a method is needed not only considers its trend but also takes randomness into account. This method is called the least squares collocation.


Robotica ◽  
2000 ◽  
Vol 18 (3) ◽  
pp. 299-303 ◽  
Author(s):  
Carl-Henrik Oertel

Machine vision-based sensing enables automatic hover stabilization of helicopters. The evaluation of image data, which is produced by a camera looking straight to the ground, results in a drift free autonomous on-board position measurement system. No additional information about the appearance of the scenery seen by the camera (e.g. landmarks) is needed. The technique being applied is a combination of the 4D-approach with two dimensional template tracking of a priori unknown features.


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