Search results for "Linear"
showing 10 items of 7165 documents
Mathematical Model of Unmanned Aircraft In Ground Effect for Optimal Collision Avoidance
2011
The fundamental aim of the present paper is to model the aerodynamic characteristics of an Unmanned Aerial Vehicle(UAV) flying in ground effect. The second aim is to determine the relationship between the optimal avoidance maneuver and the control to execute it. In fact, this relationship is basilar to the development of a guidance scheme capable of approximating the optimal trajectory in real time. In the first part of this work ,a non-linear model is built in order to model the aerodynamic characteristics of an UAV flying In Ground Effect. To use a single model in the whole range of flying altitude, aerodynamic coefficients are modeled by means of hyperbolic equations. In particular, thes…
Amplification of Interstory Drift and Velocity for the Passive Control of Structural Vibrations
2008
Mitigation of structural damage due to earthquake ground motion may be performed by inserting dampers in the structure. In order to enhance the damping effect various toggle brace configurations have been recently proposed. In this paper these equipments are analyzed in detail and compared with a new one here proposed. The analysis is performed by taking into account the inherent nonlinearities of the damper by means of stochastic analysis and validated by using time histories of recorder accelerograms and by the stochastic analysis using spectrum consistent power spectral density.
European vestibular experiments on the Spacelab-1 mission: 2. Experimental equipment and methods
1986
A series of vestibular experiments were performed in conjunction with the first Spacelab mission, consisting of sets of pre-, in- and postflight tests. A multipurpose experimental apparatus used for the diverse flight and ground tests is presented. Additional apparatus together with the multi-purpose package were used in the baseline data collection facility at the landing site at NASA Dryden Flight Research Facility for the ground tests. The tests involved optokinetic, caloric and mechanical (whole-body or head-alone) stimulation. The latter included linear acceleration in the subject's x, y and z axes, static roll and yaw about an earth-vertical axis. Physiological parameters such as elec…
Conjugate Gradient Method for Brain Magnetic Resonance Images Segmentation
2018
Part 8: Pattern Recognition and Image Processing; International audience; Image segmentation is the process of partitioning the image into regions of interest in order to provide a meaningful representation of information. Nowadays, segmentation has become a necessity in many practical medical imaging methods as locating tumors and diseases. Hidden Markov Random Field model is one of several techniques used in image segmentation. It provides an elegant way to model the segmentation process. This modeling leads to the minimization of an objective function. Conjugate Gradient algorithm (CG) is one of the best known optimization techniques. This paper proposes the use of the nonlinear Conjugat…
Formal Group Laws for Affine Kac-Moody groups and group quantization
1987
We describe a method for obtaining Formal Group Laws from the structure constants of Affine Kac-Moody groups and then apply a group manifold quantization procedure which permits construction of physical representations by using only canonical structures on the group. As an intermediate step we get an explicit expression for two-cocycles on Loop Groups. The programme is applied to the AffineSU(2) group.
On a relation between massive Yang-Mills theories and dual string models
1983
The relations between mass terms in Yang-Mills theories, projective representations of the group of gauge transformations, boundary conditions on vector potentials and Schwinger terms in local charge algebra commutation relations are discussed. The commutation relations (with Schwinger terms) are similar to the current algebra commutation relations of the SU(N) extended dual string model.
An efficient algorithm to estimate the sparse group structure of an high-dimensional generalized linear model
2014
Massive regression is one of the new frontiers of computational statistics. In this paper we propose a generalization of the group least angle regression method based on the differential geometrical structure of a generalized linear model specified by a fixed and known group structure of the predictors. An efficient algorithm is also proposed to compute the proposed solution curve.
H$^{-}$ extraction systems for CERN’s Linac4 H$^{-}$ ion source
2018
Linac4 is a 160 MeV linear H accelerator at CERN. It is an essential part of the beam luminosity upgrade of the Large Hadron Collider (LHC) and will be the primary injector into the chain of circular accelerators. It aims at increasing the beam brightness by a factor of 2, when compared to the currently used 50 MeV linear proton accelerator, Linac2. Linac4’s ion source is a cesiated RF-plasma H ion source. Several beam extraction systems were designed for H beams of 45 keV energy, 50 mA intensity and an electron to H ratio smaller than 5. The goal was to extract a beam with an rms-emittance of mm mrad. One of the main challenges in designing an H extraction system is dumping of the co-extra…
Fine-mapping of the B-cell epitope domain at the N-terminus of the preS2 region of the hepatitis B surface antigen
2002
In this study, we report the exact localization and substitutional characterization of a B-cell epitope domain at the N-terminus of the preS2 region of the hepatitis B surface antigen. A set of deletion variants containing preS2 sequences of different length was generated on the basis of frCP as a carrier. It was found after Western blot analysis that three monoclonal antibodies (MAbs) (2-11B1, 3-11C2, HB.OT10) recognized the linear preS2 sequence within the amino acid (aa) stretch 3-WNSTTFHQTLQDP-13. The importance of each aa residue of the epitope was proved by comparison of antibody binding to alanine-substituted peptides in both free-peptide and Pepscan variants.
Using Landsat TM and field data to produce maps of predicted bird densities in Latvian farmland
2005
Models of farmland bird population densities established from field surveys were applied to classified satellite data for mapping of predicted bird numbers. The field survey system was based upon point counts of birds and descriptions of their habitat within a 200 m radius. The relationship between birds and habitats was analysed by means of multiple regression analysis. The resulting regression models were coded into classified Landsat Enhanced Thematic Mapper (ETM+) data which had similar land cover/use classes as the field observation data. With the use of a circular 200 m radius moving window approach, simulated maps of predicted bird population densities were produced. The results indi…