Search results for "vector [form factor]"
showing 10 items of 770 documents
Explanation of theΔ5/2−(1930)as aρΔbound state
2009
We use the $\ensuremath{\rho}\ensuremath{\Delta}$ interaction in the hidden gauge formalism to dynamically generate ${N}^{*}$ and ${\ensuremath{\Delta}}^{*}$ resonances. We show, through a comparison of the results from this analysis and from a quark model study with data, that the ${\ensuremath{\Delta}}_{5/{2}^{\ensuremath{-}}}(1930)$, ${\ensuremath{\Delta}}_{3/{2}^{\ensuremath{-}}}(1940)$, and ${\ensuremath{\Delta}}_{1/{2}^{\ensuremath{-}}}(1900)$ resonances can be assigned to $\ensuremath{\rho}\ensuremath{\Delta}$ bound states. More precisely the ${\ensuremath{\Delta}}_{5/{2}^{\ensuremath{-}}}(1930)$ can be interpreted as a $\ensuremath{\rho}\ensuremath{\Delta}$ bound state whereas the $…
Braiding minimal sets of vector fields
2002
We extend a classical but fundamental theorem of knot and braid theories to describe the geometry of nonsingular minimal sets of 3-dimensional flows.
The index of stable critical points
2002
Abstract In this paper we show that in dimension greater or equal than 3 the index of a stable critical point can be any integer. More concretely, given any k∈ Z and n⩾3 we construct a C ∞ vector field on R n with a unique critical point which is stable (in positive and negative time) and has index equal to k. This result extends previous ones on the index of stable critical points.
Superior Performances of the Neural Network on the Masses Lesions Classification through Morphological Lesion Differences
2007
Purpose of this work is to develop an automatic classification system that could be useful for radiologists in the breast cancer investigation. The software has been designed in the framework of the MAGIC-5 collaboration. In an automatic classification system the suspicious regions with high probability to include a lesion are extracted from the image as regions of interest (ROIs). Each ROI is characterized by some features based generally on morphological lesion differences. A study in the space features representation is made and some classifiers are tested to distinguish the pathological regions from the healthy ones. The results provided in terms of sensitivity and specificity will be p…
Perceptual adaptive insensitivity for support vector machine image coding.
2005
Support vector machine (SVM) learning has been recently proposed for image compression in the frequency domain using a constant epsilon-insensitivity zone by Robinson and Kecman. However, according to the statistical properties of natural images and the properties of human perception, a constant insensitivity makes sense in the spatial domain but it is certainly not a good option in a frequency domain. In fact, in their approach, they made a fixed low-pass assumption as the number of discrete cosine transform (DCT) coefficients to be used in the training was limited. This paper extends the work of Robinson and Kecman by proposing the use of adaptive insensitivity SVMs [2] for image coding u…
An efficient distributed algorithm for generating and updating multicast trees
2006
As group applications are becoming widespread, efficient network utilization becomes a growing concern. Multicast transmission represents a necessary lower network service for the wide diffusion of new multimedia network applications. Multicast transmission may use network resources more efficiently than multiple point-to-point messages; however, creating optimal multicast trees (Steiner Tree Problem in networks) is prohibitively expensive. This paper proposes a distributed algorithm for the heuristic solution of the Steiner Tree Problem, allowing the construction of effective distribution trees using a coordination protocol among the network nodes. Furthermore, we propose a novel distribut…
A new Media Access Control layer Quality of Service multicast scheme for IEEE 802.11s based wireless mesh networks
2014
Inderscience Publishers; International audience; We propose a new Media Access Control (MAC) layer enabling Quality of Service (QoS) multicast scheme for IEEE 802.11s networks, where a unicast routing protocol called HWMP (Hybrid Wireless Mesh Protocol) is defined. The HWMP protocol is more adapted for best effort traffic, that's why its usage is not suitable for real time multimedia applications. The goal of our proposed mechanism is to take into account multicast communication under QoS constraints for the IEEE 802.11s mesh networks where no QoS multicasting has been defined. Our multicasting scheme handles QoS guarantee for real time applications. Indeed, our scheme is based on finding t…
Support vector machines in engineering: an overview
2014
This paper provides an overview of the support vector machine SVM methodology and its applicability to real-world engineering problems. Specifically, the aim of this study is to review the current state of the SVM technique, and to show some of its latest successful results in real-world problems present in different engineering fields. The paper starts by reviewing the main basic concepts of SVMs and kernel methods. Kernel theory, SVMs, support vector regression SVR, and SVM in signal processing and hybridization of SVMs with meta-heuristics are fully described in the first part of this paper. The adoption of SVMs in engineering is nowadays a fact. As we illustrate in this paper, SVMs can …
SVM approximation for real-time image segmentation by using an improved hyperrectangles-based method
2003
A real-time implementation of an approximation of the support vector machine (SVM) decision rule is proposed. This method is based on an improvement of a supervised classification method using hyperrectangles, which is useful for real-time image segmentation. The final decision combines the accuracy of the SVM learning algorithm and the speed of a hyperrectangles-based method. We review the principles of the classification methods and we evaluate the hardware implementation cost of each method. We present the combination algorithm, which consists of rejecting ambiguities in the learning set using SVM decision, before using the learning step of the hyperrectangles-based method. We present re…
Learning spatial filters for multispectral image segmentation.
2010
International audience; We present a novel filtering method for multispectral satel- lite image classification. The proposed method learns a set of spatial filters that maximize class separability of binary support vector machine (SVM) through a gradient descent approach. Regularization issues are discussed in detail and a Frobenius-norm regularization is proposed to efficiently exclude uninformative filters coefficients. Experiments car- ried out on multiclass one-against-all classification and tar- get detection show the capabilities of the learned spatial fil- ters.