Search results for "layer"
showing 10 items of 2667 documents
Discontinuous Galerkin models for composite multilayered shells with higher order kinematics
2021
Composite multilayered shells are widely employed in aerospace, automotive and civil engineering as weight-saving structural components. In multilayered shells, despite its versatility, the interplay between the curved geometry and the properties of the composite layers induces a complex distribution of the mechanical fields, which must be accurately resolved to safely employ generally curved composite shells as load-bearing structures. The problem can be addressed through the two-dimensional shell theories, which are based on suitable assumptions on the behavior of the mechanical fields throughout the thickness of the considered structures and are a viable strategy for reducing the computa…
Derivatives and inverse of a linear-nonlinear multi-layer spatial vision model
2016
Linear-nonlinear transforms are interesting in vision science because they are key in modeling a number of perceptual experiences such as color, motion or spatial texture. Here we first show that a number of issues in vision may be addressed through an analytic expression of the Jacobian of these linear-nonlinear transforms. The particular model analyzed afterwards (an extension of [Malo & Simoncelli SPIE 2015]) is illustrative because it consists of a cascade of standard linear-nonlinear modules. Each module roughly corresponds to a known psychophysical mechanism: (1) linear spectral integration and nonlinear brightness-from-luminance computation, (2) linear pooling of local brightness…
BELM: Bayesian Extreme Learning Machine
2011
The theory of extreme learning machine (ELM) has become very popular on the last few years. ELM is a new approach for learning the parameters of the hidden layers of a multilayer neural network (as the multilayer perceptron or the radial basis function neural network). Its main advantage is the lower computational cost, which is especially relevant when dealing with many patterns defined in a high-dimensional space. This brief proposes a bayesian approach to ELM, which presents some advantages over other approaches: it allows the introduction of a priori knowledge; obtains the confidence intervals (CIs) without the need of applying methods that are computationally intensive, e.g., bootstrap…
Adaptive Medium Access Control for Distributed Processing in Wireless Sensor Networks
2019
Signal and information processing tasks over Wireless Sensor Networks can be successfully accomplished by means of a distributed implementation among the nodes. Existing distributed schemes are commonly based on iterative strategies that imply a huge demand of one-hop transmissions, which must be efficiently processed by the lower layers of the nodes. At the link layer, general purpose medium access (MAC) policies for wireless communications usually focus on avoiding collisions. These existing approaches result in a reduction of the number of simultaneous transmissions, and an underutilization of the channel as a consequence. This leads to a decrease in the performance of the distributed ta…
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…
Multilayer perceptron neural networks and radial-basis function networks as tools to forecast accumulation of deoxynivalenol in barley seeds contamin…
2011
The capacity of multi-layer perceptron artificial neural networks (MLP-ANN) and radial-basis function networks (RBFNs) to predict deoxynivalenol (DON) accumulation in barley seeds contaminated with Fusarium culmorum under different conditions has been assessed. Temperature (20-28 °C), water activity (0.94-0.98), inoculum size (7-15 mm diameter), and time were the inputs while DON concentration was the output. The dataset was used to train, validate and test many ANNs. Minimizing the mean-square error (MSE) was used to choose the optimal network. Single-layer perceptrons with low number of hidden nodes proved better than double-layer perceptrons, but the performance depended on the training …
Out-of-Band Signaling Scheme for High Speed Wireless LANs
2007
In recent years, the physical layer data rate provided by 802.11 Wireless LANs has dramatically increased thanks to significant advances in the modulation and coding techniques employed. However, previous studies show that the 802.11 MAC operation, namely the distributed coordination function (DCF), represents a limiting factor: the throughput efficiency drops as the channel bit rate increases, and a throughput upper limit does indeed exist when the channel bit rate goes to infinite high. These findings indicate that the performance of the DCF protocol will not be efficiently improved by merely increasing the channel bit rate. This paper shows that the DCF performance may significantly bene…
A Kalman Filter Approach for Distinguishing Channel and Collision Errors in IEEE 802.11 Networks
2008
In the last years, several strategies for maximizing the throughput performance of IEEE 802.11 networks have been proposed in literature. Specifically, it has been shown that optimizations are possible both at the medium access control (MAC) layer, and at the physical (PHY) layer. In fact, at the MAC layer, it is possible to minimize the channel waste due to collisions and backoff expiration times, by tuning the minimum contention window as a function of the network congestion level. At the PHY layer, it is possible to improve the transmission robustness, by selecting a suitable modulation/coding scheme as a function of the channel quality perceived by the stations. However, the feasibility…
Measuring the weather’s impact on MAC layer over 2.4GHz outdoor radio links
2015
The weather s impact on the performance of a radio link at the 2.4 GHz ISM (Industry, Scientific and Medical) band had not been yet studied in great detail up to now as it is generally believed that the ultra-high frequency band is not significantly affected by weather conditions. However, our study shows significant correlations between meteorological variables and control frame errors at MAC (Medium Access Control) layer of the IEEE 802.11b/g standard. This study is performed over an outdoor radio link setting which has been monitored for several months. Moreover, we check if link distance and so modulation scheme and data rate are also decisive features of such impact. Our real scenario …
What is the Natural Abstraction Level of an Algorithm?
2021
Abstract State Machines work with algorithms on the natural abstraction level. In this paper, we discuss the notion of the natural abstraction level of an algorithm and how ASM manage to capture this abstraction level. We will look into three areas of algorithms: the algorithm execution, the algorithm description, and the algorithm semantics. We conclude that ASM capture the natural abstraction level of the algorithm execution, but not necessarily of the algorithm description. ASM do also capture the natural abstraction level of execution semantics.