Search results for "Dependence"
showing 10 items of 2462 documents
Impact of contact resistance on the electrical properties of MoS2 transistors at practical operating temperatures
2017
Molybdenum disulphide (MoS2) is currently regarded as a promising material for the next generation of electronic and optoelectronic devices. However, several issues need to be addressed to fully exploit its potential for field effect transistor (FET) applications. In this context, the contact resistance, RC, associated with the Schottky barrier between source/drain metals and MoS2 currently represents one of the main limiting factors for suitable device performance. Furthermore, to gain a deeper understanding of MoS2 FETs under practical operating conditions, it is necessary to investigate the temperature dependence of the main electrical parameters, such as the field effect mobility (μ) an…
Sensitivity Maps of the Hilbert-Schmidt Independence Criterion
2018
Abstract Kernel dependence measures yield accurate estimates of nonlinear relations between random variables, and they are also endorsed with solid theoretical properties and convergence rates. Besides, the empirical estimates are easy to compute in closed form just involving linear algebra operations. However, they are hampered by two important problems: the high computational cost involved, as two kernel matrices of the sample size have to be computed and stored, and the interpretability of the measure, which remains hidden behind the implicit feature map. We here address these two issues. We introduce the sensitivity maps (SMs) for the Hilbert–Schmidt independence criterion (HSIC). Sensi…
Quasi-nash equilibria for non-convex distributed power allocation games in cognitive radios
2013
In this paper, we consider a sensing-based spectrum sharing scenario in cognitive radio networks where the overall objective is to maximize the sum-rate of each cognitive radio user by optimizing jointly both the detection operation based on sensing and the power allocation, taking into account the influence of the sensing accuracy and the interference limitation to the primary users. The resulting optimization problem for each cognitive user is non-convex, thus leading to a non-convex game, which presents a new challenge when analyzing the equilibria of this game where each cognitive user represents a player. In order to deal with the non-convexity of the game, we use a new relaxed equilib…
Field estimation in wireless sensor networks using distributed kriging
2012
In this paper, we tackle the problem of spatial interpolation for distributed estimation in Wireless Sensor Networks by using a geostatistical technique called kriging. We present a novel Distributed Iterative Kriging Algorithm (DIKA) which is composed of two main phases. First, the spatial dependence of the field is exploited by calculating semivariograms in an iterative way. Second, the kriging system of equations is solved by an initial set of nodes in a distributed manner, providing some initial interpolation weights to each node. In our algorithm, the estimation accuracy can be improved by iteratively adding new nodes and updating appropriately the weights, which leads to a reduction i…
Estimating biophysical variable dependences with kernels
2010
This paper introduces a nonlinear measure of dependence between random variables in the context of remote sensing data analysis. The Hilbert-Schmidt Independence Criterion (HSIC) is a kernel method for evaluating statistical dependence. HSIC is based on computing the Hilbert-Schmidt norm of the cross-covariance operator of mapped samples in the corresponding Hilbert spaces. The HSIC empirical estimator is very easy to compute and has good theoretical and practical properties. We exploit the capabilities of HSIC to explain nonlinear dependences in two remote sensing problems: temperature estimation and chlorophyll concentration prediction from spectra. Results show that, when the relationshi…
Optimum plastic design for multiple sets of loads
1974
We study optimum plastic design of structures made up, or conceived as assemblies of finite elements, each having an elemental piece-wise linear rigid-plastic behaviour. Since cost function linearly dependent on design variables are considered, optimization problems in linear programming are encountered. Allowance is made for design dependent mass forces, and for some technological constraints. The design growing process is studied in the case of various sets of alternative applied loads, and the optimality conditions are written in a proper geometrical form which leads to a generalization of the concept of Foulkes mechanism.
Hedging of Spatial Temperature Risk with Market-Traded Futures
2011
The main objective of this work is to construct optimal temperature futures from available market-traded contracts to hedge spatial risk. Temperature dynamics are modelled by a stochastic differential equation with spatial dependence. Optimal positions in market-traded futures minimizing the variance are calculated. Examples with numerical simulations based on a fast algorithm for the generation of random fields are presented.
Detecting All Dependences in Systems of Geometric Constraints Using the Witness Method
2007
In geometric constraints solving, the detection of dependences and the decomposition of the system into smaller subsystems are two important steps that characterize any solving process, but nowadays solvers, which are graph-based in most of the cases, fail to detect dependences due to geometric theorems and to decompose such systems. In this paper, we discuss why detecting all dependences between constraints is a hard problem and propose to use the witness method published recently to detect both structural and non structural dependences.We study various examples of constraints systems and show the promising results of the witness method in subtle dependences detection and systems decomposi…
Causes and underlying processes of measurement variability in field erosion plots in Mediterranean conditions
2007
Published online 25 May 2006
THE ROLE OF SUNK COSTS IN THE DECISION TO INVEST IN R&D
2009
We present a dynamic empirical model of a firm's R&D decisions that is consistent with the existence of sunk R&D costs, taking into account that these costs may differ between small and large firms, and among different technological regimes. We estimate a multivariate dynamic discrete choice model using firm-level data of Spanish manufacturing for 1990–2000. Conditional on firm heterogeneity and serially correlated unobservable factors, we find that R&D history matters. This true state dependence allows inferring the existence of sunk R&D costs associated with performing R&D. Sunk R&D costs are found to be higher for large, high-tech firms.