Multilayer perceptron with local constraint as an emerging method in spatial data analysis

The use of Geographic Information Systems has revolutionalized the handling and the visualization of geo-referenced data and has underlined the critic role of spatial analysis. The usual tools for such a purpose are geostatistics which are widely used in Earth science. Geostatistics are based upon several hypothesis which are not always verified in practice. On the other hand, Artificial Neural Network (ANN) a priori can be used without special assumptions and are known to be flexible. This paper proposes to discuss the application of ANN in the case of the interpolation of a geo-referenced variable.

Qualitat de vida i centres d'educació especial: una aproximació a la seva conceptualització i avaluació

La qualitat de vida s’està convertint en un concepte clau i unificador en l’atenció i educació de les persones amb discapacitat intel•lectual. Així mateix, la percepció actual sobre les persones amb discapacitat ha canviat substancialment. En el moment actual, cal plantejar-se quines són les aplicacions i les implicacions que tenen per l’atenció i educació de les persones amb discapacitat intel•lectual els principis derivats del nou concepte de discapacitat i de la qualitat de vida. Aquesta investigació pretén essencialment elaborar un conjunt d’instruments que permetin avaluar la qualitat de les pràctiques educatives dels centres d’educació especial. Amb aquest objectiu s’ha seguit un procediment estructurat i ordenat en l’elaboració dels instruments com en la seva valoració inicial. Per avaluar la qualitat dels centres d’educació especial es proposen una sèrie qüestionaris tant pels professionals, les famílies i els alumnes. Els resultats indiquen que el conjunt d’instruments d’avaluació permeten recollir informació àmplia i variada de les pràctiques d’un centre d’educació especial, determinar les seves fortaleses i debilitats i servir de base per establir plans de millora estretament relacionats amb el context particular del centre i amb el que es considera una bona pràctica educativa.

Active Learning of Very-High Resolution Optical Imagery with SVM: Entropy vs Margin Sampling

An active learning method is proposed for the semi-automatic selection of training sets in remote sensing image classification. The method adds iteratively to the current training set the unlabeled pixels for which the prediction of an ensemble of classifiers based on bagged training sets show maximum entropy. This way, the algorithm selects the pixels that are the most uncertain and that will improve the model if added in the training set. The user is asked to label such pixels at each iteration. Experiments using support vector machines (SVM) on an 8 classes QuickBird image show the excellent performances of the methods, that equals accuracies of both a model trained with ten times more pixels and a model whose training set has been built using a state-of-the-art SVM specific active learning method

EU “actorness” in International Relations: The Non-Proliferation Policy of the EU in the Southern Mediterranean

El punt de partida d'aquesta investigació és una retòrica molt utilitzada que la UE és un actor global. En vista d'això, la no proliferació de la política comunitària al sud de la Mediterrània s'examina. L'estudi es realitza sobre la base de la conceptualització de la UE "actorness" ia través d'alguns criteris (context extern, l'evolució de l'aparell de política exterior de la UE, la Unió Europea l'auto-presentació i la percepció de tercers, la consistència i la disponibilitat d'instruments de política i accions concretes) que involucren tant factors ideacionals i materials, d'acord amb el "pluralisme metodològic". Aquest marc conceptual va ajudar a avaluar la no proliferació de la política comunitària en aquesta regió en particular on la UE té interessos i bones raons per actuar. Cada un dels criteris de manifest els avantatges i desavantatges de la UE "actorness" en aquest camp seleccionat i la caixa. Aquest document sosté que la no proliferació "actorness" de la UE a la regió del sud de la Mediterrània ha estat limitat a causa d'una varietat de raons.

An Instrumental analysis of the European Union´s capability to act in conflict response

Since its origins, the European Union has striven to be an actor on the International scene and a place in conflict Management. Yet the EU’s lack of activity cannot be justified by a mere lack of capacities. The EU counts with numerous political, economic, and, since 2003, civil and military instruments that should allow it to precede a comprehensive conflict response. This publication consists of a description of these instruments and an analysis of the final use that the Union makes of them in the different stages of a conflict. Examples will show us the EU’s main weakness in providing a comprehensive and timely response when a conflict breaks out.

Kernel-based methods for change detection in remote sensing images

Nowadays, the joint exploitation of images acquired daily by remote sensing instruments and of images available from archives allows a detailed monitoring of the transitions occurring at the surface of the Earth. These modifications of the land cover generate spectral discrepancies that can be detected via the analysis of remote sensing images. Independently from the origin of the images and of type of surface change, a correct processing of such data implies the adoption of flexible, robust and possibly nonlinear method, to correctly account for the complex statistical relationships characterizing the pixels of the images. This Thesis deals with the development and the application of advanced statistical methods for multi-temporal optical remote sensing image processing tasks. Three different families of machine learning models have been explored and fundamental solutions for change detection problems are provided. In the first part, change detection with user supervision has been considered. In a first application, a nonlinear classifier has been applied with the intent of precisely delineating flooded regions from a pair of images. In a second case study, the spatial context of each pixel has been injected into another nonlinear classifier to obtain a precise mapping of new urban structures. In both cases, the user provides the classifier with examples of what he believes has changed or not. In the second part, a completely automatic and unsupervised method for precise binary detection of changes has been proposed. The technique allows a very accurate mapping without any user intervention, resulting particularly useful when readiness and reaction times of the system are a crucial constraint. In the third, the problem of statistical distributions shifting between acquisitions is studied. Two approaches to transform the couple of bi-temporal images and reduce their differences unrelated to changes in land cover are studied. The methods align the distributions of the images, so that the pixel-wise comparison could be carried out with higher accuracy. Furthermore, the second method can deal with images from different sensors, no matter the dimensionality of the data nor the spectral information content. This opens the doors to possible solutions for a crucial problem in the field: detecting changes when the images have been acquired by two different sensors.

Is the PHY layer dead?

This article originates from a panel with the above title, held at IEEE VTC Spring 2009, in which the authors took part. The enthusiastic response it received prompted us to discuss for a wider audience whether research at the physical layer (PHY) is still relevant to the field of wireless communications. Using cellular systems as the axis of our exposition, we exemplify areas where PHY research has indeed hit a performance wall and where any improvements are expected to be marginal. We then discuss whether the research directions taken in the past have always been the right choice and how lessons learned could influence future policy decisions. Several of the raised issues are subsequently discussed in greater details, e.g., the growing divergence between academia and industry. With this argumentation at hand, we identify areas that are either under-developed or likely to be of impact in coming years - hence corroborating the relevance and importance of PHY research.

A unified treatment of optimum pilot overhead in multipath fading channels

The optimization of the pilot overhead in single-user wireless fading channels is investigated, and the dependence of this overhead on various system parameters of interest (e.g., fading rate, signal-to-noise ratio) is quantified. The achievable pilot-based spectral efficiency is expanded with respect to the fading rate about the no-fading point, which leads to an accurate order expansion for the pilot overhead. This expansion identifies that the pilot overhead, as well as the spectral efficiency penalty with respect to a reference system with genie-aided CSI (channel state information) at the receiver, depend on the square root of the normalized Doppler frequency. It is also shown that the widely-used block fading model is a special case of more accurate continuous fading models in terms of the achievable pilot-based spectral efficiency. Furthermore, it is established that the overhead optimization for multiantenna systems is effectively the same as for single-antenna systems with the normalized Doppler frequency multiplied by the number of transmit antennas.

Geometry-based demosaicking

Demosaicking is a particular case of interpolation problems where, from a scalar image in which each pixel has either the red, the green or the blue component, we want to interpolate the full-color image. State-of-the-art demosaicking algorithms perform interpolation along edges, but these edges are estimated locally. We propose a level-set-based geometric method to estimate image edges, inspired by the image in-painting literature. This method has a time complexity of O(S) , where S is the number of pixels in the image, and compares favorably with the state-of-the-art algorithms both visually and in most relevant image quality measures.

Transmit diversity vs. spatial multiplexing in modern MIMO systems

A contemporary perspective on the tradeoff between transmit antenna diversity andspatial multiplexing is provided. It is argued that, in the context of most modern wirelesssystems and for the operating points of interest, transmission techniques that utilizeall available spatial degrees of freedom for multiplexing outperform techniques that explicitlysacrifice spatial multiplexing for diversity. In the context of such systems, therefore,there essentially is no decision to be made between transmit antenna diversity and spatialmultiplexing in MIMO communication. Reaching this conclusion, however, requires thatthe channel and some key system features be adequately modeled and that suitable performancemetrics be adopted; failure to do so may bring about starkly different conclusions. Asa specific example, this contrast is illustrated using the 3GPP Long-Term Evolution systemdesign.

Impact of antenna correlation on the capacity of multiantenna channels

This paper applies random matrix theory to obtain analytical characterizations of the capacity of correlated multiantenna channels. The analysis is not restricted to the popular separable correlation model, but rather it embraces a more general representation that subsumesmost of the channel models that have been treated in the literature. For arbitrary signal-to-noise ratios (SNR), the characterization is conducted in the regime of large numbers of antennas. For the low- and high-SNR regions, in turn, we uncover compact capacity expansions that are valid for arbitrary numbers of antennas and that shed insight on how antenna correlation impacts the tradeoffs between power, bandwidth and rate.

Optimum power allocation for parallel Gaussian channels with arbitrary input distributions

The mutual information of independent parallel Gaussian-noise channels is maximized, under an average power constraint, by independent Gaussian inputs whose power is allocated according to the waterfilling policy. In practice, discrete signalling constellations with limited peak-to-average ratios (m-PSK, m-QAM, etc) are used in lieu of the ideal Gaussian signals. This paper gives the power allocation policy that maximizes the mutual information over parallel channels with arbitrary input distributions. Such policy admits a graphical interpretation, referred to as mercury/waterfilling, which generalizes the waterfilling solution and allows retaining some of its intuition. The relationship between mutual information of Gaussian channels and nonlinear minimum mean-square error proves key to solving the power allocation problem.

High-SNR power offset in multiantenna communication

The analysis of the multiantenna capacity in the high-SNR regime has hitherto focused on the high-SNR slope (or maximum multiplexing gain), which quantifies the multiplicative increase as function of the number of antennas. This traditional characterization is unable to assess the impact of prominent channel features since, for a majority of channels, the slope equals the minimum of the number of transmit and receive antennas. Furthermore, a characterization based solely on the slope captures only the scaling but it has no notion of the power required for a certain capacity. This paper advocates a more refined characterization whereby, as function of SNRjdB, the high-SNR capacity is expanded as an affine function where the impact of channel features such as antenna correlation, unfaded components, etc, resides in the zero-order term or power offset. The power offset, for which we find insightful closed-form expressions, is shown to play a chief role for SNR levels of practical interest.

Capacity-achieving input covariance for single-user multi-antenna channels

We characterize the capacity-achieving input covariance for multi-antenna channels known instantaneously at the receiver and in distribution at the transmitter. Our characterization, valid for arbitrary numbers of antennas, encompasses both the eigenvectors and the eigenvalues. The eigenvectors are found for zero-mean channels with arbitrary fading profiles and a wide range of correlation and keyhole structures. For the eigenvalues, in turn, we present necessary and sufficient conditions as well as an iterative algorithm that exhibits remarkable properties: universal applicability, robustness and rapid convergence. In addition, we identify channel structures for which an isotropic input achieves capacity.

Comprehensive evaluation of the IEEE 802.15.4 MAC layer performance with retransmissions

Supported by IEEE 802.15.4 standardization activities, embedded networks have been gaining popularity in recent years. The focus of this paper is to quantify the behavior of key networking metrics of IEEE 802.15.4 beacon-enabled nodes under typical operating conditions, with the inclusion of packet retransmissions. We corrected and extended previous analyses by scrutinizing the assumptions on which the prevalent Markovian modeling is generally based. By means of a comparative study, we singled out which of the assumptions impact each of the performance metrics (throughput, delay, power consumption, collision probability, and packet-discard probability). In particular, we showed that - unlike what is usually assumed - the probability that a node senses the channel busy is not constant for all the stages of the backoff procedure and that these differences have a noticeable impact on backoff delay, packet-discard probability, and power consumption. Similarly, we showed that - again contrary to common assumption - the probability of obtaining transmission access to the channel depends on the number of nodes that is simultaneously sensing it. We evidenced that ignoring this dependence has a significant impact on the calculated values of throughput and collision probability. Circumventing these and other assumptions, we rigorously characterize, through a semianalytical approach, the key metrics in a beacon-enabled IEEE 802.15.4 system with retransmissions.