Priors Stabilizers and Basis Functions: From Regularization to Radial, Tensor and Additive Splines

We had previously shown that regularization principles lead to approximation schemes, as Radial Basis Functions, which are equivalent to networks with one layer of hidden units, called Regularization Networks. In this paper we show that regularization networks encompass a much broader range of approximation schemes, including many of the popular general additive models, Breiman's hinge functions and some forms of Projection Pursuit Regression. In the probabilistic interpretation of regularization, the different classes of basis functions correspond to different classes of prior probabilities on the approximating function spaces, and therefore to different types of smoothness assumptions. In the final part of the paper, we also show a relation between activation functions of the Gaussian and sigmoidal type.

A Nonparametric Approach to Pricing and Hedging Derivative Securities via Learning Networks

We propose a nonparametric method for estimating derivative financial asset pricing formulae using learning networks. To demonstrate feasibility, we first simulate Black-Scholes option prices and show that learning networks can recover the Black-Scholes formula from a two-year training set of daily options prices, and that the resulting network formula can be used successfully to both price and delta-hedge options out-of-sample. For comparison, we estimate models using four popular methods: ordinary least squares, radial basis functions, multilayer perceptrons, and projection pursuit. To illustrate practical relevance, we also apply our approach to S&P 500 futures options data from 1987 to 1991.

Support Vector Machines: Training and Applications

The Support Vector Machine (SVM) is a new and very promising classification technique developed by Vapnik and his group at AT&T Bell Labs. This new learning algorithm can be seen as an alternative training technique for Polynomial, Radial Basis Function and Multi-Layer Perceptron classifiers. An interesting property of this approach is that it is an approximate implementation of the Structural Risk Minimization (SRM) induction principle. The derivation of Support Vector Machines, its relationship with SRM, and its geometrical insight, are discussed in this paper. Training a SVM is equivalent to solve a quadratic programming problem with linear and box constraints in a number of variables equal to the number of data points. When the number of data points exceeds few thousands the problem is very challenging, because the quadratic form is completely dense, so the memory needed to store the problem grows with the square of the number of data points. Therefore, training problems arising in some real applications with large data sets are impossible to load into memory, and cannot be solved using standard non-linear constrained optimization algorithms. We present a decomposition algorithm that can be used to train SVM's over large data sets. The main idea behind the decomposition is the iterative solution of sub-problems and the evaluation of, and also establish the stopping criteria for the algorithm. We present previous approaches, as well as results and important details of our implementation of the algorithm using a second-order variant of the Reduced Gradient Method as the solver of the sub-problems. As an application of SVM's, we present preliminary results we obtained applying SVM to the problem of detecting frontal human faces in real images.

Capaware: plataforma de desarrollo de software libre para aplicacines geográficas 3D multicapa

En este trabajo se presenta Capaware, una plataforma de software libre para el desarrollo de aplicaciones geográficas 3D multicapa, que surge a partir de la iniciativa del Instituto Tecnológico de Canarias en colaboración con la Universidad de Las Palmas de Gran Canaria. Este entorno simplifica la creación de aplicaciones 3D sobre territorios geográficos extensos, disponiendo de una herramienta muy visual que aporta un nuevo punto de vista muy importante para una toma de decisiones eficaz. Capaware proporciona una interfaz fácil de usar y muy flexible que simplifica el desarrollo de nuevas aplicaciones, permitiéndonos crear rápidamente entornos virtuales con múltiples capas de información sobre el terreno. Con las capacidades clásicas de un Sistema de Información Geográfica (SIG), Capaware permite actualmente la carga de capas WMS sobre entornos 3D, añadir objetos 3D sobre el terreno, y visualizar elementos dinámicos, ofreciendo una nueva perspectiva de la información analizada. Así mismo, podemos administrar las capas de recursos y elementos que se pueden representar sobre la zona geográfica en cuestión. (...)

A behavior-based scheme using reinforcement learning for autonomous underwater vehicles

This paper presents a hybrid behavior-based scheme using reinforcement learning for high-level control of autonomous underwater vehicles (AUVs). Two main features of the presented approach are hybrid behavior coordination and semi on-line neural-Q_learning (SONQL). Hybrid behavior coordination takes advantages of robustness and modularity in the competitive approach as well as efficient trajectories in the cooperative approach. SONQL, a new continuous approach of the Q_learning algorithm with a multilayer neural network is used to learn behavior state/action mapping online. Experimental results show the feasibility of the presented approach for AUVs

G+: Enhanced Traffic Grooming in WDM Mesh Networks using Lighttours

In this article, a new technique for grooming low-speed traffic demands into high-speed optical routes is proposed. This enhancement allows a transparent wavelength-routing switch (WRS) to aggregate traffic en route over existing optical routes without incurring expensive optical-electrical-optical (OEO) conversions. This implies that: a) an optical route may be considered as having more than one ingress node (all inline) and, b) traffic demands can partially use optical routes to reach their destination. The proposed optical routes are named "lighttours" since the traffic originating from different sources can be forwarded together in a single optical route, i.e., as taking a "tour" over different sources towards the same destination. The possibility of creating lighttours is the consequence of a novel WRS architecture proposed in this article, named "enhanced grooming" (G+). The ability to groom more traffic in the middle of a lighttour is achieved with the support of a simple optical device named lambda-monitor (previously introduced in the RingO project). In this article, we present the new WRS architecture and its advantages. To compare the advantages of lighttours with respect to classical lightpaths, an integer linear programming (ILP) model is proposed for the well-known multilayer problem: traffic grooming, routing and wavelength assignment The ILP model may be used for several objectives. However, this article focuses on two objectives: maximizing the network throughput, and minimizing the number of optical-electro-optical conversions used. Experiments show that G+ can route all the traffic using only half of the total OEO conversions needed by classical grooming. An heuristic is also proposed, aiming at achieving near optimal results in polynomial time

Robustness against large-scale failures in communications networks

This thesis studies robustness against large-scale failures in communications networks. If failures are isolated, they usually go unnoticed by users thanks to recovery mechanisms. However, such mechanisms are not effective against large-scale multiple failures. Large-scale failures may cause huge economic loss. A key requirement towards devising mechanisms to lessen their impact is the ability to evaluate network robustness. This thesis focuses on multilayer networks featuring separated control and data planes. The majority of the existing measures of robustness are unable to capture the true service degradation in such a setting, because they rely on purely topological features. One of the major contributions of this thesis is a new measure of functional robustness. The failure dynamics is modeled from the perspective of epidemic spreading, for which a new epidemic model is proposed. Another contribution is a taxonomy of multiple, large-scale failures, adapted to the needs and usage of the field of networking.

Mid-infrared filters for astronomical and remote sensing instrumentation

As improvements to the optical design of spectrometer and radiometer instruments evolve with advances in detector sensitivity, use of focal plane detector arrays and innovations in adaptive optics for large high altitude telescopes, interest in mid-infrared astronomy and remote sensing applications have been areas of progressive research in recent years. This research has promoted a number of developments in infrared coating performance, particularly by placing increased demands on the spectral imaging requirements of filters to precisely isolate radiation between discrete wavebands and improve photometric accuracy. The spectral design and construction of multilayer filters to accommodate these developments has subsequently been an area of challenging thin-film research, to achieve high spectral positioning accuracy, environmental durability and aging stability at cryogenic temperatures, whilst maximizing the far-infrared performance. In this paper we examine the design and fabrication of interference filters in instruments that utilize the mid-infrared N-band (6-15 µm) and Q-band (16-28 µm) atmospheric windows, together with a rationale for the selection of materials, deposition process, spectral measurements and assessment of environmental durability performance.

The radiative effect of a fir canopy on a snowpack

Models of snow processes in areas of possible large-scale change need to be site independent and physically based. Here, the accumulation and ablation of the seasonal snow cover beneath a fir canopy has been simulated with a new physically based snow-soil vegetation-atmosphere transfer scheme (Snow-SVAT) called SNOWCAN. The model was formulated by coupling a canopy optical and thermal radiation model to a physically based multilayer snow model. Simple representations of other forest effects were included. These include the reduction of wind speed and hence turbulent transfer beneath the canopy, sublimation of intercepted snow, and deposition of debris on the surface. This paper tests this new modeling approach fully at a fir site within Reynolds Creek Experimental Watershed, Idaho. Model parameters were determined at an open site and subsequently applied to the fir site. SNOWCAN was evaluated using measurements of snow depth, subcanopy solar and thermal radiation, and snowpack profiles of temperature, density, and grain size. Simulations showed good agreement with observations (e.g., fir site snow depth was estimated over the season with r(2) = 0.96), generally to within measurement error. However, the simulated temperature profiles were less accurate after a melt-freeze event, when the temperature discrepancy resulted from underestimation of the rate of liquid water flow and/or the rate of refreeze. This indicates both that the general modeling approach is applicable and that a still more complete representation of liquid water in the snowpack will be important.

High performance blocking filters for the region 1µm to 20µm

A set of filters based on the sequence of semiconductor edges is described which offers continuity of short-wave infrared blocking. The rejection throughout the stop region is greater than 103 for each filter and the transmission better than 70% through one octave with a square cutoff. The cutoff points are located at intervals of about two-thirds of an octave. Filters at 2.6 ,µm, 5.5 µm, and 12 µm which use a low-passing multilayer in combination with a semiconductor absorption edge are described in detail. The design of multilayers for optimum performance is discussed by analogy with the synthesis of electric circuit filters.

Statistical downscaling of river flows

An extensive statistical ‘downscaling’ study is done to relate large-scale climate information from a general circulation model (GCM) to local-scale river flows in SW France for 51 gauging stations ranging from nival (snow-dominated) to pluvial (rainfall-dominated) river-systems. This study helps to select the appropriate statistical method at a given spatial and temporal scale to downscale hydrology for future climate change impact assessment of hydrological resources. The four proposed statistical downscaling models use large-scale predictors (derived from climate model outputs or reanalysis data) that characterize precipitation and evaporation processes in the hydrological cycle to estimate summary flow statistics. The four statistical models used are generalized linear (GLM) and additive (GAM) models, aggregated boosted trees (ABT) and multi-layer perceptron neural networks (ANN). These four models were each applied at two different spatial scales, namely at that of a single flow-gauging station (local downscaling) and that of a group of flow-gauging stations having the same hydrological behaviour (regional downscaling). For each statistical model and each spatial resolution, three temporal resolutions were considered, namely the daily mean flows, the summary statistics of fortnightly flows and a daily ‘integrated approach’. The results show that flow sensitivity to atmospheric factors is significantly different between nival and pluvial hydrological systems which are mainly influenced, respectively, by shortwave solar radiations and atmospheric temperature. The non-linear models (i.e. GAM, ABT and ANN) performed better than the linear GLM when simulating fortnightly flow percentiles. The aggregated boosted trees method showed higher and less variable R2 values to downscale the hydrological variability in both nival and pluvial regimes. Based on GCM cnrm-cm3 and scenarios A2 and A1B, future relative changes of fortnightly median flows were projected based on the regional downscaling approach. The results suggest a global decrease of flow in both pluvial and nival regimes, especially in spring, summer and autumn, whatever the considered scenario. The discussion considers the performance of each statistical method for downscaling flow at different spatial and temporal scales as well as the relationship between atmospheric processes and flow variability.

An electrochemical study of 4-aminothiophenol/pt nanoparticle multilayers on gold electrodes

Quartz crystal microbalance (QCM) measurements of the formation of a 4-aminothiophenol (4-ATP)self-assembled monolayer (SAM) at a gold electrode showed that a surface coverage of 118 ng cm(-2) was obtained after a 3 h exposure period, indicating that good surface coverage was achieved. Cyclic voltammetry of the ferricyanide redox couple across this SAM modified surface produced similar results to those of a bare electrode; however, the electroreduction of oxygen was found to be impaired. The 4-ATP SAM layer was not stable to repeated electrochemical oxidation and reduction; it is believed that the 4-ATP SAM layer was first converted to a 4'-mercapto-N-phenylquinone diimine (NPQD) layer followed by subsequent formation of a 4'-mercapto-N-phenylquinone monoimine (NPQM) layer. We also report a quartz crystal microbalance study of the attachment of platinum nanoparticles to such SAM modified electrodes. We show that five times the amount of platinum nanoparticles can be attached to a 4-ATP modified electrode surface (observed frequency change - 187 Hz) compared with an NPQD modified electrode surface (observed frequency change -35 Hz). The presence of the platinum particles was confirmed electrochemically by their surface electrochemical properties, which were different from those of the underlying gold electrode. It is believed that this is the first time that such direct evidence of electrochemical communication between platinum nanoparticles and a SAM modified electrode surface has been obtained. It was also shown to be possible to build up multilayer SAM/nanoparticle modified surfaces while maintaining efficient electrochemical communication. Up to three SAM/nanoparticle sandwich layers were constructed.

The local adsorption geometry and electronic structure of alanine on Cu{110}

The adsorption of alanine on Cu {110} was studied by a combination of near edge X-ray absorption fine structure (NEXAFS) spectroscopy, X-ray photoelectron spectroscopy (XPS) and density functional theory (DFT). Large chemical shifts in the C 1s, N 1s, and O 1s XP spectra were found between the alanine multilayer and the chemisorbed and pseudo-(3 x 2) alaninate layers. From C, N, and O K-shell NEXAFS spectra the tilt angles of the carboxylate group (approximate to 26 degrees in plane with respect to [1 (1) over bar0] and approximate to 45 degrees out of plane) and the C-N bond angle with respect to [1 (1) over bar0] could be determined for the pseudo-(3 x 2) overlayer. Using this information three adsorption geometries could be eliminated from five p(3 x 2) structures which lead to almost identical heats of adsorption in the DFT calculations between 1.40 and 1.47 eV/molecule. Due to the small energy difference between the remaining two structures it is not unlikely that these coexist on the surface at room temperature. (c) 2006 Elsevier B.V. All rights reserved.

Adsorption of frog foam nest proteins at the air-water interface

The surfactant properties of aqueous protein mixtures ( ranaspumins) from the foam nests of the tropical frog Physalaemus pustulosus have been investigated by surface tension, two-photon excitation. uorescence microscopy, specular neutron reflection, and related biophysical techniques. Ranaspumins lower the surface tension of water more rapidly and more effectively than standard globular proteins under similar conditions. Two- photon excitation. uorescence microscopy of nest foams treated with fluorescent marker ( anilinonaphthalene sulfonic acid) shows partitioning of hydrophobic proteins into the air-water interface and allows imaging of the foam structure. The surface excess of the adsorbed protein layers, determined from measurements of neutron reflection from the surface of water utilizing H2O/D2O mixtures, shows a persistent increase of surface excess and layer thickness with bulk concentration. At the highest concentration studied ( 0.5 mg ml(-1)), the adsorbed layer is characterized by three distinct regions: a protruding top layer of similar to20 Angstrom, a middle layer of similar to30 Angstrom, and a more diffuse submerged layer projecting some 25 Angstrom into bulk solution. This suggests a model involving self-assembly of protein aggregates at the air-water interface in which initial foam formation is facilitated by specific surfactant proteins in the mixture, further stabilized by subsequent aggregation and cross-linking into a multilayer surface complex.

Interference filters and coatings for mid-infrared astronomy (8-30µm)

The VISIR instrument for the European Southern Observatory (ESO) Very Large Telescope (VLT) is a thermal-infrared imager and spectrometer currently being developed by the French Service d'Astrophysique of CEA Saclay, and Dutch NFRA ASTRON Dwingeloo consortium. This cryogenic instrument will employ precision infrared bandpass filters in the N-( =7.5-14µm) and Q-( =16-28µm) band mid-IR atmospheric windows to study interstellar and circumstellar environments crucial for star and planetary formation theories. As the filters in these mid-IR wavelength ranges are of interest to many astronomical cryogenic instruments, a worldwide astronomical filter consortium was set up with participation from 12 differing institutes, each requiring instrument specific filter operating environments and optical metrology. This paper describes the design and fabrication methods used to manufacture these astronomical consortium filters, including the rationale for the selection of multilayer coating designs, temperature-dependant optical properties of the filter materials and FTIR spectral measurements showing the changes in passband and blocking performance on cooling to <50K. We also describe the development of a 7-14µm broadband antireflection coating deposited on Ge lenses and KRS-5 grisms for cryogenic operation at 40K