A study of a soft computing based method for 3D scenario reconstruction

Several recent works deal with 3D data in mobile robotic problems, e.g., mapping. Data comes from any kind of sensor (time of flight, Kinect or 3D lasers) that provide a huge amount of unorganized 3D data. In this paper we detail an efficient approach to build complete 3D models using a soft computing method, the Growing Neural Gas (GNG). As neural models deal easily with noise, imprecision, uncertainty or partial data, GNG provides better results than other approaches. The GNG obtained is then applied to a sequence. We present a comprehensive study on GNG parameters to ensure the best result at the lowest time cost. From this GNG structure, we propose to calculate planar patches and thus obtaining a fast method to compute the movement performed by a mobile robot by means of a 3D models registration algorithm. Final results of 3D mapping are also shown.

A new approach for semi-automatic rock mass joints recognition from 3D point clouds

Rock mass characterization requires a deep geometric understanding of the discontinuity sets affecting rock exposures. Recent advances in Light Detection and Ranging (LiDAR) instrumentation currently allow quick and accurate 3D data acquisition, yielding on the development of new methodologies for the automatic characterization of rock mass discontinuities. This paper presents a methodology for the identification and analysis of flat surfaces outcropping in a rocky slope using the 3D data obtained with LiDAR. This method identifies and defines the algebraic equations of the different planes of the rock slope surface by applying an analysis based on a neighbouring points coplanarity test, finding principal orientations by Kernel Density Estimation and identifying clusters by the Density-Based Scan Algorithm with Noise. Different sources of information —synthetic and 3D scanned data— were employed, performing a complete sensitivity analysis of the parameters in order to identify the optimal value of the variables of the proposed method. In addition, raw source files and obtained results are freely provided in order to allow to a more straightforward method comparison aiming to a more reproducible research.

Astrophysical parameters of the peculiar X-ray transient IGR J11215−5952

Context. The current generation of X-ray satellites has discovered many new X-ray sources that are difficult to classify within the well-described subclasses. The hard X-ray source IGR J11215−5952 is a peculiar transient, displaying very short X-ray outbursts every 165 days. Aims. To characterise the source, we obtained high-resolution spectra of the optical counterpart, HD 306414, at different epochs, spanning a total of three months, before and around the 2007 February outburst with the combined aims of deriving its astrophysical parameters and searching for orbital modulation. Methods. We fit model atmospheres generated with the fastwind code to the spectrum, and used the interstellar lines in the spectrum to estimate its distance. We also cross-correlated each individual spectrum to the best-fit model to derive radial velocities. Results. From its spectral features, we classify HD 306414 as B0.5 Ia. From the model fit, we find Teff ≈ 24 700 K and log g ≈ 2.7, in good agreement with the morphological classification. Using the interstellar lines in its spectrum, we estimate a distance to HD 306414 d ≳ 7 kpc. Assuming this distance, we derive R∗ ≈ 40 R⊙ and Mspect ≈ 30 M⊙ (consistent, within errors, with Mevol ≈ 38 M⊙, and in good agreement with calibrations for the spectral type). Analysis of the radial velocity curve reveals that radial velocity changes are not dominated by the orbital motion, and provide an upper limit on the semi-amplitude for the optical component Kopt ≲ 11 ± 6 km   s-1. Large variations in the depth and shape of photospheric lines suggest the presence of strong pulsations, which may be the main cause of the radial velocity changes. Very significant variations, uncorrelated with those of the photospheric lines are seen in the shape and position of the Hα emission feature around the time of the X-ray outburst, but large excursions are also observed at other times. Conclusions. HD 306414 is a normal B0.5 Ia supergiant. Its radial velocity curve is dominated by an effect that is different from binary motion, and is most likely stellar pulsations. The data available suggest that the X-ray outbursts are caused by the close passage of the neutron star in a very eccentric orbit, perhaps leading to localised mass outflow.

Propagation of Dyakonon Wave-Packets at the Boundary of Metallodielectric Lattices

We rigorously analyze the propagation of localized surface waves that takes place at the boundary between a semi-infinite layered metal-dielectric (MD) nanostructure cut normally to the layers and a isotropic medium. It is demonstrated that Dyakonov-like surface waves (also coined dyakonons) with hybrid polarization may propagate in a wide angular range. As a consequence, dyakonon-based wave-packets (DWPs) may feature sub-wavelength beamwidths. Due to the hyperbolic-dispersion regime in plasmonic crystals, supported DWPs are still in the canalization regime. The apparent quadratic beam spreading, however, is driven by dissipation effects in metal.

Improving classification using a Confidence Matrix based on weak classifiers applied to OCR

This paper proposes a new feature representation method based on the construction of a Confidence Matrix (CM). This representation consists of posterior probability values provided by several weak classifiers, each one trained and used in different sets of features from the original sample. The CM allows the final classifier to abstract itself from discovering underlying groups of features. In this work the CM is applied to isolated character image recognition, for which several set of features can be extracted from each sample. Experimentation has shown that the use of CM permits a significant improvement in accuracy in most cases, while the others remain the same. The results were obtained after experimenting with four well-known corpora, using evolved meta-classifiers with the k-Nearest Neighbor rule as a weak classifier and by applying statistical significance tests.

Feature selection by multi-objective optimisation: Application to network anomaly detection by hierarchical self-organising maps

Feature selection is an important and active issue in clustering and classification problems. By choosing an adequate feature subset, a dataset dimensionality reduction is allowed, thus contributing to decreasing the classification computational complexity, and to improving the classifier performance by avoiding redundant or irrelevant features. Although feature selection can be formally defined as an optimisation problem with only one objective, that is, the classification accuracy obtained by using the selected feature subset, in recent years, some multi-objective approaches to this problem have been proposed. These either select features that not only improve the classification accuracy, but also the generalisation capability in case of supervised classifiers, or counterbalance the bias toward lower or higher numbers of features that present some methods used to validate the clustering/classification in case of unsupervised classifiers. The main contribution of this paper is a multi-objective approach for feature selection and its application to an unsupervised clustering procedure based on Growing Hierarchical Self-Organising Maps (GHSOMs) that includes a new method for unit labelling and efficient determination of the winning unit. In the network anomaly detection problem here considered, this multi-objective approach makes it possible not only to differentiate between normal and anomalous traffic but also among different anomalies. The efficiency of our proposals has been evaluated by using the well-known DARPA/NSL-KDD datasets that contain extracted features and labelled attacks from around 2 million connections. The selected feature sets computed in our experiments provide detection rates up to 99.8% with normal traffic and up to 99.6% with anomalous traffic, as well as accuracy values up to 99.12%.

Comparison of Lattice-Fluid Binary Parameters For Mixtures and Block Copolymers

The aim of this report is to discuss the method of determination of lattice-fluid binary interaction parameters by comparing well characterized immiscible blends and block copolymers of poly(methyl methacrylate) (PMMA) and poly(ϵ−caprolactone) (PCL). Experimental pressure-volume-temperature (PVT) data in the liquid state were correlated with the Sanchez—Lacombe (SL) equation of state with the scaling parameters for mixtures and copolymers obtained through combination rules of the characteristic parameters for the pure homopolymers. The lattice-fluid binary parameters for energy and volume were higher than those of block copolymers implying that the copolymers were more compatible due to the chemical links between the blocks. Therefore, a common parameter cannot account for both homopolymer blend and block copolymer phase behaviors based on current theory. As we were able to adjust all data of the mixtures with a single set of lattice-binary parameters and all data of the block copolymers with another single set we can conclude that both parameters did not depend on the composition for this system. This characteristic, plus the fact that the additivity law of specific volumes can be suitably applied for this system, allowed us to model the behavior of the immiscible blend with the SL equation of state. In addition, a discussion on the relationship between lattice-fluid binary parameters and the Flory–Huggins interaction parameter obtained from Leibler's theory is presented.

A Belief System's Organization Based on a Computational Model of the Dynamic Context: First Approximation

In this article we present a model of organization of a belief system based on a set of binary recursive functions that characterize the dynamic context that modifies the beliefs. The initial beliefs are modeled by a set of two-bit words that grow, update, and generate other beliefs as the different experiences of the dynamic context appear. Reason is presented as an emergent effect of the experience on the beliefs. The system presents a layered structure that allows a functional organization of the belief system. Our approach seems suitable to model different ways of thinking and to apply to different realistic scenarios such as ideologies.

Multiwavelength study of the fast rotating supergiant high-mass X-ray binary IGR J16465−4507

Context. Since its launch, the X-ray and γ-ray observatory INTEGRAL satellite has revealed a new class of high-mass X-ray binaries (HMXB) displaying fast flares and hosting supergiant companion stars. Optical and infrared (OIR) observations in a multi-wavelength context are essential to understand the nature and evolution of these newly discovered celestial objects. Aims. The goal of this multiwavelength study (from ultraviolet to infrared) is to characterise the properties of IGR J16465−4507, to confirm its HMXB nature and that it hosts a supergiant star. Methods. We analysed all OIR, photometric and spectroscopic observations taken on this source, carried out at ESO facilities. Results. Using spectroscopic data, we constrained the spectral type of the companion star between B0.5 and B1 Ib, settling the debate on the true nature of this source. We measured a high rotation velocity of v = 320 ± 8km s-1 from fitting absorption and emission lines in a stellar spectral model. We then built a spectral energy distribution from photometric observations to evaluate the origin of the different components radiating at each energy range. Conclusions. We finally show that, having accurately determined the spectral type of the early-B supergiant in IGR J16465−4507, we firmly support its classification as an intermediate supergiant fast X-ray transient (SFXT).

Perceção dos educadores sobre as potencialidades do livro de literatura para a infância

Tese de doutoramento, Educação (Psicologia da Educação), Universidade de Lisboa, Instituto de Educação, 2016

Controlo fuzzy semi-activo para aparelhos de amortecimento variável na protecção sísmica

Trabalho apresentado no 10º Congresso Nacional de Sismologia e Engenharia Sísmica, 20-22 abril de 2016, Ponta Delgada, Açores, Portugal

Agricultural research program : semi-annual progress report for...

"Contract No. AT-40-1-GEN-242."

... Semi-annual conference of the Church of Jesus Christ of Latter-day Saints.

Volume for the 68th- also contains an account of the General Conference of the Deseret Sunday School Union.

Proceedings of the semi-annual and annual encampments of the Department of New York, Grand Army of the Republic.

Description based on: June 28-29, 1882 and Jan. 24-25, 1883.

Semi-annual report of the Division of Reference and Research.

Submitted by the Director of Reference and Research to the President of the Board of Education.