The Overlooked Potential of Generalized Linear Models in Astronomy - I: Binomial Regression

Revealing hidden patterns in astronomical data is often the path to fundamental scientific breakthroughs; meanwhile the complexity of scientific inquiry increases as more subtle relationships are sought. Contemporary data analysis problems often elude the capabilities of classical statistical techniques, suggesting the use of cutting edge statistical methods. In this light, astronomers have overlooked a whole family of statistical techniques for exploratory data analysis and robust regression, the so-called Generalized Linear Models (GLMs). In this paper -- the first in a series aimed at illustrating the power of these methods in astronomical applications -- we elucidate the potential of a particular class of GLMs for handling binary/binomial data, the so-called logit and probit regression techniques, from both a maximum likelihood and a Bayesian perspective. As a case in point, we present the use of these GLMs to explore the conditions of star formation activity and metal enrichment in primordial minihaloes from cosmological hydro-simulations including detailed chemistry, gas physics, and stellar feedback. We predict that for a dark mini-halo with metallicity $\approx 1.3 \times 10^{-4} Z_{\bigodot}$, an increase of $1.2 \times 10^{-2}$ in the gas molecular fraction, increases the probability of star formation occurrence by a factor of 75%. Finally, we highlight the use of receiver operating characteristic curves as a diagnostic for binary classifiers, and ultimately we use these to demonstrate the competitive predictive performance of GLMs against the popular technique of artificial neural networks.Comment: 20 pages, 10 figures, 3 tables, accepted for publication in Astronomy and Computin

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Detecting covariance symmetries for classification of polarimetric SAR images

The availability of multiple images of the same scene acquired with the same radar but with different polarizations, both in transmission and reception, has the potential to enhance the classification, detection and/or recognition capabilities of a remote sensing system. A way to take advantage of the full-polarimetric data is to extract, for each pixel of the considered scene, the polarimetric covariance matrix, coherence matrix, Muller matrix, and to exploit them in order to achieve a specific objective. A framework for detecting covariance symmetries within polarimetric SAR images is here proposed. The considered algorithm is based on the exploitation of special structures assumed by the polarimetric coherence matrix under symmetrical properties of the returns associated with the pixels under test. The performance analysis of the technique is evaluated on both simulated and real L-band SAR data, showing a good classification level of the different areas within the image

Some new insights in swelling and swelling pressure of low active clay

This paper presents a multidimensional chemo-mechanical model for saturated clay treated as a two-phase deformable and chemically reactive porous medium. The constitutive relation is an extension of the original chemo-mechanical model proposed by Gajo et al. (2002) and Loret et al. (2002), in which a q-p formulation was proposed with a Cam-Clay-like elastic response. A novel hyper-elastic law is proposed in which shear stiffness and bulk stiffness change with stress state and ion concentration in pore solution. The proposed constitutive model and the associated coupled finite element formulation are implemented in a 2D, commercial, finite element code (ABAQUS) in the form of user-defined external subroutines. The proposed framework is used to simulate the oedometer tests performed on a low activity clay extracted from Costa della Gaveta slope. The computed chemo mechanical behaviour of the material prepared with distilled water is compared with the experimental results obtained from reconstituted specimens. Moreover, swelling and swelling pressure are computed for the overconsolidated material reconstituted with 1 M NaCl solution and then exposed to distilled water. The comparison of simulations and experiments shows a good agreement

Automatic recognition of military vehicles with Krawtchouk moments

The challenge of Automatic Target Recognition (ATR) of military targets within a Synthetic Aperture Radar (SAR) scene is addressed in this paper. The proposed approach exploits the discrete defined Krawtchouk moments, that are able to represent a detected extended target with few features, allowing its characterization. The proposed algorithm provides robust performance for target recognition, identification and characterization, with high reliability in presence of noise and reduced sensitivity to discretization errors. The effectiveness of the proposed approach is demonstrated using the MSTAR dataset

Forcing scale invariance in multipolarization SAR change detection

This paper considers the problem of coherent (in the sense that both amplitudes and relative phases of the polarimetric returns are used to construct the decision statistic) multi-polarization SAR change detec- tion starting from the availability of image pairs exhibiting possible power mismatches/miscalibrations. The principle of invariance is used to characterize the class of scale-invariant decision rules which are insensitive to power mismatches and ensure the Constant False Alarm Rate (CFAR) property. A maximal invariant statistic is derived together with the induced maximal invariant in the parameter space which significantly compress the data/parameters domain. A Generalized Likelihood Ratio Test (GLRT) is synthesized both for the cases of two- and three-polarimetric channels. Interestingly, for the two-channel case, it is based on the comparison of the condition number of a data-dependent matrix with a suitable threshold. Some additional invariant decision rules are also proposed. The performance of the considered scale-invariant structures is compared to those from two non- invariant counterparts using both simulated and real radar data. The results highlight the robustness of the proposed method and the performance tradeoff involve

Recurrent Nevus. A 5-Year Review

A persistência de uma lesão melanocítica, em local onde tenha sido previamente excisado um nevo melanocítico pode colocar, clínica e histologicamente, problemas no diagnóstico diferencial com melanoma, designado por alguns autores como ‘pseudomelanoma’. Neste estudo, os autores pretendem realizar uma análise comparativa entre os achados clínicos e histopatológicos das lesões melanocíticas primárias e dos nevos recorrentes. Procura-se também avaliar eventuais factores predisponentes para este fenómeno

A functional-cognitive framework for attitude research

In attitude research, behaviours are often used as proxies for attitudes and attitudinal processes. This practice is problematic because it conflates the behaviours that need to be explained (explanandum) with the mental constructs that are used to explain these behaviours (explanans). In the current chapter we propose a meta-theoretical framework that resolves this problem by distinguishing between two levels of analysis. According to the proposed framework, attitude research can be conceptualised as the scientific study of evaluation. Evaluation is defined not in terms of mental constructs but in terms of elements in the environment, more specifically, as the effect of stimuli on evaluative responses. From this perspective, attitude research provides answers to two questions: (1) Which elements in the environment moderate evaluation? (2) What mental processes and representations mediate evaluation? Research on the first question provides explanations of evaluative responses in terms of elements in the environment (functional level of analysis); research on the second question offers explanations of evaluation in terms of mental processes and representations (cognitive level of analysis). These two levels of analysis are mutually supportive, in that better explanations at one level lead to better explanations at the other level. However, their mutually supportive relation requires a clear distinction between the concepts of their explanans and explanandum, which are conflated if behaviours are treated as proxies for mental constructs. The value of this functional-cognitive framework is illustrated by applying it to four central questions of attitude research

The degeneracy between star-formation parameters in dwarf galaxy simulations and the Mstar-Mhalo relation

We present results based on a set of N-Body/SPH simulations of isolated dwarf galaxies. The simulations take into account star formation, stellar feedback, radiative cooling and metal enrichment. The dark matter halo initially has a cusped profile, but, at least in these simulations, starting from idealised, spherically symmetric initial conditions, a natural conversion to a core is observed due to gas dynamics and stellar feedback. A degeneracy between the efficiency with which the interstellar medium absorbs energy feedback from supernovae and stellar winds on the one hand, and the density threshold for star formation on the other, is found. We performed a parameter survey to determine, with the aid of the observed kinematic and photometric scaling relations, which combinations of these two parameters produce simulated galaxies that are in agreement with the observations. With the implemented physics we are unable to reproduce the relation between the stellar mass and the halo mass as determined by Guo et al. (2010), however we do reproduce the slope of this relation.Comment: Accepted for publication in MNRAS | 12 pages, 8 figure