An R Package for a General Class of Inverse Gaussian Distributions

The inverse Gaussian distribution is a positively skewed probability model that has received great attention in the last 20 years. Recently, a family that generalizes this model called inverse Gaussian type distributions has been developed. The new R package named ig has been designed to analyze data from inverse Gaussian type distributions. This package contains basic probabilistic functions, lifetime indicators and a random number generator from this model. Also, parameter estimates and diagnostics analysis can be obtained using likelihood methods by means of this package. In addition, goodness-of-fit methods are implemented in order to detect the suitability of the model to the data. The capabilities and features of the ig package are illustrated using simulated and real data sets. Furthermore, some new results related to the inverse Gaussian type distribution are also obtained. Moreover, a simulation study is conducted for evaluating the estimation method implemented in the ig package

Masked Image Modeling for Representation Learning in Earth Observation

Deep learning applied to Earth observation (EO) yields impressive results. However, a significant challenge in EO is the rapidly increasing data volume while limited annotation resources available. Self-supervised representation learning (SSL) employs large amounts of unlabeled data. Recently, Masked Image Modelling (MIM) demonstrated scalability in model and data size. MIM masks a defined ratio of the input image for training a model to predict the masked patches. The learnt encoder is transferred to downstream tasks. In this work, we explore a new approach of MIM for EO combining two state-of-the-art SSL methodologies. One employs the Masked Autoencoder (MAE), which asymmetrically masks and reconstructs the raw input with the aid of an encoder operating on the visible patches followed by a smaller decoder reconstructing. The second methodology utilizes the Masked Feature Prediction (MFP), where image feature descriptors get reconstructed. We test our approach on the (SSL4E0-s12) dataset reconstructing Histogram Oriented Gradients (HOG). We evaluate the pre-trained model on a multi-class classification for Eurosat. Experimental results indicate stable performance with more than 90% accuracy down to 10% of labeled data. An ablation study on data normalization reveals that linear classification downstream task accuracy benefits from normalization by up to 6%. In contrast, fine tuning accuracies are robust to data normalization

Good practices in logistics for SMEs: a strategy for the global marketplace

Thanks to globalization, the environment in which companies operate today has changed. Whereas a few decades ago, the same government generated protectionist policies, today with the opening of markets, competition is not only national but also international, so companies, regardless of their size, must make changes in their business model, aiming at the internationalization of markets both for the acquisition of materials and goods and for the marketing of their products, being more agile in responding to their customers in terms of product quality, expected delivery time and cost. It is in this scenario where logistics plays a fundamental role as a tool for competitiveness and, therefore, the following work aims to highlight the impact of logistics on SMEs and the need to aim for continuous improvement of their logistics processes. By means of a qualitative/descriptive methodology, relevant aspects are reviewed, finding as a final result essential components that SMEs must incorporate to attend a world-class market

On the Localized superluminal Solutions to the Maxwell Equations

In the first part of this article the various experimental sectors of physics in which Superluminal motions seem to appear are briefly mentioned, after a sketchy theoretical introduction. In particular, a panoramic view is presented of the experiments with evanescent waves (and/or tunneling photons), and with the "Localized superluminal Solutions" (SLS) to the wave equation, like the so-called X-shaped waves. In the second part of this paper we present a series of new SLSs to the Maxwell equations, suitable for arbitrary frequencies and arbitrary bandwidths: some of them being endowed with finite total energy. Among the others, we set forth an infinite family of generalizations of the classic X-shaped wave; and show how to deal with the case of a dispersive medium. Results of this kind may find application in other fields in which an essential role is played by a wave-equation (like acoustics, seismology, geophysics, gravitation, elementary particle physics, etc.). This e-print, in large part a review, was prepared for the special issue on "Nontraditional Forms of Light" of the IEEE JSTQE (2003); and a preliminary version of it appeared as Report NSF-ITP-02-93 (KITP, UCSB; 2002). Further material can be found in the recent e-prints arXiv:0708.1655v2 [physics.gen-ph] and arXiv:0708.1209v1 [physics.gen-ph]. The case of the very interesting (and more orthodox, in a sense) subluminal Localized Waves, solutions to the wave equations, will be dealt with in a coming paper. [Keywords: Wave equation; Wave propagation; Localized solutions to Maxwell equations; Superluminal waves; Bessel beams; Limited-dispersion beams; Electromagnetic wavelets; X-shaped waves; Finite-energy beams; Optics; Electromagnetism; Microwaves; Special relativity]Comment: LaTeX paper of 37 pages, with 20 Figures in jpg [to be processed by PDFlatex