Conditional tests of marginal homogeneity based on ϕ-divergence test statistics

AbstractIn this work, using the well-known result that symmetry is equivalent to quasi-symmetry and marginal homogeneity simultaneously holding, two families of test statistics based on ϕ-divergence measures are introduced for testing conditional marginal homogeneity assuming that quasi-symmetry holds

Design of Loss Functions for Solving Inverse Problems using Deep Learning

Solving inverse problems is a crucial task in several applications that strongly a ffect our daily lives, including multiple engineering fields, military operations, and/or energy production. There exist different methods for solving inverse problems, including gradient based methods, statistics based methods, and Deep Learning (DL) methods. In this work, we focus on the latest. Speci fically, we study the design of proper loss functions for dealing with inverse problems using DL. To do this, we introduce a simple benchmark problem with known analytical solution. Then, we propose multiple loss functions and compare their performance when applied to our benchmark example problem. In addition, we analyze how to improve the approximation of the forward function by: (a) considering a Hermite-type interpolation loss function, and (b) reducing the number of samples for the forward training in the Encoder-Decoder method. Results indicate that a correct desig

Estimators based on sample quantiles using (h,phi)-entropy measures

A point estimation procedure based on the maximum entropy principle for (h, phi) entropies is proposed using sample quantiles. These estimators are efficient and asymptotically normal under standard regularity conditions. A test for goodness-of-fit is constructed, being the corresponding statistic asymptotically distributed chi-squared. These results generalize the results obtained in [1]

Massive Database Generation for 2.5D Borehole Electromagnetic Measurements using Refined Isogeometric Analysis

Borehole resistivity measurements are routinely inverted in real-time during geosteering operations. The inversion process can be efficiently performed with the help of advanced artificial intelligence algorithms such as deep learning. These methods require a massive dataset that relates multiple Earth models with the corresponding borehole resistivity measurements. In here, we propose to use an advanced numerical method —refined isogeometric analysis (rIGA)— to perform rapid and accurate 2.5D simulations and generate databases when considering arbitrary 2D Earth models. Numerical results show that we can generate a meaningful synthetic database composed of 100,000 Earth models with the corresponding measurements in 56 hours using a workstation equipped with two CPUs.European POCTEFA 2014–2020 Project PIXIL (EFA362/19); The grant ‘‘Artificial Intelligence in BCAM number EXP. 2019/0043

On quadrature rules for solving Partial Differential Equations using Neural Networks

Neural Networks have been widely used to solve Partial Differential Equations. These methods require to approximate definite integrals using quadrature rules. Here, we illustrate via 1D numerical examples the quadrature problems that may arise in these applications and propose several alternatives to overcome them, namely: Monte Carlo methods, adaptive integration, polynomial approximations of the Neural Network output, and the inclusion of regularization terms in the loss. We also discuss the advantages and limitations of each proposed numerical integration scheme. We advocate the use of Monte Carlo methods for high dimensions (above 3 or 4), and adaptive integration or polynomial approximations for low dimensions (3 or below). The use of regularization terms is a mathematically elegant alternative that is valid for any spatial dimension; however, it requires certain regularity assumptions on the solution and complex mathematical analysis when dealing with sophisticated Neural Networks

Numerical simulation of an automatic depth controller for an underwater vehicle

In this paper, we analyze two diff erent mathematical strategies for solving the problem which consists in controlling a depth change manoeuverability for an specifi c type of submarine. Precisely, we will apply both controllability theory and the more classical linear quadratic optimal control theory to a simplifi ed linear model obtained from the general nonlinear DTNSRDC equations of motion. Finally, numerical results will be contrasted to show the advantages and handicaps of the proposed models. It is also important to emphasize that the results presented in this work are only a fi rst step towards a better understanding of the problem

Formal Study of a Novel Network Role-based Routing Intelligent Algorithm

AbstractNORIA (Network rOle-based Routing Intelligent Algorithm) is a novel routing algorithm for Wireless Sensor Networks (WSNs) which combines various effective techniques in order to reduce energy consumption and improve data routes. This paper presents a formal and rigorous study of NORIA. Prioritised-Timed Coloured Petri Nets (PTCPNs) have been used to describe complete and unambiguous specifications of system behaviour, whereas CPNTools is used to evaluate the correctness of the protocol using state space exploration

Mathematical models to study the biological phosphorus flow in sheep fed increasing levels of mineral

Dois modelos compartimentais foram aplicados e comparados para avaliar o fluxo biológico de fósforo em ovinos que receberam dietas com níveis crescentes do mineral - 0, 2, 4 e 6g por dia. Foram utilizados 24 machos, da raça Santa Inês, com média de peso de 33,6kg. Foi utilizado fosfato bicálcico como fonte de fósforo e 32P como traçador. Avaliou-se o fluxo de fósforo entre os compartimentos: trato gastrintestinal, sangue, ossos e tecidos moles, além da ingestão, excreção e balanço do mineral. O incremento na ingestão de P aumentou a perda fecal do mineral. O fluxo de fósforo entre o trato gastrintestinal e o sangue e o fluxo contrário foram influenciados de forma quadrática pelo incremento na ingestão, diminuindo após a ingestão de 5,5g/dia, sem diferença entre os modelos avaliados. Os modelos estudados mostraram diferenças em relação ao fluxo entre sangue, ossos e tecidos moles, sem efeito dos tratamentos sobre o balanço geral do mineral, porém os níveis de ingestão praticados interferiram no fluxo biológico do fósforo. A disponibilidade biológica do fósforo ingerido diminuiu quando a ingestão superou a necessidade do animal, o que aumentou as excreções no ambiente. A quantificação do fluxo biológico de fósforo diferiu quando aplicados os modelos estudados em decorrência da sua estrutura.Two compartimental models were applied and compared to evaluate the biological flow of P in lambs fed diets containing increasing levels of P (0, 2, 4 and 6g per day). Twenty four Santa Inês lambs with liveweight of 33.6kg were used. Dicalcium phosphate was used as P source and 32P as a tracer. P flow between compartments (gastrointestinal tract, blood, bones and soft tissues), ingestion, excretion and the mineral balance were evaluated. The increase in P intake increased fecal P loss. P flow from gastrointestinal tract to blood stream and opposite flow were affected quadratically by increased P intake, decreasing after the ingestion of 5.5g/day, without a difference among models. The models studied showed differences regarding the P flow between blood, bone and soft tissues, however, the P balance was not affected by the treatments. The increased P levels interfered with the biological P flow in sheep. The bioavailability of P diet decreases when intake exceeds the animal requirement, increasing losses to the environment. The quantification of biological P flow was different between models due to the structure of each one.Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior (CAPES)CNPqFAPEMI

Olfactory fMRI Connectivity Analysis Based on Granger Causality with Application in Anosmia Assessment

In this work, we describe hubs organization within the olfactory network with Functional Magnetic Resonance Imaging (fMRI). Granger causality analyses were applied in the supposed regions of interest (ROIs) involved in olfactory tasks, as described in [1]. We aim to get deeper knowledge about the hierarchy of the regions within the olfactory network and to describe which of these regions, in terms of strength of the connectivity, impair in different types of anosmia

Influencia del Porcentaje de SiCp en el Comportamiento a la Corrosión de la Aleación AA6061 Obtenida por Compactación Isostática

Se ha estudiado el comportamiento a la corrosión de materiales compuestos A6061/SiCp obtenidos por compactación isostática y extrusión en caliente de polvos mediante ensayos de polarización cíclica. El estudio de la naturaleza de los productos de corrosión se ha llevado a cabo mediante Microscopía Electrónica de Barrido (SEM) después de la realización de los ensayos, con objeto de estudiar la influencia de la proporción de refuerzo en el comportamiento a la corrosión. El proceso de corrosión está significativamente influenciado por la adición de partículas reforzantes, debido a que las intercaras matriz/SiCp son centros preferentes de ataque localizado por picadura