Smart histogram analysis applied to the skull-stripping problem in T1-weighted MRI

In this paper we address the "skull-stripping" problem in 3D MR images. We propose a new method that employs an efficient and unique histogram analysis. A fundamental component of this analysis is an algorithm for partitioning a histogram based on the position of the maximum deviation from a Gaussian fit. In our experiments we use a comprehensive image database, including both synthetic and real MRI. and compare our method with other two well-known methods, namely BSE and BET. For all datasets we achieved superior results. Our method is also highly independent of parameter tuning and very robust across considerable variations of noise ratio.

Non-Dominated Sorting Genetic Algorithm Based on Reinforcement Learning to Optimization of Broad-Band Reflector Antennas Satellite

This paper aims to provide an improved NSGA-II (Non-Dominated Sorting Genetic Algorithm-version II) which incorporates a parameter-free self-tuning approach by reinforcement learning technique, called Non-Dominated Sorting Genetic Algorithm Based on Reinforcement Learning (NSGA-RL). The proposed method is particularly compared with the classical NSGA-II when applied to a satellite coverage problem. Furthermore, not only the optimization results are compared with results obtained by other multiobjective optimization methods, but also guarantee the advantage of no time-spending and complex parameter tuning.

Calculation of parameter ranges for robust gain tuning of power system controllers

This work proposes a computational tool to assist power system engineers in the field tuning of power system stabilizers (PSSs) and Automatic Voltage Regulators (AVRs). The outcome of this tool is a range of gain values for theses controllers within which there is a theoretical guarantee of stability for the closed-loop system. This range is given as a set of limit values for the static gains of the controllers of interest, in such a way that the engineer responsible for the field tuning of PSSs and/or AVRs can be confident with respect to system stability when adjusting the corresponding static gains within this range. This feature of the proposed tool is highly desirable from a practical viewpoint, since the PSS and AVR commissioning stage always involve some readjustment of the controller gains to account for the differences between the nominal model and the actual behavior of the system. By capturing these differences as uncertainties in the model, this computational tool is able to guarantee stability for the whole uncertain model using an approach based on linear matrix inequalities. It is also important to remark that the tool proposed in this paper can also be applied to other types of parameters of either PSSs or Power Oscillation Dampers, as well as other types of controllers (such as speed governors, for example). To show its effectiveness, applications of the proposed tool to two benchmarks for small signal stability studies are presented at the end of this paper.

Bilayer graphene on h-BN substrate: investigating the breakdown voltage and tuning the bandgap by electric field

By performing density functional theory calculations we show that it is possible to make the electronic bandgap in bilayer graphene supported on hexagonal boron nitride (h-BN) substrates tunable. We also show that, under applied electric fields, it is possible to insert states from h-BN into the bandgap, which generate a conduction channel through the substrate making the system metallic. In addition, we verify that the breakdown voltage strongly depends on the number of h-BN layers. We also show that both the breakdown voltage and the bandgap tuning are independent of the h-BN stacking order.

Reducing the parameter space for unparticle-inspired models using white dwarf masses

Based on astrophysical constraints derived from Chandrasekhar's mass limit for white dwarfs, we study the effects of the model on the parameters of unparticle-inspired gravity, on scales Lambda(U) > 1 TeV and d(U) approximate to 1.

Charcot foot: Skin temperature as a good clinical parameter for predicting disease outcome

Twenty-eight diabetics presenting with acute Charcot foot were immobilized and the temperature difference between limbs measured at each month. All patients had monthly follow-up visits for a year and the relapse rate was zero. We found that skin temperature is a good parameter to ensure safe immobilization withdrawal. (C) 2011 Elsevier Ireland Ltd. All rights reserved.

Transformer Operation at Deep Saturation: Model and Parameter Determination

This paper proposes a model that adequately describes the operation of the transformer at deep saturation, suitable for power-electronics applications, and a method for determining its parameters. Simulation and experimental results are presented to confirm the validity of the model and the method.

Linear parameter varying control design for rotating systems supported by journal bearings

Linear parameter varying (LPV) control is a model-based control technique that takes into account time-varying parameters of the plant. In the case of rotating systems supported by lubricated bearings, the dynamic characteristics of the bearings change in time as a function of the rotating speed. Hence, LPV control can tackle the problem of run-up and run-down operational conditions when dynamic characteristics of the rotating system change significantly in time due to the bearings and high vibration levels occur. In this work, the LPV control design for a flexible shaft supported by plain journal bearings is presented. The model used in the LPV control design is updated from unbalance response experimental results and dynamic coefficients for the entire range of rotating speeds are obtained by numerical optimization. Experimental implementation of the designed LPV control resulted in strong reduction of vibration amplitudes when crossing the critical speed, without affecting system behavior in sub- or supercritical speeds. (C) 2012 Elsevier Ltd. All rights reserved.

Synthesis Methodology Applied to a Tunable Patch Filter With Independent Frequency and Bandwidth Control

A new methodology for the synthesis of tunable patch filters is presented. The methodology helps the designer to perform a theoretical analysis of the filter through a coupling matrix that includes the effect of the tuning elements used to tune the filter. This general methodology accounts for any tuning parameter desired and was applied to the design of a tunable dual-mode patch filter with independent control of center frequency and bandwidth (BW). The bandpass filter uses a single triangular resonator with two etched slots that split the fundamental degenerate modes and form the filter passband. Varactor diodes assembled across the slots are used to vary the frequency of each degenerate fundamental mode independently, which is feasible due to the nature of the coupling scheme of the filter. The varactor diode model used in simulations, their assembling, the dc bias configuration, and measured results are presented. The theory results are compared to the simulations and to measurements showing a very good agreement and validating the proposed methodology. The fabricated filter presents an elliptic response with 20% of center frequency tuning range around 3.2 GHz and a fractional BW variation from 4% to 12% with low insertion loss and high power handling with a 1-dB compression point higher than +14.5 dB.

Magnetic Tuning of All-Organic Binary Alloys between Two Stable Radicals

Mixtures of 2-(4,5,6,7-tetrafluorobenzimidazol-2-yl)-4,4,5,5-tetramethyl-4,5-dihydro-1H-imidazole-3-oxide-1-oxyl (F4BImNN) and 2-(benzi-midazol-2-yl)-4,4,5,5-tetramethyl-4,5-dihydro-1H-imidazole-3-oxide-1-oxyl (BImNN.) crystallize as solid solutions (alloys) across a wide range of binary compositions. (F4BImNN)(x)(BImNN)((1-x)) with x < 0.8 gives orthorhombic unit cells, while x >= 0.9 gives monoclinic unit cells. In all crystalline samples, the dominant intermolecular packing is controlled by one-dimensional (1D) hydrogen-bonded chains that lead to quasi-1D ferromagnetic behavior. Magnetic analysis over 0.4-300 K indicates ordering with strong 1D ferromagnetic exchange along the chains (J/k = 12-22 K). Interchain exchange is estimated to be 33- to 150-fold weaker, based on antiferromagnetic ordered phase formation below Neel temperatures in the 0.4-1.2 K range for the various compositions. The ordering temperatures of the orthorhombic samples increase linearly as (1 - x) increases from 0.25 to 1.00. The variation is attributed to increased interchain distance corresponding to decreased interchain exchange, when more F4BImNN is added into the orthorhombic lattice. The monoclinic samples are not part of the same trend, due to the different interchain arrangement associated with the phase change.

Tuning Low-Spin to High-Spin Mn Pairs in 2-D ZnO by Injecting Holes

We have performed an ab initio theoretical investigation of substitutional Mn(Zn) atoms in planar structures of ZnO, viz., monolayer [(ZnO)(1)] and bilayer [(ZnO)(2)] systems. Due to the 2-D quantum confinement effects, in those Mn -doped (ZnO)(1) and (ZnO)(2) structures, the antiferromagnetic (AFM) coupling between (nearest neighbor) Mn(Zn) impurities have been strengthened when compared with the one in ZnO bulk systems. On the other hand, we find that the magnetic state of these systems can be tuned from AFM to FM by adding holes, which can be supplied by a p-type doping or even photoionization processes. Whereas, upon addition of electrons (n-type doping), the system keeps its AFM configuration.

Parameter recovery for a skew-normal IRT model under a Bayesian approach: hierarchical framework, prior and kernel sensitivity and sample size

Item response theory (IRT) comprises a set of statistical models which are useful in many fields, especially when there is an interest in studying latent variables (or latent traits). Usually such latent traits are assumed to be random variables and a convenient distribution is assigned to them. A very common choice for such a distribution has been the standard normal. Recently, Azevedo et al. [Bayesian inference for a skew-normal IRT model under the centred parameterization, Comput. Stat. Data Anal. 55 (2011), pp. 353-365] proposed a skew-normal distribution under the centred parameterization (SNCP) as had been studied in [R. B. Arellano-Valle and A. Azzalini, The centred parametrization for the multivariate skew-normal distribution, J. Multivariate Anal. 99(7) (2008), pp. 1362-1382], to model the latent trait distribution. This approach allows one to represent any asymmetric behaviour concerning the latent trait distribution. Also, they developed a Metropolis-Hastings within the Gibbs sampling (MHWGS) algorithm based on the density of the SNCP. They showed that the algorithm recovers all parameters properly. Their results indicated that, in the presence of asymmetry, the proposed model and the estimation algorithm perform better than the usual model and estimation methods. Our main goal in this paper is to propose another type of MHWGS algorithm based on a stochastic representation (hierarchical structure) of the SNCP studied in [N. Henze, A probabilistic representation of the skew-normal distribution, Scand. J. Statist. 13 (1986), pp. 271-275]. Our algorithm has only one Metropolis-Hastings step, in opposition to the algorithm developed by Azevedo et al., which has two such steps. This not only makes the implementation easier but also reduces the number of proposal densities to be used, which can be a problem in the implementation of MHWGS algorithms, as can be seen in [R.J. Patz and B.W. Junker, A straightforward approach to Markov Chain Monte Carlo methods for item response models, J. Educ. Behav. Stat. 24(2) (1999), pp. 146-178; R. J. Patz and B. W. Junker, The applications and extensions of MCMC in IRT: Multiple item types, missing data, and rated responses, J. Educ. Behav. Stat. 24(4) (1999), pp. 342-366; A. Gelman, G.O. Roberts, and W.R. Gilks, Efficient Metropolis jumping rules, Bayesian Stat. 5 (1996), pp. 599-607]. Moreover, we consider a modified beta prior (which generalizes the one considered in [3]) and a Jeffreys prior for the asymmetry parameter. Furthermore, we study the sensitivity of such priors as well as the use of different kernel densities for this parameter. Finally, we assess the impact of the number of examinees, number of items and the asymmetry level on the parameter recovery. Results of the simulation study indicated that our approach performed equally as well as that in [3], in terms of parameter recovery, mainly using the Jeffreys prior. Also, they indicated that the asymmetry level has the highest impact on parameter recovery, even though it is relatively small. A real data analysis is considered jointly with the development of model fitting assessment tools. The results are compared with the ones obtained by Azevedo et al. The results indicate that using the hierarchical approach allows us to implement MCMC algorithms more easily, it facilitates diagnosis of the convergence and also it can be very useful to fit more complex skew IRT models.

Exploration of the parameter space in an agent-based model of tuberculosis spread: emergence of drug resistance in developing vs developed countries

In this work we present an agent-based model for the spread of tuberculosis where the individuals can be infected with either drug-susceptible or drug-resistant strains and can also receive a treatment. The dynamics of the model and the role of each one of the parameters are explained. The whole set of parameters is explored to check their importance in the numerical simulation results. The model captures the beneficial impact of the adequate treatment on the prevalence of tuberculosis. Nevertheless, depending on the treatment parameters range, it also captures the emergence of drug resistance. Drug resistance emergence is particularly likely to occur for parameter values corresponding to less efficacious treatment, as usually found in developing countries.

THE FIRST DETERMINATION OF THE VISCOSITY PARAMETER IN THE CIRCUMSTELLAR DISK OF A Be STAR

Be stars possess gaseous circumstellar decretion disks, which are well described using standard alpha-disk theory. The Be star 28 CMa recently underwent a long outburst followed by a long period of quiescence, during which the disk dissipated. Here we present the first time-dependent models of the dissipation of a viscous decretion disk. By modeling the rate of decline of the V-band excess, we determine that the viscosity parameter alpha = 1.0 +/- 0.2, corresponding to a mass injection rate (M) over dot = (3.5 +/- 1.3) x 10(-8) M-circle dot yr(-1). Such a large value of a suggests that the origin of the turbulent viscosity is an instability in the disk whose growth is limited by shock dissipation. The mass injection rate is more than an order of magnitude larger than the wind mass-loss rate inferred from UV observations, implying that the mass injection mechanism most likely is not the stellar wind, but some other mechanism.

Deviation from quark number scaling of the anisotropy parameter v(2) of pions, kaons, and protons in Au+Au collisions at root s(NN)=200 GeV

Measurements of the anisotropy parameter v(2) of identified hadrons (pions, kaons, and protons) as a function of centrality, transverse momentum p(T), and transverse kinetic energy KET at midrapidity (vertical bar eta vertical bar < 0.35) in Au + Au collisions at root s(N N) = 200 GeV are presented. Pions and protons are identified up to p(T) = 6 GeV/c, and kaons up to p(T) = 4 GeV/c, by combining information from time-of-flight and aerogel Cerenkov detectors in the PHENIX Experiment. The scaling of v(2) with the number of valence quarks (n(q)) has been studied in different centrality bins as a function of transverse momentum and transverse kinetic energy. A deviation from previously observed quark-number scaling is observed at large values of KET/n(q) in noncentral Au + Au collisions (20-60%), but this scaling remains valid in central collisions (0-10%).