Safety Critical Wide Area Network Performance Evaluation

The growing importance of real-time computing in numerous applications poses problems for network architectures, especially safety-critical Wide Area Networks (WANs). Assessing network performance in safety-critical real-time systems is difficult, and suggests the use of both human and technical performance criteria because of the importance of both dimensions in safety-critical settings. This research proposes a model that considers both technical and human performance in network evaluation

Any ll-state solutions of the Hulth\'en potential by the asymptotic iteration method

In this article, we present the analytical solution of the radial Schr\"{o}dinger equation for the Hulth\'{e}n potential within the framework of the asymptotic iteration method by using an approximation to the centrifugal potential for any $l$ states. We obtain the energy eigenvalues and the corresponding eigenfunctions for different screening parameters. The wave functions are physical and energy eigenvalues are in good agreement with the results obtained by other methods for different $\delta$ values. In order to demonstrate this, the results of the asymptotic iteration method are compared with the results of the supersymmetry, the numerical integration, the variational and the shifted 1/N expansion methods.Comment: 14 pages and 1 figur

Multi-layer photovoltaic fault detection algorithm

This study proposes a fault detection algorithm based on the analysis of the theoretical curves which describe the behaviour of an existing grid-connected photovoltaic (GCPV) system. For a given set of working conditions, a number of attributes such as voltage ratio (VR) and power ratio (PR) are simulated using virtual instrumentation LabVIEW software. Furthermore, a third-order polynomial function is used to generate two detection limits (high and low limits) for the VR and PR ratios. The high and low detection limits are compared with real-time long-term data measurements from a 1.1 kWp GCPV system installed at the University of Huddersfield, United Kingdom. Furthermore, samples that lie out of the detecting limits are processed by a fuzzy logic classification system which consists of two inputs (VR and PR) and one output membership function. The obtained results show that the fault detection algorithm accurately detects different faults occurring in the PV system. The maximum detection accuracy (DA) of the proposed algorithm before considering the fuzzy logic system is equal to 95.27%; however, the fault DA is increased up to a minimum value of 98.8% after considering the fuzzy logic system

Heritability and cross-species comparisons of human cortical functional organization asymmetry

The human cerebral cortex is symmetrically organized along large-scale axes but also presents inter-hemispheric differences in structure and function. The quantified contralateral homologous difference, that is asymmetry, is a key feature of the human brain left-right axis supporting functional processes, such as language. Here, we assessed whether the asymmetry of cortical functional organization is heritable and phylogenetically conserved between humans and macaques. Our findings indicate asymmetric organization along an axis describing a functional trajectory from perceptual/action to abstract cognition. Whereas language network showed leftward asymmetric organization, frontoparietal network showed rightward asymmetric organization in humans. These asymmetries were heritable in humans and showed a similar spatial distribution with macaques, in the case of intra-hemispheric asymmetry of functional hierarchy. This suggests (phylo)genetic conservation. However, both language and frontoparietal networks showed a qualitatively larger asymmetry in humans relative to macaques. Overall, our findings suggest a genetic basis for asymmetry in intrinsic functional organization, linked to higher order cognitive functions uniquely developed in humans

The rotating Morse potential model for diatomic molecules in the tridiagonal J-matrix representation: I. Bound states

This is the first in a series of articles in which we study the rotating Morse potential model for diatomic molecules in the tridiagonal J-matrix representation. Here, we compute the bound states energy spectrum by diagonalizing the finite dimensional Hamiltonian matrix of H2, LiH, HCl and CO molecules for arbitrary angular momentum. The calculation was performed using the J-matrix basis that supports a tridiagonal matrix representation for the reference Hamiltonian. Our results for these diatomic molecules have been compared with available numerical data satisfactorily. The proposed method is handy, very efficient, and it enhances accuracy by combining analytic power with a convergent and stable numerical technique.Comment: 18 Pages, 6 Tables, 4 Figure

Real time dielectric monitoring of glass transition in n-vinyl pyrrolidone polymerization

Real time dielectric spectroscopy was used for monitoring the dynamics during liquid glass transition in radical bulk polymerization of n-vinyl pyrrolidone. Two different relaxation mechanisms were identified. Initially segmental α-relaxation was dominant. Subsequently, contribution from slower motions became more significant and ε′(tr, ω) underwent maxima in all frequency bands up to 10 MHz. Peak amplitude increased and the occurring time was delayed with decreasing frequency. The slow region dynamics were similar to the dynamics of Chamberlin's domain-like model of glass transition. The glassy phase is formed by a segmental relaxation and a relaxation due to glassy regions. The characteristic relaxation times of slow and segmental motions were well described by a modified Vogel-Fulcher-Tammann relation. The high frequency behavior, associated with the segmental motions, is well described by Havriliak-Negami and Kohlrausch-Williams-Watts formulas, which did not provide satisfactory fittings for the dynamics of slow regions. Both real and imaginary parts of the dielectric data were fully described by a complex dielectric relaxation function, the parameters of which are found by the eigen-coordinates (EC) method. © 2007 Elsevier B.V. All rights reserved

A ONE DIMENSIONAL MATHEMATICAL MODEL FOR URODYNAMICS

ABSTRACT Millions of people in the world suffer from urinary incontinence and overactive bladder with the major causes for the symptoms being stress, urge, overflow and functional incontinence. For a more effective treatment of these ailments, a detailed understanding of the urinary flow dynamics is required. This challenging task is not easy to achieve due to the complexity of the problem and the lack of tools to study the underlying mechanisms of the urination process. Theoretical models can help find a better solution for the various disorders of the lower urinary tract, including urinary incontinence, through simulating the interaction between various components involved in the continence mechanism. Using a lumped parameter analysis, a one-dimensional, transient mathematical model was built to simulate a complete cycle of filling and voiding of the bladder. Both the voluntary and involuntary contraction of the bladder walls is modeled along with the transient response of both the internal and external sphincters which dynamically control the urination process. The model also includes the effects signals from the bladder outlet (urethral sphincter, pelvic floor muscles and fascia), the muscles involved in evacuation of the urinary bladder (detrusor muscle) as well as the abdominal wall musculature. The necessary geometrical parameters of the urodynamics model were obtained from the 3D visualization data based on the visible human project. Preliminary results show good agreement with the experimental results found in the literature. The current model could be used as a diagnostic tool for detecting incontinence and simulating possible scenarios for the circumstances leading to incontinence. INTRODUCTION Urinary incontinence has been reported to affect 35% of American women over 50 years of age an almost 15% who have leakage on a daily basi

BrainStat: A toolbox for brain-wide statistics and multimodal feature associations

Analysis and interpretation of neuroimaging datasets has become a multidisciplinary endeavor, relying not only on statistical methods, but increasingly on associations with respect to other brain-derived features such as gene expression, histological data, and functional as well as cognitive architectures. Here, we introduce BrainStat - a toolbox for (i) univariate and multivariate linear models in volumetric and surface-based brain imaging datasets, and (ii) multidomain feature association of results with respect to spatial maps of post-mortem gene expression and histology, task-based fMRI meta-analysis, as well as resting-state fMRI motifs across several common surface templates. The combination of statistics and feature associations into a turnkey toolbox streamlines analytical processes and accelerates cross-modal research. The toolbox is implemented in both Python and MATLAB, two widely used programming languages in the neuroimaging and neuroinformatics communities. BrainStat is openly available and complemented by an expandable documentation

Network of Earthquakes and Recurrences Therein

We quantify the correlation between earthquakes and use the same to distinguish between relevant causally connected earthquakes. Our correlation metric is a variation on the one introduced by Baiesi and Paczuski (2004). A network of earthquakes is constructed, which is time ordered and with links between the more correlated ones. Data pertaining to the California region has been used in the study. Recurrences to earthquakes are identified employing correlation thresholds to demarcate the most meaningful ones in each cluster. The distribution of recurrence lengths and recurrence times are analyzed subsequently to extract information about the complex dynamics. We find that the unimodal feature of recurrence lengths helps to associate typical rupture lengths with different magnitude earthquakes. The out-degree of the network shows a hub structure rooted on the large magnitude earthquakes. In-degree distribution is seen to be dependent on the density of events in the neighborhood. Power laws are also obtained with recurrence time distribution agreeing with the Omori law.Comment: 17 pages, 5 figure

Any l-state improved quasi-exact analytical solutions of the spatially dependent mass Klein-Gordon equation for the scalar and vector Hulthen potentials

We present a new approximation scheme for the centrifugal term to obtain a quasi-exact analytical bound state solutions within the framework of the position-dependent effective mass radial Klein-Gordon equation with the scalar and vector Hulth\'{e}n potentials in any arbitrary $D$ dimension and orbital angular momentum quantum numbers $l.$ The Nikiforov-Uvarov (NU) method is used in the calculations. The relativistic real energy levels and corresponding eigenfunctions for the bound states with different screening parameters have been given in a closed form. It is found that the solutions in the case of constant mass and in the case of s-wave ($l=0$) are identical with the ones obtained in literature.Comment: 25 pages, 1 figur