Miracle-dz/UniFAR-FTUs huggingface dataset:
Solving Noisy ICA Using Multivariate Wavelet Denoising with an Application to Noisy Latent Variables Regression

A novel approach to solve the independent component analysis (ICA) model in the presence of noise is proposed. We use wavelets as natural denoising tools to solve the noisy ICA model. To do this, we use a multivariate wavelet denoising algorithm allowing spatial and temporal dependency. We propose also using a statistical approach, named nested design of experiments, to select the parameters such as wavelet family and thresholding type. This technique helps us to select more convenient combination of the parameters. This approach could be extended to many other problems in which one needs to choose parameters between many choices. The performance of the proposed method is illustrated on the simulated data and promising results are obtained. Also, the suggested method applied in latent variables regression in the presence of noise on real data. The good results confirm the ability of multivariate wavelet denoising to solving noisy ICA.
Quantum boundary conditions for torus maps

The quantum states of a dynamical system whose phase space is the two-torus are periodic up to phase factors under translations by the fundamental periods of the torus in the position and momentum representations. These phases, and , are conserved quantities of the quantum evolution. We show that for a large and important class of quantum maps, and are restricted to being the coordinates of the fixed points of the automorphism induced on the fundamental group of the torus by the underlying classical dynamics. As a consequence, if the classical map commutes with lattice translations in it can be quantized for any choice of the phases, but otherwise it can be quantized for only a finite set. This result is a special case of a more general condition on the phases, which is also derived. The cat maps, perturbed cat maps, and the kicked Harper map are discussed as specific examples.
Dependence of microwave absorbing property on ferrite volume fraction in MnZn ferrite-rubber composites

The effective complex permeability and permittivity spectra in composites with various ferrite volume fractions were calculated using the Bruggeman effective medium theory. The matching conditions for the maximum microwave absorption were determined by substituting the complex permeability and permittivity in the equation for the impedance matching condition. The minimum reflection loss increases from -5 to -40 dB as the ferrite volume fraction increases for /spl nu//sub f/<0.26, where single dip of minimum reflection loss was observed. However, two matching conditions were observed for v/sub f//spl ges/0.26, and two minimum reflection losses shown to be about -40 dB. The results indicate that a microwave absorber with reflection loss of about -40 dB can be designed by controlling the ferrite volume fraction in MnZn ferrite-rubber composites in the frequency range 0.8-12 GHz.
INFORMATION ANALYSIS INCOMPATIBLE SYSTEMS OF LINEAR EQUATIONS. MINIMAX SOLUTIONS

The article concerns the acceptable solutions of incompatible systems of linear algebraic equations (SLAE), the necessity of which appears during the processing and information analysis of experimental data. There is an analysis of the efficiency of traditional approaches to the solution of similar problems, such as the least-squares method, which minimizes the norm of system residual, the method of input of correction vector of system second members. The alternative approach to the solution if incompatible SLAE was suggested. It consists in definition of regularizing algorithm for the given redefined SLAE, which makes it possible to get the approximate solution of the system, minimizing the norm of residual, for which the maximum of system equation residual is the minimum. The problem is reduced on each iteration to the finding of variables set, which provides modulo equality of all residuals for the system equations. The analytical ratios for direct calculation of components of desired set were obtained. The examples of calculations were given.
On Quantum Interacting Embedded Geometrical Objects of Various Dimensions

Modern string theory naturally gives rise to an assortment of dynamical geometrical objects of various dimensions (collectively referred to as "branes") embedded into spacetime. The aim of this thesis is to present a series of results (of varying novelty and rigor) pertinent to dynamics of the low-dimensional geometrical objects of this kind. The processes considered are the D0-brane recoil and annihilation, "local recoil" of D1-branes (which is a peculiar effect manifested by one-dimensional topological defects in response to an impact, and closely related to soliton recoil), and D- and F-string loop mixing. Apart from the practical relevance within the formalism of string theory, such considerations are worthwhile in that the quantum dynamics of the geometrical objects involved is complex enough to be interesting, yet simple enough to be tractable. Furthermore, some of the results derived here within the string theory formalism may give valuable insights into the dynamics of low-dimensional field-theoretical topological defects.
Topological entanglement complexity of systems of polygons and walks in tubes

In this thesis, motivated by modelling polymers, the topological entanglement complexity of systems of two self-avoiding polygons (2SAPs), stretched polygons and systems of self-avoiding walks (SSAWs) in a tubular sublattice of Z are investigated. In particular, knotting and linking probabilities are used to measure a polygon’s selfentanglement and its entanglement with other polygons respectively. For the case of 2SAPs, it is established that the homological linking probability goes to one at least as fast as 1−O(n−1/2) and that the topological linking probability goes to one exponentially rapidly as n, the size of the 2SAP, goes to infinity. For the case of stretched polygons, used to model ring polymers under the influence of an external force f , it is shown that, no matter the strength or direction of the external force, the knotting probability goes to one exponentially as n, the size of the polygon, goes to infinity. Associating a two-component link to each stretched polygon, it is also proved that the topological linking probability goes to unity exponentially fast as n → ∞. Furthermore, a set of entangled chains confined to a tube is modelled by a system of selfand mutually avoiding walks (SSAW). It is shown that there exists a positive number γ such that the probability that an SSAW of size n has entanglement complexity (EC), as defined in this thesis, greater than γn approaches one exponentially as n → ∞. It is also established that EC of an SSAW is bounded above by a linear function of its size. Using a transfer-matrix approach, the asymptotic form of the free energy for the SSAW model is also obtained and the average edge-density for span m SSAWs is proved to approach a constant as m → ∞. Hence, it is shown that EC is a “good” measure of entanglement complexity for dense polymer systems modelled by SSAWs, in particular, because EC increases linearly with system size, as the size of the system goes to infinity.
Label propagation algorithm based on edge clustering coefficient for community detection in complex networks

The label propagation algorithm (LPA) is a graph-based semi-supervised learning algorithm, which can predict the information of unlabeled nodes by a few of labeled nodes. It is a community detection method in the field of complex networks. This algorithm is easy to implement with low complexity and the effect is remarkable. It is widely applied in various fields. However, the randomness of the label propagation leads to the poor robustness of the algorithm, and the classification result is unstable. This paper proposes a LPA based on edge clustering coefficient. The node in the network selects a neighbor node whose edge clustering coefficient is the highest to update the label of node rather than a random neighbor node, so that we can effectively restrain the random spread of the label. The experimental results show that the LPA based on edge clustering coefficient has made improvement in the stability and accuracy of the algorithm.
Rate/distortion in fractal compression: order of transform and block symmetries

The authors have evaluated two complexity options in fractal image coding, namely the order of the fractal approximation and the benefits of searching over block symmetries. This was done in terms of the the entropy and distortion for a range of quantizations of the fractal coefficients. The results question the current wisdom in this field. Most fractal block coding systems use a low order approximation, while the present results suggest that where the distortion and compression are similar, a higher order approximation gives a noticeably sharper image. Virtually all reported fractal coding algorithms search for the best block reflections and rotations, but the present authors demonstrate that extra bits required to code the symmetry options are not compensated for by the modest fidelity gained. <<ETX>>
Analysis of the parameterization of FORE-WLS reconstruction in 3D whole-body PET imaging

The FORE-WLS (Fourier rebinning followed by a weighted least-squares iterative reconstruction) approach to 3D whole-body PET reconstruction has been investigated using a design-of-experiments (DOE) approach. Measures of image quality were analyzed at different algorithm parameterizations including lung mean value and variance, liver mean value and variance and a pseudomeasurement of resolution. One clinical 3-axial field-of-view (AFOV) study was analyzed with the DOE method and a set or parameter responses obtained. A subset of the parameters was then used in subsequent visual image quality investigations. Results: The DOE results show expected increase in resolution with number or iterations and degradation of resolution with increased post-filtering (the two main effects) but also changing the number of subsets from 20 to 40 showed a visual improvement. Lung variance degraded with number of iterations and improved with heavier post-filtering, but was somewhat less dependent on number of subsets. Liver variance showed a trend identical to lung variance as a function of parameterization, but the absolute parameter response range was over a factor of 2 for liver variance as compared to approximately a 40% range for lung variance. Mean value response for lung changed maximal by 13% while for liver it changed maximally by 31% as a function of parameterization. No significant parameter interactions were found. From subsequent visual analysis it was determined that a reasonable set of default parameters for the FORE-WLS algorithm was 3 iterations, 32 subsets, 4.30 mm loop filter and 6.0 mm post-filter. Conclusions: parameterization sensitivity of the FORE-WLS algorithm has been established. A suggested set of FORE-WLS parameters chosen from the range investigates has been made. Visual analysis of a set of clinical patient datasets has been done covering a range of 3D whole-body PET subjects and the default parameter choice appeared has been shown to be robust.
Using CNLS-net to predict the Mackey-Glass chaotic time series

The connectionist normalized local spline (CNLS) network is used to learn the dynamics of the Mackey-Glass (1977) time-delay differential equation, for the case tau =30. The authors show the optimum network operating mode and determine the accuracy and robustness of predictions. They obtain predictions of varying accuracy using some 2-120 minutes of execution time on a Sun SPRAC-1 workstation. CNLS-net is capable of very good performance in predicting the Mackey-Glass time series. <<ETX>>
Why Stepdown Procedures in Variable Selection

Recent reviews have dealt with the subject of which variables to select and which to discard in multiple regression problems. Lindley (1968) emphasized that the method to be employed in any analysis should be related to the use intended for the finally fitted regression. In the report by Beale et al. (1967), the emphasis is on selecting the best subset for any specified number of retained independent variables. Here we will be concerned with pointing out the advantages of the variable selection scheme in which independent variables are successively discarded one at a time from the original full set. While these advantages are not unknown to workers in this field, they are however not appreciated by the statistical community in general. For the purposes of this demonstration it is assumed that we are in the nonsingular case so that the number of observations exceeds the number of regressor variables. Let us begin by considering economy of effort. Suppose that we were using a step-up regression procedure, ignoring for the while its theoretical deficiencies (to be discussed later). We should then first fit k simple regressions, one for each of the k regressor variables considered, selecting the single most significant individual regressor variable. Having made this selection we would proceed with k - 1 additional fits to determine which of the remaining variables in conjunction with the first selected yielded the greatest reduction in residual variation. This process is continued on so as to provide a successive selection and ordering of variables. We may even require the ordering of all k variables, leaving for later decision what critical juncture is to be employed in determining which of the k variables to retain, which to reject-if we do so we shall have made a total of k(k + 1)/2 fits, albeit they may have differed greatly in their degree of complexity. A complete stepdown regression procedure however requires but k fits, as will now be indicated. Suppose we have done a multiple regression on all k variables and wish to consider the k possible multiple regressions on all sets of k - 1 variables, that is where 1 variable has been deleted. The results for these k possible multiple regressions are implicit in the initial k-variable regression, provided we have secured the inverse matrix, or at least its diagonal, necessary for testing the significance of the fitted partial regression coefficients. The case
Development of the detector control system for the COMPASS detector at CERN

This document describes the implementation of system control software for the COMPASS [1] experiment at CERN. This work concentrates on the GEM and silicon detectors, but it also includes parts that are generally useful for all kinds of detectors. The only prerequisites were the PVSS II SCADA-system [87] and the JCOP [90] PVSS framework [91] distributed by ITCO [89] at CERN. To achieve the given aims there was work to do both on a C++ framework called SLiC [88] for hardware access and on top of the JCOP framework to customise it for the special needs of the GEM and silicon detectors.
Two Kinds of Axially Symmetric Equilibrium Sequences of Self-Gravitating and Rotating Incompressible Fluid : Two-Ring Sequence and Core-Ring Sequence

We have computed two kinds of axially symmetric equilibrium sequences of self-gravitating and uniformly rotating fluid which is composed of two disconnected bodies - two-ring equili· brium and core-ring equilibrium. For the two-ring case there is only one sequence which does not suffer from mass-shedding. This sequence leads to (or bifurcates from) the Maclaurin sequence. For any other two-ring equilibrium sequence, mass·shedding occurs from the lighter ring to the heavier ring. The core· ring equilibrium also reaches a critical equilibrium beyond which there is no equilibrium with· the uniform r<9tation owing to mass-shedding. If the differential rotation is taken into account, the core-ring sequence may lead to the two-ring sequence without mass-shedding after occurrence of the same kind of bifurcation as the Maclaurin leads to one-ring.
How does innovation’s tail risk determine marginal tail risk of a stationary financial time series?

We discuss the relationship between the marginal tail risk probability and the innovation’s tail risk probability for some stationary financial time series models. We first give the main results on the tail behavior of a class of infinite weighted sums of random variables with heavy-tailed probabilities. And then, the main results are applied to three important types of time series models: infinite order moving averages, the simple bilinear time series and the solutions of stochastic difference equations. The explicit formulas are given to describe how the marginal tail probabilities come from the innovation’s tail probabilities for these time series. Our results can be applied to the tail estimation of time series and are useful for risk analysis in finance.
Global and Regional Cloud Properties Derived from MODIS Data

Current efforts to derive a global cloud climatology from satellite data generally suffer in situations involving multi-layered clouds. In fact, cloud properties are inferred for each imager pixel assuming only single cloud layer is present. Currently available satellite cloud climatologies provide a horizontal distribution of clouds, but need improvement in the description of the vertical distribution of clouds. The single cloud layer assumption is unfortunate because Atmospheric Radiation Measurement (ARM) observations show that clouds often occur in multiple layers simultaneously in a vertical column, i.e., cloud layers often overlap. Our goal is to work towards improving both satellite-derived and surfacederived cloud products under these complex conditions.
Electro-caloric effect in 0.45BaZr0.2Ti0.8O3-0.55Ba0.7Ca0.3TiO3 single crystal

Electro-caloric effect in 0.45BaZr0. 2Ti0.8O3-0.55Ba0. 7Ca0.3TiO3 single crystal has been investigated and electro-caloric coefficient of ∼0.38 K mm/kV has been obtained near the tetragonal-to-cubic phase transition. The value obtained is significantly higher than that for the lead-free ferroelectric materials reported so far.
FREE DISCONTINUITY PROBLEMS WITH UNBOUNDED DATA

We prove the existence of a minimizing pair for a free discontinuity problem, i.e. a variational problem in which the unknowns are a closed set K and a function suitably smooth outside K. Examples of such problems come from pattern recognition and mathematical physics, when both “volume” energy and “surface” energy are present.
The role of environmental stochasticity in a toxic phytoplankton–non‐toxic phytoplankton–zooplankton system

The effects of toxin producing plankton and environmental stochasticity are intriguing problems in marine plankton ecology. To observe the effect of stochastic fluctuation, a non‐toxic phytoplankton, toxic phytoplankton and zooplankton (NTP‐TPP‐Z) system with an assumption that the grazing pressure of zooplankton decreases due to toxic phytoplankton is proposed and analysed. The nature of the dynamics of the system is observed for both the deterministic model and the model with stochastic perturbation around the positive equilibrium. Exchange of stability is also observed for both the cases. To validate the analytical results, numerical experiments and field collected sample observations are also presented. We conclude that the deterministic extinction may be controlled by monitoring the intensity of white noise or artificial eutrophication. Copyright © 2003 John Wiley & Sons, Ltd.
Once again on the importance of propagation effects for jet noise modelling

Several turbulent jet noise models starting from the classical Lighthill acoustic analogy to state-of-the art models are considered. No attempt is made to present any complete overview of jet noise theories. Instead, the aim is to emphasise the importance of sound generation and meanflow effects for the understanding and prediction of jet noise. For a recent acoustic analogy model, the consequences of jet flow simplification on the predicted sound spectra shape and the effective noise source location in the jet are discussed.
Observed Patterns of Month-to-Month Storm-Track Variability and Their Relationship to the Background Flow*

Month-to-month storm-track variability is investigated via EOF analyses performed on ERA-40 monthlyaveraged high-pass filtered daily 850-hPa meridional heat flux and the variances of 300-hPa meridional wind and 500-hPa height. The analysis is performed both in hemispheric and sectoral domains of the Northern and Southern Hemispheres. Patterns characterized as ‘‘pulsing’’ and ‘‘latitudinal shifting’’ of the climatologicalmean storm tracks emerge as the leading sectoral patterns of variability. Based on the analysis presented, storm-track variability on the spatial scale of the two Northern Hemisphere sectors appears to be largely, but perhaps not completely, independent. Pulsing and latitudinally shifting storm tracks are accompanied by zonal wind anomalies consistent with eddy-forced accelerations and geopotential height anomalies that project strongly on the dominant patterns of geopotential height variability. The North Atlantic Oscillation (NAO)‐Northern Hemisphere annular mode (NAM) is associated with a pulsing of the Atlantic storm track and a meridional displacement of the upper-tropospheric jet exit region, whereas the eastern Atlantic (EA) pattern is associated with a latitudinally shifting storm track and an extension or retraction of the upper-tropospheric jet. Analogous patterns of stormtrack and upper-tropospheric jet variability are associated with the western Pacific (WP) and Pacific‐North America (PNA) patterns. Wave‐mean flow relationships shown here are more clearly defined than in previous studies and are shown to extend through the depth of the troposphere. The Southern Hemisphere annular mode (SAM) is associated with a latitudinally shifting storm track over the South Atlantic and Indian Oceans and a pulsing South Pacific storm track. The patterns of storm-track variability are shown to be related to simple distortions of the climatological-mean upper-tropospheric jet.
Towards the optimal design of an uncemented acetabular component using genetic algorithms

Aseptic loosening of the acetabular component (hemispherical socket of the pelvic bone) has been mainly attributed to bone resorption and excessive generation of wear particle debris. The aim of this study was to determine optimal design parameters for the acetabular component that would minimize bone resorption and volumetric wear. Three-dimensional finite element models of intact and implanted pelvises were developed using data from computed tomography scans. A multi-objective optimization problem was formulated and solved using a genetic algorithm. A combination of suitable implant material and corresponding set of optimal thicknesses of the component was obtained from the Pareto-optimal front of solutions. The ultra-high-molecular-weight polyethylene (UHMWPE) component generated considerably greater volumetric wear but lower bone density loss compared to carbon-fibre reinforced polyetheretherketone (CFR-PEEK) and ceramic. CFR-PEEK was located in the range between ceramic and UHMWPE. Although ceramic appeared to be a viable alternative to cobalt–chromium–molybdenum alloy, CFR-PEEK seems to be the most promising alternative material.