The Optical Gravitational Lensing Experiment (OGLE) project provides a rich data set of stellar objects with multiple features such as their positions, magnitudes, temporal, and other photometric parameters. This paper attempts to utilize sophisticated computational and statistical techniques to investigate the OGLE data set, which discloses intrinsic dimensional structure in feature space and dimension reduction for better interpretability. Preprocessing of the data set was initially done to resolve inconsistencies and missing values to present a strong and firm basis for analysis. The data set is normalized, and Principal Component Analysis (PCA) is employed for dimension reduction to retain only the most significant features. Not only does the reduction make the data set interpretable and easy to handle, but it also highlights the principal components responsible for the largest variance in the data. In order to study the intrinsic structure of the data set in greater depth, we calculate the distance matrix of the principal components and employ it to estimate the correlation dimension D-2, a measure of intrinsic dimensionality. This study examines the scaling behavior of the correlation function with different radii and, hence, we can understand the intrinsic structure of the observational parameter space. Our results indicate D-2 = 1.67 +/- 0.18 for the normalized feature data, implying strong correlations among the observables.

Across the world, the seasonal disease influenza is a respiratory illness that impacts all age groups in many ways. Its symptoms are fever, chills, aches, pains, headaches, fatigue, cough, and weakness. Seasonal influenza can cause mild to severe illness and lead to death at times. The task of early detection of influenza is an important research area these days. Various studies show that machine learning techniques have attracted many researchers' attention to the early detection of influenza disease. In this paper, early detection of Influenza disease among all age groups is done using various machine learning techniques. Influenza Research Database and the Human Surveillance Records data sets are used. Data analysis is undertaken, and ensemble-based stacked algorithms are implemented on the whole data set. The performance of different models has been evaluated using different performance metrics. Overall, the study proposes efficient machine learning models that can be implemented to provide a cheaper and quicker diagnostic tool for detecting influenza.

ABSTRACT We present an improved method for the determination of membership of an open cluster using ensemble-based unsupervised machine learning techniques. The working principle of this method relies on two stages: (i) choosing a suitable range of three astrometric parameters (π, μαcos δ, μδ) using k-nearest neighbour (kNN) algorithm on the data downloaded for the cluster within a smaller search radius; (ii) application of two component Gaussian mixture modelling (GMM) on the resulting one dimensional Gaussian distribution of Mahalanobis distance (MD) of stars using the range of parameters obtained from the earlier step, but with the data downloaded within a bigger search radius. MD is calculated from the mean of each of the parameters in three dimensions. Thus the use of MD reduces the input of the GMM from the 3D parameter space into a 1D parameter space for the cluster membership determination. The method has been tested on a few clusters including those which have overlaps in some/all the parameters using the data obtained from the Gaia DR3 data base. It is found that the approach can easily separate the cluster members from the field stars. The clean colour-magnitude diagrams and similar direction of proper motions of the member stars obtained for the clusters shows that this method is very efficient and robust in segregating the cluster members from the field stars.

With the increasing use of Open Source Software (OSS) in high speed networking, parallel processing and distributed computing, OSS has emerged as mainstream in the last decade and is now being broadly accepted even by the traditional proprietary software development companies. The major advantages of OSS over traditional software development are less development cost, availability of source code, quality and security. Software reliability—an important attribute of software quality, is defined as the probability that a software will operate free of failures or breakdown for a specified time under specified conditions (IEEE Std. 1633-2016). Investigation of Software reliability with the help of software reliability models (SRM) undertakes the estimation and prediction of the failure phenomenon of a software. In this paper we have investigated whether Non-homogeneous Poisson process (NHPP) based software reliability models fit in the big data open source software fault/bug data. We have extracted real and latest bug/fault data of Hadoop and Spark–open source big data applications, from bug tracking/management tool Jira. For this purpose, we have also compared these models on different goodness-of-fit and prediction criteria based on collected failure data to ascertain whether a best fitted model can also be a best predictor. It is found that the best model fitting the failure data is not a best predictor model.

ABSTRACT This is the second of a series related to the study of geometry of the Magellanic Clouds based on multiwavelength photometry of classical Cepheids. In this paper we determine the geometrical and viewing angle parameters of the Small Magellanic Cloud (SMC) using the Leavitt law for classical Cepheids with/without a break in the law at a certain period as reported in the literature. The study utilizes photometric data for more than 3400 common classical Cepheids (Fundamental (FU) and First overtone (FO)) in optical (V, I), near-infrared (Y, J, Ks) and mid-infrared ([3.6] and [4.5] μm) photometric bands. We obtain statistical reddening and distance modulus free from the effect of reddening to each of the individual Cepheids with respect to the mean distance modulus and reddening of the SMC. The reddening maps of the SMC obtained from the analyses with/without breaks in the Leavitt law show good agreement with each other as well as with other maps available in the literature. The Cartesian coordinates of individual stars with respect to the galaxy plane are obtained using the information of equatorial coordinates (α, δ) as well as extinction-free distance measurements. Modelling the observed 3D distribution of the Cepheids as a triaxial ellipsoid, we obtain the geometrical and viewing angle parameters of the SMC. The weighted average yields the following values of parameters for the SMC: the geometrical axes ratios of 1.000 ± 0.001: 1.544 ± 0.002: 9.742 ± 0.030 and the viewing angle parameters having inclination angle i = 3${^{\circ}_{.}}$465 ± 0${^{\circ}_{.}}$030 with respect to the longest axis from the line of sight and position angle of line of nodes (major axis) θlon = 63${^{\circ}_{.}}$086 ± 0${^{\circ}_{.}}$117.

We determine the geometrical and viewing angle parameters of the Large Magellanic Cloud (LMC) using the Leavitt law based on a sample of more than 3500 common classical Cepheids (FU and FO) in optical (V, I), near-infrared (JHK(s)), and mid-infrared ([3.6] mu m and [4.5] mu m) photometric bands. Statistical reddening and distance modulus free from the effect of reddening to each of the individual Cepheids are obtained using the simultaneous multiband fit to the apparent distance moduli from the analysis of the resulting Leavitt laws in these seven photometric bands. A reddening map of the LMC obtained from the analysis shows good agreement with the other maps available in the literature. Extinction-free distance measurements along with the information of the equatorial coordinates (alpha, delta) for individual stars are used to obtain the corresponding Cartesian coordinates with respect to the plane of the sky. By fitting a plane solution of the form z = f(x, y) to the observed three-dimensional distribution, the following viewing angle parameters of the LMC are obtained: inclination angle i = 25 degrees 110 +/- 0 degrees 365, and position angle of line of nodes theta(lon) = 154 degrees.02 +/- 1 degrees.378. On the other hand, modelling the observed three-dimensional distribution of the Cepheids as a triaxial ellipsoid, the following values of the geometrical axes ratios of the LMC are obtained: 1.000 +/- 0.003: 1.151 +/- 0.003: 1.890 +/- 0.014 with the viewing angle parameters: inclination angle of i = 11 degrees. 920 +/- 0 degrees. 315 with respect to the longest axis from the line of sight and position angle of line of nodes.lon = 128 degrees. 871 +/- 0 degrees. 569. The position angles are measured eastwards from north.

The significance and robustness of Free and Open Source Software (FOSS) are now well known at stages of development as well as deployment. It’s natural to assume that the products of FOSS to be deployed as a preference over the commercially available propriety software. However, proprietary software not only exists but is also thriving. The present paper looks into the aspect of adoption of FOSS, with special emphasis to India. The two natural arena for adoptionGovernance and Academia are chosen for study. The policy initiatives, frameworks and challenges in the implementation of FOSS in these two areas are discussed, while giving instances of its successful adoption. The study also discusses in brief the adoption of FOSS in business enterprise, where its adoption is dynamic and accelerated. Several challenges in adoption of FOSS over propriety software are also pointed out.

We present a detailed V-band photometric light curve modeling of 30 eclipsing binaries using the data from Pietrukowicz et al. (2009) collected with the European Southern Observatory Very Large Telescope (ESO VLT) of diameter 8-m. The light curve of these 30 eclipsing binaries were selected out of 148 of them available in the database on the basis of complete phase coverage, regular and smooth phased light curve shapes. Eclipsing binaries play pivotal role in the direct measurement of astronomical distances more accurately simply from their geometry of light curves. The accurate value of Hubble constant (H0) which measures the rate of expansion of the Universe heavily relies on extragalactic distance scale measurements. Classification of the selected binary stars in the sample were done, preliminarily on the basis of Fourier parameters in the a2-a4 plane and final classification was obtained from the Roche lobe geometry. Out of these 30 eclipsing binaries, only one was found to be detached binary system while the rest 29 of them belong to the contact binary systems. These contact binaries were further classified into the A-type and W-type based on their mass ratios. Since spectroscopic mass ratio measurements were not available for any of these binary stars, we determined the mass ratios through photometric light curve modeling with the aid of Wilson-Devinney code as implemented in PHOEBE. Various geometrical parameters and physical parameters of astrophysical importance viz., mass, radius and luminosity were obtained from the light curves of the selected stars.

We present a study of three-dimensional structure of the Small Magellanic Cloud (SMC). The V- and I-band light curves of the fundamental mode RR Lyrae (RRab) stars obtained by the Optical Gravitational Lensing Experiment-III project were utilized in order to comprehend the SMC structure. The [Fe/H]-P-phi(31) relation of Jurcsik & Kovacs is exploited to obtain the metallicities. From the three-dimensional RRab distance distributions, north-east arm and main body of the galaxy are identified. Combining metallicities with spatial distribution of these tracers, no radial metallicity gradient in the SMC has been detected. Dividing the entire sample into three parts: north-eastern, central and south-western, we find that the central part has a significantly larger line of sight depth as compared to rest of the parts, indicating that the SMC may have a bulge. Results obtained from the I-band data seem to be reliable and were further substantiated using the Smolec relation. Distribution of SMC RRab stars was modelled as a triaxial ellipsoid. Errors in structural parameters of the SMC ellipsoid were obtained from Monte Carlo simulations. We estimated the axes ratios of the galaxy as 1.00 +/- 0.000: 1.310 +/- 0.029: 8.269 +/- 0.934, the inclination of the longest axis with line of sight i = 2 degrees.265 +/- 0 degrees.784 and the position angle of the line of nodes theta(lon) = 74 degrees.307 +/- 0 degrees.509 from the variance weighted I-band determinations.

The paper investigates the role of relative motion between the fluid components of a plasma model, which is simulated by concatenation of two anisotropic magnetohydrodynamic (MHD) fluids, on the propagation of low-frequency waves and instabilities. The gyrotropic pressure of both the MHD components is given by generalized polytropic laws that allow the system to reduce to a variety of states. The linearized analysis is carried out and dispersion relation is derived using the normal mode technique. The dispersion relation, which gives numerous earlier results as special cases, is discussed both analytically as well as numerically for parameters appropriate for the space plasma. It is found that the relative motion between the two components, besides modifying the condition for fire-hose instability, causes the concatenated system to exhibit different kinds of relative ordering of the magnitudes of phase speeds of the various MHD modes in the directions parallel and antiparallel to the magnetic field. The relative motion between the components also influences the phase relationship between density and magnetic field fluctuations for the various compressive modes in the background ambient plasma. (C) 2010 American Institute of Physics. [doi:10.1063/1.3483116]

The paper investigates the role of suprathermal particles (He++) in the propagation of low‐frequency waves in average magnetosheath plasma by utilizing a model which is a concatenation of two magnetohydrodynamic (MHD) fluids. The suprathermal component is described by a relativistic, collisionless anisotropic fluid while the background plasma is assumed to be a nonrelativistic, anisotropic MHD fluid. The pressure components of both the fluids are described by heuristic double‐polytropic laws which are fairly well supported by observational data. The linearized analysis is carried out and dispersion relation is derived using normal mode technique. It is found that inclusion of the suprathermal component causes the excitation of an additional mode of propagation, besides reducing the phase speeds of slow, fast, and Alfvén modes. The additional mode, which can be characterized as a hybrid of the suprathermal and the fast modes in the direction perpendicular to the magnetic field, is the only mode which transports energy in the direction perpendicular to the magnetic field. Using appropriate polytropic indices obtained from AMPTE/IRM measurements in the magnetosheath leads to a new ordering of phase speeds and density‐magnetic field correlation of the fast mode. The new suprathermal mode shows positive density‐magnetic field correlation.

The paper discusses the propagation of waves and instabilities in a plasma model which consists of the concatenation of two magnetohydrodynamic (MHD) fluids, one of which is relativistic and has anisotropic pressure components given by double adiabatic equations derived by Gedalin [Phys. Rev. E 47, 4354 (1993)] while the other one has pressure components given by generalized polytropic laws. The polytropic laws, though empirical, are useful in that the appropriate values of the polytropic indices enable one to apply the treatment to a variety of situations ranging from an anisotropic ultrarelativistic plasma to an ordinary nonrelativistic isotropic plasma. A linearized analysis is carried out and the dispersion relation is derived using the normal mode technique. The dispersion relation, which gives numerous earlier results in special cases, is discussed both analytically as well as numerically for parameters which simulate cosmic rays and the background interstellar plasma as two MHD components. An additional mode of propagation that arises due to the concatenation of the MHD components is the only mode which transports energy in the direction perpendicular to the ambient magnetic field. Situations where this model supports instabilities are also discussed.

Linear relativistic anisotropic magnetohydrodynamic waves are investigated for an Imperfect fluid. Consideration is carried out for the plasma with finite bulk viscosity. Conditions for growth and decay of these waves are obtained in special cases of isotropy and Chew-Goldberger-Low (CGL) state.