99,750 research outputs found

    The north-south asymmetry of soft X-ray flare index during solar cycles 21, 22 and 23

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    In this paper the N-S asymmetry of the soft X-ray flare index during the solar cycles 21, 22 and 23 has been analyzed. The results show the existence of a real N-S asymmetry which is strengthened during solar minimum. The slope of the regression lines fitted to the daily values of asymmetry time series has been found to be negative in all the three cycles. The yearly asymmetry curve can be fitted by a sinusoidal function with a period of eleven years. The power spectral analysis of daily asymmetry time series reveals the significant periods of around 28.26 days, 550.73 days and 3.72 years.Comment: 15 pages; 8 figures; Published in Solar Physic

    Population I Cepheids and star formation history of the Large Magellanic Cloud

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    In this paper we study the Cepheids distribution in the Large Magellanic Cloud (LMC) as a function of their ages using data from the OGLE III photometric catalogue. To determine age of the Pop I Cepheids, we derived a period-age (PA) relationship using the Cepheids found in the LMC star clusters. We find two peaks in the period distribution at logP =0.49+/-0.01 and logP =0.28+/-0.01 days which correspond to fundamental and first overtone pulsation modes, respectively. Ages of the Cepheids are used to understand star formation scenario in the LMC in last 30-600 Myr. The age distribution of the LMC Cepheids is found to have a peak at log(Age)=8.2+/-0.1. This suggests that major star formation event took place at about 125-200 Myr ago which may have been triggered by a close encounter between the SMC and the LMC. Cepheids are found to be asymmetrically distributed throughout the LMC and many of them lie in clumpy structures along the bar. The frequency distribution of Cepheids suggests that most of the clumps are located to the eastern side of the LMC optical center.Comment: 2014, New Astronomy, 28, 2

    Working women and caste in India: A study of social disadvantage using feature attribution

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    Women belonging to the socially disadvantaged caste-groups in India have historically been engaged in labour-intensive, blue-collar work. We study whether there has been any change in the ability to predict a woman's work-status and work-type based on her caste by interpreting machine learning models using feature attribution. We find that caste is now a less important determinant of work for the younger generation of women compared to the older generation. Moreover, younger women from disadvantaged castes are now more likely to be working in white-collar jobs.Comment: Presented at the ICLR AI for Social Good Workshop 2019; Updated with Addendum (Jan 2020

    Asteroseismology of Pulsating Stars

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    The success of helioseismology is due to its capability of measuring p-mode oscillations in the Sun. This allows us to extract informations on the internal structure and rotation of the Sun from the surface to the core. Similarly, asteroseismology is the study of the internal structure of the stars as derived from stellar oscillations. In this review we highlight the progress in the observational asteroseismology, including some basic theoretical aspects. In particular, we discuss our contributions to asteroseismology through the study of chemically peculiar stars under the "Nainital-Cape Survey" project being conducted at ARIES, Nainital since 1999. This survey aims to detect new rapidly-pulsating Ap (roAp) stars in the northern hemisphere. We also discuss the contribution of ARIES towards the asteroseismic study of the compact pulsating variables. We comment on the future prospects of our project in the light of the new optical 3.6-m telescope to be install at Devasthal (ARIES). Finally, we present a preliminary optical design of the high-speed imaging photometers for this telescope.Comment: published in Journal of Astrophysics & Astronomy. arXiv admin note: text overlap with arXiv:1405.3145, arXiv:1212.5084, arXiv:1205.6407, arXiv:1212.2384, arXiv:1109.3455, arXiv:1104.5191, arXiv:1102.1884, arXiv:1310.0696, arXiv:1310.2266 by other author

    Basic Parameters of Open Star Clusters DOLIDZE 14 and NGC 110 in Infrared bands

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    The basic physical parameters of a poorly studied open cluster NGC 110 and an unstudied open cluster DOLIDZE 14 are estimated in the present study using the archival PPMXL and WISE catalogues. The radius of both the clusters are estimated by fitting the modified King's empirical model on their stellar density profiles. The other basic parameters of the clusters such as distance, reddening, and age are obtained by visual fitting of the Marigo's solar metallicity isochrone on their IR colour-magnitude diagrams (CMDs). The mean-proper motion of the clusters are estimated through the individual proper motion of probable members identified through the dynamical and statistical methods. The archival catalogues (JHKW1W2) are constructed for both the clusters by compiling the extracted data from the PPMXL and WISE catalogues. The various colour-excesses, such as E(J-H), E(H-K) and E(W1-W2), are estimated using the best fit theoretical isochrone on the (J-H)-H, (H-K)-H and (W1-W2)-H CMDs, respectively. The ratios of various infrared colours of the clusters are obtained through their two-colour diagrams. We also identify the most probable members in these clusters by estimating spatial, kinematic and spatio-kinematic probabilities of stars within the cluster. A correlation between the E(H-K) and E(W1-W2) is also established.Comment: 23 pages, 7figure

    Population I Cepheids and understanding star formation history of the Small Magellanic Cloud

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    In this paper, we study the age and spatial distributions of Cepheids in the Small Magellanic Cloud (SMC) as a function of their ages using the data from the OGLE III photometric catalogue. A period-age (PA) relation derived for the Classical Cepheids in the Large Magellanic Cloud (LMC) has been used to find the ages of Cepheids. The age distribution of the SMC Classical Cepheids is found to have a peak at log(Age) = 8.40+/-0.10 which suggests that a major star formation event might have occurred in the SMC at about 250+/-50 Myrs ago. It is believed that this star forming burst had been triggered by close interactions of the SMC with the LMC and/or the Milky Way (MW). A comparison of the observed spatial distributions of the Cepheids and open star clusters has also been carried out to study the star formation scenario in the SMC.Comment: 10 pages, 7 figures, accepted for publication in Research in Astronomy and Astrophysic

    Complex stellar system ESO65SC03: Open cluster or remnant?

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    We present a complete spatial and dynamical study of the poorly populated stellar system ESO65SC03. The radial distribution of the system gives a core and cluster radii of 1.10+/-0.63 arcmin and 5.36+/-0.24 arcmin, respectively. The surface number density profile (SNDP) does not show any clear enhancement of the surface stellar number density between the stars of the system and the field regions. We derive the optimum isochrone solution for a particular grid size in the colour-magnitude diagram (CMD) using the statistical cleaning procedure. Using the statistically cleaned CMDs, we find the distance modulus, (m-M)_0, and reddening, E({B-V}), of the system to be 11.8+/-0.2 mag and 0.45 mag, respectively. The mean proper motion of this system is -5.37+/-0.81 mas/yr and 0.31+/-0.40 in RA and DEC directions, respectively. The mean proper motion of this system is found to be almost similar to the field region. The mass function for the brighter stars is found to be too high for the system to be an open cluster. These combined results place constraints on whether stellar system ESO65SC03 is a possible open star cluster remnant (POCR) or an Asterism. Our understanding is that the ESO65SC03 is in a stage of POCR by loosing their main sequence stars in the dynamic evolution processes.Comment: 10 pages, 9 figures, accepted for publication in PAS

    Photometric studies of two W UMa type variables in the field of distant open cluster NGC6866

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    We present photometric analysis of the two W UMa type binaries identified in the field of distant open star cluster NGC6866. Although these systems, namely ID487 and ID494, were reported in the Joshi et al. (2012), but a detailed study of these stars has not been carried out earlier. The orbital periods of these stars are found to be 0.415110+/-0.000001 day and 0.366709+/-0.000004 day, respectively. Based on the photometric and infrared colours, we find their respective spectral types as K0 and K3. The photometric light variations of both the stars show O'Connell effect which could be explained by employing a dark spot on the secondary components. The V and I bands light curves are analyzed using the Wilson-Devinney (WD) code and relations given by Gazeas (2009) which yield radii and mass of the primary and secondary components of the star ID487 as R1 = 1.24+/-0.01 Rsun, R2 = 1.11+/-0.02 Rsun, and M1 = 1.24+/-0.02 Msun, M2 = 0.96+/-0.05 Msun, and for the star ID494 as R1 = 1.22+/-0.02 Rsun, R2 = 0.81+/-0.01 Rsun, and M1 = 1.20+/-0.06 Msun, M2 = 0.47+/-0.01 Msun.Comment: 12 pages, 7 figures, 2016, RAA, 16, 1

    DeepIrisNet2: Learning Deep-IrisCodes from Scratch for Segmentation-Robust Visible Wavelength and Near Infrared Iris Recognition

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    We first, introduce a deep learning based framework named as DeepIrisNet2 for visible spectrum and NIR Iris representation. The framework can work without classical iris normalization step or very accurate iris segmentation; allowing to work under non-ideal situation. The framework contains spatial transformer layers to handle deformation and supervision branches after certain intermediate layers to mitigate overfitting. In addition, we present a dual CNN iris segmentation pipeline comprising of a iris/pupil bounding boxes detection network and a semantic pixel-wise segmentation network. Furthermore, to get compact templates, we present a strategy to generate binary iris codes using DeepIrisNet2. Since, no ground truth dataset are available for CNN training for iris segmentation, We build large scale hand labeled datasets and make them public; i) iris, pupil bounding boxes, ii) labeled iris texture. The networks are evaluated on challenging ND-IRIS-0405, UBIRIS.v2, MICHE-I, and CASIA v4 Interval datasets. Proposed approach significantly improves the state-of-the-art and achieve outstanding performance surpassing all previous methods.Comment: 10 pages, 4 Figure

    Using Deep Neural Networks to Translate Multi-lingual Threat Intelligence

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    The multilingual nature of the Internet increases complications in the cybersecurity community's ongoing efforts to strategically mine threat intelligence from OSINT data on the web. OSINT sources such as social media, blogs, and dark web vulnerability markets exist in diverse languages and hinder security analysts, who are unable to draw conclusions from intelligence in languages they don't understand. Although third party translation engines are growing stronger, they are unsuited for private security environments. First, sensitive intelligence is not a permitted input to third party engines due to privacy and confidentiality policies. In addition, third party engines produce generalized translations that tend to lack exclusive cybersecurity terminology. In this paper, we address these issues and describe our system that enables threat intelligence understanding across unfamiliar languages. We create a neural network based system that takes in cybersecurity data in a different language and outputs the respective English translation. The English translation can then be understood by an analyst, and can also serve as input to an AI based cyber-defense system that can take mitigative action. As a proof of concept, we have created a pipeline which takes Russian threats and generates its corresponding English, RDF, and vectorized representations. Our network optimizes translations on specifically, cybersecurity data
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