Resonant Absorption of Transverse Oscillations and Associated Heating in a Solar Prominence. II- Numerical aspects

Transverse magnetohydrodynamic (MHD) waves are ubiquitous in the solar atmosphere and may be responsible for generating the Sun's million-degree outer atmosphere. However, direct evidence of the dissipation process and heating from these waves remains elusive. Through advanced numerical simulations combined with appropriate forward modeling of a prominence flux tube, we provide the observational signatures of transverse MHD waves in prominence plasmas. We show that these signatures are characterized by thread-like substructure, strong transverse dynamical coherence, an out-of-phase difference between plane-of-the-sky motions and LOS velocities, and enhanced line broadening and heating around most of the flux tube. A complex combination between resonant absorption and Kelvin-Helmholtz instabilities (KHI) takes place in which the KHI extracts the energy from the resonant layer and dissipates it through vortices and current sheets, which rapidly degenerate into turbulence. An inward enlargement of the boundary is produced in which the turbulent flows conserve the characteristic dynamics from the resonance, therefore guaranteeing detectability of the resonance imprints. We show that the features described in the accompanying paper (Okamoto et al. 2015) through coordinated Hinode and IRIS observations match well the numerical results.Comment: This is part 2 of a series of 2 papers. Part 1 corresponds to Okamoto et al. (2015, accepted). 36 Pages (single column), 10 figures. Accepted for publication in The Astrophysical Journa

A Survey on IRIS Recognition System: Comparative Study

Because of an increasing emphasis on security, Iris recognition has gained a great attention in both research and practical applications over the past decade. The demand for iris recognition in the various fields of access control reducing fraudulent transactions in electronic commences, security at border areas etc is increasing day by day due to its high accuracy, reliability and uniqueness. A review of various segmentation approaches used in iris recognition is done in this paper. The performance of the iris recognition systems depends heavily on segmentation and normalization techniques

Resonant absorption of transverse oscillations and associated heating in a solar prominence. II. Numerical aspects

Transverse magnetohydrodynamic (MHD) waves are ubiquitous in the solar atmosphere and may be responsible for generating the Sun's million-degree outer atmosphere. However, direct evidence of the dissipation process and heating from these waves remains elusive. Through advanced numerical simulations combined with appropriate forward modeling of a prominence flux tube, we provide the observational signatures of transverse MHD waves in prominence plasmas. We show that these signatures are characterized by a thread-like substructure, strong transverse dynamical coherence, an out-of-phase difference between plane-of-the-sky motions and line-of-sight velocities, and enhanced line broadening and heating around most of the flux tube. A complex combination between resonant absorption and Kelvin–Helmholtz instabilities (KHIs) takes place in which the KHI extracts the energy from the resonant layer and dissipates it through vortices and current sheets, which rapidly degenerate into turbulence. An inward enlargement of the boundary is produced in which the turbulent flows conserve the characteristic dynamics from the resonance, therefore guaranteeing detectability of the resonance imprints. We show that the features described in the accompanying paper through coordinated Hinode and Interface Region Imaging Spectrograph observations match the numerical results well.Publisher PDFPeer reviewe

An easy iris center detection method for eye gaze tracking system

Iris center detection accuracy has great impact on eye gaze tracking system performance. This paper proposes an easy and efficient iris center detection method based on modeling the geometric relationship between the detected rough iris center and the two corners of the eye. The method fully considers four states of iris within the eye region, i.e. center, left, right, and upper. The proposed active edge detection algorithm is utilized to extract iris edge points for ellipse fitting. In addition, this paper also presents a predicted edge point algorithm to solve the decrease in ellipse fitting accuracy, when part of the iris becomes hidden from rolling into a nasal or temporal eye corner. The evaluated result of the method on our eye database shows the global average accuracy of 94.3%. Compared with existing methods, our method achieves the highest iris center detection accuracy. Additionally, in order to test the performance of the proposed method in gaze tracking, this paper presents the results of gaze estimation achieved by our eye gaze tracking system

Characterization of a grazing incidence spectra-imager laboratory model for solar observation

This thesis describes the work made on the optical characterization of a laboratory demo-model stigmatic grazing-incidence spectra-imager for solar investigation. This instrument, stigmatic in an extended field of view, can acquire spectral features between 4 nm and 20 nm, even preserving spatial information. The system consists of a double telescope in the KirkPatrick-Baez configuration and a grazing incidence spectrograp

Infra-red astronomical photometry : one to twenty microns

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Digest of celestial X-ray missions and experiments

Information on instruments, the platforms that carried them, and the data they gathered is presented. Instrument selection was confined to detectors operating in the 0.20 to 300 keV range. Included are brief descriptions of the spacecraft, experiment packages and missions. Cross-referenced indexes are provided for types of instruments, energy ranges, time spans covered, positional catalogs and observational catalogs. Data sets from these experiments (NSSDC) are described

Machine learning in solar physics

The application of machine learning in solar physics has the potential to greatly enhance our understanding of the complex processes that take place in the atmosphere of the Sun. By using techniques such as deep learning, we are now in the position to analyze large amounts of data from solar observations and identify patterns and trends that may not have been apparent using traditional methods. This can help us improve our understanding of explosive events like solar flares, which can have a strong effect on the Earth environment. Predicting hazardous events on Earth becomes crucial for our technological society. Machine learning can also improve our understanding of the inner workings of the sun itself by allowing us to go deeper into the data and to propose more complex models to explain them. Additionally, the use of machine learning can help to automate the analysis of solar data, reducing the need for manual labor and increasing the efficiency of research in this field.Comment: 100 pages, 13 figures, 286 references, accepted for publication as a Living Review in Solar Physics (LRSP