Spherical mhd shock waves under the action of monochromatic radiation

Self-similar MHD shock waves have been studied under the action of monochromatic radiation into a non-uniform stellar atmosphere with a constant intensity on unit area. It has been assumed that the radiation flux moves through the gas. Variation of flow variables have heen shown in tables for two different cases.     

Propagation of cylindrical shock waves under the action of monochromatic radiation

A model of cylindrical shock waves is investigated under the action of monochromatic radiation into non-uniform stellar interiors with a constant intensity on a unit area. We have assumed that the radiation flux moves through the gas.     

Similarity solution for the propagation of shock waves with varying energy in non-uniform medium

A model of self-similar propagation of shock waves driven by a flare energy release in a non-uniform atmosphere has been considered. The total energy content of the model is assumed to be increased with time within the inner expanding surface and shock front. Finally the variation of velocity, pressure, density, and energy of the model have been discussed. The gas is assumed to be grey and opaque.     

The equilibrium state of shock-heated rotating atmosphere under the force of gravitation

Equations are developed to describe the flow of a rotating atmosphere under force of gravitation heated by an arbitrary distribution of cylindrical shock waves. Solutions are obtained for the outer solar atmosphere with a steady mass motion in which the heat supplied by shock wave is balanced by the convective heat loss due to this motion. It is found that, for very large range of shock strength and frequencies, the temperature profile is similar to that predicted by the constant shock-strength hypothesis. This hypothesis is used as the basis of a model of the outer solar atmosphere starting near the solar atmosphere.     

Probabilistic rainfall thresholds in Chibo,India: estimation and validation using monitoring system

The Himalayan region has been severely affected by landslides especially during the monsoons. In particular, Kalimpong region in Darjeeling Himalayas has recorded several landslides and has caused significant loss of life, property and agricultural land. The study region, Chibo has experienced several landslides in the past which were mainly debris and earth slide. Globally, several types of rainfall thresholds have been used to determine rainfall-induced landslide incidents. In this paper, probabilistic thresholds have been defined as it would provide a better understanding compared to deterministic thresholds which provide binary results, i.e., either landslide or no landslide for a particular rainfall event. Not much research has been carried out towards validation of rainfall thresholds using an effective and robust monitoring system. The thresholds are then validated using a reliable system utilizing Microelectromechanical Systems(MEMS) tilt sensor and volumetric water content sensor installed in the region. The system measures the tilt of the instrument which is installed at shallow depths and is ideal for an early warning system for shallow landslides. The change in observed tilt angles due to rainfall would give an understanding of the applicability of the probabilistic model. The probabilities determined using Bayes' theorem have been calculated using the rainfall parameters and landslide data in 2010-2016. The rainfall values were collected from an automatic rain gauge setup near the Chibo region. The probabilities were validated using the MEMS based monitoring system setup in Chibo for the monsoon season of 2017. This is the first attempt to determine probabilities and validate it with a robust and effective monitoring system in Darjeeling Himalayas. This study would help in developing an early warning system for regions where the installation of monitoring systems may not be feasible.     

Impact of Three-Parameter Weibull Models in Probabilistic Assessment of Earthquake Hazards

This paper investigates the suitability of a three-parameter (scale, shape, and location) Weibull distribution in probabilistic assessment of earthquake hazards. The performance is also compared with two other popular models from same Weibull family, namely the two-parameter Weibull model and the inverse Weibull model. A complete and homogeneous earthquake catalog (Yadav et al. in Pure Appl Geophys 167:1331–1342, 2010) of 20 events (M ≥ 7.0), spanning the period 1846 to 1995 from north–east India and its surrounding region (20°–32°N and 87°–100°E), is used to perform this study. The model parameters are initially estimated from graphical plots and later confirmed from statistical estimations such as maximum likelihood estimation (MLE) and method of moments (MoM). The asymptotic variance–covariance matrix for the MLE estimated parameters is further calculated on the basis of the Fisher information matrix (FIM). The model suitability is appraised using different statistical goodness-of-fit tests. For the study area, the estimated conditional probability for an earthquake within a decade comes out to be very high (≥0.90) for an elapsed time of 18 years (i.e., 2013). The study also reveals that the use of location parameter provides more flexibility to the three-parameter Weibull model in comparison to the two-parameter Weibull model. Therefore, it is suggested that three-parameter Weibull model has high importance in empirical modeling of earthquake recurrence and seismic hazard assessment.     

A new approach for finding an appropriate combination of texture parameters for classification

This article is an attempt to suggest a new approach for eliminating the lengthy process of selecting various parameters for extracting texture features and to quantify the relative importance of the parameters affecting textural classification. A multivariate data analysis technique called ‘conjoint analysis’ has been used in the study to analyse the relative importance of these parameters. Results indicate that the choice of texture feature and window size have higher relative importance in the classification process than quantization level or the choice of image band for extracting texture feature. Results of the classification of an Indian urban environment using spatial property (texture) have also been reported. It was observed that the classification incorporating texture features using grey level co-occurrence matrix and wavelet-based approach improves the overall accuracy in a statistically significant manner in comparison to pure spectral classification.     

Self-similar flow behind a spherical shock with varying strength in an inhomogeneous medium

The model of self-similar shock wave produced on account of an instantaneous release of energy in a non-uniform gaseous mass, has been discussed with the equilibrium conditions. The disturbance are headed by a shock of variable strength. This model is of considerable physical interest in sonic booms, phenomena associated with laser production of plasma, high altitude nuclear detonation, supernova explosion and sudden expansion of corona into the interplanetary space.     

Comparative study on projected clustering methods for hyperspectral imagery classification

In this study, projected clustering is introduced to hyperspectral imagery for unsupervised classification. The main advantage of projected clustering lies in its ability to simultaneously perform feature selection and clustering. This framework also allows selection of different sets of dimensions (features/bands) for different clusters. This framework provides an effective way to address the issues associated with the high dimensionality of the data. Experiments are conducted on both synthetic and real hyperspectral imagery. For this purpose, projected clustering algorithms are implemented and compared with k-means and k-means preceded by principal component analysis. Preliminary analyses of studied algorithms on synthetic hyperspectral imagery demonstrate good results. For real hyperspectral imagery, only ORCLUS is able to produce acceptable results as compared to other unsupervised methods. The main concern lies with identification of right parameter settings. More experiments are required in this direction.