Mathematical analysis of a chaotic model in relevance to monsoon ISO

Mathematical analysis of a predominantly bimodal chaotic attractor, Lu system, was carried out to investigate a possible application of the model as a prototype of monsoon intra-seasonal oscillation (ISO). Bifurcation structures of the system are explored as the system parameter c and the forcing parameter F are varied. Stability criteria of equilibrium points of the forced Lu system are also explored in detail. A sensitivity study is carried out, by changing forcing parameter F, to explore relationships between some of the derived variables of the model and, based on such relationships, an empirical rule is used for extended range prediction. Analogous variables are also derived from the ISO data and prediction results are compared. Application of the prediction rule of regime transition to the observed ISO and chaotic model data is purely based on the bimodal characteristics of ISO and neglects some of the intricate mechanisms therein. We have found that a forced Lu system can be a good prototype in the prediction of peak anomaly of the monsoon ISO when growth rates around a threshold value are taken as predictors.     

Hill slope stability analysis using two and three dimensions analysis: A comparative study

Slope instability is very common phenomenon, especially in tectonically active hills of the lesser Himalaya. The deformed, weathered and fragile rocks of the lesser Himalaya are often vulnerable under natural or anthropogenic influences. There were several cases of slope failure along highway sections in Uttarakhand Himalaya. The study was carried out along a highway section of NH-109. The factor of safety (FoS) is commonly most acceptable parameter that analyses the health of slopes. The two dimensional (2D) numerical analysis techniques are commonly used to obtain the FoS. It is observed that many times FoS obtained from 2D analysis techniques do not qualify the actual conditions and are usually lower in value as compared to ground conditions. This, in turn, increases the cost of remedial measures used for protection of slopes. This paper presents a comparative study of 2D and 3D numerical analysis based on the finite difference method (FDM) using fast Langrangian analysis of continua (FLAC) codes. The study indicates that there is no appreciable difference between FoS values obtained from 2D and 3D analysis based on the selected slope conditions. The difference ranges from 0.02 to 0.07 for analysed cases in uniform rock mass. The study also exhibits some of the important analytical observations and effects of variables on resultant FoS.     

Phodong (Sikkim) earthquake of 14 February 2006 and its aftershocks—Coulomb stress analysis

The 14 February 2006 Phodong (Sikkim) earthquake of moderate magnitude (Mw 5.3) triggered several aftershocks that were recorded by a local seismic network. The thrust earthquake is part of the continuing earthquake activity in the Himalayan seismic belt region that occurs on the detachment or ramp under the Higher Himalaya. The aftershocks of the earthquake occurred in increased stress regions caused by the earthquake rupture. Triggering of aftershocks by such a moderate magnitude earthquake implies that the faults in the Himalaya are critically stressed and even a small change of stress, about 0.001–0.002 MPa, can trigger earthquakes on such faults.     

Scanning sky monitor (SSM) onboard AstroSat

Scanning Sky Monitor (SSM) onboard AstroSat is an Xray sky monitor in the soft X-ray band designed with a large field of view to detect and locate transient X-ray sources and alert the astronomical community about interesting phenomena in the X-ray sky. SSM comprises position sensitive proportional counters with 1D coded mask for imaging. There are three detector units mounted on a platform capable of rotation which helps covering about 50% of the sky in one full rotation. This paper discusses the elaborate details of the instrument and few immediate results from the instrument after launch.     

A multi-layered backpropagation artificial neural network algorithm for UV spectral classification

In this paper we present an application of an artificial neural network model based on a multi-layered backpropagation algorithm for spectral classification of UV data from the International Ultraviolet Explorer (IUE) low dispersion spectra reference atlas. The model used is similar to that of von Hippel et al. (1994), and is found to reduce the classification error as compared to the recently reported results on the same data set (Gulati et al. 1994b). The improved version of the network is much simpler in structure and the training time is reduced by a factor of almost 20. Such networks will prove very useful in efficient classification of large databases Subject headings: neural networks, stellar spectra, classification