An Artificial Neural Network based approach for estimation of rain intensity from spectral moments of a Doppler Weather Radar

By using a Doppler Weather Radar (DWR) at Shriharikota (13.66°N & 80.23°E), an Artificial Neural Network (ANN) based technique is proposed to improve the accuracy of rain intensity estimation. Three spectral moments of a Doppler spectra are utilized as an input data to an ANN. Rain intensity, as measured by the tipping bucket rain gauges around the DWR station, are considered as a target values for the given inputs. Rain intensity as estimated by the developed ANN model is validated by the rain gauges measurements. With the help of a developed technique, reasonable improvement in the estimation of rain intensity is observed. By using the developed technique, root mean square error and bias are reduced in the range of 34–18% and 17–3% respectively, compared to Z–R approach.     

Spectroscopic Measurement of Coronal Compositions

Although the elemental composition in all parts of the solar photosphere appears to be the same this is clearly not the case with the solar upper atmosphere (SUA). Spectroscopic studies show that in the corona elemental composition along solar equatorial regions is usually different from polar regions; composition in quiet Sun regions is often different from coronal hole and active region compositions and the transition region composition is frequently different from the coronal composition along the same line of sight. In the following two issues are discussed. The first involves abundance ratios between the high-FIP O and Ne and the low-FIP Mg and Fe that are important for meaningful comparisons between photospheric and SUA compositions and the second involves a review of composition and time variability of SUA plasmas at heights of 1.0≤h≤1.5R _⊙.     

Computer modelling of a penetrator thermal sensor

The Philae lander is part of the Rosetta mission to investigate comet 67P/Churyumov-Gerasimenko. It will use a harpoon like device to anchor itself onto the surface. The anchor will perhaps reach depths of 1–2 m. In the anchor is a temperature sensor that will measure the boundary temperature as part of the MUPUS experiment. As the anchor attains thermal equilibrium with the comet ice it may be possible to extract the thermal properties of the surrounding ice, such as the thermal diffusivity, by using the temperature sensor data. The anchor is not an optimal shape for a thermal probe and application of analytical solutions to the heat equation is inappropriate. We prepare a numerical model to fit temperature sensor data and extract the thermal diffusivity. Penetrator probes mechanically compact the material immediately surrounding them as they enter the target. If the thermal properties, composition and dimensions of the penetrator are known, then the thermal properties of this pristine material may be recovered although this will be a challenging measurement. We report on investigations, using a numerical thermal model, to simulate a variety of scenarios that the anchor may encounter and how they will affect the measurement.     

The effect of gravity on surface temperature and net photosynthetic rate of plant leaves.

To clarify the effects of gravity on heat/gas exchange between plant leaves and the ambient air, the leaf temperatures and net photosynthetic rates of plant leaves were evaluated at 0.01, 1.0, 1.5 and 2.0 G of 20 seconds each during a parabolic airplane flight. Thermal images of leaves were captured using infrared thermography at an air temperature of 26 degrees C, a relative humidity of 15% and an irradiance of 260 W m-2. The net photosynthetic rates were determined by using a chamber method with an infrared gas analyzer at an air temperature of 20 degrees C, a relative humidity of 50% and a photosynthetic photon flux of 0.5 mmol m-2 s-1. The mean leaf temperature increased by 1 degree C and the net photosynthetic rate decreased by 13% with decreasing gravity levels from 1.0 to 0.01 G. The leaf temperature decreased by 0.5 degree C and the net photosynthetic rate increased by 7% with increasing gravity levels from 1.0 to 2.0 G. Heat/gas exchanges between leaves and the ambient air were more retarded at lower gravity levels. A restricted free air convection under microgravity conditions in space would limit plant growth by retarding heat and gas exchanges between leaves and the ambient air.     

Pulsations of the R Coronae Borealis stars

The radial pulsations of very luminous, low-mass models (L/M 10⁴, solar units), which are possible representatives of the R CrB stars, have been examined. These pulsations are extremely nonadiabatic. We find that there are in some cases at least one extra (strange) mode which makes interpretation difficult. The blue instability edges are also peculiar, in that there is an abrupt excursion of the blue edge to the blue for L/M sufficiently large. The range of periods of the model encompasses observed periods of the Cepheid-like pulsations of actual R CrB stars.     

Transient processes and stability in an LC chopper

The analysis of the transient and steady-state processes in LC choppers is presented. The method, used previously for the analysis of processes in grid-connected and self-commutated converters, is adjusted for analysis of LC chopper's processes. The difference equations describing these processes, are obtained and solved. The analytical solution of the problem and the conditions of the transient, steady-state, and stability existence in the chopper are found. Theoretical and experimental results are compared and satisfactory agreement is obtained     

The plasma mantle: Composition and other characteristics observed by means of the PROGNOZ-7 satellite

A brief summary of the main results of magnetospheric ion composition measurements in general is first presented. PROGNOZ-7 measurements in the nightside plasma mantle are then described and analyzed. Some of the results are the following: In the nightside mantle not too far from midnight the properties of the mantle are sometimes consistent with the open magnetosphere model. However during most magnetic storm situations O⁺ ions appear in the mantle in large proportions and with high energies. The acceleration process affecting the ions has been found in several cases to give equal amounts of energy to all ions independent of mass. Along the flanks of the magnetosphere the flow of the plasma is often low or absent. The O⁺ content is high (up to 20%) and the energy spectrum of both ions and electrons may be very hot, even up to the level of the ring current plasma in the keV range.The O⁺ content in the plasma mantle is positively correlated with the magnetospheric activity level. The mantle, however, does not appear to be the dominating source for the storm time ring current. Direct acceleration of ionospheric ions onto the closed field lines of the plasma sheet and ring current is most likely the main source. The magnetopause on the nightside and along the flanks of the magnetosphere appears to be a fairly solid boundary for mantle ions of ionospheric origin. This is especially evident during periods with high geomagnetic activity, when the mantle is associated with fairly strong fluxes of O⁺ ions.An interesting observation in most of the mantle passages during geomagnetically disturbed periods is the occurrence of intense, magnetosheath like, regions deep inside the mantle. In some cases these regions with strong antisunward flow and with predominant magnetosheath ion composition was observed in the innermost part of the mantle, i.e. marking a boundary region between the lobe and the mantle. These magnetosheath penetration events are usually associated with strong fluxes of accelerated ionospheric ions in nearby parts of the mantle. Evanescent penetration regions with much reduced flow properties are frequently observed in the flank mantle.     

Application of SVM on satellite images to detect hotspots in Jharia coal field region of India

The present paper deals with the application of Support Vector Machine (SVM) and image analysis techniques on NOAA/AVHRR satellite image to detect hotspots on the Jharia coal field region of India. One of the major advantages of using these satellite data is that the data are free with very good temporal resolution; while, one drawback is that these have low spatial resolution (i.e., approximately 1.1 km at nadir). Therefore, it is important to do research by applying some efficient optimization techniques along with the image analysis techniques to rectify these drawbacks and use satellite images for efficient hotspot detection and monitoring. For this purpose, SVM and multi-threshold techniques are explored for hotspot detection. The multi-threshold algorithm is developed to remove the cloud coverage from the land coverage. This algorithm also highlights the hotspots or fire spots in the suspected regions. SVM has the advantage over multi-thresholding technique that it can learn patterns from the examples and therefore is used to optimize the performance by removing the false points which are highlighted in the threshold technique. Both approaches can be used separately or in combination depending on the size of the image. The RBF (Radial Basis Function) kernel is used in training of three sets of inputs: brightness temperature of channel 3, Normalized Difference Vegetation Index (NDVI) and Global Environment Monitoring Index (GEMI), respectively. This makes a classified image in the output that highlights the hotspot and non-hotspot pixels. The performance of the SVM is also compared with the performance obtained from the neural networks and SVM appears to detect hotspots more accurately (greater than 91% classification accuracy) with lesser false alarm rate. The results obtained are found to be in good agreement with the ground based observations of the hotspots. This type of work will be quite helpful in the near future to develop a hotspots monitoring system using these operational satellites data.