Effects of partial frequency redistribution functions RII,RIII and RV on source functions

The effects of partial frequency redistribution on the formation of spectral lines have been studied. We considered the angle-averaged R_II, R_III andR _v types of redistribution with isotropic phase function, Transfer equation with plane-parallel geometry is solved in isothermal atmospheres. For an atmosphere with constant thermal sources, the frequency-dependent source function S_L (R _v) lies below S_L (R_III) but above S_L(R _III) in the line wings.     

Simultaneous optimization of the performance of flotation circuits and their simplification using the jumping gene adaptations of genetic algorithm-II: More complex problems

The binary-coded elitist non-dominated sorting genetic algorithm with the modified jumping gene operator (NSGA-II-mJG) is used to obtain global optimal solutions of flotation circuits. Several single-objective and multi-objective optimization problems are solved using the interconnecting cell linkage parameters (fraction flow rates) and the mean cell residence times as the decision variables. In the single-objective problem, the overall recovery of the concentrate stream is maximized for a desired grade of the concentrate. Two two-objective optimization problems are then solved. In one, the number of non-linking streams and the overall recovery of the concentrate are maximized simultaneously. This gives several simple circuits in a systematic manner with only marginally lower recoveries. In the other two-objective optimization problem, the overall recovery of the concentrate is maximized while the total cell volume is minimized. A three-objective problem (maximization of the overall recovery of the concentrate, maximization of the number of non-linking streams and minimization of the total cell volume) is then solved. All the problems constrain the grade of the product to lie at a fixed value. Finally, a complex and computationally intensive four-objective optimization problem is solved. The solution of several practical optimization problems in this study helps develop useful insights into the optimal solutions.     

Spatially Coherent Nonlinear Dimensionality Reduction and Segmentation of Hyperspectral Images

The nonlinear dimensionality reduction and its effects on vector classification and segmentation of hyperspectral images are investigated in this letter. In particular, the way dimensionality reduction influences and helps classification and segmentation is studied. The proposed framework takes into account the nonlinear nature of high-dimensional hyperspectral images and projects onto a lower dimensional space via a novel spatially coherent locally linear embedding technique. The spatial coherence is introduced by comparing pixels based on their local surrounding structure in the image domain and not just on their individual values as classically done. This spatial coherence in the image domain across the multiple bands defines the high-dimensional local neighborhoods used for the dimensionality reduction. This spatial coherence concept is also extended to the segmentation and classification stages that follow the dimensionality reduction, introducing a modified vector angle distance. We present the underlying concepts of the proposed framework and experimental results showing the significant classification improvements     

Potential predictability of the Asian summer monsoon on monthly and seasonal time scales

Summary ¶The potential predictability of the monthly and seasonal means during the Northern Hemisphere summer and winter is studied by estimating the signal-to-noise ratio. Based on 33 years of daily low-level wind observations and 24 years of satellite observations of outgoing long wave radiation, the predictability of the Asian summer monsoon region is contrasted with that over other tropical regions. A method of separating the contributions from slowly varying boundary forcing and internal dynamics (e.g., intraseasonal oscillations) that determine the predictability of the monthly mean tropical climate is proposed. We show that the Indian monsoon climate is only marginally predictable in monthly time scales as the contribution of the boundary forcing in this region is relatively low and that of the internal dynamics is relatively large. It is shown that excluding the Indian monsoon region, the predictable region is larger and predictability is higher in the tropics during northern summer. Even though the boundary forced variance is large during northern winter, the predictable region is smaller as the internal variance is larger and covers a larger region during northern winter (due to stronger intraseasonal activity). Consistent with the estimates of predictability of monthly means, estimates of potential predictability on seasonal time scales also indicate that predictability of seasonal mean Indian monsoon is limited.Received December 6, 2002; accepted March 16, 2003 Published online: June 12, 2003     

Passive diffusion sampling of sulfur dioxide in India: Impact assessment on arid areas

Environmental constraints have drastically limited options of sustainable development and have severely offset many developmental schemes. In this paper, possibilities of acidic deposition, as a counter measure of desertification, are analyzed. Seasonal data of ambient sulfur dioxide, pH of rain water and soil acidity are collected for over an year and analyzed. Arid environment of surrounding areas of Delhi is considered and analyzed. Though ambient sulfur deposition is well below critical level, it might not be truly indicative of plant survival in arid areas. Results may be useful in arid area afforestation, and polluting industries relocation, which holds tremendous potential vis-à-vis sustainable development.