The 100 000-Year Periodicity in Glacial Cycles and Oscillations of World Ocean Level

Izvestiya, Atmospheric and Oceanic Physics - The 100 000-year periodicity of climate changes during the Late Pleistocene (in the last 800 ka) may be related to the respective oscillations in...     

Subpollen Particles as Atmospheric Cloud Condensation Nuclei

Izvestiya, Atmospheric and Oceanic Physics - Bioparticles constitute a significant fraction of atmospheric aerosol. Their size range varies from nanometers (macromolecules) to hundreds of...     

Self-Similarity Properties of the Kerch Peninsula Stream Network and Their Comparison with the Results of Structural and Geomorphological Analysis

Izvestiya, Atmospheric and Oceanic Physics - The results of the fractal analysis of a drainage network reconstructed using a digital elevation model and the structural and geomorphological analysis...     

First Observation of Objects Found by the Tautenburg Objective Prism Survey

The spectra of ten objects discovered by the Tautenburg objective prism survey were obtained at a higher spectral resolution in order to refine the selection criteria. We found four objects to be quasars and three MARKARIAN -type galaxies.     

芬兰湾中的神秘群岛

看一眼列宁格勒区的地图,不难发现,芬兰湾北部沿岸的海岸线被切割得极深。大量的岛屿、礁石、半岛和海湾形成了芬诺斯坎迪亚典型的断崖地貌景观,后者被认为是芬兰湾北岸自然组合的样本。     

Use of remote sensing in characterization and management of Dhamni micro-watershed of Chandrapur district of Maharashtra

Soil resource characterization of Dhamni micro-watershed in Chandrapur district of Maharashtra was carried out using IRS-1D LISS-III data in conjunction with field survey and ancillary data. The study indicates that nearly 84.2 per cent of the total geographical area of the watershed is under cultivation. Forest (mainly degraded) occupy only 4.5 per cent area Whereas wasteland with scrub cover 9.4 per cent area of the watershed. Nine soil series were tentatively identified and mapped as soil series association in to five mapping units. These soils belong to order Inceptisol, Vertisol and Mollisol. Except the soils of wasteland with scrub, other soils are moderately suitable for pigeonpea and soybean and have average to good productivity.     

Considerations on Parallelizing Nonnegative Matrix Factorization for Hyperspectral Data Unmixing

Nonnegative matrix factorization (NMF) is a recently developed linear unmixing technique that assumes that the original sources and transform were positively defined. Given that the linear mixing model (LMM) for hyperspectral data requires positive endmembers and abundances, with only minor modifications, NMF can be used to solve LMM. Traditionally, NMF solutions include an iterative process resulting in considerable execution times. In this letter, we provide two novel algorithms aimed at speeding the NMF through parallel processing: the first based on the traditional multiplicative solution and the second modifying an adaptive projected gradient technique known to provide better convergence. The algorithms' implementations were tested on various data sets; the results suggest that a significant speedup can be achieved without decrease in accuracy. This supports the further use of NMF for linear unmixing.