Effect of the C-bridge length on the ultraviolet-resistance of oxycarbosilane low-k films

The ultra-violet (UV) and vacuum ultra-violet (VUV) resistance of bridging alkylene groups in organosilica films has been investigated. Similar to the Si-CH3 (methyl) bonds, the Si-CH2-Si (methylene) bonds are not affected by 5.6 eV irradiation. On the other hand, the concentration of the Si-CH2-CH2-Si (ethylene) groups decreases during such UV exposure. More significant difference in alkylene reduction is observed when the films are exposed to VUV (7.2 eV). The ethylene groups are depleted by more than 75% while only about 40% methylene and methyl groups loss is observed. The different sensitivity of bridging groups to VUV light should be taken into account during the development of curing and plasma etch processes of low-k materials based on periodic mesoporous organosilicas and oxycarbosilanes. The experimental results are qualitatively supported by ab-initio quantum-chemical calculations

Estimation of microblock sizes in mosaic crystals according to fast electron radiation characteristics

The possibilities of a previously proposed technique for determining the characteristic sizes of microblocks in mosaic aα-class crystals have been analyzed. Determination is performed according to the ratio between the measured and calculated values for the diffraction suppression of the fixed-energy bremsstrahlung yield. The limits of applicability of the technique have been revealedyesBelgorod State Universit

Improved Vote Aggregation Techniques for the Geo-Wiki Cropland Capture Crowdsourcing Game

Crowdsourcing is a new approach for solving data processing problems for which conventional methods appear to be inaccurate, expensive, or time-consuming. Nowadays, the development of new crowdsourcing techniques is mostly motivated by so called Big Data problems, including problems of assessment and clustering for large datasets obtained in aerospace imaging, remote sensing, and even in social network analysis. By involving volunteers from all over the world, the Geo-Wiki project tackles problems of environmental monitoring with applications to flood resilience, biomass data analysis and classification of land cover. For example, the Cropland Capture Game, which is a gamified version of Geo-Wiki, was developed to aid in the mapping of cultivated land, and was used to gather 4.5 million image classifications from the Earth’s surface. More recently, the Picture Pile game, which is a more generalized version of Cropland Capture, aims to identify tree loss over time from pairs of very high resolution satellite images. Despite recent progress in image analysis, the solution to these problems is hard to automate since human experts still outperform the majority of machine learning algorithms and artificial systems in this field on certain image recognition tasks. The replacement of rare and expensive experts by a team of distributed volunteers seems to be promising, but this approach leads to challenging questions such as: how can individual opinions be aggregated optimally, how can confidence bounds be obtained, and how can the unreliability of volunteers be dealt with? In this paper, on the basis of several known machine learning techniques, we propose a technical approach to improve the overall performance of the majority voting decision rule used in the Cropland Capture Game. The proposed approach increases the estimated consistency with expert opinion from 77% to 86%

How to Increase the Accuracy of Crowdsourcing Campaigns?

Crowdsourcing is a new approach to performing tasks, with a group of volunteers rather than experts. For example, the Geo-Wiki project [1] aims to improve the global land-cover map by crowdsourcing for image recognition. Though crowdsourcing gives a simple way to perform tasks that are hard to automate, analysis of data received from non-experts is a challenging problem that requires a holistic approach. Here we study in detail the dataset of the Cropland Capture game (part of Geo-Wiki project) to increase the accuracy of campaign’s results. Using this analysis, we developed a methodology for a generic type of crowdsourcing campaign similar to the Cropland Capture game. The proposed methodology relies on computer vision and machine learning techniques. Using the Cropland Capture dataset we showed that our methodology increases agreement between aggregated volunteers’ votes and experts’ decisions from 77% to 86%. [1] Fritz, Steffen, et al. “Geo-Wiki. Org: The use of crowdsourcing to improve global land cover.” Remote Sensing 1.3 (2009): 345-354

Influence of crystal mosaicity on the X-radiation characteristics observed at a small angle to the particle velocity direction

The experimentally measured yields of X-rays generated by 500-MeV electrons in oriented tungsten single crystals are analyzedye

Calculation of the X-ray reflectivity of b-class mosaic crystals via the Monte Carlo method

b-class mosaic crystals, including pyrolytic graphite, are widely used as neutron and X-ray monochromators in experimental physics and ensure a more intense yield of monochromatic radiation than do perfect crystalsye