Error resilient video over multimedia broadcast multicast services (MBMS)

With available data rates for mobile devices constantly increasing, services such as video broadcast and multicast are becoming feasible. A new standard called Multimedia Broadcast Multicast Services (MBMS) is being developed by 3GPP to enable new class of spectrum-efficient multimedia services. Multicast services are expected to serve a diverse user base with varying connectivity and capabilities. We analyze the problem of video error resilience in MBMS services that is critical to maintain consistent quality for end users. The existing error resilience techniques for IP multicasting are not applicable in the MBMS environment. In this paper, we present error resilience techniques that are applicable within the context of the MBMS standard. We propose an Intra Block Refresh method for MBMS services and the results show improved performance. We develop a methodology that can be applied to adapting traditional error resilience tools for the MBMS environment.     

Differential sensitivity of Desi (small‐seeded) and Kabuli (large‐seeded) chickpea genotypes to water stress during seed filling: effects on accumulation of seed reserves and yield

Water stress during the reproductive phase, especially during seed development, is considered detrimental for chickpea yield. In the present study, the relative sensitivity of Desi and Kabuli chickpea types to water stress during seed filling was assessed in terms of effects on quantitative and qualitative aspects of seed yield. Leaves of both types experienced stress injury (evaluated as electrolyte leakage) to the same extent and possessed almost similar values of water potential at the end of 14 days of water stress. The stressed plants of Kabuli type lost more chlorophyll and had less photosynthesis than Desi type. At maturity, Desi type showed more diminution of vegetative dry matter due to stress over control than Kabuli type. On the other hand, Kabuli type showed a proportionally greater reduction in seed weight per plant, average seed weight, average seed size, number of pods (single‐ and double‐seeded) and harvest index. The stressed seeds of Kabuli type showed 48 and 46% reduction over control in starch and protein content compared with 25 and 40%, respectively in Desi type. The accumulation of soluble sugars was relatively greater due to stress in Kabuli (47%) than Desi type (23%). Fat and fiber content declined by 39 and 35% over control in Desi seeds because of stress whereas Kabuli type showed 46 and 67% decreases, respectively. Protein fractions, namely albumins, globulins, glutelins and prolamins, decreased in stressed seeds of Kabuli by 32, 40, 16 and 15% over control relative to 40, 48, 30 and 28%, respectively, in Kabuli type. The activities of sucrose synthase, invertase and soluble starch synthase were inhibited to a higher extent in Kabuli seeds than Desi seeds under stress. Kabuli seeds showed significantly more reduction in the accumulation of amino acids such as phenylalanine + tyrosine, tryptophan, valine, alanine and histidine and minerals (Ca, P, Fe) due to stress compared with Desi type. Copyright © 2006 Society of Chemical Industry     

Decomposition of the metastable beta phase in the all-beta alloy Ti-13V-11Cr-3Al

The phase transformations which occur in the all-β titanium alloy Ti-13V-llCr-3Al at temperatures below ∼ 500°C have been studied by transmission electron microscopy, X-ray diffraction, and electrical resistivity techniques. The decomposition of the metastable β phase has been found to proceed through a transition reaction leading to the formation of two bcc phases rather than through the precipitation of the ω phase as has been previously reported. An interpretation of the observed decomposition sequence, based on thermodynamic reasoning, is presented. The decomposition characteristics of the Ti-13V-llCr-3Al alloy have been compared with those of a Ti-13V-llCr alloy to determine the influence of aluminum on the transformation behavior.     

Fetal MEG redistribution by projection operators

The fetal magnetoencephalogram (fMEG) is measured in the presence of large interference from the maternal and fetal magnetocardiograms. This interference can be efficiently attenuated by orthogonal projection of the corresponding spatial vectors. However, the projection operators redistribute the fMEG signal among sensors. Although redistribution can be readily accounted for in the forward solution, visual interpretation of the fMEG signal topography is made difficult. We have devised a general, model-independent method for correction of the redistribution effect that utilizes the assumption that we know in which channels the fMEG should be negligible (such channels are distant from the known fetal head position). In a simplified case where the fMEG can be explained by equivalent current dipoles, the correction can also be obtained from fitting the dipoles to the fMEG signal. The corrected fMEG signal topography then corresponds to the dipole forward solution, but without orthogonal projection. We illustrate the redistribution correction on an example of experimentally measured flash evoked fMEG.     

Complexation of copper by zwitterionic aminosulfonic (good) buffers

Copper binding properties were investigated for several popular zwitterionic buffers. The two buffers 4-morpholinoethanesulfonic acid (MES) and 3-N-morpholinopropanesulfonic acid (MOPS) did not bind copper and would be good choices for metal speciation studies within their operational pH range. Conversely, 3-(N-morpholino)-2-hydroxypropanesulfonic acid (MOPSO) was observed to weakly bind copper directly (log Kc 2.02). Moreover, strong copper binding was observed for 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES), 4-(2-hydroxyethyl)piperazine-1-propanesulfonic acid (HEPPS), and N-(2-hydroxyethyl)piperazine-N'-(2-hydroxypropanesulfonic acid) (HEPPSO). Log Kc values range from 7.04 to 7.68 and are indicative of strong copper binding ligands. The latter buffer also exhibited weak binding characteristics with a log Kc of 2.05. The strong Cu binding ligands were present in HEPES, HEPPS, and HEPPSO at much lower concentrations than the total buffer concentration. MES, HEPES, MOPSO, and HEPPSO were analyzed by electrospray-ionization quadrapole time-of-flight mass spectroscopy. The most prominent feature of the spectra for each buffer analyzed was the presence of multiple oligomers, indicating a propensity of interaction between buffer molecules. In addition, the presence of several contaminants was identified in the mass spectrum of the HEPES matrix, including a prominent contaminant (at m/z 131) present in levels similar to those obtained from the modeling of the copper titration data. Other contaminants were found in the other matrixes but were not identified as possible copper binding agents.     

The use of aerosol formation, flammability, and explosion information for heat-transfer fluid selection

The devastating consequences of aerosol/mist explosions have been widely documented, and there are currently efforts to understand the mechanisms of formation and explosion of aerosols. Heat-transfer fluids (HTFs) are particularly susceptible to these hazards, because they are utilized under high pressures and below their flash points, making them more prone to leaking as aerosols. In fact, there is a critical need during design stages for a perception of explosion risks associated with the selection of HTFs. This paper discusses a novel scheme to integrate the knowledge of HTF aerosol formation from leaks in process equipment into the selection of HTFs during the design process. Hazards of aerosols formed from leaks are classified qualitatively using process pressure and droplet sizes.     

Neural network approach to background modeling for video object segmentation.

This paper presents a novel background modeling and subtraction approach for video object segmentation. A neural network (NN) architecture is proposed to form an unsupervised Bayesian classifier for this application domain. The constructed classifier efficiently handles the segmentation in natural-scene sequences with complex background motion and changes in illumination. The weights of the proposed NN serve as a model of the background and are temporally updated to reflect the observed statistics of background. The segmentation performance of the proposed NN is qualitatively and quantitatively examined and compared to two extant probabilistic object segmentation algorithms, based on a previously published test pool containing diverse surveillance-related sequences. The proposed algorithm is parallelized on a subpixel level and designed to enable efficient hardware implementation.     

Fuzzy Reliability Assessment of Distribution System with Wind Farms and Plug-in Electric Vehicles

Abstract

The equipment failures are highly uncertain in nature and simple average failure rate will not reflect this uncertainty. The uncertainty level further increases in reliability evaluation due to the integration of wind farm (WF) because of the intermittent nature of wind speed and random charging patterns of plug-in electric vehicles (PEVs). In this work, the uncertain variables in the distribution system (failure rate, repair time, WF output, PEVs charging and system load factor) are represented as fuzzy numbers to handle the uncertainty. The available uncertain data are used to find the probability distribution function (PDF) of that parameter and is converted into fuzzy membership function using transformation techniques. Failure rate of equipment is converted into failure probability using Monte Carlo simulation (MCS) method. Sampling method is applied to create the PDF of a variable which has average value. Fuzzy severity index (FSI) is proposed to find the importance of an equipment on reliability and is evaluated by measuring the fuzzy distance between the fuzzy reliability indices. The proposed assessment method is validated on modified RBTS bus 2 by comparing with analytical and MCS methods. The proposed method has been tested with integration of WFs and PEVs.     

Efficient asynchronous executions of AMR computations and visualization on a GPU system

Adaptive Mesh Refinement is a method which dynamically varies the spatio-temporal resolution of localized mesh regions in numerical simulations, based on the strength of the solution features. In-situ visualization plays an important role for analyzing the time evolving characteristics of the domain structures. Continuous visualization of the output data for various timesteps results in a better study of the underlying domain and the model used for simulating the domain. In this paper, we develop strategies for continuous online visualization of time evolving data for AMR applications executed on GPUs. We reorder the meshes for computations on the GPU based on the users input related to the subdomain that he wants to visualize. This makes the data available for visualization at a faster rate. We then perform asynchronous executions of the visualization steps and fix-up operations on the CPUs while the GPU advances the solution. By performing experiments on Tesla S1070 and Fermi C2070 clusters, we found that our strategies result in 60% improvement in response time and 16% improvement in the rate of visualization of frames over the existing strategy of performing fix-ups and visualization at the end of the timesteps.