The reduction of oxygen on platium black in acid electrolytes

The oxidation potentials of smooth and of highly dispersed platinum are very similar under a variety of conditions. The kinetics of the oxygen reduction, however, differ considerably, showing no influence of a partial coverage of the metal with absorbed oxygen in the case of black platinum. A mechanism is proposed which assumes adsorptive rupture of the OO bond in initially formed HO₂ radicals. This mechanism can rationalize a number of facts which are known about the oxygen reduction on platinum.     

Computational ghost imaging for remote sensing

Computational ghost imaging is a structured-illumination active imager coupled with a single-pixel detector that has potential applications in remote sensing. Here we report on an architecture that acquires the two-dimensional spatial Fourier transform of the target object (which can be inverted to obtain a conventional image). We determine its image signature, resolution, and signal-to-noise ratio in the presence of practical constraints such as atmospheric turbulence, background radiation, and photodetector noise. We consider a bistatic imaging geometry and quantify the resolution impact of nonuniform Kolmogorov-spectrum turbulence along the propagation paths. We show that, in some cases, short-exposure intensity averaging can mitigate atmospheric-turbulence-induced resolution loss. Our analysis reveals some key performance differences between computational ghost imaging and conventional active imaging, and identifies scenarios in which theory predicts that the former will perform better than the latter.     

Learning the stress function pattern of ordered weighted average aggregation using DBSCAN clustering

Ordered weighted average (OWA) operator provides a parameterized class of mean type operators between the minimum and the maximum. It is an important tool that can reflect the strategy of a decision maker for decision-making problems. In this study, the idea of obtaining the stress function from OWA weights has been put forward to generalize and characterize OWA weights. The main idea in this paper is mainly constructed on the basis that, generally, stress functions can be constructed using a mixture of constant and linear components. So, we can consider the stress function as a piecewise linear function. For obtaining stress functions as piecewise linear functions, we present a clustering-based approach for OWA weight generalization. This generalization is made using the DBSCAN algorithm as the learning method of a stress function associated with known OWA weights. In the learning process, the whole data set is divided into clusters, and then linear functions are obtained via a least squares estimator.     

Patterns of household concentrations of multiple indoor air pollutants in China

Most previous studies on indoor air pollution from household use of solid fuels have used either indirect proxies for human exposure or measurements of individual pollutants at a single point, as indicators of (exposure to) the mixture of pollutants in solid fuel smoke. A heterogeneous relationship among pollutant-location pairs should be expected because specific fuel-stove technology and combustion and dispersion conditions such as temperature, moisture, and air flow are likely to affect the emissions and dispersion of the various pollutants differently. We report on a study for monitoring multiple pollutants--including respirable particles (RPM), carbon monoxide, sulfur dioxide, fluoride, and arsenic--at four points inside homes that used coal and/or biomass fuels in Guizhou and Shaanxi provinces of China. All pollutants exhibited large variability in emissions and spatial dispersion within and between provinces and were generally poorly correlated. RPM, followed by SO2, was generally higher than common health-based guidelines/standards and provided sufficient resolution for assessing variations within and between households in both provinces. Indoor heating played an important role in the level and spatial patterns of pollution inside homes, possibly to an extent more important than cooking. The findings indicate the need for monitoring of RPM and selected other pollutants in longer-term health studies, with focus on both cooking and living/sleeping areas.     

Geographical, spatial, and temporal distributions of multiple indoor air pollutants in four Chinese provinces

Exposure to indoor air pollution from household energy use depends on fuel, stove, housing characteristics, and stove use behavior. We monitored three important indoor air pollutants-respirable particles (RPM), carbon monoxide (CO), and sulfur dioxide (SO2)-for a total of 457 household-days in four poor provinces in China (Gansu, 129 household-days; Guizhou, 127 household-days; Inner Mongolia, 65 household-days; and Shaanxi, 136 household-days), in two time intervals during the heating season to investigate spatial and temporal patterns of pollution. The two provinces where biomass is the primary fuel (Inner Mongolia and Gansu) had the highest RPM concentrations (719 microg/m3 in the single cooking/living/bedroom in Inner Mongolia in December and 351-661 microg/m3 in different rooms and months in Gansu); lower RPM concentration were observed in the primarily coal-burning provinces of Guizhou and Shaanxi (202-352 microg/m3 and 187-361 microg/m3 in different rooms and months in Guizhou and Shaanxi, respectively). Inner Mongolia and Gansu also had higher CO concentrations (7.4 ppm in the single cooking/living/bedroom in Inner Mongolia in December and 4.8-11.3 ppm in different rooms and months in Gansu). Among the two primarily coal-burning provinces, Guizhou had lower concentrations of CO than Shaanxi (1.2-1.8 ppm in Guizhou vs 2.0-13.3 ppm in different rooms and months in Shaanxi). In the two coal-burning provinces, SO2 concentrations were substantially higher in Shaanxi than in Guizhou. Relative concentrations in different rooms and provinces indicate that in the northern provinces heating is an important source of exposure to indoor pollutants from energy use. Day-to-day variability of concentrations within individual households, although substantial, was smaller than variation across households. The implications of the findings for designing environmental health interventions in each province are discussed.     

Experimental investigation on the ball burnishing of carbon fiber reinforced polymer

The polymer-based materials are generally used in all industrial applications. Even if polymer bars can be machined easily, they need surface finishing treatment after the machining process. The ductile properties make coarse roughness on the surface that causes the elastic structure of polymer materials. The carbon fiber reinforced composite materials differ from polymer-based materials by high strength and stiffness. Its structure exhibits similar performances such as metallic materials. The effect of ball burnishing on the surface quality of rod workpiece was investigated in this study. To enhance the surface quality of high strength carbon fiber reinforced polymer rod workpiece, burnishing process was performed in three different parameters (force, feed rate, number of passes) and under four different mediums (dry, wet, boron oil, and mineral oil) conditions. The results of the experiments were analyzed, and optimum burnishing parameters were determined and discussed in detail. The best surface roughness value of the CFRP material used in the experiments was obtained as burnishing force: 250 N, feed rate: 0.05 mm/rev, four passes and wet medium. According to the results of variance analysis, it was found that the CFRP workpiece is the important leading factor for surface roughness with a contribution ratio of 62.47%.     

Speeding Up Cycle Based Logic Simulation Using Graphics Processing Units

Verification has grown to dominate the cost of electronic system design, consuming about 60% of design effort. Among several verification techniques, logic simulation remains the major verification technique. Speeding up logic simulation results in great savings and shorter time-to-market. We parallelize logic simulation using Graphics Processing Units (GPUs). In the past, GPUs were special-purpose application accelerators, suitable only for conventional graphics applications. The new generations of GPU architecture provide easier programmability and increased generality while maintaining the tremendous memory bandwidth and computational power of traditional GPUs. We develop a parallel cycle-based logic simulation algorithm that uses And Inverter Graphs (AIGs) as design representations. AIGs have proven to be an effective representation for various design automation applications, and we obtain similar benefits for speeding up logic simulation. We develop two clustering algorithms that partition the gates in the designs into independent blocks. Our algorithms exploit the massively parallel GPU architecture featuring thousands of concurrent threads, fast memory, and memory coalescing for optimizations. We demonstrate up-to 5x and 21x speedups on several benchmarks using our simulation system with the first and second clustering algorithms, respectively. Our work ultimately results in significant reduction in the overall design cycle.     

A variational framework for multiregion pairwise-similarity-based image segmentation

Variational cost functions that are based on pairwise similarity between pixels can be minimized within level set framework resulting in a binary image segmentation. In this paper we extend such cost functions and address multi-region image segmentation problem by employing a multi-phase level set framework. For multi-modal images cost functions become more complicated and relatively difficult to minimize. We extend our previous work, proposed for background/foreground separation, to the segmentation of images in more than two regions. We also demonstrate an efficient implementation of the curve evolution, which reduces the computational time significantly. Finally, we validate the proposed method on the Berkeley Segmentation Data Set by comparing its performance with other segmentation techniques.