Bayesian and Dempster-Shafer fusion

The Kalman Filter is traditionally viewed as a prediction-correction filtering algorithm. In this work we show that it can be viewed as a Bayesian fusion algorithm and derive it using Bayesian arguments. We begin with an outline of Bayes theory, using it to discuss well-known quantities such as priors, likelihood and posteriors, and we provide the basic Bayesian fusion equation. We derive the Kalman Filter from this equation using a novel method to evaluate the Chapman-Kolmogorov prediction integral. We then use the theory to fuse data from multiple sensors. Vying with this approach is the Dempster-Shafer theory, which deals with measures of “belief”, and is based on the nonclassical idea of “mass” as opposed to probability. Although these two measures look very similar, there are some differences. We point them out through outlining the ideas of the Dempster-Shafer theory and presenting the basic Dempster-Shafer fusion equation. Finally we compare the two methods, and discuss the relative merits and demerits using an illustrative example.     

Tagging of η mesons using the pd → 3Heη reaction near threshold

A zero-degree spectrometer for tagging η mesons on the CELSIUS/WASA facility is described, and its characteristics are presented. Tagging of η mesons is performed by detecting ³He ions produced by reaction pd → ³Heη close to the production threshold. The low background level (<2%) is in good agreement with the data obtained earlier on the SATURNE accelerator.     

Multiple melting in blends of poly(vinylidene fluoride) with isotactic poly(ethyl methacrylate)

Multiple melting phenomena have been studied in blends of poly(vinylidene fluoride) (PVF₂) with low molar mass isotactic poly(ethyl methacrylate) (it-PEMA). In all blends, as well as in pure PVF₂, a transition (T₁) was observed prior to the main melting point (T₂). T₁ is probably connected with the melting of secondarily-crystallized material. In addition to this, a high temperature melting endotherm (T₃) was observed, which could be ascribed completely to recrystallization of PVF₂. The highest transition (T₄) was caused by melting of the σ form of PVF₂. From Hoffman-Weeks plots—T₂ vs. crystallization temperature, T_c — it could be concluded that no thermody amic depression of the melting point of PVF₂ occurred in the blends. The stabilities of PVF₂ crystallites in the various blends were derived from the slopes of Hoffman-Weeks plots and were in good agreement with lamellar thicknesses found from SAXS measurements.     

Resource allocation in grid computing

Grid computing, in which a network of computers is integrated to create a very fast virtual computer, is becoming ever more prevalent. Examples include the TeraGrid and Planet-lab.org, as well as applications on the existing Internet that take advantage of unused computing and storage capacity of idle desktop machines, such as Kazaa, SETI@home, Climateprediction.net, and Einstein@home. Grid computing permits a network of computers to act as a very fast virtual computer. With many alternative computers available, each with varying extra capacity, and each of which may connect or disconnect from the grid at any time, it may make sense to send the same task to more than one computer. The application can then use the output of whichever computer finishes the task first. Thus, the important issue of the dynamic assignment of tasks to individual computers is complicated in grid computing by the option of assigning multiple copies of the same task to different computers. We show that under fairly mild and often reasonable conditions, maximizing task replication stochastically maximizes the number of task completions by any time. That is, it is better to do the same task on as many computers as possible, rather than assigning different tasks to individual computers. We show maximal task replication is optimal when tasks have identical size and processing times have a NWU (New Worse than Used; defined later) distribution. Computers may be heterogeneous and their speeds may vary randomly, as is the case in grid computing environments. We also show that maximal task replication, along with a c μ rule, stochastically maximizes the successful task completion process when task processing times are exponential and depend on both the task and computer, and tasks have different probabilities of completing successfully.     

Increasing X-ray image interpretation competency of cargo security screeners

X-ray screening of containers and unit load devices in the area of cargo shipping is becoming an essential and common feature at ports and airports all over the world. The detection of prohibited items in X-ray images is a challenging task for screening officers as they need to know which items are prohibited and what they look like in X-ray images. The main aim of this study was to investigate whether X-ray image interpretation competency of cargo security screeners can be increased by computer-based training. More specifically, effects of training were investigated by conducting tests before training started and after approximately three months of training. Moreover, it was examined whether viewing X-ray images in pseudo color would lead to a better detection performance compared to when X-ray images are shown in greyscale. Recurrent computer-based training resulted in large performance increases after three months. No significant difference in detection performance could be found for tests when using X-ray images in greyscale vs. pseudo color.     

Water Sorption and Diffusion in (Reduced) Graphene Oxide‐Alginate Biopolymer Nanocomposites

The water sorption and diffusion in (reduced) graphene oxide‐alginate composites of various compositions is analyzed. Water sorption of sodium alginate can be significantly reduced by the inclusion of graphene oxide sheets due to the formation of an extensive hydrogen bonding network between oxygenated groups. Crosslinking alginate with divalent metal ions and the presence of reduced graphene oxide can further improve the swelling resistance due to the strong interactions between metal ions, alginate, and filler sheets. Depending on conditions and composition, the overall water barrier properties of alginate composites improve upon (reduced) graphene oxide filling, making them attractive for moisture barrier coating applications. Water sorption kinetics in all alginate composites indicate a non‐Fickian diffusion process that can be accurately described by the Variable Surface Concentration model. In addition, the water barrier properties of sodium alginate‐graphene oxide composites can be adequately predicted using a simple model that takes the orientational order of filler sheets and their effective aspect ratio into account.

     

The bipolar plate of AISI 1045 steel with chromized coatings prepared by low-temperature pack cementation for proton exchange membrane fuel cell

The low-temperature pack chromization, a reforming pack cementation process, is employed to modify AISI 1045 steel for the application of bipolar plates in PEMFC. The process is conducted to yield a coating, containing major Cr-carbides and minor Cr-nitrides, on the substrate in view of enhancing the steel's corrosion resistance and lowering interfacial contact resistance between the bipolar plate and gas diffusion layer. Electrical discharge machining and rolling approach are used as the pretreatment to produce an activated surface on the steel before pack chromization process to reduce operating temperatures and increase deposition rates. The rolled-chromized steel shows the lowest corrosion current density, 3 × 10⁻⁸ A cm⁻², and the smallest interfacial contact resistance, 5.9 mΩ cm², at 140 N cm⁻² among all tested steels. This study clearly states the performance of 1045 carbon steel modified by activated and low-temperature pack chromization processes, which possess the potential to be bipolar plates in the application of PEMFC.     

A shape analysis framework for neuromorphometry

This paper addresses in an integrated and systematic fashion the relatively overlooked but increasingly important issue of measuring and characterizing the geometrical properties of nerve cells and structures, an area often called neuromorphology. After discussing the main motivation for such an endeavour, a comprehensive mathematical framework for characterizing neural shapes, capable of expressing variations over time, is presented and used to underline the main issues in neuromorphology. Three particularly powerful and versatile families of neuromorphological approaches, including differential measures, symmetry axes/skeletons, and complexity, are presented and their respective potentials for applications in neuroscience are identified. Examples of applications of such measures are provided based on experimental investigations related to automated dendrogram extraction, mental retardation characterization, and axon growth analysis.