Single chamber Solid Oxide Fuel Cells selective electrodes: A real chance with brownmillerite-based nanocomposites

In this contribution brownmillerite-based nanocomposite cathode for Single-Chamber Solid Oxide Fuel Cells is developed. These cells can be very attractive especially for small and cheap devices because of the absence of seals. The efficiency of SC-SOFCs is strictly connected to the selectivity of anode and cathode, the bottleneck for this technology. The development of a cathode inert in fuel oxidation is particularly challenging. Our strategy is to start from a catalytically un-active support (CFA = Ca₂FeAl_0.95Mg_0.05O₅) and induce the formation of iron oxide based nanoparticles, expected to activate oxygen. Symmetric (CFA + FeO_x/CGO/CFA + FeO_x) and complete cells (CFA + FeO_x/CGO/Ni-CGO) are studied in air and methane/oxygen 2:1 mixture. The Area Specific Resistance of CFA + FeO_x is less than 1/3 that of CFA. The high selectivity allows to reach an efficiency of 25%; power still needs to be increased but we demonstrated the possibility to develop selective low cost electrodes. The effect of air, methane/oxygen exposure and the heat treatments were carefully investigated.     

The day of the week when you were born in 700 ms: Calendar computation in an autistic savant.

Some individuals are able to determine the weekday of a given date in a few seconds (finding for instance that June 12, 1900, was a Tuesday). This ability has fascinated scientists for many years because it is predominantly observed in people with limited intelligence and may appear very early in life. Exceptional visual memory, exceptional concentration abilities, or privileged access to lower levels of information not normally available through introspection have been advanced to explain such phenomena. In the present article, the authors show that a simple cognitive model can explain all aspects of the performance of Donny, a young autistic savant who is possibly the fastest and most accurate calendar prodigy ever described. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Note of clarification on Scholten and Sherman (2006): Erratum.

Reports an error in "Tradeoffs and Theory: The Double-Mediation Model" by Marc Scholten and Steven J. Sherman (Journal of Experimental Psychology: General, 2006 May, Vol 135[2], 237-261). This article was inadvertently printed with the incorrect title. The original title was "Tradeoffs and Conflict: The Double-Mediation Model." This title highlights the relation between tradeoffs and conflict as investigated by the authors and accounted for by their model. However, readers are asked to refer to the article by the title with which it was printed to facilitate its retrieval.. (The following abstract of the original article appeared in record 2006-06642-006.) Most theories of decision making suggest that, when options imply tradeoffs between their attributes, conflict increases as tradeoff size increases, because greater sacrifices are to be incurred in choosing one option instead of another. An alternative view is that conflict decreases as tradeoff size increases, because stronger arguments can be made for any decision. The authors propose a unified model, the double-mediation model, which combines the mediating effects of sacrifice and argumentation. Our model generally predicts an inverse U-shaped relation between tradeoff size and conflict. Results support this prediction. Also, when the decision situation increases the mediating effect of sacrifice relative to that of argumentation, the relation between tradeoff size and conflict changes in an upward direction; conversely, when the decision situation increases the mediating effect of argumentation relative to that of sacrifice, the relation changes in a downward direction. Results support these predictions as well. Commonalities and differences between our model and other formulations are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A Lattice Approach to Image Segmentation

After a formal definition of segmentation as the largest partition of the space according to a criterion σ and a function f, the notion of a morphological connection is reminded. It is used as an input to a central theorem of the paper (Theorem 8), that identifies segmentation with the connections that are based on connective criteria. Just as connections, the segmentations can then be regrouped by suprema and infima. The generality of the theorem makes it valid for functions from any space to any other one. Two propositions make precise the AND and OR combinations of connective criteria. The soundness of the approach is demonstrated by listing a series of segmentation techniques. One considers first the cases when the segmentation under study does not involve initial seeds. Various modes of regularity are discussed, which all derive from Lipschitz functions. A second category of examples involves the presence of seeds around which the partition of the space is organized. An overall proposition shows that these examples are a matter for the central theorem. Watershed and jump connection based segmentations illustrate this type of situation. The third and last category of examples deals with cases when the segmentation occurs in an indirect space, such as an histogram, and is then projected back on the actual space under study. The relationships between filtering and segmentation are then investigated. A theoretical chapter introduces and studies the two notions of a pulse opening and of a connected operator. The conditions under which a family of pulse openings can yield a connected filter are clarified. The ability of segmentations to generate pyramids, or hierarchies, is analyzed. A distinction is made between weak hierarchies where the partitions increase when going up in the pyramid, and the strong hierarchies where the various levels are structured as semi-groups, and particularly as granulometric semi-groups. The last section is based on one example, and goes back over the controversy about “lattice” versus “functional” optimization. The problem is now tackled via a case of colour segmentation, where the saturation serves as a cursor between luminance and hue. The emphasis is put on the difficulty of grouping the various necessary optimizations into a single one.     

Automatic fog detection and estimation of visibility distance through use of an onboard camera

In this paper, we will present a technique for measuring visibility distances under foggy weather conditions using a camera mounted onboard a moving vehicle. Our research has focused in particular on the problem of detecting daytime fog and estimating visibility distances; thanks to these efforts, an original method has been developed, tested and patented. The approach consists of dynamically implementing Koschmieder's law. Our method enables computing the meteorological visibility distance, a measure defined by the International Commission on Illumination (CIE) as the distance beyond which a black object of an appropriate dimension is perceived with a contrast of less than 5%. Our proposed solution is an original one, featuring the advantage of utilizing a single camera and necessitating the presence of just the road and sky in the scene. As opposed to other methods that require the explicit extraction of the road, this method offers fewer constraints by virtue of being applicable with no more than the extraction of a homogeneous surface containing a portion of the road and sky within the image. This image preprocessing also serves to identify the level of compatibility of the processed image with the set of Koschmieder's model hypotheses. Nicolas Hautiére graduated from the École Nationale des Travaux Publics de l'État, France (2002). He received his M.S. and Ph.D. degree in computer vision, respectively, in 2002 and 2005 from Saint-Étienne University (France). From 2002, he is a researcher in the Laboratoire Central des Ponts et Chaussées (LCPC), Paris, France. His research interests include trafic engineering, computer vision, and pattern recognition. Jean-Philippe Tarel graduated from the École Nationale des Ponts et Chaussées, Paris, France (1991). He received his Ph.D. degree in Applied Mathematics from Paris IX-Dauphine University in 1996 and he was with the Institut National de Recherche en Informatique et Automatique (INRIA) from 1991 to 1996. From 1997 to 1998, he was a research associate at Brown University, USA. From 1999, he is a researcher in the Laboratoire Central des Ponts et Chaussées (LCPC), Paris, France, and from 2001 to 2003 in the INRIA. His research interests include computer vision, pattern recognition, and shape modeling. Jean Lavenant graduated from the École Nationale des Travaux Publics de l'État, Lyon, France (2001). He received the M.S. degree in Computer Vision from Jean Monnet university of Saint-Étienne in 2001. In 2001, he was a researcher in the Laboratoire Central des Ponts et Chaussées (LCPC). In 2002, he was a system engineer in Chicago (USA). He is currently an engineer for the french ministry of transports. Didier Aubert received the M.S. and Ph.D. degree, respectively, in 1985 and 1989 from the National Polytechnical Institut of Grenoble (INPG). From 1989--1990, he worked as a research scientist on the development of an automatic road following system for the NAVLAB at Carnegie Mellon University. From 1990–1994, he worked in the research department of a private company (ITMI). During this period he was the project leader of several projects dealing with computer vision. He is currently a researcher at INRETS since 1995 and works on Road traffic measurements, crowd monitoring, automated highway systems, and driving assistance systems for vehicles. He is an image processing expert for several companies, teaches at Universities (Paris VI, Paris XI, ENPC, ENST) and is at the editorial board of RTS (Research - Transport - Safety).     

Weight smoothing to improve network generalization

A weight smoothing algorithm is proposed in this paper to improve a neural network's generalization capability. The algorithm can be used when the data patterns to be classified are presented on an n-dimensional grid (n>/=1) and there exists some correlations among neighboring data points within a pattern. For a fully-interconnected feedforward net, no such correlation information is embedded into the architecture. Consequently, the correlations can only be extracted through sufficient amount of network training. With the proposed algorithm, a smoothing constraint is incorporated into the objective function of backpropagation to reflect the neighborhood correlations and to seek those solutions that have smooth connection weights. Experiments were performed on problems of waveform classification, multifont alphanumeric character recognition, and handwritten numeral recognition. The results indicate that (1) networks trained with the algorithm do have smooth connection weights, and (2) they generalize better.     

A unified framework for off-line permutation routing in parallel networks

In this paper we present a general strategy for finding efficient permutation routes in parallel networks. Among the popular parallel networks to which the strategy applies are mesh networks, hypercube networks, hypercube-derivative networks, ring networks, and star networks. The routes produced are generally congestion-free and take a number of routing steps that is within a small constant factor of the diameter of the network. Our basic strategy is derived from an algorithm that finds (in polynomial time) efficient permutation routes for aproduct network, G×H, given efficient permutation routes forG andH. We investigate the use of this algorithm for routingmultiple permutations and extend its applicability to a wide class of graphs, including several families ofCayley graphs. Finally, we show that our approach can be used to find efficient permutation routes among the remaining live nodes infaulty networks.This research was supported in part by a grant from the NSF, Grant No. CCR-88-12567.     

Use of weibull statistics to quantify property variability in TiAl alloys

Tensile experiments have been performed on specimens of four different investment-cast TiAl-based alloys with variations in casting conditions. The average ductilities obtained in these experiments vary between approximately 0.8 to 2.0 pct plastic strain to failure in tension. By using the three-parameter form of the Weibull relation, with the 0.2 pct offset yield strength as the minimum failure strength, the resulting variability in the data can be quantified and is found to be similar for those alloys with similar microstructural scale (grain size). Large variations in lamellar volume fraction, segregation, and phase distribution have a minor influence on property variability, compared to changes in the scale of the grain structure caused by either variations in cooling rate during casting or the addition of grain refiners.     

A New Criteria Decision Applied on the Primary Synchronization in the DS-WCDMA Interface of the UMTS System

In DS-WCDMA mobile systems such the UMTS, asynchronous cell site operation,assigning different long spreading code to each cell, yields the advantageof flexible system deployment. We can design an indoor system basedon an outdoor one. However, in general, much longer search time isrequired in asynchronous operation than in synchronous. This paperproposes three techniques to take decisions about synchronizationbased on observation of correlated signals. Classical decision criterialike maximum and threshold criterion are presented. A new decisioncriteria that we call Threshold&Max combined decision criteriais analyzed. The results of this new introduced technique is comparedwith the classical ones.