Fuzzy Learning of Talbot Effect Guides Optimal Mask Design for Proximity Field Nanopatterning Lithography

Processing methods used in photonics and nanotechnology possess many limitations restricting their application areas such as high cost, inability to produce fine details, problems with scalability, and long processing time. Proximity field nanopatterning is a lithography method which surpasses these limitations. By using interference patterns produced by a two-dimensional phase mask, the technique is able to generate a submicron detailed exposure on a millimeter-size slab of light sensitive photopolymer, which is then developed like a photographic plate to reveal three-dimensional interference patterns from the phase mask. While it is possible to use simulations to obtain the interference patterns produced by a phase mask, realizing the mask dimensions necessary for producing a desired interference pattern is analytically challenging due to the intricacies of light interactions involved in producing the final interference pattern. An alternative method is to iteratively optimize the phase mask until the interference patterns obtained converge to the desired pattern. However, depending on the optimization technique used, one either risks a significant probability of failure or requires a prohibitive number of iterations. We argue that an optimization technique that is to take advantage of the physics of the problem using machine learning methods (here fuzzy learning) can lead to competent mask design. This technique is described in this letter.     

Towards a new definition of EPOC parameters for anionic electrochemical catalysts: case of propene combustion

The electrochemical promotion of catalysis (EPOC) of propene combustion was investigated using Pt sputtered thin film on an O²⁻ conductor, 8 mol% Y₂O₃-stabilized-ZrO₂ (YSZ). In order to separate the influence of the thermal migration of the O²⁻ oxide ions from the electrolyte to the catalyst surface and the impact of an electrical polarization on the catalytic activity, several light-off experiments (cool down and heat up procedures) were successively performed under different polarizations, i.e. OCV, +2 and −2 V. These experiments have clearly shown that the presence of O²⁻ (thermally or electrochemically induced) inhibits the catalytic activity of the platinum for the propene deep oxidation. These results demonstrate the importance to define a normalized rate enhancement ratio, ρ _n , from a reference value of the catalytic rate corresponding to a Pt surface state free of O²⁻ ions.     

Incremental inconsistency detection with low memory overhead

Ensuring models’ consistency is a key concern when using a model‐based development approach. Therefore, model inconsistency detection has received significant attention over the last years. To be useful, inconsistency detection has to be sound, efficient, and scalable. Incremental detection is one way to achieve efficiency in the presence of large models. In most of the existing approaches, incrementalization is carried out at the expense of the memory consumption that becomes proportional to the model size and the number of consistency rules. In this paper, we propose a new incremental inconsistency detection approach that only consumes a small and model size‐independent amount of memory. It will therefore scale better to projects using large models and many consistency rules. Copyright © 2012 John Wiley & Sons, Ltd.     

An integrated approach for groundwater potential zoning in shallow fracture zone aquifers

This study presents an integrated approach for the identification of groundwater occurrences in shallow fracture zone (SFZ) aquifers using remote-sensing, geological, and geophysical data. The Central Eastern Desert of Egypt was selected as a test site for the present study. The distribution of major faults and shear zones was extracted from a fusion image generated by injecting high-spatial resolution phased array L-band synthetic aperture radar (PALSAR) images into Landsat Enhanced Thematic Mapper images. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) digital elevation model was processed to extract the drainage systems, slope, and topographic wetness index (TWI). The multidate PALSAR imagery acquired during rainy and dry seasons was used to estimate the relative soil moisture content. The lithology, fractures, drainage density, slope, TWI, and soil moisture content were used as thematic layers for groundwater occurrence in the SFZ aquifers. A GIS model of groundwater potential was developed by selecting the most probable locations for groundwater in each layer. The results indicate that the spatial distribution of the existing water wells is in agreement with the model where all wells fall in the regions of high groundwater potential zones. A geophysical survey was conducted using ground penetrating radar (GPR), indicating that the high groundwater potential zones are promising for drilling shallow wells. The adopted approach can be used as a cost-effective tool for groundwater exploration in the SFZ aquifers in the study area and in areas of similar geologic and hydrogeologic settings elsewhere.     

Term rewriting and its application to recognizing handwritten Hindu numerals

In this paper the theoretical basis is presented and the implementation of a term rewriting system based on algebraic specifications is described. The input to this system is represented by an algebraic specification language, which forms not only the set of axioms but also the sorts, variables, operators and terms of a specific simulated theory or application. Rewriting and matching mechanisms provide the formal methodology for evaluating terms and proving assertions in an algebraic theory. Specifications are evaluated by interpreting terms by means of rewrite rules. The rules are described by the axioms of the specifications where the finite termination and congruence properties are assumed. A term rewriting system to recognize handwritten Hindu numerals is introduced as a case study. Besides rewriting, a robust algorithm is proposed to segment the numeral's image into strokes based on feature points and to identify cavity features. A syntactic representation (term) of the input image is matched and rewritten against a set of rules. Experimental results proved that the proposed system is tolerant to recognize a variety of numeral shapes with 96% successful recognition rate.     

Replica Placement Strategies in Data Grid

Replication is a technique used in Data Grid environments that helps to reduce access latency and network bandwidth utilization. Replication also increases data availability thereby enhancing system reliability. The research addresses the problem of replication in Data Grid environment by investigating a set of highly decentralized dynamic replica placement algorithms. Replica placement algorithms are based on heuristics that consider both network latency and user requests to select the best candidate sites to place replicas. Due to dynamic nature of Grid, the candidate site holds replicas currently may not be the best sites to fetch replicas in subsequent periods. Therefore, a replica maintenance algorithm is proposed to relocate replicas to different sites if the performance metric degrades significantly. The study of our replica placement algorithms is carried out using a model of the EU Data Grid Testbed 1 [Bell et al. Comput. Appl., 17(4), 2003] sites and their associated network geometry. We validate our replica placement algorithms with total file transfer times, the number of local file accesses, and the number of remote file accesses.     

Performance of Pile-Supported Bridge Approach Slabs

A large number of pile-supported bridge approach slabs in southeastern Louisiana were examined to identify the factors that affect their long-term performance. Design drawings and subsoil conditions at these sites as well as their traffic and maintenance records were compiled, and seven representative test sites were selected for thorough field investigation that included inspection of the approach slabs, bridge decks, bridge abutments, and roadway pavement. Field evaluation included walking profiler, falling-weight deflectometer (FWD), laser profiler, geodetic survey, soil borings, cone penetrometer, and nondestructive testing. Measurements made with the walking profiler agreed well with the geodetic survey. The FWD and nondestructive testing were effectively used to detect voids under the approach slab. Results of the study indicated that the current empirical methodology used by the Louisiana Department of Transportation and Development for design of pile-supported approach slabs yields inconsistent field performance. It was concluded that this inconsistent performance is primarily due to the differences in roadway embankment design and construction and in subsoil conditions, which in turn affect the negative skin friction (downdrag) loads imparted on the piles. Impact of other variables such as ramp type, speed limit, traffic volume, and so on was found to be insignificant. Results of the field study were used to develop a new rating system for approach slabs (IRIS) based on International Roughness Index (IRI) measurements obtained with the laser profiler.     

Integrating multi-objective genetic algorithm based clustering and data partitioning for skyline computation

Skyline computation in databases has been a hot topic in the literature because of its interesting applications. The basic idea is to find non-dominated values within a database. The task is mainly a multi-objective optimization process as described in this paper. This motivated for our approach that employs a multi-objective genetic algorithm based clustering approach to find the pareto-optimal front which allows us to locate skylines within a given data. To tackle large data, we simply split the data into manageable subsets and concentrate our analysis on the subsets instead of the whole data at once. The proposed approach produced interesting results as demonstrated by the outcome from the conducted experiments.     

Experimental and numerical study of a modified ASTM C633 adhesion test for strongly-bonded coatings

When coatings are strongly bonded to their substrates it is often difficult to measure the adhesion values. The proposed method, which is suggested naming “silver print test”, consists in covering the central part of the samples with a thin layer of silver paint, before coating. The process used for testing this new method was the Air plasma spraying (APS), and the materials used were alumina coatings on C35 steel substrates, previously pre-oxidized in CO₂. The silver painted area was composed of small grains that did not oxidize but that significantly sintered during the APS process. The silver layer reduced the surface where the coating was linked to the substrate, which allowed its debonding, using the classical adhesion test ASTM C633-13, while the direct use of this test (without silver painting) led to ruptures inside the glue used in this test. The numerical modelling, based on the finite element method with the ABAQUS software, provided results in good agreement with the experimental measurements. This concordance validated the used method and allowed accessing to the values of adherence when the experimental test ASTM C633-13 failed, because of ruptures in the glue. After standardization, the “silver print test” might be used for other kinds of deposition methods, such as PVD, CVD, PECVD.