A Proof-Planning Framework with explicit Abstractions based on Indexed Formulas

A major motivation of proof-planning is to bridge the gap between high-level, cognitively adequate reasoning for specific domains, and calculus-level reasoning to ensure soundness. For high reasoning levels the cognitive adequacy of representation and reasoning techniques is a major issue, while for lower reasoning levels the adequacy wrt. the modelled domain is important. Furthermore, proof construction is an engineering task and there is a need to support the design and application of proof-search engineering methods. To this end we present a framework to explicitly support different reasoning levels. To structure reasoning levels the framework allows for an explicit representation of abstractions and proof-search refinement techniques. In order to ensure soundness within a reasoning level, we use techniques developed in the context of matrix characterisation relying on the notion of indexed formulas. Furthermore, we introduce a uniform concept for contextual reasoning, and sketch basic tacticals for the definition of tactics to organise the overall proof-search inside and across different reasoning levels.     

Effective discrepancy and numerical experiments

Many problems require the computation of a high dimensional integral, typically with a few tens of input factors, with a low number of integrand evaluations. To avoid the curse of dimensionality, we reduce the dimension before applying the Quasi-Monte Carlo method. We will show how to reduce the dimension by computing approximate Sobol indices of the variables with a two-levels fractional factorial design. Then, we will use the Sobol indices to define the effective discrepancy, which turns out to be correlated with the QMC error and thus enables one to choose a good sequence for the integral estimation.     

Yielding of Microstructured Geomaterial by Distinct Element Method Analysis

The purpose of this paper is to present macro- and micro-study on the yielding of microstructured geomaterials by numerical experiments. This target is achieved by carrying out 63 one-dimensional and biaxial compressions tests on an idealized bonded geomaterial with an extension of distinct element method, into which bond contact models proposed were implemented. Numerical results indicate that: (a) preconsolidated pressure appears to attribute to bond and looseness in the geomaterials, and an increase in void ratio leads to a decrease in yielding stress in one-dimensional tests; (b) an increase in bonding strength at interparticle contacts results in an increase in yielding stress and cohesion, and an internal friction angle that is smaller than the critical state value; (c) the observed first-yielding (initiation of bond breakage) is stress path dependent, and gross-yield (defined with respect to volumetric strain) of microstructured geomaterials is evidently related to bond breakage.     

Perceptual and cognitive load interact to control the spatial focus of attention.

Caparos and Linnell (2009, 2010) used a variable-separation flanker paradigm to show that (a) when cognitive load is low, increasing perceptual load causes spatial attention to focus and (b) when perceptual load is high, decreasing cognitive load causes spatial attention to focus. Here, we tested whether the effects of perceptual and cognitive load on spatial focus remain when, respectively, cognitive load is high and perceptual load is low. We found that decreasing cognitive load only causes spatial attention to focus when perceptual load is high and the stimulus encourages this. Moreover, and contrary to the widely held assumption that perceptual load focuses attention automatically (Lavie, Hirst, de Fockert, & Viding, 2004), perceptual load exerts its focusing effect only with the engagement of cognitive resources when cognitive load is low. In sum, perceptual and cognitive mechanisms exert interacting effects and operate in concert to focus spatial attention. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Localized Ligand Induced Electroless Plating (LIEP) Process for the Fabrication of Copper Patterns Onto Flexible Polymer Substrates

The “ligand induced electroless plating (LIEP) process” is a simple process to obtain localized metal plating onto flexible polymers such as poly(ethylene terephtalate) and polyvinylidene fluoride sheets. This generic and cost‐effective process, efficient on any common polymer surface, is based on the covalent grafting by the GraftFast process of a thin chelating polymer film, such as poly(acrylic acid), which can complex copper ions. The entrapped copper ions are then chemically reduced in situ and the resulting Cu⁰ species act as a seed layer for the electroless copper growth which, thus, starts inside the host polymer. The present work focuses on the application of the LIEP process to the patterning of localized metallic tracks via two simple lithographic methods. The first is based on a standard photolithography process using a positive photoresist masking to prevent the covalent grafting of PAA in designated areas of the polymer substrate. In the second, the patterning is performed by direct printing of the mask with a commercial laser printer. In both cases, the mask was lifted off before the copper electroless plating step, which provides ecological benefits, since only the amount of copper necessary for the metallic patterning is used.     

Defect cluster recognition system for fabricated semiconductor wafers

The International Technology Roadmap for Semiconductors (ITRS) identifies production test data as an essential element in improving design and technology in the manufacturing process feedback loop. One of the observations made from the high-volume production test data is that dies that fail due to a systematic failure have a tendency to form certain unique patterns that manifest as defect clusters at the wafer level. Identifying and categorising such clusters is a crucial step towards manufacturing yield improvement and implementation of real-time statistical process control. Addressing the semiconductor industry’s needs, this research proposes an automatic defect cluster recognition system for semiconductor wafers that achieves up to 95% accuracy (depending on the product type).     

Fault tolerant network design inspired by Physarum polycephalum

Physarum polycephalum, a true slime mould, is a primitive, unicellular organism that creates networks to transport nutrients while foraging. The design of these natural networks proved to be advanced, e.g. the slime mould was able to find the shortest path through a maze. The underlying principles of this design have been mathematically modelled in literature. As in real life the slime mould can design fault tolerant networks, its principles can be applied to the design of man-made networks. In this paper, an existing model and algorithm are adapted and extended with stimulation and migration mechanisms which encourage formation of alternative paths, optimize edge positioning and allow for automated design. The extended model can then be used to better design fault tolerant networks. The extended algorithm is applied to several national and international network configurations. Results show that the extensions allow the model to capture the fault tolerance requirements more accurately. The resulting extended algorithm overcomes weaknesses in geometric graph design and can be used to design fault tolerant networks such as telecommunication networks with varying fault tolerance requirements.