A genetic algorithm approach for group formation in collaborative learning considering multiple student characteristics

Considering that group formation is one of the key processes in collaborative learning, the aim of this paper is to propose a method based on a genetic algorithm approach for achieving inter-homogeneous and intra-heterogeneous groups. The main feature of such a method is that it allows for the consideration of as many student characteristics as may be desired, translating the grouping problem into one of multi-objective optimization. In order to validate our approach, an experiment was designed with 135 college freshmen considering three characteristics: an estimate of student knowledge levels, an estimate of student communicative skills, and an estimate of student leadership skills. Results of such an experiment allowed for the validation, not only from the computational point of view by measuring the algorithmic performance, but also from the pedagogical point of view by measuring student outcomes, and comparing them with two traditional group formation strategies: random and self-organized.     

Intrinsic Images by Clustering

Decomposing an input image into its intrinsic shading and reflectance components is a long‐standing ill‐posed problem. We present a novel algorithm that requires no user strokes and works on a single image. Based on simple assumptions about its reflectance and luminance, we first find clusters of similar reflectance in the image, and build a linear system describing the connections and relations between them. Our assumptions are less restrictive than widely‐adopted Retinex‐based approaches, and can be further relaxed in conflicting situations. The resulting system is robust even in the presence of areas where our assumptions do not hold. We show a wide variety of results, including natural images, objects from the MIT dataset and texture images, along with several applications, proving the versatility of our method.     

An open-source library for the numerical modeling of mass-transfer in solid oxide fuel cells

The generation of direct current electricity using solid oxide fuel cells (SOFCs) involves several interplaying transport phenomena. Their simulation is crucial for the design and optimization of reliable and competitive equipment, and for the eventual market deployment of this technology. An open-source library for the computational modeling of mass-transport phenomena in SOFCs is presented in this article. It includes several multicomponent mass-transport models (i.e. Fickian, Stefan–Maxwell and Dusty Gas Model), which can be applied both within porous media and in porosity-free domains, and several diffusivity models for gases. The library has been developed for its use with OpenFOAM^®, a widespread open-source code for fluid and continuum mechanics. The library can be used to model any fluid flow configuration involving multicomponent transport phenomena and it is validated in this paper against the analytical solution of one-dimensional test cases. In addition, it is applied for the simulation of a real SOFC and further validated using experimental data.Program summaryProgram title: multiSpeciesTransportModelsCatalogue identifier: AEKB_v1_0Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AEKB_v1_0.htmlProgram obtainable from: CPC Program Library, Queen?s University, Belfast, N. IrelandLicensing provisions: GNU General Public LicenseNo. of lines in distributed program, including test data, etc.: 18 140No. of bytes in distributed program, including test data, etc.: 64 285Distribution format: tar.gzProgramming language:: C++Computer: Any x86 (the instructions reported in the paper consider only the 64 bit case for the sake of simplicity)Operating system: Generic Linux (the instructions reported in the paper consider only the open-source Ubuntu distribution for the sake of simplicity)Classification: 12External routines: OpenFOAM® (version 1.6-ext) (http://www.extend-project.de)Nature of problem: This software provides a library of models for the simulation of the steady state mass and momentum transport in a multi-species gas mixture, possibly in a porous medium. The software is particularly designed to be used as the mass-transport library for the modeling of solid oxide fuel cells (SOFC). When supplemented with other sub-models, such as thermal and charge-transport ones, it allows the prediction of the cell polarization curve and hence the cell performance.Solution method: Standard finite volume method (FVM) is used for solving all the conservation equations. The pressure-velocity coupling is solved using the SIMPLE algorithm (possibly adding a porous drag term if required). The mass transport can be calculated using different alternative models, namely Fick, Maxwell–Stefan or dusty gas model. The code adopts a segregated method to solve the resulting linear system of equations. The different regions of the SOFC, namely gas channels, electrodes and electrolyte, are solved independently, and coupled through boundary conditions.Restrictions: When extremely large species fluxes are considered, current implementation of the Neumann and Robin boundary conditions do not avoid negative values of molar and/or mass fractions, which finally end up with numerical instability. However this never happened in the documented runs. Eventually these boundary conditions could be reformulated to become more robust.Running time: From seconds to hours depending on the mesh size and number of species. For example, on a 64 bit machine with Intel Core Duo T8300 and 3 GBytes of RAM, the provided test run requires less than 1 second.     

Combustion synthesis and electrochemical characterisation of Pt–Ru–Ni anode electrocatalyst for PEMFC

The present work studies the synthesis by the combustion method of an anode catalyst for protonic exchange membrane fuel cell (PEMFC) employing two different fuels, that is, urea and sucrose. The unsupported pure solid solution Pt_0.6Ru_0.3Ni_0.1 was selected from a calculated and empirical ternary phase diagram, which was previously studied. Theoretically, this particular composition exhibited single-phase features without the presence of secondary phases as RuO₃ and NiO, regarding the oxygen partial pressure conditions generated during the combustion synthesis. In the X-ray diffraction (XRD) analysis of the nanoparticles synthesized by using two different fuels, a single-phase Pt_0.6Ru_0.3Ni_0.1 alloy was detected. However, the X-ray photoelectron spectroscopy (XPS) studies showed that the nanoparticles prepared could present an onion-shell structure, in the case of the sample synthesized with sucrose as fuel, the external layers are partially constituted by Ni hydroxides, which can exhibit an active role in the hydrogen oxidation reaction. The electrochemical behaviour of this unsupported catalyst was performed by preparing MEAs, which were evaluated using a I–V polarisation curve test. The results obtained indicated that the nanoparticles prepared by sucrose have better performance, 260 mW/cm², than those prepared using urea, 170 mW/cm². These results are discussed in relation with the hydrogen oxidation mechanism. The results obtained reveal combustion synthesis as an appropriate method for preparing PEMFC electrocatalysts, due to its versatility, simplicity and fastness.     

A Narrowing-based Instantiation Rule for Rewriting-based Fold/Unfold Transformations

In this paper we show how to transfer some developments done in the field of functionallogic programming (FLP) to a pure functional setting (FP). More exactly, we propose a complete fold/unfold based transformation system for optimizing lazy functional programs. Our main contribution is the definition of a safe instantiation rule which is used to enable effective unfolding steps based on rewriting. Since instantiation has been traditionally considered problematic in FP, we take advantage of previous experiences in the more general setting of FLP where instantiation is naturally embedded into an unfolding rule based on narrowing. Inspired by the so called needed narrowing strategy, our instantiation rule inherits the best properties of this refinement of narrowing. Our proposal optimizes previous approaches (that require more transformation effort) defined in the specialized literature of pure FP by anticipating bindings on unifiers used to instantiate a given program rule and by generating redexes at different positions on instantiated rules in order to enable subsequent unfolding steps. As a consequence, our correct/complete technique avoids redundant rules and preserves the natural structure of programs.     

Nonlinear properties of tapered laser cavities

The nonlinear phenomena accompanying the process of light generation in high-power tapered semiconductor lasers are studied using a combination of simulation and experiment. Optical pumping, electrical overpumping, filamentation, and spatial hole burning are shown to be the key nonlinear phenomena influencing the operation of tapered lasers at high output powers. In the particular tapered laser studied, the optical pumping effect is found to have the largest impact on the output beam quality. The simulation model used in this study employs the wide-angle finite-difference beam propagation method for the analysis of the optical propagation within the cavity. Quasi-three-dimensional (3-D) thermal and electrical models are used for the calculation of the 3-D distributions of the temperature, electrons, holes, and electrical potential. The simulation results reproduce key features and the experimental trends.     

Influence of the gasket materials on the clamping pressure distribution in a PEM water electrolyzer: Bolt torques and operation mode in pre-conditioning

To keep optimally connected, all electrolysis cell elements is one of the most important design criteria. The optimal distribution of the clamping points is crucial to increasing cell performance. In this work, the compression pressure distribution inside of a 25 cm² PEM electrolysis cell was evaluated, using different materials: Teflon®, Viton®, ethylene propylene diene monomer rubber (EPDM), and nitrile rubber. Sealing material evaluation was performed taking as performance indicators: total compressed area (%) and compression pressure, for different torques applied. Pressure distribution was obtained by using pressure-sensitive films, analyzing the distribution of pressure points from three-dimensional plots (3D), and quantifying intensities of the images obtained. Results showed that pressure points distribution depends on the stiffness and thickness of the gasket materials. For a tightening torque of 3.70 N m, a pressure of 2.23 MPa is obtained with 85% of the membrane area compressed using nitrile rubber-EPDM gaskets.     

A cost-effective heuristic to schedule local and remote memory in cluster computers

Cluster computers represent a cost-effective alternative solution to supercomputers. In these systems, it is common to constrain the memory address space of a given processor to the local motherboard. Constraining the system in this way is much cheaper than using a full-fledged shared memory implementation among motherboards. However, memory usage among motherboards can be unfairly balanced.