Automated Parallelization of Discrete State-Space Generation

We consider the problem of generating a large state-space in a distributed fashion. Unlike previously proposed solutions that partition the set of reachable states according to a hashing function provided by the user, we explore heuristic methods that completely automate the process. The first step is an initial random walk through the state space to initialize a search tree, duplicated in each processor. Then, the reachability graph is built in a distributed way, using the search tree to assign each newly found state to classes assigned to the available processors. Furthermore, we explore two remapping criteria that attempt to balance memory usage or future workload, respectively. We show how the cost of computing the global snapshot required for remapping will scale up for system sizes in the foreseeable future. An extensive set of results is presented to support our conclusions that remapping is extremely beneficial.     

Cathodic processes in the leaching and electrochemistry of covellite in mixed sulfate–chloride media

The cathodic processes that occur on a covellite (CuS) surface in mixed sulfate–chloride solutions in the absence and presence of copper(II) ions have been studied using potentiostatic transients and cyclic voltammetry at rotating disk electrodes in the potential range 0.3–0.7 V (versus SHE). This range is relevant to the oxidative leaching of this copper mineral in sulfate and chloride lixiviants. Variations in the concentrations of sulfate and chloride ions had a small effect on the cathodic reduction of covellite in the potential range of 0.5–0.3 V, although the presence of chloride ion resulted in a significant increase in the anodic current on the reverse sweep. On the other hand, addition of copper(II) ions resulted in enhanced cathodic currents and subsequent anodic currents in both sulfate and chloride solutions due to reduction of covellite to an undefined reduced copper sulfide species. Reduction of copper(II) to copper(I) ions becomes the preferred cathodic reaction as the concentration of chloride ions increases, becoming mass transport controlled at a rotating disc electrode at potentials below about 0.4 V. Potentiostatic measurements at potentials negative to the mixed potential in acidic chloride solutions have shown that reduction of copper(II) ions is reversible and have been used to estimate the rate of oxidative dissolution of the mineral which value agrees reasonably well with previously reported leaching rates under similar conditions. Reduction of dissolved oxygen has been found to be very much slower that that of copper(II) ions under ambient conditions.     

Designing collaborative,constructionist and contextual applications for handheld devices

This paper explores current applications for handheld devices and questions which of these make full use of the unique attributes of handheld devices in order to facilitate learning in a pedagogically sensible manner. In order to do so, the paper presents a functional framework which analyses handheld application in relation to their use as well as the pedagogical underpinning, if any, that informs their development. Our framework currently consists of seven distinct categories of application, which we term: administrative, referential, interactive, microworld, data collection, location aware and collaborative. We argue that three categories, namely data collection, location aware and collaborative, are particularly suited to learning with handheld devices when they are informed by collaborative, contextual and constructionist learning theories. Furthermore, we contend that applications of the type just outlined deserve further research since they are not attempting to replicate, or even augment, existing learning scenarios but rather they try to create new learning opportunities which would not be possible without (mobile) technology. Finally, the authors introduce a number of applications and learning scenarios that they have developed for handheld devices and explain their position within the framework.     

Characterizing Strong Stability Preserving Additive Runge-Kutta Methods

Space discretization of some time dependent partial differential equations give rise to ordinary differential equations containing additive terms with different stiffness properties. In these situations, additive Runge-Kutta (additive RK) methods are used. For additive RK methods the curve of absolute monotonicity gives stepsize restrictions for monotonicity. Necessary conditions for nontrivial curves of absolute monotonicity are the nonnegativity of the additive RK coefficients and some inequalities on some incidence matrices. In this paper we characterize strong stability preserving additive Runge-Kutta methods giving some order barriers and structural properties. Research supported by the Ministerio de Educación y Ciencia, Project MTM2005-03894.     

UAVs Integration in the SWIM Based Architecture for ATM

The System Wide Information Management (SWIM) approach has been conceived to overcome the capacity and flexibility limitations of the current ATM systems. On the other hand the commercial applications of Unmanned Aerial Vehicles (UAVs) require the integration of these vehicles in the ATM. From this perspective, the unavoidable modernization of the ATM is seen as an opportunity to integrate the UAVs with the rest of the air traffic. This paper is devoted to study the feasibility and impact of the aggregation of UAVs on the future ATM supported by a SWIM inspired architecture. Departing from the existing technical documents that describe the fundamentals of SWIM we have explored the compatibility with a potential UAVs integration and also explored how the UAVs could help to improve the future ATM system. We will use the weather application as an example in both cases.     

Boosting k-nearest neighbor classifier by means of input space projection

The k-nearest neighbors classifier is one of the most widely used methods of classification due to several interesting features, such as good generalization and easy implementation. Although simple, it is usually able to match, and even beat, more sophisticated and complex methods. However, no successful method has been reported so far to apply boosting to k-NN. As boosting methods have proved very effective in improving the generalization capabilities of many classification algorithms, proposing an appropriate application of boosting to k-nearest neighbors is of great interest.Ensemble methods rely on the instability of the classifiers to improve their performance, as k-NN is fairly stable with respect to resampling, these methods fail in their attempt to improve the performance of k-NN classifier. On the other hand, k-NN is very sensitive to input selection. In this way, ensembles based on subspace methods are able to improve the performance of single k-NN classifiers. In this paper we make use of the sensitivity of k-NN to input space for developing two methods for boosting k-NN. The two approaches modify the view of the data that each classifier receives so that the accurate classification of difficult instances is favored.The two approaches are compared with the classifier alone and bagging and random subspace methods with a marked and significant improvement of the generalization error. The comparison is performed using a large test set of 45 problems from the UCI Machine Learning Repository. A further study on noise tolerance shows that the proposed methods are less affected by class label noise than the standard methods.     

Influence of β‐nucleation on polymorphism and properties in random copolymers and terpolymers of propylene

The competition between α, β, and γ polymorphs has been studied in several random copolymers and terpolymers of propylene, by performing X‐ray diffraction and differential scanning calorimetry experiments. Formation of β‐crystals, achieved by the addition of a β‐nucleating agent, was found to be highly dependent on comonomer type and crystallization conditions. Additionally, the mechanical properties have been evaluated from stress‐strain, microhardness and dynamic‐mechanical thermal analyses. POLYM. ENG. SCI., 2012. © 2012 Society of Plastics Engineers     

Mechanical properties of freely suspended semiconducting graphene-like layers based on MoS2

We fabricate freely suspended nanosheets of molybdenum disulphide (MoS₂) which are characterized by quantitative optical microscopy and high-resolution friction force microscopy. We study the elastic deformation of freely suspended nanosheets of MoS₂ using an atomic force microscope. The Young''s modulus and the initial pre-tension of the nanosheets are determined by performing a nanoscopic version of a bending test experiment. MoS₂ sheets show high elasticity and an extremely high Young''s modulus (0.30 TPa, 50% larger than steel). These results make them a potential alternative to graphene in applications requiring flexible semiconductor materials.PACS, 73.61.Le, other inorganic semiconductors, 68.65.Ac, multilayers, 62.20.de, elastic moduli, 81.40.Jj, elasticity and anelasticity, stress-strain relations.