TangiWheel: A Widget for Manipulating Collections on Tabletop Displays Supporting Hybrid Input Modality

In this paper we present TangiWheel,a collection manipulation widget for tabletop displays.Our implementation is flexible,allowing either multi-touch or interaction,or even a hybrid scheme to better suit user choice and convenience.Different TangiWheel aspects and features are compared with other existing widgets for collection manipulation.The study reveals that TangiWheel is the first proposal to support a hybrid input modality with large resemblance levels between touch and tangible interaction styles.Several experiments were conducted to evaluate the techniques used in each input scheme for a better understanding of tangible surface interfaces in complex tasks performed by a single user (e.g.,involving a typical master-slave exploration pattern).The results show that tangibles perform significantly better than fingers,despite dealing with a greater number of interactions,in situations that require a large number of acquisitions and basic manipulation tasks such as establishing location and orientation.However,when users have to perform multiple exploration and selection operations that do not require previous basic manipulation tasks,for instance when collections are fixed in the interface layout,touch input is significantly better in terms of required time and number of actions.Finally,when a more elastic collection layout or more complex additional insertion or displacement operations are needed,the hybrid and tangible approaches clearly outperform finger-based interactions.     

A co-evolutionary differential evolution algorithm for solving min–max optimization problems implemented on GPU using C-CUDA

Several areas of knowledge are being benefited with the reduction of the computing time by using the technology of graphics processing units (GPU) and the compute unified device architecture (CUDA) platform. In case of evolutionary algorithms, which are inherently parallel, this technology may be advantageous for running experiments demanding high computing time. In this paper, we provide an implementation of a co-evolutionary differential evolution (DE) algorithm in C-CUDA for solving min–max problems. The algorithm was tested on a suite of well-known benchmark optimization problems and the computing time has been compared with the same algorithm implemented in C. Results demonstrate that the computing time can significantly be reduced and scalability is improved using C-CUDA. As far as we know, this is the first implementation of a co-evolutionary DE algorithm in C-CUDA.     

Open Innovation in an Enterprise 3.0 framework: Three case studies

Nowadays, especially after the recent financial downturn, companies are looking for much more efficient and creative business processes. They need to place better solutions in the market in a less time with less cost. There is a general intuition that communication and collaboration, especially mixed with Web 2.0 approach within companies and ecosystems, can boost the innovation process with positive impacts on business indicators. Open Innovation within an Enterprise 2.0 context is a one of the most chosen paradigm for improving the innovation processes of enterprises, based on the collaborative creation and development of ideas and products. The key feature of this new paradigm is that the knowledge is exploited in a collaborative way flowing not only among internal sources, i.e. R&D departments, but also among external ones as other employees, customers, partners, etc. In this paper we show how an ontology-based analysis of plain text can provide a semantic contextualization of content support tasks, such as finding semantic distance between contents, and can help in creating relations between people with shared knowledge and interests. Along this paper we will present the results obtained by the adoption of this technology in a large corporate environment like Bankinter, a financial institution, Telefonica I+D, an international telecommunication firm and Repsol, a major oil company in Spain.     

Ontology-based semantic similarity: A new feature-based approach

Estimation of the semantic likeness between words is of great importance in many applications dealing with textual data such as natural language processing, knowledge acquisition and information retrieval. Semantic similarity measures exploit knowledge sources as the base to perform the estimations. In recent years, ontologies have grown in interest thanks to global initiatives such as the Semantic Web, offering an structured knowledge representation. Thanks to the possibilities that ontologies enable regarding semantic interpretation of terms many ontology-based similarity measures have been developed. According to the principle in which those measures base the similarity assessment and the way in which ontologies are exploited or complemented with other sources several families of measures can be identified. In this paper, we survey and classify most of the ontology-based approaches developed in order to evaluate their advantages and limitations and compare their expected performance both from theoretical and practical points of view. We also present a new ontology-based measure relying on the exploitation of taxonomical features. The evaluation and comparison of our approach’s results against those reported by related works under a common framework suggest that our measure provides a high accuracy without some of the limitations observed in other works.     

Cell formation in group technology using constraint programming and Boolean satisfiability

Cell formation consists in organizing a plant as a set of cells, each of them containing machines that process similar types or families of parts. The idea is to minimize the part flow among cells in order to reduce costs and increase productivity. The literature presents different approaches devoted to solve this problem, which are mainly based on mathematical programming and on evolutionary computing. Mathematical programming can guarantee a global optimal solution, however at a higher computational cost than an evolutionary algorithm, which can assure a good enough optimum in a fixed amount of time. In this paper, we model and solve this problem by using state-of-the-art constraint programming (CP) techniques and Boolean satisfiability (SAT) technology. We present different experimental results that demonstrate the efficiency of the proposed optimization models. Indeed, CP and SAT implementations are able to reach the global optima in all tested instances and in competitive runtime.     

Two-level classifier ensembles for credit risk assessment

Many techniques have been proposed for credit risk assessment, from statistical models to artificial intelligence methods. During the last few years, different approaches to classifier ensembles have successfully been applied to credit scoring problems, demonstrating to be generally more accurate than single prediction models. The present paper goes one step beyond by introducing composite ensembles that jointly use different strategies for diversity induction. Accordingly, the combination of data resampling algorithms (bagging and AdaBoost) and attribute subset selection methods (random subspace and rotation forest) for the construction of composite ensembles is explored with the aim of improving the prediction performance. The experimental results and statistical tests show that this new two-level classifier ensemble constitutes an appropriate solution for credit scoring problems, performing better than the traditional single ensembles and very significantly better than individual classifiers.     

Influence of oxygen content on some properties of Nb3Sn tape used for superconducting transmission lines

The influence of the presence of oxygen in the Nb-Zr substrate upon some physical and mechanical properties of the Nb-ZrO₂ substrate and/or Nb₃Sn tape superconductor prepared from such a substrate has been studied. The results have shown that the Nb₃Sn grains are much finer in the case of Nb-ZrO₂, than those obtained on Nb-Zr substrate. As a result, both the electrical and mechanical properties have been substantially improved. The critical current at a field of 5 T increased by between 100 and 200 %, the alternating current losses decreased by about one order of magnitude, the tensile strength increased by about a factor of three and the microhardness value also increased by about a factor of three for oxygen contents in the range 0.03 to 0.70 wt%. The specific resistance of this substrate increased at the same time from 17 to 22 cm and the relative elongation decreased from 5 to 3 %.     

Combined radiometric and electrochemical study of the behaviour of Tc (vii) ions at gold and platinized surfaces in acidic media

The sorption and deposition of technetium species formed from TcO ₄ ^– at gold and platinized surfaces was followed by a coupledin situ radiometric and electrochemical technique. It was found: (i) that a layer of TcO₂ species is formed preceding the massive deposition of technetium species, and (ii) that the deposition process is not connected with hydrogen evolution or reaction with adsorbed hydrogen as has been assumed in the literature. An important new finding, the electrocatalytic reduction of ClO₄ ions at surfaces covered by technetium species, was demonstrated on the basis of a comparative study of the phenomena observed in H₂SO₄ and HClO₄ supporting electrolytes.This paper is dedicated to Professor Brian E. Conway on the occasion of his 65th birthday, and in recognition of his outstanding contribution to electrochemisty.