1,669 research outputs found

    Finding co-solvers on Twitter, with a little help from Linked Data

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    In this paper we propose a method for suggesting potential collaborators for solving innovation challenges online, based on their competence, similarity of interests and social proximity with the user. We rely on Linked Data to derive a measure of semantic relatedness that we use to enrich both user profiles and innovation problems with additional relevant topics, thereby improving the performance of co-solver recommendation. We evaluate this approach against state of the art methods for query enrichment based on the distribution of topics in user profiles, and demonstrate its usefulness in recommending collaborators that are both complementary in competence and compatible with the user. Our experiments are grounded using data from the social networking service Twitter.com

    Multi-score Learning for Affect Recognition: the Case of Body Postures

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    An important challenge in building automatic affective state recognition systems is establishing the ground truth. When the groundtruth is not available, observers are often used to label training and testing sets. Unfortunately, inter-rater reliability between observers tends to vary from fair to moderate when dealing with naturalistic expressions. Nevertheless, the most common approach used is to label each expression with the most frequent label assigned by the observers to that expression. In this paper, we propose a general pattern recognition framework that takes into account the variability between observers for automatic affect recognition. This leads to what we term a multi-score learning problem in which a single expression is associated with multiple values representing the scores of each available emotion label. We also propose several performance measurements and pattern recognition methods for this framework, and report the experimental results obtained when testing and comparing these methods on two affective posture datasets

    Two Electrons in a Quantum Dot: A Unified Approach

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    Low-lying energy levels of two interacting electrons confined in a two-dimensional parabolic quantum dot in the presence of an external magnetic field have been revised within the frame of a novel model. The present formalism, which gives closed algebraic solutions for the specific values of magnetic field and spatial confinement length, enables us to see explicitly individual effects of the electron correlation.Comment: 14 page

    Possible Dibaryons with Strangeness s=-5

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    In the framework of RGMRGM, the binding energy of the six quark system with strangeness s=-5 is systematically investigated under the SU(3) chiral constituent quark model. The single ΞΩ\Xi^*\Omega channel calculation with spins S=0 and 3 and the coupled ΞΩ\Xi\Omega and ΞΩ\Xi^*\Omega channel calculation with spins S=1 and 2 are considered, respectively. The results show following observations: In the spin=0 case, ΞΩ\Xi^* \Omega is a bound dibaryon with the binding energy being 80.092.4MeV80.0 \sim 92.4 MeV. In the S=1 case, ΞΩ\Xi\Omega is also a bound dibaryon. Its binding energy is ranged from 26.2MeV26.2 MeV to 32.9MeV32.9 MeV. In the S=2 and S=3 cases, no evidence of bound dibaryons are found. The phase shifts and scattering lengths in the S=0 and S=1 cases are also given.Comment: 10 pages, late

    Universal behavior of localization of residue fluctuations in globular proteins

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    Localization properties of residue fluctuations in globular proteins are studied theoretically by using the Gaussian network model. Participation ratio for each residue fluctuation mode is calculated. It is found that the relationship between participation ratio and frequency is similar for all globular proteins, indicating a universal behavior in spite of their different size, shape, and architecture.Comment: 4 pages, 3 figures. To appear in Phys. Rev.

    Donor states in modulation-doped Si/SiGe heterostructures

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    We present a unified approach for calculating the properties of shallow donors inside or outside heterostructure quantum wells. The method allows us to obtain not only the binding energies of all localized states of any symmetry, but also the energy width of the resonant states which may appear when a localized state becomes degenerate with the continuous quantum well subbands. The approach is non-variational, and we are therefore also able to evaluate the wave functions. This is used to calculate the optical absorption spectrum, which is strongly non-isotropic due to the selection rules. The results obtained from calculations for Si/Si1x_{1-x}Gex_x quantum wells allow us to present the general behavior of the impurity states, as the donor position is varied from the center of the well to deep inside the barrier. The influence on the donor ground state from both the central-cell effect and the strain arising from the lattice mismatch is carefully considered.Comment: 17 pages, 10 figure

    The Intentional Use of Service Recovery Strategies to Influence Consumer Emotion, Cognition and Behaviour

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    Service recovery strategies have been identified as a critical factor in the success of. service organizations. This study develops a conceptual frame work to investigate how specific service recovery strategies influence the emotional, cognitive and negative behavioural responses of . consumers., as well as how emotion and cognition influence negative behavior. Understanding the impact of specific service recovery strategies will allow service providers' to more deliberately and intentionally engage in strategies that result in positive organizational outcomes. This study was conducted using a 2 x 2 between-subjects quasi-experimental design. The results suggest that service recovery has a significant impact on emotion, cognition and negative behavior. Similarly, satisfaction, negative emotion and positive emotion all influence negative behavior but distributive justice has no effect

    A computational analysis of lower bounds for big bucket production planning problems

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    In this paper, we analyze a variety of approaches to obtain lower bounds for multi-level production planning problems with big bucket capacities, i.e., problems in which multiple items compete for the same resources. We give an extensive survey of both known and new methods, and also establish relationships between some of these methods that, to our knowledge, have not been presented before. As will be highlighted, understanding the substructures of difficult problems provide crucial insights on why these problems are hard to solve, and this is addressed by a thorough analysis in the paper. We conclude with computational results on a variety of widely used test sets, and a discussion of future research
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