Negotiating SLAs-An Approach for a Generic Negotiation Framework for WS-Agreement

The current Web Services Agreement specification draft proposes a simple request-response protocol for agreement creation only addressing bilateral offer exchanges. This paper proposes a framework augmenting this WS-Agreement to enable negotiations according to a variety of bilateral and multilateral negotiation protocols. The framework design is based on a thorough analysis of taxonomies for negotiations from the literature in order to allow for capturing a variety of different negotiation models within a single, WS-Agreement compatible, framework. In order to provide for the intended flexibility, the proposed protocol takes a two-stage approach: a meta-protocol is conducted among interested parties to agree on a common negotiation protocol first before the real negotiation is carried out in the second step due to the protocol established in the first step.     

Perceptions of caring. Comparison of antepartum and postpartum patients

An exploratory, comparative survey design was used to describe and compare similarities and differences in perception of caring behaviors between hospitalized antepartum and short-stay postpartum patients. Forty-two patients completed the 63-item Caring Behavior Assessment instrument (CBA). The scale, based on Watson's theory of caring, contains seven categories. There were no statistically significant differences in age, education, gravida, or para between the two groups. Significantly more women in the postpartum group were married. There were no statistically significant differences or correlations in the total CBA scores and the demographic variables. No statistically significant differences in total CBA scores were found between antepartum participants and postpartum participants. These findings corroborate the results of "caring" studies in other patient populations, that satisfying basic needs--that is, evidence of technical knowledge and skills--is more important to patients than meeting higher order needs.     

Swarm Intelligence Approaches for Grid Load Balancing

With the rapid growth of data and computational needs, distributed systems and computational Grids are gaining more and more attention. The huge amount of computations a Grid can fulfill in a specific amount of time cannot be performed by the best supercomputers. However, Grid performance can still be improved by making sure all the resources available in the Grid are utilized optimally using a good load balancing algorithm. This research proposes two new distributed swarm intelligence inspired load balancing algorithms. One algorithm is based on ant colony optimization and the other algorithm is based on particle swarm optimization. A simulation of the proposed approaches using a Grid simulation toolkit (GridSim) is conducted. The performance of the algorithms are evaluated using performance criteria such as makespan and load balancing level. A comparison of our proposed approaches with a classical approach called State Broadcast Algorithm and two random approaches is provided. Experimental results show the proposed algorithms perform very well in a Grid environment. Especially the application of particle swarm optimization, can yield better performance results in many scenarios than the ant colony approach.     

Superquadric glyphs for symmetric second-order tensors

Symmetric second-order tensor fields play a central role in scientific and biomedical studies as well as in image analysis and feature-extraction methods. The utility of displaying tensor field samples has driven the development of visualization techniques that encode the tensor shape and orientation into the geometry of a tensor glyph. With some exceptions, these methods work only for positive-definite tensors (i.e. having positive eigenvalues, such as diffusion tensors). We expand the scope of tensor glyphs to all symmetric second-order tensors in two and three dimensions, gracefully and unambiguously depicting any combination of positive and negative eigenvalues. We generalize a previous method of superquadric glyphs for positive-definite tensors by drawing upon a larger portion of the superquadric shape space, supplemented with a coloring that indicates the quadratic form (including eigenvalue sign). We show that encoding arbitrary eigenvalue magnitudes requires design choices that differ fundamentally from those in previous work on traceless tensors that arise in the study of liquid crystals. Our method starts with a design of 2-D tensor glyphs guided by principles of scale-preservation and symmetry, and creates 3-D glyphs that include the 2-D glyphs in their axis-aligned cross-sections. A key ingredient of our method is a novel way of mapping from the shape space of three-dimensional symmetric second-order tensors to the unit square. We apply our new glyphs to stress tensors from mechanics, geometry tensors and Hessians from image analysis, and rate-of-deformation tensors in computational fluid dynamics.     

Crease Surfaces: From Theory to Extraction and Application to Diffusion Tensor MRI

Crease surfaces are two-dimensional manifolds along which a scalar field assumes a local maximum (ridge) or a local minimum (valley) in a constrained space. Unlike isosurfaces, they are able to capture extremal structures in the data. Creases have a long tradition in image processing and computer vision, and have recently become a popular tool for visualization. When extracting crease surfaces, degeneracies of the Hessian (i.e., lines along which two eigenvalues are equal) have so far been ignored. We show that these loci, however, have two important consequences for the topology of crease surfaces: First, creases are bounded not only by a side constraint on eigenvalue sign, but also by Hessian degeneracies. Second, crease surfaces are not, in general, orientable. We describe an efficient algorithm for the extraction of crease surfaces which takes these insights into account and demonstrate that it produces more accurate results than previous approaches. Finally, we show that diffusion tensor magnetic resonance imaging (DT-MRI) stream surfaces, which were previously used for the analysis of planar regions in diffusion tensor MRI data, are mathematically ill-defined. As an example application of our method, creases in a measure of planarity are presented as a viable substitute.     

The impact of trust,risk and optimism bias on E-file adoption

One of congress’ goals for 2007 was for 80% of all tax and informational returns to be filed electronically. However, to date that lofty goal has fallen well short. This research proposes a model of e-filing adoption. To test the model a survey is administered to 260 participants. The instrument assesses citizen perceptions of trust, risk and optimism bias. Structural equation modeling is used to evaluate the relationships between these three concepts and intention to use. The results indicate that trust of the Internet, trust of the e-filer, perceived risk and optimism bias all have an impact on intention to use e-filing. Implications for practice and research are discussed.     

Discovery of sound sources by an autonomous mobile robot

In this work, we describe an autonomous mobile robotic system for finding, investigating, and modeling ambient noise sources in the environment. The system has been fully implemented in two different environments, using two different robotic platforms and a variety of sound source types. Making use of a two-step approach to autonomous exploration of the auditory scene, the robot first quickly moves through the environment to find and roughly localize unknown sound sources using the auditory evidence grid algorithm. Then, using the knowledge gained from the initial exploration, the robot investigates each source in more depth, improving upon the initial localization accuracy, identifying volume and directivity, and, finally, building a classification vector useful for detecting the sound source in the future.