Calculation of film stress from pitch measurements in LCD panel manufacturing

A method based on inverting a finite element model is presented for determining film stress from pitch changes before and after a film deposition step in liquid‐crystal display panel manufacturing. It differs from the conventional methods by making use of in‐plane deformation rather than out‐of‐plane measurements to calculate film stress. The resulting film stress is confounded with glass structural relaxation. Measurements of out‐of‐plane deformation at the edge of the sheet can be used with the pitch measurements to separate the effects of glass structural relaxation and film stress.     

A Multicast-Enabled Delivery Framework for QoE Assurance of Over-The-Top Services in Multimedia Access Networks

Over-The-Top (OTT) video services are becoming more and more important in today’s broadband access networks. While original OTT services only offered short duration medium quality videos, more recently, premium content such as high definition full feature movies and live video are offered as well. For operators, who see the potential in providing Quality of Experience (QoE) assurance for an increased revenue, this introduces important new network management challenges. Traditional network management paradigms are often not suited for ensuring QoE guarantees as the provider does not have any control on the content’s origin. In this article, we focus on the management of an OTT-based video service. We present a loosely coupled architecture that can be seamlessly integrated into an existing OTT-based video delivery architecture. The framework has the goal of resolving the network bottleneck that might occur from high peaks in the requests for OTT video services. The proposed approach groups the existing Hypertext Transfer Protocol (HTTP) based video connections to be multicasted over an access network’s bottleneck and then splits them again to reconstruct the original HTTP connections. A prototype of this architecture is presented, which includes the caching of videos and incorporates retransmission schemes to ensure robust transmission. Furthermore, an autonomic algorithm is presented that allows to intelligently select which OTT videos need to be multicasted by making a remote assessment of the cache state to predict the future availability of content. The approach was evaluated through both simulation and large scale emulation and shows a significant gain in scalability of the prototype compared to a traditional video delivery architecture.     

Evolutionary search for understanding movement dynamics on mixed networks

This paper describes an approach to using evolutionary algorithms for reasoning about paths through network data. The paths investigated in the context of this research are functional paths wherein the characteristics (e.g., path length, morphology, location) of the path are integral to the objective purpose of the path. Using two datasets of combined surface and road networks, the research demonstrates how an evolutionary algorithm can be used to reason about functional paths. We present the algorithm approach, the parameters and fitness function that drive the functional aspects of the path, and an approach for using the algorithm to respond to dynamic changes in the search space. The results of the search process are presented in terms of the overall success based on the response of the search to variations in the environment and through the use of an occupancy grid characterizing the overall search process. The approach offers a great deal of flexibility over more conventional heuristic path finding approaches and offers additional perspective on dynamic network analysis.     

'Tacitus' project: identifying multi-sensory perceptions in creative 3D practice for the development of a haptic computing system for applied artists

This paper outlines the major motivating factors concerning a novel collaborative project between Edinburgh College of Art and Edinburgh Virtual Environment Centre. The Tacitus project will investigate the use of multi-modal virtual environments, specifically, the haptic (touch) modality, with regards to the creative processes employed by designers working within the field of applied arts. The salient areas of research are described, and the methods by which information regarding these areas will be obtained are considered. Initial investigations have revealed a strong need to mimic the traditional applied artists' workspaces, with co-location of visual and haptic cues a priority.     

Integrated Use of a Continuous Simulation Model and Multi-Attribute Decision-Making for Ranking Urban Watershed Management Alternatives

The objective of this paper is to introduce a continuous simulation-based screening procedure for ranking urban watershed management alternatives using multi-attribute decision making (MADM). The procedure integrates continuous urban runoff simulation results from the United States Environmental Protection Agency’s Storm Water Management Model (SWMM) with the use of an alternative evaluation index (AEI) and MADM techniques, following the driver-pressure-state-impact-response (DPSIR) approach. The analytic hierarchy process estimates the weights of the criteria, and SWMM results are used to quantify the effects of the management alternatives on water quantity and quality metrics. In addition, the tendency of AEI to reflect resident preferences toward management objectives is incorporated to include stakeholder participation in the decision-making process. This systematic decision support process is demonstrated for a Korean urban watershed. According to the AEI, seven alternatives were divided into three groups: poor (0∼0.3), acceptable (0.3∼0.6), and good (0.6∼1). The use of multiple MADM techniques provided a consistency check. The demonstration illustrates the ability of the continuous simulation-based MADM approach to provide decision makers with a ranking of suitable urban watershed management alternatives which incorporate stakeholder feedback.     

Using non-ideal gates to implement universal quantum computing between uncoupled qubits

In many physical systems, when implementing quantum gate operations unavoidable global and relative phases occur as by-products due to the internal structure of the governing Hamiltonian. To correct, additional phase rotation gates are used, which increases the computational overhead. Here, we show how these phase by-products can actually be used to our advantage by using them to implement universal quantum computing between qubits not directly coupled to each other. The gate operations, CNOT, Toffoli, and swap gates, require much less computational overhead than present schemes, and are achieved with fidelity greater than 99%. We then present a linear nearest-neighbor architecture that takes full advantage of the phase by-products, and we show how to implement gates from a universal set efficiently in this layout. In this scheme gate operations are realized by only varying a single control parameter per data qubit, and the ability to tune couplings is not required.     

Using k-nn and discriminant analyses to classify rain forest types in a Landsat TM image over northern Costa Rica

Conservation and land use planning in humid tropical lowland forests urgently need accurate remote sensing techniques to distinguish among floristically different forest types. We investigated the degree to which floristically and structurally defined Costa Rican lowland rain forest types can be accurately discriminated by a non-parametric k nearest neighbors (k-nn) classifier or linear discriminant analysis. Pixel values of Landsat Thematic Mapper (TM) image and Shuttle Radar Topography Mission (SRTM) elevation model extracted from segments or from 5 × 5 pixel windows were employed in the classifications. 104 field plots were classified into three floristic and one structural type of forest (regrowth forest). Three floristically defined forest types were formed through clustering the old-growth forest plots (n = 52) by their species specific importance values. An error assessment of the image classification was conducted via cross-validation and error matrices, and overall percent accuracy and Kappa scores were used as measures of accuracy. Image classification of the four forest types did not adequately distinguish two old-growth forest classes, so they were merged into a single forest class. The resulting three forest classes were most accurately classified by the k-nn classifier using segmented image data (overall accuracy 91%). The second best method, with respect to accuracy, was the k-nn with 5 × 5 pixel windows data (89% accuracy), followed by the canonical discriminant analysis using the 5 × 5 pixel window data (86%) and the segment data (82%). We conclude the k-nn classifier can accurately distinguish floristically and structurally different rain forest types. The classification accuracies were higher for the k-nn classifier than for the canonical discriminant analysis, but the differences in Kappa scores were not statistically significant. The segmentation did not increase classification accuracy in this study.     

A methodology for quadrilateral finite element mesh coarsening

High fidelity finite element modeling of continuum mechanics problems often requires using all quadrilateral or all hexahedral meshes. The efficiency of such models is often dependent upon the ability to adapt a mesh to the physics of the phenomena. Adapting a mesh requires the ability to both refine and/or coarsen the mesh. The algorithms available to refine and coarsen triangular and tetrahedral meshes are very robust and efficient. However, the ability to locally and conformally refine or coarsen all quadrilateral and all hexahedral meshes presents many difficulties. Some research has been done on localized conformal refinement of quadrilateral and hexahedral meshes. However, little work has been done on localized conformal coarsening of quadrilateral and hexahedral meshes. A general method which provides both localized conformal coarsening and refinement for quadrilateral meshes is presented in this paper. This method is based on restructuring the mesh with simplex manipulations to the dual of the mesh. In addition, this method appears to be extensible to hexahedral meshes in three dimensions. Sandia National Laboratories is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy under Contract DE-AC04-94AL85000.     

A Numerical Study of Diagonally Split Runge–Kutta Methods for PDEs with Discontinuities

Diagonally split Runge–Kutta (DSRK) time discretization methods are a class of implicit time-stepping schemes which offer both high-order convergence and a form of nonlinear stability known as unconditional contractivity. This combination is not possible within the classes of Runge–Kutta or linear multistep methods and therefore appears promising for the strong stability preserving (SSP) time-stepping community which is generally concerned with computing oscillation-free numerical solutions of PDEs. Using a variety of numerical test problems, we show that although second- and third-order unconditionally contractive DSRK methods do preserve the strong stability property for all time step-sizes, they suffer from order reduction at large step-sizes. Indeed, for time-steps larger than those typically chosen for explicit methods, these DSRK methods behave like first-order implicit methods. This is unfortunate, because it is precisely to allow a large time-step that we choose to use implicit methods. These results suggest that unconditionally contractive DSRK methods are limited in usefulness as they are unable to compete with either the first-order backward Euler method for large step-sizes or with Crank–Nicolson or high-order explicit SSP Runge–Kutta methods for smaller step-sizes. We also present stage order conditions for DSRK methods and show that the observed order reduction is associated with the necessarily low stage order of the unconditionally contractive DSRK methods. The work of C.B. Macdonald was partially supported by an NSERC Canada PGS-D scholarship, a grant from NSERC Canada, and a scholarship from the Pacific Institute for the Mathematical Sciences (PIMS). The work of S. Gottlieb was supported by AFOSR grant number FA9550-06-1-0255. The work of S.J. Ruuth was partially supported by a grant from NSERC Canada.