Downloads & Free Reading Options - Results

SRS and NASA/MSFC have developed software with unique capabilities to couple bearing kinematic modeling with high fidelity thermal modeling. The core thermomechanical modeling software was developed by SRS and others in the late 1980's and early 1990's under various different contractual efforts. SRS originally developed software that enabled SHABERTH (Shaft Bearing Thermal Model) and SINDA (Systems Improved Numerical Differencing Analyzer) to exchange data and autonomously allowing bearing component temperature effects to propagate into the steady state bearing mechanical model. A separate contract was issued in 1990 to create a personal computer version of the software. At that time SRS performed major improvements to the code. Both SHABERTH and SINDA were independently ported to the PC and compiled. SRS them integrated the two programs into a single program that was named SINSHA. This was a major code improvement.

This article is from Journal of Applied Crystallography , volume 47 . Abstract SHELXL2013 contains improvements over the previous versions that facilitate the refinement of macromolecular structures against neutron data. This article highlights several features of particular interest for this purpose and includes a list of restraints for H-atom refinement.

BDM provided database enhancements for the DMDC MGIB files, Operation Transition files, and the DMDC SITES files. This support included improved collection of data from the Services, analysis for quality assurance purposes, and modification of the data to meet database requirements. Test data were collected for improved versions of DORS and SITES. Support was provided to improve specific data collection methods. Enhancements were enabled for SITES, TBB, and E2R2 databases.

This report documents the current status of the Advanced Simulator for Pilot Training visual data base generation system and the improvements of the software that have been made since delivery of the system. (Author)

A refinement of manifold data is a computational process, which produces a denser set of discrete data from a given one. Such refinements are closely related to multiresolution representations of manifold data by pyramid transforms, and approximation of manifold-valued functions by repeated refinements schemes. Most refinement methods compute each refined element separately, independently of the computations of the other elements. Here we propose a global method which computes all the refined elements simultaneously, using geodesic averages. We analyse repeated refinements schemes based on this global approach, and derive conditions guaranteeing strong convergence.

Runtime Refinement Checking for Concurrent Data Structures (the VYRD* project: VerifYing Refinement by Runtime Detection) The goal of the VYRD Project is to develop a runtime verification framework for concurrently accessed data structures. Databases and file systems have such data structures at their core. Stringent performance requirements force the use of tricky synchronization mechanisms for coordinating access to shared data, which makes these systems prone to concurrency errors. In this talk, we present a method for verifying that a concurrent data structure implementation refines a specification with atomic operations. Complete verification of refinement for complex implementations is often impractical. Our method instead detects refinement violations that occur at runtime. We instrument the implementation to record its actions into a log in the order they happen. The verifier then uses the log to reconstruct interesting aspects of data structure state at certain points in the execution, runs the specification in parallel, and checks that refinement conditions are met. Refinement is formulated in terms of a correspondence between the specification and implementation states and/or method return values. To check a particularly simple notion of refinement, very little annotation by the programmer is required. We report results on the application of our method to a filesystem and the Boxwood project (on storage infrastructure) being developed at MSR Silicon Valley. We are investigating ways to generalize and automate our technique and to obtain more coverage from runtime checking. *: In Norse mythology, the three sisters of Vyrd weave together the threads of fate. ©2004 Microsoft Corporation. All rights reserved.

Runtime Refinement Checking for Concurrent Data Structures (the VYRD* project: VerifYing Refinement by Runtime Detection) The goal of the VYRD Project is to develop a runtime verification framework for concurrently accessed data structures. Databases and file systems have such data structures at their core. Stringent performance requirements force the use of tricky synchronization mechanisms for coordinating access to shared data, which makes these systems prone to concurrency errors. In this talk, we present a method for verifying that a concurrent data structure implementation refines a specification with atomic operations. Complete verification of refinement for complex implementations is often impractical. Our method instead detects refinement violations that occur at runtime. We instrument the implementation to record its actions into a log in the order they happen. The verifier then uses the log to reconstruct interesting aspects of data structure state at certain points in the execution, runs the specification in parallel, and checks that refinement conditions are met. Refinement is formulated in terms of a correspondence between the specification and implementation states and/or method return values. To check a particularly simple notion of refinement, very little annotation by the programmer is required. We report results on the application of our method to a filesystem and the Boxwood project (on storage infrastructure) being developed at MSR Silicon Valley. We are investigating ways to generalize and automate our technique and to obtain more coverage from runtime checking. *: In Norse mythology, the three sisters of Vyrd weave together the threads of fate. ©2004 Microsoft Corporation. All rights reserved.

Runtime Refinement Checking for Concurrent Data Structures (the VYRD* project: VerifYing Refinement by Runtime Detection) The goal of the VYRD Project is to develop a runtime verification framework for concurrently accessed data structures. Databases and file systems have such data structures at their core. Stringent performance requirements force the use of tricky synchronization mechanisms for coordinating access to shared data, which makes these systems prone to concurrency errors. In this talk, we present a method for verifying that a concurrent data structure implementation refines a specification with atomic operations. Complete verification of refinement for complex implementations is often impractical. Our method instead detects refinement violations that occur at runtime. We instrument the implementation to record its actions into a log in the order they happen. The verifier then uses the log to reconstruct interesting aspects of data structure state at certain points in the execution, runs the specification in parallel, and checks that refinement conditions are met. Refinement is formulated in terms of a correspondence between the specification and implementation states and/or method return values. To check a particularly simple notion of refinement, very little annotation by the programmer is required. We report results on the application of our method to a filesystem and the Boxwood project (on storage infrastructure) being developed at MSR Silicon Valley. We are investigating ways to generalize and automate our technique and to obtain more coverage from runtime checking. *: In Norse mythology, the three sisters of Vyrd weave together the threads of fate. ©2004 Microsoft Corporation. All rights reserved.

We present a program (SPINVERT; http://spinvert.chem.ox.ac.uk)for refinement of magnetic diffuse scattering data for frustrated magnets, spin liquids, spin glasses, and other magnetically disordered materials. The approach uses reverse Monte Carlo refinement to fit a large configuration of spins to experimental powder neutron diffraction data. Despite fitting to spherically-averaged data, this approach allows the recovery of the three-dimensional magnetic diffuse scattering pattern and the spin-pair correlation function. We illustrate the use of the SPINVERT program with two case studies. First we use simulated powder data for the canonical Heisenberg kagome model to discuss the sensitivity of SPINVERT refinement to both pairwise and higher-order spin correlations. The effect of limited experimental data on the results is also considered. Second, we re-analyse published experimental data on the frustrated system Y0.5Ca0.5BaCo4O7. The results from SPINVERT refinement indicate similarities between Y0.5Ca0.5BaCo4O7 and its parent compound YBaCo4O7, which were overlooked in previous analysis using powder data.

How can we automatically determine which skills must be mastered for the successful completion of an online course? Large-scale online courses (e.g., MOOCs) often contain a broad range of contents frequently intended to be a semester's worth of materials; this breadth often makes it difficult to articulate an accurate set of skills and knowledge (i.e., a skill model, or the QMatrix). We have developed an innovative method to discover skill models from the data of online courses. Our method assumes that online courses have a pre-defined skill map for which skills are associated with formative assessment items embedded throughout the online course. Our method carefully exploits correlations between various parts of student performance, as well as in the text of assessment items, to build a superior statistical model that even outperforms human experts. To evaluate our method, we compare our method with existing methods (LFA) and human engineered skill models on three Open Learning Initiative (OLI) courses at Carnegie Mellon University. The results show that (1) our method outperforms human-engineered skill models, (2) skill models discovered by our method are interpretable, and (3) our method is remarkably faster than existing methods. These results suggest that our method provides a significant contribution to the evidence-based, iterative refinement of online courses with a promising scalability. [For complete proceedings, see ED560503.]

How can we automatically determine which skills must be mastered for the successful completion of an online course? Large-scale online courses (e.g., MOOCs) often contain a broad range of contents frequently intended to be a semester's worth of materials; this breadth often makes it difficult to articulate an accurate set of skills and knowledge (i.e., a skill model, or the QMatrix). We have developed an innovative method to discover skill models from the data of online courses. Our method assumes that online courses have a pre-defined skill map for which skills are associated with formative assessment items embedded throughout the online course. Our method carefully exploits correlations between various parts of student performance, as well as in the text of assessment items, to build a superior statistical model that even outperforms human experts. To evaluate our method, we compare our method with existing methods (LFA) and human engineered skill models on three Open Learning Initiative (OLI) courses at Carnegie Mellon University. The results show that (1) our method outperforms human-engineered skill models, (2) skill models discovered by our method are interpretable, and (3) our method is remarkably faster than existing methods. These results suggest that our method provides a significant contribution to the evidence-based, iterative refinement of online courses with a promising scalability. [For complete proceedings, see ED560503.]

This open access book provides insights into the novel Locally Refined B-spline (LR B-spline) surface format, which is suited for representing terrain and seabed data in a compact way. It provides an alternative to the well know raster and triangulated surface representations. An LR B-spline surface has an overall smooth behavior and allows the modeling of local details with only a limited growth in data volume. In regions where many data points belong to the same smooth area, LR B-splines allow a very lean representation of the shape by locally adapting the resolution of the spline space to the size and local shape variations of the region. The iterative method can be modified to improve the accuracy in particular domains of a point cloud. The use of statistical information criterion can help determining the optimal threshold, the number of iterations to perform as well as some parameters of the underlying mathematical functions (degree of the splines, parameter representation). The resulting surfaces are well suited for analysis and computing secondary information such as contour curves and minimum and maximum points. Also deformation analysis are potential applications of fitting point clouds with LR B-splines.

The SEAHT program is designed to process multiple passes of altimeter data with intersecting ground tracks, with the estimation of corrections for orbital errors to each pass such that the data has the best overall agreement at the crossover points. Orbit error for each pass is modeled as a polynomial in time, with optional orders of 0, 1, or 2. One or more passes may be constrained in the adjustment process, thus allowing passes with the best orbits to provide the overall level and orientation of the estimated sea surface heights. Intersections which disagree by more than an input edit level are not used in the error parameter estimation. In the program implementation, passes are grouped into South-North passes and North-South passes, with the North-South passes partitioned out for the estimation of orbit error parameters. Computer core utilization is thus dependent on the number of parameters estimated for the set of South-North arcs, but is independent on the number of North-South passes. Estimated corrections for each pass are applied to the data at its input data rate and an output tape is written which contains the corrected data.

The SEAHT program is designed to process multiple passes of altimeter data with intersecting ground tracks, with the estimation of corrections for orbital errors to each pass such that the data has the best overall agreement at the crossover points. Orbit error for each pass is modeled as a polynomial in time, with optional orders of 0, 1, or 2. One or more passes may be constrained in the adjustment process, thus allowing passes with the best orbits to provide the overall level and orientation of the estimated sea surface heights. Intersections which disagree by more than an input edit level are not used in the error parameter estimation. In the program implementation, passes are grouped into South-North passes and North-South passes, with the North-South passes partitioned out for the estimation of orbit error parameters. Computer core utilization is thus dependent on the number of parameters estimated for the set of South-North arcs, but is independent on the number of North-South passes. Estimated corrections for each pass are applied to the data at its input data rate and an output tape is written which contains the corrected data.

This article is from BMC Evolutionary Biology , volume 12 . Abstract Background: Estimates of relationships among Staphylococcus species have been hampered by poor and inconsistent resolution of phylogenies based largely on single gene analyses incorporating only a limited taxon sample. As such, the evolutionary relationships and hierarchical classification schemes among species have not been confidently established. Here, we address these points through analyses of DNA sequence data from multiple loci (16S rRNA gene, dnaJ, rpoB, and tuf gene fragments) using multiple Bayesian and maximum likelihood phylogenetic approaches that incorporate nearly all recognized Staphylococcus taxa. Results: We estimated the phylogeny of fifty-seven Staphylococcus taxa using partitioned-model Bayesian and maximum likelihood analysis, as well as Bayesian gene-tree species-tree methods. Regardless of methodology, we found broad agreement among methods that the current cluster groups require revision, although there was some disagreement among methods in resolution of higher order relationships. Based on our phylogenetic estimates, we propose a refined classification for Staphylococcus with species being classified into 15 cluster groups (based on molecular data) that adhere to six species groups (based on phenotypic properties). Conclusions: Our findings are in general agreement with gene tree-based reports of the staphylococcal phylogeny, although we identify multiple previously unreported relationships among species. Our results support the general importance of such multilocus assessments as a standard in microbial studies to more robustly infer relationships among recognized and newly discovered lineages.

This article is from Sensors (Basel, Switzerland) , volume 10 . Abstract We propose a data refinement and channel selection method for vapor classification in a portable e-nose system. For the robust e-nose system in a real environment, we propose to reduce the noise in the data measured by sensor arrays and distinguish the important part in the data by the use of feature feedback. Experimental results on different volatile organic compounds data show that the proposed data refinement method gives good clustering for different classes and improves the classification performance. Also, we design a new sensor array that consists only of the useful channels. For this purpose, each channel is evaluated by measuring its discriminative power based on the feature mask used in the data refinement. Through the experimental results, we show that the new sensor array improves both the classification rates and the efficiency in computation and data storage.

This study is part of joint efforts by the US Army and the contractor in the field of terrain data acquisition methods activities within the German theater of operations. This report contains forestry and agricultural data for a total of 22 cells of 10 x 10 km size, the high-resolution mobility terrain data base Huenfeld (L 5324) and the seven 1:50,000 quad sheet areas L 5122, L 5124, L 5320, L 5322, L 5520, L 5522 and L 5524 of the HIMO-area /1/. Due to the amount of data involved all forestry data have been stored on computer tape. Keywords: Mobility, West Germany, Farming management, Forestry practices, Farm crop rotation, Tillage, Soil strength, Soil wetness, Visibility, Seasonal variations, Geographical distribution.

turing data transformers

As we all know, launching a new site is just the beginning. Continuous iteration and refinement are lofty goals but often in content rich sites changes are slow and time consuming. You've probably noticed the headlines on of news articles on newspaper websites subtly changing throughout the day - how might this work for other less 'time sensitive' but equally content rich sectors? In this presentation I will walk through some data driven changes we're making to a cultural website using a mix of simple web analytics and custom metrics to segment visitors and gather 'real user' personas and tailor and tweak content production on the fly. Source: http://vimeo.com/126884719 Uploader: Webstock

The activities under this grant were in the general area of Verification and Validation using the Polynomial Chaos formalism developed by the PI over the course of the past 15 years. In particular, three significant questions were formulated and addressed in the course of this research: 1. How to develop polynomial chaos representations of physical parameters from experimental measurements of these parameters? 2. How to propagate the uncertainty in these parameters (as reflected in their Polynomial Chaos representations) into the dynamical behavior of the physical system. 3. How important is data refinement: what is the significance, on the predictive value of a computational model, of collecting additional experimental measurements as opposed to performing further numerical refinement (using, for example, mesh refinement). The remainder of this report will review the highlights of each of the above three topics.

This article is from Acta Crystallographica Section E: Structure Reports Online , volume 69 . Abstract Polycrystalline silver(I) deca­calcium heptakis(orthophos­phate), AgCa10(PO4)7, was obtained by solid-state reaction. It is isotopic with members of the series MCa10(PO4)7 (M = Li, Na, K and Cs), and is closely related to the structure of β-Ca3(PO4)2. The crystal structure of the title compound is built up from a framework of [CaO9] and two [CaO8] polyhedra, one [CaO6] octa­hedron (site symmetry 3.) and three PO4 tetra­hedra (one with site symmetry 3.). The Ag+ cation is likewise located on a threefold rotation axis and resides in the cavities of the rigid [Ca10(PO4)7]− framework. It is surrounded by three O atoms in an almost regular triangular environment.

SRS and NASA/MSFC have developed software with unique capabilities to couple bearing kinematic modeling with high fidelity thermal modeling. The core thermomechanical modeling software was developed by SRS and others in the late 1980's and early 1990's under various different contractual efforts. SRS originally developed software that enabled SHABERTH (Shaft Bearing Thermal Model) and SINDA (Systems Improved Numerical Differencing Analyzer) to exchange data and autonomously allowing bearing component temperature effects to propagate into the steady state bearing mechanical model. A separate contract was issued in 1990 to create a personal computer version of the software. At that time SRS performed major improvements to the code. Both SHABERTH and SINDA were independently ported to the PC and compiled. SRS them integrated the two programs into a single program that was named SINSHA. This was a major code improvement.

One of the ways to determine ground reference data (GRD) for satellite remote sensing data is to photo-interpret low altitude aerial photographs and then digitize the cover types on a digitized tablet and register them to 7.5 minute U.S.G.S. maps (that were themselves digitized). The resulting GRD can be registered to the satellite image or, vice versa. Unfortunately, there are many opportunities for error when using digitizing tablet and the resolution of the edges for the GRD depends on the spacing of the points selected on the digitizing tablet. One of the consequences of this is that when overlaid on the image, errors and missed detail in the GRD become evident. An approach is discussed for correcting these errors and adding detail to the GRD through the use of a highly interactive, visually oriented process. This process involves the use of overlaid visual displays of the satellite image data, the GRD, and a segmentation of the satellite image data. Several prototype programs were implemented which provide means of taking a segmented image and using the edges from the reference data to mask out these segment edges that are beyond a certain distance from the reference data edges. Then using the reference data edges as a guide, those segment edges that remain and that are judged not to be image versions of the reference edges are manually marked and removed. The prototype programs that were developed and the algorithmic refinements that facilitate execution of this task are described.

One of the ways to determine ground reference data (GRD) for satellite remote sensing data is to photo-interpret low altitude aerial photographs and then digitize the cover types on a digitized tablet and register them to 7.5 minute U.S.G.S. maps (that were themselves digitized). The resulting GRD can be registered to the satellite image or, vice versa. Unfortunately, there are many opportunities for error when using digitizing tablet and the resolution of the edges for the GRD depends on the spacing of the points selected on the digitizing tablet. One of the consequences of this is that when overlaid on the image, errors and missed detail in the GRD become evident. An approach is discussed for correcting these errors and adding detail to the GRD through the use of a highly interactive, visually oriented process. This process involves the use of overlaid visual displays of the satellite image data, the GRD, and a segmentation of the satellite image data. Several prototype programs were implemented which provide means of taking a segmented image and using the edges from the reference data to mask out these segment edges that are beyond a certain distance from the reference data edges. Then using the reference data edges as a guide, those segment edges that remain and that are judged not to be image versions of the reference edges are manually marked and removed. The prototype programs that were developed and the algorithmic refinements that facilitate execution of this task are described.

- Objective\n- Background\n - Capability Resource Tables (CRT)\n - Root Cause Analysis(RCA)\n- Error types\n- RCA\n - Fishbone; 5 whys\n- Lessons Learned

We incorporate realistic pair potential energies directly into a non-linear least-square fit of diffraction data to quantitatively compare structure models with experiment for the Ni-rich $d$(AlNiCo) quasicrystal. The initial structure models are derived from a few {\it a priori} assumptions (gross features of the Patterson function) and the pair potentials. In place of the common hyperspace approach to the structure refinement of quasicrystals, we use a real-space tile decoration scheme, which does not rely on strict quasiperiodicity, and makes it easy to enforce sensible local arrangements of the atoms. Inclusion of the energies provides information complementary to the diffraction data and protects the fit procedure from converging on spurious solutions. The method pinpoints sites which are likely to break the symmetry of their local environment.

A refinement was made of ocean geoid and global gravity fields from GEOS-C altimeter data. Various mathematical procedures for calculating these phenomena are given.

To facilitate locating archaeological sites before they are compromised or destroyed, we are developing approaches for generating maps of probable archaeological sites, through detecting subtle anomalies in vegetative cover, soil chemistry, and soil moisture by analyzing remotely sensed data from multiple sources. We previously reported some success in this effort with a statistical analysis of slope, radar, and Ikonos data (including tasseled cap and NDVI transforms) with Student's t-test. We report here on new developments in our work, performing an analysis of 8-band multispectral Worldview-2 data. The Worldview-2 analysis begins by computing medians and median absolute deviations for the pixels in various annuli around each site of interest on the 28 band difference ratios. We then use principle components analysis followed by linear discriminant analysis to train a classifier which assigns a posterior probability that a location is an archaeological site. We tested the procedure using leave-one-out cross validation with a second leave-one-out step to choose parameters on a 9,859x23,000 subset of the WorldView-2 data over the western portion of Ft. Irwin, CA, USA. We used 100 known non-sites and trained one classifier for lithic sites (n=33) and one classifier for habitation sites (n=16). We then analyzed convex combinations of scores from the Archaeological Predictive Model (APM) and our scores. We found that that the combined scores had a higher area under the ROC curve than either individual method, indicating that including WorldView-2 data in analysis improved the predictive power of the provided APM.

We investigate a domain decomposed multigrid technique, segmental refinement, for solving general nonlinear elliptic boundary value problems. Brandt and Diskin first proposed this method in 1994; we continue this work by analytically and experimentally investigating its complexity. We confirm that communication of traditional parallel multigrid can be eliminated on fine grids with modest amounts of extra work and storage while maintaining the asymptotic exactness of full multigrid, although we observe a dependence on an additional parameter not considered in the original analysis. We present a communication complexity analysis that quantifies the communication costs ameliorated by segmental refinement and report performance results with up to 64K cores of a Cray XC30.

Structured Adaptive Mesh Refinement (SAMR) is a popular numerical technique to study processes with high spatial and temporal dynamic range. It reduces computational requirements by adapting the lattice on which the underlying differential equations are solved to most efficiently represent the solution. Particularly in astrophysics and cosmology such simulations now can capture spatial scales ten orders of magnitude apart and more. The irregular locations and extensions of the refined regions in the SAMR scheme and the fact that different resolution levels partially overlap, poses a challenge for GPU-based direct volume rendering methods. kD-trees have proven to be advantageous to subdivide the data domain into non-overlapping blocks of equally sized cells, optimal for the texture units of current graphics hardware, but previous GPU-supported raycasting approaches for SAMR data using this data structure required a separate rendering pass for each node, preventing the application of many advanced lighting schemes that require simultaneous access to more than one block of cells. In this paper we present a single-pass GPU-raycasting algorithm for SAMR data that is based on a kD-tree. The tree is efficiently encoded by a set of 3D-textures, which allows to adaptively sample complete rays entirely on the GPU without any CPU interaction. We discuss two different data storage strategies to access the grid data on the GPU and apply them to several datasets to prove the benefits of the proposed method.

Data fusion has played an important role in data mining because high-quality data is required in a lot of applications. As on-line data may be out-of-date and errors in the data may propagate with copying and referring between sources, it is hard to achieve satisfying results with merely applying existing data fusion methods to fuse Web data. In this paper, we make use of the crowd to achieve high-quality data fusion result. We design a framework selecting a set of tasks to ask crowds in order to improve the confidence of data. Since data are correlated and crowds may provide incorrect answers, how to select a proper set of tasks to ask the crowd is a very challenging problem. In this paper, we design an approximation solution to address this challenge since we prove that the problem is at NP-hard. To further improve the efficiency, we design a pruning strategy and a preprocessing method, which effectively improve the performance of the proposed approximation solution. Furthermore, we find that under certain scenarios, we are not interested in all the facts, but only a specific set of facts. Thus, for these specific scenarios, we also develop another approximation solution which is much faster than the general approximation solution. We verify the solutions with extensive experiments on a real crowdsourcing platform.

Tagging of visual content is becoming more and more widespread as web-based services and social networks have popularized tagging functionalities among their users. These user-generated tags are used to ease browsing and exploration of media collections, e.g. using tag clouds, or to retrieve multimedia content. However, not all media are equally tagged by users. Using the current systems is easy to tag a single photo, and even tagging a part of a photo, like a face, has become common in sites like Flickr and Facebook. On the other hand, tagging a video sequence is more complicated and time consuming, so that users just tag the overall content of a video. In this paper we present a method for automatic video annotation that increases the number of tags originally provided by users, and localizes them temporally, associating tags to keyframes. Our approach exploits collective knowledge embedded in user-generated tags and web sources, and visual similarity of keyframes and images uploaded to social sites like YouTube and Flickr, as well as web sources like Google and Bing. Given a keyframe, our method is able to select on the fly from these visual sources the training exemplars that should be the most relevant for this test sample, and proceeds to transfer labels across similar images. Compared to existing video tagging approaches that require training classifiers for each tag, our system has few parameters, is easy to implement and can deal with an open vocabulary scenario. We demonstrate the approach on tag refinement and localization on DUT-WEBV, a large dataset of web videos, and show state-of-the-art results.

When optimizing a thread in a concurrent program (either done manually or by the compiler), it must be guaranteed that the resulting thread is a refinement of the original thread. Most theories of valid optimizations are formulated in terms of valid syntactic transformations on the program code, or in terms of valid transformations on thread execution traces. We present a new theory formulated instead in terms of the state of threads at synchronization operations, and show that it provides several advantages: it supports more optimizations, and leads to more efficient and simpler procedures for refinement checking. We develop the theory for the SC-for-DRF execution model (using locks for synchronization), and show that its application in a compiler testing setting leads to large performance improvements.

When optimizing a thread in a concurrent program (either done manually or by the compiler), it must be guaranteed that the resulting thread is a refinement of the original thread. Most theories of valid optimizations are formulated in terms of valid syntactic transformations on the program code, or in terms of valid transformations on thread execution traces. We present a new theory formulated instead in terms of the state of threads at synchronization operations, and show that it provides several advantages: it supports more optimizations, and leads to more efficient and simpler procedures for refinement checking. We develop the theory for the SC-for-DRF execution model (using locks for synchronization), and show that its application in a compiler testing setting leads to large performance improvements.

The initial data for black hole collisions is constructed using a conformal-imaging approach and a new adaptive mesh refinement technique, a fully threaded tree (FTT). We developed a second-order accurate approach to the solution of the constraint equations on a non-uniformly refined high resolution Cartesian mesh including second-order accurate treatment of boundary conditions at the black hole throats. Results of test computations show convergence of the solution as the numerical resolution is increased. FTT-based mesh refinement reduces the required memory and computer time by several orders of magnitude compared to a uniform grid. This opens up the possibility of using Cartesian meshes for very high resolution simulations of black hole collisions.

"Big data" has become a major area of research and associated funding, as well as a focus of utopian thinking. In the still growing research community, one of the favourite optimistic analogies for data processing is that of the oil refinery, extracting the essence out of the raw data. Pessimists look for their imagery to the other end of the petrol cycle, and talk about the "data exhausts" of our society. Obviously, the refinement community knows how to do "refining". This paper explores the extent to which notions of refinement and data in the formal methods community relate to the core concepts in "big data". In particular, can the data refinement paradigm can be used to explain aspects of big data processing?

The paper is concerned with the finite element solution of the Poisson equation with homogeneous Dirichlet boundary condition in a three-dimensional domain. Anisotropic, graded meshes from a former paper are reused for dealing with the singular behaviour of the solution in the vicinity of the non-smooth parts of the boundary. The discretization error is analyzed for the piecewise linear approximation in the H^1(\Omega)- and L^2(\Omega)-norms by using a new quasi-interpolation operator. This new interpolant is introduced in order to prove the estimates for L^2(\Omega)-data in the differential equation which is not possible for the standard nodal interpolant. These new estimates allow for the extension of certain error estimates for optimal control problems with elliptic partial differential equation and for a simpler proof of the discrete compactness property for edge elements of any order on this kind of finite element meshes.