Query-driven visualization of time-varying adaptive mesh refinement data

The visualization and analysis of AMR-based simulations is integral to the process of obtaining new insight in scientific research. We present a new method for performing query-driven visualization and analysis on AMR data, with specific emphasis on time-varying AMR data. Our work introduces a new method that directly addresses the dynamic spatial and temporal properties of AMR grids that challenge many existing visualization techniques. Further, we present the first implementation of query-driven visualization on the GPU that uses a GPU-based indexing structure to both answer queries and efficiently utilize GPU memory. We apply our method to two different science domains to demonstrate its broad applicability.     

Improved gait recognition by gait dynamics normalization

Potential sources for gait biometrics can be seen to derive from two aspects: gait shape and gait dynamics. We show that improved gait recognition can be achieved after normalization of dynamics and focusing on the shape information. We normalize for gait dynamics using a generic walking model, as captured by a population Hidden Markov Model (pHMM) defined for a set of individuals. The states of this pHMM represent gait stances over one gait cycle and the observations are the silhouettes of the corresponding gait stances. For each sequence, we first use Viterbi decoding of the gait dynamics to arrive at one dynamics-normalized, averaged, gait cycle of fixed length. The distance between two sequences is the distance between the two corresponding dynamics-normalized gait cycles, which we quantify by the sum of the distances between the corresponding gait stances. Distances between two silhouettes from the same generic gait stance are computed in the linear discriminant analysis space so as to maximize the discrimination between persons, while minimizing the variations of the same subject under different conditions. The distance computation is constructed so that it is invariant to dilations and erosions of the silhouettes. This helps us handle variations in silhouette shape that can occur with changing imaging conditions. We present results on three different, publicly available, data sets. First, we consider the HumanlD Gait Challenge data set, which is the largest gait benchmarking data set that is available (122 subjects), exercising five different factors, i.e., viewpoint, shoe, surface, carrying condition, and time. We significantly improve the performance across the hard experiments involving surface change and briefcase carrying conditions. Second, we also show improved performance on the UMD gait data set that exercises time variations for 55 subjects. Third, on the CMU Mobo data set, we show results for matching across different walking speeds. It is worth noting that there was no separate training for the UMD and CMU data sets.     

A constraint programming approach to cutset problems

We consider the problem of finding a cutset in a directed graph G=(V,E)$G=(V,E)$, i.e., a set of vertices that cuts all cycles in G  . Finding a cutset of minimum cardinality is NP-hard. There exist several approximate and exact algorithms, most of them using graph reduction techniques. In this paper, we propose a constraint programming approach to cutset problems and design a global constraint for computing cutsets. This cutset constraint is a global constraint over boolean variables associated to the vertices of a given graph and states that the subgraph restricted to the vertices having their boolean variable set to true is acyclic. We propose a filtering algorithm based on graph contraction operations and inference of simple boolean constraints, that has a linear time complexity in O(|E|+|V|)$O(|E|+|V|)$. We discuss search heuristics based on graph properties provided by the cutset constraint, and show the efficiency of the cutset constraint on benchmarks of the literature for pure minimum cutset problems, and on an application to log-based reconciliation problems where the global cutset constraint is mixed with other boolean constraints.     

Using difference intervals for time-varying isosurface visualization

We present a novel approach to out-of-core time-varying isosurface visualization. We attempt to interactively visualize time-varying datasets which are too large to fit into main memory using a technique which is dramatically different from existing algorithms. Inspired by video encoding techniques, we examine the data differences between time steps to extract isosurface information. We exploit span space extraction techniques to retrieve operations necessary to update isosurface geometry from neighboring time steps. Because only the changes between time steps need to be retrieved from disk, I/O bandwidth requirements are minimized. We apply temporal compression to further reduce disk access and employ a point-based previewing technique that is refined in idle interaction cycles. Our experiments on computational simulation data indicate that this method is an extremely viable solution to large time-varying isosurface visualization. Our work advances the state-of-the-art by enabling all isosurfaces to be represented by a compact set of operations.     

A simple strategy for calibrating the geometry of light sources

We present a methodology for calibrating multiple light source locations in 3D from images. The procedure involves the use of a novel calibration object that consists of three spheres at known relative positions. The process uses intensity images to find the positions of the light sources. We conducted experiments to locate light sources in 51 different positions in a laboratory setting. Our data shows that the vector from a point in the scene to a light source can be measured to within 2.7±4° at α=.05 (6 percent relative) of its true direction and within 0.13±.02 m at α=.05 (9 percent relative) of its true magnitude compared to empirically measured ground truth. Finally, we demonstrate how light source information is used for color correction     

Reducing the overhead of dynamic compilation

The execution model for mobile, dynamically‐linked, object‐oriented programs has evolved from fast interpretation to a mix of interpreted and dynamically compiled execution. The primary motivation for dynamic compilation is that compiled code executes significantly faster than interpreted code. However, dynamic compilation, which is performed while the application is running, introduces execution delay. In this paper we present two dynamic compilation techniques that enable high performance execution while reducing the effect of this compilation overhead. These techniques can be classified as (1) decreasing the amount of compilation performed, and (2) overlapping compilation with execution. We first present and evaluate lazy compilation, an approach used in most dynamic compilation systems in which individual methods are compiled on‐demand upon their first invocation. This is in contrast to eager compilation, in which all methods in a class are compiled when a new class is loaded. In this work, we describe our experience with eager compilation, as well as the implementation and transition to lazy compilation. We empirically detail the effectiveness of this decision. Our experimental results using the SpecJVM Java benchmarks and the Jalapeño JVM show that, compared to eager compilation, lazy compilation results in 57% fewer methods being compiled and reductions in total time of 14 to 26%. Total time in this context is compilation plus execution time. Next, we present profile‐driven, background compilation, a technique that augments lazy compilation by using idle cycles in multiprocessor systems to overlap compilation with application execution. With this approach, compilation occurs on a thread separate from that of application threads so as to reduce intermittent, and possibly substantial, delay in execution. Profile information is used to prioritize methods as candidates for background compilation. Methods are compiled according to this priority scheme so that performance‐critical methods are invoked using optimized code as soon as possible. Our results indicate that background compilation can achieve the performance of off‐line compiled applications and masks almost all compilation overhead. We show significant reductions in total time of 14 to 71% over lazy compilation. Copyright © 2001 John Wiley & Sons, Ltd.     

A SWAT evaluation of the effect of climate change on the hydrology of the Volta River basin

The SWAT (Soil and Water Assessment Tool) was used to evaluate the impacts of a climate scenario based on IPCC A1B emissions on flows in the Volta River basin in West Africa for 2021–2050 and 2071–2100, using 1983–2012 as the reference period. Overall, the simulation indicates increased variability and a decrease of up to 40% in river flow as a consequence of decreasing rainfall and increasing temperature. In particular, the analysis shows smaller absolute but greater relative changes in the hydrology of the northern (upper) part of the basin, particularly at the end of the century.     

Synthesis of Nanocrystalline Lanthanum Strontium Manganite Powder by the Urea–Formaldehyde Polymer Gel Combustion Route

Nanocrystalline lanthanum strontium manganite (LSM) powder has been synthesized by combustion of a transparent gel obtained by the polymerization of methylol urea and urea in a solution containing La³⁺, Sr²⁺, and Mn²⁺ (LSM ions). Chemistry of the transparent urea–formaldehyde (UF) polymer gel formation and structure of the gel have been proposed such that the LSM ions act in between the growing UF polymer chains by interacting through NH, OH, and CO groups by co-ordination and prevent polymer self-assembly through inter-chain hydrogen bonding as evidenced from infrared spectrum. Thermally stable structures formed by the decomposition of UF polymer below 300°C undergo combustion in the presence of nitrate oxidant in a temperature range from 350°–450°C. A perovskite LSM phase has been formed by self-sustained combustion of the dried gel initiated with little kerosene. The powder obtained after deagglomeration and calcination at 600°C for 2 h has a D ₅₀ value of 0.19 μm, and the particles are aggregates of crystallites 10–25 nm in size.     

Ferromagnetic mixed tribridged dinuclear copper(II) complex [Cu2(OAc)2(OH)(dpa)2]PF6 · H2O (dpa = 2,2′-dipyridylamine): 3D superstructure based on hydrogen bond and π…π interaction

A new dinuclear complex [Cu₂(OAc)₂(OH)(dpa)₂] PF₆ · H₂O (1) is prepared and structurally and magneto-structurally characterized. The monocationic core contains one acetate in familiar bidentate η¹:η¹:μ₂-bridge and another in the rare monoatomic bridge along with one hydroxo intermediary. 1 packs through N–H…O and O–H…O hydrogen bonds and π…π interaction resulting a 3D supramolecular continuum and displays high-energy intraligand ¹(π − π^*) fluorescence and intraligand ³(π − π^*) phosphorescence in glassy solution.     

An iterative technique for fitting exponentials

An interative method to fit the function \documentclass{article}\pagestyle{empty}\begin{document}$\mathop \[y = \sum\nolimits_i^n { = 1} a_i e^{lix}\] $\end{document} to data is considered. The technique used is that of inversion of a linear differential operator with constant coefficients. This method reproduces the parameters for mathematically precise data and gives satisfactory results when the data are affected by random errors.