An A Posteriori Error Estimate for the Local Discontinuous Galerkin Method Applied to Linear and Nonlinear Diffusion Problems

In this paper we present a new residual-based reliable a posteriori error estimator for the local discontinuous Galerkin approximations of linear and nonlinear diffusion problems in polygonal regions of R ². Our analysis, which applies to convex and nonconvex domains, is based on Helmholtz decompositions of the error and a suitable auxiliary polynomial function interpolating the Dirichlet datum. Several examples confirming the reliability of the estimator and providing numerical evidences for its efficiency are given. Furthermore, the associated adaptive method, which considers meshes with and without hanging nodes, is shown to be much more efficient than a uniform refinement to compute the discrete solutions. In particular, the experiments illustrate the ability of the adaptive algorithm to localize the singularities of each problem.Mathematics Subject Classifications (1991). 65N30This revised version was published online in July 2005 with corrected volume and issue numbers.     

Statistical Modeling to Forecast Odor Levels of Biosolids Applied to Reuse Sites

Proper use or disposal of wastewater solids is an important responsibility of wastewater treatment plants. At present, there are several options for wastewater solids, including agriculture, forestry, and mine reclamation reuse; production of marketable products such as compost and dried pellets; and disposal in landfills and incinerators. Land application of biosolids products is beneficial as part of recycling efforts on local farms, forests, tree farms, and mines and has gained greater acceptance of late. Coupled with these beneficial aspects are odors, which must be managed relative to the receiving populations. In this paper we present several statistical models that predict biosolids odor levels based on processing and management variables as well as ambient conditions. Such models are useful to managers at advanced wastewater treatment plants in helping them to better forecast the biosolids odors and minimize the “odor footprint,” thus making these biosolids products better received.     

Text classification without negative examples revisit

Traditionally, building a classifier requires two sets of examples: positive examples and negative examples. This paper studies the problem of building a text classifier using positive examples (P) and unlabeled examples (U). The unlabeled examples are mixed with both positive and negative examples. Since no negative example is given explicitly, the task of building a reliable text classifier becomes far more challenging. Simply treating all of the unlabeled examples as negative examples and building a classifier thereafter is undoubtedly a poor approach to tackling this problem. Generally speaking, most of the studies solved this problem by a two-step heuristic: first, extract negative examples (N) from U. Second, build a classifier based on P and N. Surprisingly, most studies did not try to extract positive examples from U. Intuitively, enlarging P by P' (positive examples extracted from U) and building a classifier thereafter should enhance the effectiveness of the classifier. Throughout our study, we find that extracting P' is very difficult. A document in U that possesses the features exhibited in P does not necessarily mean that it is a positive example, and vice versa. The very large size of and very high diversity in U also contribute to the difficulties of extracting P'. In this paper, we propose a labeling heuristic called PNLH to tackle this problem. PNLH aims at extracting high quality positive examples and negative examples from U and can be used on top of any existing classifiers. Extensive experiments based on several benchmarks are conducted. The results indicated that PNLH is highly feasible, especially in the situation where |P| is extremely small.     

Towards Reduced Basis Approaches in ab initio Electronic Structure Computations

Due to the high dimensionality of the spaces where the problems are set, adapted discretization basis are often advocated in complex physical problems (Navier–Stokes equations, solid mecanics, ab initio electronic structure computations) to express the solution in terms of solution of similar (but easier to solve) problems. However, very few mathematical studies have been undertaken to asses the numerical properties of these approximations. Within this context, we will present in this paper an overview of the tools required to develop more rigorous reduced basis approaches for quantum chemistry: a posteriori numerical analysis and fast exponential decay of the n-width of the solution set.     

HPCVIEW: A Tool for Top-down Analysis of Node Performance

It is increasingly difficult for complex scientific programs to attain a significant fraction of peak performance on systems that are based on microprocessors with substantial instruction-level parallelism and deep memory hierarchies. Despite this trend, performance analysis and tuning tools are still not used regularly by algorithm and application designers. To a large extent, existing performance tools fail to meet many user needs and are cumbersome to use. To address these issues, we developed HPCVIEW—a toolkit for combining multiple sets of program profile data, correlating the data with source code, and generating a database that can be analyzed anywhere with a commodity Web browser. We argue that HPCVIEW addresses many of the issues that have limited the usability and the utility of most existing tools. We originally built HPCVIEW to facilitate our own work on data layout and optimizing compilers. Now, in addition to daily use within our group, HPCVIEW is being used by several code development teams in DoD and DoE laboratories as well as at NCSA.     

Robot Dynamic Modeling Using a Power Flow Approach with Application to Biped Locomotion

In this paper, we present a method for robots modeling called bidirectional dynamic modeling. This new method takes into account the gear efficiency and the direction of power transmission in the gears. Epicyclic gearboxes have often different efficiencies in the two directions of power transmission. The characteristics of the chain of transmission must then be taken into consideration in order to describe the dynamic behavior of robots. The two directions of power flow can indeed occur in robot motions. Depending on that direction the dynamic model is different. The bidirectional dynamic modeling is experimentally applied to a bipedal walking robot. Our method exhibits a better accuracy over classical modeling. Moreover, when applied to computed torque control, the bidirectional model increases the tracking performances.     

On rejecting emotional lures created by phonological neighborhood activation.

The authors conducted 2 experiments to assess how phonologically related lures are rejected in a false memory paradigm. Some phonological lures were emotional (i.e., taboo) words, and others were not. The authors manipulated the presence of taboo items on the study list and reduced the ability to use controlled rejection strategies by dividing attention and forcing a short response deadline. The results converge on the idea that participants reduce false alarms to emotional lures by setting more stringent recognition criteria for these items based on their expected memorability. Additionally, emotional lures are less familiar than nonemotional lures because emotional lures have affective and semantic features that mismatch studied nonemotional items. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

High temperature 1H NMR studies of epoxy cure: A neglected technique

Summary By reference to the reaction of a copper complex of phenyl glycidyl ether and 2-ethyl-4-methylimidazole, and Bisphenol A diglycidyl ether, ¹H nuclear magnetic resonance spectroscopy at high temperature is shown to be an excellent and under-utilized method for measuring the degree of cure, enabling kinetic parameters to be obtained.