West Virginia University

About: West Virginia University is a education organization based out in Morgantown, West Virginia, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 25632 authors who have published 48308 publications receiving 1343934 citations. The organization is also known as: WVU & West Virginia University, WVU.

Effects of Pore Structure on Performance of An Activated-Carbon Supercapacitor Electrode Recycled from Scrap Waste Tires

Abstract: It is important to address the challenges posed with the ever-increasing demand for energy supply and environmental sustainability. Activated carbon, which is the common material for commercial supercapacitor electrodes, is currently derived from petroleum-based precursors. This paper presents an effective synthetic method that utilizes waste tires as the precursor to prepare the activated carbon electrodes by the pyrolysis and chemical activation processes. Adjusting the activation parameters can tailor multiple physical properties of the resulting activated carbon, which in turns tunes the performance of the activated carbon electrode. Statistical multiple linear regression and stepwise regression methods are employed to investigate the dependence of the specific capacitance and the rate capability upon the physical properties (such as porosity) of the activated carbon electrode. The specific capacitance of activated carbon electrode is controlled by the micropore volume but independent of the mesopores...

Robust prediction of fault-proneness by random forests

Abstract: Accurate prediction of fault prone modules (a module is equivalent to a C function or a C+ + method) in software development process enables effective detection and identification of defects. Such prediction models are especially beneficial for large-scale systems, where verification experts need to focus their attention and resources to problem areas in the system under development. This paper presents a novel methodology for predicting fault prone modules, based on random forests. Random forests are an extension of decision tree learning. Instead of generating one decision tree, this methodology generates hundreds or even thousands of trees using subsets of the training data. Classification decision is obtained by voting. We applied random forests in five case studies based on NASA data sets. The prediction accuracy of the proposed methodology is generally higher than that achieved by logistic regression, discriminant analysis and the algorithms in two machine learning software packages, WEKA [I. H. Witten et al. (1999)] and See5. The difference in the performance of the proposed methodology over other methods is statistically significant. Further, the classification accuracy of random forests is more significant over other methods in larger data sets.

Spectroscopic determination of leaf morphological and biochemical traits for northern temperate and boreal tree species

Abstract: The morphological and biochemical properties of plant canopies are strong predictors of photosynthetic capacity and nutrient cycling. Remote sensing research at the leaf and canopy scales has demonstrated the ability to characterize the biochemical status of vegetation canopies using reflectance spectroscopy, including at the leaf level and canopy level from air- and spaceborne imaging spectrometers. We developed a set of accurate and precise spectroscopic calibrations for the determination of leaf chemistry (contents of nitrogen, carbon, and fiber constituents), morphology (leaf mass per area, Marea), and isotopic composition (δ15N) of temperate and boreal tree species using spectra of dried and ground leaf material. The data set consisted of leaves from both broadleaf and needle-leaf conifer species and displayed a wide range in values, determined with standard analytical approaches: 0.7–4.4% for nitrogen (Nmass), 42–54% for carbon (Cmass), 17–58% for fiber (acid-digestible fiber, ADF), 7–44% for lignin (acid-digestible lignin, ADL), 3–31% for cellulose, 17–265 g/m2 for Marea, and −9.4‰ to 0.8‰ for δ15N. The calibrations were developed using a partial least-squares regression (PLSR) modeling approach combined with a novel uncertainty analysis. Our PLSR models yielded model calibration (independent validation shown in parentheses) R2 and the root mean square error (RMSE) values, respectively, of 0.98 (0.97) and 0.10% (0.13%) for Nmass, R2 = 0.77 (0.73) and RMSE = 0.88% (0.95%) for Cmass, R2 = 0.89 (0.84) and RMSE = 2.8% (3.4%) for ADF, R2 = 0.77 (0.69) and RMSE = 2.4% (3.9%) for ADL, R2 = 0.77 (0.72) and RMSE = 1.4% (1.9%) for leaf cellulose, R2 = 0.62 (0.60) and RMSE = 0.91‰ (1.5‰) for δ15N, and R2 = 0.88 (0.87) with RMSE = 17.2 g/m2 (22.8 g/m2) for Marea. This study demonstrates the potential for rapid and accurate estimation of key foliar traits of forest canopies that are important for ecological research and modeling activities, with a single calibration equation valid over a wide range of northern temperate and boreal species and leaf physiognomies. The results provide the basis to characterize important variability between and within species, and across ecological gradients using a rapid, cost-effective, easily replicated method.

An intercomparison of radiatively driven entrainment and turbulence in a smoke cloud, as simulated by different numerical models

Abstract: This paper reports an intercomparison study of a stratocumulus-topped planetary boundary layer (PBL) generated from ten 3D large eddy simulation (LES) codes and four 2D cloud-resolving models (CRMs). These models vary in the numerics, the parameterizations of the subgrid-scale (SGS) turbulence and condensation processes, and the calculation of longwave radiative cooling. Cloud-top radiative cooling is often the major source of buoyant production of turbulent kinetic energy in the stratocumulus-topped PBL. An idealized nocturnal stratocumulus case was selected for this study. It featured a statistically horizontally homogeneous and nearly solid cloud deck with no drizzle, no solar radiation, little wind shear, and little surface heating. Results of the two-hour simulations showed that the overall cloud structure, including cloud-top height, cloud fraction, and the vertical distributions of many turbulence statistics, compared well among all LESs despite the code variations. However, the entrainmen...