A comprehensive analysis of cavitation and liquid impingement erosion data

Cavitation-erosion experimental data previously covering several materials tested in a rotating disk device and a magnetostriction apparatus were analyzed using new normalization and curve-fitting techniques. From this process a universal approach is derived which can include data from cavitation and liquid impingement studies for specific materials from different test devices

Universal approach to analysis of cavitation and liquid-impingement erosion data

Cavitation erosion experimental data was analyzed by using normalization and curve-fitting techniques. Data were taken from experiments on several materials tested in both a rotating disk device and a magnetostriction apparatus. Cumulative average volume loss rate and time data were normalized relative to the peak erosion rate and the time to peak erosion rate, respectively. From this process a universal approach was derived that can include data on specific materials from different test devices for liquid impingement and cavitation erosion studies

The MIR Flickr Retrieval Evaluation Proposal Based on User Tags and Textual Passwords

In most well known image retrieval test sets, the imagery typically cannot be freely distributed or is not representative of a large community of users. In this paper we present a collection for the MIR community comprising 69,000 images from the Flickr website which are redistributable for research purposes and represent a real community of users both in the image content and image tags. We have extracted the tags and EXIF image meta data, and also make all of these publicly available. In addition we discuss several challenges for benchmarking retrieval and classification methods and applications

Enhancing productivity of water under variable climate

Crop productionMaizeClimateRainFamersDecision making

Enhancing productivity of water under variable climate

Irrigated farmingProductivityCrop productionMaizeSimulation modelsClimateForecasting

Geometry of good sets in n-fold Cartesian product

We propose here a multidimensional generalisation of the notion of link introduced in our previous papers and we discuss some consequences for simplicial measures and sums of function algebras.Comment: 17 pages, no figures, no table

Robust filtering for stochastic genetic regulatory networks with time-varying delay

This is the post print version of the article. The official published version can be obtained from the link - Copyright 2009 Elsevier LtdThis paper addresses the robust filtering problem for a class of linear genetic regulatory networks (GRNs) with stochastic disturbances, parameter uncertainties and time delays. The parameter uncertainties are assumed to reside in a polytopic region, the stochastic disturbance is state-dependent described by a scalar Brownian motion, and the time-varying delays enter into both the translation process and the feedback regulation process. We aim to estimate the true concentrations of mRNA and protein by designing a linear filter such that, for all admissible time delays, stochastic disturbances as well as polytopic uncertainties, the augmented state estimation dynamics is exponentially mean square stable with an expected decay rate. A delay-dependent linear matrix inequality (LMI) approach is first developed to derive sufficient conditions that guarantee the exponential stability of the augmented dynamics, and then the filter gains are parameterized in terms of the solution to a set of LMIs. Note that LMIs can be easily solved by using standard software packages. A simulation example is exploited in order to illustrate the effectiveness of the proposed design procedures.This work was supported in part by the Biotechnology and Biological Sciences Research Council (BBSRC) of the U.K. under Grants BB/C506264/1 and 100/EGM17735, an International Joint Project sponsored by the Royal Society of the U.K., the Research Grants Council of Hong Kong under Grant HKU 7031/06P, the National Natural Science Foundation of China under Grant 60804028, and the Alexander von Humboldt Foundation of Germany