The application of laser-induced breakdown detection (LIBD) as a new and powerful particle-analyzing technique for the determination of solubility data by monitoring initial colloid generation, when the metal ion concentration just exceeds the solubility at a given pH value, is investigated. Laser-induced breakdown spectroscopy (LIBS) is used for selective analysis of an aqueous suspension of l...

In order to improve network intrusion detection precision, this paper proposed a network intrusion detection model based on simultaneous selecting features and parameters of support vector machine (SVM) by particle swarm optimization (PSO) algorithm. Firstly, the features and parameters of SVM are coded to particle, and then the PSO is used to find the optimal features and SVM parameters by col...

We investigate the contour detection task in complex natural images. We propose a novel contour detection algorithm which locally tracks small pieces of edges called edgelets. The combination of the Bayesian modeling and the edgelets enables the use of semi-local prior information and image-dependent likelihoods. We use a mixed offline and online learning strategy to detect the most relevant ed...

Weakly Interacting Massive Particle (WIMP) direct detection experiments are just reaching the sensitivity required to detect Galactic dark matter in the form of neutralinos (or indeed any stable weakly interacting particle). Detection strategies and data analyses are often based on the simplifying assumption of a standard spherical, isothermal halo model, but observations and numerical simulati...

in this study, a specific ch4 sensor is fabricated based on interdigitated electrode that modified with core-shell of tungsten carbide/tin oxide (wc/sno2) nanoparticles by wet chemical method in different percents of carbon and tungsten. the morphology of wet chemical-synthesized wc/sno2 core-shell was evaluated by different methods such as patterned x-ray diffraction (xrd), and particle size a...

In this paper, a dual estimation methodology is developed for both time-varying parameters and states of a nonlinear stochastic system based on the Particle Filtering (PF) scheme. Our developed methodology is based on a concurrent implementation of state and parameter estimation filters as opposed to using a single filter for simultaneously estimating the augmented states and parameters. The co...

In this work, we report a portable microfluidic chip based on Si-Porous-Pt MSNs(Mesoporous Silica Nanoparticles) -enhanced electrochemical detection for single-bacteria diognostic. The possibility of single-bacteria detection is realized here by using electroactive molecules modified on Si-Porous-Pt MSNs(Mesoporous Silica Nanoparticles) to detect and differentiate Staphylococcus aureus and Pseu...

In this study, the authors consider online detection and separation of superimposed events by applying particle filtering. They observe only a single-channel superimposed signal, which consists of a background signal and one or more event signals in the discrete-time domain. It is assumed that the signals are statistically independent and can be described by random processes with known parametr...