A coupled photocatalytic-biological process for degradation of 1-amino-8-naphthol-3, 6-disulfonic acid (H-acid)

 There has been growing emphasis on the development of coupled treatment systems (e.g., advanced oxidation–biological) for treating poorly biodegradable wastewater. An attempt has been made in the present study to couple photocatalytic (TiO₂/UV) pretreatment with conventional activated sludge process to achieve improvement in the biodegradation of H-acid. The combination of titanium dioxide and UV light has been known to generate strong oxidants that degrade several organic pollutants into carbon dioxide via the formation of some intermediates. The intermediates formed may undergo biodegradation readily. Accordingly, photodegradation experiments were carried out initially at an optimized TiO₂ dose and the minimum pretreatment time required for transforming H-acid was identified. For this purpose, UV–vis spectrophotometry and high-performance liquid chromatography (HPLC) were extensively used. Subsequently, it was attempted to biodegrade untreated and pretreated H-acid using activated sludge from the textile industry acclimatized to H-acid. It was found that photocatalytic pretreatment of H-acid for 30 min, during which period approximately 8–10% chemical oxygen demand (COD) removal occurred, can be coupled to second-stage biological treatment for achieving enhanced biodegradation of H-acid.     

Measurements of shear stress in a square array rod bundle

A flush-mounted hot film sensor was used to determine the shear stress distribution on the centrally located rod in a 1.4 pitch to diameter ratio square array, nine rod bundle with axial flow. The film sensor was calibrated in a concentric annulus flow geometry. Shear stress measurements were made at a position 65 hydraulic diameters from the flow entrance for Reynolds numbers from 12 000 to 32 000. The circumferential variation of the shear stress was nearly sinusoidal around the central rod and the maximum and minimum values occurred at the maximum and minimum subchannel spacing. The peak to peak variation of the sinusoidal shear stress distribution is about 4 to 6% of the mean value.     

Stability of two-layered fluid flows in an inclined channel

A linear stability analysis of two-layer fluid flows in an inclined channel geometry has been carried out. The onset of flow transitions and the spatio-temporal characteristics of secondary flows produced by the flow instabilities have been examined. The effects of density and viscosity stratifications and surface tension on flow structures also have been investigated at various values of Froude numbers (channel inclinations). Multi-domain Chebyshev–Tau spectral methods along with MATLAB QZ eigenvalue solver are used to determine the whole spectrum of the eigenvalues and associated eigenfunctions. The neutral stability diagrams and stability boundaries are constructed for various values of flow parameters. The onset of flow transitions and flow structures predicted by linear stability analysis are compared against experimental results and they agree reasonably well. The results presented in the present paper imply that the shear mode of flow transitions is the one likely to be identified in experiments.     

Combined buoyancy and viscous effects in liquid–liquid flows in a vertical pipe

This paper presents experimental and numerical results of interfacial dynamics of liquid–liquid flows when an immiscible core liquid is introduced into a continuous liquid flow. The fully developed flow model predicts multiple solutions of the jet diameter over a range of dimensionless numbers: flow rate ratio, viscosity ratio, Bond and Capillary numbers. Experiments have been carried out using Polyethylene Glycol (PEG) and Canola oil to investigate the realizability of the three possible solutions predicted by the fully developed flow model. The measured values of inner fluid radii agree very well with the lower branch of the three branched solution while deviating from the top branch beyond a critical flow ratio value. This deviation is attributed to the fact that the flow develops a non-axisymmetric solution at this critical point. Computational fluid dynamics simulations have also been performed to examine the developing core annular flow and to compare the analytical solution results of liquid jet radius. The results predicted by numerical simulations agree very well with both the lower and upper branches of solution predicted by the analytical theory.     

Containment capsule stresses for encapsulated phase change materials

The encapsulation of a phase change material to store thermal energy is considered here for concentrated solar power systems. The stress distribution in a spherical nickel shell of 250 μ thickness formed around a ball of zinc by the electroless deposition process and a stainless steel cylindrical shell containing zinc are considered. The effect of external forces and imperfections within the shell structure that could affect the deformation are also modeled. The aim of the simulations performed is to establish a suitable thickness for the encapsulating material. It is concluded that while the shell can deform and safely withstand the anticipated expansion of the zinc, the added effects from point loads caused by the weight of the surrounding encapsulated capsules and other possible imperfections in the capsule structure could cause failure. A three-dimensional finite element model is used to establish the stresses in cylinders of different aspect ratio caused by the expansion of zinc as it melts inside of the encapsulation. The amount of void space that must be left inside of the capsule, so that the expansion of the zinc during phase change and the increase in gas pressure inside of the vessel will not cause failure of the shell, is determined from simulations. Results indicate that the cylinder with welded ends could easily contain up to 86% of the initial volume full of zinc with only a very small amount of plastic deformation, less than 0.5% strain, corresponding to an internal pressure of 2.03 MPa.     

Recent advances in the automatic recognition of audiovisual speech

Visual speech information from the speaker's mouth region has been successfully shown to improve noise robustness of automatic speech recognizers, thus promising to extend their usability in the human computer interface. In this paper, we review the main components of audiovisual automatic speech recognition (ASR) and present novel contributions in two main areas: first, the visual front-end design, based on a cascade of linear image transforms of an appropriate video region of interest, and subsequently, audiovisual speech integration. On the latter topic, we discuss new work on feature and decision fusion combination, the modeling of audiovisual speech asynchrony, and incorporating modality reliability estimates to the bimodal recognition process. We also briefly touch upon the issue of audiovisual adaptation. We apply our algorithms to three multisubject bimodal databases, ranging from small- to large-vocabulary recognition tasks, recorded in both visually controlled and challenging environments. Our experiments demonstrate that the visual modality improves ASR over all conditions and data considered, though less so for visually challenging environments and large vocabulary tasks.     

An efficient full-bridge resonant converter for light emitting diode (LED) application with simple current control

New power control is introduced in the full-bridge dc-dc converter to drive an LED lamp in this paper. LEDs are semiconductor devices that behave like a constant voltage load with low equivalent series resistance (ESR). Hence, they require precise control for current regulation. In the proposed driver, the LED lamp is driven by two voltage sources connected in series through a series resonant circuit. It processes the majority of lamp power through the full-bridge diode rectifier and supplies small power through a center-tapped rectifier. The LED lamp current is controlled at the selected operating current by using center-tapped rectifier output voltage. In addition, pulse-width modulation (PWM) dimming is implemented. The proposed topology features zero-voltage switching (ZVS), regulation of lamp current, dimming operation, and high efficiency. The working principle, performance, and prototype validation are given for the proposed LED driver.     

A Cascade Visual Front End for Speaker Independent Automatic Speechreading

We propose a three-stage pixel-based visual front end for automatic speechreading (lipreading) that results in significantly improved recognition performance of spoken words or phonemes. The proposed algorithm is a cascade of three transforms applied on a three-dimensional video region-of-interest that contains the speaker's mouth area. The first stage is a typical image compression transform that achieves a high-energy, reduced-dimensionality representation of the video data. The second stage is a linear discriminant analysis-based data projection, which is applied on a concatenation of a small amount of consecutive image transformed video data. The third stage is a data rotation by means of a maximum likelihood linear transform that optimizes the likelihood of the observed data under the assumption of their class-conditional multivariate normal distribution with diagonal covariance. We applied the algorithm to visual-only 52-class phonetic and 27-class visemic classification on a 162-subject, 8-hour long, large vocabulary, continuous speech audio-visual database. We demonstrated significant classification accuracy gains by each added stage of the proposed algorithm which, when combined, can achieve up to 27% improvement. Overall, we achieved a 60% (49%) visual-only frame-level visemic classification accuracy with (without) use of test set viseme boundaries. In addition, we report improved audio-visual phonetic classification over the use of a single-stage image transform visual front end. Finally, we discuss preliminary speech recognition results.     

Maximally fault tolerant neural networks

An application of neural network modeling is described for generating hypotheses about the relationships between response properties of neurons and information processing in the auditory system. The goal is to study response properties that are useful for extracting sound localization information from directionally selective spectral filtering provided by the pinna. For studying sound localization based on spectral cues provided by the pinna, a feedforward neural network model with a guaranteed level of fault tolerance is introduced. Fault tolerance and uniform fault tolerance in a neural network are formally defined and a method is described to ensure that the estimated network exhibits fault tolerance. The problem of estimating weights for such a network is formulated as a large-scale nonlinear optimization problem. Numerical experiments indicate that solutions with uniform fault tolerance exist for the pattern recognition problem considered. Solutions derived by introducing fault tolerance constraints have better generalization properties than solutions obtained via unconstrained back-propagation.