Distributed learning consensus control based on neural networks for heterogeneous nonlinear multiagent systems

This paper considers a novel distributed iterative learning consensus control algorithm based on neural networks for the control of heterogeneous nonlinear multiagent systems. The system's unknown nonlinear function is approximated by suitable neural networks; the approximation error is countered by a robust term in the control. Two types of control algorithms, both of which utilize distributed learning laws, are provided to achieve consensus. In the provided control algorithms, the desired reference is considered to be an unknown factor and then estimated using the associated learning laws. The consensus convergence is proven by the composite energy function method. A numerical simulation is ultimately presented to demonstrate the efficacy of the proposed control schemes.     

Systematic convergence of nonlinear stochastic estimators on the Special Orthogonal Group SO(3)

This paper introduces two novel nonlinear stochastic attitude estimators developed on the Special Orthogonal Group with the tracking error of the normalized Euclidean distance meeting predefined transient and steady‐state characteristics. The tracking error is confined to initially start within a predetermined large set such that the transient performance is guaranteed to obey dynamically reducing boundaries and decrease smoothly and asymptotically to the origin in probability from almost any initial condition. The proposed estimators produce accurate attitude estimates with remarkable convergence properties using measurements obtained from low‐cost inertial measurement units. The estimators proposed in continuous form are complemented by their discrete versions for the implementation purposes. The simulation results illustrate the effectiveness and robustness of the proposed estimators against uncertain measurements and large initialization error, whether in continuous or discrete form.     

Suitability,efficiency and microbiological safety of novel physical technologies for the processing of ready‐to‐eat meals,meats and pumpable products

Consumer studies and market reports show an increase in consumption of ready‐to‐eat (RTE) foods. Although conventional processing technologies can in most cases produce safe products, they can also lead to the degradation of nutritional compounds and negatively affect quality characteristics. Consumers strongly prefer food that is minimally processed with the maximum amount of health‐promoting substances. Novel processing technologies as pre‐ or post‐treatment decontamination methods or as substitutes of conventional technologies have the potential to produce foods that are safe, rich in nutrient content and with superior organoleptic properties. Combining novel with conventional processes can eliminate potential drawbacks of novel technologies. This review examines available scientific information and critically evaluates the suitability and efficiency of various novel thermal and nonthermal technologies in terms of microbial safety, quality as well as nutrient content on the production of RTE meals, meats and pumpable products.     

On‐the‐Spot Immobilization of Quantum Dots,Graphene Oxide,and Proteins via Hydrophobins

Class I hydrophobin Vmh2, a peculiar surface active and versatile fungal protein, is known to self‐assemble into chemically stable amphiphilic films, to be able to change wettability of surfaces, and to strongly adsorb other proteins. Herein, a fast, highly homogeneous and efficient glass functionalization by spontaneous self‐assembling of Vmh2 at liquid–solid interfaces is achieved (in 2 min). The Vmh2‐coated glass slides are proven to immobilize not only proteins but also nanomaterials such as graphene oxide (GO) and quantum dots (QDs). As models, bovine serum albumin labeled with Alexa 555 fluorophore, anti‐immunoglobulin G antibodies, and cadmium telluride QDs are patterned in a microarray fashion in order to demonstrate functionality, reproducibility, and versatility of the proposed substrate. Additionally, a GO layer is effectively and homogeneously self‐assembled onto the studied functionalized surface. This approach offers a quick and simple alternative to immobilize nanomaterials and proteins, which is appealing for new bioanalytical and nanobioenabled applications.     

A Distribution‐freeCUSUMChart for Monitoring Variability of AutocorrelatedProcesses

We present a distribution‐free tabular cumulative sum chart for monitoring the variability of an autocorrelated process. A quantity known as the asymptotic variance parameter is employed as a measure of the variability, and a distribution‐free tabular cumulative sum chart is applied to variance estimates calculated from batches of nonoverlapping samples. The proposed chart is applicable to a stationary process with a general marginal distribution and a general autocorrelation structure. It also determines control limits analytically without trial‐and‐error simulations. The performance of the proposed chart is tested on stationary processes with both normal and nonnormal marginals with various autocorrelation structures. Copyright © 2014 John Wiley & Sons, Ltd.     

Visualizing for the Non‐Visual: Enabling the Visually Impaired to Use Visualization

The majority of visualizations on the web are still stored as raster images, making them inaccessible to visually impaired users. We propose a deep‐neural‐network‐based approach that automatically recognizes key elements in a visualization, including a visualization type, graphical elements, labels, legends, and most importantly, the original data conveyed in the visualization. We leverage such extracted information to provide visually impaired people with the reading of the extracted information. Based on interviews with visually impaired users, we built a Google Chrome extension designed to work with screen reader software to automatically decode charts on a webpage using our pipeline. We compared the performance of the back‐end algorithm with existing methods and evaluated the utility using qualitative feedback from visually impaired users.     

Inhibition of microbial growth in ready‐to‐eat food stored at ambient temperature by modified atmosphere packaging

This study was undertaken to develop a modified atmosphere package to control microbial growth in ready‐to‐eat (RTE) products stored at ambient temperature. Ethanol and/or limonene associated with modified atmosphere (CO₂ : O₂ : N₂ = 30% : 5% : 65%) was used to inhibit the growth of total air‐borne microorganisms and Escherichia coli in RTE products stored at 25°C. The results indicated that 0.05% ethanol vapour in the headspace was effective to inhibit the growth of air‐borne microorganisms and E. coli at 25°C for 72 h in a model study, and the effectiveness was related to ethanol content. Both 73 ppm limonene and 0.05% ethanol vapour enhanced the bacteriostatic effect of modified atmosphere in RTE sushi roll products, and no off‐flavour was detected using this formulated gas; however, no significant inhibitory effect was observed for RTE cold noodle products. This study concludes that combinations of carbon dioxide, ethanol or limonene vapours are effective to inhibit microbial growth in RTE food at ambient temperature, and the outcome may be due to the hurdle effect. Copyright © 2003 John Wiley & Sons, Ltd.     

Oligo(ethylene oxide) side‐chain steric screening effects on conductimetric properties of grafted poly(4‐vinylpyridinium) salts in aqueous solutions

A set of poly[N‐oligo(ethylene oxide)yl 4‐vinylpyridinium tosylate] (P4VOEOOTs) has been prepared by spontaneous polymerization of 4‐vinylpyridine. This method gives a grafted polyelectrolyte having a positive charge on every backbone pyridinic moiety. The P4VP15Ts, P4VP164Ts, P4VP350Ts and P4VP750Ts aqueous solution conductivities were determined in the concentration range from 6 × 10^?4 to 10^?2 M at 25 °C. The variation of the conductivity versus concentration of the investigated system exhibits typical polyelectrolyte behaviour. The polyelectrolyte mobility was found to be dependent on the oligo(ethylene oxide) (OEO) side‐chain length. Manning's rod‐like model fails to describe these results. A simple steric effect is proposed to explain the influence of the OEO length. Copyright © 2003 Society of Chemical Industry     

A Least Squares Approach to Escalator Algorithms for Adaptive Filtering

In this paper, we introduce an escalator (ESC) algorithm based on the least squares (LS) criterion. The proposed algorithm is relatively insensitive to the eigenvalue spread ratio (ESR) of an input signal and has a faster convergence speed than the conventional ESC algorithms. This algorithm exploits the fast adaptation ability of least squares methods and the orthogonalization property of the ESC structure. From the simulation results, the proposed algorithm shows superior convergence performance.