Improved formic acid oxidation using electrodeposited Pd–Cd electrocatalysts in sulfuric acid solution

In the present research, nanostructured Pd–Cd alloy electrocatalysts with different compositions were produced using the electrodeposition process. The morphology of the samples was studied by scanning electron microscopy analysis. Also, the elemental composition of the samples was determined by energy-dispersive X-ray spectroscopy and elemental mapping tests. Tafel polarization and electrochemical impedance spectroscopy methods were employed to determine the electrochemical corrosion properties of the synthesized samples in a solution containing 0.5 M sulfuric acid and 0.1 M formic acid. The linear sweep voltammetry, cyclic voltammetry, and chronoamperometry techniques were also employed to evaluate the electrocatalytic activity of prepared samples toward the oxidation of formic acid. In this respect, the influence of some factors such as formic acid and sulfuric acid concentrations and also potential scan rate was investigated. Compared to the pure Pd sample, the Pd–Cd samples were more reactive for the oxidation of formic acid. Besides, the sample with a lower amount of Pd (Pd_1·3Cd) demonstrated much higher electrocatalytic activity than the Pd_7·1Cd and Pd_2·1Cd samples. The observed high mass activity of 15.06 A mg^?1_Pd for the Pd_1·3Cd sample which is 21.1 times higher than Pd/C is an interesting result of this study.     

Learning nonlinear dynamics with behavior ordinary/partial/system of the differential equations: looking through the lens of orthogonal neural networks

In this paper, size-dependent dynamic stability of axially loaded functionally graded (FG) composite truncated conical microshells with magnetostrictive facesheets surrounded by nonlinear viscoelastic foundations including a two-parameter Winkler–Pasternak medium augmented via a Kelvin–Voigt viscoelastic approach is analyzed considering nonlinear cubic stiffness. To this purpose, von Karman-type kinematic nonlinearity along with modified couple stress theory of elasticity was applied to third-order shear deformation conical shell theory in the presence of magnetic permeability tensor and magnetic fluxes. The numerical technique of generalized differential quadrature (GDQ) was used for the solution of microstructural-dependent dynamic stability responses of FG composite truncated conical microshells. It was seen that moving from prebuckling to postbuckling domain somehow increased the significance of couple stress type of size dependency on frequency. In addition, within both prebuckling and postbuckling regimes, an increase of material gradient index decreased the importance of couple stress type of size dependency on the frequency of an axially loaded FG composite truncated conical microshell. Furthermore, it was revealed that by applying a positive magnetic field to an axially loaded truncated conical microshell with magnetostrictive facesheets, its frequency at a specific axial load value was increased in prebuckling domain and decreased in postbuckling domain. However, this pattern was reversed by applying a negative magnetic field.

     

A Measurement‐Based Approach for Designing Fixed‐Order Controllers for Unknown Closed‐Loop Architecture

This paper presents a new technique to design fixed‐structure controllers for linear unknown systems using a set of measurements. In model‐based approaches, the measured data are used to identify a model of the plant for which a suitable controller can be designed. Due to the fact that real processes cannot be described perfectly by mathematical models, designing controllers using such models to guarantee some desired closed‐loop performance is a challenging task. Hence, a possible alternative to model‐based methods is to directly utilize the measured data in the design process. We propose an approach to designing structured controllers using a set of closed‐loop frequency‐domain data. The principle of such an approach is based on computing the parameters of a fixed‐order controller for which the closed‐loop frequency response fits a desired frequency response that describes some desired performance indices. This problem is formulated as an error minimization problem, which can be solved to find suitable values of the controller parameters. The main feature of the proposed control methodology is that it can be applied to stable and unstable plants. Additionally, the design process depends on a pre‐selected controller structure, which allows for the selection of low‐order controllers. An application of the proposed method to a DC servomotor system is presented to experimentally validate and demonstrate its efficacy.     

The design of a collision avoidance system for use by Pilots operating on the airport ramp and in taxiway areas

Ground collisions have serious implications from both a safety and a commercial perspective. This paper reports on human computer interaction (HCI) research related to the advancement of a collision avoidance system, for use by Pilots operating on the airport ramp and in taxiway areas. Primarily, this paper focuses on the key findings of this research and the emerging HCI design solution.     

A C5 parallel robot identification and control

The paper proposes a controller scheme based on a priori identification for a C5 parallel robot. First we realize the identification of dynamic parameters of the robot using the Least Squares technique. Different data are used for this step of identification. The cross validation permitted to select and confirm the identified parameters. After, a control scheme (computed torque) is applied to control the C5 parallel robot. The functions of this control scheme are based on precedent identified parameters. In order to reduce the effect of the identification error, we have added a robustness term based on sliding mode technique. The stability of the system in closed loop is presented using the Lyapunov principle. Experimental results of identification and control are presented and show the effectiveness of our methodology.     

Blind spatial unmixing of multispectral images: New methods combining sparse component analysis,clustering and non-negativity constraints

Remote sensing has become an unavoidable tool for better managing our environment, generally by realizing maps of land cover using classification techniques. Traditional classification techniques assign only one class (e.g., water, soil, grass) to each pixel of remote sensing images. However, the area covered by one pixel contains more than one surface component and results in the mixture of these surface components. In such situations, classical classification is not acceptable for many major applications, such as environmental monitoring, agriculture, mineral exploration and mining, etc. Most methods proposed for treating this problem have been developed for hyperspectral images. On the contrary, there are very few automatic techniques suited to multispectral images. In this paper, we propose new unsupervised spatial methods (called 2D-Corr-NLS and 2D-Corr-NMF) in order to unmix each pixel of a multispectral image for better recognizing the surface components constituting the observed scene. These methods are related to the blind source separation (BSS) problem, and are based on sparse component analysis (SCA), clustering and non-negativity constraints. Our approach consists in first identifying the mixing matrix involved in this BSS problem, by using the first stage of a spatial correlation-based SCA method with very limited source sparsity constraints, combined with clustering. Non-negative least squares (NLS) or non-negative matrix factorization (NMF) methods are then used to extract spatial sources. An important advantage of our proposed methods is their applicability to the possibly globally underdetermined, but locally (over)determined BSS model in multispectral remote sensing images. Experiments based on realistic synthetic mixtures and real multispectral images collected by the Landsat ETM+ and the Formosat-2 sensors are performed to evaluate the performance of the proposed approach. We also show that our methods significantly outperform the sequential maximum angle convex cone (SMACC) method.     

DISTRIBUTION AND HABITAT USE OF THE MISSOURI RIVER AND LOWER YELLOWSTONE RIVER BENTHIC FISHES FROM 1996 TO 1998: A BASELINE FOR FISH COMMUNITY RECOVERY

Past and present Missouri River management practices have resulted in native fishes being identified as in jeopardy. In 1995, the Missouri River Benthic Fishes Study was initiated to provide improved information on Missouri River fish populations and how alterations might affect them. The study produced a baseline against which to evaluate future changes in Missouri River operating criteria. The objective was to evaluate population structure and habitat use of benthic fishes along the entire mainstem Missouri River, exclusive of reservoirs. Here we use the data from this study to provide a recent‐past baseline for on‐going Missouri River fish population monitoring programmes along with a more powerful method for analysing data containing large percentages of zero values. This is carried out by describing the distribution and habitat use of 21 species of Missouri River benthic fishes based on catch‐per‐unit area data from multiple gears. We employ a Bayesian zero‐inflated Poisson model expanded to include continuous measures of habitat quality (i.e. substrate composition, depth, velocity, temperature, turbidity and conductivity). Along with presenting the method, we provide a relatively complete picture of the Missouri River benthic fish community and the relationship between their relative population numbers and habitat conditions. We demonstrate that our single model provides all the information that is often obtained by a myriad of analytical techniques. An important advantage of the present approach is reliable inference for patterns of relative abundance using multiple gears without using gear efficiencies. Copyright © 2011 John Wiley & Sons, Ltd.     

Artificial intelligence implementation in the APS process diagnostic

Thermal spray process is a technique of coating manufacturing implementing a wide variety of materials and processes. This technique is characterized by up to 150 processing parameters influencing the coating properties. The control of the coating quality is needed through the consideration of a robust methodology that takes into account the parameter interdependencies, the process variability and offers the ability to quantify the processing parameter-process response relationships. The aim of this work is to introduce a new approach based on artificial intelligence responding to these requirements. A detailed procedure is presented considering an artificial neural network (ANN) structure which encodes implicitly the physical phenomena governing the process. The implementation of such a structure was coupled to experimental results of an optic sensor controlling the powder particle fusion state before the coating formation. The optimization steps were discussed and the predicted results were compared to the experimental ones allowing the identification of the control factors.     

Real-time wrist localization in color images based on corner analysis

Hand detection and gestures recognition have become very popular in recent human-computer interaction systems. Although several methods of hand detection have been proposed in the literature, they exist few methods that use the wrist as a factor of detection, others impose constraints on the length of the sleeves and on the orientation of the hand. In this work, we present a new two-stage algorithm of wrist localization designed for hand detection and gestures recognition systems. The first stage of the algorithm consists in separating the skin region containing the hand from the background, and in the second stage, the wrist is localized from the resulted skin mask. The main contribution of the proposed method is based on the analysis of corners along the contour of the skin masks to localize the wrist emplacement. Based on an evaluation on 437 color images with their ground-truth and three sets of skin masks, we compared our method with other efficient methods of literature and the results obtained were very satisfactory.