Reduction of matched and unmatched uncertainties for a class of nonlinear perturbed systems via robust control

The aim of this paper is to design a robust control for stabilization of a class of nonlinear perturbed system subject to matched and unmatched disturbances. Here, the concept of dynamic sliding mode control and the attractive ellipsoid method advantages are used to design a robust nonlinear control algorithm, which reduces considerably the perturbation effects. Hence, in finite time, the dynamic sliding mode control brings the system trajectory to a specific configuration. After this time, the controller reduces the perturbation effects by using the high‐gain control obtained in the attractive ellipsoid method. Thus, based on the solution of a specific matrix inequality, the feedback control of the system guarantees that the trajectory will be stabilized in the ultimate uniform bounded sense. To illustrate the theoretical results, a numerical example with a comparative study is introduced. Finally, the performance of the controller designed in this paper is tested on an electromechanical real‐time system.     

Simultaneous localization and mapping for aerial vehicles: a 3-D sensor-based GAS filter

This paper presents the design, analysis, and experimental validation of a globally asymptotically stable (GAS) filter for simultaneous localization and mapping (SLAM) with application to unmanned aerial vehicles. The main contributions of this paper are the results of global convergence and stability for SLAM in tridimensional (3-D) environments. The SLAM problem is formulated in a sensor-based framework and modified in such a way that the structure may be regarded as linear time-varying for observability purposes, from which a Kalman filter with GAS error dynamics follows naturally. The proposed solution includes the estimation of both body-fixed linear velocity and rate gyro measurement biases. Experimental results from several runs, using an instrumented quadrotor equipped with a RGB-D camera, are included in the paper to illustrate the performance of the algorithm under realistic conditions.     

Moderating effect of learning styles on a learning management system’s success

This study uses the DeLone and McLean model to determine the moderating impact of learning styles on the success of learning management systems from a student’s point of view. The main objectives of this research are: (1) to evaluate the Delone and McLean model of information system success in the context of learning management systems and, (2) to determine the effect of the learning styles of students on this model. An in-person survey of 258 engineering students was used to evaluate the research model. The analysis is based on structural equation modelling, specifically partial least squares. The results indicate that the research model explains use, user satisfaction, and perceived benefits of a learning management system. In addition, the Felder-Silverman learning styles (sensing-intuitive, visual-verbal; active-reflective; sequential-global) modify the strength of the relationships between the variables of the success model.     

Comparison of thin‐layer and bulk MIPs synthesized by photoinitiated in situ crosslinking polymerization from the same reaction mixtures

The synthesis and comparative characterization of molecularly imprinted polymers (MIPs) in two different formats, as thin layers grafted to the entire surface of polypropylene microfiltration membranes and as conventional particles, are described. Imprinting with atrazine was performed by using itaconic acid and N,N′‐methylene‐bisacrylamide as functional and crosslinker monomers in methanol as the solvent. Polymerization had been initiated by UV irradiation of benzoin ethyl ether and driven to low monomer conversion for the thin‐layer polymers and to high monomer conversion for the bulk materials. The binding performance of MIP composite membranes and of MIP particles packed into cartridges was evaluated in solid‐phase extraction (SPE) experiments of atrazin and simazin from aqueous solutions. The SPE performance depended strongly on pH and buffer concentration. Although an imprinting effect was observed for both formats, the specificity (MIP versus Blank) and the selectivity (atrazin versus simazin) were much higher for the thin‐layer composite membranes than for the bulk polymer particles. In particular, the atrazin/simazin selectivity increased from 32% for the Blank to 78% for the MIP composite membranes. A major reason is the hindered accessibility of the internal pore structure of the particles, whereas the porous filtration membranes are much more compatible with the fast SPE protocol. Furthermore, based on pK_a of the functional carboxylic acid groups—from potentiometric titration and polarity of the binding environment—from fluorescent probe analysis, different properties of the imprinted binding sites can be postulated for the two MIP formats. However, the differences between MIP and Blank were much more pronounced for the thin‐layer composite membranes. The hydrophobic surface of the polypropylene membrane appeared to be a major factor affecting the binding performance of thin‐layer MIPs. The new porous composite membranes could be particularly useful as selective SPE materials in environmental, pharmaceutical, and analytical applications. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 98: 362–372, 2005     

Retention properties of efficient adsorbent to silver(I)

The binding capability of crosslinked poly(acrylic acid‐co‐2‐acrylamide‐2‐methyl‐1‐propane sulfonic acid) for silver(I) ions by the batch equilibrium method is investigated. The effects of the pH, temperature, time of contact, and resin–metal ion molar ratio on the retention ability are studied. The retention for silver(I) increases from 21.7% at pH 1 to 94.6% at pH 5. The adsorption capacity at pH 5 is 1.18 meq/g dry resin. The maximum load capacity at the optimum pH is determined. In order to recover the resin, elution runs in acid and basic media are carried out. The best eluent is 4M HNO₃ (84.9%). Moreover, retention–elution cycles are performed. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 83: 1501–1506, 2002     

Fighting over water values: diverse framings of flower and food production with communal irrigation in the Ecuadorian Andes

Water management studies often overlook community diversity, different stakeholders’ values, and frames to claim water rights. Using a political-ecology approach, this article examines an irrigation system in Ecuador’s highlands via Fraser’s principles of justice (recognition, representation, redistribution). Large flower companies and indigenous smallholders frame their arguments differently to legitimize water allocation claims. Framing is effective when it resonates with other stakeholders’ values. Some unexpected findings are explained: most of the water is still used by large companies since communities took control; rules regarding water use differ greatly among sectors in the system; and small flower producers have been appearing recently.     

A practical approach for active camera coordination based on a fusion-driven multi-agent system

In this paper, we propose a multi-agent system architecture to manage spatially distributed active (or pan-tilt-zoom) cameras. Traditional video surveillance algorithms are of no use for active cameras, and we have to look at different approaches. Such multi-sensor surveillance systems have to be designed to solve two related problems: data fusion and coordinated sensor-task management. Generally, architectures proposed for the coordinated operation of multiple cameras are based on the centralisation of management decisions at the fusion centre. However, the existence of intelligent sensors capable of decision making brings with it the possibility of conceiving alternative decentralised architectures. This problem is approached by means of a MAS, integrating data fusion as an integral part of the architecture for distributed coordination purposes. This paper presents the MAS architecture and system agents.     

Fast and Scalable Mesh Superfacets

In the field of computer vision, the introduction of a low‐level preprocessing step to oversegment images into superpixels – relatively small regions whose boundaries agree with those of the semantic entities in the scene – has enabled advances in segmentation by reducing the number of elements to be labeled from hundreds of thousands, or millions, to a just few hundred. While some recent works in mesh processing have used an analogous oversegmentation, they were not intended to be general and have relied on graph cut techniques that do not scale to current mesh sizes. Here, we present an iterative superfacet algorithm and introduce adaptations of undersegmentation error and compactness, which are well‐motivated and principled metrics from the vision community. We demonstrate that our approach produces results comparable to those of the normalized cuts algorithm when evaluated on the Princeton Segmentation Benchmark, while requiring orders of magnitude less time and memory and easily scaling to, and enabling the processing of, much larger meshes.     

Hydrodynamic Instabilities in Well-Balanced Finite Volume Schemes for Frictional Shallow Water Equations. The Kinematic Wave Case

We report the developments of hydrodynamic instabilities in several well-balanced finite volume schemes that are observed during the computation of the temporal evolution of an out-balance flow which is essentially a kinematic wave. The numerical simulations are based on the one-dimensional shallow-water equations for a uniformly sloping bed with hydraulic resistance. Subsequently, we highlight the need of low dissipative high-order well-balanced filter schemes for non-equilibrium flows with variable cut-off wavenumber to compute the out-balance flow under consideration, i.e. the kinematic wave.     

A comparative study of efficient initialization methods for the k-means clustering algorithm

K-means is undoubtedly the most widely used partitional clustering algorithm. Unfortunately, due to its gradient descent nature, this algorithm is highly sensitive to the initial placement of the cluster centers. Numerous initialization methods have been proposed to address this problem. In this paper, we first present an overview of these methods with an emphasis on their computational efficiency. We then compare eight commonly used linear time complexity initialization methods on a large and diverse collection of data sets using various performance criteria. Finally, we analyze the experimental results using non-parametric statistical tests and provide recommendations for practitioners. We demonstrate that popular initialization methods often perform poorly and that there are in fact strong alternatives to these methods.