Assessment of the continuous wavelet transform in the modal parameters estimation of 2MM and 3MM systems

In this paper, our interest is in the identification of a special class of electromechanical systems: a motor‐drive system using the continuous wavelet transform method. This new modal analysis technique is evaluated in terms of its accuracy in the estimation of the modal parameters, its ability in distinguishing and separating several modes, its resistance to noisy conditions, and its usability with different excitations types. For this investigation, two models of elastic drive systems are considered: the two‐mass model and the three‐mass model. Simulation results of the study are presented, and the effectiveness of the developed identification method is discussed. © 2012 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Analysis of a discrete time table polling system with MAP input and time‐limited service discipline

An iterative procedure based on the MAP/PH/1 and MAP/PH/1/K queues with vacation is presented for approximating the performance measures of a table polling system. Each queue has a time limit after which it relinquishes the server. This is formally known as the token holding time (THT) in IEEE 802.5 and IEEE 802.4 standards. The polling table can be tailored such that queues with limits on the cycle time are visited more frequently, thus, limiting the delays for real time applications. The visit period and vacation period distributions were obtained based on the properties of the discrete phase distribution. Several examples are presented and they show that the algorithm converges fairly fast and gives reasonable results. This revised version was published online in June 2006 with corrections to the Cover Date.     

Application of a Possibilitic-Based Approach to Mobile Robotics

Possibility theory offers a nice setting for information combination or data fusion. This attractiveness arises from the elastic constraints that govern the basic concepts pertaining to this theory. Consequently, many combination modes are available ranging from the conjunctive to the disjunctive passing through the compromise mode. Therefore the problem of what is the suitable combination mode for a given situation is still open. The adaptive rule proposed by Dubois and Prade contributes partly to this problem, and has been successfully employed in several applications like robotics. In this paper we apply the recently new combination rule referred to as progressive rule, which permits us to handle robustness with respect to shape modelling and takes account for a possible presence of erroneous information, to mobile robotics context. The rule explicitly accounts for the distance between each alternative and the consensus zone. The rule is then incorporated into a general scheme of fusion methodology, which allows a transformation of raw inputs into meaningful and homogeneous information that will be refined by the progressive rule. A robotics application corresponding to mobile robot localization in a structured environment is carried out. The feasibility of the possibilistic approach is demonstrated by a comparison with a standard method based on Kalman filter.     

Alfa fiber/polypropylene composites: Influence of fiber extraction method and chemical treatments

Alfa fiber/polypropylene composites were manufactured using twin-screw extrusion. Fibers were extracted using alkaline and steam explosion methods. Three chemical treatments were also applied to the alkaline-extracted fibers: stearic acid (SA), and potassium permanganate dissolved in water (KW) and in acetone (KA). Finally, thermal annealing was applied to the composites. The results indicate that composites with steam-exploded fibers had a significantly higher melt flow index than composites with alkaline-extracted fibers. Moreover, the incorporation of fibers into the matrix increased the Young's modulus, where the optimum results were obtained utilizing the alkaline-extracted fibers. Both extraction methods also significantly decreased the water uptake, especially the steam explosion. The three chemical treatments increased the melt flow index and conversely decreased the tensile strength and Young's modulus. In addition, KW treatment decreased the water uptake. Finally, thermal annealing increased the tensile strength and Young's modulus of composites with SA-treated fibers. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47392.     

Effect of mechanical activation on the structure and ferroelectric property of Na0.5K0.5NbO3

Mechanical activation synthesis of Na_0.5K_0.5NbO₃ (NKN) was studied in order to explore the effect of mechanochemical interaction on the crystal structure and microstructure of NKN powder and ceramic. A single phase, nanocrystalline perovskite NKN powder has been derived from a mixture of oxide/carbonates via a mechanical activation route with heating at an elevated temperature. With the increase in milling time, the distortion of orthorhombic structure for NKN was weakened and the cell volume of NKN powder slightly decreased. The relative density and remnant polarization of NKN ceramics were improved, and the grain became uniform and smaller for prolonged milling NKN. The developed method is well suited for the production of NKN nanocrystallite powders and refined grain NKN ceramics.     

A distributed detection and prevention scheme from malicious nodes in vehicular networks

Vehicular environments still remain vulnerable to various potential attacks because of continuous interactions and information exchange between vehicles despite the deployment of authentication techniques by communication standards. Therefore, an authenticated node with a certificate could initiate an attack while complying with implemented protocols. Some mechanisms were proposed to enhance communication technologies, but none of them was able to anticipate nodes' behavior. They also mismanage oscillating vehicles, because they evict them automatically after misbehaving. In this paper, we propose a preventive mechanism, namely, Intrusion Prevention and Detection System (IPDS), able to predict vehicles behavior. This mechanism is based on a Kalman filter to predict the future vehicles' behavior and classify them into three categories (white, gray, and black) based on their expected trustworthiness. The main concerns of this work are to prevent from various attacks, namely, DoS, false alert, and Sybil, and deal with oscillating vehicles. Therefore, IPDS treats these latter in a different way where they are introduced into a gray list and used for routing purposes until they persist in their attacks. Simulations performed using ns3 simulator highlight IPDS accuracy regarding the detection rate of malicious nodes and its good impact on the network applications performances. Copyright © 2016 John Wiley & Sons, Ltd.     

Direct limit analysis based topology optimization of foundations

Topology optimization of foundation structures is conducted using a direct limit analysis based optimization approach. Originally developed for plastic topology design of 2D superstructures and industrial structures, which are traditionally designed based on elasticity, the direct limit analysis based design method demonstrated strong intrinsic properties that make of it a promising alternative for topology design. Unlike existing methods the one proposed here is fundamentally conceived and developed in the framework of direct plastic limit analysis which is the natural and usual known framework for the analysis and design of geotechnical structures. The method is extended to handle foundation design by providing for the simultaneous presence of two materials: the soil and the reinforcement, governed by Coulomb failure law. Two types of designs are considered, namely, continuous and discrete. The first allows a range of graded densities of reinforcement that may in practice represent the types of mixtures used in soil improvement, such as cementation. In the discrete design the reinforcement consists exclusively of solid structural elements. A series of two dimensional example problems demonstrate the capabilities of the method to generate rational classical designs or uncommon but intuitively sound foundation configurations that could inspire designers to develop novel solutions.     

Space charge measurements by the thermal step method in epoxidic polymer materials

To improve the performance of insulators, space charge measurements and localisation are of fundamental importance. For this purpose we have utilised the thermal step method (TSM) which allows measurement of the space charge density within the material. The object of this study is to characterise the electric state of epoxidic polymer material used in electrical insulation, and to study the influence of different factors involving the appearance and the evolution of space charge. The influence of poling temperature as well as the manufacturing process of the material on the remaining space charge distribution is also studied. Measurements show that the space charge behaviour was influenced by two factors: the poling temperature and the manufacturing process. © 2000 Society of Chemical Industry     

A robust competitive clustering algorithm with applications incomputer vision

This paper addresses three major issues associated with conventional partitional clustering, namely, sensitivity to initialization, difficulty in determining the number of clusters, and sensitivity to noise and outliers. The proposed robust competitive agglomeration (RCA) algorithm starts with a large number of clusters to reduce the sensitivity to initialization, and determines the actual number of clusters by a process of competitive agglomeration. Noise immunity is achieved by incorporating concepts from robust statistics into the algorithm. RCA assigns two different sets of weights for each data point: the first set of constrained weights represents degrees of sharing, and is used to create a competitive environment and to generate a fuzzy partition of the data set. The second set corresponds to robust weights, and is used to obtain robust estimates of the cluster prototypes. By choosing an appropriate distance measure in the objective function, RCA can be used to find an unknown number of clusters of various shapes in noisy data sets, as well as to fit an unknown number of parametric models simultaneously. Several examples, such as clustering/mixture decomposition, line/plane fitting, segmentation of range images, and estimation of motion parameters of multiple objects, are shown