144 resultados para Self-organizing networks


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This work deals with neural network (NN)-based gait pattern adaptation algorithms for an active lower-limb orthosis. Stable trajectories with different walking speeds are generated during an optimization process considering the zero-moment point (ZMP) criterion and the inverse dynamic of the orthosis-patient model. Additionally, a set of NNs is used to decrease the time-consuming analytical computation of the model and ZMP. The first NN approximates the inverse dynamics including the ZMP computation, while the second NN works in the optimization procedure, giving an adapted desired trajectory according to orthosis-patient interaction. This trajectory adaptation is added directly to the trajectory generator, also reproduced by a set of NNs. With this strategy, it is possible to adapt the trajectory during the walking cycle in an on-line procedure, instead of changing the trajectory parameter after each step. The dynamic model of the actual exoskeleton, with interaction forces included, is used to generate simulation results. Also, an experimental test is performed with an active ankle-foot orthosis, where the dynamic variables of this joint are replaced in the simulator by actual values provided by the device. It is shown that the final adapted trajectory follows the patient intention of increasing the walking speed, so changing the gait pattern. (C) Koninklijke Brill NV, Leiden, 2011

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During the last few years, the evolution of fieldbus and computers networks allowed the integration of different communication systems involving both production single cells and production cells, as well as other systems for business intelligence, supervision and control. Several well-adopted communication technologies exist today for public and non-public networks. Since most of the industrial applications are time-critical, the requirements of communication systems for remote control differ from common applications for computer networks accessing the Internet, such as Web, e-mail and file transfer. The solution proposed and outlined in this work is called CyberOPC. It includes the study and the implementation of a new open communication system for remote control of industrial CNC machines, making the transmission delay for time-critical control data shorter than other OPC-based solutions, and fulfilling cyber security requirements.

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This work presents a statistical study on the variability of the mechanical properties of hardened self-compacting concrete, including the compressive strength, splitting tensile strength and modulus of elasticity. The comparison of the experimental results with those derived from several codes and recommendations allows evaluating if the hardened behaviour of self-compacting concrete can be appropriately predicted by the existing formulations. The variables analyzed include the maximum size aggregate, paste and gravel content. Results from the analyzed self-compacting concretes presented variability measures in the same range than the expected for conventional vibrated concrete, with all the results within a confidence level of 95%. From several formulations for conventional concrete considered in this study, it was observed that a safe estimation of the modulus of elasticity can be obtained from the value of compressive strength; with lower strength self-compacting concretes presenting higher safety margins. However, most codes overestimate the material tensile strength. (C) 2010 Elsevier Ltd. All rights reserved.

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Artificial neural networks have been used to analyze a number of engineering problems, including settlement caused by different tunneling methods in various types of ground mass. This paper focuses on settlement over shotcrete- supported tunnels on Sao Paulo subway line 2 (West Extension) that were excavated in Tertiary sediments using the sequential excavation method. The adjusted network is a good tool for predicting settlement above new tunnels to be excavated in similar conditions. The influence of network training parameters on the quality of results is also discussed. (C) 2007 Elsevier Ltd. All rights reserved.

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This paper presents a strategy for the solution of the WDM optical networks planning. Specifically, the problem of Routing and Wavelength Allocation (RWA) in order to minimize the amount of wavelengths used. In this case, the problem is known as the Min-RWA. Two meta-heuristics (Tabu Search and Simulated Annealing) are applied to take solutions of good quality and high performance. The key point is the degradation of the maximum load on the virtual links in favor of minimization of number of wavelengths used; the objective is to find a good compromise between the metrics of virtual topology (load in Gb/s) and of the physical topology (quantity of wavelengths). The simulations suggest good results when compared to some existing in the literature.

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In all-optical networks, management of physical layer restrictions should collaborate in lightpath establishment. Label-Switched Path validation in Generalized MultiProtocol Label Switching on Dense Wavelength Division Multiplexing network requires the treatment of the physical impairment-related parameters along the provisioned route. In this paper we propose, for the first time in our view, the generation of an optical layer database by simulation that specifically characterizes the dynamic FWM impairments for the lightpaths provisioned in a GMPLS/DWDM network.

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Considering the increasing popularity of network-based control systems and the huge adoption of IP networks (such as the Internet), this paper studies the influence of network quality of service (QoS) parameters over quality of control parameters. An example of a control loop is implemented using two LonWorks networks (CEA-709.1) interconnected by an emulated IP network, in which important QoS parameters such as delay and delay jitter can be completely controlled. Mathematical definitions are provided according to the literature, and the results of the network-based control loop experiment are presented and discussed.

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Wireless Sensor Networks (WSNs) have a vast field of applications, including deployment in hostile environments. Thus, the adoption of security mechanisms is fundamental. However, the extremely constrained nature of sensors and the potentially dynamic behavior of WSNs hinder the use of key management mechanisms commonly applied in modern networks. For this reason, many lightweight key management solutions have been proposed to overcome these constraints. In this paper, we review the state of the art of these solutions and evaluate them based on metrics adequate for WSNs. We focus on pre-distribution schemes well-adapted for homogeneous networks (since this is a more general network organization), thus identifying generic features that can improve some of these metrics. We also discuss some challenges in the area and future research directions. (C) 2010 Elsevier B.V. All rights reserved.

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The continuous growth of peer-to-peer networks has made them responsible for a considerable portion of the current Internet traffic. For this reason, improvements in P2P network resources usage are of central importance. One effective approach for addressing this issue is the deployment of locality algorithms, which allow the system to optimize the peers` selection policy for different network situations and, thus, maximize performance. To date, several locality algorithms have been proposed for use in P2P networks. However, they usually adopt heterogeneous criteria for measuring the proximity between peers, which hinders a coherent comparison between the different solutions. In this paper, we develop a thoroughly review of popular locality algorithms, based on three main characteristics: the adopted network architecture, distance metric, and resulting peer selection algorithm. As result of this study, we propose a novel and generic taxonomy for locality algorithms in peer-to-peer networks, aiming to enable a better and more coherent evaluation of any individual locality algorithm.

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Video adaptation is an extensively explored content providing technique aimed at appropriately suiting several usage scenarios featured by different network requirements and constraints, user`s terminal and preferences. However, its usage in high-demand video distribution systems, such as CNDs, has been badly approached, ignoring several aspects of optimization of network use. To address such deficiencies, this paper presents an approach for implementing the adaptation service by exploring the concept of overlay services networks. As a result of demonstrate the benefits of this proposal, it is made a comparison of this proposed adaptation service with other strategies of video adaptation.

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This paper proposes a simple high-level programming language, endowed with resources that help encoding self-modifying programs. With this purpose, a conventional imperative language syntax (not explicitly stated in this paper) is incremented with special commands and statements forming an adaptive layer specially designed with focus on the dynamical changes to be applied to the code at run-time. The resulting language allows programmers to easily specify dynamic changes to their own program`s code. Such a language succeeds to allow programmers to effortless describe the dynamic logic of their adaptive applications. In this paper, we describe the most important aspects of the design and implementation of such a language. A small example is finally presented for illustration purposes.

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This paper shows a new hybrid method for risk assessment regarding interruptions in sensitive processes due to faults in electric power distribution systems. This method determines indices related to long duration interruptions and short duration voltage variations (SDVV), such as voltage sags and swells in each customer supplied by the distribution network. Frequency of such occurrences and their impact on customer processes are determined for each bus and classified according to their corresponding magnitude and duration. The method is based on information regarding network configuration, system parameters and protective devices. It randomly generates a number of fault scenarios in order to assess risk areas regarding long duration interruptions and voltage sags and swells in an especially inventive way, including frequency of events according to their magnitude and duration. Based on sensitivity curves, the method determines frequency indices regarding disruption in customer processes that represent equipment malfunction and possible process interruptions due to voltage sags and swells. Such approach allows for the assessment of the annual costs associated with each one of the evaluated power quality indices.

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In this paper a computational implementation of an evolutionary algorithm (EA) is shown in order to tackle the problem of reconfiguring radial distribution systems. The developed module considers power quality indices such as long duration interruptions and customer process disruptions due to voltage sags, by using the Monte Carlo simulation method. Power quality costs are modeled into the mathematical problem formulation, which are added to the cost of network losses. As for the EA codification proposed, a decimal representation is used. The EA operators, namely selection, recombination and mutation, which are considered for the reconfiguration algorithm, are herein analyzed. A number of selection procedures are analyzed, namely tournament, elitism and a mixed technique using both elitism and tournament. The recombination operator was developed by considering a chromosome structure representation that maps the network branches and system radiality, and another structure that takes into account the network topology and feasibility of network operation to exchange genetic material. The topologies regarding the initial population are randomly produced so as radial configurations are produced through the Prim and Kruskal algorithms that rapidly build minimum spanning trees. (C) 2009 Elsevier B.V. All rights reserved.

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This work presents the development and implementation of an artificial neural network based algorithm for transmission lines distance protection. This algorithm was developed to be used in any transmission line regardless of its configuration or voltage level. The described ANN-based algorithm does not need any topology adaptation or ANN parameters adjustment when applied to different electrical systems. This feature makes this solution unique since all ANN-based solutions presented until now were developed for particular transmission lines, which means that those solutions cannot be implemented in commercial relays. (c) 2011 Elsevier Ltd. All rights reserved.

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Effective solids suspension is a necessary precondition for particle collection, and solids suspension is largely dependent on the hydrodynamics of the flotation cell. This study attempted to correlate the status of the suspension of apatite particles of different sizes in a Denver laboratory flotation cell versus the impeller rotational speed (N) adopted to operate the machine. The latter variable (N) influences the impeller capacity to lift the particles from the bottom of the tank and also to disperse them throughout the volume of the vessel. Such an impeller capacity can be characterized by the critical impeller speed for the accomplishment of solids off-bottom suspension (N(z)) and also by the velocity of the radial water flow discharged by the impeller (U) divided by the particle terminal settling velocity (U(s)). This way, the status of the suspension of apatite particles inside the flotation cell can be characterized by one of three categories: ""segregation"" (N/N(2) < 0.60 and U(s)/U > 0.08); ""suspension"" (0.60 <= N/N(2) < 1 and 0.06 < U(s)/U < 0.10); and ""dragging"" (N/N(2) >= 1 and U(s)/U <= 0.03). The range of impeller rotational speed (N), which was able to suspend the finest particles (D(p) = 90,mu m), was unable to suspend the coarsest particles (D(P) = 254 mu m). Conversely, the high value of N (N > 1,300 rpm), which is adequate to suspend the coarsest particles, may promote the entrainment of the finest particles to the froth layer.