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Scientometrics - Scholars present their new research at seminars and conferences and send drafts to peers in hopes of receiving comments and suggestions that will improve the quality of their work....     

Optimization–Simulation Model for Planning Supply Transport to Large Infrastructure Public Works Located in Congested Urban Areas

This article proposes an optimization–simulation model for planning the transport of supplies to large public infrastructure works located in congested urban areas. The purpose is to minimize their impact on the environment and on private transportation users on the local road network. To achieve this goal, the authors propose and solve an optimization problem for minimizing the total system cost made up of operating costs for various alternatives for taking supplies to the worksite and the costs supported by private vehicle users as a result of increased congestion due to the movement of heavy goods vehicles transporting material to the worksite. The proposed optimization problem is a bi-level Math Program model. The upper level defines the total cost of the system, which is minimized taking into account environmental constraints on atmospheric and noise pollution. The lower level defines the optimization problem representing the private transportation user behavior, assuming they choose the route that minimizes their total individual journey costs. Given the special characteristics of the problem, a heuristic algorithm is proposed for finding optimum solutions. Both the model developed and the specific solution algorithm are applied to the real case of building a new port at Laredo (Northern Spain). A series of interesting conclusions are obtained from the corresponding sensitivity analysis.     

A stable multimodel scheme control for the regulation of the transient behavior of a tunnel-diode trigger circuit

A multimodel scheme is designed for a triggering tunnel-diode circuit. The scheme improves the transient behavior during the transition time period after switching from a stable system equilibrium point to another one which is known as a triggering process. Each model is obtained by a linearization of the circuit near an equilibrium point. Moreover, each of these models can be described as a combination of two other transfer functions describing the linearized plant behavior near two different equilibrium points. The scheme chooses online the model with the best tracking performance in order to generate the control law. Different reference transfer functions are proposed with the aim of generating the desired transient in the triggering process. Some simulations show the usefulness of this scheme.     

Attacking the Pollard Generator

Let p be a prime and let c be an integer modulo p. The Pollard generator is a sequence (u_n) of pseudorandom numbers defined by the relation u_n+1equivu_n ²+c mod p. It is shown that if c and 9/14 of the most significant bits of two consecutive values u_n,u_n+1 of the Pollard generator are given, one can recover in polynomial time the initial value u₀ with a probabilistic algorithm. This result is an improvement of a theorem in a recent paper which requires that 2/3 of the most significant bits be known     

Recurrent ANN-based modelling of the dynamic evolution of the surface roughness in grinding

Grinding is critical in modern manufacturing due to its capacity for producing high surface quality and high-precision parts. One of the most important parameters that indicate the grinding quality is the surface roughness (R _a). Analytical models developed to predict surface finish are not easy to apply in the industry. Therefore, many researchers have made use of artificial neural networks. However, all the approaches provide a particular solution for a wheel–workpiece pair, not generalizing to new grinding wheels. Besides, these solutions do not give surface roughness values related to the grinding wheel status. Therefore, in this work the modelling of the dynamic evolution of the surface roughness (R _a) based on recurrent neural networks is presented with the capability to generalize to new grinding wheels and conditions taking into account the wheel wear. Results show excellent prediction of the surface finish dynamic evolution. The absolute maximum error is below 0.49 µm, being the average error around 0.32 µm. Besides, the analysis of the relative importance of the inputs shows that the grinding conditions have higher influence than the wheel characteristics over the prediction of the surface roughness confirming experimental knowledge of grinding technology users.

     

Robustly stable adaptive control of a tandem of master-slave robotic manipulators with force reflection by using a multiestimation scheme.

The problem of controlling a tandem of robotic manipulators composing a teleoperation system with force reflection is addressed in this paper. The final objective of this paper is twofold: 1) to design a robust control law capable of ensuring closed-loop stability for robots with uncertainties and 2) to use the so-obtained control law to improve the tracking of each robot to its corresponding reference model in comparison with previously existing controllers when the slave is interacting with the obstacle. In this way, a multiestimation-based adaptive controller is proposed. Thus, the master robot is able to follow more accurately the constrained motion defined by the slave when interacting with an obstacle than when a single-estimation-based controller is used, improving the transparency property of the teleoperation scheme. The closed-loop stability is guaranteed if a minimum residence time, which might be updated online when unknown, between different controller parameterizations is respected. Furthermore, the analysis of the teleoperation and stability capabilities of the overall scheme is carried out. Finally, some simulation examples showing the working of the multiestimation scheme complete this paper.     

Screening of Fe–Cu-Zeolites Prepared by Different Methodology for Application in NSR–SCR Combined DeNOx Systems

The NO_x NH₃-SCR performance of several Cu and Fe catalysts supported on BETA and ZSM-5 zeolites has been studied in single SCR and double NSR–SCR configuration, and the activity related to the nature and reducibility of metal species on the catalyst surface. Intermediate ammonia formed in NSR improved greatly NO_x conversion at the exit of the double NSR–SCR configuration, which was practically totally converted to N₂.     

Characterization of the Main Semiconductor Laser Static and Dynamic Working Parameters From CW Optical Spectrum Measurements

We present a complete characterization of the work parameters of several types of semiconductor lasers. Static parameters as: power, linewidth and linewidth enhancement factor and also dynamic parameters such as: relaxation oscillations, relative intensity noise and damping rates are calculated using measurements of the optical spectrum of the lasers operated in continuous-wave mode. Methods for the calculation of these parameters are described and applied to the lasers under test by means of a single general setup and a single set of measurements     

An energy efficient intelligent torque vectoring approach based on fuzzy logic controller and neural network tire forces estimator

Neural Computing and Applications - In electric vehicles (EVs) with multiple motors, torque vectoring (TV) control can effectively enhance the cornering response and safety. Moreover, TV systems...