Optimal location of supports in beam structures using genetic algorithms

Real structures can be thought as an assembly of components, as for instances plates, shells and beams. This later type of component is very commonly found in structures like frames which can involve a significant degree of complexity or as a reinforcement element of plates or shells. To obtain the desired mechanical behavior of these components or to improve their operating conditions when rehabilitating structures, one of the eventual parameters to consider for that purpose, when possible, is the location of the supports. In the present work, a beam-type structure is considered, and for a set of cases concerning different number and types of supports, as well as different load cases, the authors optimize the location of the supports in order to obtain minimum values of the maximum transverse deflection. The optimization processes are carried out using genetic algorithms. The results obtained, clearly show a good performance of the approach proposed. © 2014 IEEE.

Segmentation of striatal brain structures from high resolution pet images

Dissertation presented at the Faculty of Science and Technology of the New University of Lisbon in fulfillment of the requirements for the Masters degree in Electrical Engineering and Computers

Optimal location of the workpiece in a PKM-based machining robotic cell

Most machining tasks require high accuracy and are carried out by dedicated machine-tools. On the other hand, traditional robots are flexible and easy to program, but they are rather inaccurate for certain tasks. Parallel kinematic robots could combine the accuracy and flexibility that are usually needed in machining operations. Achieving this goal requires proper design of the parallel robot. In this chapter, a multi-objective particle swarm optimization algorithm is used to optimize the structure of a parallel robot according to specific criteria. Afterwards, for a chosen optimal structure, the best location of the workpiece with respect to the robot, in a machining robotic cell, is analyzed based on the power consumed by the manipulator during the machining process.

Evidence for non-coaxiality of ferrimagnetic and paramagnetic fabrics, developed during magma flow and cooling in a thick mafic dyke

A detailed analysis of fabrics of the chilled margin of a thick dolerite dyke (Foum Zguid dyke, Southern Morocco) was performed in order to better understand the development of sub-fabrics during dyke emplacement and cooling. AMS data were complemented with measurements of paramagnetic and ferrimagnetic fabrics (measured with high field torque magnetometer), neutron texture and microstructural analyses. The ferrimagnetic and AMS fabrics are similar, indicating that the ferrimagnetic minerals dominate the AMS signal. The paramagnetic fabric is different from the previous ones. Based on the crystallization timing of the different mineralogical phases, the paramagnetic fabric appears related to the upward flow, while the ferrimagnetic fabric rather reflects the late-stage of dyke emplacement and cooling stresses. (C) 2014 Elsevier B.V. All rights reserved.

Wrong sign and symmetric limits and non-decoupling in 2HDMs

We analyse the possibility that, in two Higgs doublet models, one or more of the Higgs couplings to fermions or to gauge bosons change sign, relative to the respective Higgs Standard Model couplings. Possible sign changes in the coupling of a neutral scalar to charged ones are also discussed. These wrong signs can have important physical consequences, manifesting themselves in Higgs production via gluon fusion or Higgs decay into two gluons or into two photons. We consider all possible wrong sign scenarios, and also the symmetric limit, in all possible Yukawa implementations of the two Higgs doublet model, in two different possibilities: the observed Higgs boson is the lightest CP-even scalar, or the heaviest one. We also analyse thoroughly the impact of the currently available LHC data on such scenarios. With all 8 TeV data analysed, all wrong sign scenarios are allowed in all Yukawa types, even at the 1 sigma level. However, we will show that B-physics constraints are crucial in excluding the possibility of wrong sign scenarios in the case where tan beta is below 1. We will also discuss the future prospects for probing the wrong sign scenarios at the next LHC run. Finally we will present a scenario where the alignment limit could be excluded due to non-decoupling in the case where the heavy CP-even Higgs is the one discovered at the LHC.

Optimal approximation of fractional derivatives through discrete-time fractions using genetic algorithms

This study addresses the optimization of rational fraction approximations for the discrete-time calculation of fractional derivatives. The article starts by analyzing the standard techniques based on Taylor series and Padé expansions. In a second phase the paper re-evaluates the problem in an optimization perspective by tacking advantage of the flexibility of the genetic algorithms.

Equilibrium distributions of discrete non-autonomous graphs

We introduce the notions of equilibrium distribution and time of convergence in discrete non-autonomous graphs. Under some conditions we give an estimate to the convergence time to the equilibrium distribution using the second largest eigenvalue of some matrices associated with the system.

Comments on ‘‘Modeling fractional stochastic systems as non-random fractional dynamics driven Brownian motions

Applied Mathematical Modelling, Vol.33

Global localization with non-quantized local image features

In the field of appearance-based robot localization, the mainstream approach uses a quantized representation of local image features. An alternative strategy is the exploitation of raw feature descriptors, thus avoiding approximations due to quantization. In this work, the quantized and non-quantized representations are compared with respect to their discriminativity, in the context of the robot global localization problem. Having demonstrated the advantages of the non-quantized representation, the paper proposes mechanisms to reduce the computational burden this approach would carry, when applied in its simplest form. This reduction is achieved through a hierarchical strategy which gradually discards candidate locations and by exploring two simplifying assumptions about the training data. The potential of the non-quantized representation is exploited by resorting to the entropy-discriminativity relation. The idea behind this approach is that the non-quantized representation facilitates the assessment of the distinctiveness of features, through the entropy measure. Building on this finding, the robustness of the localization system is enhanced by modulating the importance of features according to the entropy measure. Experimental results support the effectiveness of this approach, as well as the validity of the proposed computation reduction methods.

Cournot competition between a non-profit firm and a for-profit firm with uncertainty

In this paper, we consider a Cournot competition between a nonprofit firm and a for-profit firm in a homogeneous goods market, with uncertain demand. Given an asymmetric tax schedule, we compute explicitly the Bayesian-Nash equilibrium. Furthermore, we analyze the effects of the tax rate and the degree of altruistic preference on market equilibrium outcomes.

Treatment of relapsing chronic infections of the respiratory tract: a comparative study of the effectiveness of non specific immunotherapy with the immunoadjuvant p40 and of vaccinotherapy

The treatment of relapsing chronic infections (RCI) encounters many difficulties. In the present study, the use of the immuno adjuvant P40 either alone or in association with vaccinotherapy for the treatment of RCI turned out to be very effective, whereas vaccinotherapy alone was not. It is hypothesized that cell-mediated immunity may play a major role in controlling RCI, since the clinical improvement of the patients kept up with the positivation of previously negative skin tests carried out with either the specific infecting agent or with recall-anti gens.

A coherent approach to non-integer order derivatives

Signal Processing, vol. 86, nº 10

Optimal offering strategies for wind power producers considering uncertainty and risk

This paper provides a two-stage stochastic programming approach for the development of optimal offering strategies for wind power producers. Uncertainty is related to electricity market prices and wind power production. A hybrid intelligent approach, combining wavelet transform, particle swarm optimization and adaptive-network-based fuzzy inference system, is used in this paper to generate plausible scenarios. Also, risk aversion is explicitly modeled using the conditional value-at-risk methodology. Results from a realistic case study, based on a wind farm in Portugal, are provided and analyzed. Finally, conclusions are duly drawn.

Occurrence of campylobacter jejuni in diarrhoeic and non-diarrhoeic children in Sao Paulo, Brazil

Campylobacter jejuni was looked for in the feaces of 262 children, beeing 189 with acute diarrhoea, 31 with chronic diarrhoea and 42 controls. The organism was isolated from 14 (7.4%), 2 (6.5%) and 6 (14.3%) of the children, and each group, respectively.

Optimal design for active damping in sandwich structures using the Direct MultiSearch method

This paper addresses the problem of optimal positioning of surface bonded piezoelectric patches in sandwich plates with viscoelastic core and laminated face layers. The objective is to maximize a set of modal loss factors for a given frequency range using multiobjective topology optimization. Active damping is introduced through co-located negative velocity feedback control. The multiobjective topology optimization problem is solved using the Direct MultiSearch Method. An application to a simply supported sandwich plate is presented with results for the maximization of the first six modal loss factors. The influence of the finite element mesh is analyzed and the results are, to some extent, compared with those obtained using alternative single objective optimization.