Fractional dynamics of genetic algorithms using hexagonal space tessellation

The paper formulates a genetic algorithm that evolves two types of objects in a plane. The fitness function promotes a relationship between the objects that is optimal when some kind of interface between them occurs. Furthermore, the algorithm adopts an hexagonal tessellation of the two-dimensional space for promoting an efficient method of the neighbour modelling. The genetic algorithm produces special patterns with resemblances to those revealed in percolation phenomena or in the symbiosis found in lichens. Besides the analysis of the spacial layout, a modelling of the time evolution is performed by adopting a distance measure and the modelling in the Fourier domain in the perspective of fractional calculus. The results reveal a consistent, and easy to interpret, set of model parameters for distinct operating conditions.

Mix design process of polyester polymer mortars modified with recycled GFRP waste materials

In this study, the effect of incorporation of recycled glass fibre reinforced plastics (GFRP) waste materials, obtained by means of shredding and milling processes, on mechanical behaviour of polyester polymer mortars (PM) was assessed. For this purpose, different contents of GFRP recyclates, between 4% up to 12% in weight, were incorporated into polyester PM materials as sand aggregates and filler replacements. The effect of the addition of a silane coupling agent to resin binder was also evaluated. Applied waste material was proceeding from the shredding of the leftovers resultant from the cutting and assembly processes of GFRP pultrusion profiles. Currently, these leftovers as well as non-conform products and scrap resulting from pultrusion manufacturing process are landfilled, with additional costs to producers and suppliers. Hence, besides the evident environmental benefits, a viable and feasible solution for these wastes would also conduct to significant economic advantages. Design of experiments and data treatment were accomplish by means of full factorial design approach and analysis of variance ANOVA. Experimental results were promising toward the recyclability of GFRP waste materials as partial replacement of aggregates and reinforcement for PM materials, with significant improvements on mechanical properties of resultant mortars with regards to waste-free formulations.

Electrochemical determination of the herbicide bentazone using a carbon nanotube b-Cyclodextrin modified electrode

An electrochemical sensor has been developed for the determination of the herbicide bentazone, based on a GC electrode modified by a combination of multiwalled carbon nanotubes (MWCNT) with b-cyclodextrin (b-CD) incorporated in a polyaniline film. The results indicate that the b-CD/MWCNT modified GC electrode exhibits efficient electrocatalytic oxidation of bentazone with high sensitivity and stability. A cyclic voltammetric method to determine bentazone in phosphate buffer solution at pH 6.0, was developed, without any previous extraction, clean-up, or derivatization steps, in the range of 10–80 mmolL 1, with a detection limit of 1.6 mmolL 1 in water. The results were compared with those obtained by an established HPLC technique. No statistically significant differences being found between both methods.

Use of negative information in positioning and tracking algorithms

To avoid additional hardware deployment, indoor localization systems have to be designed in such a way that they rely on existing infrastructure only. Besides the processing of measurements between nodes, localization procedure can include the information of all available environment information. In order to enhance the performance of Wi-Fi based localization systems, the innovative solution presented in this paper considers also the negative information. An indoor tracking method inspired by Kalman filtering is also proposed.

Tomographic imaging with a scanning laser ophtalmoscop

Retinal imaging with a confocal scaning laser Ophthalmoscope (cSLO) involves scanning a small laser beam over the retina and constructing an image from the reflected light. By applying the confocal principle, tomographic images can be produced by measuring a sequence of slices at different depths. However, the thickness of such slices, when compared with the retinal thickness, is too large to give useful 3D retinal images, if no processing is done. In this work, a prototype cSLO was modified in terms hardware and software to give the ability of doing the tomographic measurements with the maximum theoretical axial resolution possible. A model eye was built to test the performance of the system. A novel algorithm has been developed which fits a double Gaussian curve to the axial intensity profiles generated from a stack of images slices. The underlying assumption is that the laser light has mainly been reflected by two structures in the retina, the internal limiting membrane and the retinal pigment epithelium. From the fitted curve topographic images and novel thickness images of the retina can be generated. Deconvolution algorithms have also been developed to improve the axial resolution of the system, using a theoretically predicted cSLO point spread function. The technique was evaluated using measurements made on a model eye, four normal eyes and seven eyes containing retinal pathology. The reproducibility, accuracy and physiological measurements obtained, were compared with available published data, and showed good agreement. The difference in the measurements when using a double rather than a single Gaussian model was also analysed.

Task assignment algorithms for two-type heterogeneous multiprocessors

Consider the problem of assigning real-time tasks on a heterogeneous multiprocessor platform comprising two different types of processors — such a platform is referred to as two-type platform. We present two linearithmic timecomplexity algorithms, SA and SA-P, each providing the follow- ing guarantee. For a given two-type platform and a given task set, if there exists a feasible task-to-processor-type assignment such that tasks can be scheduled to meet deadlines by allowing them to migrate only between processors of the same type, then (i) using SA, it is guaranteed to find such a feasible task-to- processor-type assignment where the same restriction on task migration applies but given a platform in which processors are 1+α/2 times faster and (ii) SA-P succeeds in finding 2 a feasible task-to-processor assignment where tasks are not allowed to migrate between processors but given a platform in which processors are 1+α/times faster, where 0<α≤1. The parameter α is a property of the task set — it is the maximum utilization of any task which is less than or equal to 1.

On the implementation of real-time slotbased task-splitting scheduling algorithms for multiprocessor systems

In this paper we discuss challenges and design principles of an implementation of slot-based tasksplitting algorithms into the Linux 2.6.34 version. We show that this kernel version is provided with the required features for implementing such scheduling algorithms. We show that the real behavior of the scheduling algorithm is very close to the theoretical. We run and discuss experiments on 4-core and 24-core machines.

Implementing multicore real-time scheduling algorithms based on task splitting using ada 2012

Multiprocessors, particularly in the form of multicores, are becoming standard building blocks for executing reliable software. But their use for applications with hard real-time requirements is non-trivial. Well-known realtime scheduling algorithms in the uniprocessor context (Rate-Monotonic [1] or Earliest-Deadline-First [1]) do not perform well on multiprocessors. For this reason the scientific community in the area of real-time systems has produced new algorithms specifically for multiprocessors. In the meanwhile, a proposal [2] exists for extending the Ada language with new basic constructs which can be used for implementing new algorithms for real-time scheduling; the family of task splitting algorithms is one of them which was emphasized in the proposal [2]. Consequently, assessing whether existing task splitting multiprocessor scheduling algorithms can be implemented with these constructs is paramount. In this paper we present a list of state-of-art task-splitting multiprocessor scheduling algorithms and, for each of them, we present detailed Ada code that uses the new constructs.

Analysis of the nano-surface of a modified glassy carbon electrode by pseudo phase plane method

This paper presents the Pseudo phase plane (PPP) method for detecting the existence of a nanofilm on the nitroazobenzene-modified glassy carbon electrode (NAB-GC) system. This modified electrode systems and nitroazobenze-nanofilm were prepared by the electrochemical reduction of diazonium salt of NAB at the glassy carbon electrodes (GCE) in nonaqueous media. The IR spectra of the bare glassy carbon electrodes (GCE), the NAB-GC electrode system and the organic NAB film were recorded. The IR data of the bare GC, NAB-GC and NAB film were categorized into five series consisting of FILM1, GC-NAB1, GC1; FILM2, GC-NAB2, GC2; FILM3, GC-NAB3, GC3 and FILM4, GC-NAB4, GC4 respectively. The PPP approach was applied to each group of the data of unmodified and modified electrode systems with nanofilm. The results provided by PPP method show the existence of the NAB film on the modified GC electrode.

Characterization approach to modified glassy carbon electrode-nanofilm system within multidimensional scaling

The aim of this work is to characterize the nanofilm consisting of the benzoic acid-modified glassy carbon (GC) electrode system through multidimensional scaling space analysis. The surface modification is based on the electrochemical reaction between the GC electrode and benzoic acid-diazonium salt (BA-DAS). As a result, the nonofilms regarding the benzoic acid-glassy carbon (BA-GC) electrode surface was obtained. For the analysis of the naonfilm of BC-GC electrode system, the IR spectra of the modified BA-GC electrode surface, GC surface and BA-DAS were recorded in the spectral range of 599.84 – 3996.34 [cm–1]. The IR data vectors of the above three forms were processed by the using the multidimensional scaling space approach to demonstrate the existence of a nanofilm on the modified BA-GC electrode system. Two- and three-dimensional MDS profiles obtained by application of multidimensional scaling approach to the data sets {CG1,...,CG10}, {BA-GC1,...,BA-GC10} and {FILM1,...,FILM10} allow a good recognition of the nanofilm on the modified glassy carbon (GC) electrode system.

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.

Biodiesel production over lithium modified lime catalysts: activity and deactivation

Biodiesel production by methanolysis of semi-refined rapeseed oil was studied over lime based catalysts. In order to improve the catalysts basicity a commercial CaO material was impregnated with aqueous solution of lithium nitrate (Li/Ca = 03 atomic ratio). The catalysts were calcined at 575 degrees C and 800 degrees C, for 5 h, to remove nitrate ions before reaction. The XRD patterns of the fresh catalysts, including the bare CaO, showed lines ascribable to CaO and Ca(OH)(2). The absence of XRD lines belonging to Li phases confirms the efficient dispersion of Li over CaO. In the tested condition (W-cat/W-oil = 5%; CH3OH/oil = 12 molar ratio) all the fresh catalysts provided similar biodiesel yields (FAME >93% after 4 h) but the bare CaO catalyst was more stable. The activity decay of the Li modified samples can be related to the enhanced, by the higher basicity, calcium diglyceroxide formation during methanolysis which promotes calcium leaching. The calcination temperature for Li modified catalysts plays an important role since encourages the crystals sinterization which appears to improve the catalyst stability. (C) 2013 Elsevier B.V. All rights reserved.

Fitness function evaluation through fractional algorithms

This paper proposes a Genetic Algorithm (GA) for the design of combinational logic circuits. The fitness function evaluation is calculated using Fractional Calculus. This approach extends the classical fitness function by including a fractional-order dynamical evaluation. The experiments reveal superior results when comparing with the classical method.

Application of genetic algorithms in the design of an electrical potential of fractional order

Fractional calculus (FC) is currently being applied in many areas of science and technology. In fact, this mathematical concept helps the researches to have a deeper insight about several phenomena that integer order models overlook. Genetic algorithms (GA) are an important tool to solve optimization problems that occur in engineering. This methodology applies the concepts that describe biological evolution to obtain optimal solution in many different applications. In this line of thought, in this work we use the FC and the GA concepts to implement the electrical fractional order potential. The performance of the GA scheme, and the convergence of the resulting approximation, are analyzed. The results are analyzed for different number of charges and several fractional orders.

Optimal tuning of fractional controllers using genetic algorithms

This study addresses the optimization of fractional algorithms for the discrete-time control of linear and non-linear systems. The paper starts by analyzing the fundamentals of fractional control systems and genetic algorithms. In a second phase the paper evaluates the problem in an optimization perspective. The results demonstrate the feasibility of the evolutionary strategy and the adaptability to distinct types of systems.