A differential inclusion approach for modeling and analysis of dynamical systems under uncertainty

In this paper we deal with the application of differential inclusions to modeling nonlinear dynamical systems under uncertainty in parameters. In this case, differential inclusions seem to be better suited to modeling practical situations under uncertainty and imprecision than formulations by means of fuzzy differential equations. We develop a practical algorithm to approximate the reachable sets of a class of nonlinear differential inclusion, which eludes the computational problems of a previous set-valued version of the Heun’s method. Our algorithm is based on a complete discretization (time and state space) of the differential inclusion and it suits hardware features, handling the memory used by the method in a controlled fashion during all iterations. As a case of study, we formulate a differential inclusion to model an epidemic outbreak of dengue fever under Cuban conditions. The model takes into account interaction of human and mosquito populations as well as vertical transmission in the mosquito population. It is studied from the theoretical point of view to apply the Practical Algorithm. Also, we estimate the temporal evolution of the different human and mosquito populations given by the model in the Dengue 3 epidemic in Havana 2001, through the computation of the reachable sets using the Practical Algorithm.     

Automatic mapping of parallel applications on multicore architectures using the Servet benchmark suite

Servet is a suite of benchmarks focused on detecting a set of parameters with high influence on the overall performance of multicore systems. These parameters can be used for autotuning codes to increase their performance on multicore clusters. Although Servet has been proved to detect accurately cache hierarchies, bandwidths and bottlenecks in memory accesses, as well as the communication overhead among cores, up to now the impact of the use of this information on application performance optimization has not been assessed. This paper presents a novel algorithm that automatically uses Servet for mapping parallel applications on multicore systems and analyzes its impact on three testbeds using three different parallel programming models: message-passing, shared memory and partitioned global address space (PGAS). Our results show that a suitable mapping policy based on the data provided by this tool can significantly improve the performance of parallel applications without source code modification.     

Morphological contrast index based on the Weber's law

In this article, a morphological contrast index based on the Weber's law is proposed to quantify the contrast in a processed image. This measure involves the contours of the image along with its background. The proposal made here is applied to detect the image with higher contrast, and also identify the enhanced image most similar to the original. Moreover, the contrast index is compared with other four indexes reported in the current literature. © 2012 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 22, 137–144, 2012     

Diagnostic Tools for Wireless Sensor Networks: A Comparative Survey

The availability of tools to diagnose Wireless Sensor Network (WSN) failures is a key success factor for this type of networks as already demonstrated by several long-running deployments. By nature, WSNs are resource-constrained, fragile, complex to analyse, and failure-prone. Naturally, with the growing number of installations, it is becoming fundamental to efficiently diagnose failures as soon as possible, in order to deal with the underlying causes. In accordance with this, from 2005 onwards, the offer of diagnostic tools has been increasing, as the other base technologies (e.g. networking, operating system, localisation, synchronisation) become reasonably stable. The purpose of this survey is to provide an overview of existing post-deployment WSN diagnostic tools, by briefly presenting their functionality, architecture and constraints, in order to enable a basic understating of each tool. The survey also includes a multi-dimensional comparative analysis of the various tools, based on a proposed classification scheme and evaluation criteria, as well as an identification of the main open research issues. Although the number of diagnostic tools is high and considerable work has been done in this area, we conclude that there are still several challenges concerning post-deployment WSN diagnostic tools, regarding scope, flexibility, generality, mobility and security. Moreover, there is a need for mature, native diagnostic-oriented functionality in WSN platforms and operating systems.     

Coercivity Control of Variable-Length Iron Chains in Phthalocyanine Thin Films

The magnetic characteristics of iron phthalocyanine thin films are studied with a vibrating sample magnetometer, identifying a ferromagnetic transition temperature at 4.5?K. The metal ions at the center of the molecule are self-assembled along chains producing quasi one-dimensional magnetic chains of variable length in the thin films. The average chain length is varied from 20 to 300?nm via substrate temperature during deposition. Below the critical transition temperature, the magnetization curves have the shape of wasp-waisted or constricted loops. The in-plane chain length modulates the coercivity and saturation field and larger grains increase the coercivity significantly. First-order reversal curves of the wasp-waisted hysteresis loops reveal a long narrow strip that suggests a broad distribution of coercive fields and weak intergrain magnetic interactions. These findings are also supported through simulations based on the Preisach model.     

Rheological properties and gel strength of Phaseolus lunatus protein/carboxymethylated flamboyant gum systems

The rheological behaviour and gel strength of hydrocolloid mixture systems (HMSs) of carboxymethylated flamboyant gum (CFG) with protein hydrolysates (PHs) of Phaseolus lunatus were examined to evaluate the influence of the protein/polysaccharide ratio (2:1 and 3:1), pH (3 and 9) and concentration of solids, according to a 2³ factorial design. The protein concentrate of P. lunatus was hydrolysed with pepsin–pancreatin enzymes. The flow curve results were fitted to the Ostwald–de Waele model. The flow behaviour index (0.66–0.78) for all conditions studied was indicative of the shear‐thinning behaviour. For the HMS, the consistency index (k) values ranged from 0.4 Pa sⁿ to 1.2 Pa sⁿ. The analyses of variance showed that the ratio of PH/CFG and pH were the main variables that had significant effect on k values (P < 0.05). Only PH system presented a weak gel‐like viscoelastic behaviour. Both functional properties were affected by the protein degree of hydrolysis (DH).     

Short‐term load forecasting based on support vector regression and load profiling

The article proposes a methodology to forecast the electric load for the 24 h of the following day based on support vector regression. The study considers 24 distinct models, one for each predicted hour, where each individual model is treated independently. Its objective is to find the optimal combination of support vector machine parameters that could generalize low forecasting errors, using simulated annealing as a metaheuristic. The adopted methodology is compared to concurrent methods based on neural networks when applied to a simulated load diagram (to illustrate a distribution feeder supplying a sample of 740 consumers). The results have proven its effectiveness with mean absolute percentage errors being less than 5% for testing samples. The study also focuses on evaluating the potential benefits of adopting load profiling information as input in support vector regression, giving a consistent proof of its importance. Copyright © 2013 John Wiley & Sons, Ltd.     

Dispatching heuristics for the single machine weighted quadratic tardiness scheduling problem

In this paper, we consider the single machine scheduling problem with weighted quadratic tardiness costs. Several efficient dispatching rules are proposed. These include existing heuristics for the linear problem, as well as procedures suitably adapted to the quadratic objective function. Also, both forward and backward scheduling procedures are considered.The computational results show that the heuristics that specifically take into account the quadratic objective significantly outperform their linear counterparts. Also, the backward scheduling approach proves to be superior, and the difference in performance is even more noticeable for the harder instances.The best of the backward scheduling heuristics is both quite efficient and effective. Indeed, this procedure can quickly generate a schedule even for large instances. Also, its relative deviation from the optimum is usually rather low, and it performs adequately even for the more difficult instances.