A hybrid PSO-ANFIS approach for short-term wind power prediction in Portugal

The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Wind power prediction plays a key role in tackling these challenges. The contribution of this paper is to propose a new hybrid approach, combining particle swarm optimization and adaptive-network-based fuzzy inference system, for short-term wind power prediction in Portugal. Significant improvements regarding forecasting accuracy are attainable using the proposed approach, in comparison with the results obtained with five other approaches.

A hybrid approach to multi-agent decision-making

In the aftermath of a large-scale disaster, agents' decisions derive from self-interested (e.g. survival), common-good (e.g. victims' rescue) and teamwork (e.g. fire extinction) motivations. However, current decision-theoretic models are either purely individual or purely collective and find it difficult to deal with motivational attitudes; on the other hand, mental-state based models find it difficult to deal with uncertainty. We propose a hybrid, CvI-JI, approach that combines: i) collective 'versus' individual (CvI) decisions, founded on the Markov decision process (MDP) quantitative evaluation of joint-actions, and ii)joint-intentions (JI) formulation of teamwork, founded on the belief-desire-intention (BDI) architecture of general mental-state based reasoning. The CvI-JI evaluation explores the performance's improvement

Short-term electricity prices forecasting in a competitive market by a hybrid PSO-ANFIS approach

In this paper, a novel hybrid approach is proposed for electricity prices forecasting in a competitive market, considering a time horizon of 1 week. The proposed approach is based on the combination of particle swarm optimization and adaptive-network based fuzzy inference system. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications, to demonstrate its effectiveness regarding forecasting accuracy and computation time. Finally, conclusions are duly drawn. (C) 2012 Elsevier Ltd. All rights reserved.

Desilication of MOR zeolite: Conventional versus microwave assisted heating

MOR zeolites were modified via desilication treatments with NaOH, under conventional and microwave heating. The samples were characterized by powder X-ray diffraction, (27)Al and (29)Si NMR spectroscopy. TEM and N(2) adsorption at -196 degrees C. The acidity of the samples and the space available inside the pores were evaluated through a catalytic model reaction, the isomerization of m-xylene, for which the profiles of the coke thermal decomposition were also analyzed. Powder X-ray diffraction and (29)Si and (27)Al MNR results show that in comparison with conventional heating, microwave irradiation (a less time consuming process) leads to identical amount of Si extraction from the zeolite framework. With this treatment. in addition to the customary mesopores development promoted by conventional heating, a partial conversion of the zeolite microporosity into larger micropores, is observed. The microwave irradiated and conventionally heated samples show different catalytic behavior in the m-xylene isomerization model reaction. It was observed that, by controlling the experimental conditions, it is possible to obtain samples with catalytic properties closer to the parent material, which is also confirmed by the respective coke analysis. (C) 2011 Elsevier B.V. All rights reserved.

Hybrid Wavelet-PSO-ANFIS Approach for Short-Term Electricity Prices Forecasting

A novel hybrid approach, combining wavelet transform, particle swarm optimization, and adaptive-network-based fuzzy inference system, is proposed in this paper for short-term electricity prices forecasting in a competitive market. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications. Finally, conclusions are duly drawn.

Short-term electricity prices forecasting in a competitive market by a hybrid intelligent approach

In this paper, a hybrid intelligent approach is proposed for short-term electricity prices forecasting in a competitive market. The proposed approach is based on the wavelet transform and a hybrid of neural networks and fuzzy logic. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications. Conclusions are duly drawn. (C) 2010 Elsevier Ltd. All rights reserved.

Accessing indoor fungal contamination using conventional and molecular methods in Portuguese poultries

Epidemiological studies showed increased prevalence of respiratory symptoms and adverse changes in pulmonary function parameters in poultry workers, corroborating the increased exposure to risk factors, such as fungal load and their metabolites. This study aimed to determine the occupational exposure threat due to fungal contamination caused by the toxigenic isolates belonging to the complex of the species of Aspergillus flavus and also isolates fromAspergillus fumigatus species complex. The study was carried out in seven Portuguese poultries, using cultural and molecularmethodologies. For conventional/cultural methods, air, surfaces, and litter samples were collected by impaction method using the Millipore Air Sampler. For the molecular analysis, air samples were collected by impinger method using the Coriolis μ air sampler. After DNA extraction, samples were analyzed by real-time PCR using specific primers and probes for toxigenic strains of the Aspergillus flavus complex and for detection of isolates from Aspergillus fumigatus complex. Through conventional methods, and among the Aspergillus genus, different prevalences were detected regarding the presence of Aspergillus flavus and Aspergillus fumigatus species complexes, namely: 74.5 versus 1.0% in the air samples, 24.0 versus 16.0% in the surfaces, 0 versus 32.6% in new litter, and 9.9 versus 15.9%in used litter. Through molecular biology, we were able to detect the presence of aflatoxigenic strains in pavilions in which Aspergillus flavus did not grow in culture. Aspergillus fumigatus was only found in one indoor air sample by conventional methods. Using molecular methodologies, however, Aspergillus fumigatus complex was detected in seven indoor samples from three different poultry units. The characterization of fungal contamination caused by Aspergillus flavus and Aspergillus fumigatus raises the concern of occupational threat not only due to the detected fungal load but also because of the toxigenic potential of these species.

A hybrid MLS technique for room impulse response estimation

The measurement of room impulse response (RIR) when there are high background noise levels frequently means one must deal with very low signal-to-noise ratios (SNR). if such is the case, the measurement might yield unreliable results, even when synchronous averaging techniques are used. Furthermore, if there are non-linearities in the apparatus or system time variances, the final SNR can be severely degraded. The test signals used in RIR measurement are often disturbed by non-stationary ambient noise components. A novel approach based on the energy analysis of ambient noise - both in the time and in frequency - was considered. A modified maximum length sequence (MLS) measurement technique. referred to herein as the hybrid MLS technique, was developed for use in room acoustics. The technique consists of reducing the noise energy of the captured sequences before applying the averaging technique in order to improve the overall SNRs and frequency response accuracy. Experiments were conducted under real conditions with different types of underlying ambient noises. Results are shown and discussed. Advantages and disadvantages of the hybrid MLS technique over standard MLS technique are evaluated and discussed. Our findings show that the new technique leads to a significant increase in the overall SNR. (C) 2008 Elsevier Ltd. All rights reserved.

Data mining framework for fatty liver disease classification in ultrasound: a hybrid feature extraction paradigm

PURPOSE: Fatty liver disease (FLD) is an increasing prevalent disease that can be reversed if detected early. Ultrasound is the safest and ubiquitous method for identifying FLD. Since expert sonographers are required to accurately interpret the liver ultrasound images, lack of the same will result in interobserver variability. For more objective interpretation, high accuracy, and quick second opinions, computer aided diagnostic (CAD) techniques may be exploited. The purpose of this work is to develop one such CAD technique for accurate classification of normal livers and abnormal livers affected by FLD. METHODS: In this paper, the authors present a CAD technique (called Symtosis) that uses a novel combination of significant features based on the texture, wavelet transform, and higher order spectra of the liver ultrasound images in various supervised learning-based classifiers in order to determine parameters that classify normal and FLD-affected abnormal livers. RESULTS: On evaluating the proposed technique on a database of 58 abnormal and 42 normal liver ultrasound images, the authors were able to achieve a high classification accuracy of 93.3% using the decision tree classifier. CONCLUSIONS: This high accuracy added to the completely automated classification procedure makes the authors' proposed technique highly suitable for clinical deployment and usage.

Gene expression regulation and lineage evolution: the North and South tale of the hybrid polyploid Squalius alburnoides complex

The evolution of hybrid polyploid vertebrates, their viability and their perpetuation over evolutionary time have always been questions of great interest. However, little is known about the impact of hybridization and polyploidization on the regulatory networks that guarantee the appropriate quantitative and qualitative gene expression programme. The Squalius alburnoides complex of hybrid fish is an attractive system to address these questions, as it includes a wide variety of diploid and polyploid forms, and intricate systems of genetic exchange. Through the study of genome-specific allele expression of seven housekeeping and tissue-specific genes, we found that a gene copy silencing mechanism of dosage compensation exists throughout the distribution range of the complex. Here we show that the allele-specific patterns of silencing vary within the complex, according to the geographical origin and the type of genome involved in the hybridization process. In southern populations, triploids of S. alburnoides show an overall tendency for silencing the allele from the minority genome, while northern population polyploids exhibit preferential biallelic gene expression patterns, irrespective of genomic composition. The present findings further suggest that gene copy silencing and variable expression of specific allele combinations may be important processes in vertebrate polyploid evolution.

Complementarity of conventional and molecular methods in the assessment of fungal contamination caused by Aspergillus fumigatus complex in one Portuguese composting plant

The handling of waste and compost that occurs frequently in composting plants (compost turning, shredding, and screening) has been shown to be responsible for the release of dust and air borne microorganisms and their compounds in the air. Thermophilic fungi, such as A. fumigatus, have been reported and this kind of contamination in composting facilities has been associated with increased respiratory symptoms among compost workers. This study intended to characterize fungal contamination in a totally indoor composting plant located in Portugal. Besides conventional methods, molecular biology was also applied to overcome eventual limitations.

Simulation and theory of hybrid aligned liquid crystal films

We present a study of the effects of nanoconfinement on a system of hard Gaussian overlap particles interacting with planar substrates through the hard-needle-wall potential, extending earlier work by two of us [D. J. Cleaver and P. I. C. Teixeira, Chem. Phys. Lett. 338, 1 (2001)]. Here, we consider the case of hybrid films, where one of the substrates induces strongly homeotropic anchoring, while the other favors either weakly homeotropic or planar anchoring. These systems are investigated using both Monte Carlo simulation and density-functional theory, the latter implemented at the level of Onsager's second-virial approximation with Parsons-Lee rescaling. The orientational structure is found to change either continuously or discontinuously depending on substrate separation, in agreement with earlier predictions by others. The theory is seen to perform well in spite of its simplicity, predicting the positional and orientational structure seen in simulations even for small particle elongations.

Despacho económico de unidades com funções de custo não convexas usando enxames

Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Energia

Lesion detection performance in an anthropomorphic chest phantom: comparative analysis of low-dose CT data on two hybrid imaging systems

Introduction: multimodality environment; requirement for greater understanding of the imaging technologies used, the limitations of these technologies, and how to best interpret the results; dose optimization; introduction of new techniques; current practice and best practice; incidental findings, in low-dose CT images obtained as part of the hybrid imaging process, are an increasing phenomenon with advancing CT technology; resultant ethical and medico-legal dilemmas; understanding limitations of these procedures important when reporting images and recommending follow-up; free-response observer performance study was used to evaluate lesion detection in low-dose CT images obtained during attenuation correction acquisitions for myocardial perfusion imaging, on two hybrid imaging systems.

Short-term electricity prices forecasting in a competetive market by a hybrid Pso-Anfis approach

In this paper, a novel hybrid approach is proposed for electricity prices forecasting in a competitive market, considering a time horizon of 1 week. The proposed approach is based on the combination of particle swarm optimization and adaptive-network based fuzzy inference system. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications, to demonstrate its effectiveness regarding forecasting accuracy and computation time. Finally, conclusions are duly drawn.