Data Mining Applied to Harmonic Current Sources Identification in Residential Consumers

This work proposes a method based on both preprocessing and data mining with the objective of identify harmonic current sources in residential consumers. In addition, this methodology can also be applied to identify linear and nonlinear loads. It should be emphasized that the entire database was obtained through laboratory essays, i.e., real data were acquired from residential loads. Thus, the residential system created in laboratory was fed by a configurable power source and in its output were placed the loads and the power quality analyzers (all measurements were stored in a microcomputer). So, the data were submitted to pre-processing, which was based on attribute selection techniques in order to minimize the complexity in identifying the loads. A newer database was generated maintaining only the attributes selected, thus, Artificial Neural Networks were trained to realized the identification of loads. In order to validate the methodology proposed, the loads were fed both under ideal conditions (without harmonics), but also by harmonic voltages within limits pre-established. These limits are in accordance with IEEE Std. 519-1992 and PRODIST (procedures to delivery energy employed by Brazilian`s utilities). The results obtained seek to validate the methodology proposed and furnish a method that can serve as alternative to conventional methods.

Cluster identification and characterization in the riser of a circulating fluidized bed from numerical simulation results

A methodology of identification and characterization of coherent structures mostly known as clusters is applied to hydrodynamic results of numerical simulation generated for the riser of a circulating fluidized bed. The numerical simulation is performed using the MICEFLOW code, which includes the two-fluids IIT`s hydrodynamic model B. The methodology for cluster characterization that is used is based in the determination of four characteristics, related to average life time, average volumetric fraction of solid, existing time fraction and frequency of occurrence. The identification of clusters is performed by applying a criterion related to the time average value of the volumetric solid fraction. A qualitative rather than quantitative analysis is performed mainly owing to the unavailability of operational data used in the considered experiments. Concerning qualitative analysis, the simulation results are in good agreement with literature. Some quantitative comparisons between predictions and experiment were also presented to emphasize the capability of the modeling procedure regarding the analysis of macroscopic scale coherent structures. (c) 2007 Elsevier Inc. All rights reserved.

A hybrid Particle Swarm Optimization - Simplex algorithm (PSOS) for structural damage identification

This study proposes a new PSOS-model based damage identification procedure using frequency domain data. The formulation of the objective function for the minimization problem is based on the Frequency Response Functions (FRFs) of the system. A novel strategy for the control of the Particle Swarm Optimization (PSO) parameters based on the Nelder-Mead algorithm (Simplex method) is presented; consequently, the convergence of the PSOS becomes independent of the heuristic constants and its stability and confidence are enhanced. The formulated hybrid method performs better in different benchmark functions than the Simulated Annealing (SA) and the basic PSO (PSO(b)). Two damage identification problems, taking into consideration the effects of noisy and incomplete data, were studied: first, a 10-bar truss and second, a cracked free-free beam, both modeled with finite elements. In these cases, the damage location and extent were successfully determined. Finally, a non-linear oscillator (Duffing oscillator) was identified by PSOS providing good results. (C) 2009 Elsevier Ltd. All rights reserved

On the analysis of notched concrete beams: From measurement with digital image correlation to identification with boundary element method of a cohesive model

A way of coupling digital image correlation (to measure displacement fields) and boundary element method (to compute displacements and tractions along a crack surface) is presented herein. It allows for the identification of Young`s modulus and fracture parameters associated with a cohesive model. This procedure is illustrated to analyze the latter for an ordinary concrete in a three-point bend test on a notched beam. In view of measurement uncertainties, the results are deemed trustworthy thanks to the fact that numerous measurement points are accessible and used as entries to the identification procedure. (C) 2010 Elsevier Ltd. All rights reserved.

Morphological and molecular characterization of cyanobacteria from a Brazilian facultative wastewater stabilization pond and evaluation of microcystin production

The cyanobacterial population in the Cajati waste stabilization pond system (WSP) from Sao Paulo State, Brazil was assessed by cell isolation and direct microscope counting techniques. Ten strains, belonging to five genera (Synechococcus, Merismopedia, Leptolyngbya, Limnothrix, and Nostoc), were isolated and identified by morphological and molecular analyses. Morphological identification of the isolated strains was congruent with their phylogenetic analyses based on 16S rDNA gene sequences. Six cyanobacterial genera (Synechocystis, Aphanocapsa, Merismopedia, Lyngbya, Phormidium, and Pseudanabaena) were identified by direct microscope inspection. Both techniques were complementary, since, of the six genera identified by direct microscopic inspection, only Merismopedia was isolated, and the four other isolated genera were not detected by direct inspection. Direct microscope counting of preserved cells showed that cyanobacteria were the dominant members (> 90%) of the phytoplankton community during both periods evaluated (summer and autumn). ELISA tests specific for hepatotoxicmicrocystins gave positive results for six strains (Synechococcus CENA108, Merismopedia CENA106, Leptolyngbya CENA103, Leptolyngbya CENA112, Limnothrix CENA109, and Limnothrix CENA110), and for wastewater samples collected from raw influent (3.70 mu g microcystins/l) and treated effluent (3.74 mu g microcystins/l) in summer. Our findings indicate that toxic cyanobacteria in WSP systems are of concern, since the treated effluent containing cyanotoxins will be discharged into rivers, irrigation channels, estuaries, or reservoirs, and can affect human and animal health.

Evaluation of the anaerobic degradation of black liquor from a Kraft pulp plant with addition of organic co-substrates

The purpose of this study was to assess the anaerobic degradation of black liquor with and without additional carbon sources. Batch experiments were conducted using black liquor, from an integrated pulp and paper mill adding ethanol, methanol and nutrients. The PCR/DGGE technique was used to characterize the structure of the microbial community. The addition of extra sources of carbon did not significantly influence the degradation of black liquor under the conditions evaluated and the microbial community was similar in all experiments. It was observed an increase in some members of the archaeal in reactors that had the best efficiencies for removal of black liquor (around 7.5%). Either ethanol or methanol can be used as co-substrates because the produce the same quantitative and qualitative effect.

Performance of a horizontal-flow anaerobic immobilized biomass (HAIB) reactor and dynamics of the microbial community during degradation of pentachlorophenol (PCP)

The anaerobic biological treatment of pentachlorophenol (PCP) and methanol as the main carbon source was investigated in a horizontal-flow anaerobic immobilized biomass (HAIB) reactor at 30 +/- 1 degrees C, during a 220-day trial period. The reactor biomass was developed as an attached biofilm on polyurethane foam particles, with 24 h of hydraulic retention time. The PCP concentrations, which ranged from 2.0 to 13.0 mg/L, were controlled by adding synthetic substrate. The HAIB reactor reduced 97% of COD and removed 99% of PCP. The microbial biofilm communities of the HAIB reactor amended with PCP, without previous acclimatization, were characterized by polymerase chain reaction (PCR) and amplified ribosomal DNA restriction analysis (ARDRA) with specific Archaea oligonucleotide primers. The ARDRA technique provided an adequate analysis of the community, revealing the profile of the selected population along the reactor. The biomass activities in the HAIB reactor at the end of the experiments indicated the development of PCP degraders and the maintenance of the population of methanogenic Archaea, ensuring the high efficiency of the system treating PCP with added methanol as the cosubstrate. The use of the simplified ARDRA method enabled us to monitor the microbial population with the addition of high concentrations of toxic compounds and highlighting a selection of microorganisms in the biofilm. (C) 2008 Published by Elsevier Ltd.

Application of molecular techniques to evaluate the methanogenic archaea and anaerobic bacteria in the presence of oxygen with different COD : sulfate ratios in a UASB reactor

In this paper, the microbial characteristics of the granular sludge in the presence of oxygen (3.0 +/- 0.7 mg O-2 1(-1)) were analyzed using molecular biology techniques. The granules were provided by an upflow anaerobic sludge blanket (UASB) operated over 469 days and fed with synthetic substrate. Ethanol and sulfate were added to obtain different COD/SO42- ratios (3.0, 2.0, and 1.6). The results of fluorescent in situ hybridization (FISH) analyses showed that archaeal cells, detected by the ARC915 probe, accounted for 77%, 84%, and 75% in the COD/SO42- ratios (3.0, 2.0, and 1.6, respectively). Methanosaeta sp. was the predominant acetoclastic archaea observed by optical microscopy and FISH analyses, and confirmed by sequencing of the excised bands of the DGGE gel with a similarity of 96%. The sulfate-reducing bacterium Desulfovibrio vulgaris subsp. vulgaris (similarity of 99%) was verified by sequencing of the DGGE band. Others identified microorganism were similar to Shewanella sp. and Desulfitobacterium hafniense, with similarities of 95% and 99%, respectively. These results confirmed that the presence of oxygen did not severely affect the metabolism of microorganisms that are commonly considered strictly anaerobic. We obtained mean efficiencies of organic matter conversion and sulfate reducing higher than 74%. (C) 2008 Elsevier Ltd. All rights reserved.

Learning Profile Identification Based on the Analysis of the User Context of Interaction

One of the e-learning environment goal is to attend the individual needs of students during the learning process. The adaptation of contents, activities and tools into different visualization or in a variety of content types is an important feature of this environment, bringing to the user the sensation that there are suitable workplaces to his profile in the same system. Nevertheless, it is important the investigation of student behaviour aspects, considering the context where the interaction happens, to achieve an efficient personalization process. The paper goal is to present an approach to identify the student learning profile analyzing the context of interaction. Besides this, the learning profile could be analyzed in different dimensions allows the system to deal with the different focus of the learning.

Fast experimental identification of suspension models for control design

This paper presents both the theoretical and the experimental approaches of the development of a mathematical model to be used in multi-variable control system designs of an active suspension for a sport utility vehicle (SUV), in this case a light pickup truck. A complete seven-degree-of-freedom model is successfully quickly identified, with very satisfactory results in simulations and in real experiments conducted with the pickup truth. The novelty of the proposed methodology is the use of commercial software in the early stages of the identification to speed up the process and to minimize the need for a large number of costly experiments. The paper also presents major contributions to the identification of uncertainties in vehicle suspension models and in the development of identification methods using the sequential quadratic programming, where an innovation regarding the calculation of the objective function is proposed and implemented. Results from simulations of and practical experiments with the real SUV are presented, analysed, and compared, showing the potential of the method.

Dynamic Imaging in Electrical Impedance Tomography of the Human Chest With Online Transition Matrix Identification

One of the electrical impedance tomography objectives is to estimate the electrical resistivity distribution in a domain based only on electrical potential measurements at its boundary generated by an imposed electrical current distribution into the boundary. One of the methods used in dynamic estimation is the Kalman filter. In biomedical applications, the random walk model is frequently used as evolution model and, under this conditions, poor tracking ability of the extended Kalman filter (EKF) is achieved. An analytically developed evolution model is not feasible at this moment. The paper investigates the identification of the evolution model in parallel to the EKF and updating the evolution model with certain periodicity. The evolution model transition matrix is identified using the history of the estimated resistivity distribution obtained by a sensitivity matrix based algorithm and a Newton-Raphson algorithm. To numerically identify the linear evolution model, the Ibrahim time-domain method is used. The investigation is performed by numerical simulations of a domain with time-varying resistivity and by experimental data collected from the boundary of a human chest during normal breathing. The obtained dynamic resistivity values lie within the expected values for the tissues of a human chest. The EKF results suggest that the tracking ability is significantly improved with this approach.

Identification and control of occupational risks in a Sao Paulo metropolitan region quarry

Crushed stone mining is the third largest mining economy in Brazil, where almost half is produced in the Sao Paulo metropolitan region. The segment registers the highest number of accidents among the extractive industries, which justifies the concern with workers` health and safety, and the importance of controlling occupational hazards. Since 2002, the NR-22 Standard (NR-22: Occupational Health and Safety in Mining) makes compulsory the elaboration of a Risk Management Program that identifies risks and establishes control measures. Considering the crushed stone mining industry importance to the state, this paper evaluates and discusses the risks identified in unit operations during the production process of crushed stone in an open pit mine in order to propose control measures for the development of the Risk Management Program. Although this study refers to a specific quarry, it can be applied to other mines from the same sector since some considerations are made regarding differences in manufacturing processes. The research was based on the identification of the main risks associated with drilling, blasting, load & haulage, crushing and screening through field measurements of some hazardous agents, together with company reports. The results contributed to the choice of the appropriate control measures for the improvement Of workers` health and safety conditions.

Identification of Elastic, Dielectric, and Piezoelectric Constants in Piezoceramic Disks

Three-dimensional modeling of piezoelectric devices requires a precise knowledge of piezoelectric material parameters. The commonly used piezoelectric materials belong to the 6mm symmetry class, which have ten independent constants. In this work, a methodology to obtain precise material constants over a wide frequency band through finite element analysis of a piezoceramic disk is presented. Given an experimental electrical impedance curve and a first estimate for the piezoelectric material properties, the objective is to find the material properties that minimize the difference between the electrical impedance calculated by the finite element method and that obtained experimentally by an electrical impedance analyzer. The methodology consists of four basic steps: experimental measurement, identification of vibration modes and their sensitivity to material constants, a preliminary identification algorithm, and final refinement of the material constants using an optimization algorithm. The application of the methodology is exemplified using a hard lead zirconate titanate piezoceramic. The same methodology is applied to a soft piezoceramic. The errors in the identification of each parameter are statistically estimated in both cases, and are less than 0.6% for elastic constants, and less than 6.3% for dielectric and piezoelectric constants.

Valve friction and nonlinear process model closed-loop identification

Among several process variability sources, valve friction and inadequate controller tuning are supposed to be two of the most prevalent. Friction quantification methods can be applied to the development of model-based compensators or to diagnose valves that need repair, whereas accurate process models can be used in controller retuning. This paper extends existing methods that jointly estimate the friction and process parameters, so that a nonlinear structure is adopted to represent the process model. The developed estimation algorithm is tested with three different data sources: a simulated first order plus dead time process, a hybrid setup (composed of a real valve and a simulated pH neutralization process) and from three industrial datasets corresponding to real control loops. The results demonstrate that the friction is accurately quantified, as well as ""good"" process models are estimated in several situations. Furthermore, when a nonlinear process model is considered, the proposed extension presents significant advantages: (i) greater accuracy for friction quantification and (ii) reasonable estimates of the nonlinear steady-state characteristics of the process. (C) 2010 Elsevier Ltd. All rights reserved.

Frequency Domain Connectivity Identification: An Application of Partial Directed Coherence in fMRI

Functional magnetic resonance imaging (fMRI) has become an important tool in Neuroscience due to its noninvasive and high spatial resolution properties compared to other methods like PET or EEG. Characterization of the neural connectivity has been the aim of several cognitive researches, as the interactions among cortical areas lie at the heart of many brain dysfunctions and mental disorders. Several methods like correlation analysis, structural equation modeling, and dynamic causal models have been proposed to quantify connectivity strength. An important concept related to connectivity modeling is Granger causality, which is one of the most popular definitions for the measure of directional dependence between time series. In this article, we propose the application of the partial directed coherence (PDC) for the connectivity analysis of multisubject fMRI data using multivariate bootstrap. PDC is a frequency domain counterpart of Granger causality and has become a very prominent tool in EEG studies. The achieved frequency decomposition of connectivity is useful in separating interactions from neural modules from those originating in scanner noise, breath, and heart beating. Real fMRI dataset of six subjects executing a language processing protocol was used for the analysis of connectivity. Hum Brain Mapp 30:452-461, 2009. (C) 2007 Wiley-Liss, Inc.