Noise reduction in biomedical speech signal processing based on time and frequency Kalman filtering combined with spectral subtraction

The goal of this paper is to study and propose a new technique for noise reduction used during the reconstruction of speech signals, particularly for biomedical applications. The proposed method is based on Kalman filtering in the time domain combined with spectral subtraction. Comparison with discrete Kalman filter in the frequency domain shows better performance of the proposed technique. The performance is evaluated by using the segmental signal-to-noise ratio and the Itakura-Saito`s distance. Results have shown that Kalman`s filter in time combined with spectral subtraction is more robust and efficient, improving the Itakura-Saito`s distance by up to four times. (C) 2007 Elsevier Ltd. All rights reserved.

An approach based on neural networks for estimation and generalization of crossflow filtration processes

The crossflow filtration process differs of the conventional filtration by presenting the circulation flow tangentially to the filtration surface. The conventional mathematical models used to represent the process have some limitations in relation to the identification and generalization of the system behaviour. In this paper, a system based on artificial neural networks is developed to overcome the problems usually found in the conventional mathematical models. More specifically, the developed system uses an artificial neural network that simulates the behaviour of the crossflow filtration process in a robust way. Imprecisions and uncertainties associated with the measurements made on the system are automatically incorporated in the neural approach. Simulation results are presented to justify the validity of the proposed approach. (C) 2007 Elsevier B.V. All rights reserved.

GOOAL: A routine based on Genetic Algorithms to track harmonics in electric power systems

Voltage and current waveforms of a distribution or transmission power system are not pure sinusoids. There are distortions in these waveforms that can be represented as a combination of the fundamental frequency, harmonics and high frequency transients. This paper presents a novel approach to identifying harmonics in power system distorted waveforms. The proposed method is based on Genetic Algorithms, which is an optimization technique inspired by genetics and natural evolution. GOOAL, a specially designed intelligent algorithm for optimization problems, was successfully implemented and tested. Two kinds of representations concerning chromosomes are utilized: binary and real. The results show that the proposed method is more precise than the traditional Fourier Transform, especially considering the real representation of the chromosomes.

Gait Pattern Adaptation for an Active Lower-Limb Orthosis Based on Neural Networks

This work deals with neural network (NN)-based gait pattern adaptation algorithms for an active lower-limb orthosis. Stable trajectories with different walking speeds are generated during an optimization process considering the zero-moment point (ZMP) criterion and the inverse dynamic of the orthosis-patient model. Additionally, a set of NNs is used to decrease the time-consuming analytical computation of the model and ZMP. The first NN approximates the inverse dynamics including the ZMP computation, while the second NN works in the optimization procedure, giving an adapted desired trajectory according to orthosis-patient interaction. This trajectory adaptation is added directly to the trajectory generator, also reproduced by a set of NNs. With this strategy, it is possible to adapt the trajectory during the walking cycle in an on-line procedure, instead of changing the trajectory parameter after each step. The dynamic model of the actual exoskeleton, with interaction forces included, is used to generate simulation results. Also, an experimental test is performed with an active ankle-foot orthosis, where the dynamic variables of this joint are replaced in the simulator by actual values provided by the device. It is shown that the final adapted trajectory follows the patient intention of increasing the walking speed, so changing the gait pattern. (C) Koninklijke Brill NV, Leiden, 2011

A novel multiobjective optimization algorithm based on bacterial chemotaxis

In this article a novel algorithm based on the chemotaxis process of Echerichia coil is developed to solve multiobjective optimization problems. The algorithm uses fast nondominated sorting procedure, communication between the colony members and a simple chemotactical strategy to change the bacterial positions in order to explore the search space to find several optimal solutions. The proposed algorithm is validated using 11 benchmark problems and implementing three different performance measures to compare its performance with the NSGA-II genetic algorithm and with the particle swarm-based algorithm NSPSO. (C) 2009 Elsevier Ltd. All rights reserved.

Optimization of modal filters based on arrays of piezoelectric sensors

Modal filters may be obtained by a properly designed weighted sum of the output signals of an array of sensors distributed on the host structure. Although several research groups have been interested in techniques for designing and implementing modal filters based on a given array of sensors, the effect of the array topology on the effectiveness of the modal filter has received much less attention. In particular, it is known that some parameters, such as size, shape and location of a sensor, are very important in determining the observability of a vibration mode. Hence, this paper presents a methodology for the topological optimization of an array of sensors in order to maximize the effectiveness of a set of selected modal filters. This is done using a genetic algorithm optimization technique for the selection of 12 piezoceramic sensors from an array of 36 piezoceramic sensors regularly distributed on an aluminum plate, which maximize the filtering performance, over a given frequency range, of a set of modal filters, each one aiming to isolate one of the first vibration modes. The vectors of the weighting coefficients for each modal filter are evaluated using QR decomposition of the complex frequency response function matrix. Results show that the array topology is not very important for lower frequencies but it greatly affects the filter effectiveness for higher frequencies. Therefore, it is possible to improve the effectiveness and frequency range of a set of modal filters by optimizing the topology of an array of sensors. Indeed, using 12 properly located piezoceramic sensors bonded on an aluminum plate it is shown that the frequency range of a set of modal filters may be enlarged by 25-50%.

A Fault-Tolerant Manipulator Robot Based on H(2), H(infinity), and Mixed H(2)/H(infinity) Markovian Controls

This paper develops a Markovian jump model to describe the fault occurrence in a manipulator robot of three joints. This model includes the changes of operation points and the probability that a fault occurs in an actuator. After a fault, the robot works as a manipulator with free joints. Based on the developed model, a comparative study among three Markovian controllers, H(2), H(infinity), and mixed H(2)/H(infinity) is presented, applied in an actual manipulator robot subject to one and two consecutive faults.

A FEM procedure based on positions and unconstrained vectors applied to non-linear dynamic of 3D frames

This study presents an alternative three-dimensional geometric non-linear frame formulation based on generalized unconstrained vector and positions to solve structures and mechanisms subjected to dynamic loading. The formulation is classified as total Lagrangian with exact kinematics description. The resulting element presents warping and non-constant transverse strain modes, which guarantees locking-free behavior for the adopted three-dimensional constitutive relation, Saint-Venant-Kirchhoff, for instance. The application of generalized vectors is an alternative to the use of finite rotations and rigid triad`s formulae. Spherical and revolute joints are considered and selected dynamic and static examples are presented to demonstrate the accuracy and generality of the proposed technique. (C) 2010 Elsevier B.V. All rights reserved.

Determination of in situ uniaxial compressive strength of coal seams based on geophysical data

The central issue for pillar design in underground coal mining is the in situ uniaxial compressive strength (sigma (cm)). The paper proposes a new method for estimating in situ uniaxial compressive strength in coal seams based on laboratory strength and P wave propagation velocity. It describes the collection of samples in the Bonito coal seam, Fontanella Mine, southern Brazil, the techniques used for the structural mapping of the coal seam and determination of seismic wave propagation velocity as well as the laboratory procedures used to determine the strength and ultrasonic wave velocity. The results obtained using the new methodology are compared with those from seven other techniques for estimating in situ rock mass uniaxial compressive strength.

Estimation of Mass Transfer Velocity Based on Measured Turbulence Parameters

The aim of this study is to quantify the mass transfer velocity using turbulence parameters from simultaneous measurements of oxygen concentration fields and velocity fields. The surface divergence model was considered in more detail, using data obtained for the lower range of beta (surface divergence). It is shown that the existing models that use the divergence concept furnish good predictions for the transfer velocity also for low values of beta, in the range of this study. Additionally, traditional conceptual models, such as the film model, the penetration-renewal model, and the large eddy model, were tested using the simultaneous information of concentration and velocity fields. It is shown that the film and the surface divergence models predicted the mass transfer velocity for all the range of the equipment Reynolds number used here. The velocity measurements showed viscosity effects close to the surface, which indicates that the surface was contaminated with some surfactant. Considering the results, this contamination can be considered slight for the mass transfer predictions. (C) 2009 American Institute of Chemical Engineers AIChE J, 56: 2005-2017; 2010

Atmospheric impacts of the life cycle emissions of fuel ethanol in Brazil: based on chemical exergy

An assessment is made of the atmospheric emissions from the life cycle of fuel ethanol coupled with the cogeneration of electricity from sugarcane in Brazil. The total exergy loss from the most quantitative relevant atmospheric emission substances produced by the life cycle of fuel ethanol is 3.26E+05 kJ/t of C(2)H(5)OH, Compared with the chemical exergy of 1 t of ethanol (calculated as 34.56E + 06 kJ). the exergy loss from the life cycle`s atmospheric emission represents 1.11% of the product`s exergy. The activity that most contributes to atmospheric emission chemical exergy losses is the harvesting of sugarcane through the methane emitted in burning. Suggestions for improved environmental quality and greater efficiency of the life cycle of fuel ethanol with cogenerated energy are: harvesting the sugarcane without burning, renewable fuels should be used in tractors, trucks and buses instead of fossil fuel and the transportation of products and input should be logistically optimized. (C) 2009 Elsevier Ltd. All rights reserved.

New prediction methods for CO2 evaporation inside tubes: Part II - An updated general flow boiling heat transfer model based on flow patterns

Corresponding to the updated flow pattern map presented in Part I of this study, an updated general flow pattern based flow boiling heat transfer model was developed for CO2 using the Cheng-Ribatski-Wojtan-Thome [L. Cheng, G. Ribatski, L. Wojtan, J.R. Thome, New flow boiling heat transfer model and flow pattern map for carbon dioxide evaporating inside horizontal tubes, Int. J. Heat Mass Transfer 49 (2006) 4082-4094; L. Cheng, G. Ribatski, L. Wojtan, J.R. Thome, Erratum to: ""New flow boiling heat transfer model and flow pattern map for carbon dioxide evaporating inside tubes"" [Heat Mass Transfer 49 (21-22) (2006) 4082-4094], Int. J. Heat Mass Transfer 50 (2007) 391] flow boiling heat transfer model as the starting basis. The flow boiling heat transfer correlation in the dryout region was updated. In addition, a new mist flow heat transfer correlation for CO2 was developed based on the CO2 data and a heat transfer method for bubbly flow was proposed for completeness sake. The updated general flow boiling heat transfer model for CO2 covers all flow regimes and is applicable to a wider range of conditions for horizontal tubes: tube diameters from 0.6 to 10 mm, mass velocities from 50 to 1500 kg/m(2) s, heat fluxes from 1.8 to 46 kW/m(2) and saturation temperatures from -28 to 25 degrees C (reduced pressures from 0.21 to 0.87). The updated general flow boiling heat transfer model was compared to a new experimental database which contains 1124 data points (790 more than that in the previous model [Cheng et al., 2006, 2007]) in this study. Good agreement between the predicted and experimental data was found in general with 71.4% of the entire database and 83.2% of the database without the dryout and mist flow data predicted within +/-30%. However, the predictions for the dryout and mist flow regions were less satisfactory due to the limited number of data points, the higher inaccuracy in such data, scatter in some data sets ranging up to 40%, significant discrepancies from one experimental study to another and the difficulties associated with predicting the inception and completion of dryout around the perimeter of the horizontal tubes. (C) 2007 Elsevier Ltd. All rights reserved.

Improvement of radiology services based on the process management approach

The health sector requires continuous investments to ensure the improvement of products and services from a technological standpoint, the use of new materials, equipment and tools, and the application of process management methods. Methods associated with the process management approach, such as the development of reference models of business processes, can provide significant innovations in the health sector and respond to the current market trend for modern management in this sector (Gunderman et al. (2008) [4]). This article proposes a process model for diagnostic medical X-ray imaging, from which it derives a primary reference model and describes how this information leads to gains in quality and improvements. (C) 2010 Elsevier Ireland Ltd. All rights reserved.

Modeling of Distributed Control Systems in Intelligent Building based on Colored Petri Nets

Distributed control systems consist of sensors, actuators and controllers, interconnected by communication networks and are characterized by a high number of concurrent process. This work presents a proposal for a procedure to model and analyze communication networks for distributed control systems in intelligent building. The approach considered for this purpose is based on the characterization of the control system as a discrete event system and application of coloured Petri net as a formal method for specification, analysis and verification of control solutions. With this approach, we develop the models that compose the communication networks for the control systems of intelligent building, which are considered the relationships between the various buildings systems. This procedure provides a structured development of models, facilitating the process of specifying the control algorithm. An application example is presented in order to illustrate the main features of this approach.

MODELING OF AN INFORMATION SYSTEM FOR WINE TRACEABILITY BASED ON A SERVICE ORIENTED ARCHITECTURE

The purpose is to present a scientific research that led to the modeling of an information system which aimed at the maintenance of traceability data in the Brazilian wine industry, according to the principles of a service-oriented architecture (SOA). Since 2005, traceability data maintenance is an obligation for all producers that intend to export to any European Union country. Also, final customers, including the Brazilian ones, have been asking for information about food products. A solution that collectively contemplated the industry was sought in order to permit that producer consortiums of associations could share the costs and benefits of such a solution. Following an extensive bibliographic review, a series of interviews conducted with Brazilian researchers and wine producers in Bento Goncalves - RS, Brazil, elucidated many aspects associated with the wine production process. Information technology issues related to the theme were also researched. The software was modeled with the Unified Modeling Language (UML) and uses web services for data exchange. A model for the wine production process was also proposed. A functional prototype showed that the adopted model is able to fulfill the demands of wine producers. The good results obtained lead us to consider the use of this model in other domains.