Análise de DFA e de agrupamento do perfil de densidade de poços de petróleo

In recent years, the DFA introduced by Peng, was established as an important tool capable of detecting long-range autocorrelation in time series with non-stationary. This technique has been successfully applied to various areas such as: Econophysics, Biophysics, Medicine, Physics and Climatology. In this study, we used the DFA technique to obtain the Hurst exponent (H) of the profile of electric density profile (RHOB) of 53 wells resulting from the Field School of Namorados. In this work we want to know if we can or not use H to spatially characterize the spatial data field. Two cases arise: In the first a set of H reflects the local geology, with wells that are geographically closer showing similar H, and then one can use H in geostatistical procedures. In the second case each well has its proper H and the information of the well are uncorrelated, the profiles show only random fluctuations in H that do not show any spatial structure. Cluster analysis is a method widely used in carrying out statistical analysis. In this work we use the non-hierarchy method of k-means. In order to verify whether a set of data generated by the k-means method shows spatial patterns, we create the parameter Ω (index of neighborhood). High Ω shows more aggregated data, low Ω indicates dispersed or data without spatial correlation. With help of this index and the method of Monte Carlo. Using Ω index we verify that random cluster data shows a distribution of Ω that is lower than actual cluster Ω. Thus we conclude that the data of H obtained in 53 wells are grouped and can be used to characterize space patterns. The analysis of curves level confirmed the results of the k-means

DFA e análise de agrupamento aplicadas a perfis de porosidade neutrônico em poços de petróleo

Peng was the first to work with the Technical DFA (Detrended Fluctuation Analysis), a tool capable of detecting auto-long-range correlation in time series with non-stationary. In this study, the technique of DFA is used to obtain the Hurst exponent (H) profile of the electric neutron porosity of the 52 oil wells in Namorado Field, located in the Campos Basin -Brazil. The purpose is to know if the Hurst exponent can be used to characterize spatial distribution of wells. Thus, we verify that the wells that have close values of H are spatially close together. In this work we used the method of hierarchical clustering and non-hierarchical clustering method (the k-mean method). Then compare the two methods to see which of the two provides the best result. From this, was the parameter � (index neighborhood) which checks whether a data set generated by the k- average method, or at random, so in fact spatial patterns. High values of � indicate that the data are aggregated, while low values of � indicate that the data are scattered (no spatial correlation). Using the Monte Carlo method showed that combined data show a random distribution of � below the empirical value. So the empirical evidence of H obtained from 52 wells are grouped geographically. By passing the data of standard curves with the results obtained by the k-mean, confirming that it is effective to correlate well in spatial distribution

Análise de DFA e de agrupamento do perfil de densidade de poços de petróleo

In recent years, the DFA introduced by Peng, was established as an important tool capable of detecting long-range autocorrelation in time series with non-stationary. This technique has been successfully applied to various areas such as: Econophysics, Biophysics, Medicine, Physics and Climatology. In this study, we used the DFA technique to obtain the Hurst exponent (H) of the profile of electric density profile (RHOB) of 53 wells resulting from the Field School of Namorados. In this work we want to know if we can or not use H to spatially characterize the spatial data field. Two cases arise: In the first a set of H reflects the local geology, with wells that are geographically closer showing similar H, and then one can use H in geostatistical procedures. In the second case each well has its proper H and the information of the well are uncorrelated, the profiles show only random fluctuations in H that do not show any spatial structure. Cluster analysis is a method widely used in carrying out statistical analysis. In this work we use the non-hierarchy method of k-means. In order to verify whether a set of data generated by the k-means method shows spatial patterns, we create the parameter Ω (index of neighborhood). High Ω shows more aggregated data, low Ω indicates dispersed or data without spatial correlation. With help of this index and the method of Monte Carlo. Using Ω index we verify that random cluster data shows a distribution of Ω that is lower than actual cluster Ω. Thus we conclude that the data of H obtained in 53 wells are grouped and can be used to characterize space patterns. The analysis of curves level confirmed the results of the k-means

Parallel Cyclostationarity-Exploiting Algorithm for Energy-Efficient Spectrum Sensing

The evolution of wireless communication systems leads to Dynamic Spectrum Allocation for Cognitive Radio, which requires reliable spectrum sensing techniques. Among the spectrum sensing methods proposed in the literature, those that exploit cyclostationary characteristics of radio signals are particularly suitable for communication environments with low signal-to-noise ratios, or with non-stationary noise. However, such methods have high computational complexity that directly raises the power consumption of devices which often have very stringent low-power requirements. We propose a strategy for cyclostationary spectrum sensing with reduced energy consumption. This strategy is based on the principle that p processors working at slower frequencies consume less power than a single processor for the same execution time. We devise a strict relation between the energy savings and common parallel system metrics. The results of simulations show that our strategy promises very significant savings in actual devices.

Desenvolvimento de circuitos planares sobre substratos têxteis

The use of flexible materials for the development of planar circuits is one of the most desired and studied characteristics, lately, by researchers. This happens because the flexibility of the substrate can provide previously impracticable applications, due to the rigidity of the substrates normally used that makes it difficult to fit into the circuits in irregular surfaces. The constant interest in recent years for more lighter devices, increasingly more compacts, flexible and with low cost, led to a new line of research of great interest from both academic and technological views, that is the study and development of textile substrates that can be applied in the development of planar circuits, for applications in the areas of security, biomedical and telecommunications. This paper proposes the development of planar circuits, such as antennas , frequency selective surfaces (FSS) and planar filters, using textile (cotton ticking, jeans and brim santista) as the dielectric substrate and the Pure Copper Polyester Taffeta Fabric, a textile of pure copper, highly conductive, lightweight and flexible, commercially sold as a conductive material. The electrical characteristics of textiles (electric permittivity and loss tangent) were characterized using the transmission line method (rectangular waveguide) and compared with those found in the literature. The structures were analyzed using commercial software Ansoft Designer and Ansoft HFSS, both from the company Ansys and for comparison we used the Iterative Method of Waves (WCIP). For the purpose of validation were built and measured several prototypes of antennas, planar filters and FSS, being possible to confirm an excellent agreement between simulated and measured results

Caracterização de circuitos planares de micro-ondas pelo método iterativo das ondas

The planar circuits are structures that increasingly attracting the attention of researchers, due the good performance and capacity to integrate with other devices, in the prototyping of systems for transmitting and receiving signals in the microwave range. In this context, the study and development of new techniques for analysis of these devices have significantly contributed in the design of structures with excellent performance and high reliability. In this work, the full-wave method based on the concept of electromagnetic waves and the principle of reflection and transmission of waves at an interface, Wave Concept Iterative Procedure (WCIP), or iterative method of waves is described as a tool with high precision study microwave planar circuits. The proposed method is applied to the characterization of planar filters, microstrip antennas and frequency selective surfaces. Prototype devices were built and the experimental results confirmed the proposed mathematical model. The results were also compared with simulated results by Ansoft HFSS, observing a good agreement between them.

Bio-óleo e biogás da degradação termoquímica de lodo de esgoto doméstico em cilindro rotativo

The objective of this study was to produce biofuels (bio-oil and gas) from the thermal treatment of sewage sludge in rotating cylinder, aiming industrial applications. The biomass was characterized by immediate and instrumental analysis (elemental analysis, scanning electron microscopy - SEM, X-ray diffraction, infrared spectroscopy and ICP-OES). A kinetic study on non-stationary regime was done to calculate the activation energy by Thermal Gravimetric Analysis evaluating thermochemical and thermocatalytic process of sludge, the latter being in the presence of USY zeolite. As expected, the activation energy evaluated by the mathematical model "Model-free kinetics" applying techniques isoconversionais was lowest for the catalytic tests (57.9 to 108.9 kJ/mol in the range of biomass conversion of 40 to 80%). The pyrolytic plant at a laboratory scale reactor consists of a rotating cylinder whose length is 100 cm with capable of processing up to 1 kg biomass/h. In the process of pyrolysis thermochemical were studied following parameters: temperature of reaction (500 to 600 ° C), flow rate of carrier gas (50 to 200 mL/min), frequency of rotation of centrifugation for condensation of bio-oil (20 to 30 Hz) and flow of biomass (4 and 22 g/min). Products obtained during the process (pyrolytic liquid, coal and gas) were characterized by classical and instrumental analytical techniques. The maximum yield of liquid pyrolytic was approximately 10.5% obtained in the conditions of temperature of 500 °C, centrifugation speed of 20 Hz, an inert gas flow of 200 mL/min and feeding of biomass 22 g/min. The highest yield obtained for the gas phase was 23.3% for the temperature of 600 °C, flow rate of 200 mL/min inert, frequency of rotation of the column of vapor condensation 30 Hz and flow of biomass of 22 g/min. The non-oxygenated aliphatic hydrocarbons were found in greater proportion in the bio-oil (55%) followed by aliphatic oxygenated (27%). The bio-oil had the following characteristics: pH 6.81, density between 1.05 and 1.09 g/mL, viscosity between 2.5 and 3.1 cSt and highest heating value between 16.91 and 17.85 MJ/ kg. The main components in the gas phase were: H2, CO, CO2 and CH4. Hydrogen was the main constituent of the gas mixture, with a yield of about 46.2% for a temperature of 600 ° C. Among the hydrocarbons formed, methane was found in higher yield (16.6%) for the temperature 520 oC. The solid phase obtained showed a high ash content (70%) due to the abundant presence of metals in coal, in particular iron, which was also present in bio-oil with a rate of 0.068% in the test performed at a temperature of 500 oC.

Parallel Cyclostationarity-Exploiting Algorithm for Energy-Efficient Spectrum Sensing

The evolution of wireless communication systems leads to Dynamic Spectrum Allocation for Cognitive Radio, which requires reliable spectrum sensing techniques. Among the spectrum sensing methods proposed in the literature, those that exploit cyclostationary characteristics of radio signals are particularly suitable for communication environments with low signal-to-noise ratios, or with non-stationary noise. However, such methods have high computational complexity that directly raises the power consumption of devices which often have very stringent low-power requirements. We propose a strategy for cyclostationary spectrum sensing with reduced energy consumption. This strategy is based on the principle that p processors working at slower frequencies consume less power than a single processor for the same execution time. We devise a strict relation between the energy savings and common parallel system metrics. The results of simulations show that our strategy promises very significant savings in actual devices.

Applicability of non-pharmacological strategies for pain relief in parturient: integrative review

MORAES, Maísa Suares Teixeira; ROLIM, Lariane Thays Albuquerque; ENDERS, Bertha Cruz; FARIAS, Glaucea Maciel de; DAVIM, Rejane Marie Barbosa. Applicability of non-pharmacological strategies for pain relief in parturient: integrative review. Revista de Enfermagem UFPE on line, v.4, n.especial, p.131-136, May/June 2010. Disponivel em:< http://www.ufpe.br/revistaenfermagem/index.php/revista/>.

A Methodology for Building Service-Oriented Applications in the Presence of Non-Functional Properties

This thesis presents ⇡SOD-M (Policy-based Service Oriented Development Methodology), a methodology for modeling reliable service-based applications using policies. It proposes a model driven method with: (i) a set of meta-models for representing non-functional constraints associated to service-based applications, starting from an use case model until a service composition model; (ii) a platform providing guidelines for expressing the composition and the policies; (iii) model-to-model and model-to-text transformation rules for semi-automatizing the implementation of reliable service-based applications; and (iv) an environment that implements these meta-models and rules, and enables the application of ⇡SOD-M. This thesis also presents a classification and nomenclature for non-functional requirements for developing service-oriented applications. Our approach is intended to add value to the development of service-oriented applications that have quality requirements needs. This work uses concepts from the service-oriented development, non-functional requirements design and model-driven delevopment areas to propose a solution that minimizes the problem of reliable service modeling. Some examples are developed as proof of concepts