Applying LSSVM algorithm as a novel and accurate method for estimation of interfacial tension of brine and hydrocarbons

One of the critical parameters in petroleum and chemical engineering is the interfacial tension between brine and hydrocarbon which has major effects on trapping and residual oil in reservoir pore throat so it becomes one of the interesting topics in enhancement of oil recovery in this work Least squares support vector machine (LSSVM) algorithm was applied as a novel predicting machine for prediction of interfacial tension of brine and hydrocarbons in terms of hydrocarbon carbon number, temperature, pressure and ionic strength of brine. A total number of 175 interfacial tensions were collected from literature in the purpose of training and testing of the model. The root mean squared error (RMSE), average absolute relative deviation (AARD) and the coefficient of determination (R²) were calculated overall datasets as 0.23964, 0.27444 and 0.98509 respectively. The results of study showed that predicting LSSVM machine can be applicable for estimation of interfacial tension and EOR processes.     

Environmental impact of alternative fuel mix in electricity generation in Malaysia

The Fuel Diversification Strategy was incorporated into the Malaysian National Energy Policy in order to achieve a more balanced consumption of fuel, namely gas, hydro, coal and petroleum. The objective of this paper is to evaluate changes in CO_2, SO₂ and NO_x emission due to changes in the fuel mix specified in the Fuel Diversification Strategy. Using the environmental extended Leontief's input–output framework it was found that the fuel mix as envisioned by the Fuel Diversification Strategy generates higher CO_2, SO₂ and NO_x emissions. As such, to ensure a sustainable energy policy, the proposed fuel mix must be accompanied by efficiency gain so that the negative impact on the environment could be mitigated.     

The effect of morphological modification on the thermoelectric properties of ZnO nanomaterials

At present, huge research efforts are dedicated to improve the efficiency of thermoelectric (TE) materials. Nanostructuring is one of the suggested methods to improve their TE performance. However, the morphology of a nanomaterial might play a significant role on its TE properties. In this work, we demonstrated this effect by producing zinc oxide (ZnO) in two different morphologies using the microwave assisted chemical route. Nanoparticles (NPs) and nanorods (NRs) were synthesised by changing the molar ratios of the starting precursors. The obtained results show that the NRs have improved TE properties compared to those of the NPs, particularly at high temperature. At 673 K the Seebeck coefficient, electrical conductivity and power factor values of the ZnO NRs reached ?1020 μV/K, 22 S/m and 23 μW/m.K², respectively. The NPs have only recorded ?850 μV/K, 3 S/m and 2.4 μW/m.K² of these factors. Moreover, the thermal conductivity of the NRs was found to be three times lower than that of the NPs. As a result of these differences the Figure of Merit (zT) value of the NRs is around 0.012, while that of the NPs is only 0.001. Power generation characteristics of single leg modules made of the ZnO NPs and NRs, measured under the conditions of actual applications in an air atmosphere were also investigated. The output power of the ZnO NRs is found to be several times higher than that of the NPs. These results have clearly demonstrated the effect of nanostructures morphology on the TE performance, which might be important for future TE generators.     

Food neophobia levels of Lebanese and American college students

Food neophobia, defined as the reluctance to eat novel foods, is a personality trait that influences everyday human food choices. The objectives of this work were first, to compare food neophobia levels among American and Lebanese college students (n = 1122), second to assess the effect of personal variables such as country of residence, socio-economic status (SES) on food neophobia levels, and third to examine the effect of food neophobia levels on the familiarity and willingness to try ratings of familiar and novel foods. Average food neophobia scale (FNS) score for all respondents was 33.1 ± 11.3. Differences on FNS scores were obtained between American (29.8) and Lebanese (36.4) students (P < 0.05). Number of trips taken outside the country, frequency of eating ethnic foods and history of sickness after eating a new food were significant (P < 0.05). Food neophilic subjects had higher familiarity and willingness to try scores for familiar and novel foods.     

Structural and Magnetocaloric Properties of ErFe 2 . 4 Al 0 . 6 Compound

The structural and magnetic properties of the single-phase pseudobinary ErFe _2.4Al _0.6 compound, obtained under arc-melting conditions, have been investigated. Single crystal X-ray diffraction analysis revealed that this compound is stabilized with a hexagonal CeNi ₃-type structure (space group P6 ₃ /mmc). The partial substitution of Fe by Al in this compound occurring at all the metallic sites is reflected in the decrease of the Curie temperature Tc. Magnetization curves (2–450 K; 0–5 T) indicate a ferrimagnetic ordering with four magnetic phases induced by competitional interactions between magnetic moments of both Er and Fe. The magnetocaloric effect has been estimated from the magnetic isotherms. The relative cooling power (RCP) value indicates relatively promising magnetic refrigerant material.     

Survey of computer communications loop networks: Part 2

Loop networks for computer communications have inherent advantages of performance, modularity and cost. In Part 1 several demand-shared loops, their configuration and topology were discussed. In the second part control distribution, timing and synchronization, reliability and performance are covered. The section on performance includes a comparison of loops with each other and with other topologies, particularly stars, random-access highways and polled highways.     

A generic architecture model based-methodology for an efficient design of hardware/software application-specific multiprocessor System-on-Chip

In this paper, we describe a methodology and flow for systematic design of application specific multiprocessor system-on-chip (mp-SoC). Our approach is based on a generic architecture platform which is used as a model throughout the design process. This model is modular, flexible and scalable, making it possible to cover a large application field. A complete design flow from system specification to register transfer level (rtl) consists of two principal stages. The first stage is architecture exploration where the system-level performance estimation method is required to find the best system architecture. The goal of this stage is to fix the optimal architectural parameters specific to the application. The second stage is the systematic design flow. The architectural parameters are used in this stage to produce thertl architecture. This paper focuses on the definition of the architecture model and the systematic design flow that was now automated. The feasibility and effectiveness of this approach are illustrated by several telecommunication applications.     

Semi-empirical calibration of the IEM backscattering model using radar images and moisture and roughness field measurements

Estimating surface parameters by radar-image inversion requires the use of well-calibrated backscattering models. None of the existing models is capable of correctly simulating scatterometer or satellite radar data. We propose a semi-empirical calibration of the Integral Equation Model (IEM) backscattering model in order to better reproduce the radar backscattering coefficient over bare agricultural soils. As correlation length is not only the least accurate but also the most difficult to measure of the parameters required in the models, we propose that it be replaced by a calibration parameter that would be estimated empirically from experimental databases of radar images and field measurements. This calibration was carried out using a number of radar configurations with different incidence angles, polarization configurations, and radar frequencies. Using several databases, the relationship between the calibration parameter and the surface roughness was determined for each radar configuration. In addition, the effect of the correlation function shape on IEM performance was studied using the three correlation functions (exponential, fractal, and Gaussian). The calibrated version of the IEM was then validated using another independent set of experimental data. The results show good agreement between the backscattering coefficient provided by the radar systems and that simulated by the calibrated version of the IEM. This calibrated version of the IEM can be used in inversion procedures to retrieve surface roughness and/or moisture values from radar images.     

Assessment of the ASAR sensor radiometric quality in comparison to ERS‐2 and RADARSAT‐1 SAR data

The estimation of geophysical parameters from Synthetic Aperture Radar (SAR) data necessitates well‐calibrated sensors with good radiometric precision. In this paper, the radiometric calibration of the new Advanced Synthetic Aperture Radar (ASAR‐ENVISAT) sensor was assessed by comparing ASAR data with ERS‐2 and RADARSAT‐1 SAR data. By analysing the difference between radar signals of forest stands, the results show differences of varying importance between the ASAR on the one hand, and the ERS‐2 and the RADARSAT‐1 on the other. For recent data acquired at the end of 2005, the difference varies from ?0.72 to +0.72 dB, with temporal variations that can reach 1.1 dB. For older data acquired in 2003 and 2004, we observe a sharp decrease in the radar signal in the range direction, which can attain 3.5 dB. The use of revised calibration constants provided recently by the European Space Agency (ESA) significantly improves the results of the radiometric calibration, where the difference between the ASAR and the other SARs will be lower than 0.5 dB.     

Potential of ASAR/ENVISAT for the characterization of soil surface parameters over bare agricultural fields

The objective of this investigation is to analyze the sensitivity of ASAR (Advanced Synthetic Aperture Radar) data to soil surface parameters (surface roughness and soil moisture) over bare fields, at various polarizations (HH, HV, and VV) and incidence angles (20°-43°). The relationships between backscattering coefficients and soil parameters were examined by means of 16 ASAR images and several field campaigns. We have found that HH and HV polarizations are more sensitive than VV polarization to surface roughness. The results also show that the radar signal is more sensitive to surface roughness at high incidence angle (43°). However, the dynamics of the radar signal as a function of soil roughness are weak for root mean square (rms) surface heights between 0.5 cm and 3.56 cm (only 3 dB for HH polarization and 43° incidence angle). The estimation of soil moisture is optimal at low and medium incidence angles (20°-37°). The backscattering coefficient is more sensitive to volumetric soil moisture in HH polarization than in HV polarization. In fact, the results show that the depolarization ratio σ_HH⁰/σ_HV⁰ is weakly dependent on the roughness condition, whatever the radar incidence. On the other hand, we observe a linear relationship between the ratio σ_HH⁰/σ_HV⁰ and the soil moisture. The backscattering coefficient ratio between a low and a high incidence angle decreases with the rms surface height, and minimizes the effect of the soil moisture.