Hyperspectral imaging as an effective tool for prediction the moisture content and textural characteristics of roasted pistachio kernels

The objective of this study was to develop calibration models for prediction of moisture content and textural characteristics (fracture force, hardness, apparent modulus of elasticity and compressive energy) of pistachio kernels roasted in different conditions (temperatures 90, 120 and 150 °C; times 20, 35 and 50 min and air velocities 0.5, 1.5 and 2.5 m/s) using Vis/NIR hyperspectral imaging and multivariate analysis. The effects of different pre-processing methods and spectral treatments such as normalization [multiplicative scatter correction (MSC), standard normal variate transformation (SNV)], smoothing (median filter, Savitzky–Golay and Wavelet) and differentiation (first derivative, D¹ and second derivative, D²) on the obtained data were investigated. The prediction models were developed by partial least square regression (PLSR) and artificial neural network (ANN). The results indicated that ANN models have higher potential to predict moisture content and textural characteristics of roasted pistachio kernels comparing to PLSR models. High correlation was observed between reflectance data and fracture force (R²?=?0.957 and RMSEP?=?3.386) using MSC, Savitzky–Golay and D¹, compressive energy (R²?=?0.907 and RMSEP?=?15.757) using the combination of MSC, Wavelet and D¹, moisture content (R²?=?0.907 and RMSEP?=?0.179) and apparent modulus of elasticity (R²?=?0.921 and RMSEP?=?2.366) employing combination of SNV, Wavelet and D¹, respectively. Moreover, Vis–NIR data correlated well with hardness (R²?=?0.876 and RMSEP?=?5.216) using SNV, Wavelet and D². These results showed the capability of Vis/NIR hyperspectral imaging and the central role of multivariate analysis in developing accurate models for prediction of moisture content and textural properties of roasted pistachio kernels.     

Integrating a Decision Tree Perspective at the Operational-Level of BPM+

Decision trees are among the best-known decision-making techniques and have been used extensively for both data analysis and predictive modeling. BPM+ is a novel process modeling approach that helps represent business process models in a consistent and structured way to meet different stakeholders’ process representation needs. This paper reports on the outcomes of an ontological analysis of the potential use of decision-tree representations as a new BPM+ perspective for the operational level of abstraction. This new perspective effectively demonstrates how a specialized/operational BPM stakeholder perspective can be used to improve the existing organizational business process model repository.     

PI/PID controller design based on IMC and percentage overshoot specification to controller setpoint change

In this work, the normalized Internal Model Control (IMC) filter time constant is designed to achieve a specified value of the maximum sensitivity for stable first and second order plus time delay process models, respectively. Since a particular value of the maximum sensitivity results in an almost constant percentage overshoot to controller setpoint change, an empirical relationship between the normalized IMC filter time constant and percentage overshoot is presented. The main advantage of the proposed method is that only a user-defined overshoot is required to design a PI/PID controller. Simulation examples are given to demonstrate the value of the proposed method.     

Antioxidants and antiradicals in almond hull and shell (Amygdalus communis L.) as a function of genotype

To compare the antioxidant and antiradical activity of Amygdalus communis L. hulls and shells phenolic extracts in different genotypes, 18 A. communis L. genotypes were selected from those in Qooshchi, Qalgachi, Qovarchin Qale, Najaf Abad, Jamal Abad, Kahriz, Sfahlan of West and East Azerbayjan provinces of Iran in 2007. The fruits of these almonds were collected, their hulls and shells dried, ground and then methanolic extracts prepared from these hulls and shells. Total phenolic content was determined using the Folin–Ciocalteu (F–C) method. The extracts’ reducing power and scavenging capacity for radical nitrite, hydrogen peroxide and superoxide were evaluated. Significant differences were found in phenolic content of hulls and shells among various genotypes, radical scavenging capacity percentage varied significantly among genotypes and their hulls and shells. S₃-7 genotype with the highest phenolic content and antioxidant activity in its hulls represents a valuable genotype for procuring antioxidant phenolic compounds.     

Investigation of directly suspended droplet micro extraction method for extraction of trihalomethane and halomethane in water samples

Simple and efficient directly suspended droplet micro extraction (DSDME) in conjunction with gas chromatography-electron capture detector (GC-ECD) has been developed for extraction and determination of Halomethane and Trihalomethane from water samples. In this technique a micro drop of n-hexane is delivered to the surface of an aqueous sample while being agitated by a stirring bar in the bulk of solution. Factors relevant to the extraction efficiency were studied and optimized. The optimized extraction conditions were extraction solvent: n- hexane; NaCl concentration: 1 M; solvent extraction volume: 50 μL; stirring rate: 720 rpm and the extraction time: 5 min. The detection limits of the method were in the range of 0.059–0.137 µg L^?1, relative standard deviation (n = 3) range were 0.019–0.048%. A good linearity (r² ≥ 0.997) and a relatively broad dynamic linear range (10–200 µg L^?1) were obtained and recoveries of method were in the range of 97.69–99.51%. Finally, the proposed method was successfully utilized for pre concentration and determination of halo methane in different real samples. Successfully DSDME technique combined with capillary GC-ECD for the analysis of THMs and HMs in the water investigated samples.     

Design and demonstration of direct UV-written small angle X couplers in silica-on-silicon for broadband operation

Experimental demonstration of small angle (0.8 degrees-5 degrees ) direct UV-written X couplers in silica-on-silicon is presented. Maximum and minimum coupling ratios of 95%(+/-0.8%) and 1.9% (+/-1%), respectively, were recorded. The structures also display very low polarization and wavelength dependence. A typical excess loss of 1.0 dB(+/-0.5 dB) was recorded. Device modeling using the beam propagation method and an analytical model showed good agreement with experimental results over a broad crossing angle and wavelength range.     

First direct synthesis of highly ordered bifunctionalized mesoporous silica thin films

Optically transparent and highly ordered mesoporous organosilica thin films functionalized with two different organic groups in various proportions were synthesized by templated-directed cocondensation of tetraethylorthosilicate (TEOS) and a mixture of two distinct and functional organotriethoxysilanes [NC(CH2)3Si(OEt)3 and O=P(OEt)2(CH2)3Si(OEt)3]. The mesostructured films obtained by evaporation induced self-assembly (EISA) approach were deposited on glass or silicon substrates by dip-coating. They were characterized by Grazing Incidence Small Angle X-ray Scattering (GISAXS) and X-ray reflectivity. We showed that whatever the proportion in organic groups, only 2D hexagonal phase having p6m symmetry was observed for all the materials indicating a good compatibility between the organic groups. The bi-functionalization of the internal pores surface by the organotriethoxysilanes groups was clearly evidenced by using micro-Raman spectroscopy.     

Paraelectric thin films by nanoscale engineering of epitaxy and planar anisotropy for microwave phase shifter applications

Epitaxial and (110) oriented paraelectric thin films of Ba0.60Sro.40TiO3 were grown on (100) oriented NdGaO3 orthorhombic substrates, and the nonlinear dielectric properties were studied at 10 GHz along selected in-plane crystallographic directions in the film thickness range of 25-1200 nm. The measured dielectric properties show strong residual strain and in-plane directional dependence. For instance, the in-plane relative permittivity is found to vary from as much as 500 to 150 along [110] and [001], respectively, in the 600 nm film. Tunability was found to vary from as much as 54% to 20% in all films and directions. In a given film, the best tunability is observed along the compressed axis in a mixed strain state, 54% along [110] in the 600 nm film. It is shown that, by nanoscale manipulation of epitaxy and planar anisotropy, the return loss and phase shift in a paraelectric can be tuned over a rather wide range. The approach presented herein opens avenues for obtaining various degrees of phase shift on the same film, enabling one with an additional degree of freedom in device design and fabrication as well as multifunctionality.     

Filter for biomedical imaging and image processing

Image filtering techniques have numerous potential applications in biomedical imaging and image processing. The design of filters largely depends on the a priori, knowledge about the type of noise corrupting the image. This makes the standard filters application specific. Widely used filters such as average, Gaussian, and Wiener reduce noisy artifacts by smoothing. However, this operation normally results in smoothing of the edges as well. On the other hand, sharpening filters enhance the high-frequency details, making the image nonsmooth. An integrated general approach to design a finite impulse response filter based on Hebbian learning is proposed for optimal image filtering. This algorithm exploits the interpixel correlation by updating the filter coefficients using Hebbian learning. The algorithm is made iterative for achieving efficient learning from the neighborhood pixels. This algorithm performs optimal smoothing of the noisy image by preserving high-frequency as well as low-frequency features. Evaluation results show that the proposed finite impulse response filter is robust under various noise distributions such as Gaussian noise, salt-and-pepper noise, and speckle noise. Furthermore, the proposed approach does not require any a priori knowledge about the type of noise. The number of unknown parameters is few, and most of these parameters are adaptively obtained from the processed image. The proposed filter is successfully applied for image reconstruction in a positron emission tomography imaging modality. The images reconstructed by the proposed algorithm are found to be superior in quality compared with those reconstructed by existing PET image reconstruction methodologies.