Single phase multi color emitting Ca2LuTaO6: Dy3+/Eu3+ double perovskite oxide phosphors

The trivalent rare-earth (RE³⁺) doped phosphors show tremendous achievement in narrow band multicolor line emission for various applications. However, the 4f–4f absorption transition of these ions is forbidden in UV and blue light excitation. Usually, a sensitizer having spin allowed transition was used as a co-dopant to excite these ions via the energy transfer phenomenon. Another approach promisingly using to excite these ions by efficient energy transfer from the intrinsic emission of the Ca₂LuTaO₆ double perovskite phosphors host lattice. Phosphors of Ca₂LuTaO₆ with double perovskite structure were synthesized by using a high-temperature solid-state reaction method. The produced Ca₂LuTaO₆ double perovskite phosphors show an intrinsic broad band emission centered at 424 nm under the excitation of 313 nm UV light. The origin of this broad band blue emission was deeply investigated by using computation and experimental approaches. The trivalent activator Dy³⁺ and Eu³⁺ were doped is a single and co-dopant in the produced Ca₂LuTaO₆ phosphors to check their excitation in UV and near-UV spectral region. X-ray diffraction and scanning electron microscopy were used to investigate the structure and phase analysis. Various characterizations such as photoluminescence excitation, emission, and CIE chromaticity coordinates were measured which illustrate the potential of Dy³⁺ and Eu³⁺ activated Ca₂LuTaO₆ double perovskite phosphors for narrow band multicolor line emission for various applications.     

Thermal antioxidative kinetics of sesamol in triacylglycerols and fatty acid methyl esters of sesame,olive, and canola oils

Oxidation kinetics of the triacylglycerols (TAGs) and fatty acid methyl esters (FAMEs) of sesame, olive, and canola oils were studied in the presence of the different concentrations of sesamol (0.1%–0.16%) at 60, 80, and 100°C. Sesamol increased the temperature coefficient, T_C, and Q₁₀ number of the TAGs more significantly compared to the FAMEs. All the sesamol-added TAG and FAME systems, respectively, of the olive, canola, and sesame oils, respectively, exerted increased values of the Arrhenius (activation energy, E_a, and frequency factor, A) and Eyring (enthalpy, ΔH⁺⁺, and entropy, ΔS⁺⁺) equation parameters. Sesamol improved the Gibbs free energy (ΔG⁺⁺) of the activated complex formation in the canola, sesame, and olive systems, respectively, and the effect was greater in the FAMEs.     

Preparation and characterization of poly(vinyl alcohol)/gum tragacanth/cellulose nanocomposite film

The effects of gum tragacanth obtained from two species of Astragalus Gossypinus (GT-G) and A. Parrowianus (GT-P) at two levels of 10% and 30% combined with cellulose nanofibers (CNF; 5%) on the physico-mechanical and structural properties of polyvinyl alcohol (PVA) nanocomposite film were investigated in this study. The water solubility and water vapor permeability of the films decreased with increasing the content of both gums, especially in the film containing 30% GT-P. The highest values of the tensile strength (39.3 MPa) and elongation at break (445%) belonged to the treatment containing 10% GT-P (90/10P/0). The FTIR and DSC analyses confirmed good interactions between GT and PVA in the 90/10P/0 treatment. SEM images indicated the dense structure of this film as the optimum treatment. Although the presence of CNF in the films containing GT-G improved some properties, especially the Young modulus, it impaired all the functional properties of nanocomposite GT-P film.     

Investigation of Creep Feed Grinding Parameters and Heat treatment Effects on the Nickel-base Superalloys

The Nickel base Superalloys are the most famous complicated and useable of Superalloys to make hot zone components of the gas turbines. The complicated dimensional tolerances, specially at the root of the blade show importance of grinding processes at the production of blades root. The prediction of the effect of machining parameters on the soundness of component surface strengthening for reaching to a suitable surface finishing and avoiding from crack formation at the work part during machining operation often is not easy and feasible so needs to more industrial investigation.This research is about frame 5 blade designed by GE and made from Superalloy IN738LC has been investigated. The formation of a plastically deformed and heat affected zone during grinding of Superalloy IN738LC with a high depth of cut but slow work speed (creep feed grinding) was investigated. Parameters such as work speed, depth of cut and radial dressing speed have been considered as variables and their effects have been studied. During experimental performed, the voltage and current of motor measured and power and special energy calculated.Some samples heat-treated (of the 1176℃ for 1 hr under neutral argon gas and cooling rate of 15℃/min up to 537℃ and then air cooling) to study grains recrystallization. Other samples have been created from the roots of blades and then coated by Nickel to measure boundary layer micro-hardness. The results show that increasing work speed leads to increasing the use power. Increasing the depth of cut, by increasing material removal rate, and the radial dressing speed, by decreasing power, lead to decreasing special energy. The temperature created by grinding lead to decreasing plastic deformation and boundary layer formation. When the radial dressing speed changes from 1 to 0.6μm/rev and other parameters are kept unchanged the roughness of surface increases and the special energy decreases. Sufficient dressing is very essential in limiting the width of the molten zone to few micrometers. As a result, it was found that local melting at contact spots to be a rather common mechanism during grinding of superalloys, lead to so-called white layers which can easily be observed on metallographic cross sections.     

Short‐Time Linear Quadratic Form Technique for Estimating Fast‐Varying Parameters in Feedback Loops

The precision of a closed‐loop controller system designed for an uncertain plant depends strongly upon the maximum extent to which it is possible to track the trend of time‐varying parameters of the plant. The aim of this study is to describe a new parameter estimation algorithm that is able to follow fast‐varying parameters in closed‐loop systems. The short‐time linear quadratic form (STLQF) estimation algorithm introduced in this paper is a technique for tracking time‐varying parameters based on short‐time analysis of the regressing variables in order to minimize locally a linear quadratic form cost function. The established cost function produces a linear combination of errors with several delays. To meet this objective, mathematical development of the STLQF estimation algorithm is described. To implement the STLQF algorithm, the algorithm is applied to a planar mobile robot with fast‐varying parameters of inertia and viscous and coulomb frictions. Next, performance of the proposed algorithm is assessed against noise effects and variation in the type of parameters.     

Comparative evaluation of performance measures for human driving skills

In this paper, we evaluate the adequacy of several performance measures for the evaluation of driving skills between different drivers. This work was motivated by the need for a training system that captures the driving skills of an expert driver and transfers the skills to novice drivers using a haptic-enabled driving simulator. The performance measures examined include traditional task performance measures, e.g., the mean position error, and a stochastic distance between a pair of hidden Markov models (HMMs), each of which is trained for an individual driver. The emphasis of the latter is on the differences between the stochastic somatosensory processes of human driving skills. For the evaluation, we developed a driving simulator and carried out an experiment that collected the driving data of an expert driver whose data were used as a reference for comparison and of many other subjects. The performance measures were computed from the experimental data, and they were compared to each other. We also collected the subjective judgement scores of the driver’s skills made by a highly-experienced external evaluator, and these subjective scores were compared with the objective performance measures. Analysis results showed that the HMM-based distance metric had a moderately high correlation between the subjective scores and it was also consistent with the other task performance measures, indicating the adequacy of the HMM-based metric as an objective performance measure for driving skill learning. The findings of this work can contribute to developing a driving simulator for training with an objective assessment function of driving skills.     

Fast implementation of dense stereo vision algorithms on a highly parallel SIMD architecture

In this paper, we present faster than real-time implementation of a class of dense stereo vision algorithms on a low-power massively parallel SIMD architecture, the CSX700. With two cores, each with 96 Processing Elements, this SIMD architecture provides a peak computation power of 96 GFLOPS while consuming only 9 Watts, making it an excellent candidate for embedded computing applications. Exploiting full features of this architecture, we have developed schemes for an efficient parallel implementation with minimum of overhead. For the sum of squared differences (SSD) algorithm and for VGA (640 × 480) images with disparity ranges of 16 and 32, we achieve a performance of 179 and 94 frames per second (fps), respectively. For the HDTV (1,280 × 720) images with disparity ranges of 16 and 32, we achieve a performance of 67 and 35 fps, respectively. We have also implemented more accurate, and hence more computationally expensive variants of the SSD, and for most cases, particularly for VGA images, we have achieved faster than real-time performance. Our results clearly demonstrate that, by developing careful parallelization schemes, the CSX architecture can provide excellent performance and flexibility for various embedded vision applications.     

U-shaped energy loss curves utilization for distributed generation optimization in distribution networks

We propose novel techniques to find the optimal achieve the maximum loss reduction for distribution networks location, size, and power factor of distributed generation （DG） to Determining the optimal DG location and size is achieved simultaneously using the energy loss curves technique for a pre-selected power factor that gives the best DG operation. Based on the network＇s total load demand, four DG sizes are selected. They are used to form energy loss curves for each bus and then for determining the optimal DG options. The study shows that by defining the energy loss minimization as the objective function, the time-varying load demand significantly affects the sizing of DG resources in distribution networks, whereas consideration of power loss as the objective function leads to inconsistent interpretation of loss reduction and other calculations. The devised technique was tested on two test distribution systems of varying size and complexity and validated by comparison with the exhaustive iterative method （EIM） and recently published results. Results showed that the proposed technique can provide an optimal solution with less computation.     

A review of interoperability assessment models

Interoperability is the ability of systems to provide services to and accept services from other systems, and to use the services exchanged so as to operate together in a more effective manner. The fact that interoperability can be improved means that the metrics for measuring interoperability can be defined. For the purpose of measuring the interoperability between systems, an interoperability assessment model is required. This paper deals with the existing interoperability assessment models. A compara- tive analysis among these models is provided to evaluate the similarities and differences in their philosophy and implementation. The analysis yields a set of recommendations for any party that is open to the idea of creating or improving an interoperability assessment model.     

Sound source localization using compressive sensing-based feature extraction and spatial sparsity

In this paper, we propose a source localization algorithm based on a sparse Fast Fourier Transform (FFT)-based feature extraction method and spatial sparsity. We represent the sound source positions as a sparse vector by discretely segmenting the space with a circular grid. The location vector is related to microphone measurements through a linear equation, which can be estimated at each microphone. For this linear dimensionality reduction, we have utilized a Compressive Sensing (CS) and two-level FFT-based feature extraction method which combines two sets of audio signal features and covers both short-time and long-time properties of the signal. The proposed feature extraction method leads to a sparse representation of audio signals. As a result, a significant reduction in the dimensionality of the signals is achieved. In comparison to the state-of-the-art methods, the proposed method improves the accuracy while the complexity is reduced in some cases.