Efficiency of magnetic coupled boost DC‐DC converters mainly dedicated to renewable energy systems: influence of the coupling factor

This paper presents a specific analysis of an individual basic magnetically coupled direct current‐to‐direct current (DC–DC) converter specially designed for integration in a distributed architecture of renewable energy generators for smart grid applications. In such distributed architecture dedicated for renewable energy, parallel high‐voltage DC presents many advantages over the classical centralized one. We show that in such setup, high voltage can be advantageously produced using a specific magnetically coupled boost converter, and we point out the influence of the coupling factor, generally considered equal to one, on the overall performance of the converter and on the global energy efficiency of the installation. In this study, the generalized concepts of system energy parameters of DC–DC converters are introduced and applied to the transient analysis. Consequently, the operation of a magnetic coupled DC–DC converter with a recovery stage is modeled. The simulation results are compared with those of the behavioral study, deduced from the model pointing out the large influence of the coupling factor value on the global behavior and mainly on the value of the recovery voltage, in all the various parts of the switching cycle. The renewable energy generator operating parameters, such as current and voltage values, can then be predicted in a more useful way to compute new similar DC–DC converter systems. Copyright © 2014 John Wiley & Sons, Ltd.     

Direction of Arrival Estimation using EM-ESPRIT with Nonuniform Arrays

This paper deals with the problem of the Direction Of Arrival (DOA) estimation with nonuniform linear arrays. The proposed method is based on the Expectation Maximization method where ESPRIT is used in the maximization step. The key idea is to iteratively interpolate the data to a virtual uniform linear array in order to apply ESPRIT to estimate the DOA. The iterative approach allows one to improve the interpolation using the previously estimated DOA. One of this method’s novelties lies in its capacity of dealing with any nonuniform array geometry. This technique manifests significant performance and computational advantages over previous algorithms such as Spectral MUSIC, EM-IQML and the method based on manifold separation technique. EM-ESPRIT is shown to be more robust to additive noise. Furthermore, EM-ESPRIT fully exploits the advantages of using a nonuniform array over a uniform array: simulations show that for the same aperture and with a smaller number of sensors, the nonuniform array presents almost identical performance as the equivalent uniform array.     

Prediction of gas barrier properties of high polymers

This paper studies the correlation of polymer structure and morphology and gas permeability. A scale of numerical values based on polymer cohesive energy density and fractional free volume has been devised to predict permeability and also to estimate diffusion and solubility properties.     

Piecewise monotone filtering in discrete-time with smallobservation noise

A discrete-time model for filtering with small observation noise is considered. A piecewise linear observation function is considered with two intervals of monotonicity. A sequential quadratic variation test is found to detect intervals of linearity of the observation function. Diffusion approximations to certain discrete processes are made to estimate the mean times for reaching a decision and the error probabilities     

Nonlinear adaptive filtering using kernel‐based algorithms with dictionary adaptation

Nonlinear adaptive filtering has been extensively studied in the literature, using, for example, Volterra filters or neural networks. Recently, kernel methods have been offering an interesting alternative because they provide a simple extension of linear algorithms to the nonlinear case. The main drawback of online system identification with kernel methods is that the filter complexity increases with time, a limitation resulting from the representer theorem, which states that all past input vectors are required. To overcome this drawback, a particular subset of these input vectors (called dictionary) must be selected to ensure complexity control and good performance. Up to now, all authors considered that, after being introduced into the dictionary, elements stay unchanged even if, because of nonstationarity, they become useless to predict the system output. The objective of this paper is to present an adaptation scheme of dictionary elements, which are considered here as adjustable model parameters, by deriving a gradient‐based method under collinearity constraints. The main interest is to ensure a better tracking performance. To evaluate our approach, dictionary adaptation is introduced into three well‐known kernel‐based adaptive algorithms: kernel recursive least squares, kernel normalized least mean squares, and kernel affine projection. The performance is evaluated on nonlinear adaptive filtering of simulated and real data sets. As confirmed by experiments, our dictionary adaptation scheme allows either complexity reduction or a decrease of the instantaneous quadratic error, or both simultaneously. Copyright © 2015 John Wiley & Sons, Ltd.     

Exceptionally High Dielectric Constant in Ceramic Pr2CuO4

The pristine layered cuprate Pr₂CuO₄ samples of >95% density were fabricated as thin disks. The samples, analyzed by X‐ray diffraction and Scanning electron microscopy, showed clean T′‐type phase with Rietveld refined lattice parameters a = b = 3.95805(±5) Å and c = 12.2262(±5) Å. The measured dielectric properties of the Pr₂CuO₄ ceramics, in the temperature range ?100°C–150°C and frequencies (ν) 0.1 Hz–1 MHz, showed extremely high ε_r′ > 10⁴ (above ?30°C), and dissipation (tan δ = ε_r′′/ε_r′) between 0.1 and 5 (for 500 Hz ≤ ν ≤ 1 MHz, and ?100 ≤ T ≤ 150°C). The ac conductivity of Pr₂CuO₄ ceramics ranged between 10^?6 and 10^?3 Scm^?1 for the measured frequencies and temperatures, and showed frequency‐dependent double power law behavior akin to a modified Jonscher's power law.     

Detection of traps induced and activated by high field stress in an N-channel VDMOSFET transistor using current deep level transient spectroscopy (CDLTS)

Commercial VDMOSFETs transistors were subjected to positive and negative high field stress. A new model of current deep level transient spectroscopy (CDLTS) characterization is adopted in a research of defects induced and activated by electrical stress. This model is based on pulse width scan instead of classical temperature scan. The band gap is scanned by varying the pulse base level. Positive and negative high field stresses were applied for different periods ranging from 30 to 120 min. After each stress period, activation energies and capture cross sections of detected traps were estimated. Different defects were detected and we have distinguished the doping levels and interface states from deep levels located in the forbidden band gap.     

La motivation à l'accomplissement et l'auto-évaluation des performances en relation avec le rendement scolaire.

32 overachieving and 33 underachieving secondary school students, equated for IQ range were required to perform a series of school and nonschool tasks and to evaluate their own achievement on these tasks. Self-evaluation scores were then correlated with Ss' school achievement. Underachievers were self-critical, inconsistent in their answers, and had difficulty in accurate self-evaluation, indicating a low interiorization of high standards of performance in the tasks required. Results confirm the importance of the cognitive mechanisms controlling a task as motivating factors determining academic achievement. It is proposed that these mechanisms, when studied through self-evaluation, might supplement the theory of achievement motivation in explaining the lack of motivation observed in underachievers. (23 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)