Condensation of all-cis-tetraphenylcyclotetrasiloxanetetraol in ammonia: new method for preparation of ladder-like polyphenylsilsesquioxanes

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Stability analysis of a feedback-controlled resonant DC-DC converter

This paper reports on the stability analysis of one member of a dual-channel resonant DC-DC converter family. The study is confined to the buck configuration in symmetrical operation. The output voltage of the converter is controlled by a closed loop applying constant-frequency pulsewidth modulation. The dynamic analysis reveals that a bifurcation cascade develops as a result of increasing the loop gain. The trajectory of the variable-structure piecewise-linear nonlinear system pierces through the Poincare plane at the fixed point in state space when the loop gain is small. For stability criterion the positions of the characteristic multipliers of the Jacobian matrix belonging to the Poincare map function defined around the fixed point located in the Poincare plane is applied. In addition to the stability analysis, a bifurcation diagram is developed showing the four possible states of the feedback loop: the periodic, the quasi-periodic, the subharmonic, and the chaotic states. Simulation and test results verify the theory.     

Training and optimization of an artificial neural network controlling a hybrid power filter

A hybrid power compensator (HPC) consisting of a static VAr compensator and a dynamic compensator needs to be optimally controlled during the compensation of nonlinear loads. The HPC must be controlled to meet minimum requirements in terms of power factor and harmonic distortion, while at the same time minimizing its total cost. An artificial neural network (ANN) is used to control the HPC amidst a very dynamic power system environment. The performance of a reference ANN is evaluated while controlling an HPC connected to a typical nonlinear industrial load. The training and performance of the ANN is then optimized in terms of training set size, training set packing and ANN topology and the performance compared to the reference ANN. This paper highlights the importance of optimising the mentioned ANN parameters to achieve optimum ANN training and modeling accuracy. The results obtained reveals that the application of an ANN in controlling an HPC is feasible given that the ANN parameters are chosen appropriately.     

Towards intelligent dressing

The aim of this article is to state the principles of an intelligent monitoring and control system for the grinding machine, comprising the dressing process as well as grinding stability.     

Radiative lifetimes of electrons and holes in a thin semiconductor layer

Radiative lifetimes of nondegenerate electrons and holes distributed uniformly in a semiconductor layer either deposited on a substrate or bounded by two dielectric media are calculated. The obtained expression takes into account the radiation reabsorbtion and interference effects and determines the dependences of the radiative lifetimes on the refractive indices of the external media and on the layer thickness.     

LiNbO3 optical waveguides formed in a new proton source

Proton-exchanged planar waveguides have been fabricated on Z-cut and X-cut lithium niobate crystals by using a new proton source formed by a mixture of benzoic and adipic acids. Waveguide index profiles and optical characteristics have been obtained at different values of the adipic-benzoic acid concentration ratio. The samples have been structurally characterized by Raman and infrared (IR) absorption spectroscopy and double-crystal X-ray diffraction. Good quality samples have been fabricated by using 30 mol% ratio dilution, showing very low scattering levels (<0.1 dB/cm), relatively high electrooptic coefficient (r₃₃=0.88 pm/V), and low relative percentage of interstitial protons (26%). The main factor limiting the waveguide optical properties is the substitutional-interstitial proton ratio, which can be easily controlled to produce good quality waveguides. A demonstration of the repeatability of the exchange process in the acid mixture is also provided     

High-frequency analysis of the Ellipticus antenna

Efficient numerical solution techniques have been developed and used to examine the electromagnetic fields that can be developed in the working volume of the CW Ellipticus antenna operated at frequencies from 100 kHz to 1 GHz. An exponentially tapered transition section is designed to obtain the desired illumination pattern in the working volume. The input transition section is needed for impedance matching and to drive efficiently the Ellipticus antenna. A parametric study is performed to ascertain the performance of the Ellipticus antenna for frequencies up to 1 GHz     

Application of neural networks and machine learning in networkdesign

Communication network design is becoming increasingly complex, involving making networks more usable, affordable, and reliable. To help with this, we have proposed an expert network designer (END) for configuring, modeling, simulating, and evaluating large structured computer networks, employing artificial intelligence, knowledge representation, and network simulation tools. We present a neural network/knowledge acquisition machine-learning approach to improve the END's efficiency in solving the network design problem and to extend its scope to acquire new networking technologies, learn new network design techniques, and update the specifications of existing technologies     

Synthesis and analysis of transformer-isolated converters

A systematic and straightforward procedure is developed for the synthesis and analysis of transformer-isolated power converters. The procedure can be used to determine the ranges of duty-ratio over which the transformer-isolated power converters of a given class can be operated without transformer saturation. The procedure can also be used to study the dependence of the power converter switch stresses on duty-ratios. This information is useful in the selection of the transformer-isolated power converter most suitable for a given application and in the design of this power converter with minimum switch stresses, high power density, and low cost     

Logarithmic L 2-Small Ball Asymptotics with Respect to a Self-Similar Measure for Some Gaussian Processes

We find logarithmic small ball asymptotics for the L₂-norm with respect to self-similar measures for a certain class of Gaussian processes including Brownian motion, Ornstein-Uhlenbeck process, and their integrated counterparts. Bibliography: 46 titles. __________ Translated from Zapiski Nauchnykh Seminarov POMI, Vol. 311, 2004, pp. 190–213.