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

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Stability of O3 + N2, O3 + O2 and O3 + CO2 double hydrates: DFT study

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State of polarization changes: Classification and measurement

We propose a standardization procedure that provides a convenient, quantitative and reproducible laboratory-based method for measuring the state of polarization (SOP) fluctuations produced by polarization varying devices. This method is based on the SOP distributions generated by commercial polarization scramblers. We show that these devices generate distributions of the maximum change of the SOP (in a given sample time) that follow Rayleigh statistics, which scale linearly with scrambling frequency and the sample time. We use this procedure to measure the SOP fluctuations in a short length of coiled fiber subject to mechanical perturbations.     

Robust vector control of induction motors using full-order observer in consideration of core loss

This paper proposes a method for designing a robust full-order observer for vector-controlled induction motors taking core loss into account. Although conventional research focuses on parameter identification, global stability of the identification remains questionable. Therefore, robustness against some parameters is required. This paper describes the design of a robust full-order observer which takes core loss into account, using both the gain-scheduled H/sub /spl infin// control and the linear matrix inequality technique. This design always results in a stable controller. The robustness of the proposed method against variations of resistances is evaluated by experiments.     

Optical-transmission characteristics of optical-fiber cables and installed optical-fiber cable networks for WDM systems

Many cables containing 1.3-/spl mu/m zero-dispersion single-mode (SM) optical fibers are installed in trunk and access networks. Recently, there have been a number of studies on wavelength-division-multiplexing (WDM) systems designed to increase transmission capacity and flexibility. If we can construct WDM systems using SM optical-fiber cable networks designed to transmit using wavelengths in the 1.3-/spl mu/m window (O-band), this will prove very effective in reducing construction costs. It is therefore important to examine the wavelength dependence of the transmission characteristics of SM optical-fiber cables and networks that have already been installed and in which several optical fibers are joined. In this paper, we describe the measured optical characteristics of SM optical-fiber cables and installed optical-fiber cable networks at various wavelengths. The optical characteristics were stable in the 1.46 to 1.625-/spl mu/m wavelength range and we confirmed that the installed SM optical-fiber cable networks could be used for WDM system applications.     

Using the magneto-optical Kerr effect to study magnetization processes in two-dimensional magnonic crystals based on YIG thin films

The magneto-optical Kerr effect for red (628 nm) and green (532 nm) light is used to study magnetization processes in 2D magnonic crystals obtained by etching pits with the diameter D ≈ 32 μm to a depth of t ≤ 2 μm in a 16.1-μm-thick film of yttrium iron garnet (YIG). Hysteresis loops obtained in the case of the inplane crystal magnetization at 628 nm are characterized by lower saturation fields H _s and higher remanent magnetizations than those obtained at 532 nm, a result that is attributed to different absorption coefficients of the YIG film at these wavelengths. This difference between the magnetization curves reflects the fact that the magnonic-crystal surface probed with the green light makes a greater contribution to the magneto-optical Kerr effect. Therefore, the green light is more sensitive to the demagnetizing fields, which govern magnetization processes in the magnonic crystals.     

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.     

A VQ-based blind image restoration algorithm

Learning-based algorithms for image restoration and blind image restoration are proposed. Such algorithms deviate from the traditional approaches in this area, by utilizing priors that are learned from similar images. Original images and their degraded versions by the known degradation operator (restoration problem) are utilized for designing the VQ codebooks. The codevectors are designed using the blurred images. For each such vector, the high frequency information obtained from the original images is also available. During restoration, the high frequency information of a given degraded image is estimated from its low frequency information based on the codebooks. For the blind restoration problem, a number of codebooks are designed corresponding to various versions of the blurring function. Given a noisy and blurred image, one of the codebooks is chosen based on a similarity measure, therefore providing the identification of the blur. To make the restoration process computationally efficient, the principal component analysis (PCA) and VQ-nearest neighbor approaches are utilized. Simulation results are presented to demonstrate the effectiveness of the proposed algorithms.