By utilizing meteorological data such as relative humidity, temperature, pressure, rain rate and precipitation duration at eight (8) stations in Aegean Archipelagos from six recent years (2007 -2012), the effect of the weather on Electromagnetic wave propagation is studied. The EM wave propagation characteristics depend on atmospheric refractivity and consequently on Rain-Rate which vary in time and space randomly. Therefore the statistics of radio refractivity, Rain-Rate and related propagation effects are of main interest. This work investigates the maximum value of rain rate in monthly rainfall records, for a 5 min interval comparing it with different values of integration time as well as different percentages of time. The main goal is to determine the attenuation level for microwave links based on local rainfall data for various sites in Greece (L-zone), namely Aegean Archipelagos, with a view on improved accuracy as compared with more generic zone data available. A measurement of rain attenuation for a link in the S-band has been carried out and the data compared with prediction based on the standard ITU-R method.
In this study, the effect of the addition of multi-walled carbon nanotubes (MWCNTs), at three percentages, into the urea-formaldehyde (UF) shell-wall of microcapsules on the healing efficiency is reported. The modified shell-wall created a conductive network in semi-conductive epoxies, which led to an improvement of the electromagnetic interference shielding effectiveness (EMI SE); utilizing the excellent electrical properties of the CNTs. The microcapsule’s mean diameter and shell wall were examined via scanning electron microscopy (SEM). Thermal stability was evaluated via thermogravimetric analysis (TGA). The healing efficiency was assessed in terms of fracture toughness, while the electrical properties were measured using impedance spectroscopy. The measurements of the EMI SE were carried out in the frequency range of 7–9 GHz. The derived results indicated that the incorporation of the CNTs resulted in a decrease in the mean size of the microcapsules, while the thermal stability remained unchanged. In particular, the introduction of 0.5% w/v CNTs did not affect the healing efficiency, while it increased the initial mechanical properties of the epoxy after the incorporation of the self-healing system by 27%. At the same time, it led to the formation of a conductive network, providing electrical conductivity to the epoxies. The experimental results showed that the SE increased on average 5 dB or more after introducing conductive microcapsules.
In this article, we propose a new approach for effective detection of infrared (IR) radiation, using an absorber consisting of two successive metal‐dielectric layers. To this end, a low cost, high‐efficiency composite IR absorber structure consisting of a set of two double‐layered element of thin metal layers paired with dielectric materials is presented. The proposed composite absorber can be tuned based on the metal layer sheet resistance and the thickness of various poly‐Si media; by appropriate choice of physical, electrical, and optical parameters, so that maximal absorption over both mid‐wave IR band regions (MWIR) and long wavelength IR band regions (LWIR) (3–12 μm), is achieved. The outcome of study indicates that the presented absorber configuration may be a promising candidate for integration into microbolometric detectors; while offering improved efficiency and functionality, for not critical timing applications, synchronously in both the MWIR and LWIR atmospheric thermal windows.
Electroencephalographic (EEG) inverse problems are often ill-posed due to the high condition number of the transfer matrix. In the present work simulated cortical source distributions are reconstructed, using a formulation providing information about extended intracranial distributions, with separate current source and sink positions. To overcome the influence of noise on measured voltages, as expected in real laboratory recordings, the Tikhonov regularization technique (TRT) is used for solving the discrete inverse problem matrix equation. Two criteria are used and compared in providing an approximation to the optimal regularization parameter, the composite residual and smoothing operator (CRESO) criterion and the minimum-product (MP) criterion. For levels of Gaussian measurement noise equal to or greater than 10%, the CRESO criterion performed significantly better than MP criterion, provided that the application of both criteria was extended to include as approximations even boundary regularization parameter values.
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