Current climate models often predict fractional cloud cover on the basis of a diagnostic probability density function (PDF) describing the subgrid-scale variability of the total water specific humidity, qt, favouring schemes with limited complexity. Standard shapes are uniform or triangular PDFs the width of which is assumed to scale with the gridbox mean qt or the grid-box mean saturation specific humidity, qs. In this study, the qt variability is analysed from large-eddy simulations for two stratocumulus, two shallow cumulus, and one deep convective cases. We find that in most cases, triangles are a better approximation to the simulated PDFs than uniform distributions. In two of the 24 slices examined, the actual distributions were so strongly skewed that the simple symmetric shapes could not capture the PDF at all. The distribution width for either shape scales acceptably well with both the mean value of qt and qs, the former being a slightly better choice. The qt variance is underestimated by the fitted PDFs, but overestimated by the existing parameterisations. While the cloud fraction is in general relatively well diagnosed from fitted or parameterised uniform or triangular PDFs, it fails to capture cases with small partial cloudiness, and in 10 – 30% of the cases misdiagnoses clouds in clear skies or vice-versa. The results suggest choosing a parameterisation with a triangular shape, where the distribution width would scale with the grid-box mean qt using a scaling factor of 0.076. This, however, is subject to the caveat that the reference simulations examined here were partly for rather small domains and driven by idealised boundary conditions.

It is known that a matched filter is optimal for a signal corrupted by Gaussian noise. In a wireless environment, the received signal may be corrupted by Gaussian noise and a variety of other channel disturbances: cochannel interference, multiple access interference, large and small-scale fading, etc. Adaptive filtering is the usual approach to mitigating this channel distortion. Existing adaptive filtering techniques usually attempt to minimize the mean square error (MSE) of some aspect of the received signal, with respect to the desired aspect of that signal. Adaptive minimization of MSE does not always guarantee minimization of bit error rate (BER). The main focus of this research involves estimation of the probability density function (PDF) of the received signal; this PDF estimate is used to adaptively determine a solution that minimizes BER. To this end, a new adaptive procedure called the Minimum BER Estimation (MBE) algorithm has been developed. MBE shows improvement over the Least Mean Squares (LMS) algorithm for most simulations involving interference and in some multipath situations. Furthermore, the new algorithm is more robust than LMS to changes in algorithm parameters such as stepsize and window width. / Master of Science

No description available.

Emerging Ultra Wideband (UWB) Orthogonal Frequency Division Multiplexing (OFDM) systems hold the promise of delivering wireless data at high speeds, exceeding hundreds of megabits per second over typical distances of 10 meters or less. The purpose of this Thesis is to estimate the timing accuracies required with such systems in order to achieve Bit Error Rates (BER) of the order of magnitude of 10-12 and thereby avoid overloading the correction of irreducible errors due to misaligned timing errors to a small absolute number of bits in error in real-time relative to a data rate of hundreds of megabits per second. Our research approach involves managing bit error rates through identifying maximum timing synchronization errors. Thus, it became our research goal to determine the timing accuracies required to avoid operation of communication systems within the asymptotic region of BER flaring at low BERs in the resultant BER curves. We propose pushing physical layer bit error rates to below 10-12 before using forward error correction (FEC) codes. This way, the maximum reserve is maintained for the FEC hardware to correct for burst as well as recurring bit errors due to corrupt bits caused by other than timing synchronization errors.

Yes / The broadcast nature of wireless local area networks has made them prone to several types of wireless injection attacks, such as Man-in-the-Middle (MitM) at the physical layer, deauthentication, and rogue access point attacks. The implementation of novel intrusion detection systems (IDSs) is fundamental to provide stronger protection against these wireless injection attacks. Since most attacks manifest themselves through different metrics, current IDSs should leverage a cross-layer approach to help toward improving the detection accuracy. The data fusion technique based on the Dempster–Shafer (D-S) theory has been proven to be an efficient technique to implement the cross-layer metric approach. However, the dynamic generation of the basic probability assignment (BPA) values used by D-S is still an open research problem. In this paper, we propose a novel unsupervised methodology to dynamically generate the BPA values, based on both the Gaussian and exponential probability density functions, the categorical probability mass function, and the local reachability density. Then, D-S is used to fuse the BPA values to classify whether the Wi-Fi frame is normal (i.e., non-malicious) or malicious. The proposed methodology provides 100% true positive rate (TPR) and 4.23% false positive rate (FPR) for the MitM attack and 100% TPR and 2.44% FPR for the deauthentication attack, which confirm the efficiency of the dynamic BPA generation methodology. / Gulf Science, Innovation and Knowledge Economy Programme of the U.K. Government under UK-Gulf Institutional Link Grant IL 279339985 and in part by the Engineering and Physical Sciences Research Council (EPSRC), U.K., under Grant EP/R006385/1.

В работе изучается динамическая восприимчивость феррожидкости, которая моделируется системой взаимодействующих подвижных магнитных частиц. Предполагается, что система находится в постоянном и переменном магнитном полях, направленных параллельно друг другу. / In this work, we study the dynamic susceptibility of a ferrofluid, which is modeled by an system of interacting moving magnetic particles. It is assumed that the system is in a constant and an alternating magnetic field, directed parallel to each other.

A prescription is given to obtain some exact results for certain external potentials �� (r) of the time-independent Gross-Pitaevskii and Schrodinger equations. The study motivation is the ability to program �� (r) experimentally in cold atom Bose-Einstein condensates. Rather than derive wavefunctions that are solutions for a given �� (r), we ask which �� (r) will have a given pdf (probability density function) �� (r). Several examples in 1 dimension (1D), 2 dimensions (2D), and 3 dimensions (3D) are presented for well-known pdfs in the position space. Exact potentials with zero, one and two walls are obtained and explained in detail. Apart from position space, the method is also applicable to obtain exact solutions for the Time-independent Schr¨odinger equation (TISE) and Gross-Pitaevskii equation (GPeq) for pdfs in momentum space. For this, we derived the potentials which are generated from the pdfs of the hydrogen atom in the real space as well as in the momentum space. However, the method was also extended for the time-dependent case. The prescription is also applicable to solve time-dependent pdfs. The aim is to find the ��(r, ��) which generates the pdf ��(r, ��). As a special case, we tested our method by studying the well known case for the Gaussian wave packet in 1D with zero potential ��(��, ��) = 0.

An accurate PDF of irradiance for a FSO channel is important when designing a laser radar, active laser imaging, or a communications system to operate over the channel. Parameters such as detector threshold level, probability of detection, mean fade time, number of fades, BER, and SNR are derived from the PDF and determine the design constraints of the receiver, transmitter, and corresponding electronics. Current PDF models of irradiance, such as the Gamma-Gamma, do not fully capture the effect of aperture averaging; a reduction in scintillation as the diameter of the collecting optic is increased. The Gamma-Gamma PDF of irradiance is an attractive solution because the parameters of the distribution are derived strictly from atmospheric turbulence parameters; propagation path length, Cn2, l0, and L0. This dissertation describes a heuristic physics-based modeling technique to develop a new PDF of irradiance based upon the optical field. The goal of the new PDF is three-fold: capture the physics of the turbulent atmosphere, better describe aperture averaging effects, and relate parameters of the new model to measurable atmospheric parameters. The modeling decomposes the propagating electromagnetic field into a sum of independent random-amplitude spatial plane waves using an approximation to the Karhunen-Loeve expansion. The scattering effects of the turbulence along the propagation path define the random-amplitude of each component of the expansion. The resulting PDF of irradiance is a double finite sum containing a Bessel function. The newly developed PDF is a generalization of the Gamma-Gamma PDF, and reduces to such in the limit. An experiment was setup and performed to measure the PDF of irradiance for several receiver aperture sizes under moderate to strong turbulence conditions. The propagation path was instrumented with scintillometers and anemometers to characterize the turbulence conditions. The newly developed PDF model and the GG model were compared to histograms of the experimental data. The new PDF model was typically able to match the data as well or better than the GG model under conditions of moderate aperture averaging. The GG model fit the data better than the new PDF under conditions of significant aperture averaging. Due to a limiting scintillation index value of 3, the new PDF was not compared to the GG for point apertures under strong turbulence; a regime where the GG is known to fit data well.

No description available.

<p>In recent years, two estimators have been proposed to correct the bias exhibited by the leastsquares (LS) estimator of the lagged dependent variable (LDV) coefficient in dynamic regression models when the sample is finite. They have been termed as &lsquo / mean-unbiased&rsquo / and &lsquo / medianunbiased&rsquo / estimators. Relative to other similar procedures in the literature, the two locationbased estimators have the advantage that they offer an exact and uniform methodology for LS estimation of the LDV coefficient in a first order autoregressive model with or without exogenous regressors i.e. ARX(1).</p> <p><br /> However, no attempt has been made to accurately establish and/or compare the statistical properties among these estimators, or relative to those of the LS estimator when the LDV coefficient is restricted to realistic values. Neither has there been an attempt to&nbsp / compare their performance in terms of their mean squared error (MSE) when various forms of the exogenous regressors are considered. Furthermore, only implicit confidence intervals have been given for the &lsquo / medianunbiased&rsquo / estimator. Explicit confidence bounds that are directly usable for inference are not available for either estimator. In this study a new estimator of the LDV coefficient is proposed / the &lsquo / most-probably-unbiased&rsquo / estimator. Its performance properties vis-a-vis the existing estimators are determined and compared when the parameter space of the LDV coefficient is restricted. In addition, the following new results are established: (1) an explicit computable form for the density of the LS estimator is derived for the first time and an efficient method for its numerical evaluation is proposed / (2) the exact bias, mean, median and mode of the distribution of the LS estimator are determined in three specifications of the ARX(1) model / (3) the exact variance and MSE of LS estimator is determined / (4) the standard error associated with the determination of same quantities when simulation rather than numerical integration method is used are established and the methods are compared in terms of computational time and effort / (5) an exact method of evaluating the density of the three estimators is described / (6) their exact bias, mean, variance and MSE are determined and analysed / and finally, (7) a method of obtaining the explicit exact confidence intervals from the distribution functions of the estimators is proposed.</p> <p><br /> The discussion and results show that the estimators are still biased in the usual sense: &lsquo / in expectation&rsquo / . However the bias is substantially reduced compared to that of the LS estimator. The findings are important in the specification of time-series regression models, point and interval estimation, decision theory, and simulation.</p>