Non-reproducibility of the cross sections of the products induced from dissipative reaction of F-19+Al-27

The differential cross sections of the dissipative products B, Q N, O, F, Ne, Na and Mg induced from the reactions of F-19+Al-27 at two incident energies have been measured at the HI-13 tandem accelerator, Beijing. In the case of a fixed beam incident energy 114MeV or 118.75MeV respectively, identical reaction system and the same detection system, 20 target points in steps of 2mm on(.)a 10mmx50mm rectangular Al foil have been bombarded. The experimental results indicate that the probability distribution of the cross sections is much wider than a standard Gaussian distribution. This non-reproducibility of the cross sections can't be interpreted by the statistical property of a finite count rate.

How Well Can TCP Infer Network State?

The Transmission Control Protocol (TCP) has been the protocol of choice for many Internet applications requiring reliable connections. The design of TCP has been challenged by the extension of connections over wireless links. We ask a fundamental question: What is the basic predictive power of TCP of network state, including wireless error conditions? The goal is to improve or readily exploit this predictive power to enable TCP (or variants) to perform well in generalized network settings. To that end, we use Maximum Likelihood Ratio tests to evaluate TCP as a detector/estimator. We quantify how well network state can be estimated, given network response such as distributions of packet delays or TCP throughput that are conditioned on the type of packet loss. Using our model-based approach and extensive simulations, we demonstrate that congestion-induced losses and losses due to wireless transmission errors produce sufficiently different statistics upon which an efficient detector can be built; distributions of network loads can provide effective means for estimating packet loss type; and packet delay is a better signal of network state than short-term throughput. We demonstrate how estimation accuracy is influenced by different proportions of congestion versus wireless losses and penalties on incorrect estimation.

Statistical analysis of extreme forest fires

Forest fires can cause extensive damage to natural resources and properties. They can also destroy wildlife habitat, affect the forest ecosystem and threaten human lives. In this paper extreme wildland fires are analysed using a point process model for extremes. The model based on a generalised Pareto distribution is used to model data on acres of wildland burnt by extreme fire in the US since 1825. A semi-parametric smoothing approach is adapted with maximum likelihood method to estimate model parameters.

Semi-Parametric Analysis of Extreme Forest Fires

Forest fires can cause extensive damage to natural resources and properties. They can also destroy wildlife habitat, affect the forest ecosystem and threaten human lives. In this paper incidences of extreme wildland fires are modelled by a point process model which incorporates time-trend. A model based on a generalised Pareto distribution is used to model data on acres of wildland burnt by extreme fire in the US since 1825. A semi-parametric smoothing approach, which is very useful in exploratory analysis of changes in extremes, is illustrated with the maximum likelihood method to estimate model parameters.

B-type supergiants in the Small Magellanic Cloud: rotational velocities and implications for evolutionary models

High-resolution spectra for 24 SMC and Galactic B-type supergiants have been analysed to estimate the contributions of both macroturbulence and rotation to the broadening of their metal lines. Two different methodologies are considered, viz. goodness-of-fit comparisons between observed and theoretical line profiles and identifying zeros in the Fourier transforms of the observed profiles. The advantages and limitations of the two methods are briefly discussed with the latter techniques being adopted for estimating projected rotational velocities ( v sin i) but the former being used to estimate macroturbulent velocities. The projected rotational velocity estimates range from approximately 20 to 60 kms(-1), apart from one SMC supergiant, Sk 191, with a v sin i similar or equal to 90 km s(-1). Apart from Sk 191, the distribution of projected rotational velocities as a function of spectral type are similar in both our Galactic and SMC samples with larger values being found at earlier spectral types. There is marginal evidence for the projected rotational velocities in the SMC being higher than those in the Galactic targets but any differences are only of the order of 5 - 10 km s(-1), whilst evolutionary models predict differences in this effective temperature range of typically 20 to 70 km s(-1). The combined sample is consistent with a linear variation of projected rotational velocity with effective temperature, which would imply rotational velocities for supergiants of 70 kms(-1) at an effective temperature of 28 000 K ( approximately B0 spectral type) decreasing to 32 km s(-1) at 12 000 K (B8 spectral type). For all targets, the macroturbulent broadening would appear to be consistent with a Gaussian distribution ( although other distributions cannot be discounted) with an 1/e half-width varying from approximately 20 km s(-1) at B8 to 60 km s(-1) at B0 spectral types.

The VLT-FLAMES survey of massive stars: stellar parameters and rotational velocities in NGC 3293, NGC 4755 and NGC 6611

An analysis is presented of VLT-FLAMES spectroscopy for three Galactic clusters, NGC3293, NGC4755 and NGC6611. Non-LTE model atmosphere calculations have been used to estimate effective temperatures (from either the helium spectrum or the silicon ionization equilibrium) and gravities (from the hydrogen spectrum). Projected rotational velocities have been deduced from the helium spectrum (for fast and moderate rotators) or the metal line spectrum (for slow rotators). The origin of the low gravity estimates for apparently near main sequence objects is discussed and is related to the stellar rotational velocity. The atmospheric parameters have been used to estimate cluster distances (which are generally in good agreement with previous determinations) and these have been used to estimate stellar luminosities and evolutionary masses. The observed Hertzsprung-Russell diagrams are compared with theoretical predictions and some discrepancies including differences in the main sequence luminosities are discussed. Cluster ages have been deduced and evidence for non-coeval star formation is found for all three of the clusters. Projected rotational velocities for targets in the older clusters, NGC3293 and NGC4755, have been found to be systematically larger than those for the field, confirming recent results in other similar age clusters. The distribution of projected rotational velocities are consistent with a Gaussian distribution of intrinsic rotational velocities. For the relatively unevolved targets in the older clusters, NGC3293 and NGC4755, the peak of the velocity distribution would be 250 km s(-1) with a full-width-half-maximum of approximately 180 km s(-1). For NGC6611, the sample size is relatively small but implies a lower mean rotational velocity. This may be evidence for the spin-down effect due to angular momentum loss through stellar winds, although our results are consistent with those found for very young high mass stars. For all three clusters we deduce present day mass functions with Gamma-values in the range of -1.5 to -1.8, which are similar to other young stellar clusters in the Milky Way.

Barrier height variations and interface properties of PtSi/Si structures

To study some of the interfacial properties of PtSi/Si diodes, Schottky structures were fabricated on (100) crystalline silicon substrates by conventional thermal evaporation of Pt on Si followed by annealing at different temperatures (from 400 degrees C to 700 degrees C) to form PtSi. The PtSi/n-Si diodes, all yielded Schottky barrier (SB) heights that are remarkably temperature dependent. The temperature range (20-290 K) over which the I-V characteristics were measured in the present study is broader with a much lower limit (20 K), than what is usually reported in literature. These variations in the barrier height are adequately interpreted by introducing spatial inhomogeneity into the barrier potential with a Gaussian distribution having a mean barrier of 0.76 eV and a standard deviation of 30 meV. Multi-frequency capacitance-voltage measurements suggest that the barrier is primarily controlled by the properties of the silicide-silicon interface. The forward C-V characteristics, in particular, show small peaks at low frequencies that can be ascribed to interface states rather than to a series resistance effect.

Performance Analysis of Randomized Distributed Space-Time Codes over Composite Gamma/Lognormal Fading Channels

This work investigates the end-to-end performance of randomized distributed space-time codes with complex Gaussian distribution, when employed in a wireless relay network. The relaying nodes are assumed to adopt a decode-and-forward strategy and transmissions are affected by small and large scale fading phenomena. Extremely tight, analytical approximations of the end-to-end symbol error probability and of the end-to-end outage probability are derived and successfully validated through Monte-Carlo simulation. For the high signal-to-noise ratio regime, a simple, closed-form expression for the symbol error probability is further provided.

Barrier characteristics of PtSi/p-Si schottky diodes as determined from I-V-T measurements

The current-voltage-temperature characteristics of PtSi/p-Si Schottky barrier diodes were measured in the temperature range 60-115 K. Deviation of the ideality factor from unity below 80 K may be modelled using the so-called T-0 parameter with T-0 = 18 K. It is also shown that the curvature in the Richardson plots may be remedied by using the flatband rather than the zero-bias saturation current density. Physically, the departure from ideality is interpreted in terms of an inhomogeneous Schottky contact. Here we determine a mean barrier height at T = 0 K, phi(b)(-0) = 223 mV, with an (assumed) Gaussian distribution of standard deviation sigma(phi) = 12.5 mV. These data are correlated with the zero-bias barrier height, phi(j)(0) = 192 mV (at T = 90 K), the photoresponse barrier height, phi(ph) = 205 mV, and the flatband barrier height, phi(fb) = 214 mV. Finally, the temperature coefficient of the flatband barrier was found to be -0.121 mV K-1, which is approximately equal to 1/2(dE(g)(i)/dT), thus suggesting that the Fermi level at the interface is pinned to the middle of the band gap.

Polarization effects in fiber-optic communication systems

In this thesis we perform a detailed analysis of the state of polarization (SOP) of light scattering process using a concatenation of ber-coil based polarization controllers (PCs). We propose a polarization-mode dispersion (PMD) emulator, built through the concatenation of bercoil based PCs and polarization-maintaining bers (PMFs), capable of generate accurate rst- and second-order PMD statistics. We analyze the co-propagation of two optical waves inside a highbirefringence ber. The evolution along the ber of the relative SOP between the two signals is modeled by the de nition of the degree of co-polarization parameter. We validate the model for the degree of co-polarization experimentally, exploring the polarization dependence of the four-wave mixing e ect into a ber with high birefringence. We also study the interaction between signal and noise mediated by Kerr e ect in optical bers. A model accurately describing ampli ed spontaneous emission noise in systems with distributed Raman gain is derived. We show that the noise statistics depends on the propagation distance and on the signal power, and that for distances longer than 120 km and signal powers higher than 6 mW it deviates signi catively from the Gaussian distribution. We explore the all-optical polarization control process based on the stimulated Raman scattering e ect. Mapping parameters like the degree of polarization (DOP), we show that the preferred ampli cation of one particular polarization component of the signal allows a polarization pulling over a wavelength range of 60 nm. The e ciency of the process is higher close to the maximum Raman gain wavelength, where the DOP is roughly constant for a wavelength range of 15 nm. Finally, we study the polarization control in quantum key distribution (QKD) systems with polarization encoding. A model for the quantum bit error rate estimation in QKD systems with time-division multiplexing and wavelength-division multiplexing based polarization control schemes is derived.

Classification of incomplete feature vectors by radial basis function networks

The paper describes the use of radial basis function neural networks with Gaussian basis functions to classify incomplete feature vectors. The method uses the fact that any marginal distribution of a Gaussian distribution can be determined from the mean vector and covariance matrix of the joint distribution.

A probabilistic methodology for distributed generation location in isolated electrical service area

Distributed generation unlike centralized electrical generation aims to generate electrical energy on small scale as near as possible to load centers, interchanging electric power with the network. This work presents a probabilistic methodology conceived to assist the electric system planning engineers in the selection of the distributed generation location, taking into account the hourly load changes or the daily load cycle. The hourly load centers, for each of the different hourly load scenarios, are calculated deterministically. These location points, properly weighted according to their load magnitude, are used to calculate the best fit probability distribution. This distribution is used to determine the maximum likelihood perimeter of the area where each source distributed generation point should preferably be located by the planning engineers. This takes into account, for example, the availability and the cost of the land lots, which are factors of special relevance in urban areas, as well as several obstacles important for the final selection of the candidates of the distributed generation points. The proposed methodology has been applied to a real case, assuming three different bivariate probability distributions: the Gaussian distribution, a bivariate version of Freund’s exponential distribution and the Weibull probability distribution. The methodology algorithm has been programmed in MATLAB. Results are presented and discussed for the application of the methodology to a realistic case and demonstrate the ability of the proposed methodology for efficiently handling the determination of the best location of the distributed generation and their corresponding distribution networks.

Practical simulation of GNSS signals in the presence of ionospheric scintillaton

We propose a low complexity technique to generate amplitude correlated time-series with Nakagami-m distribution and phase correlated Gaussian-distributed time-series, which is useful in the simulation of ionospheric scintillation effects during the transmission of GNSS signals. The method requires only the knowledge of parameters S4 (scintillation index) and σΦ (phase standard deviation) besides the definition of models for the amplitude and phase power spectra. The Zhang algorithm is used to produce Nakagami-distributed signals from a set of Gaussian autoregressive processes.

Exact Skewness-Kurtosis Tests for Multivariate Normality and Goodness-of-fit in Multivariate Regressions with Application to Asset Pricing Models

We study the problem of testing the error distribution in a multivariate linear regression (MLR) model. The tests are functions of appropriately standardized multivariate least squares residuals whose distribution is invariant to the unknown cross-equation error covariance matrix. Empirical multivariate skewness and kurtosis criteria are then compared to simulation-based estimate of their expected value under the hypothesized distribution. Special cases considered include testing multivariate normal, Student t; normal mixtures and stable error models. In the Gaussian case, finite-sample versions of the standard multivariate skewness and kurtosis tests are derived. To do this, we exploit simple, double and multi-stage Monte Carlo test methods. For non-Gaussian distribution families involving nuisance parameters, confidence sets are derived for the the nuisance parameters and the error distribution. The procedures considered are evaluated in a small simulation experi-ment. Finally, the tests are applied to an asset pricing model with observable risk-free rates, using monthly returns on New York Stock Exchange (NYSE) portfolios over five-year subperiods from 1926-1995.

Computationally Efficient Bootstrap Prediction Intervals for Returns and Volatilities in ARCH and GARCH Processes

We propose a novel, simple, efficient and distribution-free re-sampling technique for developing prediction intervals for returns and volatilities following ARCH/GARCH models. In particular, our key idea is to employ a Box–Jenkins linear representation of an ARCH/GARCH equation and then to adapt a sieve bootstrap procedure to the nonlinear GARCH framework. Our simulation studies indicate that the new re-sampling method provides sharp and well calibrated prediction intervals for both returns and volatilities while reducing computational costs by up to 100 times, compared to other available re-sampling techniques for ARCH/GARCH models. The proposed procedure is illustrated by an application to Yen/U.S. dollar daily exchange rate data.