Single-carrier frequency domain equalisation for hammerstein communication systems using complex-valued neural networks

Single-carrier (SC) block transmission with frequency-domain equalisation (FDE) offers a viable transmission technology for combating the adverse effects of long dispersive channels encountered in high-rate broadband wireless communication systems. However, for high bandwidthefficiency and high power-efficiency systems, the channel can generally be modelled by the Hammerstein system that includes the nonlinear distortion effects of the high power amplifier (HPA) at transmitter. For such nonlinear Hammerstein channels, the standard SC-FDE scheme no longer works. This paper advocates a complex-valued (CV) B-spline neural network based nonlinear SC-FDE scheme for Hammerstein channels. Specifically, We model the nonlinear HPA, which represents the CV static nonlinearity of the Hammerstein channel, by a CV B-spline neural network, and we develop two efficient alternating least squares schemes for estimating the parameters of the Hammerstein channel, including both the channel impulse response coefficients and the parameters of the CV B-spline model. We also use another CV B-spline neural network to model the inversion of the nonlinear HPA, and the parameters of this inverting B-spline model can easily be estimated using the standard least squares algorithm based on the pseudo training data obtained as a natural byproduct of the Hammerstein channel identification. Equalisation of the SC Hammerstein channel can then be accomplished by the usual one-tap linear equalisation in frequency domain as well as the inverse B-spline neural network model obtained in time domain. Extensive simulation results are included to demonstrate the effectiveness of our nonlinear SC-FDE scheme for Hammerstein channels.

Using reanalysis data to quantify extreme wind power generation statistics : a 33 year case study in Great Britain

With a rapidly increasing fraction of electricity generation being sourced from wind, extreme wind power generation events such as prolonged periods of low (or high) generation and ramps in generation, are a growing concern for the efficient and secure operation of national power systems. As extreme events occur infrequently, long and reliable meteorological records are required to accurately estimate their characteristics. Recent publications have begun to investigate the use of global meteorological “reanalysis” data sets for power system applications, many of which focus on long-term average statistics such as monthly-mean generation. Here we demonstrate that reanalysis data can also be used to estimate the frequency of relatively short-lived extreme events (including ramping on sub-daily time scales). Verification against 328 surface observation stations across the United Kingdom suggests that near-surface wind variability over spatiotemporal scales greater than around 300 km and 6 h can be faithfully reproduced using reanalysis, with no need for costly dynamical downscaling. A case study is presented in which a state-of-the-art, 33 year reanalysis data set (MERRA, from NASA-GMAO), is used to construct an hourly time series of nationally-aggregated wind power generation in Great Britain (GB), assuming a fixed, modern distribution of wind farms. The resultant generation estimates are highly correlated with recorded data from National Grid in the recent period, both for instantaneous hourly values and for variability over time intervals greater than around 6 h. This 33 year time series is then used to quantify the frequency with which different extreme GB-wide wind power generation events occur, as well as their seasonal and inter-annual variability. Several novel insights into the nature of extreme wind power generation events are described, including (i) that the number of prolonged low or high generation events is well approximated by a Poission-like random process, and (ii) whilst in general there is large seasonal variability, the magnitude of the most extreme ramps is similar in both summer and winter. An up-to-date version of the GB case study data as well as the underlying model are freely available for download from our website: http://www.met.reading.ac.uk/~energymet/data/Cannon2014/.

Testing projected wild bee distributions in agricultural habitats: predictive power depends on species traits and habitat type

Species distribution models (SDM) are increasingly used to understand the factors that regulate variation in biodiversity patterns and to help plan conservation strategies. However, these models are rarely validated with independently collected data and it is unclear whether SDM performance is maintained across distinct habitats and for species with different functional traits. Highly mobile species, such as bees, can be particularly challenging to model. Here, we use independent sets of occurrence data collected systematically in several agricultural habitats to test how the predictive performance of SDMs for wild bee species depends on species traits, habitat type, and sampling technique. We used a species distribution modeling approach parametrized for the Netherlands, with presence records from 1990 to 2010 for 193 Dutch wild bees. For each species, we built a Maxent model based on 13 climate and landscape variables. We tested the predictive performance of the SDMs with independent datasets collected from orchards and arable fields across the Netherlands from 2010 to 2013, using transect surveys or pan traps. Model predictive performance depended on species traits and habitat type. Occurrence of bee species specialized in habitat and diet was better predicted than generalist bees. Predictions of habitat suitability were also more precise for habitats that are temporally more stable (orchards) than for habitats that suffer regular alterations (arable), particularly for small, solitary bees. As a conservation tool, SDMs are best suited to modeling rarer, specialist species than more generalist and will work best in long-term stable habitats. The variability of complex, short-term habitats is difficult to capture in such models and historical land use generally has low thematic resolution. To improve SDMs’ usefulness, models require explanatory variables and collection data that include detailed landscape characteristics, for example, variability of crops and flower availability. Additionally, testing SDMs with field surveys should involve multiple collection techniques.

Improving power and accuracy of genome-wide association studies via a multi-locus mixed linear model methodology

Genome-wide association studies (GWAS) have been widely used in genetic dissection of complex traits. However, common methods are all based on a fixed-SNP-effect mixed linear model (MLM) and single marker analysis, such as efficient mixed model analysis (EMMA). These methods require Bonferroni correction for multiple tests, which often is too conservative when the number of markers is extremely large. To address this concern, we proposed a random-SNP-effect MLM (RMLM) and a multi-locus RMLM (MRMLM) for GWAS. The RMLM simply treats the SNP-effect as random, but it allows a modified Bonferroni correction to be used to calculate the threshold p value for significance tests. The MRMLM is a multi-locus model including markers selected from the RMLM method with a less stringent selection criterion. Due to the multi-locus nature, no multiple test correction is needed. Simulation studies show that the MRMLM is more powerful in QTN detection and more accurate in QTN effect estimation than the RMLM, which in turn is more powerful and accurate than the EMMA. To demonstrate the new methods, we analyzed six flowering time related traits in Arabidopsis thaliana and detected more genes than previous reported using the EMMA. Therefore, the MRMLM provides an alternative for multi-locus GWAS.

Importance of estimating matrix quality for modeling species distribution in complex tropical landscapes: a test with Atlantic forest small mammals

Information to guide decision making is especially urgent in human dominated landscapes in the tropics, where urban and agricultural frontiers are still expanding in an unplanned manner. Nevertheless, most studies that have investigated the influence of landscape structure on species distribution have not considered the heterogeneity of altered habitats of the matrix, which is usually high in human dominated landscapes. Using the distribution of small mammals in forest remnants and in the four main altered habitats in an Atlantic forest landscape, we investigated 1) how explanatory power of models describing species distribution in forest remnants varies between landscape structure variables that do or do not incorporate matrix quality and 2) the importance of spatial scale for analyzing the influence of landscape structure. We used standardized sampling in remnants and altered habitats to generate two indices of habitat quality, corresponding to the abundance and to the occurrence of small mammals. For each remnant, we calculated habitat quantity and connectivity in different spatial scales, considering or not the quality of surrounding habitats. The incorporation of matrix quality increased model explanatory power across all spatial scales for half the species that occurred in the matrix, but only when taking into account the distance between habitat patches (connectivity). These connectivity models were also less affected by spatial scale than habitat quantity models. The few consistent responses to the variation in spatial scales indicate that despite their small size, small mammals perceive landscape features at large spatial scales. Matrix quality index corresponding to species occurrence presented a better or similar performance compared to that of species abundance. Results indicate the importance of the matrix for the dynamics of fragmented landscapes and suggest that relatively simple indices can improve our understanding of species distribution, and could be applied in modeling, monitoring and managing complex tropical landscapes.

A complex network-based approach for boundary shape analysis

This paper introduces a novel methodology to shape boundary characterization, where a shape is modeled into a small-world complex network. It uses degree and joint degree measurements in a dynamic evolution network to compose a set of shape descriptors. The proposed shape characterization method has all efficient power of shape characterization, it is robust, noise tolerant, scale invariant and rotation invariant. A leaf plant classification experiment is presented on three image databases in order to evaluate the method and compare it with other descriptors in the literature (Fourier descriptors, Curvature, Zernike moments and multiscale fractal dimension). (C) 2008 Elsevier Ltd. All rights reserved.

Border trees of complex networks

The comprehensive characterization of the structure of complex networks is essential to understand the dynamical processes which guide their evolution. The discovery of the scale-free distribution and the small-world properties of real networks were fundamental to stimulate more realistic models and to understand important dynamical processes related to network growth. However, the properties of the network borders (nodes with degree equal to 1), one of its most fragile parts, remained little investigated and understood. The border nodes may be involved in the evolution of structures such as geographical networks. Here we analyze the border trees of complex networks, which are defined as the subgraphs without cycles connected to the remainder of the network (containing cycles) and terminating into border nodes. In addition to describing an algorithm for identification of such tree subgraphs, we also consider how their topological properties can be quantified in terms of their depth and number of leaves. We investigate the properties of border trees for several theoretical models as well as real-world networks. Among the obtained results, we found that more than half of the nodes of some real-world networks belong to the border trees. A power-law with cut-off was observed for the distribution of the depth and number of leaves of the border trees. An analysis of the local role of the nodes in the border trees was also performed.

Harold Pinter: A Night Out : A Study in the Political ConnotationsAnd the Abuse of Power

Harold Pinter’s A Night Out is a significant but rarely produced piece of drama. Therefore, there is very little criticism to support or contradict my argument. The reason why I chose to do my essay on this particular play is to open doors for academic research and to try and make it an equal to its sister plays. I will raise questions and topics to prove the play is worth the readers’ time and effort and that A Night Out is a sharp piece of political theatre. Although at first glance it is a simple enough story, a straightforward tale of the nasty consequences of motherly love when it is pushed to the limit, on deeper inspection, a more far reaching and complex analysis of the abuse of power can be observed. The play offers a variety of themes, including: interpersonal power struggles, failed attempts at communication, antagonistic relationships, the threat of impending or past violence, the struggle for survival or identity, domination and submission, politics, lies and verbal, physical, psychological and sexual abuse. The prevailing theme in the play is the abuse of power: powerful parties oppressing weaker ones, and the results of the oppressed party looking for a vent in someone even weaker than themselves.

Board of directors and top management team: a study on CEO relative power and financial return

Best corporate governance practices published in the primers of Brazilian Securities and Exchange Commission and the Brazilian Corporate Governance Institute promote board independence as much as possible, as a way to increase the effectiveness of governance mechanism (Sanzovo, 2010). Therefore, this paper aims at understanding if what the managerial literature portraits as being self-evident - stricter governance, better performance - can be observed in actual evidence. The question answered is: do companies with a stricter control and monitoring system perform better than others? The method applied in this paper consists on comparing 116 companies in respect to the their independence level between top management team and board directors– being that measured by four parameters, namely, the percentage of independent outsiders in the board, the separation of CEO and chairman, the adoption of contingent compensation and the percentage of institutional investors in the ownership structure – and their financial return measured in terms return on assets (ROA) from the latest Quarterly Earnings release of 2012. From the 534 companies listed in the Stock Exchange of Sao Paulo – Bovespa – 116 were selected due to their level of corporate governance. The title “Novo Mercado” refers to the superior level of governance level within companies listed in Bovespa, as they have to follow specific criteria to assure shareholders ´protection (BM&F, 2011). Regression analyses were conducted in order to reveal the correlation level between two selected variables. The results from the regression analysis were the following: the correlation between each parameter and ROA was 10.26%; the second regression analysis conducted measured the correlation between the independence level of top management team vis-à-vis board directors – namely, CEO relative power - and ROA, leading to a multiple R of 5.45%. Understanding that the scale is a simplification of the reality, the second part of the analysis transforms all the four parameters into dummy variables, excluding what could be called as an arbitrary scale. The ultimate result from this paper led to a multiple R of 28.44%, which implies that the combination of the variables are still not enough to translate the complex reality of organizations. Nonetheless, an important finding can be taken from this paper: two variables (percentage of outside directors and percentage of institutional investor ownership) are significant in the regression, with p-value lower than 10% and with negative coefficients. In other words, counter affirming what the literature very often portraits as being self-evident – stricter governance leads to higher performance – this paper has provided evidences to believe that the increase in the formal governance structure trough outside directors in the board and ownership by institutional investor might actually lead to worse performance. The section limitations and suggestions for future researches presents some reasons explaining why, although supported by strong theoretical background, this paper faced some challenging methodological assumptions, precluding categorical statements about the level of governance – measured by four selected parameters – and the financial return in terms of financial on assets.

Economic landscapes, what are they? an application to the Brazilian economy and to the sugar cane complex

In assessing the economic impact of a sector or group of sectors on a single or multiregional economy, input-output analysis has proven to be a popular method. . However, there has a problem in displaying all the information that can be obtained from this analytical approach. In this paper, we have tried to set new directions in the use of input-output analysis by presenting an improved way of looking at the economic landscapes. While this is not a new concept, a new meaning is explored in this paper; essentially, it will now be possible to visualize, in a simple picture, all the relations in the economy as well as being able to view how one sector is related to the other sectors/regions in the economy. These relations can be measured in terms of structural changes, production, value added, employment, imports, etc. While all the possibilities cannot be explored in this paper, the basic idea is given here and the smart reader can uncover all the various possibilities. To illustrate the power of analysis provided by the economic landscapes, an application is made to the sugar cane complex using an interregional inputoutput system for the Brazilian economy, constructed for 2 regions (Northeast and Rest of Brazil), for the years of 1985, 1992, and 1995.

An efficient neural approach to economic load dispatch in power systems

A neural approach to solve the problem defined by the economic load dispatch in power systems is presented in this paper, Systems based on artificial neural networks have high computational rates due to the use of a massive number of simple processing elements and the high degree of connectivity between these elements the ability of neural networks to realize some complex nonlinear function makes them attractive for system optimization the neural networks applyed in economic load dispatch reported in literature sometimes fail to converge towards feasible equilibrium points the internal parameters of the modified Hopfield network developed here are computed using the valid-subspace technique These parameters guarantee the network convergence to feasible quilibrium points, A solution for the economic load dispatch problem corresponds to an equilibrium point of the network. Simulation results and comparative analysis in relation to other neural approaches are presented to illustrate efficiency of the proposed approach.

Improvements for ZCS-PWM commutation cell in high-power-factor preregulator application

A Summary of different topological arrangements concerning a ZCS-PWM cell is presented, based on the analysis of its application in boost rectifying preregulators, controlled by the technique of instantaneous average values of input current, with the purpose of obtaining high-input-power-factor rectifier and high efficiency in single-phase applications in telecommunication systems. The main characteristics of each switching cell are described, providing conditions to establish a qualitative comparison among the structures. In addition, experimental results are presented for a prototype of the latest version of the ZCS-PWM boost rectifier, implemented for processing normal values of 1200 W output power and 400 V output average voltage, at 220 V Input RMS voltage and 50 kHz switching frequency.

Load compensation in four-wire electrical power systems

This work describes a methodology for power factor control and correction of the unbalanced currents in four-wire electric circuits. The methodology is based on the insertion of two compensation networks, one wye-grounded neutral and another in delta, in parallel to the load. The mathematical development has been proposed in previous work [3]. In this paper, however, the methodology was adapted to accept different power factors for the system to be compensated. on the other hand, the determination of the compensation susceptances is based on the instantaneous values of the load currents. The results are obtained using the MatLab - Simulink environment.

High power factor dimmable electronic ballast for multiple tubular fluorescent lamps

This paper presents a dimmable electronic ballast designed for multiple fluorescent lamps applications. A ZCS-PWM Boost rectifier and a classical resonant Full-Bridge inverter compose this new electronic ballast, providing conditions for the obtaining of high input power-factor, and soft-switching processes for all semiconductor devices employed in the structure. The instantaneous average input current control technique is employed in the Boost rectifier. Concerning the Full-Bridge inverter, it is controlled by the imposition of phase-shift in the current processed through the sets of resonant filters + lamps, according to an adaptation in a specially designed control IC, called IR2159. Experimental results are presented in order to validate the analyses developed in this paper.

A simple feedback control for a chaotic oscillator with limited power supply

We proposed a simple feedback control method to suppress chaotic behavior in oscillators with limited power supply. The small-amplitude controlling signal is applied directly to the power supply system, so as to alter the characteristic curve of the driving motor. Numerical results are presented showing the method efficiency for a wide range of control parameters. Moreover, we have found that, for some parameters, this kind of control may introduce coexisting periodic attractors with complex basins of attraction and, therefore, serious problems with predictability of the final state the system will asymptote to. (c) 2006 Elsevier Ltd. All rights reserved.