Justified Fault-Ride-Through Requirements for Wind Turbines in Power Systems

In this paper, a novel adaptive strategy to obtain technically justified fault-ride-through requirements for wind turbines (WTs) is proposed. The main objective is to promote an effective integration of wind turbines into power systems with still low penetration levels of wind power based on technical and economical considerations. The level of requirement imposed by the strategy is increased stepwise over time, depending on system characteristics and on wind power penetration level. The idea behind is to introduce stringent requirements only when they are technically needed for a reliable and secure power system operation. Voltage stability support and fault-ride-through requirements are considered in the strategy. Simulations are based on the Chilean transmission network, a midsize isolated power system with still low penetration levels of wind power. Simulations include fixed speed induction generators and doubly fed induction generators. The effects on power system stability of the wind power injections, integrated into the network by adopting the adaptive strategy, are compared with the effects that have the same installed capacity of wind power but only considering WTs able to fulfill stringent requirements (fault-ride-through capability and support voltage stability). Based on simulations and international experience, technically justified requirements for the Chilean case are proposed.

Placement over containers with fixed dimensions solved with adaptive neighborhood simulated annealing

This work deals with the problem of minimizing the waste of space that occurs on a rotational placement of a set of irregular bi-dimensional items inside a bi-dimensional container. This problem is approached with a heuristic based on Simulated Annealing (SA) with adaptive neighborhood. The objective function is evaluated in a constructive approach, where the items are placed sequentially. The placement is governed by three different types of parameters: sequence of placement, the rotation angle and the translation. The rotation applied and the translation of the polygon are cyclic continuous parameters, and the sequence of placement defines a combinatorial problem. This way, it is necessary to control cyclic continuous and discrete parameters. The approaches described in the literature deal with only type of parameter (sequence of placement or translation). In the proposed SA algorithm, the sensibility of each continuous parameter is evaluated at each iteration increasing the number of accepted solutions. The sensibility of each parameter is associated to its probability distribution in the definition of the next candidate.

Simulated annealing with adaptive neighborhood: A case study in off-line robot path planning

Simulated annealing (SA) is an optimization technique that can process cost functions with degrees of nonlinearities, discontinuities and stochasticity. It can process arbitrary boundary conditions and constraints imposed on these cost functions. The SA technique is applied to the problem of robot path planning. Three situations are considered here: the path is represented as a polyline; as a Bezier curve; and as a spline interpolated curve. In the proposed SA algorithm, the sensitivity of each continuous parameter is evaluated at each iteration increasing the number of accepted solutions. The sensitivity of each parameter is associated to its probability distribution in the definition of the next candidate. (C) 2010 Elsevier Ltd. All rights reserved.

Adaptive Carrier Tracking for Mars to Earth Communications During Entry, Descent, and Landing

We propose a robust and low complexity scheme to estimate and track carrier frequency from signals traveling under low signal-to-noise ratio (SNR) conditions in highly nonstationary channels. These scenarios arise in planetary exploration missions subject to high dynamics, such as the Mars exploration rover missions. The method comprises a bank of adaptive linear predictors (ALP) supervised by a convex combiner that dynamically aggregates the individual predictors. The adaptive combination is able to outperform the best individual estimator in the set, which leads to a universal scheme for frequency estimation and tracking. A simple technique for bias compensation considerably improves the ALP performance. It is also shown that retrieval of frequency content by a fast Fourier transform (FFT)-search method, instead of only inspecting the angle of a particular root of the error predictor filter, enhances performance, particularly at very low SNR levels. Simple techniques that enforce frequency continuity improve further the overall performance. In summary we illustrate by extensive simulations that adaptive linear prediction methods render a robust and competitive frequency tracking technique.

Transient and Steady-State Analysis of the Affine Combination of Two Adaptive Filters

In this paper, we propose an approach to the transient and steady-state analysis of the affine combination of one fast and one slow adaptive filters. The theoretical models are based on expressions for the excess mean-square error (EMSE) and cross-EMSE of the component filters, which allows their application to different combinations of algorithms, such as least mean-squares (LMS), normalized LMS (NLMS), and constant modulus algorithm (CMA), considering white or colored inputs and stationary or nonstationary environments. Since the desired universal behavior of the combination depends on the correct estimation of the mixing parameter at every instant, its adaptation is also taken into account in the transient analysis. Furthermore, we propose normalized algorithms for the adaptation of the mixing parameter that exhibit good performance. Good agreement between analysis and simulation results is always observed.

Distributed Estimation Over an Adaptive Incremental Network Based on the Affine Projection Algorithm

We study the problem of distributed estimation based on the affine projection algorithm (APA), which is developed from Newton`s method for minimizing a cost function. The proposed solution is formulated to ameliorate the limited convergence properties of least-mean-square (LMS) type distributed adaptive filters with colored inputs. The analysis of transient and steady-state performances at each individual node within the network is developed by using a weighted spatial-temporal energy conservation relation and confirmed by computer simulations. The simulation results also verify that the proposed algorithm provides not only a faster convergence rate but also an improved steady-state performance as compared to an LMS-based scheme. In addition, the new approach attains an acceptable misadjustment performance with lower computational and memory cost, provided the number of regressor vectors and filter length parameters are appropriately chosen, as compared to a distributed recursive-least-squares (RLS) based method.

Improving the tracking capability of adaptive filters via convex combination

As is well known, Hessian-based adaptive filters (such as the recursive-least squares algorithm (RLS) for supervised adaptive filtering, or the Shalvi-Weinstein algorithm (SWA) for blind equalization) converge much faster than gradient-based algorithms [such as the least-mean-squares algorithm (LMS) or the constant-modulus algorithm (CMA)]. However, when the problem is tracking a time-variant filter, the issue is not so clear-cut: there are environments for which each family presents better performance. Given this, we propose the use of a convex combination of algorithms of different families to obtain an algorithm with superior tracking capability. We show the potential of this combination and provide a unified theoretical model for the steady-state excess mean-square error for convex combinations of gradient- and Hessian-based algorithms, assuming a random-walk model for the parameter variations. The proposed model is valid for algorithms of the same or different families, and for supervised (LMS and RLS) or blind (CMA and SWA) algorithms.

SKAN: Skin Scanner - System for Skin Cancer Detection Using Adaptive Techniques

SKAN: Skin Scanner - System for Skin Cancer Detection Using Adaptive Techniques - combines computer engineering concepts with areas like dermatology and oncology. Its objective is to discern images of skin cancer, specifically melanoma, from others that show only common spots or other types of skin diseases, using image recognition. This work makes use of the ABCDE visual rule, which is often used by dermatologists for melanoma identification, to define which characteristics are analyzed by the software. It then applies various algorithms and techniques, including an ellipse-fitting algorithm, to extract and measure these characteristics and decide whether the spot is a melanoma or not. The achieved results are presented with special focus on the adaptive decision-making and its effect on the diagnosis. Finally, other applications of the software and its algorithms are presented.

The AdapLib Library for Execution of Adaptive Devices: Architecture and Use

In this paper it is presented the theoretical background, the architecture (using the ""4+1"" model), and the use of the library for execution of adaptive devices, AdapLib. This library was created seeking to be accurate to the adaptive devices theory, and to allow its easy extension considering the specific details of solutions that employ this kind of device. As an example, it is presented a case study in which the library was used to create a proof of concept to monitor and diagnose problems in an online news portal.

Using indicators of deforestation and land-use dynamics to support conservation strategies: A case study of central Rondonia, Brazil

In Rondonia State, Brazil, settlement processes have cleared 68,000 km 2 of tropical forests since the 1970s. The intensity of deforestation has differed by region depending on driving factors like roads and economic activities. Different histories of land-use activities and rates of change have resulted in mosaics of forest patches embedded in an agricultural matrix. Yet, most assessments of deforestation and its effects on vegetation, soil and water typically focus on landscape patterns of current conditions, yet historical deforestation dynamics can influence current conditions strongly. Here, we develop and describe the use of four land-use dynamic indicators to capture historical land-use changes of catchments and to measure the rate of deforestation (annual deforestation rate), forest regeneration level (secondary forest mean proportion), time since disturbance (mean time since deforestation) and deforestation profile (deforestation profile curvature). We used the proposed indices to analyze a watershed located in central Rondonia. Landsat TM and ETM+ images were used to produce historical land-use maps of the last 18 years, each even year from 1984 to 2002 for 20 catchments. We found that the land-use dynamics indicators are able to distinguish catchments with different land-use change profiles. Four categories of historical land-use were identified: old and dominant pasture cover on small properties, recent deforestation and dominance of secondary growth, old extensive pastures and large forest remnants and, recent deforestation, pasture and large forest remnants. Knowing historical deforestation processes is important to develop appropriate conservation strategies and define priorities and actions for conserving forests currently under deforestation. (C) 2009 Elsevier B.V. All rights reserved.

Plasmodium vivax recombinant vaccine candidate AMA-1 plays an important role in adaptive immune response eliciting differentiation of dendritic cells

The Apical Membrane Antigen-1 (AMA-1) is a well-characterized and functionally important merozoite protein and is currently considered a major candidate antigen for a malaria vaccine. Previously, we showed that AMA-1 has an influence on cellular immune responses of malaria-naive subjects, resulting in an alternative activation of monocyte-derived dendritic cells and induction of a pro-inflammatory response by stimulated PBMCs. Although there is evidence, from human and animal malaria model systems that cell-mediated immunity may contribute to both protection and pathogenesis, the knowledge on cellular immune responses in vivax malaria and the factors that may regulate this immunity are poorly understood. In the current work, we describe the maturation of monocyte-derived dendritic cells of P. vivax naturally infected individuals and the effect of P. vivax vaccine candidate Pv-AMA-1 on the immune responses of the same donors. We show that malaria-infected subjects present modulation of DC maturation, demonstrated by a significant decrease in expression of antigen-presenting molecules (CD1a, HLA-ABC and HLA-DR), accessory molecules (CD40, CD80 and CD86) and Fc gamma RI (CD64) receptor (P <= 0.05). Furthermore, Pv-AMA-1 elicits an upregulation of CD1a and HLA-DR molecules on the surface of monocyte-derived dendritic cells (P=0.0356 and P=0.0196, respectively), and it is presented by AMA-1-stimulated DCs. A significant pro-inflammatory response elicited by Pv-AMA-1-pulsed PBMCs is also demonstrated, as determined by significant production of TNF-alpha, IL-12p40 and IFN-gamma (P <= 0.05). Our results suggest that Pv-AMA-1 may partially revert DC down-modulation observed in infected subjects, and exert an important role in the initiation of pro-inflammatory immunity that might contribute substantially to protection. (c) 2009 Elsevier Ltd. All rights reserved.

A wavelet-based adaptive technique for adsorption problems involving steep gradients

A general, fast wavelet-based adaptive collocation method is formulated for heat and mass transfer problems involving a steep moving profile of the dependent variable. The technique of grid adaptation is based on sparse point representation (SPR). The method is applied and tested for the case of a gas–solid non-catalytic reaction in a porous solid at high Thiele modulus. Accurate and convergent steep profiles are obtained for Thiele modulus as large as 100 for the case of slab and found to match the analytical solution.

A fast cross-entropy method for estimating buffer overflows in queuing networks

In this paper, we propose a fast adaptive importance sampling method for the efficient simulation of buffer overflow probabilities in queueing networks. The method comprises three stages. First, we estimate the minimum cross-entropy tilting parameter for a small buffer level; next, we use this as a starting value for the estimation of the optimal tilting parameter for the actual (large) buffer level. Finally, the tilting parameter just found is used to estimate the overflow probability of interest. We study various properties of the method in more detail for the M/M/1 queue and conjecture that similar properties also hold for quite general queueing networks. Numerical results support this conjecture and demonstrate the high efficiency of the proposed algorithm.

Public support for sustainable commercial harvesting of wildlife: An Australian case study

This paper surveys a sample of 204 members of the Australian public to determine their attitude to the sustainable commercial harvesting of wildlife generally, and considers their specific support for the sustainable commercial harvesting of each of 24 Australian native species. The general attitude of the sample to wildlife harvesting is related to their attitude to nature conservation. The relationship between respondents’ support for the sustainable commercial harvesting of each of the species and their degree of endangerment based on IUCN Red List rankings is established and found to be an inverse one. Support for the commercial sustainable use of each of the species is compared with the willingness of respondents to pay for their conservation. Support for sustainable commercial harvesting of species is found to be inversely related to the willingness of respondents to pay is for a particular species’ conservation. In turn, this willingness to pay is found to rise with the degree of endangerment of species. While the likeability of a species has some influence on whether there is support or not for its commercial harvesting, it does not seem to be the predominant influence— the degree of endangerment of a species appears to be the major influence here. Even so, this does not imply majority support for the harvest of all species that are not threatened; rather, majority support for harvest was observed only for some species known to be abundant. None of the species that appear in the Red List have majority support for harvesting. Implications are outlined of the results for the policy of promoting wildlife conservation by means of sustainable use.