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.

Interface Energy Measurement of MgO and ZnO: Understanding the Thermodynamic Stability of Nanoparticles

Nanomaterials have triggered excitement in both fundamental science and technological applications in several fields However, the same characteristic high interface area that is responsible for their unique properties causes unconventional instability, often leading to local collapsing during application Thermodynamically, this can be attributed to an increased contribution of the interface to the free energy, activating phenomena such as sintering and grain growth The lack of reliable interface energy data has restricted the development of conceptual models to allow the control of nanoparticle stability on a thermodynamic basis. Here we introduce a novel and accessible methodology to measure interface energy of nanoparticles exploiting the heat released during sintering to establish a quantitative relation between the solid solid and solid vapor interface energies. We exploited this method in MgO and ZnO nanoparticles and determined that the ratio between the solid solid and solid vapor interface energy is 11 for MgO and 0.7 for ZnO. We then discuss that this ratio is responsible for a thermodynamic metastable state that may prevent collapsing of nanoparticles and, therefore, may be used as a tool to design long-term stable nanoparticles.

Interface excess and polymorphic stability of nanosized zirconia-magnesia

Controlling the phase stability of ZrO2 nanoparticles is of major importance in the development of new ZrO2-based nanotechnologies. Because of the fact that in nanoparticles the surface accounts for a larger fraction of the total atoms, the relative phase stability can be controlled throughout the surface composition, which can be toned by surface excess of one of the components of the system., The objective of this work is to delineate a relationship between surface excess (or solid solution) of MgO relative to ZrO2 and the polymorphic stability of (ZrO2)(1-x) - (MgO), nanopowders, where 0.0 <= x <= 0.6. The nanopowders were prepared by a liquid precursor method at 500 degrees C and characterized by N-2 adsorption (BET), X-ray diffraction (XRD), X-Ray photoelectron spectroscopy (XPS), and Raman spectroscopy. For pure ZrO2 samples, both tetragonal and monoclinic polymorphs were detected, as expected considering the literature. For MgO molar fractions varying from 0.05 to 0.10, extensive solid solution could not be detected, and a ZrO2 surface energy reduction, caused by Mg surface excess detected by XPS, promoted tetragonal polymorph thermodynamic stabilization with relation to monoclinic. For MgO molar fractions higher than 0.10 and up to 0.40, Mg solid solution could be detected and induced cubic phase stabilization. MgO periclase was observed only at x = 0.6. A discussion based on the relationship between the surface excess, surface energy, and polymorph stability is presented.

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.

Construction and Evaluation of an Opto-Coupled Potentiostat with a PC/PDA Interface

The design, construction, and characterization of a portable opto-coupled potentiostat are presented. The potentiostat is battery-powered, managed by a microcontroller, which implements cyclic voltammetry (CV) using suitable sensor electrodes. Its opto-coupling permits a wide range of current measurements, varying from mA to nA. Two software interfaces were developed to perform the CV measurement: a virtual instrument for a personal computer (PC) and a C-base interface for personal digital assistant (PDA). The potentiostat has been evaluated by detection of potassium ferrocyanide in KCl medium, both with macro and microelectrodes. There was good agreement between the instrumental results and those from commercial equipment.

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.

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.

The BCD transient recorder revisited: firmware for the ISA-to-USB bridging card and software for the graphical user interface

This report describes recent updates to the custom-built data-acquisition hardware operated by the Center for Hypersonics. In 2006, an ISA-to-USB bridging card was developed as part of Luke Hillyard's final-year thesis. This card allows the hardware to be connected to any recent personal computers via a (USB or RS232) serial port and it provides a number of simple text-based commands for control of the hardware. A graphical user interface program was also updated to help the experimenter manage the data acquisition functions. Sampled data is stored in text files that have been compressed with the gzip for mat. To simplify the later archiving or transport of the data, all files specific to a shot are stored in a single directory. This includes a text file for the run description, the signal configuration file and the individual sampled-data files, one for each signal that was recorded.

When oceans meet: a teleost shows secondary intergradation at an Indian-Pacific interface

The Indo-West Pacific is characterized by extraordinary marine species diversity. The evolutionary mechanisms responsible for generating this diversity remain puzzling, but are often linked to Pleistocene sea level fluctuations. The impact of these sea level changes on the population genetic architecture of the estuarine fish Lates calcarifer are investigated via a natural experiment in a region of the Indo-West Pacific known to have undergone considerable change during the Pleistocene. L. calcarifer, a coastline-restricted catadromous teleost, provides an excellent model for studying the effects of sea level change as its habitat requirements potentially make it sensitive to the region's physical history. Evidence was found for a large phylogenetic break (4% mtDNA control region; 0.47% ATPase 6 and 8) either side of the Torres Strait, which separates the Western Pacific and Indian Oceans, although some mixing of the clades was evident. This suggests clinal secondary introgression of the clades via contemporary gene flow. Further, populations on Australia's east coast appear to have passed through a bottleneck. This was linked to the historical drying of the Great Barrier Reef coastal lagoon, which resulted in a significant loss of habitat and forced retreat into isolated refugia. These results suggest that historical eustatic changes have left a significant imprint on the molecular diversity within marine species as well as among them in the Indo-West Pacific.