Shaking table tests of structures with hysteretic dampers: experimental results vs. prediction using non-linear static methods

The use of seismic hysteretic dampers for passive control is increasing exponentially in recent years for both new and existing buildings. In order to utilize hysteretic dampers within a structural system, it is of paramount importance to have simplified design procedures based upon knowledge gained from theoretical studies and validated with experimental results. Non-linear Static Procedures (NSPs) are presented as an alternative to the force-based methods more common nowadays. The application of NSPs to conventional structures has been well established; yet there is a lack of experimental information on how NSPs apply to systems with hysteretic dampers. In this research, several shaking table tests were conducted on two single bay and single story 1:2 scale structures with and without hysteretic dampers. The maximum response of the structure with dampers in terms of lateral displacement and base shear obtained from the tests was compared with the prediction provided by three well-known NSPs: (1) the improved version of the Capacity Spectrum Method (CSM) from FEMA 440; (2) the improved version of the Displacement Coefficient Method (DCM) from FEMA 440; and (3) the N2 Method implemented in Eurocode 8. In general, the improved version of the DCM and N2 methods are found to provide acceptable accuracy in prediction, but the CSM tends to underestimate the response.

A unified framework for linear function approximation of value functions in stochastic control

This paper contributes with a unified formulation that merges previ- ous analysis on the prediction of the performance ( value function ) of certain sequence of actions ( policy ) when an agent operates a Markov decision process with large state-space. When the states are represented by features and the value function is linearly approxi- mated, our analysis reveals a new relationship between two common cost functions used to obtain the optimal approximation. In addition, this analysis allows us to propose an efficient adaptive algorithm that provides an unbiased linear estimate. The performance of the pro- posed algorithm is illustrated by simulation, showing competitive results when compared with the state-of-the-art solutions.

Análise de acetona em ar exalado: desenvolvimento de método eletroanalítico e algoritmo para processamento de sinais

Propõe-se método novo e completo para análise de acetona em ar exalado envolvendo coleta com pré-concentração em água, derivatização química e determinação eletroquímica assistida por novo algoritmo de processamento de sinais. Na literatura recente a acetona expirada vem sendo avaliada como biomarcador para monitoramento não invasivo de quadros clínicos como diabetes e insuficiência cardíaca, daí a importância da proposta. Entre as aminas que reagem com acetona para formar iminas eletroativas, estudadas por polarografia em meados do século passado, a glicina apresentou melhor conjunto de características para a definição do método de determinação por voltametria de onda quadrada sem a necessidade de remoção de oxigênio (25 Hz, amplitude de 20 mV, incremento de 5 mV, eletrodo de gota de mercúrio). O meio reacional, composto de glicina (2 mol·L-1) em meio NaOH (1 mol·L-1), serviu também de eletrólito e o pico de redução da imina em -1,57 V vs. Ag|AgCl constituiu o sinal analítico. Para tratamento dos sinais, foi desenvolvido e avaliado um algoritmo inovador baseado em interpolação de linha base por ajuste de curvas de Bézier e ajuste de gaussiana ao pico. Essa combinação permitiu reconhecimento e quantificação de picos relativamente baixos e largos sobre linha com curvatura acentuada e ruído, situação em que métodos convencionais falham e curvas do tipo spline se mostraram menos apropriadas. A implementação do algoritmo (disponível em http://github.com/batistagl/chemapps) foi realizada utilizando programa open source de álgebra matricial integrado diretamente com software de controle do potenciostato. Para demonstrar a generalidade da extensão dos recursos nativos do equipamento mediante integração com programação externa em linguagem Octave (open source), implementou-se a técnica da cronocoulometria tridimensional, com visualização de resultados já tratados em projeções de malha de perspectiva 3D sob qualquer ângulo. A determinação eletroquímica de acetona em fase aquosa, assistida pelo algoritmo baseado em curvas de Bézier, é rápida e automática, tem limite de detecção de 3,5·10-6 mol·L-1 (0,2 mg·L-1) e faixa linear que atende aos requisitos da análise em ar exalado. O acetaldeído, comumente presente em ar exalado, em especial, após consumo de bebidas alcoólicas, dá origem a pico voltamétrico em -1,40 V, contornando interferência que prejudica vários outros métodos publicados na literatura e abrindo possibilidade de determinação simultânea. Resultados obtidos com amostras reais são concordantes com os obtidos por método espectrofotométrico, em uso rotineiro desde o seu aperfeiçoamento na dissertação de mestrado do autor desta tese. Em relação à dissertação, também se otimizou a geometria do dispositivo de coleta, de modo a concentrar a acetona num volume menor de água gelada e prover maior conforto ao paciente. O método completo apresentado, englobando o dispositivo de amostragem aperfeiçoado e o novo e efetivo algoritmo para tratamento automático de sinais voltamétricos, está pronto para ser aplicado. Evolução para um analisador portátil depende de melhorias no limite de detecção e facilidade de obtenção eletrodos sólidos (impressos) com filme de mercúrio, vez que eletrodos de bismuto ou diamante dopado com boro, entre outros, não apresentaram resposta.

Krylov subspace methods for solving large unsymmetric linear systems /

"COO-2383-0077"--P. 1 of cover.

Efficient Bayesian inference for learning in the Ising linear perceptron and signal detection in CDMA

Efficient new Bayesian inference technique is employed for studying critical properties of the Ising linear perceptron and for signal detection in code division multiple access (CDMA). The approach is based on a recently introduced message passing technique for densely connected systems. Here we study both critical and non-critical regimes. Results obtained in the non-critical regime give rise to a highly efficient signal detection algorithm in the context of CDMA; while in the critical regime one observes a first-order transition line that ends in a continuous phase transition point. Finite size effects are also studied. © 2006 Elsevier B.V. All rights reserved.

Statnote 20: non-linear regression: fitting a general polynomial curve

In some circumstances, there may be no scientific model of the relationship between X and Y that can be specified in advance and indeed the objective of the investigation may be to provide a ‘curve of best fit’ for predictive purposes. In such an example, the fitting of successive polynomials may be the best approach. There are various strategies to decide on the polynomial of best fit depending on the objectives of the investigation.

Data methods in optometry. Part 6: fitting a regression line to data

1. Fitting a linear regression to data provides much more information about the relationship between two variables than a simple correlation test. A goodness of fit test of the line should always be carried out. Hence, r squared estimates the strength of the relationship between Y and X, ANOVA whether a statistically significant line is present, and the ‘t’ test whether the slope of the line is significantly different from zero. 2. Always check whether the data collected fit the assumptions for regression analysis and, if not, whether a transformation of the Y and/or X variables is necessary. 3. If the regression line is to be used for prediction, it is important to determine whether the prediction involves an individual y value or a mean. Care should be taken if predictions are made close to the extremities of the data and are subject to considerable error if x falls beyond the range of the data. Multiple predictions require correction of the P values. 3. If several individual regression lines have been calculated from a number of similar sets of data, consider whether they should be combined to form a single regression line. 4. If the data exhibit a degree of curvature, then fitting a higher-order polynomial curve may provide a better fit than a straight line. In this case, a test of whether the data depart significantly from a linear regression should be carried out.

LIPPRED:a web server for accurate prediction of lipoprotein signal sequences and cleavage sites

Bacterial lipoproteins have many important functions and represent a class of possible vaccine candidates. The prediction of lipoproteins from sequence is thus an important task for computational vaccinology. Naïve-Bayesian networks were trained to identify SpaseII cleavage sites and their preceding signal sequences using a set of 199 distinct lipoprotein sequences. A comprehensive range of sequence models was used to identify the best model for lipoprotein signal sequences. The best performing sequence model was found to be 10-residues in length, including the conserved cysteine lipid attachment site and the nine residues prior to it. The sensitivity of prediction for LipPred was 0.979, while the specificity was 0.742. Here, we describe LipPred, a web server for lipoprotein prediction; available at the URL: http://www.jenner.ac.uk/LipPred/. LipPred is the most accurate method available for the detection of SpaseIIcleaved lipoprotein signal sequences and the prediction of their cleavage sites.

Nonlinear signal transformations:path to capacity above the linear AWGN Shannon limit

We present a methodology for simultaneous optimization of modulation format and regenerative transformations in nonlinear communication channels. We derived analytically the maximum regenerative Shannon capacity, towards which any regenerative channel tends at high SNR and large number of regenerators.

Two-Path All-pass Based Half-Band Infinite Impulse Response Decimation Filters and the Effects of Their Non-Linear Phase Response on ECG Signal Acquisition

This paper is based on the novel use of a very high fidelity decimation filter chain for Electrocardiogram (ECG) signal acquisition and data conversion. The multiplier-free and multi-stage structure of the proposed filters lower the power dissipation while minimizing the circuit area which are crucial design constraints to the wireless noninvasive wearable health monitoring products due to the scarce operational resources in their electronic implementation. The decimation ratio of the presented filter is 128, working in tandem with a 1-bit 3rd order Sigma Delta (ΣΔ) modulator which achieves 0.04 dB passband ripples and -74 dB stopband attenuation. The work reported here investigates the non-linear phase effects of the proposed decimation filters on the ECG signal by carrying out a comparative study after phase correction. It concludes that the enhanced phase linearity is not crucial for ECG acquisition and data conversion applications since the signal distortion of the acquired signal, due to phase non-linearity, is insignificant for both original and phase compensated filters. To the best of the authors’ knowledge, being free of signal distortion is essential as this might lead to misdiagnosis as stated in the state of the art. This article demonstrates that with their minimal power consumption and minimal signal distortion features, the proposed decimation filters can effectively be employed in biosignal data processing units.

Data-Driven Dynamic Prediction of Interrelated Heat and Electric Outputs of Microturbines

Microturbines are among the most successfully commercialized distributed energy resources, especially when they are used for combined heat and power generation. However, the interrelated thermal and electrical system dynamic behaviors have not been fully investigated. This is technically challenging due to the complex thermo-fluid-mechanical energy conversion processes which introduce multiple time-scale dynamics and strong nonlinearity into the analysis. To tackle this problem, this paper proposes a simplified model which can predict the coupled thermal and electric output dynamics of microturbines. Considering the time-scale difference of various dynamic processes occuring within microturbines, the electromechanical subsystem is treated as a fast quasi-linear process while the thermo-mechanical subsystem is treated as a slow process with high nonlinearity. A three-stage subspace identification method is utilized to capture the dominant dynamics and predict the electric power output. For the thermo-mechanical process, a radial basis function model trained by the particle swarm optimization method is employed to handle the strong nonlinear characteristics. Experimental tests on a Capstone C30 microturbine show that the proposed modeling method can well capture the system dynamics and produce a good prediction of the coupled thermal and electric outputs in various operating modes.

Prediction and improved estimation in linear models /

Includes index.