Stability and convergence analysis of transform-domain LMS adaptive filters with second-order autoregressive process

In this paper, the stability and convergence properties of the class of transform-domain least mean square (LMS) adaptive filters with second-order autoregressive (AR) process are investigated. It is well known that this class of adaptive filters improve convergence property of the standard LMS adaptive filters by applying the fixed data-independent orthogonal transforms and power normalization. However, the convergence performance of this class of adaptive filters can be quite different for various input processes, and it has not been fully explored. In this paper, we first discuss the mean-square stability and steady-state performance of this class of adaptive filters. We then analyze the effects of the transforms and power normalization performed in the various adaptive filters for both first-order and second-order AR processes. We derive the input asymptotic eigenvalue distributions and make comparisons on their convergence performance. Finally, computer simulations on AR process as well as moving-average (MA) process and autoregressive-moving-average (ARMA) process are demonstrated for the support of the analytical results.

Experimental and numerical analysis of the deformed process of cracks/cavities

In this paper, the three-point bending tests of beams with a small single-edge crack are conducted to demonstrate the reliability and accuracy of the laser diffraction technique in detecting its deformation and evolution. As a comparison, the quasi-static analysis of the beam subjected to 3-point bending is further proceeded using the finite element method and the related results have been in good agreement with those from the tests.

Determination of sodium oxalate in Bayer process liquors using flow analysis with tris(2,2'-bipyridyl)ruthenium(II) chemiluminescence detection

The research was a detailed investigation into a challenging analytical chemistry problem for the alumina industry. The successful outcomes were derived through innovative reagent chemistry and novel instrumental development. The resultant methodology and instrumentation deployed on this most demanding sample matrix is more robust, reliable and less expensive than anything currently used in this industry worldwide.

Functional analysis of the leading malaria vaccine candidate AMA-1 reveals an essential role for the cytoplasmic domain in the invasion process

A key process in the lifecycle of the malaria parasite Plasmodium falciparum is the fast invasion of human erythrocytes. Entry into the host cell requires the apical membrane antigen 1 (AMA-1), a type I transmembrane protein located in the micronemes of the merozoite. Although AMA-1 is evolving into the leading blood-stage malaria vaccine candidate, its precise role in invasion is still unclear. We investigate AMA-1 function using live video microscopy in the absence and presence of an AMA-1 inhibitory peptide. This data reveals a crucial function of AMA-1 during the primary contact period upstream of the entry process at around the time of moving junction formation. We generate a Plasmodium falciparum cell line that expresses a functional GFP-tagged AMA-1. This allows the visualization of the dynamics of AMA-1 in live parasites. We functionally validate the ectopically expressed AMA-1 by establishing a complementation assay based on strain-specific inhibition. This method provides the basis for the functional analysis of essential genes that are refractory to any genetic manipulation. Using the complementation assay, we show that the cytoplasmic domain of AMA-1 is not required for correct trafficking and surface translocation but is essential for AMA-1 function. Although this function can be mimicked by the highly conserved cytoplasmic domains of P. vivax and P. berghei, the exchange with the heterologous domain of the microneme protein EBA-175 or the rhoptry protein Rh2b leads to a loss of function. We identify several residues in the cytoplasmic tail that are essential for AMA-1 function. We validate this data using additional transgenic parasite lines expressing AMA-1 mutants with TY1 epitopes. We show that the cytoplasmic domain of AMA-1 is phosphorylated. Mutational analysis suggests an important role for the phosphorylation in the invasion process, which might translate into novel therapeutic strategies.

Numerical modeling and analysis for forming process of dual-phase 980 steel exposed to infrared local heating

A recent experiment confirmed that the infrared (IR) local heating method drastically reduces springback of dual-phase (DP) 980 sheets. In the experiment, only the plastic deformation zone of the sheets was locally heated using condensed IR heating. The heated sheets were then deformed by V-bending or 2D-draw bending. Although the experimental observation proved the merit of using the IR local heating to reduce springback, numerical modeling has not been reported. Numerical modeling has been required to predict springback and improve the understanding of the forming process. This paper presents a numerical modeling for V-bending and 2D-draw bending of DP 980 sheets exposed to the IR local heating with the finite element method (FEM). For describing the thermo-mechanical behavior of the DP 980 sheet, a flow stress model which includes a function of temperature and effective plastic strain was newly implemented into Euler-backward stress integration method. The numerical analysis shows that the IR local heating reduces the level of stress in the deformation zone, although it heats only the limited areas, and then it reduces the springback. The simulation also provides a support that the local heating method has an advantage of shape accuracy over the method to heat the material as a whole in V-bending. The simulated results of the springback in both V-bending and 2D-draw bending also show good predictions.

Systematic approach to the quantitative voltammetric analysis of the Fe III /Fe II component of the [α 2 -Fe(OH 2 )P 2 W 17 O 61 ] 7-/8- reduction process in buffered and unbuffered aqueous media

The one-electron reduction of [α2-FeIII(OH2)P2W17O61]7- at a glassy carbon electrode was investigated using cyclic and rotating-disk-electrode voltammetry in buffered and unbuffered aqueous solutions over the pH range 3.45−7.50 with an ionic strength of approximately 0.6 M maintained. The behavior is well-described by a square-scheme mechanism P + e- ↔ Q (E10/ = −0.275 V, k10/ = 0.008 cm s-1, and α1 = 1/2), PH+ + e- ↔ QH+ (E20/ = −0.036 V, k20/ = 0.014 cm s-1, and α2 = 1/2), PH+ ↔ P + H+ (KP = 3.02 × 10-6 M), and QH+ ↔ Q + H+ (KQ = 2.35 × 10-10 M), where P, Q, PH+, and QH+ correspond to [α2-FeIII(OH)P2W17O61]8-, [α2-FeII(OH)P2W17O61]9-, [α2-FeIII(OH2)P2W17O61]7-, and [α2-FeII(OH2)P2W17O61]8-, respectively; E10‘ and E20‘ are the formal potentials, k10‘ and k20‘ are the formal (standard) rate constants, and KP and KQ are the acid dissociation constants for the relevant reactions. The analysis for the buffered media is based on the approach of Laviron who demonstrated that a square scheme with fully reversible protonations, reversible or quasi reversible electron transfers with the assumption that α1 = α2, can be well-described by the behavior of a simple redox couple, ox + e- ↔ red, whose formal potential, Eapp0‘, and standard rate constant, kapp0‘, are straightforwardly derived functions of pH, as are the values of E10‘, k10‘, E20‘, k20‘, and KP (only three of the four thermodynamic parameters in a square scheme can be specified). It was assumed that αapp = 1/2, and the simulation program DigiSim was used to determine the values of Eapp0‘ and kapp0‘, which are required to describe the cyclic voltammograms obtained in buffered media in the pH range from 3.45 to 7.52 (buffer-related reactions which effect general acid−base catalysis are included in the simulations). DigiSim simulations of cyclic voltammograms obtained in unbuffered media yielded the values of E10‘ and k10‘; KQ was then directly computed from thermodynamic constraints. These simulations included additional reactions between the redox species and H2O. The value of the diffusion coefficient of the [α2-FeIII(OH2)P2W17O61]7-, 2.92 × 10-6 cm2 s-1, was determined using DigiSim simulations of voltammograms at a rotating disk electrode in buffered and unbuffered media at pH 3.45. The diffusion coefficients of all redox species were assumed to be identical. When the pH is greater than 6, instability of P (i.e., [α2-FeIII(OH)P2W17O61]8-) led to the loss of the reactant and precluded lengthy experimentation.

A note on multivariate non-normal process capability analysis using "mvtnorm" library in R

In this note we examine using Genzbretz and Miwa algorithms to improve estimation of proposition of non-conformance in multivariate normal distributions. This estimation is required in the procedure outlined in Abbasi and Niaki (Int J Adv Manuf Technol 50(5-8):823-830, 2010) to determine process capability index of multivariate non-normal processes.

Process capability analysis in non normal linear regression profiles

When the distribution of a process characterized by a profile is non normal, process capability analysis using normal assumption often leads to erroneous interpretations of the process performance. Profile monitoring is a relatively new set of techniques in quality control that is used in situations where the state of product or process is represented by a function of two or more quality characteristics. Such profiles can be modeled using linear or nonlinear regression models. In some applications, it is assumed that the quality characteristics follow a normal distribution; however, in certain applications this assumption may fail to hold and may yield misleading results. In this article, we consider process capability analysis of non normal linear profiles. We investigate and compare five methods to estimate non normal process capability index (PCI) in profiles. In three of the methods, an estimation of the cumulative distribution function (cdf) of the process is required to analyze process capability in profiles. In order to estimate cdf of the process, we use a Burr XII distribution as well as empirical distributions. However, the resulted PCI with estimating cdf of the process is sometimes far from its true value. So, here we apply artificial neural network with supervised learning which allows the estimation of PCIs in profiles without the need to estimate cdf of the process. Box-Cox transformation technique is also developed to deal with non normal situations. Finally, a comparison study is performed through the simulation of Gamma, Weibull, Lognormal, Beta and student-t data.

Evaluation of deterministic and complex analytical hierarchy process methods for agricultural land suitability analysis in a changing climate

Land suitability analysis is employed to evaluate the appropriateness of land for a particular purpose whilst integrating both qualitative and quantitative inputs, which can be continuous in nature. However, in agricultural modelling there is often a disregard of this contiguous aspect. Therefore, some parametric procedures for suitability analysis compartmentalise units into defined membership classes. This imposition of crisp boundaries neglects the continuous formations found throughout nature and overlooks differences and inherent uncertainties found in the modelling. This research will compare two approaches to suitability analysis over three differing methods. The primary approach will use an Analytical Hierarchy Process (AHP), while the other approach will use a Fuzzy AHP over two methods; Fitted Fuzzy AHP and Nested Fuzzy AHP. Secondary to this, each method will be assessed into how it behaves in a climate change scenario to understand and highlight the role of uncertainties in model conceptualisation and structure. Outputs and comparisons between each method, in relation to area, proportion of membership classes and spatial representation, showed that fuzzy modelling techniques detailed a more robust and continuous output. In particular the Nested Fuzzy AHP was concluded to be more pertinent, as it incorporated complex modelling techniques, as well as the initial AHP framework. Through this comparison and assessment of model behaviour, an evaluation of each methods predictive capacity and relevance for decision-making purposes in agricultural applications is gained.