Hydraulic Behavior of Mechanically and Chemically Activated Synthetic Merwinite

The hydraulic behavior of synthetic merwinite was investigated after activation by two different methods, aiming to enhance its hydraulic activity which is weak in water. Mechanical activation, by means of extensive milling in a bead mill, led to amorphization of merwinite and a decrease in its crystallite size. The combined effect of higher specific surface area and of structural disorder resulted in a notable increase of hydraulic reactivity. The hydraulic reactivity was substantially more pronounced with chemical activation compared to mechanical activation. Crystalline and amorphous C‐S‐H and brucite were the main hydration products formed in the hydrated, mechanically activated merwinite, whereas portlandite precipitated additionally in the case of chemical activation. Spectroscopic analyses of FTIR and ²⁹Si MAS NMR verified the C‐S‐H formation. TEM investigations revealed formation of Mg‐low C‐S‐H gel around the merwinite particles. Both mechanically and chemically activated merwinite systems were capable of developing mechanical strength.     

Effects of Errors in the Viewing Geometry on Shape Estimation

A sequence of images acquired by a moving sensor contains information about the three-dimensional motion of the sensor and the shape of the imaged scene. Interesting research during the past few years has attempted to characterize the errors that arise in computing 3D motion (egomotion estimation) as well as the errors that result in the estimation of the scene's structure (structure from motion). Previous research is characterized by the use of optic flow or correspondence of features in the analysis as well as by the employment of particular algorithms and models of the scene in recovering expressions for the resulting errors. This paper presents a geometric framework that characterizes the relationship between 3D motion and shape in the presence of errors. We examine how the three-dimensional space recovered by a moving monocular observer, whose 3D motion is estimated with some error, is distorted. We characterize the space of distortions by its level sets, that is, we characterize the systematic distortion via a family of iso-distortion surfaces, which describes the locus over which the depths of points in the scene in view are distorted by the same multiplicative factor. The framework introduced in this way has a number of applications: Since the visible surfaces have positive depth (visibility constraint), by analyzing the geometry of the regions where the distortion factor is negative, that is, where the visibility constraint is violated, we make explicit situations which are likely to give rise to ambiguities in motion estimation, independent of the algorithm used. We provide a uniqueness analysis for 3D motion analysis from normal flow. We study the constraints on egomotion, object motion, and depth for an independently moving object to be detectable by a moving observer, and we offer a quantitative account of the precision needed in an inertial sensor for accurate estimation of 3D motion.     

Domain decomposition methods for parallel solution of shape sensitivity analysis problems

This paper presents the implementation of advanced domain decomposition techniques for parallel solution of large‐scale shape sensitivity analysis problems. The methods presented in this study are based on the FETI method proposed by Farhat and Roux which is a dual domain decomposition implementation. Two variants of the basic FETI method have been implemented in this study: (i) FETI‐1 where the rigid‐body modes of the floating subdomains are computed explicitly. (ii) FETI‐2 where the local problem at each subdomain is solved by the PCG method and the rigid‐body modes are computed explicitly. A two‐level iterative method is proposed particularly tailored to solve re‐analysis type of problems, where the dual domain decomposition method is incorporated in the preconditioning step of a subdomain global PCG implementation. The superiority of this two‐level iterative solver is demonstrated with a number of numerical tests in serial as well as in parallel computing environments. Copyright © 1999 John Wiley & Sons, Ltd.     

Force/position tracking for a robotic manipulator in compliant contact with a surface using neuro-adaptive control

The problem of force/position tracking for a robotic manipulator in compliant contact with a surface under non-parametric uncertainties is considered. In particular, structural uncertainties are assumed to characterize the compliance and surface friction models, as well as the robot dynamic model. A novel neuro-adaptive controller is proposed, that exploits the approximation capabilities of the linear in the weights neural networks, guaranteeing the uniform ultimate boundedness of force and position error with respect to arbitrarily small sets, plus the boundedness of all signals in the closed loop. Simulations highlight the approach.     

Using economically designed Shewhart and adaptive ―X charts for monitoring the quality of tiles

This paper presents the economic design of ―X control charts for monitoring a critical stage of the main production process at a tile manufacturer in Greece. Two types of ―X charts were developed: a Shewhart‐type chart with fixed parameters and adaptive charts with variable sampling intervals and/or sample size. Our prime motivation was to improve the statistical control scheme employed for monitoring an important quality characteristic of the process with the objective of minimizing the relevant costs. At the same time we tested and confirmed the applicability of the theoretical models supporting the economic design of control charts with fixed and variable parameters in a practical situation. We also evaluated the economic benefits of moving from the broadly used static charts to the application of the more flexible and effective adaptive control charts. The main result of our study is that, by redesigning the currently employed Shewhart chart using economic criteria, the quality‐related cost is expected to decrease by approximately 50% without increasing the implementation complexity. Monitoring the process by means of an adaptive ―X chart with variable sampling intervals will increase the expected cost savings by about 10% compared with the economically designed Shewhart chart at the expense of some implementation difficulty. Copyright © 2006 John Wiley & Sons, Ltd.     

Fullerene C60 Supported on Silica and γ-Alumina Catalyzed Photooxidations of Alkenes

Deposition of fullerene C₆₀ (2% w/w) on silica and -alumina provokes a two orders-of-magnitude increase of its activity for the liquid-phase photooxidation of 2-methyl-2-heptene. Kinetic studies concerning the above photooxidation showed a first-order dependence of the reaction rate on the alkene concentration. The corresponding reaction-rate constant was found to be higher in the case where -alumina was used as carrier. The nature of the carrier does not influence the mechanism and the selectivity of the reaction. High dispersion of the supported fullerene is achieved on the surface of the carriers, which increase the fullerene light absorbance especially in the visible range.     

Simulation of multiple etch fronts

We developed a series of algorithms, based on the string model, that simulate the inhomogeneous etching process of polymeric materials, which exhibit swelling during dissolution by an organic solvent, used in IC process fabrication. The swelling creates a gel layer between the solid (polymer) and the liquid (solvent) phases. Usually, simulations based on the string development model assume an abrupt solid-liquid interface. Our algorithms are capable of simulating two interrelated etch fronts, and may easily be extended to simulate n interrelated etch fronts. The speed with which the points of the gel-solid boundary advance depends on the distance of each point from the gel-liquid boundary. Considering the two boundaries as plane curves, one must deal with the problem of what we define as the “distance” of every point of the first curve from the second. The algorithm developed can deal with any pair of non-intersecting curves in two dimensions. Two pairs of curves were used to test the algorithm: the first with curves of a simple form, and the second with curves of a complicated form. Next we simulated the development process of an e-beam resist that exhibits swelling. The results were perfect for the minimum distance subalgorithm, and they predicted a longer development time for the e-beam resist compared with that required for a non-swelling resist.     

Big data regression with parallel enhanced and convex incremental extreme learning machines

This work considers scalable incremental extreme learning machine (I‐ELM) algorithms, which could be suitable for big data regression. During the training of I‐ELMs, the hidden neurons are presented one by one, and the weights are based solely on simple direct summations, which can be most efficiently mapped on parallel environments. Existing incremental versions of ELMs are the I‐ELM, enhanced incremental ELM (EI‐ELM), and convex incremental ELM (CI‐ELM). We study the enhanced and convex incremental ELM (ECI‐ELM) algorithm, which is a combination of the last 2 versions. The main findings are that ECI‐ELM is fast, accurate, and fully scalable when it operates in a parallel system of distributed memory workstations. Experimental simulations on several benchmark data sets demonstrate that the ECI‐ELM is the most accurate among the existing I‐ELM, EI‐ELM, and CI‐ELM algorithms. We also analyze the convergence as a function of the hidden neurons and demonstrate that ECI‐ELM has the lowest error rate curve and converges much faster than the other algorithms in all of the data sets. The parallel simulations also reveal that the data parallel training of the ECI‐ELM can guarantee simplicity and straightforward mappings and can deliver speedups and scale‐ups very close to linear.