Crack growth retardation following the application of an overload cycle using a strip-yield model

Experiments have shown that the application of an overload cycle can act to retard crack growth and even potentially lead to crack arrest. This paper describes a new method for investigating fatigue crack growth after the application of an overload cycle under plane stress conditions. The developed method is based on the concept of plasticity-induced crack closure and utilises the distributed dislocation technique and a modified strip-yield model. The present results are compared to previous experimental data for several materials. A good agreement is found, with the predictions showing the same trends in the various stages of post-overload crack growth.     

Effective harvesting,detection, and conversion of IR radiation due to quantum dots with built-in charge

We analyze the effect of doping on photoelectron kinetics in quantum dot [QD] structures and find two strong effects of the built-in-dot charge. First, the built-in-dot charge enhances the infrared [IR] transitions in QD structures. This effect significantly increases electron coupling to IR radiation and improves harvesting of the IR power in QD solar cells. Second, the built-in charge creates potential barriers around dots, and these barriers strongly suppress capture processes for photocarriers of the same sign as the built-in-dot charge. The second effect exponentially increases the photoelectron lifetime in unipolar devices, such as IR photodetectors. In bipolar devices, such as solar cells, the solar radiation creates the built-in-dot charge that equates the electron and hole capture rates. By providing additional charge to QDs, the appropriate doping can significantly suppress the capture and recombination processes via QDs. These improvements of IR absorption and photocarrier kinetics radically increase the responsivity of IR photodetectors and photovoltaic efficiency of QD solar cells.     

Parameters of cache systems based on a Zipf-like distribution

The object of this paper is to explain a system of Internet traffic caching. The task is to create an analytical model of a cache system linking its size with other parameters by boundary conditions. A definition of a dynamic cache model is introduced. The parameters of a cache system are calculated using the Zipf's first law and Zipf-like distribution. The correspondence between size of a cache system and aggregated bandwidth of external links is derived.     

High-speed,high-sensitivity,gated surface profiling with closed-loop optical coherence topography

We describe and experimentally demonstrate a novel (to our knowledge) surface profiling technique, for which we propose the term closed-loop optical coherence topography. This technique is a scanning beam, servo-locked variation of low-coherence interferometry. It allows for the sub-wavelength-resolution tracking of a weakly scattering macroscopic-scale surface, with the surface profile being directly output by the controlling electronics. The absence of significant real-time computational overhead makes the technique well suited to high-speed tracking. The use of a micrometer-scale coherence gate efficiently suppresses signals arising from structures not associated with the surface. These features make the technique particularly well suited to real-time surface profiling of in vivo, macroscopic biological surfaces.     

Incremental construction of minimal deterministic finite cover automata

We present a fast incremental algorithm for constructing minimal Deterministic Finite Cover Automata (DFCA) for a given language. Since it was shown that the minimal DFCA for a language L has less states than the minimal Deterministic Finite Automata (DFA) for the same language L, this technique seems to be the best choice for incrementally building the automaton for a large language, especially when the number of states in the DFCA is significantly less than the number of states in the corresponding minimal DFA. We have implemented the proposed algorithm and have tested it against the best-known DFCA minimization technique.     

Automatic diatom identification using contour analysis by morphological curvature scale spaces

A method for automatic identification of diatoms (single-celled algae with silica shells) based on extraction of features on the contour of the cells by multi-scale mathematical morphology is presented. After extracting the contour of the cell, it is smoothed adaptively, encoded using Freeman chain code, and converted into a curvature representation which is invariant under translation and scale change. A curvature scale space is built from these data, and the most important features are extracted from it by unsupervised cluster analysis. The resulting pattern vectors, which are also rotation-invariant, provide the input for automatic identification of diatoms by decision trees and k-nearest neighbor classifiers. The method is tested on two large sets of diatom images. The techniques used are applicable to other shapes besides diatoms. Andrei C. Jalba received his B.Sc. (1998) and M.Sc. (1999) in Applied Electronics and Information Engineering from “Politehnica” University of Bucharest, Romania. He recently obtained a Ph.D. degree at the Institute for Mathematics and Computing Science of the University of Groningen, where he now is a postdoctoral researcher. His research interests include computer vision, pattern recognition, image processing, and parallel computing. Michael Wilkinson obtained an M.Sc. in astronomy from the Kapteyn Laboratory, University of Groningen (RuG) in 1993, after which he worked on image analysis of intestinal bacteria at the Department of Medical Microbiology, RuG. This work formed the basis of his Ph.D. at the Institute of Mathematics and Computing Science (IWI), RuG, in 1995. He was appointed as researcher at the Centre for High Performance Computing (also RuG) working on simulating the intestinal microbial ecosystem on parallel computers. During that time he edited the book “Digital Image Analysis of Microbes” (John Wiley, UK, 1998) together with Frits Schut. After this he worked as a researcher at the IWI on image analysis of diatoms. He is currently assistant professor at the IWI. Jos B.T.M. Roerdink received his M.Sc. (1979) in theoretical physics from the University of Nijmegen, the Netherlands. Following his Ph.D. (1983) from the University of Utrecht and a 2-year position (1983--1985) as a Postdoctoral Fellow at the University of California, San Diego, both in the area of stochastic processes, he joined the Centre for Mathematics and Computer Science in Amsterdam. There he worked from 1986-1992 on image processing and tomographic reconstruction. He was appointed associate professor (1992) and full professor (2003), respectively, at the Institute for Mathematics and Computing Science of the University of Groningen, where he currently holds a chair in Scientific Visualization and Computer Graphics. His current research interests include biomedical visualization, neuroimaging and bioinformatics. Micha Bayer graduated from St. Andrews University, Scotland, with an M.Sc. in Marine Biology in 1994. He obtained his Ph.D. in Marine Biology from there in 1998, and then followed this up with two postdoctoral positions at the Royal Botanic Garden Edinburgh, Scotland, first on the ADIAC and then on the DIADIST project. In both of these projects he was responsible for establishing the collections of diatom training data to be used for the pattern recognition systems. From 2002–2003 he was enrolled for an M.Sc. in information technology at the University of Glasgow, Scotland, and is now working as a grid developer at the National e-Science Centre at Glasgow University. Stephen Juggins is a senior lecturer at the School of Geography, Politics and Sociology, University of Newcastle. His research focuses on the use of diatoms for monitoring environmental change and on the analysis of ecological and palaeoecological data. He has worked in Europe, North America and Central Asia on problems of river water quality, historical lake acidification, coastal eutrophication and Quaternary climate change.     

The power of communication: P systems with symport/antiport

In the attempt to have a framework where the computation is done by communication only, we consider the biological phenomenon of trans-membrane transport of couples of chemicals (one say symport when two chemicals pass together through a membrane, in the same direction, and antiport when two chemicals pass simultaneously through a membrane, in opposite directions). Surprisingly enough, membrane systems without changing (evolving) the used objects and with the communication based on rules of this type are computationally complete, and this result is achieved even for pairs of communicated objects (as encountered in biology). Five membranes are used; the number of membranes is reduced to two if more than two chemicals may collaborate when passing through membranes. Andrei Paun: He graduated the Faculty of Mathematics of Bucharest University in 1998, received his M.Sc. degree from The University of Western Ontario in 1999, and since then he is a PhD student in the Computer Science Department of University of Western Ontario, London, Canada (under the guidance of prof. Sheng Yu). The topic of his thesis is Molecular Computing (especially, DNA and Membrane Computing), but his research interests also include neural networks, implementing automata, combinatorics on words. Gheorghe Paun: (the proud father of two sons, including the first author of this paper) He is a member of the Romanian Academy, working as a senior researcher in the Institute of Mathematics of the Romanian Academy, Bucharest, and as a Ramon y Cajal researcher in Rovira i Virgili University of Tarragona, Spain. He is one of the most active authors in (the theory of) DNA Computing, (co)author of many papers in this area, (co)author and (co)editor of several books. In 1998 he has initiated the area of Membrane Computing. Other research interests: regulated rewriting, grammar systems, contextual grammars, combinatorics on words, computational linguistics.     

Nonlinear elasticity imaging: theory and phantom study

In tissue the Young's modulus cannot be assumed constant over a wide deformation range. For example, direct mechanical measurements on human prostate show up to a threefold increase in Young's modulus over a 10% deformation. In conventional elasticity imaging, these effects produce strain-dependent elastic contrast. Ignoring these effects generally leads to suboptimal contrast (stiffer tissues at lower strain are contrasted against softer tissues at higher strain), but measuring the nonlinear behavior results in enhanced tissue differentiation. To demonstrate the methods extracting nonlinear elastic properties, both simulations and measurements were performed on an agar-gelatin phantom. Multiple frames of phase-sensitive ultrasound data are acquired as the phantom is deformed by 12%. All interframe displacement data are brought back to the geometry of the first frame to form a three-dimensional (3-D) data set (depth, lateral, and preload dimensions). Data are fit to a 3-D second order polynomial model for each pixel that adjusts for deformation irregularities. For the phantom geometry and elastic properties considered in this paper, reconstructed frame-to-frame strain images using this model result in improved contrast to noise ratios (CNR) at all preload levels, without any sacrifice in spatial resolution. From the same model, strain hardening at all preload levels can be extracted. This is an independent contrast mechanism. Its maximum CNR occurs at 5.13% preload, and it is a 54% improvement over the best case (preload 10.6%) CNR for frame-to-frame strain reconstruction. Actual phantom measurements confirm the essential features of the simulation. Results show that modeling of the nonlinear elastic behavior has the potential to both increase detectability in elasticity imaging and provide a new independent mechanism for tissue differentiation.     

CPM: a deformable model for shape recovery and segmentation based on charged particles

A novel, physically motivated deformable model for shape recovery and segmentation is presented. The model, referred to as the charged-particle model (CPM), is inspired by classical electrodynamics and is based on a simulation of charged particles moving in an electrostatic field. The charges are attracted towards the contours of the objects of interest by an electrostatic field, whose sources are computed based on the gradient-magnitude image. The electric field plays the same role as the potential forces in the snake model, while internal interactions are modeled by repulsive Coulomb forces. We demonstrate the flexibility and potential of the model in a wide variety of settings: shape recovery using manual initialization, automatic segmentation, and skeleton computation. We perform a comparative analysis of the proposed model with the active contour model and show that specific problems of the latter are surmounted by our model. The model is easily extendable to 3D and copes well with noisy images.     

Effects of interface roughness on the spectral properties of thin films and multilayers

We introduce two parameters, large-scale and small-scale rms roughness, to take into account the interface properties of thin films and multilayers in the calculation of their specular reflectance and transmittance. A theoretical motivation for the introduction of these two parameters instead of a standard single rms roughness is provided. Experimental power spectral density functions of several samples are used to illustrate ways in which the parameters introduced can be evaluated.