Method of classifier selection using the genetic approach

Abstract: The paper presents a novel machine learning algorithm used for training a compound classifier system that consists of a set of area classifiers. Area classifiers recognize objects derived from the respective competence area. Splitting feature space into areas and selecting area classifiers are two key processes of the algorithm; both take place simultaneously in the course of an optimization process aimed at maximizing the system performance. An evolutionary algorithm is used to find the optimal solution. A number of experiments have been carried out to evaluate system performance. The results prove that the proposed method outperforms each elementary classifier as well as simple voting.     

Model predictive control of a rotary cement kiln

A first principles model of a cement kiln is used to control and optimize the burning of clinker in the cement production process. The model considers heat transfer between a gas and a feed state via convection and radiation. Furthermore, it contains effects such as chemical reactions, feed transport, energy losses and energy input. A model predictive controller is used to stabilize a temperature profile along the rotary kiln, guarantee good combustion conditions and maximize production. Moving horizon estimation was used for online estimation of selected model parameters and unmeasured states. Results from the pilot site are presented.     

Atomic RMI: A Distributed Transactional Memory Framework

This paper presents Atomic RMI, a distributed transactional memory framework that supports the control flow model of execution. Atomic RMI extends Java RMI with distributed transactions that can run on many Java virtual machines located on different network nodes. Our system employs SVA, a fully-pessimistic concurrency control algorithm that provides exclusive access to shared objects and supports rollback and fault tolerance. SVA is capable of achieving a relatively high level of parallelism by interweaving transactions that access the same objects and by making transactions that do not share objects independent of one another. It also allows any operations within transactions, including irrevocable ones, like system calls, and provides an unobtrusive API. Our evaluation shows that in most cases Atomic RMI performs better than fine grained mutual-exclusion and read/write locking mechanisms. Atomic RMI also performs better than an optimistic transactional memory in environments with high contention and a high ratio of write operations, while being competitive otherwise.     

A learning-based colour image segmentation with extended and compact structural tensor feature representation

In this paper a novel Tensor-Based Image Segmentation Algorithm (TBISA) is presented, which is dedicated for segmentation of colour images. A purpose of TBISA is to distinguish specific objects based on their characteristics, i.e. shape, colour, texture, or a mixture of these features. All of those information are available in colour channel data. Nonetheless, performing image analysis on the pixel level using RGB values, does not allow to access information on texture which is hidden in relation between neighbouring pixels. Therefore, to take full advantage of all available information, we propose to incorporate the Structural Tensors as a feature extraction method. It forms enriched feature set which, apart from colour and intensity, conveys also information of texture. This set is next processed by different classification algorithms for image segmentation. Quality of TBISA is evaluated in a series of experiments carried on benchmark images. Obtained results prove that the proposed method allows accurate and fast image segmentation.     

QuadCover - Surface Parameterization using Branched Coverings

We introduce an algorithm for the automatic computation of global parameterizations on arbitrary simplicial 2-manifolds, whose parameter lines are guided by a given frame field, for example, by principal curvature frames. The parameter lines are globally continuous and allow a remeshing of the surface into quadrilaterals. The algorithm converts a given frame field into a single vector field on a branched covering of the 2-manifold and generates an integrable vector field by a Hodge decomposition on the covering space. Except for an optional smoothing and alignment of the initial frame field, the algorithm is fully automatic and generates high quality quadrilateral meshes.     

Preparation of high-quality ultrathin transmission electron microscopy specimens of a nanocrystalline metallic powder

This article explores the achievable transmission electron microscopy specimen thickness and quality by using three different preparation methods in the case of a high-strength nanocrystalline Cu-Nb powder alloy. Low specimen thickness is essential for spatially resolved analyses of the grains in nanocrystalline materials. We have found that single-sided as well as double-sided low-angle Ar ion milling of the Cu-Nb powders embedded into epoxy resin produced wedge-shaped particles of very low thickness (<10 nm) near the edge. By means of a modified focused ion beam lift-out technique generating holes in the lamella interior large micrometer-sized electron-transparent regions were obtained. However, this lamella displayed a higher thickness at the rim of ≥30 nm. Limiting factors for the observed thicknesses are discussed including ion damage depths, backscattering, and surface roughness, which depend on ion type, energy, current density, and specimen motion. Finally, sections cut by ultramicrotomy at low stroke rate and low set thickness offered vast, several tens of square micrometers uniformly thin regions of ～10-nm minimum thickness. As major drawbacks, we have detected a thin coating on the sections consisting of epoxy deployed as the embedding material and considerable nanoscale thickness variations.     

Yielding of Microstructured Geomaterial by Distinct Element Method Analysis

The purpose of this paper is to present macro- and micro-study on the yielding of microstructured geomaterials by numerical experiments. This target is achieved by carrying out 63 one-dimensional and biaxial compressions tests on an idealized bonded geomaterial with an extension of distinct element method, into which bond contact models proposed were implemented. Numerical results indicate that: (a) preconsolidated pressure appears to attribute to bond and looseness in the geomaterials, and an increase in void ratio leads to a decrease in yielding stress in one-dimensional tests; (b) an increase in bonding strength at interparticle contacts results in an increase in yielding stress and cohesion, and an internal friction angle that is smaller than the critical state value; (c) the observed first-yielding (initiation of bond breakage) is stress path dependent, and gross-yield (defined with respect to volumetric strain) of microstructured geomaterials is evidently related to bond breakage.     

Anisotropic Filtering of Non-Linear Surface Features

A new method for noise removal of arbitrary surfaces meshes is presented which focuses on the preservation and sharpening of non‐linear geometric features such as curved surface regions and feature lines. Our method uses a prescribed mean curvature flow (PMC) for simplicial surfaces which is based on three new contributions: 1. the definition and efficient calculation of a discrete shape operator and principal curvature properties on simplicial surfaces that is fully consistent with the well‐known discrete mean curvature formula, 2. an anisotropic discrete mean curvature vector that combines the advantages of the mean curvature normal with the special anisotropic behaviour along feature lines of a surface, and 3. an anisotropic prescribed mean curvature flow which converges to surfaces with an estimated mean curvature distribution and with preserved non‐linear features. Additionally, the PMC flow prevents boundary shrinkage at constrained and free boundary segments.     

Radiation- and Photo-Induced Oxidation Pathways of Methionine in Model Peptide Backbone under Anoxic Conditions

Within the reactive oxygen species (ROS) generated by cellular metabolisms, hydroxyl radicals (HO^•) play an important role, being the most aggressive towards biomolecules. The reactions of HO^• with methionine residues (Met) in peptides and proteins have been intensively studied, but some fundamental aspects remain unsolved. In the present study we examined the biomimetic model made of Ac-Met-OMe, as the simplest model peptide backbone, and of HO^• generated by ionizing radiation in aqueous solutions under anoxic conditions. We performed the identification and quantification of transient species by pulse radiolysis and of final products by LC-MS and high-resolution MS/MS after γ-radiolysis. By parallel photochemical experiments, using 3-carboxybenzophenone (CB) triplet with the model peptide, we compared the outcomes in terms of short-lived intermediates and stable product identification. The result is a detailed mechanistic scheme of Met oxidation by HO^•, and by CB triplets allowed for assigning transient species to the pathways of products formation.