Decentralized observers with consensus filters for distributed discrete-time linear systems

This paper presents a decentralized observer with a consensus filter for the state observation of discrete-time linear distributed systems. Each agent in the distributed system has an observer with a model of the plant that utilizes the set of locally available measurements, which may not make the full plant state detectable. This lack of detectability is overcome by utilizing a consensus filter that blends the state estimate of each agent with its neighbors’ estimates. It is proven that the state estimates of the proposed observer exponentially converge to the actual plant states under arbitrarily changing, but connected, communication and pseudo-connected sensing graph topologies. Except these connectivity properties, full knowledge of the sensing and communication graphs is not needed at the design time. As a byproduct, we obtained a result on the location of eigenvalues, i.e., the spectrum, of the Laplacian for a family of graphs with self-loops.     

Utilising semantic technologies for intelligent indexing and retrieval of digital images

The proliferation of digital media has led to a huge interest in classifying and indexing media objects for generic search and usage. In particular, we are witnessing a colossal growth in digital image repositories that are difficult to navigate using free-text search mechanisms, which often return inaccurate matches as they in principle rely on statistical analysis of query keyword recurrence in the image annotation or surrounding text. In this paper we present a semantically-enabled image annotation and retrieval engine that is designed to satisfy the requirements of the commercial image collections market in terms of both accuracy and efficiency of the retrieval process. Our search engine relies on methodically structured ontologies for image annotation, thus allowing for more intelligent reasoning about the image content and subsequently obtaining a more accurate set of results and a richer set of alternatives matchmaking the original query. We also show how our well-analysed and designed domain ontology contributes to the implicit expansion of user queries as well as the exploitation of lexical databases for explicit semantic-based query expansion.     

Poly(Acrylamide-Sepiolite) Composite Hydrogels: Preparation, Swelling and Dye Adsorption Properties

Summary Polymer-clay hydrogel composite was prepared on the basis of polyacrylamide (PAAm) gel containing the clay mineral sepiolite. The properties of swelling and dye adsorption of poly(acrylamide-sepiolite) (AAm/Sep) composite hydrogel were investigated. The parameters of swelling and diffusion in water and dye solutions were calculated for the AAm and AAm/Sep hydrogels. It was found that the equilibrium swelling degree of obtained composite higher than that of AAm gel. Spectroscopic analysis of composite and composite-dye systems was done with FT-IR method. Adsorption of monovalent cationic dyes such as Basic Blue 12 (BB-12) Basic Blue 9 (BB-9), and Basic Violet 1 (BV-1), was studied on the composite. In the adsorption experiments, S (Sigmoidal) type for composite gel adsorption isotherms in the Giles classification system was found. Adsorption studies indicated that the amounts of adsorbed dyes on the AAm/Sep composite hydrogel were increased with following order; BB-12 > BB-9 > BV-1. The composite hydrogel may be considered as good candidate for environmental application to retain more water and dyes.     

New aspects in cationization of lignocellulose materials. IX. Flame retardancy effect of modification with nitrogen and sulfur containing groups

Lignocellulose materials were modified with 3-chlor-2-hydroxypropyltrimethylammoniumchloride, 1,3-bis(3-chlor-2-hydroxypropyl)imidazoliumhydrogensulphate, and 2-chlorethyl-sodiumsulphonate and the flame-retardant properties of materials obtained were studied. The flame-retardant effect was proved using the limited oxygen index (LOI) method and values up to 32.8 vol % of oxygen were determined. The LOI values were higher when the modification was done without using NaOH for activation, but in that case the alkylating groups were not chemically bonded to the material. The NaOH activation was necessary to obtain material with flame-retardant properties stable against washing. No synergistic effects were observed when the material was modified with both nitrogen- and sulfur-containing groups.     

Corrosion inhibition of stainless steel by polyaniline,poly(2-chloroaniline), and poly(aniline-co-2-chloroaniline) in HCl

Polyaniline (PANi), poly(2-chloroaniline) (PClANi), and poly(aniline-co-2-chloroaniline) (co-PClANi) films were synthesized by electrochemical deposition on 304-stainless steel (SS) from an acetonitrile solution. The structural properties of these polymer films were characterized by spectroscopic (FTIR and UV–vis) and electrochemical (cyclic voltammetry) methods. Open circuit potential–time (E_ocp–time) curves, potentiodynamic polarization, and electrochemical impedance (EIS) measurements showed that these films have significant protective performance against corrosion of SS in 0.5 M HCl solution. It was found that co-PClANi film has acted as a passivator as well as barrier for cathodic reduction reaction in a similar manner as PANi film. However, PClANi film has behaved only as barrier for corrosion protection of SS in 0.5 M HCl.     

Energy profile of rollback-recovery strategies in high performance computing

Extreme-scale computing is set to provide the infrastructure for the advances and breakthroughs that will solve some of the hardest problems in science and engineering. However, resilience and energy concerns loom as two of the major challenges for machines at that scale. The number of components that will be assembled in the supercomputers plays a fundamental role in these challenges. First, a large number of parts will substantially increase the failure rate of the system compared to the failure frequency of current machines. Second, those components have to fit within the power envelope of the installation and keep the energy consumption within operational margins. Extreme-scale machines will have to incorporate fault tolerance mechanisms and honor the energy and power restrictions. Therefore, it is essential to understand how fault tolerance and energy consumption interplay. This paper presents a comparative evaluation and analysis of energy consumption of three different rollback-recovery protocols: checkpoint/restart, message logging and parallel recovery. Our experimental evaluation shows parallel recovery has the minimum execution time and energy consumption. Additionally, we present an analytical model that projects parallel recovery can reduce energy consumption more than 37% compared to checkpoint/restart at extreme scale.     

Prioritized Mobile Robot Exploration Based on Percolation Enhanced Entropy Based Fast SLAM

The major aim in search and rescue using mobile robots is to detect and reach trapped survivors and to support rescue operations through disaster environments. Our motivation is based on the fact that a search and rescue (SAR) robot can navigate within and penetrate a disaster area only if the area in question possesses connected voids. Traversability or penetrability of a disaster area is a primary factor that guides the navigation of a search and rescue (SAR) robot, since it is highly desirable that the robot, without hitting a dead end or getting stuck, keeps its mobility for its primary task of reconnaissance and mapping when searching the highly unstructured environment. We propose a novel percolation guidance that collaborates with entropy based SLAM under a switching control setting the priority to either position or map accuracy. This newly developed methodology has proven to combine the superiority of both percolator guidance and entropy based prioritization so that the active SLAM becomes speedy, with high coverage rate of the area as well as increased accuracy in localization. Our percolator guidance stems from a frontier based conditioning of a-posteriori occurrences of upcoming connected voids that uses the fact that every obstacle partially seen at the frontier of the explored domain has a spatial continuity into the unexplored area. The developed modular architecture is introduced in details and demonstrative examples are provided and discussed.     

Verifying anonymity in voting systems using CSP

We present formal definitions of anonymity properties for voting protocols using the process algebra CSP. We analyse a number of anonymity definitions, and give formal definitions for strong and weak anonymity, highlighting the difference between these definitions. We show that the strong anonymity definition is too strong for practical purposes; the weak anonymity definition, however, turns out to be ideal for analysing voting systems. Two case studies are presented to demonstrate the usefulness of the formal definitions: a conventional voting system, and Prêt à Voter, a paper-based, voter-verifiable scheme. In each case, we give a CSP model of the system, and analyse it against our anonymity definitions by specification checks using the Failures-Divergences Refinement (FDR2) model checker. We give a detailed discussion on the results from the analysis, emphasizing the assumptions that we made in our model as well as the challenges in modelling electronic voting systems using CSP.     

Sparse Non-negative Stencils for Anisotropic Diffusion

We introduce a new discretization scheme for Anisotropic Diffusion, AD-LBR, on two and three dimensional Cartesian grids. The main features of this scheme is that it is non-negative and has sparse stencils, of cardinality bounded by 6 in 2D, by 12 in 3D, despite allowing diffusion tensors of arbitrary anisotropy. The radius of these stencils is not a-priori bounded however, and can be quite large for pronounced anisotropies. Our scheme also has good spectral properties, which permits larger time steps and avoids e.g. chessboard artifacts. AD-LBR relies on Lattice Basis Reduction, a tool from discrete mathematics which has recently shown its relevance for the discretization on grids of strongly anisotropic Partial Differential Equations (Mirebeau in Preprint, 2012). We prove that AD-LBR is in 2D asymptotically equivalent to a finite element discretization on an anisotropic Delaunay triangulation, a procedure more involved and computationally expensive. Our scheme thus benefits from the theoretical guarantees of this procedure, for a fraction of its cost. Numerical experiments in 2D and 3D illustrate our results.     

Prediction of suspended sediment concentration from water quality variables

This study investigates use of water quality (WQ) variables, namely total chromium concentration, total iron concentration, and turbidity for predicting suspended sediment concentration (SSC). For this purpose, the artificial neural networks (ANNs) and regression analysis (RA) models are employed. Seven different RA models are constructed, considering the functional relation between measured WQ variables and SSC. The WQ and SSC data are fortnightly obtained from six monitoring stations, located on the stream Harsit, Eastern Black Sea Basin, Turkey. A total of 132 water samples are collected from April 2009 to February 2010. Model prediction results reveal that ANN is able to predict SSC from WQ data, with mean absolute error (MAE) of 10.30 mg/L and root mean square error (RMSE) of 13.06 mg/L. Among seven RA models, the best one, which has the form including all independent parameters, produces results comparable to those of ANN, with MAE = 14.28 mg/L and RMSE = 15.35 mg/L. The sensitivity analysis results reveal that the most effective parameter on the SSC is total chromium concentration. These results have time- and cost-saving implications.