A quantitative feedback solution to the multivariable tracking error problem

This paper introduces a novel solution for the multi‐input multi‐output (MIMO) quantitative feedback theory control design problem with tracking error specifications. Looking for a minimum controller overdesign, the technique finds new controller quantitative feedback theory bounds based on necessary and sufficient conditions for the existence of suitable associated prefilter matrix elements. It improves previous approaches to the subject and includes (i) the possibility of a free selection of the nominal plant, (ii) a less conservative application of the Schwartz inequality to decisively reduce the potential controller overdesign, (iii) a methodology to design independently the elements of the prefilter matrix, and (iv) a scope of application to both sequential and nonsequential MIMO controller design methods. The benefits of the new control design technique are illustrated by means of two examples. The first one, a standard 2 × 2 MIMO problem, is provided for comparison purposes with previous approaches. The second example, included as a major control challenge, deals with a well‐known demanding distillation column benchmark problem. Copyright © 2013 John Wiley & Sons, Ltd.     

Factors affecting the mechanical properties of mica-filled polypropylenes

Water-ground Phlogopite mica (Kemira Siilinjarvi phlogopite) has been evaluated as a reinforcing filler in polypropylene. The major factors which influence the composite strength and modulus include the size, aspect ratio, and uniformity of the mica flakes. Aqueous delamination permits the production of very small flakes (less than 44 microns diameter) with aspect ratios near 50. Such small flakes impart greater tensile and modulus values to polypropylene than larger flakes and the former can also be reprocessed many times without any deterioration of properties. Surface treatment is necessary for adequate dispersion and coupling, particularly with the finely divided mica fillers. Other properties such as the heat-distortion temperature, fracture toughness, and gas permeability are also influenced by the mean size and aspect ratio of the mica filler. Guidelines are presented to indicate the preferred characteristics of mica fillers for optimum performance.     

Gewinnung von Brennstoff für Kraftwerke aus Klärschlamm

Production of a combustible for coal-fired power stations based on sewage sludge . This article describes various means of achieving more extensive mechanical dewatering of sewage sludges. The heat content of the sludge solids can become available for combustion processes. The sludge filter cakes obtained by the “CarboSed” process can be disposed of with minimum energy consumption by fluidized bed combustion or be used after appropriate work-up as a combustible in coal-fired power stations with full exploitation of their heat content for generation of steam and electric current. Partial substitution of primary energy sources such as coal and fuel oil by sludge filter cake is feasible in all cases. The processes thus make a contribution to the saving of energy resources and the disposal of sludge.     

pH sensitive phosphate crosslinked films of starch-carboxymethyl cellulose

This work aims to develop hydrogel films of starch and carboxymethyl cellulose (CMC) crosslinked with sodium trimetaphosphate (STMP) and to characterize some of their properties. Starch and STMP (S/T), starch and CMC (S/C), and mixed (S/T/C) films were prepared by casting. The degree of substitution, morphology, swelling degree, FTIR, mechanical properties, and sorption isotherms were studied. Reticulated samples (S/T and S/T/C) showed the same degree of substitution (0.050 ± 0.001). All films presented homogeneous morphology, but the mixed film showed greater roughness. Crosslinking increased the swelling capacity of the mixed hydrogel at pH 7, although it remained decreased concerning the S/T hydrogel. However, this property was sensitive to pH variations. The mixed film (S/T/C) showed greater mechanical resistance. The casting process was efficient to produce hydrogel films of starch/CMC crosslinked with STMP and the general results demonstrated the advantages of the mixed hydrogel.     

Characterizing corrosion behavior under atmospheric conditions using electrochemical techniques

AC and DC electrochemical experiments were performed as a function of humidity and contaminant concentration in an effort to identify the range of atmospheric environments where corrosion processes could be detected and possibly quantified. AC measurements exhibited two time constants at 25% relative humidity (RH), possibly indicating the ability to resolve both electrolyte resistance and interfacial impedance. Galvanic current measurements were sensitive to the presence of Cl_2(g) at 30% RH and electrochemical transients were detected at both 30% and 50% RH levels, also indicating sensitivity to interfacial processes. Higher humidity levels allowed better quantification due to decreasing electrolyte and interfacial impedances.     

Learning to rank academic experts in the DBLP dataset

Expert finding is an information retrieval task that is concerned with the search for the most knowledgeable people with respect to a specific topic, and the search is based on documents that describe people's activities. The task involves taking a user query as input and returning a list of people who are sorted by their level of expertise with respect to the user query. Despite recent interest in the area, the current state‐of‐the‐art techniques lack in principled approaches for optimally combining different sources of evidence. This article proposes two frameworks for combining multiple estimators of expertise. These estimators are derived from textual contents, from graph‐structure of the citation patterns for the community of experts and from profile information about the experts. More specifically, this article explores the use of supervised learning to rank methods, as well as rank aggregation approaches, for combining all of the estimators of expertise. Several supervised learning algorithms, which are representative of the pointwise, pairwise and listwise approaches, were tested, and various state‐of‐the‐art data fusion techniques were also explored for the rank aggregation framework. Experiments that were performed on a dataset of academic publications from the Computer Science domain attest the adequacy of the proposed approaches.     

Query answering under probabilistic uncertainty in Datalog+ / − ontologies

The recently introduced Datalog+?/?? family of ontology languages is especially useful for representing and reasoning over lightweight ontologies, and is set to play a central role in the context of query answering and information extraction for the Semantic Web. Recently, it has become apparent that it is necessary to develop a principled way to handle uncertainty in this domain. In addition to uncertainty as an inherent aspect of the Web, one must also deal with forms of uncertainty due to inconsistency and incompleteness, uncertainty resulting from automatically processing Web data, as well as uncertainty stemming from the integration of multiple heterogeneous data sources. In this paper, we take an important step in this direction by developing a probabilistic extension of Datalog+?/??. This extension uses Markov logic networks as the underlying probabilistic semantics. Here, we focus especially on scalable algorithms for answering threshold queries, which correspond to the question “what is the set of all ground atoms that are inferred from a given probabilistic ontology with a probability of at least p?”. These queries are especially relevant to Web information extraction, since uncertain rules lead to uncertain facts, and only information with a certain minimum confidence is desired. We present several algorithms, namely a basic approach, an anytime one, and one based on heuristics, which is guaranteed to return sound results. Furthermore, we also study inconsistency in probabilistic Datalog+?/?? ontologies. We propose two approaches for computing preferred repairs based on two different notions of distance between repairs, namely symmetric and score-based distance. We also study the complexity of the decision problems corresponding to computing such repairs, which turn out to be polynomial and NP-complete in the data complexity, respectively.     

A multivariate fuzzy c-means method

Fuzzy c-means (FCMs) is an important and popular unsupervised partitioning algorithm used in several application domains such as pattern recognition, machine learning and data mining. Although the FCM has shown good performance in detecting clusters, the membership values for each individual computed to each of the clusters cannot indicate how well the individuals are classified. In this paper, a new approach to handle the memberships based on the inherent information in each feature is presented. The algorithm produces a membership matrix for each individual, the membership values are between zero and one and measure the similarity of this individual to the center of each cluster according to each feature. These values can change at each iteration of the algorithm and they are different from one feature to another and from one cluster to another in order to increase the performance of the fuzzy c-means clustering algorithm. To obtain a fuzzy partition by class of the input data set, a way to compute the class membership values is also proposed in this work. Experiments with synthetic and real data sets show that the proposed approach produces good quality of clustering.