Introducing robustness in model predictive control with multiple modelsand switching

Model predictive control is model-based. Therefore, the procedure is inherently not robust to modelling uncertainties. Further, a crucial design parameter is the prediction horizon. Only offline procedures to estimate an upper bound of the optimal value of this parameter are available. These procedures are computationally intensive and model-based. Besides, a single choice of this horizon is perhaps not the best option at all time instants. This is especially true when the control objective is to track desired trajectories. In this paper, we resolve the issue by a time-varying horizon achieved by switching between multiple model-predictive controllers. The stability of the overall system is discussed. In addition, an introduction of multiple models to handle modelling uncertainties makes the overall system robust. The improvement in performance is demonstrated through several examples.     

Terpolymers. II. Mechanical properties and transition temperatures of terpolymers of vinyl stearate,vinyl acetate,and vinyl chloride

Vinyl stearate was studied as a major internal plasticizer in terpolymers containing vinyl acetate and vinyl chloride. The terpolymers were prepared by systematically replacing vinyl acetate by close increments of vinyl stearate starting with combinations of vinyl acetate and vinyl chloride, in increments, over all compositions. For comparison of properties, a complete range of copolymers of vinyl stearate and vinyl chloride, as well as mixtures of poly(vinyl chloride) and di-2-ethylhexyl phthalate (DOP) were also made. The external plasticizer was more efficient in reducing the glass temperature than was vinyl stearate. The decline in T_g with weight fraction of plasticizer was linear for the copolymers and terpolymers but concave downward with the liquid diluent. The linear decline was shown to involve mere additivity of the free volume contributed by each side-chain methylene (or methyl) group in both vinyl esters to reducing T_g. The mechanism of the diluent system was more complex. However, the magnitude of the reduction of tensile modulus at a given weight fraction of DOP could be equaled or exceeded by the same amount of vinyl stearate, by increasing the vinyl acetate content of the base copolymer to 40 mole-% or more. Unfortunately, the ultimate strengths and elongations of internally plasticized systems were reduced more than those of the mixtures at comparable compositions. Vinyl stearate was found to markedly retard photolytic degradation compared to both vinyl acetate and the external plasticizer in unstabilized samples having nearly the same thermal treatment. The effect was greater than could be ascribed to dilution by the long alkyl group. The production of a stearoyl radical more stable than the radicals initiating dehydrochlorination is suggested as a possible mechanism.     

Mechanical properties and transition temperatures of copolymers of N-n-alkylacrylamides and vinylidene chloride

Mechanical and solution properties, melting transitions, torsional stiffness temperatures, T_f, and selected modulus-temperature curves are presented for copolymers of the N-n-alkylacrylamides with vinylidene chloride. Copolymers were prepared at 60°C across the range of compositions, using as comonomers N-n-butyl-, octyl-, dodecyl- and oleyl-acrylamide, which have amorphous side-chains, and N-n-octadecyl acrylamide and n-octadecyl acrylate whose side-chains are crystalline. The mechanical properties reflected the effect of the decline in backbone crystallinity and the simultaneous development of strong intermolecular interactions in the amorphous stage. Copolymers were stiff or showed brittle failure across the compositional range except when intermolecular forces were reduced (with n-octadrcyl acrylate) and side-chain crystallization eliminated (with N-oleylacrylamide). These systems and the n-dodecylacrylamide copolymers had yield strengths less than brittle strengths and substantial elongations. Backbone crystallinity was eliminated at about 15 mole % amide and side-chain crystallinity vanished at less than 10 mole % of the amide in the N-n-octadecylacrylamide series. No depression in side-chain melting point occurred with dilution by segments of vinylidene chloride. Over-all decline in the flex-temperature was the normal monotonic function of composition except that values increased in magnitude at high vinylidene chloride contents, the effect presumably being caused by the presence of crystallinity. An empirical equation was developed which permitted the calculation of T_f for any N-n-alkylacrylamide composition with any number of carbon atoms in the side-chain, above 3.     

Approximate similarity search for online multimedia services on distributed CPU–GPU platforms

Similarity search in high-dimensional spaces is a pivotal operation for several database applications, including online content-based multimedia services. With the increasing popularity of multimedia applications, these services are facing new challenges regarding (1) the very large and growing volumes of data to be indexed/searched and (2) the necessity of reducing the response times as observed by end-users. In addition, the nature of the interactions between users and online services creates fluctuating query request rates throughout execution, which requires a similarity search engine to adapt to better use the computation platform and minimize response times. In this work, we address these challenges with Hypercurves, a flexible framework for answering approximate k-nearest neighbor (kNN) queries for very large multimedia databases. Hypercurves executes in hybrid CPU–GPU environments and is able to attain massive query-processing rates through the cooperative use of these devices. Hypercurves also changes its CPU–GPU task partitioning dynamically according to the observed load, aiming for optimal response times. In our empirical evaluation, dynamic task partitioning reduced query response times by approximately 50 % compared to the best static task partition. Due to a probabilistic proof of equivalence to the sequential kNN algorithm, the CPU–GPU execution of Hypercurves in distributed (multi-node) environments can be aggressively optimized, attaining superlinear scalability while still guaranteeing, with high probability, results at least as good as those from the sequential algorithm.     

Coal liquefaction in nitrogen compounds

Model compound studies have shown that 1,2,3,4-tetrahydroquinoline is an exceptionally good coal solvent. In the pure compound, subbituminous coal conversion to THF-soluble products approaches 100% under relatively mild reaction conditions. The effectiveness of tetrahydroquinoline for coal conversion appears to be related to its concentration relative to coal. The unique behaviour of tetrahydroquinoline is ascribed to its being a highly active H-donor; the fact that it is regenerable under reaction conditions by the reaction of hydrogen and quinoline; and that its polarity allows penetration of the coal structure and aids in dispersion of the dissolved coal. It has been found that, during reaction with coal, tetrahydroquinoline and other nitrogen compounds undergo extensive condensation reactions which result in an increase in the nitrogen content of the high boiling and non-distillable liquefaction products.     

Viscometric determination of the molecular weight of polymers in the low molecular weight region

In order to overcome the difficulty of the determination of the molecular weight of a polymer in the low molecular weight region by viscometry using the Mark–Houwink–Sakurada (MHS) equation, we have proposed the Dondos–Benoit relationship [η]^?1 = A₂ + AM^?1/2, for a number of polymer–solvent systems, for which we give the numerical values of the parameters A₁ and A₂. Furthermore, we suggest a method for the determination of the above parameters using the MHS constants a and k.     

Parallel and scalable processing of spatio-temporal RDF queries using Spark

The ever-increasing size of data emanating from mobile devices and sensors, dictates the use of distributed systems for storing and querying these data. Typically, such data sources provide some spatio-temporal information, alongside other useful data. The RDF data model can be used to interlink and exchange data originating from heterogeneous sources in a uniform manner. For example, consider the case where vessels report their spatio-temporal position, on a regular basis, by using various surveillance systems. In this scenario, a user might be interested to know which vessels were moving in a specific area for a given temporal range. In this paper, we address the problem of efficiently storing and querying spatio-temporal RDF data in parallel. We specifically study the case of SPARQL queries with spatio-temporal constraints, by proposing the DiStRDF system, which is comprised of a Storage and a Processing Layer. The DiStRDF Storage Layer is responsible for efficiently storing large amount of historical spatio-temporal RDF data of moving objects. On top of it, we devise our DiStRDF Processing Layer, which parses a SPARQL query and produces corresponding logical and physical execution plans. We use Spark, a well-known distributed in-memory processing framework, as the underlying processing engine. Our experimental evaluation, on real data from both aviation and maritime domains, demonstrates the efficiency of our DiStRDF system, when using various spatio-temporal range constraints.

     

Effect of theθ-α-Al2O3 transformation on the oxidation behavior ofβ-NiAl + Zr

Isothermal oxidation of NiAl + Zr has been performed over the temperature range of 800–1200°C and studied by TGA, XRD, and SEM. A discontinuous decrease in growth rate of two orders of magnitude was observed at 1000° C due to the formation of -Al₂O₃ from -Al₂O₃. This transformation also resulted in a dramatic change in the surface morphology of the scales, as a whisker topography was changed into a weblike network of oxide ridges and radial transformation cracks. It is believed that the ridges are evidence for a shortcircuit outward aluminum diffusion growth mechanism that has been documented in a number of¹⁸O tracer studies.     

Automated speech recognition for spreadsheet tasks: Performance effects for experts and novices

The performance of spreadsheet users was compared for two modes of input to the computer, keyboard and automated speech recognition (ASR). Subjects from both an expert group and a novice group were also classified by decision style. Dependent measures were task completion time, accuracy, keystroke count, correction count, and user confidence. Results for a speaker‐dependent, discrete‐word recognizer showed that, for both simple data input and more complex analytical spreadsheet tasks, neither the experts nor the novices performed more effectively using ASR. However, both groups expressed the desirability of having speech input as an option for desktop computing.