Developing Approaches for Solving a Telecommunications Feature Subscription Problem

Call control features (e.g., call-divert, voice-mail) are primitive options to which users can subscribe off-line to personalise their service. The configuration of a feature subscription involves choosing and sequencing features from a catalogue and is subject to constraints that prevent undesirable feature interactions at run-time. When the subscription requested by a user is inconsistent, one problem is to find an optimal relaxation, which is a generalisation of the feedback vertex set problem on directed graphs, and thus it is an NP-hard task. We present several constraint programming formulations of the problem. We also present formulations using partial weighted maximum Boolean satisfiability and mixed integer linear programming. We study all these formulations by experimentally comparing them on a variety of randomly generated instances of the feature subscription problem.

An optimal algorithm for low power multiplierless FIR filter design using chebychev criterion

In this paper, we propose a novel finite impulse response (FIR) filter design methodology that reduces the number of operations with a motivation to reduce power consumption and enhance performance. The novelty of our approach lies in the generation of filter coefficients such that they conform to a given low-power architecture, while meeting the given filter specifications. The proposed algorithm is formulated as a mixed integer linear programming problem that minimizes chebychev error and synthesizes coefficients which consist of pre-specified alphabets. The new modified coefficients can be used for low-power VLSI implementation of vector scaling operations such as FIR filtering using computation sharing multiplier (CSHM). Simulations in 0.25um technology show that CSHM FIR filter architecture can result in 55% power and 34% speed improvement compared to carry save multiplier (CSAM) based filters.

On-off based charging strategies for EVs connected to a Low Voltage distributon network

The development of appropriate Electric Vehicle (EV) charging strategies has been identified as an effective way to accommodate an increasing number of EVs on Low Voltage (LV) distribution networks. Most research studies to date assume that future charging facilities will be capable of regulating charge rates continuously, while very few papers consider the more realistic situation of EV chargers that support only on-off charging functionality. In this work, a distributed charging algorithm applicable to on-off based charging systems is presented. Then, a modified version of the algorithm is proposed to incorporate real power system constraints. Both algorithms are compared with uncontrolled and centralized charging strategies from the perspective of both utilities and customers. © 2013 IEEE.

Advances in Learning Bayesian Networks of Bounded Treewidth

This work presents novel algorithms for learning Bayesian networks of bounded treewidth. Both exact and approximate methods are developed. The exact method combines mixed integer linear programming formulations for structure learning and treewidth computation. The approximate method consists in sampling k-trees (maximal graphs of treewidth k), and subsequently selecting, exactly or approximately, the best structure whose moral graph is a subgraph of that k-tree. The approaches are empirically compared to each other and to state-of-the-art methods on a collection of public data sets with up to 100 variables.

Kuznetsov independence for interval-valued expectations and sets of probability distributions: Properties and algorithms

Kuznetsov independence of variables X and Y means that, for any pair of bounded functions f(X) and g(Y), E[f(X)g(Y)]=E[f(X)] *times* E[g(Y)], where E[.] denotes interval-valued expectation and *times* denotes interval multiplication. We present properties of Kuznetsov independence for several variables, and connect it with other concepts of independence in the literature; in particular we show that strong extensions are always included in sets of probability distributions whose lower and upper expectations satisfy Kuznetsov independence. We introduce an algorithm that computes lower expectations subject to judgments of Kuznetsov independence by mixing column generation techniques with nonlinear programming. Finally, we define a concept of conditional Kuznetsov independence, and study its graphoid properties.

Two-stage mixed discrete-continuous identification of radial basis function (RBF) neural models for nonlinear systems

The identification of nonlinear dynamic systems using radial basis function (RBF) neural models is studied in this paper. Given a model selection criterion, the main objective is to effectively and efficiently build a parsimonious compact neural model that generalizes well over unseen data. This is achieved by simultaneous model structure selection and optimization of the parameters over the continuous parameter space. It is a mixed-integer hard problem, and a unified analytic framework is proposed to enable an effective and efficient two-stage mixed discrete-continuous; identification procedure. This novel framework combines the advantages of an iterative discrete two-stage subset selection technique for model structure determination and the calculus-based continuous optimization of the model parameters. Computational complexity analysis and simulation studies confirm the efficacy of the proposed algorithm.

Bayesian Dependence Tests for Continuous, Binary and Mixed Continuous-Binary Variables

Tests for dependence of continuous, discrete and mixed continuous-discrete variables are ubiquitous in science. The goal of this paper is to derive Bayesian alternatives to frequentist null hypothesis significance tests for dependence. In particular, we will present three Bayesian tests for dependence of binary, continuous and mixed variables. These tests are nonparametric and based on the Dirichlet Process, which allows us to use the same prior model for all of them. Therefore, the tests are “consistent” among each other, in the sense that the probabilities that variables are dependent computed with these tests are commensurable across the different types of variables being tested. By means of simulations with artificial data, we show the effectiveness of the new tests.

New binary direction aftereffect does not add up

Neural adaptation and inhibition are pervasive characteristics of the primate brain, and are probably understood better within the context of visual processing than any other sensory modality. These processes are thought to underlie illusions in which one motion affects the perceived direction of another, such as the direction aftereffect (DAE) and direction repulsion. The DAE describes how, following prolonged viewing of motion in one direction, the direction of a subsequently viewed test pattern is misperceived. In the case of direction repulsion, the direction difference between two transparently moving surfaces is over-estimated. Explanations of the DAE appeal to neural adaptation whilst direction repulsion is accounted for through lateral inhibition. Here we report on a new illusion, the Binary DAE, in which superimposed slow and fast dots moving in the same direction are perceived to move in different directions following adaptation to a mixed-speed stimulus. This new phenomenon is essentially a combination of the DAE and direction repulsion. Interestingly the magnitude of the binary DAE is greater than would be expected simply through a linear combination of the DAE and direction repulsion, suggesting that the mechanisms underlying these two phenomena interact in a non-linear fashion.

Catalytic Hydrogenolysis of Aromatic Ketones in Mixed Choline-Betainium Ionic Liquids

The palladium-catalyzed hydrogenolysis of aromatic ketones to alkylbenzenes was studied in mixtures of ionic liquids to explore the promotional effect of these reaction media. Choline-based ionic liquids displayed complete miscibility with the aromatic ketone substrate at reaction temperature and a clear phase separation of the derived alkylbenzene product at room temperature. Selected ionic liquids were then assessed as reaction media in the hydrogenolysis of aromatic ketones over palladium catalysts. A binary mixture of choline and betainium bis(trifluoromethylsulfonyl)imide ionic liquids resulted in the highest conversion and selectivity values in the hydrogenolysis of acetophenone. At the end of the reaction, the immiscible alkylbenzene separates from the ionic liquid mixture and the pure product phase can be isolated by simple decantation. After optimization of the reaction conditions, high yields (>90%) of alkylbenzene were obtained in all cases. The catalyst and the ionic liquid could be used at least three times without any loss of activity or selectivity.

Controlling Assembly of Mixed Thiol Monolayers on Silver Nanoparticles to Tune Their Surface Properties

Modifying the surfaces of metal nanoparticles with self-assembled monolayers of functionalized thiols provides a simple and direct method to alter their surface properties. Mixed self-assembled monolayers can extend this approach since, in principle, the surfaces can be tuned by altering the proportion of each modifier that is adsorbed. However, this works best if the composition and microstructure of the monolayers can be controlled. Here, we have modified preprepared silver colloids with binary mixtures of thiols at varying concentrations and modifier ratios. Surface-enhanced Raman spectroscopy was then used to determine the effect of altering these parameters on the composition of the resulting mixed monolayers. The data could be explained using a new model based on a modified competitive Langmuir approach. It was found that the composition of the mixed monolayer only reflected the ratio of modifiers in the feedstock when the total amount of modifier was sufficient for approximately one monolayer coverage. At higher modifier concentrations the thermodynamically favored modifier dominated, but working at near monolayer concentrations allowed the surface composition to be controlled by changing the ratios of modifiers. Finally, a positively charged porphyrin probe molecule was used to investigate the microstructure of the mixed monolayers, i.e., homogeneous versus domains. In this case the modifier domains were found to be <2 nm.

Phase Behaviour, Interactions, and Structural Studies of (Amines+Ionic Liquids) Binary Mixtures

We present a study on the phase equilibrium behaviour of binary mixtures containing two 1-alkyl-3-methylimidazolium bis{(trifluoromethyl)sulfonyl}imide-based ionic liquids, [Cnmim] [NTf2] (n=2 and 4), mixed with diethylamine or triethylamine as a function of temperature and composition using different experimental techniques. Based on this work, two systems showing an LCST and one system with a possible hourglass shape are measured. Their phase behaviours are then correlated and predicted by using Flory–Huggins equations and the UNIQUAC method implemented in Aspen. The potential of the COSMO-RS methodology to predict the phase equilibria was also tested for the binary systems studied. However, this methodology is unable to predict the trends obtained experimentally, limiting its use for systems involving amines in ionic liquids. The liquid-state structure of the binary mixture ([C2mim] [NTf2]+diethylamine) is also investigated by molecular dynamics simulation and neutron diffraction. Finally, the absorption of gaseous ethane by the ([C2mim][NTf2]+diethylamine) binary mixture is determined and compared with that observed in the pure solvents.

Nonlinear scattering by anisotropic dielectric periodic structures

The combinatorial frequency generation by the periodic stacks of binary layers of anisotropic nonlinear dielectrics is examined. The products of nonlinear scattering are characterised in terms of the three-wave mixing processes. It is shown that the intensity of the scattered waves of combinatorial frequencies is strongly influenced by the constitutive and geometrical parameters of the anisotropic layers, and the frequency ratio and angles of incidence of pump waves. The enhanced efficiency of the frequency conversion at Wolf-Bragg resonances has been demonstrated for the lossless and lossy-layered structures. © 2012 O. V. Shramkova and A. G. Schuchinsky.

Structure and dynamics of dextran in binary mixtures of a good and a bad solvent

The structure and dynamics of the common polysaccharide dextran have been investigated in mixed solvents at two different temperatures using small-angle X-ray scattering (SAXS) and viscosity measurements. More specifically, binary mixtures of a good solvent (water, formamide, dimethylsulfoxide, ethanolamine) and the bad solvent ethanol as the minority component have been considered. The experimentally observed effects on the polymer conformation (intrinsic viscosity, coil radius, and radius of gyration) of the bad solvent addition are discussed in terms of hydrogen bonding density and are correlated with the Hansen solubility parameters and the surface tension of the solvent mixtures. Hydrogen bonding appears to be an important contributor to the solubility of dextran but is not sufficient to capture the dextran coil contraction in the mixtures of good+bad solvents.