Reversible Jump MCMC in mixtures of normal distributions with the same component means

The Bayesian estimation of a special case of mixtures of normal distributions with an unknown number of components is considered. More specifically, the case where some components may have identical means is studied. The standard Reversible Jump MCMC algorithm for the estimation of a normal mixture model consisting of components with distinct parameters naturally fails to give precise results in the case where (at least) two of the mixture components have equal means. In particular, this algorithm either tends to combine such components resulting in a posterior distribution for their number having mode at a model with fewer components than those of the true one, or overestimates the number of components. This problem is overcome by defining-for every number of components-models with different number of parameters and introducing a new move type that bridges these competing models. The proposed method is applied in conjunction with suitable modifications of the standard split-combine and birth-death moves for updating the number of components. The method is illustrated by using two simulated datasets and the well-known galaxy dataset.     

Numerical investigation of the oxy-fuel combustion in large scale boilers adopting the ECO-Scrub technology

The present paper presents a three-dimensional numerical investigation of a pulverized-fuel, tangentially-fired utility boiler located at Florina/Greece under air, partial and full oxy-fuel conditions. Heat and mass transfer and major species concentration, such as CO₂, CO and O₂ are calculated; whilst the results for the reference air case scenario studied are in good agreement with the corresponding operational data measured in the plant, both for combustion calculations and NO_x emissions. Results for the partial and full oxy-fuel operation scenarios are in line with similar experimental and numerical investigations found in the recent literature. This numerical investigation of oxy-fuel conditions scenarios prior to their implementation under real scale conditions demonstrates the utmost of its importance, since significant results regarding the operation of a boiler in terms of lignite particle trajectories and burning rates are attained. Furthermore, NO_x calculations have been performed for all the examined case studies.     

An overview of Greece's wholesale electricity market with emphasis on ancillary services

Greece's wholesale electricity market is a mandatory pool in which the commodities of energy and ancillary services are simultaneously traded and dispatched on the generation units. In this paper, we provide an overview of the Greek wholesale electricity market with emphasis on ancillary services. Considering the wide range of ancillary services, our goal is to contribute to the growing literature on individual case studies and comparisons of different ancillary services markets worldwide, pointing out similarities and differences with other market models. In addition, we discuss several aspects, and report on some of the strengths and weaknesses of the Greek wholesale electricity market model.     

Transitive node similarity: predicting and recommending links in signed social networks

Online social networks (OSNs) like Facebook, Myspace, and Hi5 have become popular, because they allow users to easily share content. OSNs recommend new friends to registered users based on local features of the graph (i.e., based on the number of common friends that two users share). However, OSNs do not exploit the whole structure of the network. Instead, they consider only pathways of maximum length 2 between a user and his candidate friends. On the other hand, there are global approaches, which detect the overall path structure in a network, being computationally prohibitive for huge-size social networks. In this paper, we define a basic node similarity measure that captures effectively local graph features (i.e., by measuring proximity between nodes). We exploit global graph features (i.e., by weighting paths that connect two nodes) introducing transitive node similarity. We also derive variants of our method that apply to different types of networks (directed/undirected and signed/unsigned). We perform extensive experimental comparison of the proposed method against existing recommendation algorithms using synthetic and real data sets (Facebook, Hi5 and Epinions). Our experimental results show that our FriendTNS algorithm outperforms other approaches in terms of accuracy and it is also time efficient. Finally, we show that a significant accuracy improvement can be gained by using information about both positive and negative edges.     

Comparing hybrid learning with traditional approaches on learning the Microsoft Office Power Point 2003 program in tertiary education

The purpose of this study was to determine the effectiveness of a hybrid learning approach to deliver a computer science course concerning the Microsoft office PowerPoint 2003 program in comparison to delivering the same course content in the form of traditional lectures. A hundred and seventy-two first year university students were randomly assigned into two teaching method groups: traditional lecture instruction (TLI) and hybrid lecture instruction (HLI). Each group received six 95-min periods of instruction divided into 4 sections: a) 5-min brief outline of the key learning points, b) 40-min lecture on general knowledge c) 45-min constructivist-inspired learning activities and d) 5-min summary on key learning points. In the beginning and the end of this study students completed a 17-item multiple choice knowledge test. Two-way analysis of variances (ANOVA), with repeated measures on the last factor, were conducted to determine effect of method groups (TLI, HLI) and measures (pre-test, post-test) on knowledge test. The measures main effect was significant, as well as the groups x measures interaction effect. Two independent-samples t test were conducted to follow up the significant interaction. Differences in mean ratings of knowledge performance between the two teaching groups were not significantly different at first measure, while the TLI method group yielded a significantly lower mean rating at second measure. The findings indicated that HLI approach might be a superior option for undergraduate students on learning the Microsoft office PowerPoint 2003 program.     

Uniting bounded control and MPC for stabilization of constrained linear systems

In this work, a hybrid control scheme, uniting bounded control with model predictive control (MPC), is proposed for the stabilization of linear time-invariant systems with input constraints. The scheme is predicated upon the idea of switching between a model predictive controller, that minimizes a given performance objective subject to constraints, and a bounded controller, for which the region of constrained closed-loop stability is explicitly characterized. Switching laws, implemented by a logic-based supervisor that constantly monitors the plant, are derived to orchestrate the transition between the two controllers in a way that safeguards against any possible instability or infeasibility under MPC, reconciles the stability and optimality properties of both controllers, and guarantees asymptotic closed-loop stability for all initial conditions within the stability region of the bounded controller. The hybrid control scheme is shown to provide, irrespective of the chosen MPC formulation, a safety net for the practical implementation of MPC, for open-loop unstable plants, by providing a priori knowledge, through off-line computations, of a large set of initial conditions for which closed-loop stability is guaranteed. The implementation of the proposed approach is illustrated, through numerical simulations, for an exponentially unstable linear system.