Popular Mixed Matchings

We study the problem of matching applicants to jobs under one-sided preferences: that is, each applicant ranks a non-empty subset of jobs under an order of preference, possibly involving ties. A matching M is said to be rnore popular than T if the applicants that prefer M to T outnumber those that prefer T to M. A matching is said to be popular if there is no matching more popular than it. Equivalently, a matching M is popular if phi(M,T) >= phi(T, M) for all matchings T, where phi(X, Y) is the number of applicants that prefer X to Y. Previously studied solution concepts based oil the popularity criterion are either not guaranteed to exist for every instance (e.g., popular matchings) or are NP-hard to compute (e.g., least unpopular matchings). This paper addresses this issue by considering mixed matchings. A mixed matching is simply a probability distributions over matchings in the input graph. The function phi that compares two matchings generalizes in a natural manner to mixed matchings by taking expectation. A mixed matching P is popular if phi(P,Q) >= phi(Q,P) for all mixed matchings Q. We show that popular mixed matchings always exist. and we design polynomial time algorithms for finding them. Then we study their efficiency and give tight bounds on the price of anarchy and price of stability of the popular matching problem.

A new mixed-matrix membrane for DMFCs

A new mixed-matrix membrane based on stabilized phosphotungstic acid (PTA) incorporated to chitosan (CS)-hydroxy ethyl cellulose (HEC) for application in direct methanol fuel cells (DMFCs) is reported. Membranes are characterised using Fourier Transform Spectroscopy (FTIR), Thermo-Gravimetric Analysis (TGA), Scanning Electron Microscopy (SEM) and their mechanical properties are evaluated. The PTA content in the CS-HEC blend and its influence on proton conductivity, water/methanol sorption, and methanol cross-over in the DMFC is studied. The DMFC with 3 wt. % stabilized PTA-CS-HEC mixed-matrix membrane delivers peak power-density of 58 mW/cm(2) at a load current-density of 210 mA/cm(2) with a lower methanol cross-over than that observed for a DMFC operating with a Nafion membrane electrolyte.

Mixed mode (I and II) crack tip fields in bulk metallic glasses

Stationary crack tip fields in bulk metallic glasses under mixed mode (I and II) loading are studied through detailed finite element simulations assuming plane strain, small scale yielding conditions. The influence of internal friction or pressure sensitivity on the plastic zones. notch deformation, stress and plastic strain fields is examined for different mode mixities. Under mixed mode loading, the notch deforms into a shape such that one part of its surface sharpens while the other part blunts. Increase in mode If component of loading dramatically enhances the normalized plastic zone size, lowers the stresses but significantly elevates the plastic strain levels near the notch tip. Higher internal friction reduces the peak tangential stress but increases the plastic strain and stretching near the blunted part of the notch. The simulated shear bands are straight and extend over a long distance ahead of the notch tip under mode II dominant loading. The possible variations of fracture toughness with mode mixity corresponding to failure by brittle micro-cracking and ductile shear banding are predicted employing two simple fracture criteria. The salient results from finite element simulations are validated by comparison with those from mixed mode (I and II) fracture experiments on a Zr-based bulk metallic glass.

Joint evaluation of multiple speech patterns for speech recognition and training

We are addressing the novel problem of jointly evaluating multiple speech patterns for automatic speech recognition and training. We propose solutions based on both the non-parametric dynamic time warping (DTW) algorithm, and the parametric hidden Markov model (HMM). We show that a hybrid approach is quite effective for the application of noisy speech recognition. We extend the concept to HMM training wherein some patterns may be noisy or distorted. Utilizing the concept of ``virtual pattern'' developed for joint evaluation, we propose selective iterative training of HMMs. Evaluating these algorithms for burst/transient noisy speech and isolated word recognition, significant improvement in recognition accuracy is obtained using the new algorithms over those which do not utilize the joint evaluation strategy.

Steady mixed convection stagnation-point flow of upper convected Maxwell fluids with magnetic field

The steady MHD mixed convection flow of a viscoelastic fluid in the vicinity of two-dimensional stagnation point with magnetic field has been investigated under the assumption that the fluid obeys the upper-convected Maxwell (UCM) model. Boundary layer theory is used to simplify the equations of motion. induced magnetic field and energy which results in three coupled non-linear ordinary differential equations which are well-posed. These equations have been solved by using finite difference method. The results indicate the reduction in the surface velocity gradient, surface heat transfer and displacement thickness with the increase in the elasticity number. These trends are opposite to those reported in the literature for a second-grade fluid. The surface velocity gradient and heat transfer are enhanced by the magnetic and buoyancy parameters. The surface heat transfer increases with the Prandtl number, but the surface velocity gradient decreases.

Co(II) and Cr(III) complexes of formate-formamide mixed ligands: synthesis, structures, single crystal-to-single crystal transformation and magnetic behaviour

Solvothermal treatment of an equimolar mixture of Co(NO3)(2)center dot 6H(2)O, HCONH2 and NaN3 in MeOH at 100 degrees C yielded a three-dimensional NaCl type network Co(HCOO)(2)(HCONH2)(2) center dot HCONH2 (1a) containing formamides in the pores of the structure. Solvated pink 1a undergoes single crystal-to-single crystal (SCSC) transformation at 215 degrees C to form the desolvated dark brown product Co(HCOO)(2)-( HCONH2)(2) (1b) with the retention of the original framework. Reversible single crystal-to-single crystal transformation of 1b (brown) to 1a (pink) in the presence of excess formamide was also established at room temperature. The coordination environment around Co(II) in both 1a and 1b is octahedral with a CoN2O4 coordination composition. A similar reaction replacing Co(II) by Cr(III) produced a heterometallic 3D extended network Na[Cr(HCOO)(4)(HCONH2)(2)]center dot 2H(2)O (2a) at 100 degrees C. An increase in reaction temperature to 150 degrees C produced a simple mononuclear complex Cr(HCOO)(3)(HCONH2)(3) center dot 3H(2)O (2b). Variable temperature magnetic studies revealed the presence of a canting phenomena in both 1a and 1b, and hysteresis loop in the field dependent magnetisation plot at 2 K whereas complex 2a is simply paramagnetic in nature.

Blended learning in medical imaging pre-clinical skills training – does it work?

Undergraduate Medical Imaging (MI)students at QUT attend their first clinical placement towards the end of semester two. Students undertake two (pre)clinical skills development units – one theory and one practical. Students gain good contextual and theoretical knowledge during these units via a blended learning model with multiple learning methods employed. Students attend theory lectures, practical sessions, tutorial sessions in both a simulated and virtual environment and also attend pre-clinical scenario based tutorial sessions. The aim of this project is to evaluate the use of blended learning in the context of 1st year Medical Imaging Radiographic Technique and its effectiveness in preparing students for their first clinical experience. It is hoped that the multiple teaching methods employed within the pre-clinical training unit at QUT builds students clinical skills prior to the real situation. A quantitative approach will be taken, evaluating via pre and post clinical placement surveys. This data will be correlated with data gained in the previous year on the effectiveness of this training approach prior to clinical placement. In 2014 59 students were surveyed prior to their clinical placement demonstrated positive benefits of using a variety of learning tools to enhance their learning. 98.31%(n=58)of students agreed or strongly agreed that the theory lectures were a useful tool to enhance their learning. This was followed closely by 97% (n=57) of the students realising the value of performing role-play simulation prior to clinical placement. Tutorial engagement was considered useful for 93.22% (n=55) whilst 88.14% (n=52) reasoned that the x-raying of phantoms in the simulated radiographic laboratory was beneficial. Self-directed learning yielded 86.44% (n=51). The virtual reality simulation software was valuable for 72.41% (n=42) of the students. Of the 4 students that disagreed or strongly disagreed with the usefulness of any tool they strongly agreed to the usefulness of a minimum of one other learning tool. The impact of the blended learning model to meet diverse student needs continues to be positive with students engaging in most offerings. Students largely prefer pre -clinical scenario based practical and tutorial sessions where 'real-world’ situations are discussed.

Intuitive interaction in a mixed reality system

Tangible physical systems are more intuitive than Intangible virtual Systems. Mixed reality systems are considered as an alternative to virtual systems, bringing advantages of tangible systems into an interaction. However, past research has mainly focussed on technical aspects of incorporating pervasive-ness and immersive-ness in the virtual systems. This paper reports on an empirical study of intuitive Interaction in a Mixed Reality game system for children and the design aspects that could facilitate intuitive Interaction in such systems. A related samples Friedman’s test showed that the Mixed Reality game system demonstrated more intuitive interactions than non-intuitive Interactions. A linear regression analysis further established that the variation in intuitive Interaction in the Mixed Reality system could be statistically significantly explained primarily by physical affordances offered by the Mixed Reality system and to a lesser extent by the perceived affordances in the system. Design guidelines to develop intuitive Mixed Reality systems are discussed. These guidelines should allow designers to exploit the wonders of advances in technology and at the same time allow users to directly interact with the physical real world. This will allow users to access maximal physical affordances, which are primary contributors to intuitive interaction in Tangible and Mixed Reality systems.

Functional Imagery Training to reduce snacking: Testing a novel motivational intervention based on Elaborated Intrusion theory

Functional Imagery Training (FIT) is a new theory-based, manualized intervention that trains positive goal imagery. Multisensory episodic imagery of proximal personal goals is elicited and practised, to sustain motivation and compete with less functional cravings. This study tested the impact of a single session of FIT plus a booster phone call on snacking. In a stepped-wedge design, 45 participants who wanted to lose weight or reduce snacking were randomly assigned to receive a session of FIT immediately or after a 2-week delay. High-sugar and high-fat snacks were recorded using timeline follow back for the previous 3 days, at baseline, 2 and 4 weeks. At 2 weeks, snacking was lower in the immediate group than in the delayed group, and the reduction after FIT was replicated in the delayed group between 2 and 4 weeks. Frequencies of motivational thoughts about snack reduction rose following FIT for both groups, and this change correlated with reductions in snacking and weight loss. By showing that FIT can support change in eating behaviours, these findings show its potential as a motivational intervention for weight management.

Why do birds participate in mixed-species foraging flocks? A large-scale synthesis

Mixed-species flocks of foraging birds have been documented from terrestrial habitats all over the world and are thought to form for either improved feeding efficiency or better protection from predators. Two kinds of flock participants are recognized: those that join other species ('followers') and are therefore likely to be the recipients of the benefits of flock participation and those that are joined ('leaders'). Through comparative analyses, using a large sample of flocks from around the world, we show that (1) 'followers' tend to be smaller, more insectivorous, and feed in higher strata than matched species that participate in flocks to a lesser extent and (2) 'leaders' tend to be cooperative breeders more often than matched species that are not known to lead flocks. Furthermore, meta-analyses of published results from across the world showed that bird species in terrestrial mixed-species flocks increase foraging rates and reduce vigilance compared to when they are solitary or in conspecific groups. Moreover, the increase in foraging rates is seen only with flock followers and not flock leaders. These findings suggest a role for predation in the evolution of mixed-species flocking. Species that are vulnerable to predation follow species whose vigilance they can exploit. By doing so, they are able to reduce their own vigilance and forage at higher rates. (C) 2009 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved.

Cluster based training for scaling non-linear support vector machines

Support Vector Machines(SVMs) are hyperplane classifiers defined in a kernel induced feature space. The data size dependent training time complexity of SVMs usually prohibits its use in applications involving more than a few thousands of data points. In this paper we propose a novel kernel based incremental data clustering approach and its use for scaling Non-linear Support Vector Machines to handle large data sets. The clustering method introduced can find cluster abstractions of the training data in a kernel induced feature space. These cluster abstractions are then used for selective sampling based training of Support Vector Machines to reduce the training time without compromising the generalization performance. Experiments done with real world datasets show that this approach gives good generalization performance at reasonable computational expense.