Towards Speech Emotion Recognition "in the wild" using Aggregated Corpora and Deep Multi-Task Learning

One of the challenges in Speech Emotion Recognition (SER) "in the wild" is the large mismatch between training and test data (e.g. speakers and tasks). In order to improve the generalisation capabilities of the emotion models, we propose to use Multi-Task Learning (MTL) and use gender and naturalness as auxiliary tasks in deep neural networks. This method was evaluated in within-corpus and various cross-corpus classification experiments that simulate conditions "in the wild". In comparison to Single-Task Learning (STL) based state of the art methods, we found that our MTL method proposed improved performance significantly. Particularly, models using both gender and naturalness achieved more gains than those using either gender or naturalness separately. This benefit was also found in the high-level representations of the feature space, obtained from our method proposed, where discriminative emotional clusters could be observed.Comment: Published in the proceedings of INTERSPEECH, Stockholm, September, 201

A FRAMEWORK FOR THE ECONOMIC EVALUATION OF ENVIRONMENTAL SCIENCE

Economists, especially agricultural economists, have undertaken extensive analysis of the gains of technological-based scientific research. This is in stark contrast to the efforts undertaken to understand the economic effects of environmental scientific research. Economic evaluation of environmental science is important because knowledge-based government agencies are regularly required to justify their research expenditure and set clear priorities for their research programmes. This paper addresses the gap in the literature by offering a general framework for evaluating environmental scientific research. The paper is structured around two themes central to appraisals of environmental research: (a) the non-market nature of environmental outcomes; and (b) the pathways to achieve these outcomes. Some of the more important and unique issues addressed include the links between the natural systems being researched, the benefits in terms of resulting goods and services, and their subsequent values, as well as the factors influencing the overall contribution research makes to environmental decision-making.Environmental Economics and Policy, Research and Development/Tech Change/Emerging Technologies,

Optimization and evaluation of a coarse-grained model of protein motion using X-ray crystal data

Simple coarse-grained models, such as the Gaussian Network Model, have been shown to capture some of the features of equilibrium protein dynamics. We extend this model by using atomic contacts to define residue interactions and introducing more than one interaction parameter between residues. We use B-factors from 98 ultra-high resolution X-ray crystal structures to optimize the interaction parameters. The average correlation between GNM fluctuation predictions and the B-factors is 0.64 for the data set, consistent with a previous large-scale study. By separating residue interactions into covalent and noncovalent, we achieve an average correlation of 0.74, and addition of ligands and cofactors further improves the correlation to 0.75. However, further separating the noncovalent interactions into nonpolar, polar, and mixed yields no significant improvement. The addition of simple chemical information results in better prediction quality without increasing the size of the coarse-grained model.Comment: 18 pages, 4 figures, 1 supplemental file (cnm_si.tex

Examining sustainability performance in the supply chain: The case of the Greek dairy sector

This is the post-print version of the final paper published in Industrial Marketing Management. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2013 Elsevier B.V.This paper evaluates the sustainability performance of the Greek dairy chain and the performance of its individual members by using key indicators in relation to efficiency, flexibility, responsiveness and product quality. We assessed the importance of these indicators based on the relevant perceptions of key members of this chain. A structured questionnaire was developed where nineteen sustainability-related issues were examined. Two hundred and fifty three members of the Greek dairy supply chain responded including breeders, manufacturers, wholesalers, retailers and catering companies. Our findings illustrate the immediate need for improvement in many key sustainability performance indicators. They also show the critical role of large dairy manufacturers who are the “sustainability performance champions” in this chain and are the driving force for the implementation of many sustainability initiatives.European Unio

Regulations and robust low-carbon buildings

Building regulations and associated calculation methods have been rapidly evolving, driven in Europe by the European Union Energy Performance of Buildings Directive. As an example, the current UK regulations are explored in relation to buildings that are naturally ventilated, mechanically ventilated, or mechanically ventilated and cooled. The UK regulatory energy and carbon calculation methods are investigated using a standard office design with typical, best practice, and advanced building fabric and systems applied. The criteria and calculations for demonstrating avoidance of excessive temperatures in buildings that have no mechanical cooling are also explored. Observations are made on how the regulations may influence future adoption of mechanical cooling. Current regulatory methods can be subjective and limited in scope. For example, they do not include adaptive comfort criteria or uncertainties in parameters such as occupant behaviour, climate, internal gains from equipment, etc. A design methodology is proposed that addresses these issues and provides a capability parameter to quantify robustness. This capability parameter allows comparison of design options and provides an indication to building users of the limitations to a building's use beyond which mitigating action would have to be taken for performance to be maintained

Opportunistic Third-Party Backhaul for Cellular Wireless Networks

With high capacity air interfaces and large numbers of small cells, backhaul -- the wired connectivity to base stations -- is increasingly becoming the cost driver in cellular wireless networks. One reason for the high cost of backhaul is that capacity is often purchased on leased lines with guaranteed rates provisioned to peak loads. In this paper, we present an alternate \emph{opportunistic backhaul} model where third parties provide base stations and backhaul connections and lease out excess capacity in their networks to the cellular provider when available, presumably at significantly lower costs than guaranteed connections. We describe a scalable architecture for such deployments using open access femtocells, which are small plug-and-play base stations that operate in the carrier's spectrum but can connect directly into the third party provider's wired network. Within the proposed architecture, we present a general user association optimization algorithm that enables the cellular provider to dynamically determine which mobiles should be assigned to the third-party femtocells based on the traffic demands, interference and channel conditions and third-party access pricing. Although the optimization is non-convex, the algorithm uses a computationally efficient method for finding approximate solutions via dual decomposition. Simulations of the deployment model based on actual base station locations are presented that show that large capacity gains are achievable if adoption of third-party, open access femtocells can reach even a small fraction of the current market penetration of WiFi access points.Comment: 9 pages, 6 figure

Hierarchical bounding structures for efficient virial computations: Towards a realistic molecular description of cholesterics

We detail the application of bounding volume hierarchies to accelerate second-virial evaluations for arbitrary complex particles interacting through hard and soft finite-range potentials. This procedure, based on the construction of neighbour lists through the combined use of recursive atom-decomposition techniques and binary overlap search schemes, is shown to scale sub-logarithmically with particle resolution in the case of molecular systems with high aspect ratios. Its implementation within an efficient numerical and theoretical framework based on classical density functional theory enables us to investigate the cholesteric self-assembly of a wide range of experimentally-relevant particle models. We illustrate the method through the determination of the cholesteric behaviour of hard, structurally-resolved twisted cuboids, and report quantitative evidence of the long-predicted phase handedness inversion with increasing particle thread angles near the phenomenological threshold value of $45^\circ$. Our results further highlight the complex relationship between microscopic structure and helical twisting power in such model systems, which may be attributed to subtle geometric variations of their chiral excluded-volume manifold