COST COMPETITIVENESS OF THE CANADIAN PORK PROCESSING INDUSTRY

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Towards the improvement of self-service systems via emotional virtual agents

Affective computing and emotional agents have been found to have a positive effect on human-computer interactions. In order to develop an acceptable emotional agent for use in a self-service interaction, two stages of research were identified and carried out; the first to determine which facial expressions are present in such an interaction and the second to determine which emotional agent behaviours are perceived as appropriate during a problematic self-service shopping task. In the first stage, facial expressions associated with negative affect were found to occur during self-service shopping interactions, indicating that facial expression detection is suitable for detecting negative affective states during self-service interactions. In the second stage, user perceptions of the emotional facial expressions displayed by an emotional agent during a problematic self-service interaction were gathered. Overall, the expression of disgust was found to be perceived as inappropriate while emotionally neutral behaviour was perceived as appropriate, however gender differences suggested that females perceived surprise as inappropriate. Results suggest that agents should change their behaviour and appearance based on user characteristics such as gender

Oxidation studies of a novel barrier polymer system

The thermal oxidation of two model compounds representing the aromatic polyamide, MXD6 (poly m-xylylene adipamide) have been investigated. The model compounds (having different chemical structures, viz, one corresponding to the aromatic part of the chain and the other to the aliphatic part), based on the structure of MXD6 were prepared and reactions with different concentrations of cobalt ions examined with the aim of identifying the role of the different structural components of MXD6 on the mechanism of oxidation. The study showed that cobalt, in the presence of sodium phosphite (which acts as an antioxidant for MXD6 and the model compounds), increases the oxidation of the model compounds. It is believed that the cobalt acts predominantly as a catalyst for the decomposition of hydroperoxides, formed during oxidation of the models in the melt phase, to free radical products and to a lesser extent as a catalyst for the initiation of the oxidation reaction by complex formation with the amide, which is more likely to take place in the solid phase. An oxidation cycle has been proposed consisting of two parts both of which will occur, to some extent under all conditions of oxidation (in the melt and in the solid phase), but their individual predominance must be determined by the prevailing oxygen pressure at the reaction site. The different aspects of this proposed mechanism were examined from extensive model compound studies, and the evidence based on the nature of product formation and the kinetics of these reactions. Main techniques used to compare the rates of oxidation and the study of kinetics included, oxygen absorption, FT-IR, UV and TGA. HPLC was used for product separation and identification

Phonological priming and phonetic carry-over in two Danish-English bilinguals

In this study we investigate whether the phonetic carry-over effects (or gestural drift) reported in the literature as occurring in the speech of bilinguals after long-term phonological priming (i.e., several months), also occur after short-term priming of less than all hour. Two bilingual Danish-English speakers were asked to read word lists after being primed for some time in one or other of their languages. In the Danish mode, a number of switches into English occurred in the word-list, and in the English mode switches into Danish were included. The switches allowed the examination of three possible carry-over effects: two with vowels and one with consonants. The results demonstrated no effect with the switches that would require the greatest phonetic change. They also showed that some potential carry-over effects were more likely long-term interference pattems. Acoustic aualysis did suggest that with one of the vowel switches carry-over effects going both ways between Danish and English and English and Danish did occur, although this was clearer with one subject than the other

The Influence of Psycholinguistic Variables on Articulatory Errors in Naming in Progressive Motor Speech Degeneration

We describe an analysis of speech errors on a naming task in a man with progressive speech degeneration. Early assessment indicated naming impairments with no significant phonological or semantic impairment. To examine naming and the factors that influence speech errors, we selected 210 words varying in lexical and phonetic variables and conducted logistic regression analysis on speech error types. No significant naming errors were found. The only significant predictor of articulation errors was phonemic length and the only error type predicted was phone omissions. Results suggest that the sound omissions in naming are caused by motor speech impairment unrelated to lexical factors

A large-scale evaluation framework for EEG deep learning architectures

EEG is the most common signal source for noninvasive BCI applications. For such applications, the EEG signal needs to be decoded and translated into appropriate actions. A recently emerging EEG decoding approach is deep learning with Convolutional or Recurrent Neural Networks (CNNs, RNNs) with many different architectures already published. Here we present a novel framework for the large-scale evaluation of different deep-learning architectures on different EEG datasets. This framework comprises (i) a collection of EEG datasets currently including 100 examples (recording sessions) from six different classification problems, (ii) a collection of different EEG decoding algorithms, and (iii) a wrapper linking the decoders to the data as well as handling structured documentation of all settings and (hyper-) parameters and statistics, designed to ensure transparency and reproducibility. As an applications example we used our framework by comparing three publicly available CNN architectures: the Braindecode Deep4 ConvNet, Braindecode Shallow ConvNet, and two versions of EEGNet. We also show how our framework can be used to study similarities and differences in the performance of different decoding methods across tasks. We argue that the deep learning EEG framework as described here could help to tap the full potential of deep learning for BCI applications.Comment: 7 pages, 3 figures, final version accepted for presentation at IEEE SMC 2018 conferenc

BFKL predictions at small x from k_T and collinear factorization viewpoints

Hard scattering processes involving hadrons at small $x$ are described by a $k_T$-factorization formula driven by a BFKL gluon. We explore the equivalence of this description to a collinear-factorization approach in which the anomalous dimensions $\gamma_{gg}$ and $\gamma_{qg}/\alpha_S$ are expressed as power series in $\alpha_S \log (1/x)$, or to be precise $\alpha_S/\omega$ where $\omega$ is the moment index. In particular we confront the collinear-factorization expansion with that extracted from the BFKL approach with running coupling included.Comment: 11 LaTeX pages, 1 figure (uuencoded