A comparative study of four novel sleep apnoea episode prediction systems

The prediction of sleep apnoea and hypopnoea episodes could allow treatment to be applied before the event be-comes detrimental to the patients sleep, and for a more spe-cific form of treatment. It is proposed that features extracted from breaths preceding an apnoea and hypopnoea could be used in neural networks for the prediction of these events. Four different predictive systems were created, processing the nasal airflow signal using epoching, the inspiratory peak and expiratory trough values, principal component analysis (PCA) and empirical mode decomposition (EMD). The neu-ral networks were validated with naïve data from six over-night polysomnographic records, resulting in 83.50% sensi-tivity and 90.50% specificity. Reliable prediction of apnoea and hypopnoea is possible using the epoched flow and EMD of breaths preceding the event

Machine learning-based affect detection within the context of human-horse interaction

This chapter focuses on the use of machine learning techniques within the field of affective computing, and more specifically for the task of emotion recognition within the context of human-horse interaction. Affective computing focuses on the detection and interpretation of human emotion, an application that could significantly benefit quantitative studies in the field of animal assisted therapy. The chapter offers a thorough description, an experimental design, and experimental results on the use of physiological signals, such as electroencephalography (EEG), electrocardiography (ECG), and electromyography (EMG) signals, for the creation and evaluation of machine learning models for the prediction of the emotional state of an individual during interaction with horses

Reanalyzing language expectations: Native language knowledge modulates the sensitivity to intervening cues during anticipatory processing

Issue Online:21 September 2018We investigated how native language experience shapes anticipatory language processing. Two groups of bilinguals (either Spanish or Basque natives) performed a word matching task (WordMT) and a picture matching task (PictureMT). They indicated whether the stimuli they visually perceived matched with the noun they heard. Spanish noun endings were either diagnostic of the gender (transparent) or ambiguous (opaque). ERPs were time-locked to an intervening gender-marked determiner preceding the predicted noun. The determiner always gender agreed with the following noun but could also introduce a mismatching noun, so that it was not fully task diagnostic. Evoked brain activity time-locked to the determiner was considered as reflecting updating/reanalysis of the task-relevant preactivated representation. We focused on the timing of this effect by estimating the comparison between a gender-congruent and a gender-incongruent determiner. In the WordMT, both groups showed a late N400 effect. Crucially, only Basque natives displayed an earlier P200 effect for determiners preceding transparent nouns. In the PictureMT, both groups showed an early P200 effect for determiners preceding opaque nouns. The determiners of transparent nouns triggered a negative effect at similar to 430 ms in Spanish natives, but at similar to 550 ms in Basque natives. This pattern of results supports a "retracing hypothesis" according to which the neurocognitive system navigates through the intermediate (sublexical and lexical) linguistic representations available from previous processing to evaluate the need of an update in the linguistic expectation concerning a target lexical item.Spanish Ministry of Economy and Competitiveness (MINECO), Agencia Estatal de Investigación (AEI), Fondo Europeo de Desarrollo Regional (FEDER) (grant PSI2015‐65694‐P to N. M.), Spanish Ministry of Economy and Competitiveness “Severo Ochoa” Programme for Centres/Units of Excellence in R&D (grant SEV‐2015‐490

The doctoral research abstracts. Vol:7 2015 / Institute of Graduate Studies, UiTM

Foreword: The Seventh Issue of The Doctoral Research Abstracts captures the novelty of 65 doctorates receiving their scrolls in UiTM’s 82nd Convocation in the field of Science and Technology, Business and Administration, and Social Science and Humanities. To the recipients I would like to say that you have most certainly done UiTM proud by journeying through the scholastic path with its endless challenges and impediments, and persevering right till the very end. This convocation should not be regarded as the end of your highest scholarly achievement and contribution to the body of knowledge but rather as the beginning of embarking into high impact innovative research for the community and country from knowledge gained during this academic journey. As alumni of UiTM, we will always hold you dear to our hearts. A new ‘handshake’ is about to take place between you and UiTM as joint collaborators in future research undertakings. I envisioned a strong research pact between you as our alumni and UiTM in breaking the frontier of knowledge through research. I wish you all the best in your endeavour and may I offer my congratulations to all the graduands. ‘UiTM sentiasa dihati ku’ / Tan Sri Dato’ Sri Prof Ir Dr Sahol Hamid Abu Bakar , FASc, PEng Vice Chancellor Universiti Teknologi MAR

Human Being Emotion in Cognitive Intelligent Robotic Control Pt I: Quantum / Soft Computing Approach

Abstract. The article consists of two parts. Part I shows the possibility of quantum / soft computing optimizers of knowledge bases (QSCOptKB™) as the toolkit of quantum deep machine learning technology implementation in the solution’s search of intelligent cognitive control tasks applied the cognitive helmet as neurointerface. In particular, case, the aim of this part is to demonstrate the possibility of classifying the mental states of a human being operator in on line with knowledge extraction from electroencephalograms based on SCOptKB™ and QCOptKB™ sophisticated toolkit. Application of soft computing technologies to identify objective indicators of the psychophysiological state of an examined person described. The role and necessity of applying intelligent information technologies development based on computational intelligence toolkits in the task of objective estimation of a general psychophysical state of a human being operator shown. Developed information technology examined with special (difficult in diagnostic practice) examples emotion state estimation of autism children (ASD) and dementia and background of the knowledge bases design for intelligent robot of service use is it. Application of cognitive intelligent control in navigation of autonomous robot for avoidance of obstacles demonstrated.

Political economy of climate policy

Die vorliegende Arbeit beschäftigt sich modelltheoretisch, empirisch und experimentell mit dem Thema der Klimapolitik aus einer politökonomischen Perspektive. Der Ansatz der Neuen Politischen Ökonomie versucht, die ökonomischen Modelle um den politischen Prozess zu erweitern. Die Motivation für dieses Vorgehen steht in einem engen Zusammenhang mit der Erkenntnis, dass es unzureichend ist, die ökonomische Analyse auf Probleme des Marktversagens zu reduzieren. Neben Marktversagen können durch den politischen Prozess Probleme generiert werden (sog. Politikversagen). Im Rahmen einer positiven Analyse kann die Neue Politische Ökonomie Erklärungsansätze liefern, die eng mit der Fragestellung verknüpft sind, warum bekannte Ineffizienzen den politischen Prozess überdauern. Dieses Problem lässt sich in vielen Fällen durch Partikularinteressen erklären. Aus einer normativen Perspektive lassen sich die resultierenden Erkenntnisse für Politikempfehlungen heranziehen. Vordergründig sind dabei jene Handlungsalternativen (zum Teil auch Handlungsbeschränkungen z.B. auf konstitutioneller Ebene) die es dem Staat ermöglichen seine Handlungen möglichst unabhängig von Partikularinteressen durchzuführen. Die vorliegende Arbeit gliedert sich in acht Kapitel. Das erste Kapitel dient zur Einleitung. Kapitel zwei bis sieben umfassen den Hauptteil der Arbeit. In Kapitel acht werden die wesentlichen Ergebnisse noch einmal kurz zusammengefasst

Using EEG to evaluate the effects of horse assisted therapy in children with autism spectrum disorders: Definition of the methods and preliminary experiments with an ASD group

Resumo Do Projeto: Atualmente, o Perturbação do Espectro do Autismo (PEA) é considerado um distúrbio do neurode-senvolvimento caraterizado por deficits na comunicação e interação social, além de mudanças com-portamentais. Um possível método de intervenção terapêutica para o desenvolvimento de capacidade nas áreas deficitárias de crianças com PEA é a terapia assistida por cavalos. Vários estudos têm de-monstrado que a hipoterapia tem um impacto positivo no desenvolvimento dessas crianças; no entanto, o tipo de avaliação feita tem sido apenas qualitativa. A recolha de dados é realizada de forma observacional do comportamento e estado de concen-tração da criança durante a terapia e também por meio de entrevistas e preenchimento de formulá-rios sobre comunicação, interação social e comportamento das crianças. Portanto, o fato de os dados serem apenas qualitativos e subjetivos é uma limitação para avaliar a evolução do desempenho de cada criança durante a sessão de terapia. O objetivo principal desta dissertação é, portanto, contribuir para a validação científica da terapia assistida por cavalos, enquanto método terapêutico para o desenvolvimento das crianças com PEA. Para tal foi construída uma metodologia baseada num sistema de estimulação visual associado à mo-nitorização cerebral EEG (eletroencefalograma), como forma de avaliar parâmetros relacionados com a interação social (em termos de processamento de emoções) e atenção em crianças com PEA. Contudo, a escassez dos dados obtidos nesta tese permite apenas uma avaliação preliminar da meto-dologia desenvolvida.Autism Spectrum Disorder (ASD) is presently considered aneurodevelopmental disorder catego-rized by deficits in communication and social interaction, along with behavioural changes. A possible method of a therapeutic intervention for capacity development of children with ASD is horse-assisted therapy. Studies have shown that hippotherapy has a positive impact on the development of these children, however, the type of performed evaluation is merely qualitative.Indeed, the data collection is performed in an observational way of the behaviour and state of concentration of the child during the therapy and also through interviews and filling of forms on the communication, social interaction and behaviour of the children. Therefore, the fact that the data are only qualitative and subjective is a limitation for assessing the evolution of the child along with the therapy. The main objective of this dissertation is, therefore, to contribute to the scientific validation of horse-assisted therapy, as a therapeutic method for the development of children with ASD. To that end, a methodology was built based on a visual stimulation system associated with brain monitoring EEG (electroencephalogram), as a way of assessing parameters related to social interaction (in terms of processing emotions) and attention in children with ASD. However, the scarcity of the results ob-tained in this thesis allows only a preliminary assessment of the developed methodology