Design Strategies and Modelling of Low-Power Sigma-Delta Analog-to-Digital Converters

Oggi, i dispositivi portatili sono diventati la forza trainante del mercato consumer e nuove sfide stanno emergendo per aumentarne le prestazioni, pur mantenendo un ragionevole tempo di vita della batteria. Il dominio digitale è la miglior soluzione per realizzare funzioni di elaborazione del segnale, grazie alla scalabilità della tecnologia CMOS, che spinge verso l'integrazione a livello sub-micrometrico. Infatti, la riduzione della tensione di alimentazione introduce limitazioni severe per raggiungere un range dinamico accettabile nel dominio analogico. Minori costi, minore consumo di potenza, maggiore resa e una maggiore riconfigurabilità sono i principali vantaggi dell'elaborazione dei segnali nel dominio digitale. Da più di un decennio, diverse funzioni puramente analogiche sono state spostate nel dominio digitale. Ciò significa che i convertitori analogico-digitali (ADC) stanno diventando i componenti chiave in molti sistemi elettronici. Essi sono, infatti, il ponte tra il mondo digitale e analogico e, di conseguenza, la loro efficienza e la precisione spesso determinano le prestazioni globali del sistema. I convertitori Sigma-Delta sono il blocco chiave come interfaccia in circuiti a segnale-misto ad elevata risoluzione e basso consumo di potenza. I tools di modellazione e simulazione sono strumenti efficaci ed essenziali nel flusso di progettazione. Sebbene le simulazioni a livello transistor danno risultati più precisi ed accurati, questo metodo è estremamente lungo a causa della natura a sovracampionamento di questo tipo di convertitore. Per questo motivo i modelli comportamentali di alto livello del modulatore sono essenziali per il progettista per realizzare simulazioni veloci che consentono di identificare le specifiche necessarie al convertitore per ottenere le prestazioni richieste. Obiettivo di questa tesi è la modellazione del comportamento del modulatore Sigma-Delta, tenendo conto di diverse non idealità come le dinamiche dell'integratore e il suo rumore termico. Risultati di simulazioni a livello transistor e dati sperimentali dimostrano che il modello proposto è preciso ed accurato rispetto alle simulazioni comportamentali.

Priming moral self-ambivalence heightens deliberative behaviour in self-ambivalent individuals

Background: Recent work on cognitive-behavioural models of obsessive-compulsive disorder has focused on the roles played by various aspects of self-perception. In particular, moral self-ambivalence has been found to be associated with obsessive-compulsive phenomena. Aims: In this study we used an experimental task to investigate whether artificially priming moral self-ambivalence would increase participants' deliberation on ethical problems, an index that might be analogous to obsessive-compulsive behaviour. Method: Non-clinical participants completed two online tasks designed to prime either moral self-ambivalence, general uncertainty, or neither. All participants then completed a task requiring them to consider solutions to moral dilemmas. We recorded the time participants took to respond to the dilemmas and the length of their responses; we then combined these variables to create a measure of deliberation. Results: Priming moral self-ambivalence led to increases in deliberation, but this was only significant among those participants who scored highly on a baseline measure of moral self-ambivalence. Priming general uncertainty had no significant effect upon deliberation. Conclusions: The results suggest that moral self-ambivalence may play a role in the maintenance of obsessive-compulsive behaviour. We propose that individuals who are morally self-ambivalent might respond to situations in which this ambivalence is made salient by exhibiting behaviour with obsessive-compulsive characteristics. These findings have implications for the incorporation of ideas about self-concept into theories of obsessive-compulsive disorder.

Do Children's Health Resources Differ According to Preschool Physical Activity Programmes and Parental Behaviour? A Mixed Methods Study

Preschool can have positive effects on the development of a healthy lifestyle. The present study analysed to what extent different conditions, structures and behavioural models in preschool and family-children's central social microsystems-can lead to differences in children's health resources. Using a cross-sectional mixed methods approach, contrast analyses of "preschools with systematic physical activity programmes" versus "preschools without physical activity programmes" were conducted to assess the extent to which children's physical activity, quality of life and social behaviour differ between preschools with systematic and preschools without physical activity programmes. Differences in children's physical activity according to parental behaviour were likewise assessed. Data on child-related outcomes and parent-related factors were collected via parent questionnaires and child interviews. A qualitative focused ethnographic study was performed to obtain deeper insight into the quantitative survey data. Two hundred and twenty seven (227) children were interviewed at 21 preschools with systematic physical activity programmes, and 190 at 25 preschools without physical activity programmes. There was no significant difference in children's physical activity levels between the two preschool types (p = 0.709). However, the qualitative data showed differences in the design and quality of programmes to promote children's physical activity. Data triangulation revealed a strong influence of parental behaviour. The triangulation of methods provided comprehensive insight into the nature and extent of physical activity programmes in preschools and made it possible to capture the associations between systematic physical activity promotion and children's health resources in a differential manner.

PCA 4 DCA: the application of principal component analysis to the Dendritic Cell Algorithm

As one of the newest members in the field of articial immune systems (AIS), the Dendritic Cell Algorithm (DCA) is based on behavioural models of natural dendritic cells (DCs). Unlike other AIS, the DCA does not rely on training data, instead domain or expert knowledge is required to predetermine the mapping between input signals from a particular instance to the three categories used by the DCA. This data preprocessing phase has received the criticism of having manually over-fitted the data to the algorithm, which is undesirable. Therefore, in this paper we have attempted to ascertain if it is possible to use principal component analysis (PCA) techniques to automatically categorise input data while still generating useful and accurate classication results. The integrated system is tested with a biometrics dataset for the stress recognition of automobile drivers. The experimental results have shown the application of PCA to the DCA for the purpose of automated data preprocessing is successful.

Autism : an introduction to behavioural therapy models used for autism and nursing the person with autism in the primary care setting

Childhood autism falls under the guise of autism spectrum disorders and is generally found in children over two years of age. There are of course variations in severity and clinical manifestations, however the most common features being disinterest in social interaction and engagement in ritualistic and repetitive behaviours. In Singapore the incidence of autism is on the rise as parents are becoming more aware of the early signs of autism and seek healthcare programmes to ensure the quality of life for their child is optimised. Two such programmes, Applied Behaiour Analysis and Floortime approach have proven successful in alleviating some of the behavioural and social skills problems associated with autism. Using positive behaviour reinforcement both Applied Behaviour Analysis and Floortime approach reward behaviour associated with positive social responses.

Behavioural context of multi-scale species distribution models assessed by radio-tracking

Incorporating ecological processes and animal behaviour into Species Distribution Models (SDMs) is difficult. In species with a central resting or breeding place, there can be conflict between the environmental requirements of the 'central place' and foraging habitat. We apply a multi-scale SDM to examine habitat trade-offs between the central place, roost sites, and foraging habitat in . Myotis nattereri. We validate these derived associations using habitat selection from behavioural observations of radio-tracked bats. A Generalised Linear Model (GLM) of roost occurrence using land cover variables with mixed spatial scales indicated roost occurrence was positively associated with woodland on a fine scale and pasture on a broad scale. Habitat selection of radio-tracked bats mirrored the SDM with bats selecting for woodland in the immediate vicinity of individual roosts but avoiding this habitat in foraging areas, whilst pasture was significantly positively selected for in foraging areas. Using habitat selection derived from radio-tracking enables a multi-scale SDM to be interpreted in a behavioural context. We suggest that the multi-scale SDM of . M. nattereri describes a trade-off between the central place and foraging habitat. Multi-scale methods provide a greater understanding of the ecological processes which determine where species occur and allow integration of behavioural processes into SDMs. The findings have implications when assessing the resource use of a species at a single point in time. Doing so could lead to misinterpretation of habitat requirements as these can change within a short time period depending on specific behaviour, particularly if detectability changes depending on behaviour. © 2011 Gesellschaft für ökologie.

Towards a cognitive-behavioural intervention for adult grief reactions

Published accounts of behavioural interventions for grief have relied on exposure and habituation to grief cues as the primary strategy. Such an approach is excessively narrow, since it does not adequately confront the challenges that are posed by a bereavement. Many people cope with a bereavement by themselves, and for those, intervention may well be counterproductive. A cognitive-behavioural intervention, following models for depression/anxiety, can assist vulnerable individuals obtain a more rapid or complete adjustment. The proposed approach differs from dynamic treatments by placing less emphasis on defensive behavior, insight, and interpretation and more emphasis on training of coping skills.

Models of supervision : from theory to practice

This chapter will address psychodynamic, cognitive-behavioural, and developmental models in supervision by initially considering the historical underpinnings of each and then examining in turn some of the key processes that are evident in the supervisory relationships. Case studies are included where appropriate to highlight the application of theory to practice and several processes are fully elaborated over all models to enable a contemporary view of style and substance in the supervision context.

Simplified numerical models of LiteSteel Beam floor joists with Web openings for the prediction of section moment capacities

This paper is aimed at investigating the effect of web openings on the plastic bending behaviour and section moment capacity of a new cold-formed steel beam known as LiteSteel beam (LSB) using numerical modelling. Different LSB sections with varying circular hole diameter and spacing were considered. A simplified but appropriate numerical modelling technique was developed for the modelling of monosymmetric sections such as LSBs subject to bending, and was used to simulate a series of section moment capacity tests of LSB flexural members with web openings. The buckling and ultimate strength behaviour was investigated in detail and the modeling technique was further improved through a comparison of numerical and experimental results. This paper describes the simplified finite element modeling technique used in this study that includes all the significant behavioural effects affecting the plastic bending behaviour and section moment capacity of LSB sections with web holes. Numerical and test results and associated findings are also presented.

Attribute exclusion strategies in airline choice : accounting for exogenous information on decision maker processing strategies in models of discrete choice

We examine the impact of individual-specific information processing strategies (IPSs) on the inclusion/exclusion of attributes on the parameter estimates and behavioural outputs of models of discrete choice. Current practice assumes that individuals employ a homogenous IPS with regards to how they process attributes of stated choice (SC) experiments. We show how information collected exogenous of the SC experiment on whether respondents either ignored or considered each attribute may be used in the estimation process, and how such information provides outputs that are IPS segment specific. We contend that accounting the inclusion/exclusion of attributes will result in behaviourally richer population parameter estimates.

Relative entropy rate based design for linear hybrid system models

Hybrid system representations have been applied to many challenging modeling situations. In these hybrid system representations, a mixture of continuous and discrete states is used to capture the dominating behavioural features of a nonlinear, possible uncertain, model under approximation. Unfortunately, the problem of how to best design a suitable hybrid system model has not yet been fully addressed. This paper proposes a new joint state measurement relative entropy rate based approach for this design purpose. Design examples and simulation studies are presented which highlight the benefits of our proposed design approaches.

Behavioural evidence for social preferences

A central topic in economics is the existence of social preferences. Behavioural economics in general has approached the issue from several angles. Controlled experimental settings, surveys, and field experiments are able to show that in a number of economic environments, people usually care about immaterial things such as fairness or equity of allocations. Findings from experimental economics specifically have lead to large increase in theories addressing social preferences. Most (pro)social phenomena are well understood in the experimental settings but very difficult to observe 'in the wild'. One criticism in this regard is that many findings are bound by the artificial environment of the computer lab or survey method used. A further criticism is that the traditional methods also fail to directly attribute the observed behaviour to the mental constructs that are expected to stand behind them. This thesis will first examine the usefulness of sports data to test social preference models in a field environment, thus overcoming limitations of the lab with regards to applicability to other - non-artificial - environments. The second major contribution of this research establishes a new neuroscientific tool - the measurement of the heart rate variability - to observe participants' emotional reactions in a traditional experimental setup.

Are alphabetic language-derived models of L2 reading relevant to L1 logographic background readers?

In this paper, we argue that second language (L2) reading research, which has been informed by studies involving first language (L1) alphabetic English reading, may be less relevant to L2 readers with non-alphabetic reading backgrounds, such as Chinese readers with an L1 logographic (Chinese character) learning history. We provide both neuroanatomical and behavioural evidence from Chinese language reading studies to support our claims. The paper concludes with an argument outlining the need for a universal L2 reading model which can adequately account for readers with diverse L1 orthographic language learning histories.