23 resultados para phone tapping

em CentAUR: Central Archive University of Reading - UK


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We performed mutual tapping experiments between two humans to investigate the conditions required for synchronized motion. A transition from an alternative mode to a synchronization mode was discovered under the same conditions when a subject changed from a reactive mode to an anticipation mode in single tapping experiments. Experimental results suggest that the cycle time for each tapping motion is tuned by a proportional control that is based on synchronization errors and cycle time errors. As the tapping frequency increases, the mathematical model based on the feedback control in the sensory-motor closed loop predicts a discrete mode transition as the gain factors of the proportional control decease. The conditions of the synchronization were shown as a consequence of the coupled dynamics based on the subsequent feedback loop in the sensory-motor system.

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This paper discusses ECG classification after parametrizing the ECG waveforms in the wavelet domain. The aim of the work is to develop an accurate classification algorithm that can be used to diagnose cardiac beat abnormalities detected using a mobile platform such as smart-phones. Continuous time recurrent neural network classifiers are considered for this task. Records from the European ST-T Database are decomposed in the wavelet domain using discrete wavelet transform (DWT) filter banks and the resulting DWT coefficients are filtered and used as inputs for training the neural network classifier. Advantages of the proposed methodology are the reduced memory requirement for the signals which is of relevance to mobile applications as well as an improvement in the ability of the neural network in its generalization ability due to the more parsimonious representation of the signal to its inputs.

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Disequilibria between Pb-210 and Ra-226 can be used to trace magma degassing, because the intermediate nuclides, particularly Rn-222, are volatile. Products of the 1980-1986 eruptions of Mount St. Helens have been analysed for (Pb-210/Ra-226). Both excesses and deficits of Pb-210 are encountered suggesting rapid gas transfer. The time scale of diffuse, non-eruptive gas escape prior to 1980 as documented by Pb-210 deficits is on the order of a decade using the model developed by Gauthier and Condomines (Earth Planet. Sci. Lett. 172 (1999) 111-126) for a non-renewed magma chamber and efficient Rn removal. The time required to build-up Pb-210 excess is much shorter (months) as can be observed from steady increases of (Pb-210/Ra-226) with time during 1980-1982. The formation of Pb-210 excess requires both rapid gas transport through the magma and periodic blocking of gas escape routes. Superposed on this time trend is the natural variability of (Pb-210/Ra-226) in a single eruption caused by tapping magma from various depths. The two time scales of gas transport, to create both Pb-210 deficits and Pb-210 excesses, cannot be reconciled in a single event. Rather Pb-210 deficits are associated with pre-eruptive diffuse degassing, while Pb-210 excesses document the more vigorous degassing associated with eruption and recharge of the system. (c) 2006 Elsevier B.V. All rights reserved.

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Short-term memory (STM) has often been considered to be a central resource in cognition. This study addresses its role in rapid serial visual presentation (RSVP) tasks tapping into temporal attention-the attentional blink (AB). Various STM operations are tested for their impact on performance and, in particular, on the AB. Memory tasks were found to exert considerable impact on general performance but the size of the AB was more or less immune to manipulations of STM load. Likewise, the AB was unaffected by manipulating the match between items held in STM and targets or temporally close distractors in the RSVP stream. The emerging picture is that STM resources, or their lack, play no role in the AB. Alternative accounts assuming serial consolidation, selection for action, and distractor-induced task-set interference are discussed.

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This RTD project, 2007-2009, is partly funded by the European Commission, in Framework Programme 6. It aims to assist elderly people for living well, independently and at case. ENABLE will provide a number of services for elderly people based on the new technology provided by mobile phones. The project is developing a Wrist unit with both integrated and external sensors, and with a radio frequency link to a mobile phone. Dedicated ENABLE software running on the wrist unit and mobile phone makes these services fully accessible for the elderly users. This paper outlines the fundamental motivation and the approach which currently is undertaken in order to collect the more detailed user needs and requirements. The general architecture and the design of the ENABLE system are outlined.

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The ENABLE project, which is partly funded by the European Commission, aims to assist elderly people to live well, independently and at case. In this project a wrist unit with both integrated and external sensors, and with a radio frequency link to a mobile phone. will be developed. ENABLE will provide a number of services for elderly people. among them also a remote control service for the home environment. This paper briefly describes the project in general and then focuses on the initial user needs investigation which was carried Out in early 2007 in six different European countries. The provisional findings are discussed and an outlook on the ongoing and future project work is given. A special focus of this paper is on the environmental control service.

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Transient episodes of synchronisation of neuronal activity in particular frequency ranges are thought to underlie cognition. Empirical mode decomposition phase locking (EMDPL) analysis is a method for determining the frequency and timing of phase synchrony that is adaptive to intrinsic oscillations within data, alleviating the need for arbitrary bandpass filter cut-off selection. It is extended here to address the choice of reference electrode and removal of spurious synchrony resulting from volume conduction. Spline Laplacian transformation and independent component analysis (ICA) are performed as pre-processing steps, and preservation of phase synchrony between synthetic signals. combined using a simple forward model, is demonstrated. The method is contrasted with use of bandpass filtering following the same preprocessing steps, and filter cut-offs are shown to influence synchrony detection markedly. Furthermore, an approach to the assessment of multiple EEG trials using the method is introduced, and the assessment of statistical significance of phase locking episodes is extended to render it adaptive to local phase synchrony levels. EMDPL is validated in the analysis of real EEG data, during finger tapping. The time course of event-related (de)synchronisation (ERD/ERS) is shown to differ from that of longer range phase locking episodes, implying different roles for these different types of synchronisation. It is suggested that the increase in phase locking which occurs just prior to movement, coinciding with a reduction in power (or ERD) may result from selection of the neural assembly relevant to the particular movement. (C) 2009 Elsevier B.V. All rights reserved.

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We followed 100 university students in the UK for one week, instructing them to record all face-to-face, phone and digital contacts during the day as well as their positive and negative affect. We wanted to see how positive and negative affect spread around a social network while taking into account participants’ socio-demographic data, personality, general health and gratitude scores. We focused on the participants’ connections with those in their class; excluding friends and family outside this group. The data was analysed using actor-based models implemented in SIENA. Results show differences between positive and negative affect dynamics in this environment and an influence of personality traits on the average number and rate of communication.

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Although the Unified Huntington's Disease Rating Scale (UHDRS) is widely used in the assessment of Huntington disease (HD), the ability of individual items to discriminate individual differences in motor or behavioral manifestations has not been extensively studied in HD gene expansion carriers without a motor-defined clinical diagnosis (ie, prodromal-HD or prHD). To elucidate the relationship between scores on individual motor and behavioral UHDRS items and total score for each subscale, a nonparametric item response analysis was performed on retrospective data from 2 multicenter longitudinal studies. Motor and behavioral assessments were supplied for 737 prHD individuals with data from 2114 visits (PREDICT-HD) and 686 HD individuals with data from 1482 visits (REGISTRY). Option characteristic curves were generated for UHDRS subscale items in relation to their subscale score. In prHD, overall severity of motor signs was low, and participants had scores of 2 or above on very few items. In HD, motor items that assessed ocular pursuit, saccade initiation, finger tapping, tandem walking, and to a lesser extent, saccade velocity, dysarthria, tongue protrusion, pronation/supination, Luria, bradykinesia, choreas, gait, and balance on the retropulsion test were found to discriminate individual differences across a broad range of motor severity. In prHD, depressed mood, anxiety, and irritable behavior demonstrated good discriminative properties. In HD, depressed mood demonstrated a good relationship with the overall behavioral score. These data suggest that at least some UHDRS items appear to have utility across a broad range of severity, although many items demonstrate problematic features.

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The plethora, and mass take up, of digital communication tech- nologies has resulted in a wealth of interest in social network data collection and analysis in recent years. Within many such networks the interactions are transient: thus those networks evolve over time. In this paper we introduce a class of models for such networks using evolving graphs with memory dependent edges, which may appear and disappear according to their recent history. We consider time discrete and time continuous variants of the model. We consider the long term asymptotic behaviour as a function of parameters controlling the memory dependence. In particular we show that such networks may continue evolving forever, or else may quench and become static (containing immortal and/or extinct edges). This depends on the ex- istence or otherwise of certain infinite products and series involving age dependent model parameters. To test these ideas we show how model parameters may be calibrated based on limited samples of time dependent data, and we apply these concepts to three real networks: summary data on mobile phone use from a developing region; online social-business network data from China; and disaggregated mobile phone communications data from a reality mining experiment in the US. In each case we show that there is evidence for memory dependent dynamics, such as that embodied within the class of models proposed here.

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We propose and analyse a class of evolving network models suitable for describing a dynamic topological structure. Applications include telecommunication, on-line social behaviour and information processing in neuroscience. We model the evolving network as a discrete time Markov chain, and study a very general framework where, conditioned on the current state, edges appear or disappear independently at the next timestep. We show how to exploit symmetries in the microscopic, localized rules in order to obtain conjugate classes of random graphs that simplify analysis and calibration of a model. Further, we develop a mean field theory for describing network evolution. For a simple but realistic scenario incorporating the triadic closure effect that has been empirically observed by social scientists (friends of friends tend to become friends), the mean field theory predicts bistable dynamics, and computational results confirm this prediction. We also discuss the calibration issue for a set of real cell phone data, and find support for a stratified model, where individuals are assigned to one of two distinct groups having different within-group and across-group dynamics.

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This paper proposes hybrid capital securities as a significant part of senior bank executive incentive compensation in light of Basel III, a new global regulatory standard on bank capital adequacy and liquidity agreed by the members of the Basel Committee on Banking Supervision. The committee developed Basel III in a response to the deficiencies in financial regulation brought about by the global financial crisis. Basel III strengthens bank capital requirements and introduces new regulatory requirements on bank liquidity and bank leverage. The hybrid bank capital securities we propose for bank executives’ compensation are preferred shares and subordinated debt that the June 2004 Basel II regulatory framework recognised as other admissible forms of capital. The past two decades have witnessed dramatic increase in performance-related pay in the banking industry. Stakeholders such as shareholders, debtholders and regulators criticise traditional cash and equity-based compensation for encouraging bank executives’ excessive risk taking and short-termism, which has resulted in the failure of risk management in high profile banks during the global financial crisis. Paying compensation in the form of hybrid bank capital securities may align the interests of executives with those of stakeholders and help banks regain their reputation for prudence after years of aggressive risk-taking. Additionally, banks are desperately seeking to raise capital in order to bolster balance sheets damaged by the ongoing credit crisis. Tapping their own senior employees with large incentive compensation packages may be a viable additional source of capital that is politically acceptable in times of large-scale bailouts of the financial sector and economically wise as it aligns the interests of the executives with the need for a stable financial system.

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Context: Emotion regulation is critically disrupted in depression and use of paradigms tapping these processes may uncover essential changes in neurobiology during treatment. In addition, as neuroimaging outcome studies of depression commonly utilize solely baseline and endpoint data – which is more prone to week-to week noise in symptomatology – we sought to use all data points over the course of a six month trial. Objective: To examine changes in neurobiology resulting from successful treatment. Design: Double-blind trial examining changes in the neural circuits involved in emotion regulation resulting from one of two antidepressant treatments over a six month trial. Participants were scanned pretreatment, at 2 months and 6 months posttreatment. Setting: University functional magnetic resonance imaging facility. Participants: 21 patients with Major Depressive Disorder and without other Axis I or Axis II diagnoses and 14 healthy controls. Interventions: Venlafaxine XR (doses up to 300mg) or Fluoxetine (doses up to 80mg). Main Outcome Measure: Neural activity, as measured using functional magnetic resonance imaging during performance of an emotion regulation paradigm as well as regular assessments of symptom severity by the Hamilton Rating Scale for Depression. To utilize all data points, slope trajectories were calculated for rate of change in depression severity as well as rate of change of neural engagement. Results: Those depressed individuals showing the steepest decrease in depression severity over the six months were those individuals showing the most rapid increases in BA10 and right DLPFC activity when regulating negative affect over the same time frame. This relationship was more robust than when using solely the baseline and endpoint data. Conclusions: Changes in PFC engagement when regulating negative affect correlate with changes in depression severity over six months. These results are buttressed by calculating these statistics which are more reliable and robust to week-to-week variation than difference scores.