Questions à mouvement multiple en bulgare

Ce mémoire examine les questions à mouvement multiple en bulgare, en accordant une importance particulière aux mécanismes qui régissent l’ordre des syntagmes interrogatifs antéposés. Outre la présentation d’un phénomène linguistique complexe et très intéressant, l’étude propose un aperçu critique des hypothèses les plus importantes émises au fil des ans à propos des interrogatives multiples. Dans un premier temps, nous discutons des différentes approches renfermant l’idée que l’ordre des mots interrogatifs au début de la proposition dépend entièrement des règles syntaxiques. Ensuite, nous présentons les analyses qui tentent d’expliquer la problématique en faisant appel à des traits spécifiques des syntagmes Qu-, tels que [animé] ou [lié au discours]. Le rôle de la topicalisation et de la focalisation dans la formation des questions multiples, les projections fonctionnelles de la « périphérie gauche » en bulgare accueillant différents syntagmes, ainsi que la résomption comptent également parmi les sujets traités dans ce mémoire.

Processing empty categories in a second language: When naturalistic exposure fills the (intermediate) gap

An ongoing debate on second language (L2) processing revolves around whether or not L2 learners process syntactic information similarly to monolinguals (L1), and what factors lead to a native-like processing. According to the Shallow Structure Hypothesis (Clahsen & Felser, 2006a), L2 learners’ processing does not include abstract syntactic features, such as intermediate gaps of wh-movement, but relies more on lexical/semantic information. Other researchers have suggested that naturalistic L2 exposure can lead to native-like processing (Dussias, 2003). This study investigates the effect of naturalistic exposure in processing wh-dependencies. Twenty-six advanced Greek learners of L2 English with an average nine years of naturalistic exposure, 30 with classroom exposure, and 30 native speakers of English completed a self-paced reading task with sentences involving intermediate gaps. L2 learners with naturalistic exposure showed evidence of native-like processing of the intermediate gaps, suggesting that linguistic immersion can lead to native-like abstract syntactic processing in the L2.

Extraposition in English and Spanish: A comparative study

451 p.

Impedance control is tuned to multiple directions of movement

Humans are able to learn tool-handling tasks, such as carving, demonstrating their competency to make and vary the direction of movements in unstable environments. It has been shown that when a single reaching movement is repeated in unstable dynamics, the central nervous system (CNS) learns an impedance internal model to compensate for the environment instability. However, there is still no explanation for how humans can learn to move in various directions in such environments. In this study, we investigated whether and how humans compensate for instability while learning two different reaching movements simultaneously. Results show that when performing movements in two different directions, separated by a 35° angle, the CNS was able to compensate for the unstable dynamics. After adaptation, the force was found to be similar to the free movement condition, but stiffness increased in the direction of instability, specifically for each direction of movement. Our findings suggest that the CNS either learned an internal model generalizing over different movements, or alternatively that it was able to switch between specific models acquired simultaneously. © 2008 IEEE.

Impedance control is selectively tuned to multiple directions of movement

Humans are able to learn tool-handling tasks, such as carving, demonstrating their competency to make movements in unstable environments with varied directions. When faced with a single direction of instability, humans learn to selectively co-contract their arm muscles tuning the mechanical stiffness of the limb end point to stabilize movements. This study examines, for the first time, subjects simultaneously adapting to two distinct directions of instability, a situation that may typically occur when using tools. Subjects learned to perform reaching movements in two directions, each of which had lateral instability requiring control of impedance. The subjects were able to adapt to these unstable interactions and switch between movements in the two directions; they did so by learning to selectively control the end-point stiffness counteracting the environmental instability without superfluous stiffness in other directions. This finding demonstrates that the central nervous system can simultaneously tune the mechanical impedance of the limbs to multiple movements by learning movement-specific solutions. Furthermore, it suggests that the impedance controller learns as a function of the state of the arm rather than a general strategy. © 2011 the American Physiological Society.

Modelling 3D camera movement for vibration characterisation and multiple object identification with application to lighting assessment

Utilising cameras as a means to survey the surrounding environment is becoming increasingly popular in a number of different research areas and applications. Central to using camera sensors as input to a vision system, is the need to be able to manipulate and process the information captured in these images. One such application, is the use of cameras to monitor the quality of airport landing lighting at aerodromes where a camera is placed inside an aircraft and used to record images of the lighting pattern during the landing phase of a flight. The images are processed to determine a performance metric. This requires the development of custom software for the localisation and identification of luminaires within the image data. However, because of the necessity to keep airport operations functioning as efficiently as possible, it is difficult to collect enough image data to develop, test and validate any developed software. In this paper, we present a technique to model a virtual landing lighting pattern. A mathematical model is postulated which represents the glide path of the aircraft including random deviations from the expected path. A morphological method has been developed to localise and track the luminaires under different operating conditions. © 2011 IEEE.

On the incremental learning and recognition of the pattern of movement of multiple labelled objects in dynamic scenes

In this paper we discuss combining incremental learning and incremental recognition to classify patterns consisting of multiple objects, each represented by multiple spatio-temporal features. Importantly the technique allows for ambiguity in terms of the positions of the start and finish of the pattern. This involves a progressive classification which considers the data at each time instance in the query and thus provides a probable answer before all the query information becomes available. We present two methods that combine incremental learning and incremental recognition: a time instance method and an overall best match method.

Learning people movement model from multiple cameras for behaviour recognition

In surveillance systems for monitoring people behaviours, it is important to build systems that can adapt to the signatures of people's tasks and movements in the environment. At the same time, it is important to cope with noisy observations produced by a set of cameras with possibly different characteristics. In previous work, we have implemented a distributed surveillance system designed for complex indoor environments [1]. The system uses the Abstract Hidden Markov mEmory Model (AHMEM) for modelling and specifying complex human behaviours that can take place in the environment. Given a sequence of observations from a set of cameras, the system employs approximate probabilistic inference to compute the likelihood of different possible behaviours in real-time. This paper describes the techniques that can be used to learn the different camera noise models and the human movement models to be used in this system. The system is able to monitor and classify people behaviours as data is being gathered, and we provide classification results showing the system is able to identify behaviours of people from their movement signatures.

Robust real-time bio-kinematic movement tracking using multiple kinects for tele-rehabilitation

This paper investigates the robust and accurate capture of human joint poses and bio-kinematic movements for exercise monitoring in real-time tele-rehabilitation applications. Recently developed model-based estimation ideas are used to improve the accuracy, robustness, and real-time characteristics considered vital for applications, where affordability and domestic use are the primary focus. We use the spatial diversity of the arbitrarily positioned Microsoft Kinect receivers to improve the reliability and promote the uptake of the concept. The skeleton-based information is fused to enhance accuracy and robustness, critical for biomedical applications. A specific version of a robust Kalman filter (KF) in a linear framework is employed to ensure superior estimator convergence and real-time use, compared to other commonly used filters. The algorithmic development was conducted in a generic form and computer simulations were conducted to verify our assertions. Hardware implementations were carried out to test the viability of the proposed state estimator in terms of the core requirements of reliability, accuracy, and real-time use. Performance of the overall system implemented in an information fusion context was evaluated against the commercially available and industry standard Vicon system for different exercise routines, producing comparable results with much less infrastructure and financial investment.

Book review : belonging in Oceania : movement, place-making and multiple identifications

Book review of Belonging in Oceania: Movement, Place-Making and Multiple Identifications by Elfriede Hermann, Wolfgang Kempf and Toon van Meijl.

Effect of Pedestrian Movement on MIMO-OFDM Channel Capacity in an Indoor Environment

Effects of pedestrian movement on multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) channel capacity have been investigated using experiment and simulation. The experiment was conducted at 5.2 GHz by a MIMO-OFDM packet transmission demonstrator using four transmitters and four receivers built in-house. Geometric optics based ray tracing technique was used to simulate the experimental scenarios. Changes in the channel capacity dynamic range have been analysed for different number of pedestrian (0-3) and antennas (2-4). Measurement and simulation results show that the dynamic range increases with the number of pedestrian and the number of antennas on the transmitter and receiver array.