Learning facial-expression models with crowdsourcing

The computational power is increasing day by day. Despite that, there are some tasks that are still difficult or even impossible for a computer to perform. For example, while identifying a facial expression is easy for a human, for a computer it is an area in development. To tackle this and similar issues, crowdsourcing has grown as a way to use human computation in a large scale. Crowdsourcing is a novel approach to collect labels in a fast and cheap manner, by sourcing the labels from the crowds. However, these labels lack reliability since annotators are not guaranteed to have any expertise in the field. This fact has led to a new research area where we must create or adapt annotation models to handle these weaklylabeled data. Current techniques explore the annotators’ expertise and the task difficulty as variables that influences labels’ correction. Other specific aspects are also considered by noisy-labels analysis techniques. The main contribution of this thesis is the process to collect reliable crowdsourcing labels for a facial expressions dataset. This process consists in two steps: first, we design our crowdsourcing tasks to collect annotators labels; next, we infer the true label from the collected labels by applying state-of-art crowdsourcing algorithms. At the same time, a facial expression dataset is created, containing 40.000 images and respective labels. At the end, we publish the resulting dataset.

Peer interaction and learning opportunities in cohesive and less cohesive L2 classrooms

The present study investigates peer to peer oral interaction in two task based language teaching classrooms, one of which was a self-declared cohesive group, and the other a self- declared less cohesive group, both at B1 level. It studies how learners talk cohesion into being and considers how this talk leads to learning opportunities in these groups. The study was classroom-based and was carried out over the period of an academic year. Research was conducted in the classrooms and the tasks were part of regular class work. The research was framed within a sociocognitive perspective of second language learning and data came from a number of sources, namely questionnaires, interviews and audio recorded talk of dyads, triads and groups of four students completing a total of eight oral tasks. These audio recordings were transcribed and analysed qualitatively for interactions which encouraged a positive social dimension and behaviours which led to learning opportunities, using conversation analysis. In addition, recordings were analysed quantitatively for learning opportunities and quantity and quality of language produced. Results show that learners in both classes exhibited multiple behaviours in interaction which could promote a positive social dimension, although behaviours which could discourage positive affect amongst group members were also found. Analysis of interactions also revealed the many ways in which learners in both the cohesive and less cohesive class created learning opportunities. Further qualitative analysis of these interactions showed that a number of factors including how learners approach a task, the decisions they make at zones of interactional transition and the affective relationship between participants influence the amount of learning opportunities created, as well as the quality and quantity of language produced. The main conclusion of the study is that it is not the cohesive nature of the group as a whole but the nature of the relationship between the individual members of the small group completing the task which influences the effectiveness of oral interaction for learning.This study contributes to our understanding of the way in which learners individualise the learning space and highlights the situated nature of language learning. It shows how individuals interact with each other and the task, and how talk in interaction changes moment-by-moment as learners react to the ‘here and now’ of the classroom environment.

Learning joint representations for order and timing of perceptual-motor sequences: a dynamic neural field approach

Many of our everyday tasks require the control of the serial order and the timing of component actions. Using the dynamic neural field (DNF) framework, we address the learning of representations that support the performance of precisely time action sequences. In continuation of previous modeling work and robotics implementations, we ask specifically the question how feedback about executed actions might be used by the learning system to fine tune a joint memory representation of the ordinal and the temporal structure which has been initially acquired by observation. The perceptual memory is represented by a self-stabilized, multi-bump activity pattern of neurons encoding instances of a sensory event (e.g., color, position or pitch) which guides sequence learning. The strength of the population representation of each event is a function of elapsed time since sequence onset. We propose and test in simulations a simple learning rule that detects a mismatch between the expected and realized timing of events and adapts the activation strengths in order to compensate for the movement time needed to achieve the desired effect. The simulation results show that the effector-specific memory representation can be robustly recalled. We discuss the impact of the fast, activation-based learning that the DNF framework provides for robotics applications.

Off-line simulation inspires insight: a neurodynamics approach to efficient robot task learning

There is currently an increasing demand for robots able to acquire the sequential organization of tasks from social learning interactions with ordinary people. Interactive learning-by-demonstration and communication is a promising research topic in current robotics research. However, the efficient acquisition of generalized task representations that allow the robot to adapt to different users and contexts is a major challenge. In this paper, we present a dynamic neural field (DNF) model that is inspired by the hypothesis that the nervous system uses the off-line re-activation of initial memory traces to incrementally incorporate new information into structured knowledge. To achieve this, the model combines fast activation-based learning to robustly represent sequential information from single task demonstrations with slower, weight-based learning during internal simulations to establish longer-term associations between neural populations representing individual subtasks. The efficiency of the learning process is tested in an assembly paradigm in which the humanoid robot ARoS learns to construct a toy vehicle from its parts. User demonstrations with different serial orders together with the correction of initial prediction errors allow the robot to acquire generalized task knowledge about possible serial orders and the longer term dependencies between subgoals in very few social learning interactions. This success is shown in a joint action scenario in which ARoS uses the newly acquired assembly plan to construct the toy together with a human partner.

A behavioral study of alpha-1b adrenergic receptor knockout mice: increased reaction to novelty and selectively reduced learning capacities.

Knockout mice lacking the alpha-1b adrenergic receptor were tested in behavioral experiments. Reaction to novelty was first assessed in a simple test in which the time taken by the knockout mice and their littermate controls to enter a second compartment was compared. Then the mice were tested in an open field to which unknown objects were subsequently added. Special novelty was introduced by moving one of the familiar objects to another location in the open field. Spatial behavior and memory were further studied in a homing board test, and in the water maze. The alpha-1b knockout mice showed an enhanced reactivity to new situations. They were faster to enter the new environment, covered longer paths in the open field, and spent more time exploring the new objects. They reacted like controls to modification inducing spatial novelty. In the homing board test, both the knockout mice and the control mice seemed to use a combination of distant visual and proximal olfactory cues, showing place preference only if the two types of cues were redundant. In the water maze the alpha-1b knockout mice were unable to learn the task, which was confirmed in a probe trial without platform. They were perfectly able, however, to escape in a visible platform procedure. These results confirm previous findings showing that the noradrenergic pathway is important for the modulation of behaviors such as reaction to novelty and exploration, and suggest that this is mediated, at least partly, through the alpha-1b adrenergic receptors. The lack of alpha-1b adrenergic receptors in spatial orientation does not seem important in cue-rich tasks but may interfere with orientation in situations providing distant cues only.

MENTAL IMAGERY IN PERCEPTUAL LEARNING

L'imagerie mentale est définie comme une expérience similaire à la perception mais se déroulant en l'absence d'une stimulation physique. Des recherches antérieures ont montré que l'imagerie mentale améliore la performance dans certains domaines, comme par exemple le domaine moteur. Cependant, son rôle dans l'apprentissage perceptif n'a pas encore été étudié. L'apprentissage perceptif correspond à l'amélioration permanente des performances suite à la répétition de la même tâche. Cette thèse présente une série des résultats empiriques qui montrent que l'apprentissage perceptif peut aussi être achevé en l'absence des stimuli physiques. En effet, imaginer des stimuli visuels amène à une meilleure performance avec les stimuli réels. Donc, les processus sous-jacents l'apprentissage perceptif ne sont pas uniquement déclenchés par les stimuli sensoriels, mais également par des signaux internes. En plus, l'apprentissage perceptif à travers l'imagerie mentale ne se réalise que seule-ment quand les stimuli ne sont pas (complètement) présents, mais gaiement quand les stimuli montrés ne sont pas utiles quant à la résolution de la tâche. - Mental imagery is described as an experience that resembles pereeptnal ex-perience but which occurs in the absence ef a physical stimulation. Despite its beneficial effects in, among others, motor performance, the role of mental imagery m perceptual learning has not yet been addressed. Here we focus on a specific sensory modality: vision. Perceptual learning is the ability to improve perception in a stable way through the repetition of a given task Here I demonstrate by a series of empirical results that a perceptual improve¬ment can also occur in the absence of a stimulation. Imagining visual stimuli is sufficient for successful perceptual learning. Hence, processes underlying perceptual learning are not only stimulus-driven but can also be driven by internally generated signals. Moreover, I also show that perceptual learning via mental imagery can occur not only when physical stimuli are (partially) absent, but also in conditions where stimuli are uninformative with respect to the task that has to be learned.

Impairment of mossy fiber long-term potentiation and associative learning in pituitary adenylate cyclase activating polypeptide type I receptor-deficient Mice

The pituitary adenylate cyclase activating polypeptide (PACAP) type I receptor (PAC1) is a G-protein-coupled receptor binding the strongly conserved neuropeptide PACAP with 1000-fold higher affinity than the related peptide vasoactive intestinal peptide. PAC1-mediated signaling has been implicated in neuronal differentiation and synaptic plasticity. To gain further insight into the biological significance of PAC1-mediated signaling in vivo, we generated two different mutant mouse strains, harboring either a complete or a forebrain-specific inactivation of PAC1. Mutants from both strains show a deficit in contextual fear conditioning, a hippocampus-dependent associative learning paradigm. In sharp contrast, amygdala-dependent cued fear conditioning remains intact. Interestingly, no deficits in other hippocampus-dependent tasks modeling declarative learning such as the Morris water maze or the social transmission of food preference are observed. At the cellular level, the deficit in hippocampus-dependent associative learning is accompanied by an impairment of mossy fiber long-term potentiation (LTP). Because the hippocampal expression of PAC1 is restricted to mossy fiber terminals, we conclude that presynaptic PAC1-mediated signaling at the mossy fiber synapse is involved in both LTP and hippocampus-dependent associative learning.

CLFP intrinsic constraints-based group management of blended learning situations

When applying a Collaborative Learning Flow Pattern (CLFP) to structure sequences of activities in real contexts, one of the tasks is to organize groups of students according to the constraints imposed by the pattern. Sometimes,unexpected events occurring at runtime force this pre-defined distribution to be changed. In such situations, an adjustment of the group structures to be adapted to the new context is needed. If the collaborative pattern is complex, this group redefinitionmight be difficult and time consuming to be carried out in real time. In this context, technology can help on notifying the teacher which incompatibilitiesbetween the actual context and the constraints imposed by the pattern. This chapter presents a flexible solution for supporting teachers in the group organization profiting from the intrinsic constraints defined by a CLFPs codified in IMS Learning Design. A prototype of a web-based tool for the TAPPS and Jigsaw CLFPs and the preliminary results of a controlled user study are alsopresented as a first step towards flexible technological systems to support grouping tasks in this context.

Modes of acquisition of health literacy skills in informal learning contexts

In this article we try to analyze the learning processes of health literacy skills in informal contexts. We intend to broaden the understanding of the learning process beyond the formal contexts, thus contributing to the elucidation of health professionals on how individuals acquire and manage their knowledge in health matters. Given our goal, we use an analytic corpus constituted by one hundred autobiographical narratives written between 2006 and 2011, in educational contexts but with recognized potential for use in different scientific fields, including health. The results reveal the existence of three different types of modes of learning health literacy skills in informal context: : i) learning that takes place in action, in achieving daily tasks; ii) learning processes that result from problem solving; iii) learning that occurs in an unplanned manner, resulting from accidental circumstances and, in some cases, devoid of intentionality.

Intrahippocampal cholinergic grafts in aged rats compensate impairments in a radial maze and in a place learning task

Age-related cognitive impairments were studied in rats kept in semi-enriched conditions during their whole life, and tested during ontogeny and adult life in various classical spatial tasks. In addition, the effect of intrahippocampal grafts of fetal septal-diagonal band tissue, rich in cholinergic neurons, was studied in some of these subjects. The rats received bilateral cell suspensions when aged 23-24 months. Starting 4 weeks after grafting, they were trained during 5 weeks in an 8-arm maze made of connected plexiglass tunnels. No age-related impairment was detected during the first eight trials, when the maze shape was that of a classical radial maze in which the rats had already been trained when young. The older rats were impaired when the task was made more difficult by rendering two arms parallel to each other. They developed an important neglect of one of the parallel tunnels resulting in a high amount of errors before completion of the task. In addition, the old rats developed a systematic response pattern of visits to adjacent arms in a sequence, which was not observed in the younger subjects. None of these behaviours were observed in the old rats with a septal transplant. Sixteen weeks after grafting, another experiment was conducted in a homing hole board task. Rats were allowed to escape from a large circular arena through one hole out of many, and to reach home via a flexible tube under the table. The escape hole was at a fixed position according to distant room cues, and olfactory cues were made irrelevant by rotating the table between the trials. An additional cue was placed on the escape position. No age-related difference in escape was observed during training. During a probe trial with no hole connected and no proximal cue present, the old untreated rats were less clearly focussed on the training sector than were either the younger or the grafted old subjects. Taken together, these experiments indicate that enriched housing conditions and spatial training during adult life do not protect against all age-related deterioration in spatial ability. However, it might be that the considerable improvement observed in the grafted subjects results from an interaction between the graft treatment and the housing conditions.

Semantic domains and supersens tagging for domain-specific ontology learning

In this paper we propose a novel unsupervised approach to learning domain-specific ontologies from large open-domain text collections. The method is based on the joint exploitation of Semantic Domains and Super Sense Tagging for Information Retrieval tasks. Our approach is able to retrieve domain specific terms and concepts while associating them with a set of high level ontological types, named supersenses, providing flat ontologies characterized by very high accuracy and pertinence to the domain.

Analysis, modelling and classification of geospatial data using machine learning

The research considers the problem of spatial data classification using machine learning algorithms: probabilistic neural networks (PNN) and support vector machines (SVM). As a benchmark model simple k-nearest neighbor algorithm is considered. PNN is a neural network reformulation of well known nonparametric principles of probability density modeling using kernel density estimator and Bayesian optimal or maximum a posteriori decision rules. PNN is well suited to problems where not only predictions but also quantification of accuracy and integration of prior information are necessary. An important property of PNN is that they can be easily used in decision support systems dealing with problems of automatic classification. Support vector machine is an implementation of the principles of statistical learning theory for the classification tasks. Recently they were successfully applied for different environmental topics: classification of soil types and hydro-geological units, optimization of monitoring networks, susceptibility mapping of natural hazards. In the present paper both simulated and real data case studies (low and high dimensional) are considered. The main attention is paid to the detection and learning of spatial patterns by the algorithms applied.

Web Services for Bayesian Learning

In this demonstration we present our web services to perform Bayesian learning for classification tasks.

Spatial learning by rats across visually disconnected environments

Two spatial tasks were designed to test specific properties of spatial representation in rats. In the first task, rats were trained to locate an escape hole at a fixed position in a visually homogeneous arena. This arena was connected with a periphery where a full view of the room environment existed. Therefore, rats were dependent on their memory trace of the previous position in the periphery to discriminate a position within the central region. Under these experimental conditions, the test animals showed a significant discrimination of the training position without a specific local view. In the second task, rats were trained in a radial maze consisting of tunnels that were transparent at their distal ends only. Because the central part of the maze was non-transparent, rats had to plan and execute appropriate trajectories without specific visual feedback from the environment. This situation was intended to encourage the reliance on prospective memory of the non-visited arms in selecting the following move. Our results show that acquisition performance was only slightly decreased compared to that shown in a completely transparent maze and considerably higher than in a translucent maze or in darkness. These two series of experiments indicate (1) that rats can learn about the relative position of different places with no common visual panorama, and (2) that they are able to plan and execute a sequence of visits to several places without direct visual feed-back about their relative position.

Analysing Professional Discourse in Interactive Learning: Integrating Historical and Situational Perspectives

Peer-reviewed