The use and potential of artificial intelligence for supporting clinical observation of child behaviour.

Background: Observation of child behaviour provides valuable clinical information but often requires rigorous, tedious, repetitive and time expensive protocols. For this reason, tests requiring significant time for administration and rating are rarely used in clinical practice, however useful and effective they are. This article shows that Artificial Intelligence (AI), designed to capture and store the human ability to perform standardised tasks consistently, can alleviate this problem.

The School Attachment Monitor-A novel computational tool for assessment of attachment in middle childhood.

Background: Attachment research has been limited by the lack of quick and easy measures. We report development and validation of the School Attachment Monitor (SAM), a novel measure for largescale assessment of attachment in children aged 5-9, in the general population. SAM offers automatic presentation, on computer, of story-stems based on the Manchester Child Attachment Story Task (MCAST), without the need for trained administrators.

Infinite Feature Selection: A Graph-based Feature Filtering Approach.

We propose a filtering feature selection framework that considers subsets of features as paths in a graph, where a node is a feature and an edge indicates pairwise (customizable) relations among features, dealing with relevance and redundancy principles. By two different interpretations (exploiting properties of power series of matrices and relying on Markov chains fundamentals) we can evaluate the values of paths (i.e.

Automatic Recognition of Personality Profiles Using EEG Functional Connectivity During Emotional Processing.

Personality is the characteristic set of an individual's behavioral and emotional patterns that evolve from biological and environmental factors. The recognition of personality profiles is crucial in making human-computer interaction (HCI) applications realistic, more focused, and user friendly. The ability to recognize personality using neuroscientific data underpins the neurobiological basis of personality.

Social signals: from theory to applications.

The Special Issue Editorial introduces the research milieu in which Social Signal Processing originates, by merging computer scientists and social scientists and giving rise to this field in parallel with Human-Computer Interaction, Affective Computing, and Embodied Conversational Agents, all similarly characterized by high interdisciplinarity, stress on multimodality of communication, and the continuous loop from theory to simulation and application. Some frameworks of the cognitive and social processes underlying social signals are identified as reference points (Theory of Mind and Intersubjectivity, mirror neurons, and the ontogenesis and phylogenesis of communication), while three dichotomies (automatic vs. controlled, individualistic vs.

Conversation analysis at work: detection of conflict in competitive discussions through semi-automatic turn-organization analysis.

This study proposes a semi-automatic approach aimed at detecting conflict in conversations. The approach is based on statistical techniques capable of identifying turn-organization regularities associated with conflict. The only manual step of the process is the segmentation of the conversations into turns (time intervals during which only one person talks) and overlapping speech segments (time intervals during which several persons talk at the same time).

Offline recognition of unconstrained handwritten texts using HMMs and statistical language models.

This paper presents a system for the offline recognition of large vocabulary unconstrained handwritten texts. The only assumption made about the data is that it is written in English. This allows the application of Statistical Language Models in order to improve the performance of our system.

Noisy text categorization.

This work presents categorization experiments performed over noisy texts. By noisy, we mean any text obtained through an extraction process (affected by errors) from media other than digital texts (e.g.