22,839 research outputs found
A Probabilistic Logic Programming Event Calculus
We present a system for recognising human activity given a symbolic
representation of video content. The input of our system is a set of
time-stamped short-term activities (STA) detected on video frames. The output
is a set of recognised long-term activities (LTA), which are pre-defined
temporal combinations of STA. The constraints on the STA that, if satisfied,
lead to the recognition of a LTA, have been expressed using a dialect of the
Event Calculus. In order to handle the uncertainty that naturally occurs in
human activity recognition, we adapted this dialect to a state-of-the-art
probabilistic logic programming framework. We present a detailed evaluation and
comparison of the crisp and probabilistic approaches through experimentation on
a benchmark dataset of human surveillance videos.Comment: Accepted for publication in the Theory and Practice of Logic
Programming (TPLP) journa
Indexing the Event Calculus with Kd-trees to Monitor Diabetes
Personal Health Systems (PHS) are mobile solutions tailored to monitoring
patients affected by chronic non communicable diseases. A patient affected by a
chronic disease can generate large amounts of events. Type 1 Diabetic patients
generate several glucose events per day, ranging from at least 6 events per day
(under normal monitoring) to 288 per day when wearing a continuous glucose
monitor (CGM) that samples the blood every 5 minutes for several days. This is
a large number of events to monitor for medical doctors, in particular when
considering that they may have to take decisions concerning adjusting the
treatment, which may impact the life of the patients for a long time. Given the
need to analyse such a large stream of data, doctors need a simple approach
towards physiological time series that allows them to promptly transfer their
knowledge into queries to identify interesting patterns in the data. Achieving
this with current technology is not an easy task, as on one hand it cannot be
expected that medical doctors have the technical knowledge to query databases
and on the other hand these time series include thousands of events, which
requires to re-think the way data is indexed. In order to tackle the knowledge
representation and efficiency problem, this contribution presents the kd-tree
cached event calculus (\ceckd) an event calculus extension for knowledge
engineering of temporal rules capable to handle many thousands events produced
by a diabetic patient. \ceckd\ is built as a support to a graphical interface
to represent monitoring rules for diabetes type 1. In addition, the paper
evaluates the \ceckd\ with respect to the cached event calculus (CEC) to show
how indexing events using kd-trees improves scalability with respect to the
current state of the art.Comment: 24 pages, preliminary results calculated on an implementation of
CECKD, precursor to Journal paper being submitted in 2017, with further
indexing and results possibilities, put here for reference and chronological
purposes to remember how the idea evolve
Spatial movement pattern recognition in soccer based on relative player movements
Knowledge of spatial movement patterns in soccer occurring on a regular basis can give a soccer coach, analyst or reporter insights in the playing style or tactics of a group of players or team. Furthermore, it can support a coach to better prepare for a soccer match by analysing (trained) movement patterns of both his own as well as opponent players. We explore the use of the Qualitative Trajectory Calculus (QTC), a spatiotemporal qualitative calculus describing the relative movement between objects, for spatial movement pattern recognition of players movements in soccer. The proposed method allows for the recognition of spatial movement patterns that occur on different parts of the field and/or at different spatial scales. Furthermore, the Levenshtein distance metric supports the recognition of similar movements that occur at different speeds and enables the comparison of movements that have different temporal lengths. We first present the basics of the calculus, and subsequently illustrate its applicability with a real soccer case. To that end, we present a situation where a user chooses the movements of two players during 20 seconds of a real soccer match of a 2016-2017 professional soccer competition as a reference fragment. Following a pattern matching procedure, we describe all other fragments with QTC and calculate their distance with the QTC representation of the reference fragment. The top-k most similar fragments of the same match are presented and validated by means of a duo-trio test. The analyses show the potential of QTC for spatial movement pattern recognition in soccer
Probabilistic foundations of quantum mechanics and quantum information
We discuss foundation of quantum mechanics (interpretations, superposition,
principle of complementarity, locality, hidden variables) and quantum
information theory.Comment: Contextual probabilistic viewpoint to quantum cryptography projec
Stochastic Calculus of Wrapped Compartments
The Calculus of Wrapped Compartments (CWC) is a variant of the Calculus of
Looping Sequences (CLS). While keeping the same expressiveness, CWC strongly
simplifies the development of automatic tools for the analysis of biological
systems. The main simplification consists in the removal of the sequencing
operator, thus lightening the formal treatment of the patterns to be matched in
a term (whose complexity in CLS is strongly affected by the variables matching
in the sequences).
We define a stochastic semantics for this new calculus. As an application we
model the interaction between macrophages and apoptotic neutrophils and a
mechanism of gene regulation in E.Coli
Artificial Intelligence and Systems Theory: Applied to Cooperative Robots
This paper describes an approach to the design of a population of cooperative
robots based on concepts borrowed from Systems Theory and Artificial
Intelligence. The research has been developed under the SocRob project, carried
out by the Intelligent Systems Laboratory at the Institute for Systems and
Robotics - Instituto Superior Tecnico (ISR/IST) in Lisbon. The acronym of the
project stands both for "Society of Robots" and "Soccer Robots", the case study
where we are testing our population of robots. Designing soccer robots is a
very challenging problem, where the robots must act not only to shoot a ball
towards the goal, but also to detect and avoid static (walls, stopped robots)
and dynamic (moving robots) obstacles. Furthermore, they must cooperate to
defeat an opposing team. Our past and current research in soccer robotics
includes cooperative sensor fusion for world modeling, object recognition and
tracking, robot navigation, multi-robot distributed task planning and
coordination, including cooperative reinforcement learning in cooperative and
adversarial environments, and behavior-based architectures for real time task
execution of cooperating robot teams
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