Search results for "artificial intelligence"
showing 10 items of 6122 documents
Modeling and Query Language for Hospitals
2013
So far the traditional process modeling languages have found a limited use in the hospital settings. One of the reasons behind this delay has been the lack of clear definition of the sequence of activities that are carried out in the hospital. We propose a new modeling language (as a profile of UML Class diagrams) that captures all the useful features from various UML diagrams and can be used in modeling of the hospitals. Based on the modeling language, we have developed an easy-to-perceive graphical query language, which allows the physicians to retrieve directly from the various hospital databases information they need to better understand the flow of clinical processes.
Vagueness expressions in Italian, Spanish and English task-oriented dialogues
2017
In this article, we present a corpus-based analysis on the use of Vagueness Expressions (VEs) in Italian, Spanish and English in Task-oriented Dialogues. Following the distinction among informational, relational and discourse vagueness (Voghera 2012), we compare the width of the functional space of the most frequent VEs. In particular we investigate whether and to what extent the VEs cover all the types of vagueness in the three languages. Quantitative and qualitative analysis brings evidence about a high convergence in the vagueness functions expressed by the VEs of the three languages.
Terminología y traducción económica francés-español: evaluación de recursos terminológicos en el ámbito contable
2014
The aim of this paper is to evaluate a series of terminology resources and determine their suitability to the practice of French-Spanish translation of accounting documents. First we identify the terminology needs of a specific group of translator trainees when facing business translation, as well as the resources they use particularly when translating annual accounts. Then, we select various terminology resources used in this context and evaluate them according to their needs. The results suggest the development of a French-Spanish dictionary of accounting terms adapted to the terminology needs of the practice of translation in this area.
Pervasive access to MRI bias artifact suppression service on a grid.
2009
Bias artifact corrupts magnetic resonance images in such a way that the image is afflicted by illumination variations. Some of the authors proposed the Exponential Entropy Driven - Homomorphic Unsharp Masking (E2D-HUM) algorithm that corrects this artifact without any a priori hypothesis about the tissues or the Magnetic Resonance image modality. Moreover, E2D-HUM does not care about the body part under examination and does not require any particular training task. People who want to use this algorithm, which is Matlab-based, have to set their own computers in order to execute it. Furthermore, they have to be Matlab-skilled to exploit all the features of the algorithm. In our work we propos…
Learning Automaton Based On-Line Discovery and Tracking of Spatio-temporal Event Patterns
2010
Published version of an article from the book: Lecture Notes in Computer Science, 2010, Volume 6230/2010, 327-338. The original publication is available at Springerlink. http://dx.doi.org/10.1007/978-3-642-15246-7_31 Discovering and tracking of spatio-temporal patterns in noisy sequences of events is a difficult task that has become increasingly pertinent due to recent advances in ubiquitous computing, such as community-based social networking applications. The core activities for applications of this class include the sharing and notification of events, and the importance and usefulness of these functionalites increases as event-sharing expands into larger areas of one’s life. Ironically, …
A vision agent for mobile robot navigation in time-variable environments
2002
We present an architecture for mobile robot navigation based on Bayesian networks. The architecture allows a robot to plan the correct path inside an environment with dynamic obstacles. Interactions between the robot and the environment are based on a powerful vision agent. The results of simulations, showing the effectiveness of the approach, are described.
ERP denoising in multichannel EEG data using contrasts between signal and noise subspaces
2009
Abstract In this paper, a new method intended for ERP denoising in multichannel EEG data is discussed. The denoising is done by separating ERP/noise subspaces in multidimensional EEG data by a linear transformation and the following dimension reduction by ignoring noise components during inverse transformation. The separation matrix is found based on the assumption that ERP sources are deterministic for all repetitions of the same type of stimulus within the experiment, while the other noise sources do not obey the determinancy property. A detailed derivation of the technique is given together with the analysis of the results of its application to a real high-density EEG data set. The inter…
Developing Self-Awareness in Robots via Inner Speech
2019
The experience of inner speech is a common one. Such a dialogue accompanies the introspection of mental life and fulfills essential roles in human behavior, such as self-restructuring, self-regulation, and re-focusing on attentional resources. Although the underpinning of inner speech is mostly investigated in psychological and philosophical fields, the research in robotics generally does not address such a form of self-aware behavior. Existing models of inner speech inspire computational tools to provide a robot with this form of self-awareness. Here, the widespread psychological models of inner speech are reviewed, and a cognitive architecture for a robot implementing such a capability is…
The Average State Complexity of the Star of a Finite Set of Words Is Linear
2008
We prove that, for the uniform distribution over all sets Xof m(that is a fixed integer) non-empty words whose sum of lengths is n, $\mathcal{D}_X$, one of the usual deterministic automata recognizing X*, has on average $\mathcal{O}(n)$ states and that the average state complexity of X*is i¾?(n). We also show that the average time complexity of the computation of the automaton $\mathcal{D}_X$ is $\mathcal{O}(n\log n)$, when the alphabet is of size at least three.
On achieving near-optimal “Anti-Bayesian” Order Statistics-Based classification fora asymmetric exponential distributions
2013
Published version of a Chapter in the book: Computer Analysis of Images and Patterns. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-642-40261-6_44 This paper considers the use of Order Statistics (OS) in the theory of Pattern Recognition (PR). The pioneering work on using OS for classification was presented in [1] for the Uniform distribution, where it was shown that optimal PR can be achieved in a counter-intuitive manner, diametrically opposed to the Bayesian paradigm, i.e., by comparing the testing sample to a few samples distant from the mean - which is distinct from the optimal Bayesian paradigm. In [2], we showed that the results could be extended for a few sym…