Search results for "Artificial"
showing 10 items of 7394 documents
A gearbox model for processing large volumes of data by using pipeline systems encapsulated into virtual containers
2020
Software pipelines enable organizations to chain applications for adding value to contents (e.g., confidentially, reliability, and integrity) before either sharing them with partners or sending them to the cloud. However, the pipeline components add overhead when processing large volumes of data, which can become critical in real-world scenarios. This paper presents a gearbox model for processing large volumes of data by using pipeline systems encapsulated into virtual containers. In this model, the gears represent applications, whereas gearboxes represent software pipelines. This model was implemented as a collaborative system that automatically performs Gear up (by using parallel patterns…
The Three Steps of Clustering in the Post-Genomic Era: A Synopsis
2011
Clustering is one of the most well known activities in scientific investigation and the object of research in many disciplines, ranging from Statistics to Computer Science. Following Handl et al., it can be summarized as a three step process: (a) choice of a distance function; (b) choice of a clustering algorithm; (c) choice of a validation method. Although such a purist approach to clustering is hardly seen in many areas of science, genomic data require that level of attention, if inferences made from cluster analysis have to be of some relevance to biomedical research. Unfortunately, the high dimensionality of the data and their noisy nature makes cluster analysis of genomic data particul…
Responsible cognitive digital clones as decision-makers: A design science research study
2022
This study uses a design science research methodology to develop and evaluate the Pi-Mind agent, an information technology artefact that acts as a responsible, resilient, ubiquitous cognitive clone – or a digital copy – and an autonomous representative of a human decision-maker. Pi-Mind agents can learn the decision-making capabilities of their “donors” in a specific training environment based on generative adversarial networks. A trained clone can be used by a decision-maker as an additional resource for one’s own cognitive enhancement, as an autonomous representative, or even as a replacement when appropriate. The assumption regarding this approach is as follows: when someone was forced t…
A Non-Local Mode-I Cohesive Model for Ascending Thoracic Aorta Dissections (ATAD)
2018
This paper presents a non-local interface mechanical model to describe aortic dissection. In this regard, the mode-I debonding problem based on a cohesive zone modeling is endowed with non-local terms to include long-range interactions that are present in multi-layered biological tissue. Such non-local effects are related to the collagen fibers that transmit forces between non-adjacent elements. Numerical simulations are provided with different values of the non-local parameters in order to show the effect of the non-locality during the debonding processes.
Indeterminacy Reduction in Agent Communication Using a Semantic Language
2015
In recent years, the importance of vagueness and uncertainty in the messages exchanged between agents has been highlighted, mainly due to the ubiquitous nature of the (artificial or human) agents’ communication. The imprecision in the communication becomes more significant when the autonomy of the agents increases or the number of exchanged messages for a communicative goal is limited. In this paper we conjugate ideas drawn from situation semantics theory, human communication, and the multi-agent systems (MAS) field to reduce the impact of vagueness and uncertainty present in the communication. The main advances are achieved with the help of context information, collaboration and reinforcem…
HOWERD: A Hidden Markov Model for Automatic OWL-ERD Alignment
2016
The HOWERD model for estimating the most likely alignment between an OWL ontology and an Entity Relation Diagram (ERD) is presented. Automatic alignment between relational schema and ontology represents a big challenge in Semantic Web research due to the different expressiveness of these representations. A relational schema is less expressive than the ontology; this is a non trivial problem when accessing data via an ontology and for ontology storing by means of a relational schema. Existent alignment methodologies fail in loosing some contents of the involved representations because the ontology captures more semantic information, and several elements are left unaligned. HOWERD relies on a…
Spatialization of the Semantic Web
2012
syntax for Horn-like rules. The SWRL as the form, antecedentconsequent, where both antecedent and consequent are conjunctions of atoms written a1^ ... ^ an. Atoms in rules can be of the form C(x), P(x,y), Q(x,z), sameAs(x,y), differentFrom(x,y), or builtIn(pred, z1, ..., zn), where C is an OWL description, P is an OWL individual-valued property, Q is an OWL data-valued property, pred is a datatype predicate URIref, x and y are either individual-valued variables or OWL individuals, and z, z1, ... zn are either data-valued variables or OWL data literals. An OWL data literal is either a typed literal or a plain literal. Variables are indicated by using the standard convention of prefixing the…
Applying fully tensorial ICA to fMRI data
2016
There are two aspects in functional magnetic resonance imaging (fMRI) data that make them awkward to analyse with traditional multivariate methods - high order and high dimension. The first of these refers to the tensorial nature of observations as array-valued elements instead of vectors. Although this can be circumvented by vectorizing the array, doing so simultaneously loses all the structural information in the original observations. The second aspect refers to the high dimensionality along each dimension making the concept of dimension reduction a valuable tool in the processing of fMRI data. Different methods of tensor dimension reduction are currently gaining popUlarity in literature…
Análisis de un autómata clasificador de imágenes. Implicaciones filosóficas sobre los conceptos.
2017
El presente trabajo se ocupa de la construcción de un clasificador visual automático (un programa de ordenador, en realidad) de imágenes basado en regresiones logísticas. Se pretende, además, comprobar su eficacia en la realización de dicha tarea (la clasificación de imágenes), y reflexionar sobre las implicaciones filosóficas de los resultados obtenidos. En la introducción se apuntarán, en términos generales, la problemática que suscita el reconocimiento de imágenes por ordenador. Después se plantea una situación concreta, en un escenario típico de recuperación de información visual, donde se realiza un experimento que permitirá extraer datos empíricos (capítulo 2), y a continuación se des…
From imprecise probability assessments to conditional probabilities with quasi additive classes of conditioning events
2012
In this paper, starting from a generalized coherent (i.e. avoiding uniform loss) intervalvalued probability assessment on a finite family of conditional events, we construct conditional probabilities with quasi additive classes of conditioning events which are consistent with the given initial assessment. Quasi additivity assures coherence for the obtained conditional probabilities. In order to reach our goal we define a finite sequence of conditional probabilities by exploiting some theoretical results on g-coherence. In particular, we use solutions of a finite sequence of linear systems.