Search results for "Embedding"
showing 10 items of 175 documents
The Group Mind Hypothesis between Social ontology and Philosophy of Mind: Some Critical Notes
2013
Some recent theoretical analyses of collective behavior in social ontology, philosophy of mind and situated cognitive science have proposed arguments to revive the notion of group mind as the proper bearer of joint cognitive processes and actions. In this paper I analyse two kinds of arguments supporting this view: first, since group reasons in joint actions claim, at least sometimes, to have a priority over individual reasons, then groups are psychologically autonomous from their members. Second, the structure of the causal and functional dynamics of individual and collective cognition mirror each other in such a way that, by parity of reasoning, we must talk of a collective mind as underl…
Leveraging Knowledge Graph Embedding Techniques for Industry 4.0 Use Cases
2018
Industry is evolving towards Industry 4.0, which holds the promise of increased exibility in manufacturing, better quality and improved productivity. A core actor of this growth is using sensors, which must capture data that can used in unforeseen ways to achieve a performance not achievable without them. However, the complexity of this improved setting is much greater than what is currently used in practice. Hence, it is imperative that the management cannot only be performed by human labor force, but part of that will be done by automated algorithms instead. A natural way to represent the data generated by this large amount of sensors, which are not acting measuring independent variables,…
Biased GraphWalks for RDF Graph Embeddings
2017
Knowledge Graphs have been recognized as a valuable source for background information in many data mining, information retrieval, natural language processing, and knowledge extraction tasks. However, obtaining a suitable feature vector representation from RDF graphs is a challenging task. In this paper, we extend the RDF2Vec approach, which leverages language modeling techniques for unsupervised feature extraction from sequences of entities. We generate sequences by exploiting local information from graph substructures, harvested by graph walks, and learn latent numerical representations of entities in RDF graphs. We extend the way we compute feature vector representations by comparing twel…
Global RDF Vector Space Embeddings
2017
Vector space embeddings have been shown to perform well when using RDF data in data mining and machine learning tasks. Existing approaches, such as RDF2Vec, use local information, i.e., they rely on local sequences generated for nodes in the RDF graph. For word embeddings, global techniques, such as GloVe, have been proposed as an alternative. In this paper, we show how the idea of global embeddings can be transferred to RDF embeddings, and show that the results are competitive with traditional local techniques like RDF2Vec. peerReviewed
Embeddings of graph braid and surface groups in right-angled Artin groups and braid groups
2003
We prove by explicit construction that graph braid groups and most surface groups can be embedded in a natural way in right-angled Artin groups, and we point out some consequences of these embedding results. We also show that every right-angled Artin group can be embedded in a pure surface braid group. On the other hand, by generalising to right-angled Artin groups a result of Lyndon for free groups, we show that the Euler characteristic -1 surface group (given by the relation x^2y^2=z^2) never embeds in a right-angled Artin group.
AI Ethics - Critical Reflections on Embedding Ethical Frameworks in AI Technology
2021
Embedding ethical frameworks in artificial intelligence (AI) technologies has been a popular topic for academic research for the past decade [1, 2, 3, 4, 5, 6, 7]. The approaches of the studies differ in how AI technology, ethics, role of technical artefacts and socio-technical aspects of AI are perceived. In addition, most studies define insufficiently what the connection between the process of embedding ethical frameworks to AI technology and the larger framework of AI ethics is. These deficiencies have caused that the concept of AI ethics and the construct of embedding ethical parameters into AI are used in an ambiguous, rather than in a complementary manner. One reason for the ambiguity…
Embedding Preschool Assessment Methods into Digital Learning Games to Predict Early Reading Skills
2017
The aim of this pilot study was to explore the predictive accuracy of computer-based assessment tasks (embedded within the GraphoLearn digital learning game platform) in identifying slow and normal readers. The results were compared to those obtained from the traditional paper-and-pencil tasks currently used to assess school readiness in Finland. The data were derived from a cohort of preschool-age children (mean age 6.7 years, N = 57) from a town in central Finland. A year later, at the end of first grade, participants were categorized as either slow (n = 11) or normal readers (n = 46) based on their reading scores. Logistic regression analyses indicated that computer tasks were as efficie…
Compensated transfer entropy as a tool for reliably estimating information transfer in physiological time series
2013
We present a framework for the estimation of transfer entropy (TE) under the conditions typical of physiological system analysis, featuring short multivariate time series and the presence of instantaneous causality (IC). The framework is based on recognizing that TE can be interpreted as the difference between two conditional entropy (CE) terms, and builds on an efficient CE estimator that compensates for the bias occurring for high dimensional conditioning vectors and follows a sequential embedding procedure whereby the conditioning vectors are formed progressively according to a criterion for CE minimization. The issue of IC is faced accounting for zero-lag interactions according to two a…
Localization of the bradykinin B2 receptor in uterus, bladder and Madin-Darby canine kidney cells
1997
Kinins are biologically active peptides that act through specific receptors, B1 and B2. Here we describe the localization of the bradykinin B2 receptor in Madin-Darby canine kidney cells and in the uterus and urinary bladder of rat or human origin. We discuss the suitability of anti-peptide antibodies to assess the tissue distribution of bradykinin B2 receptors.
Functional Extrapolations to Tame Unbound Anions in Density-Functional Theory Calculations
2019
Standard flavors of density-functional theory (DFT) calculations are known to fail in describing anions, due to large self-interaction errors. The problem may be circumvented using localized basis sets of reduced size, leaving no variational flexibility for the extra electron to delocalize. Alternatively, a recent approach exploiting DFT evaluations of total energies on electronic densities optimized at the Hartree-Fock (HF) level has been reported, showing that the self-interaction-free HF densities are able to lead to an improved description of the additional electron, returning affinities in close agreement with the experiments. Nonetheless, such an approach can fail when the HF densitie…