Search results for "Mathematical logic"
showing 10 items of 394 documents
A convolutional neural network for virtual screening of molecular fingerprints
2019
In the last few years, Deep Learning (DL) gained more and more impact on drug design because it allows a huge increase of the prediction accuracy in many stages of such a complex process. In this paper a Virtual Screening (VS) procedure based on Convolutional Neural Networks (CNN) is presented, that is aimed at classifying a set of candidate compounds as regards their biological activity on a particular target protein. The model has been trained on a dataset of active/inactive compounds with respect to the Cyclin-Dependent Kinase 1 (CDK1) a very important protein family, which is heavily involved in regulating the cell cycle. One qualifying point of the proposed approach is the use of molec…
Conclusion: University Ambiguities and Analytic Eclecticism
2018
This volume has examined six cases of university engagement in peripheral regions. While these regions have often been overlooked in the mainstream literature on university-region dynamics because they do not readily offer up success stories, they do facilitate an exploration into the challenges and difficulties that arise at the intersection of the university and region. Beginning with a theory rooted in institutionalist literature that depicts the university as a set of five ambiguities rather than as a coherent whole, the chapters have sought to apply the ambiguities of intention, causality, history, structure, and meaning to their regional context. In this conclusion, we pull together a…
On Metadata Support for Integrating Evolving Heterogeneous Data Sources
2019
With the emergence of big data technologies, the problem of structure evolution of integrated heterogeneous data sources has become extremely topical due to dynamic and diverse nature of big data. To solve the big data evolution problem, we propose an architecture that allows to store and process structured and unstructured data at different levels of detail, analyze them using OLAP capabilities and semi-automatically manage changes in requirements and data expansion. In this paper, we concentrate on the metadata essential for the operation of the proposed architecture. We propose a metadata model to describe schemata and supplementary properties of data sets extracted from sources and tran…
Measuring diversity. A review and an empirical analysis
2021
Abstract Maximum diversity problems arise in many practical settings from facility location to social networks, and constitute an important class of NP-hard problems in combinatorial optimization. There has been a growing interest in these problems in recent years, and different mathematical programming models have been proposed to capture the notion of diversity. They basically consist of selecting a subset of elements of a given set in such a way that a measure based on their pairwise distances is maximized to achieve dispersion or representativeness. In this paper, we perform an exhaustive comparison of four mathematical models to achieve diversity over the public domain library MDPLIB, …
La teoría fuerte de los derechos sociales: reconstrucción y crítica | The Strong Theory of Social Rights: Reconstruction and Criticism
2016
RESUMEN. En este artículo es objeto de análisis la teoría fuerte de los derechos sociales, que es presentada como una teoría unificadora del fundamento, la estructura normativa y los procedimientos de garantía de los diversos tipos de derechos y, en particular, de derechos sociales y de libertad. La teoría es objeto de una serie de consideraciones críticas que apuntan a algunos de sus presupuestos éticos, a sus consecuencias político-constitucionales, a sus problemáticos efectos económicos, al modo en que reconstruye la estructura normativa de los derechos que se considera deficiente y al modelo de garantía judicial propuesto para los derechos sociales que se reputa contraproducente. ABST…
Are Neural Networks Imitations of Mind?
2015
Artificial neural networks are often understood as a good way to imitate mind through the web structure of neurons in brain, but the very high complexity of human brain prevents to consider neural networks as good models for human mind;anyway neural networks are good devices for computation in parallel. The difference between feed-forward and feedback neural networks is introduced; the Hopfield network and the multi-layers Perceptron are discussed. In a very weak isomorphism (not similitude) between brain and neural networks, an artificial form of short term memory and of acknowledgement, in Elman neural networks, is proposed.
Recent advances in space-time statistics with applications to environmental data: An overview
2003
[1] This paper introduces a special section based on general environmental scientific problems, with a particular focus on using atmospheric data. All the papers and authors provide the methodology to study, analyze, predict, and evaluate the spatial-temporal behavior and the complicated spatial-temporal structure of the data. The overall aim is to present up-to-date developments in spatial and spatiotemporal statistics in the field of the atmosphere, to present on-going research, and to discuss important problems to be addressed in the near future.
Value Creation and Power Asymmetries in Digital Ecosystems : A Study of a Cloud Gaming Provider
2020
Digital platforms connecting users and service providers have a central role in determining the value creation structure of ecosystems. Platform developers try to achieve a dominant position for the platform with a strong ecosystem around it. The size and attractiveness of the services can attract new users, and growing user volume can bring new co-operative service providers to the service partner network. An interesting question is how the presence of power and potential power asymmetry affect the value creation capability and the structure of a network around a platform? This chapter describes an example of value creation and the influence of power asymmetry in a digital ecosystem built …
A Dominance Variant Under the Multi-Unidimensional Pairwise-Preference Framework: Model Formulation and Markov Chain Monte Carlo Estimation.
2018
Forced-choice questionnaires have been proposed as a way to control some response biases associated with traditional questionnaire formats (e.g., Likert-type scales). Whereas classical scoring methods have issues of ipsativity, item response theory (IRT) methods have been claimed to accurately account for the latent trait structure of these instruments. In this article, the authors propose the multi-unidimensional pairwise preference two-parameter logistic (MUPP-2PL) model, a variant within Stark, Chernyshenko, and Drasgow’s MUPP framework for items that are assumed to fit a dominance model. They also introduce a Markov Chain Monte Carlo (MCMC) procedure for estimating the model’s paramete…
Invited commentary: Differential learning is different from contextual interference learning.
2016
There has been renewed interest in the detailed structure of what is learned and the boundary conditions that foster motor learning. The accompanying article by Hossner et al. (2016), particularly their findings about augmented feedback in the context of different levels of additional noise, is consistent with this focus. Unfortunately, the findings from Hossner and colleagues appear to be based on incorrect interpretations of the differential learning (DL) approach. Essential discrepancies in the experimental conditions suggest the basis for the deviating results obtained in comparison to those of the original DL experiments. In this comment, it is also shown that the author's assumptions …