Search results for "present"
showing 10 items of 3598 documents
Integrating LSTMs with Online Density Estimation for the Probabilistic Forecast of Energy Consumption
2019
In machine learning applications in the energy sector, it is often necessary to have both highly accurate predictions and information about the probabilities of certain scenarios to occur. We address this challenge by integrating and combining long short-term memory networks (LSTMs) and online density estimation into a real-time data streaming architecture of an energy trader. The online density estimation is done in the MiDEO framework, which estimates joint densities of data streams based on ensembles of chains of Hoeffding trees. One attractive feature of the solution is that queries can be sent to the here-called forecast-based point density estimators (FPDE) to derive information from …
Evaluation of the ARCore Indoor Localization Technology
2020
Augmented reality has become a very powerful tool nowadays. With the recent technological advance, smartphones have the ability to display augmented content on the screen. What makes the difference is the naturalness with which the multimedia content is superimposed over the video stream acquired with the phone's camera. This perfect overlay depends on the accurate estimation of the position and orientation of the smartphone's camera relative to the 3D representation of the space. ARCore is an augmented reality framework that computes the position and orientation of the smartphone. In order to assess the possibility of integrating ARCore within a virtual and augmented reality platform, we e…
Local dimensionality reduction and supervised learning within natural clusters for biomedical data analysis
2006
Inductive learning systems were successfully applied in a number of medical domains. Nevertheless, the effective use of these systems often requires data preprocessing before applying a learning algorithm. This is especially important for multidimensional heterogeneous data presented by a large number of features of different types. Dimensionality reduction (DR) is one commonly applied approach. The goal of this paper is to study the impact of natural clustering--clustering according to expert domain knowledge--on DR for supervised learning (SL) in the area of antibiotic resistance. We compare several data-mining strategies that apply DR by means of feature extraction or feature selection w…
An open-source computational and data resource to analyze digital maps of immunopeptidomes
2015
We present a novel mass spectrometry-based high-throughput workflow and an open-source computational and data resource to reproducibly identify and quantify HLA-associated peptides. Collectively, the resources support the generation of HLA allele-specific peptide assay libraries consisting of consensus fragment ion spectra, and the analysis of quantitative digital maps of HLA peptidomes generated from a range of biological sources by SWATH mass spectrometry (MS). This study represents the first community-based effort to develop a robust platform for the reproducible and quantitative measurement of the entire repertoire of peptides presented by HLA molecules, an essential step towards the de…
Genomic determinants of speciation and spread of the Mycobacterium tuberculosis complex
2019
14 páginas, 6 figuras
Si esto es un padre
2016
E<span>n la película de László Nemes, El hijo de Saúl (2015), el protagonista encuentra a un niño agonizante que ha sobrevivido a la cámara de gas en el campo de Auschwitz-Birkenau y a quien después un médico de las SS asfixia con sus propias manos. La escena de este asesinato confronta a Saúl (Géza Röhrig) en sus límites como viviente; decide con determinación entonces que este cadáver no se sumará a la maquinaria de muerte que es el campo de exterminio y busca desesperadamente un rabino para enterrarlo. Este artículo analiza la enigmática obstinación de este personaje en relación con los límites de la vida humana que puso en juego el nazismo y con los límites visuales de la represen…
Incorporating stand level risk management options into forest decision support systems
2018
Aim of study: To examine methods of incorporating risk and uncertainty to stand level forest decisions. Area of study: A case study examines a small forest holding from Jonkoping, Sweden. Material and methods: We incorporate empirically estimated uncertainty into the simulation through a Monte Carlo approach when simulating the forest stands for the next 100 years. For the iterations of the Monte Carlo approach, errors were incorporated into the input data which was simulated according to the Heureka decision support system. Both the Value at Risk and the Conditional Value at Risk of the net present value are evaluated for each simulated stand. Main results: Visual representation of the er…
The new course of FITs mechanism for PV systems in Italy: novelties, strong points and criticalities
2011
The paper deals with the new course of the Feed-in Tariffs mechanism for photovoltaic systems that will start from January 1, 2011 in Italy with the actuation of the Government Decree DM 06/08/2010. After a short introduction on Feed-in Tariffs and Net-metering in Italy, the paper focuses the attention on an economical comparison between the incentives established by the Government Decree DM 19/02/07, ended on December 31, 2010 and those introduced by the DM 06/08/2010. The economical comparison is based on three indexes: the Pay Back Period, the Net Present Value and the Internal Rate of Return, characterizing the investments done for the realization of the photovoltaic systems. In particu…
Probabilistic Logic under Coherence, Model-Theoretic Probabilistic Logic, and Default Reasoning
2001
We study probabilistic logic under the viewpoint of the coherence principle of de Finetti. In detail, we explore the relationship between coherence-based and model-theoretic probabilistic logic. Interestingly, we show that the notions of g-coherence and of g-coherent entailment can be expressed by combining notions in model-theoretic probabilistic logic with concepts from default reasoning. Crucially, we even show that probabilistic reasoning under coherence is a probabilistic generalization of default reasoning in system P. That is, we provide a new probabilistic semantics for system P, which is neither based on infinitesimal probabilities nor on atomic-bound (or also big-stepped) probabil…
B-Deformable Superquadrics for 3D Reconstruction
1995
We propose a new model for 3D representation and reconstruction. It is based on deformable superquadrics and parametric B-Splines. The 3D object deformation method uses B-Splines, instead of a Finite Element Method (FEM). This new model exhibits advantages of B-Splines It is significantly faster than deformable superquadrics without loss of generality (no assumption is made on object shapes,).