Search results for "embedding"
showing 10 items of 175 documents
Diffusion of naltrexone across reconstituted human oral epithelium and histomorphological features
2006
Abstract In transbuccal absorption a major limitation could be the low permeability of the mucosa which implies low drug bioavailability. The ability of naltrexone hydrochloride (NLX) to penetrate a resembling histologically human buccal mucosa was assessed and the occurrence of any histomorphological changes observed. We used reconstituted human oral (RHO) non-keratinised epithelium as mucosal section and a Transwell diffusion cells system as bicompartmental model. Buccal permeation was expressed in terms of drug flux ( J s ) and permeability coefficients ( K p ). Data were collected using both artificial and natural human saliva. The main finding was that RHO does not restrain NLX permeat…
A Novel Multi-Scale Strategy for Multi-Parametric Optimization
2017
The motion of a sailing yacht is the result of an equilibrium between the aerodynamic forces, generated by the sails, and the hydrodynamic forces, generated by the hull(s) and the appendages (such as the keels, the rudders, the foils, etc.), which may be fixed or movable and not only compensate the aero-forces, but are also used to drive the boat. In most of the design, the 3D shape of an appendage is the combination of a plan form (2D side shape) and a planar section(s) perpendicular to it, whose design depends on the function of the appendage. We often need a section which generates a certain quantity of lift to fulfill its function, but the lift comes with a penalty which is the drag. Th…
The p-Laplacian with respect to measures
2013
We introduce a definition for the $p$-Laplace operator on positive and finite Borel measures that satisfy an Adams-type embedding condition.
A New Technique of Invariant Statistical Embedding and Averaging in Terms of Pivots for Improvement of Statistical Decisions Under Parametric Uncerta…
2021
In this chapter, a new technique of invariant embedding of sample statistics in a decision criterion (performance index) and averaging this criterion via pivotal quantities (pivots) is proposed for intelligent constructing efficient (optimal, uniformly non-dominated, unbiased, improved) statistical decisions under parametric uncertainty. This technique represents a simple and computationally attractive statistical method based on the constructive use of the invariance principle in mathematical statistics. Unlike the Bayesian approach, the technique of invariant statistical embedding and averaging in terms of pivotal quantities (ISE&APQ) is independent of the choice of priors and represents …
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…
The best constant for the Sobolev trace embedding from into
2004
Abstract In this paper we study the best constant, λ 1 ( Ω ) for the trace map from W 1 , 1 ( Ω ) into L 1 ( ∂ Ω ) . We show that this constant is attained in BV ( Ω ) when λ 1 ( Ω ) 1 . Moreover, we prove that this constant can be obtained as limit when p ↘ 1 of the best constant of W 1 , p ( Ω ) ↪ L p ( ∂ Ω ) . To perform the proofs we will look at Neumann problems involving the 1-Laplacian, Δ 1 ( u ) = div ( Du / | Du | ) .
Measuring Semantic Coherence of a Conversation
2018
Conversational systems have become increasingly popular as a way for humans to interact with computers. To be able to provide intelligent responses, conversational systems must correctly model the structure and semantics of a conversation. We introduce the task of measuring semantic (in)coherence in a conversation with respect to background knowledge, which relies on the identification of semantic relations between concepts introduced during a conversation. We propose and evaluate graph-based and machine learning-based approaches for measuring semantic coherence using knowledge graphs, their vector space embeddings and word embedding models, as sources of background knowledge. We demonstrat…
Deep Generative Model-Driven Multimodal Prostate Segmentation in Radiotherapy
2019
Deep learning has shown unprecedented success in a variety of applications, such as computer vision and medical image analysis. However, there is still potential to improve segmentation in multimodal images by embedding prior knowledge via learning-based shape modeling and registration to learn the modality invariant anatomical structure of organs. For example, in radiotherapy automatic prostate segmentation is essential in prostate cancer diagnosis, therapy, and post-therapy assessment from T2-weighted MR or CT images. In this paper, we present a fully automatic deep generative model-driven multimodal prostate segmentation method using convolutional neural network (DGMNet). The novelty of …
Incorporating depth information into few-shot semantic segmentation
2021
International audience; Few-shot segmentation presents a significant challengefor semantic scene understanding under limited supervision.Namely, this task targets at generalizing the segmentationability of the model to new categories given a few samples.In order to obtain complete scene information, we extend theRGB-centric methods to take advantage of complementary depthinformation. In this paper, we propose a two-stream deep neuralnetwork based on metric learning. Our method, known as RDNet,learns class-specific prototype representations within RGB anddepth embedding spaces, respectively. The learned prototypesprovide effective semantic guidance on the corresponding RGBand depth query ima…
Weighted samples, kernel density estimators and convergence
2003
This note extends the standard kernel density estimator to the case of weighted samples in several ways. In the first place I consider the obvious extension by substituting the simple sum in the definition of the estimator by a weighted sum, but I also consider other alternatives of introducing weights, based on adaptive kernel density estimators, and consider the weights as indicators of the informational content of the observations and in this sense as signals of the local density of the data. All these ideas are shown using the Penn World Table in the context of the macroeconomic convergence issue.