Search results for "parametric model"
showing 10 items of 63 documents
Sample size planning of two-arm superiority and noninferiority survival studies with discrete follow-up
2016
In clinical trials using lifetime as primary outcome variable, it is more the rule than the exception that even for patients who are failing in the course of the study, survival time does not become known exactly since follow-up takes place according to a restricted schedule with fixed, possibly long intervals between successive visits. In practice, the discreteness of the data obtained under such circumstances is plainly ignored both in data analysis and in sample size planning of survival time studies. As a framework for analyzing the impact of making no difference between continuous and discrete recording of failure times, we use a scenario in which the partially observed times are assig…
Statistical Shape and Probability Prior Model for Automatic Prostate Segmentation
2011
International audience; Accurate prostate segmentation in Trans Rectal Ultra Sound (TRUS) images is an important step in different clinical applications. However, the development of computer aided automatic prostate segmentation in TRUS images is a challenging task due to low contrast, heterogeneous intensity distribution inside the prostate region, imaging artifacts like shadow, and speckle. Significant variations in prostate shape, size and contrast between the datasets pose further challenges to achieve an accurate segmentation. In this paper we propose to use graph cuts in a Bayesian framework for automatic initialization and propagate multiple mean parametric models derived from princi…
Social Network-Based Content Delivery in Device-to-Device Underlay Cellular Networks Using Matching Theory
2017
With the popularity of social network-based services, the unprecedented growth of mobile date traffic has brought a heavy burden on the traditional cellular networks. Device-to-device (D2D) communication, as a promising solution to overcome wireless spectrum crisis, can enable fast content delivery based on user activities in social networks. In this paper, we address the content delivery problem related to optimization of peer discovery and resource allocation by combining both the social and physical layer information in D2D underlay networks. The social relationship, which is modeled as the probability of selecting similar contents and estimated by using the Bayesian nonparametric models…
Numerical model for the characterization of biocomposites reinforced by sisal fibres
2018
Abstract Although several works have been recently published in literature about biocomposites, i.e. on innovative and ecofriendly polymer matrix composites reinforced by natural fibers, there are not studies on the influence of the waviness that various natural fiber present after their extraction. In order to give a contribution to the knowledge of the effects of the fiber waviness on the main mechanical properties of biocomposites, as the longitudinal Young modulus, in the present study a systematic numerical analysis has been carried out by using parametric models properly developed, that let the user to consider the effects of the key influence parameters as the fiber concentrations an…
A Time-to-Event Model for Acute Kidney Injury after Reduced-Intensity Conditioning Stem Cell Transplantation Using a Tacrolimus- and Sirolimus-based …
2017
There is a paucity of data evaluating acute kidney injury (AKI) incidence and its relationship with the tacrolimus-sirolimus (Tac-Sir) concentrations in the setting of reduced-intensity conditioning (RIC) after allogeneic stem cell transplantation (allo-HSCT). This multicenter retrospective study evaluated risk factors of AKI defined by 2 classification systems, Kidney Disease Improving Global Outcome (KDIGO) score and "Grade 0-3 staging," in 186 consecutive RIC allo-HSCT recipients with Tac-Sir as graft-versus-host disease prophylaxis. Conditioning regimens consisted of fludarabine and busulfan (n = 53); melphalan (n = 83); or a combination of thiotepa, fludarabine, and busulfan (n = 50). …
Information Dynamics Analysis: A new approach based on Sparse Identification of Linear Parametric Models*
2020
The framework of information dynamics allows to quantify different aspects of the statistical structure of multivariate processes reflecting the temporal dynamics of a complex network. The information transfer from one process to another can be quantified through Transfer Entropy, and under the assumption of joint Gaussian variables it is strictly related to the concept of Granger Causality (GC). According to the most recent developments in the field, the computation of GC entails representing the processes through a Vector Autoregressive (VAR) model and a state space (SS) model typically identified by means of the Ordinary Least Squares (OLS). In this work, we propose a new identification …
Extended causal modeling to assess Partial Directed Coherence in multiple time series with significant instantaneous interactions.
2010
The Partial Directed Coherence (PDC) and its generalized formulation (gPDC) are popular tools for investigating, in the frequency domain, the concept of Granger causality among multivariate (MV) time series. PDC and gPDC are formalized in terms of the coefficients of an MV autoregressive (MVAR) model which describes only the lagged effects among the time series and forsakes instantaneous effects. However, instantaneous effects are known to affect linear parametric modeling, and are likely to occur in experimental time series. In this study, we investigate the impact on the assessment of frequency domain causality of excluding instantaneous effects from the model underlying PDC evaluation. M…
Vector Autoregressive Fractionally Integrated Models to Assess Multiscale Complexity in Cardiovascular and Respiratory Time Series
2020
Cardiovascular variability is the result of the activity of several physiological control mechanisms, which involve different variables and operate across multiple time scales encompassing short term dynamics and long range correlations. This study presents a new approach to assess the multiscale complexity of multivariate time series, based on linear parametric models incorporating autoregressive coefficients and fractional integration. The approach extends to the multivariate case recent works introducing a linear parametric representation of multiscale entropy, and is exploited to assess the complexity of cardiovascular and respiratory time series in healthy subjects studied during postu…
Optimal Design of Piezoelectric Cantilevered Actuators for Charge-Based Self-Sensing Applications
2019
Charge-based Self-Sensing Actuation (SSA) is a cost and space-saving method for accurate piezoelectric based-actuator positioning. However, the performance of its implementation resides in the choice of its geometry and the properties of the constituent materials. This paper intends to analyze the charge-based SSA&rsquo
Design and Digital Fabrication of a Parametric Joint for Bamboo Sustainable Structures
2019
The study deepens the design of a joining system for bamboo spatial structure by proposing new and advanced solutions that guarantee maximum freedom of composition to the designer. The joint allows to determine and control parametrically the adaptability to any spatial grid configuration of culms with heterogeneous dimensions. Despite the bamboo being one of the main natural building materials in the field of sustainable architecture, currently, it is not used enough due to the lack of adequate connection systems. Bamboo is a rapidly growing renewable resource, naturally available, which is quite strong and lends itself to structural applications. The paper proposes an innovative approach t…