Search results for "probability"
showing 10 items of 3417 documents
Deriving scaling laws in geodynamics using adjoint gradients
2018
Abstract Whereas significant progress has been made in modelling of lithospheric and crustal scale processes in recent years, it often remains a challenge to understand which of the many model parameters is of key importance for a particular simulation. Determining this is usually done by manually changing the model input parameters and performing new simulations. For a few cases, such as for folding or Rayleigh-Taylor instabilities, one can use thick-plate stability analysis to derive scaling laws to obtain such insights. Yet, for more general cases, it is not straightforward to do this (apart from running many simulations). Here, we discuss a numerically cheaper approach to compute scalin…
Towards a mean body for apparel design
2016
This paper focuses on shape average with applications to the apparel industry. Apparel industry uses a consensus sizing system; its major concern is to fit most of the population into it. Since anthropometric measures do not grow linearly, it is important to find prototypes to accurately represent each size. This is done using random compact mean sets, obtained from a cloud of 3D points given by a scanner and applying to the sample a previous definition of mean set. Additionally, two approaches to define confidence sets are introduced. The methodology is applied to data obtained from a real anthropometric survey. This paper has been partially supported by the following grants: TIN2009-14392…
Numerical study of the components positioning influence on the stability of a reverse shoulder prosthesis
2014
Aim of this paper is to setup a novel procedure able to analyze performances of a reverse shoulder prosthesis when different geometrical configurations are assumed. Nowadays, such a prosthesis is widely used but, because of its novelty, data in literature give poor information about performances and limits to its applicability. The activity has been divided into the following steps. At the beginning the shape of the prosthesis has been digitally acquired via a 3D scanner. Then, CAD models of all prosthetic components have been geometrically optimized in a way to obtain final entities suitable for numerical simulations. After that, CAD assemblies have been created between prosthetic componen…
A geometric street scattering channel model for car-to-car communication systems
2011
This paper presents a geometric street scattering channel model for car-to-car (C2C) communication systems under line-of-sight (LOS) and non-LOS (NLOS) propagation conditions. Starting from the geometric model, we develop a stochastic reference channel model, where the scatterers are uniformly distributed in rectangles in the form of stripes parallel to both sides of the street. We derive analytical expressions for the probability density functions (PDFs) of the angle-of-departure (AOD) and the angle-of-arrival (AOA). We also investigate the Doppler power spectral density (PSD) and the autocorrelation function (ACF) of the proposed model, assuming that the mobile transmitter (MT) and the mo…
Performance Analysis of M-DPSK Modulation over Fast-Hoyt Fading Channels under Non-Isotropic Scattering Conditions
2021
In this paper, we analyze the symbol error probability (SEP) performance of M-ary differential phase shift keying (M-DPSK) modulation schemes over frequency-flat fast-varying Hoyt multipath fading channels. Assuming general non-isotropic scattering conditions, we first derive a finite-range integral expression for the probability density function (PDF) of the phase difference between two non-isotropic Hoyt vectors perturbed by additive white Gaussian noise (AWGN). Based upon the theory of M-DPSK modulation and the obtained PDF formula, the SEP of M-DPSK and its corresponding asymptotic behavior in non-isotropic fast-Hoyt fading channels are derived. Specifically, a double semi-finite range …
Management of uncertain pairwise comparisons in AHP through probabilistic concepts
2019
Abstract Fast and judicious decision-making is paramount for the success of many activities and processes. However, various degrees of difficulty may affect the achievement of effective and optimal solutions. Decisions should ideally meet the best trade-off among as many of the involved factors as possible, especially in the case of complex problems. Substantial cognitive and technical skills are indispensable, while not always sufficient, to carry out optimal evaluations. One of the most common causes of wrong decisions derives from uncertainty and vagueness in making forecasts or attributing judgments. The literature shows numerous efforts towards the optimization and modeling of uncertai…
Combining hashing and enciphering algorithms for epidemiological analysis of gathered data.
2008
Summary Objectives: Compiling individual records coming from different sources is necessary for multi-center studies. Legal aspects can be satisfied by implementing anonymization procedures. When using these procedures with a different key for each study it becomes almost impossible to link records from separate data collections. Methods: The originality of the method relies on the way the combination of hashing and enciphering techniques is performed: like in asymmetric encryption, two keys are used but the private key depends on the patient’s identity. Results: The combination of hashing and enciphering techniques provides a great improvement in the overall security of the proposed scheme…
“Anti-Bayesian” flat and hierarchical clustering using symmetric quantiloids
2017
A myriad of works has been published for achieving data clustering based on the Bayesian paradigm, where the clustering sometimes resorts to Naive-Bayes decisions. Within the domain of clustering, the Bayesian principle corresponds to assigning the unlabelled samples to the cluster whose mean (or centroid) is the closest. Recently, Oommen and his co-authors have proposed a novel, counter-intuitive and pioneering PR scheme that is radically opposed to the Bayesian principle. The rational for this paradigm, referred to as the “Anti-Bayesian” (AB) paradigm, involves classification based on the non-central quantiles of the distributions. The first-reported work to achieve clustering using the A…
Discretized Bayesian Pursuit – A New Scheme for Reinforcement Learning
2012
Published version of a chapter in the book: Advanced Research in Applied Artificial Intelligence. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-642-31087-4_79 The success of Learning Automata (LA)-based estimator algorithms over the classical, Linear Reward-Inaction ( L RI )-like schemes, can be explained by their ability to pursue the actions with the highest reward probability estimates. Without access to reward probability estimates, it makes sense for schemes like the L RI to first make large exploring steps, and then to gradually turn exploration into exploitation by making progressively smaller learning steps. However, this behavior becomes counter-intuitive wh…
Solving Non-Stationary Bandit Problems by Random Sampling from Sibling Kalman Filters
2010
Published version of an article from Lecture Notes in Computer Science. Also available at SpringerLink: http://dx.doi.org/10.1007/978-3-642-13033-5_21 The multi-armed bandit problem is a classical optimization problem where an agent sequentially pulls one of multiple arms attached to a gambling machine, with each pull resulting in a random reward. The reward distributions are unknown, and thus, one must balance between exploiting existing knowledge about the arms, and obtaining new information. Dynamically changing (non-stationary) bandit problems are particularly challenging because each change of the reward distributions may progressively degrade the performance of any fixed strategy. Alt…