Search results for "Algorithm"
showing 10 items of 4887 documents
Spectrophotometric investigation of the binding of vitamin E to water-containing reversed micelles.
2002
The distribution constants of vitamin E partitioned between apolar organic phase and water-containing reversed micelles of sodium bis (2-ethylhexyl) sulfosuccinate (AOT), didodecyldimethylammonium bromide (DDAB), soybean phosphatidylcholine (lecithin) and tetraethylene glycol monododecyl ether (C12E4) have been evaluated by a spectrophotometric method. The results suggest that in the presence of domains from apolar organic solvent to surfactant and to water, vitamin E is partitioned between the micellar palisade layer and the organic solvent and also that its binding strength to reversed micelles depends mainly by specific interactions between the head group of vitamin E and that of the sur…
Pervasive access to MRI bias artifact suppression service on a grid.
2009
Bias artifact corrupts magnetic resonance images in such a way that the image is afflicted by illumination variations. Some of the authors proposed the Exponential Entropy Driven - Homomorphic Unsharp Masking (E2D-HUM) algorithm that corrects this artifact without any a priori hypothesis about the tissues or the Magnetic Resonance image modality. Moreover, E2D-HUM does not care about the body part under examination and does not require any particular training task. People who want to use this algorithm, which is Matlab-based, have to set their own computers in order to execute it. Furthermore, they have to be Matlab-skilled to exploit all the features of the algorithm. In our work we propos…
SAVU: A Statistical Approach for Uncertain Data in Dynamics of Axially Moving Materials
2012
In physics and engineering problems, model input is never exact. The effect of small uncertainties on the solution is thus an important question. In this study, a direct statistical-visual approach to approximate the solution set is investigated in the context of axially moving materials. The multidimensional probability distribution for the input uncertainties is assumed known. It is considered as a deterministic object, which is then mapped through the model. The resulting probability density of the model output is visualized. The proposed system consists of three non-trivial parts, which are briefly discussed: a multidimensional sampler, a density estimator, and a high dynamic range (HDR…
A Simulation Based Analysis of an Multi Objective Diffusive Load Balancing Algorithm
2018
In this paper, we presented a further development of our research on developing an optimal software-hardware mapping framework. We used the Petri Net model of the complete hardware and software High Performance Computing (HPC) system running a Computational Fluid Dynamics (CFD) application, to simulate the behaviour of the proposed diffusive two level multi-objective load-balancing algorithm. We developed an meta-heuristic algorithm for generating an approximation of the Pareto-optimal set to be used as reference. The simulations showed the advantages of this algorithm over other diffusive algorithms: reduced computational and communication overhead and robustness due to low dependence on u…
ERP denoising in multichannel EEG data using contrasts between signal and noise subspaces
2009
Abstract In this paper, a new method intended for ERP denoising in multichannel EEG data is discussed. The denoising is done by separating ERP/noise subspaces in multidimensional EEG data by a linear transformation and the following dimension reduction by ignoring noise components during inverse transformation. The separation matrix is found based on the assumption that ERP sources are deterministic for all repetitions of the same type of stimulus within the experiment, while the other noise sources do not obey the determinancy property. A detailed derivation of the technique is given together with the analysis of the results of its application to a real high-density EEG data set. The inter…
Marketing Research Regarding the Usage of Online Social Networking Sites by High School Students
2013
This paper aims to present the concept of online social networks (OSN) and its evolution in the world of business as well as several important advantages and disadvantages of using online social networking sites. We are presenting a quantitative research on the main reasons for using online networking sites by high schools students from the several counties of Romania. The authors will present the results of the research which underline: the main activities undertaken by students with this new communication tool, the average number of friends the students have and the selection criteria for them as well as the influence level of OSN sites on the life and activity (school and private) of the…
Using the Breeder genetic algorithm to optimize a multiple regression analysis model used in prediction of the mesiodistal width of unerupted teeth
2014
For the prediction of the unerupted canine and premolars mesiodistal size, have been proposed different variants of multiple linear regression equations (MLRE). These are based on the amount of the upper and lower permanent incisors with a tooth of the lateral support. Aim of present study was to develop a method for optimization of MLRE, using a genetic algorithm for determining a set of coefficients that minimizes the prediction error for the sum of permanent premolars and canines dimensions from a group of young people in an area Romania's central city represented by Sibiu. To test the proposed method, we used a multiple linear regression equation derived from the estimation method propo…
“Anti-Bayesian” parametric pattern classification using order statistics criteria for some members of the exponential family
2013
This paper submits a comprehensive report of the use of order statistics (OS) for parametric pattern recognition (PR) for various distributions within the exponential family. Although the field of parametric PR has been thoroughly studied for over five decades, the use of the OS of the distributions to achieve this has not been reported. The pioneering work on using OS for classification was presented earlier for the uniform distribution and for some members of the exponential family, where it was shown that optimal PR can be achieved in a counter-intuitive manner, diametrically opposed to the Bayesian paradigm, i.e., by comparing the testing sample to a few samples distant from the mean. A…
Spectral identification of forced oscillation in PMU signal using mode decomposition
2018
This article gives a new method to identify the frequency of Forced Oscillation (FO) in phasor measurement units (PMUs) signals. The processing of the signal by Empirical Mode Decomposition (EMD) technique leads to effective detection with improvement in accuracy. After testing some improved versions of EMD, it is observed that ‘improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN-2014)’ is the best version to use in processing. The developed methodology is able to spot the frequency of FOs even if there exist multiple modes with mode mixing and multiple events. In such cases, self-coherence method fails to spot FO. Spectral analysis is conducted on the decom…
Implementation and performance of the ATLAS second level jet trigger
2008
ATLAS is one of the four major LHC experiments, designed to cover a wide range of physics topics. In order to cope with a rate of 40 MHz and 25 interactions per bunch crossing, the ATLAS trigger system is divided in three different levels. The first one (LVL1, hardware based) identifies signatures in 2 microseconds that are confirmed by the the following trigger levels (software based). The Second Level Trigger (LVL2) only looks at a region of the space around the LVL1 signature (called Region of Interest or ROI), confirming/rejecting the event in about 10 ms, while the Event Filter (Third Level Trigger, EF) has potential full event access and larger processing times, of the order of 1 s. T…