Search results for "Algorithms"
showing 10 items of 1716 documents
Convolution-based ensemble learning algorithms to estimate the bond strength of the corroded reinforced concrete
2022
Reinforced concrete bond strength deterioration is one of the most serious problems in the construction industry. It is one of the most common factors impacting structural deterioration and the major cause of premature decadence of reinforced concrete structures. Therefore, developing an accurate model with the lowest variance and high reliability for the bond strength of corroded reinforced concrete is very important. The current work evaluates the efficiency of convolution-based ensemble learning algorithms. To address these issues, convolution-based ensemble learning models are developed using a database collected from the previous experimental studies of relative bond strength for corro…
Precīzie kvantu algoritmi, izmantojot 1-kvantu-vaicājuma izsaukumus
2018
Darbā ir analizēti zināmi unikāli precīzie kvantu algoritmi, kuru īpašības ir atšķirīgas no citiem literatūrā atrodamiem algoritmiem, un uzsākts pētīt iespējas vispārināt šajos algoritmos esošos paņēmienus. Darbā ir noformulēts jauns skaitļošanas modelis, kas ir saistīts ar precīzo kvantu vaicājumu modeli. Veikti skaitliski aprēķini, lai palīdzētu saprast jaunā modeļa iespējas un ierobežojumus. Izteiktas hipotēzes un virzieni, kādos turpināt analīzi un pētījumu.
Evaluation of Record Linkage Methods for Iterative Insertions
2009
Summary Objectives: There have been many developments and applications of mathematical methods in the context of record linkage as one area of interdisciplinary research efforts. However, comparative evaluations of record linkage methods are still underrepresented. In this paper improvements of the Fellegi-Sunter model are compared with other elaborated classification methods in order to direct further research endeavors to the most promising methodologies. Methods: The task of linking records can be viewed as a special form of object identification. We consider several non-stochastic methods and procedures for the record linkage task in addition to the Fellegi-Sunter model and perform an e…
Testing different ICA algorithms and connectivity analyses on MS patients.
2015
Multiple sclerosis (MS) is a progressive neurological disorder that affects the central nervous system. Functional magnetic resonance imaging (fMRI) has been employed to track the course and disease progression in patients with MS. The two main aims of this study were to apply in a data-driven approach the independent component analysis (ICA) in the spatial domain to depict the active sources and to look at the effective connectivity between the identified spatial sources. Several ICA algorithms have been proposed for fMRI data analysis. In this study, we aimed to test two well characterized algorithms, namely, the fast ICA and the complex infomax algorithms, followed by two effective conne…
An efficient functional magnetic resonance imaging data reduction strategy using neighborhood preserving embedding algorithm
2021
High dimensionality data have become common in neuroimaging fields, especially group-level functional magnetic resonance imaging (fMRI) datasets. fMRI connectivity analysis is a widely used, powerful technique for studying functional brain networks to probe underlying mechanisms of brain function and neuropsychological disorders. However, data-driven technique like independent components analysis (ICA), can yield unstable and inconsistent results, confounding the true effects of interest and hindering the understanding of brain functionality and connectivity. A key contributing factor to this instability is the information loss that occurs during fMRI data reduction. Data reduction of high …
Mutual information-based feature selection for low-cost BCIs based on motor imagery
2016
In the present study a feature selection algorithm based on mutual information (MI) was applied to electro-encephalographic (EEG) data acquired during three different motor imagery tasks from two dataset: Dataset I from BCI Competition IV including full scalp recordings from four subjects, and new data recorded from three subjects using the popular low-cost Emotiv EPOC EEG headset. The aim was to evaluate optimal channels and band-power (BP) features for motor imagery tasks discrimination, in order to assess the feasibility of a portable low-cost motor imagery based Brain-Computer Interface (BCI) system. The minimal sub set of features most relevant to task description and less redundant to…
Determination of particle number and brightness using a laser scanning confocal microscope operating in the analog mode
2008
We describe a method to obtain the brightness and number of molecules at each pixel of an image stack obtained with a laser scanning microscope. The method is based on intensity fluctuations due to the diffusion of molecules in a pixel. For a detector operating in the analog mode, the variance must be proportional to the intensity. Once this constant has been calibrated, we use the ratio between the variance and the intensity to derive the particle brightness. Then, from the ratio of the intensity to the brightness we obtain the average number of particles in the pixel. We show that the method works with molecules in solution and that the results are comparable to those obtained with fluctu…
Angiocardiographic digital still images compressed via irreversible methods: concepts and experiments.
1997
Abstract We defined, implemented and tested two new methods for irreversible compression of angiocardiographic still images: brightness error limitation (BEL) and pseudo-gradient adaptive brightness and contrast error limitation (PABCEL). The scan path used to compress the digital images is based on the Peano–Hilbert plane-filling curve. The compression methods limit, for each pixel, the brightness errors introduced when approximating the original image (i.e. the difference between the values of corresponding pixels as grey levels). Additional limitations are imposed to the contrast error observed when considering along the scan path consecutive pixels of both the original and the reconstru…
A Ciliary Motility Index for Activity Measurement in Cell Cultures With Respiratory Syncytial Virus
2018
[EN] Background: The respiratory epithelium is frequently infected by the respiratory syncytial virus, resulting in inflammation, a reduction in cilia activity and an increase in the production of mucus. Methods: In this study, an automatic method has been proposed to characterize the ciliary motility from cell cultures by means of a motility index using a dense optical flow algorithm. This method allows us to determine the ciliary beat frequency (CBF) together with a ciliary motility index of the cells in the cultures. The object of this analysis is to automatically distinguish between normal and infected cells in a culture. Results: The method was applied in 2 stages. It was concluded fro…
Variable-order reference-free variant discovery with the Burrows-Wheeler Transform
2020
Abstract Background In [Prezza et al., AMB 2019], a new reference-free and alignment-free framework for the detection of SNPs was suggested and tested. The framework, based on the Burrows-Wheeler Transform (BWT), significantly improves sensitivity and precision of previous de Bruijn graphs based tools by overcoming several of their limitations, namely: (i) the need to establish a fixed value, usually small, for the order k, (ii) the loss of important information such as k-mer coverage and adjacency of k-mers within the same read, and (iii) bad performance in repeated regions longer than k bases. The preliminary tool, however, was able to identify only SNPs and it was too slow and memory con…