Search results for "Mining"
showing 10 items of 1730 documents
Knowledge discovery using diffusion maps
2013
3D MODELING OF TWO LOUTERIA FRAGMENTS BY IMAGE-BASED APPROACH
2017
Abstract. The paper presents a digital approach to the reconstruction and analysis of two small-sized fragments of louteria, a kind of large terracotta vase, found during an archaeological survey in the south of Sicily (Italy), in the area of Cignana near the Greek colony of Akragas (nowadays Agrigento). The fragments of louteria have been studied by an image-based approach in order to achieve high accurate and very detailed 3D models. The 3D models have been used to carry out interpretive and geometric analysis from an archaeological point of view. Using different digital tools, it was possible to highlight some fine details of the louteria decorations and to better understand the characte…
CLUSTERING INCOMPLETE SPECTRAL DATA WITH ROBUST METHODS
2018
Abstract. Missing value imputation is a common approach for preprocessing incomplete data sets. In case of data clustering, imputation methods may cause unexpected bias because they may change the underlying structure of the data. In order to avoid prior imputation of missing values the computational operations must be projected on the available data values. In this paper, we apply a robust nan-K-spatmed algorithm to the clustering problem on hyperspectral image data. Robust statistics, such as multivariate medians, are more insensitive to outliers than classical statistics relying on the Gaussian assumptions. They are, however, computationally more intractable due to the lack of closed-for…
Enabling Searches on Wavelengths in a Hyperspectral Indices Database
2018
Abstract. Spectral indices derived from hyperspectral reflectance measurements are powerful tools to estimate physical parameters in a non-destructive and precise way for several fields of applications, among others vegetation health analysis, coastal and deep water constituents, geology, and atmosphere composition. In the last years, several micro-hyperspectral sensors have appeared, with both full-frame and push-broom acquisition technologies, while in the near future several hyperspectral spaceborne missions are planned to be launched. This is fostering the use of hyperspectral data in basic and applied research causing a large number of spectral indices to be defined and used in various…
Advancing stem cells: New therapeutic strategies for treating central nervous system disorders
2018
In this special issue, we explore new methods and knowledge to improve stem cell transplantation in diseases and conditions such as stroke, PD, and depression. Advancing the conventional idea regarding cell replacement in stem cell therapy, stem cells may also transfer healthy mitochondria to diseased ischemic neurons in stroke and improve the therapeutic time window of tissue plasminogen activator (tPA) in a conjunctive therapy for stroke, and human Wharton’s Jelly-derived mesenchymal stromal cells (hWJ-MSCs) may rely mainly on trophic factor secretion to induce neuroprotective effects. In addition, trophic factors such as neurotrophin-4/5 (NT-4/5) and glial cell line-derived neurotrophic …
Effects of hydrogen-charging on the properties of S235JR steel
2017
The paper presents the test results of the S235JR steel susceptibility to damage under the influence of hydrogen. The test of mechanical properties was performed on the basis of a static stretch test of non-hydrogenated samples and after cathodic polarization. Electrochemical measurements for the assessment of corrosion resistance of non-hydrogenated and hydrogenated steels were carried out using open circuit potential measurement and registering of potentiodynamic polarization curves in a three-electrode measuring system. Hydrogenation was carried out for between 3 and 24 hours in a solution of 0.1 N sulfuric acid (VI) with the addition of 2 mg/dm 3 of arsenic oxide (III) at an electric cu…
Interpolative mapping of mean precipitation in the Baltic countries by using landscape characteristics
2011
Maps of the long-term mean precipitation involving local landscape variables were generated for the Baltic countries, and the effectiveness of seven modelling methods was compared. The precipitation data were recorded in 245 meteorological stations in 1966–2005, and 51 location-related explanatory variables were used. The similarity-based reasoning in the Constud software system outperformed other methods according to the validation fit, except for spring. The multivariate adaptive regression splines (MARS) was another effective method on average. The inclusion of landscape variables, compared to reverse distance-weighted interpolation, highlights the effect of uplands, larger water bodies …
High Performance 3D PET Reconstruction Using Spherical Basis Functions on a Polar Grid
2011
Statistical iterative methods are a widely used method of image reconstruction in emission tomography. Traditionally, the image space is modelled as a combination of cubic voxels as a matter of simplicity. After reconstruction, images are routinely filtered to reduce statistical noise at the cost of spatial resolution degradation. An alternative to produce lower noise during reconstruction is to model the image space with spherical basis functions. These basis functions overlap in space producing a significantly large number of non-zero elements in the system response matrix (SRM) to store, which additionally leads to long reconstruction times. These two problems are partly overcome by expl…
The factorization method for electrical impedance tomography data from a new planar device.
2006
We present numerical results for two reconstruction methods for a new planar electrical impedance tomography device. This prototype allows noninvasive medical imaging techniques if only one side of a patient is accessible for electric measurements. The two reconstruction methods have different properties: one is a linearization-type method that allows quantitative reconstructions; the other one, that is, the factorization method, is a qualitative one, and is designed to detect anomalies within the body.
SNPs detection by eBWT positional clustering
2019
Sequencing technologies keep on turning cheaper and faster, thus putting a growing pressure for data structures designed to efficiently store raw data, and possibly perform analysis therein. In this view, there is a growing interest in alignment-free and reference-free variants calling methods that only make use of (suitably indexed) raw reads data. We develop the positional clustering theory that (i) describes how the extended Burrows–Wheeler Transform (eBWT) of a collection of reads tends to cluster together bases that cover the same genome position (ii) predicts the size of such clusters, and (iii) exhibits an elegant and precise LCP array based procedure to locate such clusters in the e…