Search results for " pre-processing"
showing 10 items of 22 documents
Using NASA'S Long Term Data Record version 3 for the monitoring of land surface vegetation
2011
Numerous datasets have been made available for the observation of our planet from space. The aim of this work is the observation of changes in vegetation, through the use of a recent remote sensing dataset, NASA's Long Term Data Record (LTDR). Several authors have pointed out that vegetation monitoring benefits of the simultaneous use of Normalized Difference Vegetation Index (NDVI) and land surface temperature (LST). Therefore, this work presents the procedure developed to monitor vegetation with the LTDR dataset, using both NDVI and LST parameters. This procedure includes data preprocessing (estimation of NDVI and LST, orbital drift correction, atmospherically contaminated data reconstruc…
A statistical calibration model for Affymetrix probe level data
2009
Gene expression microarrays allow a researcher to measure the simultaneous response of thousands of genes to external conditions. Affymetrix GeneChip{ $Ⓡ$} expression array technology has become a standard tool in medical research. Anyway, a preprocessing step is usually necessary in order to obtain a gene expression measure. Aim of this paper is to propose a calibration method to estimate the nominal concentration based on a nonlinear mixed model. This method is an enhancement of a method proposed in Mineo et al. (2006). The relationship between raw intensities and concentration is obtained by using the Langmuir isotherm theory.
Pre-production validation of the ATLAS level-1 calorimeter trigger system
2006
The Level-1 Calorimeter Trigger is a major part of the first stage of event selection for the ATLAS experiment at the LHC. It is a digital, pipelined system with several stages of processing, largely based on FPGAs, which perform programmable algorithms in parallel with a fixed latency to process about 300 Gbyte/s of input data. The real-time output consists of counts of different types of trigger objects and energy sums. Prototypes of all module types have been undergoing intensive testing before final production during 2005. Verification of their correct operation has been performed stand-alone and in the ATLAS test-beam at CERN. Results from these investigations will be presented, along …
Rule-guided identification of cosmic-ray patterns in PLASTEX
1992
Some techniques devised in the computer science fields of pattern recognition and expert systems are being applied to the interpretation of EAS responses in the PLASTEX experiment. An attempt is made to codity in a set of rules the expertise of trained researchers who are able to recognize and classify different hit patterns even in the presence of noisy background, and in spite of imperfections in the detector response. The patterns expected to be useful include, but are not limited to, track patterns. The software described here, as a progress report, automatically finds patterns corresponding to isolated tracks, and patterns composed of tracks that connect with each other in a layer of d…
Modeling recurrent distributions in streams using possible worlds
2015
Discovering changes in the data distribution of streams and discovering recurrent data distributions are challenging problems in data mining and machine learning. Both have received a lot of attention in the context of classification. With the ever increasing growth of data, however, there is a high demand of compact and universal representations of data streams that enable the user to analyze current as well as historic data without having access to the raw data. To make a first step towards this direction, we propose a condensed representation that captures the various — possibly recurrent — data distributions of the stream by extending the notion of possible worlds. The representation en…
RPPanalyzer Toolbox: An improved R package for analysis of reverse phase protein array data
2014
Analysis of large-scale proteomic data sets requires specialized software tools, tailored toward the requirements of individual approaches. Here we introduce an extension of an open-source software solution for analyzing reverse phase protein array (RPPA) data. The R package RPPanalyzer was designed for data preprocessing followed by basic statistical analyses and proteomic data visualization. In this update, we merged relevant data preprocessing steps into a single user-friendly function and included a new method for background noise correction as well as new methods for noise estimation and averaging of replicates to transform data in such a way that they can be used as input for a new t…
On the Optimization of Self-Organizing Maps by Genetic Algorithms
1999
Publisher Summary This chapter reviews the research on the genetic optimization of self-organizing maps (SOMs). The optimization of learning rule parameters and of initial weights is able to improve network performance. The latter, however, requires chromosome sizes proportional to the size of the SOM and becomes unwieldy for large networks. The optimization of learning rule structures leads to self-organization processes of character similar to the standard learning rule. A particularly strong potential lies in the optimization of SOM topologies, which allows the study of global dynamical properties of SOMs and related models, as well as to develop tools for their analysis. Hierarchies of …
MuLiMs-MCoMPAs: A Novel Multiplatform Framework to Compute Tensor Algebra-Based Three-Dimensional Protein Descriptors
2019
This report introduces the MuLiMs-MCoMPAs software (acronym for Multi-Linear Maps based on N-Metric and Contact Matrices of 3D Protein and Amino-acid weightings), designed to compute tensor-based 3D protein structural descriptors by applying two- and three-linear algebraic forms. Moreover, these descriptors contemplate generalizing components such as novel 3D protein structural representations, (dis)similarity metrics, and multimetrics to extract geometrical related information between two and three amino acids, weighting schemes based on amino acid properties, matrix normalization procedures that consider simple-stochastic and mutual probability transformations, topological and geometrical…
WhoSNext: Recommending Twitter Users to Follow Using a Spreading Activation Network Based Approach
2020
The huge number of modern social network users has made the web a fertile ground for the growth and development of a plethora of recommender systems. To date, recommending a new user profile X to a given user U that could be interested in creating a relationship with X has been tackled using techniques based on content analysis, existing friendship relationships and other pieces of information coming from different social networks or websites. In this paper we propose a recommending architecture - called WhoSNext (WSN) - tested on Twitter and which aim is promoting the creation of new relationships among users. As recent researches show, this is an interesting recommendation problem: for a …