Search results for "Identification"

A review of second‐order blind identification methods

2021

Second-order source separation (SOS) is a data analysis tool which can be used for revealing hidden structures in multivariate time series data or as a tool for dimension reduction. Such methods are nowadays increasingly important as more and more high-dimensional multivariate time series data are measured in numerous fields of applied science. Dimension reduction is crucial, as modeling such high-dimensional data with multivariate time series models is often impractical as the number of parameters describing dependencies between the component time series is usually too high. SOS methods have their roots in the signal processing literature, where they were first used to separate source sign…

Comparative Study of Human and Automated Screening for Antinuclear Antibodies by Immunofluorescence on HEp-2 Cells

2015

Background : Several automated systems had been developed in order to reduce inter-observer variability in indirect immunofluorescence (IIF) interpretation. We aimed to evaluate the performance of a processing system in antinuclear antibodies (ANA) screening on HEp-2 cells. Patients and Methods : This study included 64 ANA-positive sera and 107 ANA-negative sera that underwent IIF on two commercial kits of HEp-2 cells (BioSystems® and Euroimmun®). IIF results were compared with a novel automated interpretation system, the “ Cyclopus CADImmuno®” (CAD). Results : All ANA-positive sera images were recognized as positive by CAD (sensitivity = 100%), while 17 (15.9%) of the ANA-negative sera ima…

ERG signal analysis using wavelet transform

2009

The wavelet analysis is a powerful tool for analyzing and detecting features of signals characterized by time-dependent statistical properties, as biomedical signals. The identification and the analysis of the components of these signals in the time-frequency domain, give meaningful information about the physiological mechanisms that govern them. This article presents the results of the wavelet analysis applied to the a-wave component of the human electroretinogram. In order to deepen and improve our knowledge about the behavior of the early photoreceptoral response, including the possible activation of interactions and correlations among the photoreceptors, we have detected and identified …

Testing for local structure in spatiotemporal point pattern data

2017

The detection of clustering structure in a point pattern is one of the main focuses of attention in spatiotemporal data mining. Indeed, statistical tools for clustering detection and identification of individual events belonging to clusters are welcome in epidemiology and seismology. Local second-order characteristics provide information on how an event relates to nearby events. In this work, we extend local indicators of spatial association (known as LISA functions) to the spatiotemporal context (which will be then called LISTA functions). These functions are then used to build local tests of clustering to analyse differences in local spatiotemporal structures. We present a simulation stud…

Towards next-generation diagnostics for tuberculosis: identification of novel molecular targets by large-scale comparative genomics.

2020

5 páginas, 2 figuras. AVAILABILITY AND IMPLEMENTATION: The database of non-tuberculous mycobacteria assemblies can be accessed at: 10.5281/zenodo.3374377. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online: http://dx.doi.org/10.1093/bioinformatics/btz729

Newton algorithm for Hamiltonian characterization in quantum control

2014

We propose a Newton algorithm to characterize the Hamiltonian of a quantum system interacting with a given laser field. The algorithm is based on the assumption that the evolution operator of the system is perfectly known at a fixed time. The computational scheme uses the Crank-Nicholson approximation to explicitly determine the derivatives of the propagator with respect to the Hamiltonians of the system. In order to globalize this algorithm, we use a continuation method that improves its convergence properties. This technique is applied to a two-level quantum system and to a molecular one with a double-well potential. The numerical tests show that accurate estimates of the unknown paramete…

Les chiffres du crime en débat. Pour une exploitation raisonnée des statistiques pénales en sciences sociales

2007

Using Unfold-PCA for batch-to-batch start-up process understanding and steady-state identification in a sequencing batch reactor

2007

In chemical and biochemical processes, steady-state models are widely used for process assessment, control and optimisation. In these models, parameter adjustment requires data collected under nearly steady-state conditions. Several approaches have been developed for steady-state identification (SSID) in continuous processes, but no attempt has been made to adapt them to the singularities of batch processes. The main aim of this paper is to propose an automated method based on batch-wise unfolding of the three-way batch process data followed by a principal component analysis (Unfold-PCA) in combination with the methodology of Brown and Rhinehart 2 for SSID. A second goal of this paper is to…

Is Andy Murray More British Than Scottish? It Depends on His Success! Game Outcome and the MOATing Effect

2020

Prior research indicates that when we shared a part of a social identity with others, we tend to include or exclude them from our in-group depending on their success and failure. In this research, we investigated the extent to which this strategy (i.e., MOATing, “moving others away/toward the in-group”) is used for self-enhancement as compared to self-protection. Our experiment included a stereotype measure that assessed whether others were perceived as more typical of the in-group or the out-group. The results generally replicate those of prior research and suggest that MOATing primarily serves a self-enhancement function. We discuss theoretical and methodological implications.

A Procedure for the Producibility Curve Identification of a Dish-Stirling Plant, Starting from Experimental Data

2019

This article presents a procedure for the producibility curve identification of a dish-Stirling plant, starting from experimental data. The producibility data was measured, recorded, analysed, filtered and monthly aggregated. Moreover, the incidence of the ambient temperature and of the mirrors cleaning on producibility data is highlighted and a procedure to normalize the measured data in temperature and cleaning level was developed. To provide a validation of the developed procedure the producibility curves at 25 °C have been obtained and compared with the one issued by the manufacturer. The two curves are in good agreement, presenting a maximum deviation of the 7 %.