Search results for "IDENTIFICATION"
showing 10 items of 1600 documents
Transformations that preserve learnability
1996
We consider transformations (performed by general recursive operators) mapping recursive functions into recursive functions. These transformations can be considered as mapping sets of recursive functions into sets of recursive functions. A transformation is said to be preserving the identification type I, if the transformation always maps I-identifiable sets into I-identifiable sets.
A novel identification procedure from ambient vibration data
2020
AbstractAmbient vibration modal identification, also known as Operational Modal Analysis, aims to identify the modal properties of a structure based on vibration data collected when the structure is under its operating conditions, i.e., no initial excitation or known artificial excitation. This procedure for testing and/or monitoring historic buildings, is particularly attractive for civil engineers concerned with the safety of complex historic structures. However, since the external force is not recorded, the identification methods have to be more sophisticated and based on stochastic mechanics. In this context, this contribution will introduce an innovative ambient identification method b…
Machine learning techniques demonstrating individual movement patterns of the vertebral column: the fingerprint of spinal motion
2022
Surface topography systems enable the capture of spinal dynamic movement; however, it is unclear whether vertebral dynamics are unique enough to identify individuals. Therefore, in this study, we investigated whether the identification of individuals is possible based on dynamic spinal data. Three different data representations were compared (automated extracted features using contrastive loss and triplet loss functions, as well as simple descriptive statistics). High accuracies indicated the possible existence of a personal spinal 'fingerprint', therefore enabling subject recognition. The present work forms the basis for an objective comparison of subjects and the transfer of the method to…
The RFID technology for neurosciences: feasibility of limbs' monitoring in sleep diseases.
2009
This contribution investigates the feasibility of the passive UHF RF identification technology for the wireless monitoring of human body movements in some common sleep disorders by means of passive tags equipped with inertial switches. Electromagnetic and mechanical models as well as preliminary experimentations are introduced to analyze all the significant issues concerning the required power, the tag antenna design, the read distance, and the expected biosignals collected by the interrogation device.
An Automatic HEp-2 Specimen Analysis System Based on an Active Contours Model and an SVM Classification
2019
The antinuclear antibody (ANA) test is widely used for screening, diagnosing, and monitoring of autoimmune diseases. The most common methods to determine ANA are indirect immunofluorescence (IIF), performed by human epithelial type 2 (HEp-2) cells, as substrate antigen. The evaluation of ANA consist an analysis of fluorescence intensity and staining patterns. This paper presents a complete and fully automatic system able to characterize IIF images. The fluorescence intensity classification was obtained by performing an image preprocessing phase and implementing a Support Vector Machines (SVM) classifier. The cells identification problem has been addressed by developing a flexible segmentati…
Dog-bite-related attacks: A new forensic approach
2020
Dog attacks today represent a health hazard considering that prevention strategies have not always been successful. The identification of the dog that attacked the victim is necessary, considering the civil or criminal consequences for the animal's owner. An accurate scene analysis must be performed collecting a series of important information.Forensic investigations in dog attacks involve different methods, such as the evaluating of the canine Short Tandem Repeat (STR) typing in saliva traces on wounds or bite mark analysis, however, these techniques cannot always be applied. The effort to find new methods to identify the dog that attacked the victim represents a very interesting field for…
Identification of Reading Difficulties by a Digital Game-Based Assessment Technology
2020
Computerized game-based assessment (GBA) system for screening reading difficulties may provide substantial time and cost benefits over traditional paper-and-pencil assessment while providing means also to individually adapt learning content in educational games. To study the reliability and validity of a GBA system to identify struggling readers performing below a standard deviation from mean in paper-and-pencil test either in raw scores and grade-normative scores, a large-scale study with first to fourth grade students ( N = 723) was conducted, where GBA was administrated as a group test by tablet devices. Overall, the results indicated that the GBA can be successfully used to identify st…
Interpretable machine learning models for single-cell ChIP-seq imputation
2019
AbstractMotivationSingle-cell ChIP-seq (scChIP-seq) analysis is challenging due to data sparsity. High degree of data sparsity in biological high-throughput single-cell data is generally handled with imputation methods that complete the data, but specific methods for scChIP-seq are lacking. We present SIMPA, a scChIP-seq data imputation method leveraging predictive information within bulk data from ENCODE to impute missing protein-DNA interacting regions of target histone marks or transcription factors.ResultsImputations using machine learning models trained for each single cell, each target, and each genomic region accurately preserve cell type clustering and improve pathway-related gene i…
An Application of Iterative Identification and Control in the Robotics Field
2006
The plant model appropriate for designing the control strongly depends on the requirements. Simple models are enough to compute nondemanding controls. The parameters of well-defined structural models of flexible robot manipulators are difficult to determine because their effect is only visible if the manipulator is under strong actions or with high-frequency excitation. Thus, in this chapter, an iterative approach is suggested. This approach is applied to a one-degree-of-freedom flexible robot manipulator, first using some well-known models and then controlling a lab prototype. This approach can be used with a variety of control design and/or identification techniques.
Convolutional Neural Networks for the Identification of Regions of Interest in PET Scans: A Study of Representation Learning for Diagnosing Alzheimer…
2017
When diagnosing patients suffering from dementia based on imaging data like PET scans, the identification of suitable predictive regions of interest (ROIs) is of great importance. We present a case study of 3-D Convolutional Neural Networks (CNNs) for the detection of ROIs in this context, just using voxel data, without any knowledge given a priori. Our results on data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) suggest that the predictive performance of the method is on par with that of state-of-the-art methods, with the additional benefit of potential insights into affected brain regions.