Search results for "Data analysi"
showing 10 items of 391 documents
Studying Nucleosomes Positioning by a Multi-Layer Model
2007
Eukaryotic DNA is packaged into a highly compact and dynamic structure called chromatin. While this packaging allows the cell to organize a large and complex genome in the nucleus, it can also block the access of transcription factors and other proteins to DNA. Nucleosomes are the fundamental repeating units of eukaryotic chromatin. Nucleosome position can be regulated in vivo by multi-subunit chromatin remodeling complexes, and their position can influence gene expression in eukaryotic cells. Alterations in chromatin structure, and hence in nucleosome organization, can result in a variety of diseases, including cancer, highlighting the need to achieve a better understanding of the molecula…
The Acts project: track reconstruction software for HL-LHC and beyond
2019
The reconstruction of trajectories of the charged particles in the tracking detectors of high energy physics experiments is one of the most difficult and complex tasks of event reconstruction at particle colliders. As pattern recognition algorithms exhibit combinatorial scaling to high track multiplicities, they become the largest contributor to the CPU consumption within event reconstruction, particularly at current and future hadron colliders such as the LHC, HL-LHC and FCC-hh. Current algorithms provide an extremely high standard of physics and computing performance and have been tested on billions of simulated and recorded data events. However, most algorithms were first written 20 year…
Changes in the flow and quality of water in the dam reservoir of the Mała Panew catchment (South Poland) characterized by multidimensional data analys…
2023
Multidimensional exploratory techniques, such as the Principal Component Analysis (PCA), have been used to analyze long-term changes in the fl ow regime and quality of water of the lowland dam reservoir Turawa (south-west Poland) in the catchment of the Mała Panew river (a tributary of the Odra). The paper proves that during the period of 1998–2016 the Turawa reservoir was equalizing the river’s water fl ow. Moreover, various physicochemical water quality indicators were analyzed at three measurement points (at the tributary’s mouth into the reservoir, in the reservoir itself and at the outfl ow from the reservoir). The water quality assessment was performed by analyzing physicochemical ind…
Empirical Orthogonal Function and Functional Data Analysis Procedures to Impute Long Gaps in Environmental Data
2016
Air pollution data sets are usually spatio-temporal multivariate data related to time series of different pollutants recorded by a monitoring network. To improve the estimate of functional data when missing values, and mainly long gaps, are present in the original data set, some procedures are here proposed considering jointly Functional Data Analysis and Empirical Orthogonal Function approaches. In order to compare and validate the proposed procedures, a simulation plan is carried out and some performance indicators are computed. The obtained results show that one of the proposed procedures works better than the others, providing a better reconstruction especially in presence of long gaps.
On the cellular mechanisms underlying working memory capacity in humans
2016
The cellular processes underlying individual differences in the Working Memory Capacity (WMC) of humans are essentially unknown. Psychological experiments suggest that subjects with lower working memory capacity (LWMC), with respect to subjects with higher capacity (HWMC), take more time to recall items from a list because they search through a larger set of items and are much more susceptible to interference during retrieval. However, a more precise link between psychological experiments and cellular properties is lacking and very difficult to investigate experimentally. In this paper, we investigate the possible underlying mechanisms at the single neuron level by using a computational mod…
Neutrino interaction classification with a convolutional neural network in the DUNE far detector
2020
The Deep Underground Neutrino Experiment is a next-generation neutrino oscillation experiment that aims to measure CP-violation in the neutrino sector as part of a wider physics program. A deep learning approach based on a convolutional neural network has been developed to provide highly efficient and pure selections of electron neutrino and muon neutrino charged-current interactions. The electron neutrino (antineutrino) selection efficiency peaks at 90% (94%) and exceeds 85% (90%) for reconstructed neutrino energies between 2–5 GeV. The muon neutrino (antineutrino) event selection is found to have a maximum efficiency of 96% (97%) and exceeds 90% (95%) efficiency for reconstructed neutrino…
Analysis of data fusion techniques for multi-microphone audio event detection in adverse environments
2017
Acoustic event detection (AED) is currently a very active research area with multiple applications in the development of smart acoustic spaces. In this context, the advances brought by Internet of Things (IoT) platforms where multiple distributed microphones are available have also contributed to this interest. In such scenarios, the use of data fusion techniques merging information from several sensors becomes an important aspect in the design of multi-microphone AED systems. In this paper, we present a preliminary analysis of several data-fusion techniques aimed at improving the recognition accuracy of an AED system by taking advantage of the diversity provided by multiple microphones in …
Singular hyperbolic systems
1999
We construct a class of vector fields on 3-manifolds containing the hyperbolic ones and the geometric Lorenz attractor. Conversely, we shall prove that nonhyperbolic systems in this class resemble the Lorenz attractor: they have Lorenz-like singularities accumulated by periodic orbits and they cannot be approximated by flows with nonhyperbolic critical elements.
FINITE ELEMENT APPROXIMATION OF NONLOCAL HEAT RADIATION PROBLEMS
1998
This paper focuses on finite element error analysis for problems involving both conductive and radiative heat transfers. The radiative heat exchange is modeled with a nonlinear and nonlocal term that also makes the problem non-monotone. The continuous problem has a maximum principle which suggests the use of inverse monotone discretizations. We also estimate the error due to the approximation of the boundary by showing continuous dependence on the geometric data for the continuous problem. The final result of this paper is a rigorous justification and error analysis for methods that use the so-called view factors for numerical modeling of the heat radiation.
Combining Inter-Subject Modeling with a Subject-Based Data Transformation to Improve Affect Recognition from EEG Signals
2019
Existing correlations between features extracted from Electroencephalography (EEG) signals and emotional aspects have motivated the development of a diversity of EEG-based affect detection methods. Both intra-subject and inter-subject approaches have been used in this context. Intra-subject approaches generally suffer from the small sample problem, and require the collection of exhaustive data for each new user before the detection system is usable. On the contrary, inter-subject models do not account for the personality and physiological influence of how the individual is feeling and expressing emotions. In this paper, we analyze both modeling approaches, using three public repositories. T…