Search results for "Signal processing"
showing 10 items of 2451 documents
Rough Set Theory for Optimization of Packet Management Mechanism in IP Routers
2020
Bandwidth and consequently optimum overall efficiency of network system relies greatly on mechanism of packet management in IP routers. Our research objective is to implement rough set theory to minimizing number of the network system attributes responsible for decision making in selection of those packets, which improve its transmission. Such an approach is called priority queuing system model, as we assign priority to the packets selected, following rough set theory. Regardless of the file format, for all the routers, packets are transmitted in sequence one-by-one. Nonetheless, quality of streaming data largely depends on how much the packet loss is minimized, or eliminated at all, if pos…
Seismic behavior of structures equipped with variable friction dissipative (VFD) systems
2021
Usually, to mitigate the stresses in framed structures, different strategies are used. Among them, base isolation, viscous/friction/metallic yielding dampers and tuned mass dumpers have been widely investigated. Fluid Viscous Dampers (FVD) probably result the most diffused for the simplicity in the applications. However, these type of dampers request limited interstorey drifts to avoid dangerous effects. Further, they have an elevate cost. On the contrary, friction dampers are not so expensive but request high interstorey drifts to give a significant contribute in the dissipation of energy during an earthquake. In this paper an approach for the energy dissipation by friction, modified with …
Urinary 1H Nuclear Magnetic Resonance Metabolomic Fingerprinting Reveals Biomarkers of Pulse Consumption Related to Energy-Metabolism Modulation in a…
2017
Little is known about the metabolome fingerprint of pulse consumption. The study of robust and accurate biomarkers for pulse dietary assessment has great value for nutritional epidemiology regarding health benefits and their mechanisms. To characterize the fingerprinting of dietary pulses (chickpeas, lentils and beans), spot urine samples from a subcohort from the PREDIMED study were stratified, using a validated food frequency questionnaire. Non-pulse consumers (≤ 4 g/day of pulse intake) and habitual pulse consumers (≥ 25 g/day of pulse intake) were analysed using a 1H-NMR metabolomics approach combined with multi- and univariate data analysis. Pulse consumption showed differences through…
Group analysis of ongoing EEG data based on fast double-coupled nonnegative tensor decomposition
2019
Abstract Background Ongoing EEG data are recorded as mixtures of stimulus-elicited EEG, spontaneous EEG and noises, which require advanced signal processing techniques for separation and analysis. Existing methods cannot simultaneously consider common and individual characteristics among/within subjects when extracting stimulus-elicited brain activities from ongoing EEG elicited by 512-s long modern tango music. New method Aiming to discover the commonly music-elicited brain activities among subjects, we provide a comprehensive framework based on fast double-coupled nonnegative tensor decomposition (FDC-NTD) algorithm. The proposed algorithm with a generalized model is capable of simultaneo…
Detecting differences with magnetoencephalography of somatosensory processing after tactile and electrical stimuli.
2018
Abstract Background Deviant stimuli within a standard, frequent stimulus train induce a cortical somatosensory mismatch response (SMMR). The SMMR reflects the brain’s automatic mechanism for the detection of change in a somatosensory domain. It is usually elicited by electrical stimulation, which activates nerve fibers and receptors in superficial and deep skin layers, whereas tactile stimulation is closer to natural stimulation and activates uniform fiber types. We recorded SMMRs after electrical and tactile stimuli. Method 306-channel magnetoencephalography recordings were made with 16 healthy adults under two conditions: electrical (eSMMR) and tactile (tSMMR) stimulations. The SMMR proto…
Models for preterm cortical development using non invasive clinical EEG
2017
AbstractThe objective of this study was to evaluate the piglet and the mouse as model systems for preterm cortical development. According to the clinical context, we used non invasive EEG recordings. As a prerequisite, we developed miniaturized Ag/AgCl electrodes for full band EEG recordings in mice and verified that Urethane had no effect on EEG band power. Since mice are born with a “preterm” brain, we evaluated three age groups: P0/P1, P3/P4 and P13/P14. Our aim was to identify EEG patterns in the somatosensory cortex which are distinguishable between developmental stages and represent a physiologic brain development. In mice, we were able to find clear differences between age groups wit…
Novel and known signals of selection for fat deposition in domestic sheep breeds from Africa and Eurasia
2018
International audience; Genomic regions subjected to selection frequently show signatures such as within-population reduced nucleotide diversity and outlier values of differentiation among differentially selected populations. In this study, we analyzed 50K SNP genotype data of 373 animals belonging to 23 sheep breeds of different geographic origins using the Rsb (extended haplotype homozygosity) and FST statistical approaches, to identify loci associated with the fat-tail phenotype. We also checked if these putative selection signatures overlapped with regions of high-homozygosity (ROH). The analyses identified novel signals and confirmed the presence of selection signature in genomic regio…
The Importance of Cerebellar Connectivity on Simulated Brain Dynamics
2020
The brain shows a complex multiscale organization that prevents a direct understanding of how structure, function and dynamics are correlated. To date, advances in neural modeling offer a unique opportunity for simulating global brain dynamics by embedding empirical data on different scales in a mathematical framework. The Virtual Brain (TVB) is an advanced data-driven model allowing to simulate brain dynamics starting from individual subjects' structural and functional connectivity obtained, for example, from magnetic resonance imaging (MRI). The use of TVB has been limited so far to cerebral connectivity but here, for the first time, we have introduced cerebellar nodes and interconnecting…
Quantitatively characterizing drug-induced arrhythmic contractile motions of human stem cell-derived cardiomyocytes.
2018
Quantification of abnormal contractile motions of cardiac tissue has been a noteworthy challenge and significant limitation in assessing and classifying the drug-induced arrhythmias (i.e. Torsades de pointes). To overcome these challenges, researchers have taken advantage of computational image processing tools to measure contractile motion from cardiomyocytes derived from human induced pluripotent stem cells (hiPSC-CMs). However, the amplitude and frequency analysis of contractile motion waveforms doesn't produce sufficient information to objectively classify the degree of variations between two or more sets of cardiac contractile motions. In this paper, we generated contractile motion dat…
Revealing community structures by ensemble clustering using group diffusion
2018
We propose an ensemble clustering approach using group diffusion to reveal community structures in data. We represent data points as a directed graph and assume each data point belong to single cluster membership instead of multiple memberships. The method is based on the concept of ensemble group diffusion with a parameter to represent diffusion depth in clustering. The ability to modulate the diffusion-depth parameter by varying it within a certain interval allows for more accurate construction of clusters. Depending on the value of the diffusion-depth parameter, the presented approach can determine very well both local clusters and global structure of data. At the same time, the ability …