Search results for "Control systems"
showing 10 items of 590 documents
KRAS-mutated iCCA display distinct molecular alterations and a preferential sensitivity towards PARP-1 inhibition
2021
Filter-based infrared detectors for high temperature size exclusion chromatography analysis of polyolefins: calibration with a small number of standa…
2012
Infrared detection has been shown to be very appropriate for high temperature analysis of polyolefins. After some early reports in which dispersive or single-band filter-based detectors were applied, Fourier transform detectors have been described for this application, in order to improve the method sensitivity. Modern simple filter-based detectors prove, however, comparable sensitivity while providing a number of practical advantages when coupled to chromatographic systems: reduced cell volume, simplified hardware, continuous generation of absorbance chromatograms, as well as simpler data collection and processing. A practical method for calibration, using multiple-band signals obtained wi…
Circulating fluidized bed reactors – part 01: analyzing the effect of particle modelling parameters in computational particle fluid dynamic (CPFD) si…
2019
A CPFD hydrodynamic model was developed for a circulating fluidized bed system and the simulation results were validated against experimental data based on particle circulation rate. Sensitivity of the computational mesh was primarily tested and extended grid refinement was needed at the loopseal to match the particle circulation rate with experimental data. The particle circulation rate was independent of the range of number of computational particles used in this study. A 10% reduction of the particle circulation rate was observed as the particle-wall interaction parameter was changed from 0.85 to 0.55 and 17% increment when the close-packed volume fraction was changed from 0.56 to 0.62. …
Regularized Regression Incorporating Network Information: Simultaneous Estimation of Covariate Coefficients and Connection Signs
2014
We develop an algorithm that incorporates network information into regression settings. It simultaneously estimates the covariate coefficients and the signs of the network connections (i.e. whether the connections are of an activating or of a repressing type). For the coefficient estimation steps an additional penalty is set on top of the lasso penalty, similarly to Li and Li (2008). We develop a fast implementation for the new method based on coordinate descent. Furthermore, we show how the new methods can be applied to time-to-event data. The new method yields good results in simulation studies concerning sensitivity and specificity of non-zero covariate coefficients, estimation of networ…
Tighter Relations between Sensitivity and Other Complexity Measures
2014
The sensitivity conjecture of Nisan and Szegedy [12] asks whether the maximum sensitivity of a Boolean function is polynomially related to the other major complexity measures of Boolean functions. Despite major advances in analysis of Boolean functions in the past decade, the problem remains wide open with no positive result toward the conjecture since the work of Kenyon and Kutin from 2004 [11].
Moving Learning Machine Towards Fast Real-Time Applications: A High-Speed FPGA-based Implementation of the OS-ELM Training Algorithm
2018
Currently, there are some emerging online learning applications handling data streams in real-time. The On-line Sequential Extreme Learning Machine (OS-ELM) has been successfully used in real-time condition prediction applications because of its good generalization performance at an extreme learning speed, but the number of trainings by a second (training frequency) achieved in these continuous learning applications has to be further reduced. This paper proposes a performance-optimized implementation of the OS-ELM training algorithm when it is applied to real-time applications. In this case, the natural way of feeding the training of the neural network is one-by-one, i.e., training the neur…
Hierarchical modeling for rare event detection and cell subset alignment across flow cytometry samples.
2013
Flow cytometry is the prototypical assay for multi-parameter single cell analysis, and is essential in vaccine and biomarker research for the enumeration of antigen-specific lymphocytes that are often found in extremely low frequencies (0.1% or less). Standard analysis of flow cytometry data relies on visual identification of cell subsets by experts, a process that is subjective and often difficult to reproduce. An alternative and more objective approach is the use of statistical models to identify cell subsets of interest in an automated fashion. Two specific challenges for automated analysis are to detect extremely low frequency event subsets without biasing the estimate by pre-processing…
Exudates as Landmarks Identified through FCM Clustering in Retinal Images
2020
The aim of this work was to develop a method for the automatic identification of exudates, using an unsupervised clustering approach. The ability to classify each pixel as belonging to an eventual exudate, as a warning of disease, allows for the tracking of a patient&rsquo
Measuring the agreement between brain connectivity networks.
2016
Investigating the level of similarity between two brain networks, resulting from measures of effective connectivity in the brain, can be of interest from many respects. In this study, we propose and test the idea to borrow measures of association used in machine learning to provide a measure of similarity between the structure of (un-weighted) brain connectivity networks. The measures here explored are the accuracy, Cohen's Kappa (K) and Area Under Curve (AUC). We implemented two simulation studies, reproducing two contexts of application that can be particularly interesting for practical applications, namely: i) in methodological studies, performed on surrogate data, aiming at comparing th…
Monitoring of blood pulsation using non-contact technique
2009
Time resolved detection and analysis of the skin back-scattered optical signals (reflection photoplethysmography or contact PPG) provide rich information on skin blood volume pulsations and can serve for cardiovascular assessment. The widely used contact PPG technique has many limitations, like high sensitivity to sensor movement etc. The newly developed non-contact PPG technique has been developed in this work. Potential of the new technique for express-assessment of human cardio-vascular condition has been demonstrated.