Search results for "SHO"
showing 10 items of 5071 documents
Efficient parallel computations of flows of arbitrary fluids for all regimes of Reynolds, Mach and Grashof numbers
2002
This paper presents a unified numerical method able to address a wide class of fluid flow problems of engineering interest. Arbitrary fluids are treated specifying totally arbitrary equations of state, either in analytical form or through look‐up tables. The most general system of the unsteady Navier–Stokes equations is integrated with a coupled implicit preconditioned method. The method can stand infinite CFL number and shows the efficiency of a quasi‐Newton method independent of the multi‐block partitioning on parallel machines. Computed test cases ranging from inviscid hydrodynamics, to natural convection loops of liquid metals, and to supersonic gasdynamics, show a solution efficiency i…
Optimal nonlinear damping control of second-order systems
2020
Novel nonlinear damping control is proposed for the second-order systems. The proportional output feedback is combined with the damping term which is quadratic to the output derivative and inverse to the set-point distance. The global stability, passivity property, and convergence time and accuracy are demonstrated. Also the control saturation case is explicitly analyzed. The suggested nonlinear damping is denoted as optimal since requiring no design additional parameters and ensuring a fast convergence, without transient overshoots for a non-saturated and one transient overshoot for a saturated control configuration.
Implementation of algorithms forK shortest loopless paths
1986
Implementations of loopless k shortest path algorithms are examined. Efficient storage structures for a large number of paths are given. A fast algorithm for determining the shortest paths in Yen's method is developed. Timing experiments show that a hybrid of Clarke's and Yen's methods is generally the fastest, although not significantly. Using upper bounds for the lengths of paths essentially improves all methods.
Single neuron binding properties and the magical number 7
2008
When we observe a scene, we can almost instantly recognize a familiar object or can quickly distinguish among objects differing by apparently minor details. Individual neurons in the medial temporal lobe of humans have been shown to be crucial for the recognition process, and they are selectively activated by different views of known individuals or objects. However, how single neurons could implement such a sparse and explicit code is unknown and almost impossible to investigate experimentally. Hippocampal CA1 pyramidal neurons could be instrumental in this process. Here, in an extensive series of simulations with realistic morphologies and active properties, we demonstrate how n radial (ob…
Snapshot hyperspectral system for noninvasive skin blood oxygen saturation monitoring
2018
The present study introduces recently developed compact hyperspectral snapshot system (device and software) for skin oxygen saturation monitoring. This prototype device involves compact snapshot hyperspectral camera, multi-wavelength illuminator, optical filter and crossed polarizers. The device was validated using reference color samples and and in-vivo during finger arterial occlusion tests. The prototype system demonstrated good performance of skin hyperspectral measurements in spectral range of 500-630nm. The results confirmed reliability of developed system for in-vivo assessment of skin blood oxygen saturation.
CRISPR sequences are sometimes erroneously translated and can contaminate public databases with spurious proteins containing spaced repeats
2020
© The Author(s) 2020.
Unsupervised image processing scheme for transistor photon emission analysis in order to identify defect location
2015
International audience; The study of the light emitted by transistors in a highly scaled complementary metal oxide semiconductor (CMOS) integrated circuit (IC) has become a key method with which to analyze faulty devices, track the failure root cause, and have candidate locations for where to start the physical analysis. The localization of defective areas in IC corresponds to a reliability check and gives information to the designer to improve the IC design. The scaling of CMOS leads to an increase in the number of active nodes inside the acquisition area. There are also more differences between the spot’s intensities. In order to improve the identification of all of the photon emission sp…
Open Set Audio Classification Using Autoencoders Trained on Few Data.
2020
Open-set recognition (OSR) is a challenging machine learning problem that appears when classifiers are faced with test instances from classes not seen during training. It can be summarized as the problem of correctly identifying instances from a known class (seen during training) while rejecting any unknown or unwanted samples (those belonging to unseen classes). Another problem arising in practical scenarios is few-shot learning (FSL), which appears when there is no availability of a large number of positive samples for training a recognition system. Taking these two limitations into account, a new dataset for OSR and FSL for audio data was recently released to promote research on solution…
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…
Extracting cloud motion from satellite image sequences
2004
This paper present a new technique for the estimation of cloud motion, using a sequence of infrared satellite images. It can be considered a challenging task due to the complexity of phenomena implied, as non-linear events and a non-rigid motion. In this circumstances most motion models are not suitable and new algorithms have to be developed. We propose a novel method, combining an Automatic Multilevel Thresholding for image segmentation, a Block Matching Algorithm (BMA) and a best candidate block search along with a vector median regularization.