46,219 research outputs found
Mathematical tools for identifying the fetal response to physical exercise during pregnancy
In the applied mathematics literature there exist a significant number of tools that can reveal the interaction between mother and fetus during rest and also during and after exercise. These tools are based on techniques from a number of areas such as signal processing, time series analysis, neural networks, heart rate variability as well as dynamical systems and chaos. We will briefly review here some of these methods, concentrating on a method of extracting the fetal heart rate from the mixed maternal-fetal heart rate signal, that is based on phase space reconstructio
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Shape descriptors for mode-shape recognition and model updating
The most widely used method for comparing mode shapes from finite elements and experimental measurements is the Modal Assurance Criterion (MAC), which returns a single numerical value and carries no explicit information on shape features. New techniques, based on image processing (IP) and pattern recognition (PR) are described in this paper. The Zernike moment descriptor (ZMD), Fourier descriptor (FD), and wavelet descriptor (WD), presented in this article, are the most popular shape descriptors having properties that include efficiency of expression, robustness to noise, invariance to geometric transformation and rotation, separation of local and global shape features and computational efficiency. The comparison of mode shapes is readily achieved by assembling the shape features of each mode shape into multi-dimensional shape feature vectors (SFVs) and determining the distances separating them. © 2009 IOP Publishing Ltd
Supercritical multicomponent solvent coal extraction
The yield of organic extract from the supercritical extraction of coal with larger diameter organic solvents such as toluene is increased by use of a minor amount of from 0.1 to 10% by weight of a second solvent such as methanol having a molecular diameter significantly smaller than the average pore diameter of the coal
Automatic Leaf Extraction from Outdoor Images
Automatic plant recognition and disease analysis may be streamlined by an
image of a complete, isolated leaf as an initial input. Segmenting leaves from
natural images is a hard problem. Cluttered and complex backgrounds: often
composed of other leaves are commonplace. Furthermore, their appearance is
highly dependent upon illumination and viewing perspective. In order to address
these issues we propose a methodology which exploits the leaves venous systems
in tandem with other low level features. Background and leaf markers are
created using colour, intensity and texture. Two approaches are investigated:
watershed and graph-cut and results compared. Primary-secondary vein detection
and a protrusion-notch removal are applied to refine the extracted leaf. The
efficacy of our approach is demonstrated against existing work.Comment: 13 pages, India-UK Advanced Technology Centre of Excellence in Next
Generation Networks, Systems and Services (IU-ATC), 201
Image-Optimized Coronal Magnetic Field Models
We have reported previously on a new method we are developing for using
image-based information to improve global coronal magnetic field models. In
that work we presented early tests of the method which proved its capability to
improve global models based on flawed synoptic magnetograms, given excellent
constraints on the field in the model volume. In this follow-up paper we
present the results of similar tests given field constraints of a nature that
could realistically be obtained from quality white-light coronagraph images of
the lower corona. We pay particular attention to difficulties associated with
the line-of-sight projection of features outside of the assumed coronagraph
image plane, and the effect on the outcome of the optimization of errors in
localization of constraints. We find that substantial improvement in the model
field can be achieved with this type of constraints, even when magnetic
features in the images are located outside of the image plane
Evolutionarily Conserved Sequence Features Regulate the Formation of the FG Network at the Center of the Nuclear Pore Complex.
The nuclear pore complex (NPC) is the portal for bidirectional transportation of cargos between the nucleus and the cytoplasm. While most of the structural elements of the NPC, i.e. nucleoporins (Nups), are well characterized, the exact transport mechanism is still under much debate. Many of the functional Nups are rich in phenylalanine-glycine (FG) repeats and are believed to play the key role in nucleocytoplasmic transport. We present a bioinformatics study conducted on more than a thousand FG Nups across 252 species. Our results reveal the regulatory role of polar residues and specific sequences of charged residues, named 'like charge regions' (LCRs), in the formation of the FG network at the center of the NPC. Positively charged LCRs prepare the environment for negatively charged cargo complexes and regulate the size of the FG network. The low number density of charged residues in these regions prevents FG domains from forming a relaxed coil structure. Our results highlight the significant role of polar interactions in FG network formation at the center of the NPC and demonstrate that the specific localization of LCRs, FG motifs, charged, and polar residues regulate the formation of the FG network at the center of the NPC
Binary Biometric Representation through Pairwise Adaptive Phase Quantization
Extracting binary strings from real-valued biometric templates is a fundamental step in template compression and protection systems, such as fuzzy commitment, fuzzy extractor, secure sketch, and helper data systems. Quantization and coding is the straightforward way to extract binary representations from arbitrary real-valued biometric modalities. In this paper, we propose a pairwise adaptive phase quantization (APQ) method, together with a long-short (LS) pairing strategy, which aims to maximize the overall detection rate. Experimental results on the FVC2000 fingerprint and the FRGC face database show reasonably good verification performances.\ud
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