Skin color-based video segmentation under time-varying illumination

A novel approach for real-time skin segmentation in video sequences is described. The approach enables reliable skin segmentation despite wide variation in illumination during tracking. An explicit second order Markov model is used to predict evolution of the skin-color (HSV) histogram over time. Histograms are dynamically updated based on feedback from the current segmentation and predictions of the Markov model. The evolution of the skin-color distribution at each frame is parameterized by translation, scaling, and rotation in color space. Consequent changes in geometric parameterization of the distribution are propagated by warping and resampling the histogram. The parameters of the discrete-time dynamic Markov model are estimated using Maximum Likelihood Estimation and also evolve over time. The accuracy of the new dynamic skin color segmentation algorithm is compared to that obtained via a static color model. Segmentation accuracy is evaluated using labeled ground-truth video sequences taken from staged experiments and popular movies. An overall increase in segmentation accuracy of up to 24 percent is observed in 17 out of 21 test sequences. In all but one case, the skin-color classification rates for our system were higher, with background classification rates comparable to those of the static segmentation.     

Non-Recursive adaptive impulse noise canceller

A non-recursive adaptive impulse noise canceller (AINC) is investigated. The AINC is designed to suppress long impulsive interferences which are a primary source of errors in many communication systems. Performance of the AINC depends upon the input filter of the receiver. It is shown that the optimum input filter is LPF; the optimum LPF bandwidth exists which provides the minimum error rate of the receiver. The system error rate is studied by means of a computer simulation. Simulation results indicate that the AINC provides a very effective suppression of impulse noise. However, conditions in a real communication channel may be quite different from those chosen for simulation. Therefore, further research remains to be done before the AINC can be recommended for practical applications.     

Wide‐band aperture array using a four‐channel manifold‐type planar multiplexer and digital 2‐D IIR filterbank

Emerging wide‐band communications and spectrum‐sensing systems demand support for multiple electronically scanned beams while maintaining a frequency independent, constant far‐field beam width. Realizing existing phased‐array technology on a digital scale is computationally intensive. Moreover, digitizing wide‐band signals at Nyquist rate requires complex high‐speed analog‐to‐digital converters (ADCs), which is challenging for real developments driven by the current ADC technology. A low‐complexity alternative proposed in this paper is the use of radio‐frequency (RF) channelizers for spectrum division followed by sub‐sampling of the RF sub‐bands, which results in extensive reduction of the necessary ADC operative frequency. The RF‐channelized array signals are directionally filtered using 2‐D digital filterbanks. This mixed‐domain RF/digital aperture array allows sub‐sampling, without utilizing multi‐rate 2‐D systolic arrays, which are difficult to realize in practice. Simulated examples showing 14–19 dB of rejection of wide‐band interference and noise for a processed bandwidth of 1.6 GHz are demonstrated. The sampling rate is 400 MHz. The proposed VLSI hardware uses a single‐phase clock signal of 400 MHz. Prototype hardware realizations and measurement using 65‐nm Xilinx field‐programmable gate arrays, as well as Cadence RTL synthesis results including gate counts, area‐time complexity, and dynamic power consumption for a 45‐nm CMOS circuit operating at B _DC = 1.1 V, are presented. Copyright © 2016 John Wiley & Sons, Ltd.     

Genetically Encoded FRET-Sensor Based on Terbium Chelate and Red Fluorescent Protein for Detection of Caspase-3 Activity

This article describes the genetically encoded caspase-3 FRET-sensor based on the terbium-binding peptide, cleavable linker with caspase-3 recognition site, and red fluorescent protein TagRFP. The engineered construction performs two induction-resonance energy transfer processes: from tryptophan of the terbium-binding peptide to Tb³⁺ and from sensitized Tb³⁺ to acceptor—the chromophore of TagRFP. Long-lived terbium-sensitized emission (microseconds), pulse excitation source, and time-resolved detection were utilized to eliminate directly excited TagRFP fluorescence and background cellular autofluorescence, which lasts a fraction of nanosecond, and thus to improve sensitivity of analyses. Furthermore the technique facilitates selective detection of fluorescence, induced by uncleaved acceptor emission. For the first time it was shown that fluorescence resonance energy transfer between sensitized terbium and TagRFP in the engineered construction can be studied via detection of microsecond TagRFP fluorescence intensities. The lifetime and distance distribution between donor and acceptor were calculated using molecular dynamics simulation. Using this data, quantum yield of terbium ions with binding peptide was estimated.     

A dynamic solution of the shear band propagation in submerged landslides

A failure mechanism of submarine landslides based on the phenomenon of shear band propagation has been investigated using the energy balance approach. Dynamic analysis includes inertia effects in the sliding layer and viscous resistance of the water, but ignores elastic and plastic wave propagation in the sliding layer. The resulting differential equation has been solved numerically. Analytical approximation of this numerical solution provides a convenient basis for the parametric and sensitivity studies. The solution allows assessing the velocity and acceleration of both the landslide and the shear band at the moment when the slide fails due to the limiting equilibrium (i.e., the initial post-failure velocity). The effects of the initial landslide velocity on the tsunami wave height are discussed and validated for a number of landslide examples.     

A Genomics-Based Model for Prediction of Severe Bioprosthetic Mitral Valve Calcification

Severe bioprosthetic mitral valve calcification is a significant problem in cardiovascular surgery. Unfortunately, clinical markers did not demonstrate efficacy in prediction of severe bioprosthetic mitral valve calcification. Here, we examined whether a genomics-based approach is efficient in predicting the risk of severe bioprosthetic mitral valve calcification. A total of 124 consecutive Russian patients who underwent mitral valve replacement surgery were recruited. We investigated the associations of the inherited variation in innate immunity, lipid metabolism and calcium metabolism genes with severe bioprosthetic mitral valve calcification. Genotyping was conducted utilizing the TaqMan assay. Eight gene polymorphisms were significantly associated with severe bioprosthetic mitral valve calcification and were therefore included into stepwise logistic regression which identified male gender, the T/T genotype of the rs3775073 polymorphism within the TLR6 gene, the C/T genotype of the rs2229238 polymorphism within the IL6R gene, and the A/A genotype of the rs10455872 polymorphism within the LPA gene as independent predictors of severe bioprosthetic mitral valve calcification. The developed genomics-based model had fair predictive value with area under the receiver operating characteristic (ROC) curve of 0.73. In conclusion, our genomics-based approach is efficient for the prediction of severe bioprosthetic mitral valve calcification.