Restoration of error-diffused images using projection onto convex sets

Cataloged from PDF version of article.In this paper, a novel inverse halftoning method is proposed to restore a continuous tone image from a given half-tone image. A set theoretic formulation is used where three sets are defined using the prior information about the problem. A new spacedomain projection is introduced assuming the halftoning is performed using error diffusion, and the error diffusion filter kernel is known. The space-domain, frequency-domain, and space-scale domain projections are used alternately to obtain a feasible solution for the inverse halftoning problem which does not have a unique solution

Characterization of sleep spindles using higher order statistics and spectra

Cataloged from PDF version of article.This work characterizes the dynamics of sleep spindles, observed in electroencephalogram (EEG) recorded from humans during sleep, using both time and frequency domain methods which depend on higher order statistics and spectra. The time domain method combines the use of second- and third-order correlations to reveal information on the stationarity of periodic spindle rhythms to detect transitions between multiple activities. The frequency domain method, based on normalized spectrum and bispectrum, describes frequency interactions associated with nonlinearities occuring in the observed EEG

Search for axions in streaming dark matter

A new search strategy for the detection of the elusive dark matter (DM) axion is proposed. The idea is based on streaming DM axions, whose flux might get temporally enormously enhanced due to gravitational lensing. This can happen if the Sun or some planet (including the Moon) is found along the direction of a DM stream propagating towards the Earth location. The experimental requirements to the axion haloscope are a wide-band performance combined with a fast axion rest mass scanning mode, which are feasible. Once both conditions have been implemented in a haloscope, the axion search can continue parasitically almost as before. Interestingly, some new DM axion detectors are operating wide-band by default. In order not to miss the actually unpredictable timing of a potential short duration signal, a network of co-ordinated axion antennae is required, preferentially distributed world-wide. The reasoning presented here for the axions applies to some degree also to any other DM candidates like the WIMPs.Comment: 5 page

Determination of natural radioactivity levels in soil and travertine of the region of Tokat and Sivas, Turkey

WOS: 000429070100015In this study, the environmental radioactivity measurements for Tokat and Sivas provinces in the northeast of Turkey were performed. Using gamma ray spectrometry, the activity concentrations of natural radionuclides in soil and travertine samples (Th-232, Ra-226, and K-40) were determined. The annual effective dose equivalent, the absorbed doses rate in air, the radium equivalent, and the external hazard index were obtained from these activities. The activity concentrations vary from 9.09 to 17.04 Bq kg(-1) for Th-232, from 36.53 to 76.95 Bq kg(-1) for Ra-226, and from 216.56 to 576.59 Bq kg(-1) for K-40 in soil samples. The activity concentrations in travertines vary from 15.99 to 21.01 Bq kg(-1) for Th-232, from 19.89 to 67.71 Bq kg(-1) for Ra-226, and from 179.89 to 314.43 Bq kg(-1) for K-40. The average dose rate in air for soil and travertine samples was 43.41 and 41.05 nGy h(-1) respectively. The obtained results are presented and compared with other studies, and the results of this study are lower than the international recommended value (55 nGy h(-1)) given by UNSCEAR (2000). The results show that the region has a background radiation level within the natural limits.Gaziosmanpasa University Scientific Research Projects Department (BAP)Gaziosmanpasa University [24/2013]This work is supported by Gaziosmanpasa University Scientific Research Projects Department (BAP) under project no. 24/2013

Tulathromycin disturbs blood oxidative and coagulation status

The aim of this study was to determine the effect of tulathromycin on serum oxidative status and coagulation factors in rabbits. Tulathromycin was administered to eight rabbits, and blood samples were obtained 0, 1, 5, 10 and 15 days after treatment. Indicators of serum oxidative status (malondialdehyde, nitric oxide, superoxide dismutase, retinol and -carotene) and coagulation values (antithrombin III, fibrinogen) were measured after tulathromycin treatment. In addition, routine serum biochemical values (creatine kinase-MB, lactate dehydrogenase, alkaline phosphatase, alanine aminotransferase, aspartate aminotransferase, gamma glutamyl transferase, creatinine, blood urea nitrogen, cholesterol, triglyceride, high density lipoprotein, amylase, total protein, albumin, glucose and calcium), haemacell counts (white and red blood cells) and arterial blood gas parameters (packed cell volume, hemoglobin, pH, partial pressure of carbon dioxide, partial pressure of oxygen, actual bicarbonate, standard bicarbonate, total carbon dioxide, base excess in vivo, base excess in vitro, oxygen saturation, sodium and potassium) were also determined. Tulathromycin increased (P < 0.05) the levels of malondialdehyde, nitric oxide and superoxide dismutase activity, and decreased (P < 0.05) the level of antithrombin III. In conclusion, tulathromycin may cause oxidative damage and coagulation disorders during the treatment period.Key words: Tulathromycin, oxidative damage, coagulation disorder

Statistical Analysis and Comparison of Optical Classification of Atmospheric Aerosol Lidar Data

In this article, we present a new study for the analysis and classification of atmospheric aerosols in remote sensing LIDAR data. Information on particle size and associated properties are extracted from these remote sensing atmospheric data which are collected by a ground-based LIDAR system. This study first considers optical LIDAR parameter-based classification methods for clustering and classification of different types of harmful aerosol particles in the atmosphere. Since accurate methods for aerosol prediction behaviors are based upon observed data, computational approaches must overcome design limitations, and consider appropriate calibration and estimation accuracy. Consequently, two statistical methods based on generalized linear models (GLM) and regression tree techniques are used to further analyze the performance of the LIDAR parameter-based aerosol classification methods. The goal of GLM and regression tree analyses is to compare and contrast distinct classification data schemes, and compare the results with the measured aerosol reflection data in the atmosphere. The detailed statistical comparisons and analyses shows that the optical methods adopted in this study for classification and prediction of various harmful aerosol types such as soot, carbon monoxide (CO), sulfates (SOx), and nitrates (NOx) are efficient under appropriate functional distributions. The article offers a method for natural ordering of the aerosol types

Recognition of vessel acoustic signatures using non-linear teager energy based features

This paper proposes a vessel recognition and classification system based on vessel acoustic signatures. Teager Energy Operator (TEO) based Mel Frequency Cepstral Coefficients (MFCC) are used for the first time in Underwater Acoustic Signal Recognition (UASR) to identify platforms the acoustic noise they generate. TEO based MFCC (TEO-MFCC), being more robust in noisy conditions than conventional MFCC, provides a better estimation platform energy. Conventionally, acoustic noise is recognized by sonar oper-ators who listen to audio signals received by ship sonars. The aim of this work is to replace this conventional human-based recognition system with a TEO-MFCC features-based classification system. TEO is applied to short-time Fourier transform (STFT) of acoustic signal frames and Mel-scale filter bank is used to obtain Mel Teager-energy spectrum. The feature vector is constructed by discrete cosine transform (DCT) of logarithmic Mel Teager-energy spectrum. Obtained spectrum is transformed into cepstral coefficients that are labeled as TEO-MFCC. This analysis and implementation are carried out with datasets of 24 different noise recordings that belong to 10 separate classes of vessels. These datasets are partially provided by National Park Service (NPS). Artificial Neural Networks (ANN) are used as a classification method. Experimental results demonstrate that TEO-MFCC achieves 99.5% accuracy in classification of vessel noises. © 2016 IEEE

Fetal nutrition : a review

Knowledge of fetal nutrient supply has greatly increased in the last decade due to the availability of fetal blood samples obtained under relatively steady-state conditions. These studies, together with studies utilizing stable isotope methodologies, have clarified some aspects of the supply of the major nutrients for the fetus such as glucose, amino acids and fatty acids. At the same time, the relevance of intrauterine growth has been recognized not only for the well-being of the neonate and child, but also for later health in adulthood. The major determinants of fetal nutrient availability are maternal nutrition and metabolism together with placental function and metabolism. The regulation of the rate of intrauterine growth is the result of complex interactions between genetic inheritance, endocrine environment and availability of nutrients to the fetus

Application of Lattice Boltzmann and Navier-Stokes Methods to NASA's Wall Mounted Hump

Lattice Boltzmann (LB) based Large Eddy Simulation (LES), Reynolds-averaged Navier-Stokes (RANS) as well as hybrid RANS/LES methods within the Launch Ascent and Vehicle Aerodynamics (LAVA) solver framework are applied to NASA's wall-mounted hump. Computational results are compared with experiments performed by Greenblatt et al. A detailed comparison between the accuracy and resolution requirements of the two approaches for turbulence resolving simulations, as well as the suitability of different grid paradigms (body-fitted curvilinear and block structured Cartesian) are presented. This test case is part of NASA's Revolutionary Computational Aerosciences (RCA) sub-project which addresses the technical challenge of predicting flow separation and reattachment accurately. Improvements in predictive accuracy by as much as 90% are demonstrated using LB as well as hybrid RANS/LES approaches compared to state-of-the-art steady state RANS simulations

Time-scale wavelet scattering using hyperbolic tangent function for vessel sound classification

We introduce a time-frequency scattering method using hyperbolic tangent function for vessel sound classification. The sound data is wavelet transformed using a two channel filter-bank and filter-bank outputs are scattered using tanh function. A feature vector similar to mel-scale cepstrum is obtained after a wavelet packed transform-like structure approximating the mel-frequency scale. Feature vectors of vessel sounds are classified using a support vector machine (SVM). Experimental results are presented and the new feature extraction method produces better classification results than the ordinary Mel-Frequency Cepstral Coefficients (MFCC) vectors. © EURASIP 2017