scholarly journals Mapping sea-ice types from Sentinel-1 considering the surface-type dependent effect of incidence angle

2020 ◽  
pp. 1-11
Author(s):  
Johannes Lohse ◽  
Anthony P. Doulgeris ◽  
Wolfgang Dierking
Keyword(s):  
Sea Ice ◽  
Incidence Angle ◽  
Mean Value ◽  
Surface Type ◽  
Validation Data ◽  
Dependent Effect ◽  
Gaussian Probability Density Function ◽  
Backscatter Intensity ◽  
The Mean ◽  
Sar Imagery

Abstract Automated classification of sea-ice types in Synthetic Aperture Radar (SAR) imagery is complicated by the class-dependent decrease of backscatter intensity with Incidence Angle (IA). In the log-domain, this decrease is approximately linear over the typical range of space-borne SAR instruments. A global correction does not consider that different surface types show different rates of decrease in backscatter intensity. Here, we introduce a supervised classification algorithm that directly incorporates the surface-type dependent effect of IA. We replace the constant mean vector of a Gaussian probability density function in a Bayesian classifier with a linearly variable mean. During training, the classifier first retrieves the slope and intercept of the linear function describing the mean value and then calculates the covariance matrix as the mean squared deviation relative to this function. The IA dependence is no longer treated as an image property but as a class property. Based on training and validation data selected from overlapping SAR and optical images, we evaluate the proposed method in several case studies and compare to other classification algorithms for which a global IA correction is applied during pre-processing. Our results show that the inclusion of the per-class IA sensitivity can significantly improve the performance of the classifier.

Sea ice classification using wide-swath SAR data considering incidence angle depenency of backscatter intensity and surface texture

2020 ◽  
Author(s):  
Wenkai Guo ◽  
Polona Itkin ◽  
Johannes Philipp Lohse
Keyword(s):  
High Resolution ◽  
Sea Ice ◽  
Surface Texture ◽  
Classification Scheme ◽  
Incidence Angle ◽  
Texture Features ◽  
Angle Variation ◽  
Backscatter Intensity ◽  
Sar Data ◽  
Wide Swath

<p>In this study we develop a novel sea ice classification scheme based on remote sensing Synthetic-aperture Radar (SAR) data, and use it to classify sea ice types over the spatial and temporal range of the Norwegian Young sea ICE cruise (N-ICE2015). Ice type classification will be conducted on wide-swath SAR datasets including RADARSAT-2 and Sentinel-1 data. We use a classification scheme that takes into account different rates of decrease in backscatter intensity with incidence angle variation for different classes. In addition, it examines texture features of different sea ice types, and also variations of surface texture with changing incidence angles, and incorporates this relationship into the classification process. Sea ice classifications using high-resolution SAR images collected over the same period and also field data retrieved from the N-ICE2015 expedition will be used for ground truthing. Earlier N-ICE2015 studies with high resolution SAR and deformation suggest high lead and pressure ridge formation. We will use our lower-resolution results to explore potential increase in the fraction of deformed and lead ice from January to June 2015 in the region north of Svalbard.</p>

scholarly journals Modelling the variability of the Antarctic Slope Current

2011 ◽  
Vol 8 (1) ◽  
pp. 1-38
Author(s):  
P. Mathiot ◽  
H. Goosse ◽  
T. Fichefet ◽  
B. Barnier ◽  
H. Gallée
Keyword(s):  
Wind Speed ◽  
Sea Ice ◽  
Seasonal Cycle ◽  
Atmospheric Model ◽  
Mean Value ◽  
Oceanic Circulation ◽  
Atmospheric Forcing ◽  
The Mean ◽  
Antarctic Slope Current ◽  
The Antarctic

Abstract. One of the main features of the oceanic circulation along Antarctica is the Antarctic Slope Current (ASC). This circumpolar current flows westward and allows communication between the three major basins around Antarctica. The ASC is not very well known due to difficult access and the presence of sea ice during several months, allowing in situ study only during summertime. Moreover, only few numerical studies of this current have been carried out. Here, we investigate the sensitivity of this current to two different atmospheric forcing sets and to four different resolutions in a coupled ocean-sea ice model (NEMO-LIM). Two sets of simulation are conducted. For the first set, global model configurations are run at coarse (2°) to eddy permitting resolutions (0.25°) with the same atmospheric forcing. For the second set, simulations with two different atmospheric forcing sets are performed with a regional circumpolar configuration (south of 30° S) at 0.5° resolution. The first atmospheric forcing set is based on ERA40 reanalysis and CORE data, while the second one is based on a downscaling of the reanalysis ERA40 by the MAR regional atmospheric model. Sensitivity experiments to resolution show that a minimum model resolution of 0.5° is needed to capture the dynamics of the ASC in term of transport and recirculation. Sensitivity of the ASC to atmospheric forcing fields shows that the wind speed along the Antarctic coast strongly controls the transport and the seasonal cycle of the ASC. An increase of the Easterlies by about 30% leads to an increase of the mean transport of ASC by about 40%. Similar effects are obtained on the seasonal cycle: using a forcing fields with a stronger amplitude of the seasonal cycle leads to double the amplitude of the seasonal cycle of the ASC. To confirm the importance of the wind speed, a simulation, where the seasonal cycle of the wind speed is removed, is carried out. This simulation shows a decrease by more than 50% of the amplitude of the seasonal cycle without changing the mean value of ASC transport.

scholarly journals Bacteria and viruses in Arctic Sea ice

2019 ◽  
Vol 59 (3) ◽  
pp. 373-382
Author(s):  
A. F. Sazhin ◽  
N. D. Romanova ◽  
A. I. Kopylov ◽  
E. A. Zabotkina
Keyword(s):  
Sea Ice ◽  
Vertical Distribution ◽  
Bacterial Abundance ◽  
Mean Value ◽  
Arctic Sea Ice ◽  
Bacterial Cells ◽  
The North ◽  
Viral Particles ◽  
Arctic Sea ◽  
The Mean

We studied vertical distribution of bacteria and viruses in different layers of the Arctic sea ice drilled at the North Pole. The sampled multi-year ice was characterized by uneven vertical distribution of bacterial abundance. This characteristic varied within the range of 8±1.2×103 to 95±2.6×103 cells ml-1. The layers with the maximal bacterial abundance were located in the intermediate and lower layers of the ice cores. Bacterial biomass varied from 0.5 to 5 mg C m-3 with the mean value 1.57±0.2 mg C m-3. The ratio of viral to bacterial abundance varied from 0.6 to 28, with the mean value 12.5. The average total number of phages attached to bacteria was 6.2×103 viral particles ml-1. The number of viral particles located within bacterial cells varied from 2 to 21 particles per a bacterial cell. The frequency of visibly infected bacterial cells (FVIC) calculated for the upper, intermediate and lower layers of the ice was 0.92, 1.23 and 0.8% of the total bacterial abundance, respectively. The overall frequency of infected cells (FIC) calculated for the same layers was 6.3, 8.4 and 0.8% of bacteria numbers, respectively, while the viral-mediated mortality of bacteria (VMB) was 7.1, 9.8 and 6.1 %, respectively. Our data show that during the study period the rate of viral infection of bacterial cells and the viral-mediated mortality of bacterial cells in the multy-year ice of the North Pole were relatively low.

scholarly journals COVLIAS 1.0 vs. MedSeg: Artificial Intelligence-Based Comparative Study for Automated COVID-19 Computed Tomography Lung Segmentation in Italian and Croatian Cohorts

Diagnostics ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 2367
Author(s):  
Jasjit S. Suri ◽  
Sushant Agarwal ◽  
Alessandro Carriero ◽  
Alessio Paschè ◽  
Pietro S. C. Danna ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Experimental Data ◽  
Computed Tomography ◽  
Characteristic Curve ◽  
Computing Time ◽  
Mean Value ◽  
Image Analysis System ◽  
Validation Data ◽  
Lung Segmentation ◽  
The Mean

(1) Background: COVID-19 computed tomography (CT) lung segmentation is critical for COVID lung severity diagnosis. Earlier proposed approaches during 2020–2021 were semiautomated or automated but not accurate, user-friendly, and industry-standard benchmarked. The proposed study compared the COVID Lung Image Analysis System, COVLIAS 1.0 (GBTI, Inc., and AtheroPointTM, Roseville, CA, USA, referred to as COVLIAS), against MedSeg, a web-based Artificial Intelligence (AI) segmentation tool, where COVLIAS uses hybrid deep learning (HDL) models for CT lung segmentation. (2) Materials and Methods: The proposed study used 5000 ITALIAN COVID-19 positive CT lung images collected from 72 patients (experimental data) that confirmed the reverse transcription-polymerase chain reaction (RT-PCR) test. Two hybrid AI models from the COVLIAS system, namely, VGG-SegNet (HDL 1) and ResNet-SegNet (HDL 2), were used to segment the CT lungs. As part of the results, we compared both COVLIAS and MedSeg against two manual delineations (MD 1 and MD 2) using (i) Bland–Altman plots, (ii) Correlation coefficient (CC) plots, (iii) Receiver operating characteristic curve, and (iv) Figure of Merit and (v) visual overlays. A cohort of 500 CROATIA COVID-19 positive CT lung images (validation data) was used. A previously trained COVLIAS model was directly applied to the validation data (as part of Unseen-AI) to segment the CT lungs and compare them against MedSeg. (3) Result: For the experimental data, the four CCs between COVLIAS (HDL 1) vs. MD 1, COVLIAS (HDL 1) vs. MD 2, COVLIAS (HDL 2) vs. MD 1, and COVLIAS (HDL 2) vs. MD 2 were 0.96, 0.96, 0.96, and 0.96, respectively. The mean value of the COVLIAS system for the above four readings was 0.96. CC between MedSeg vs. MD 1 and MedSeg vs. MD 2 was 0.98 and 0.98, respectively. Both had a mean value of 0.98. On the validation data, the CC between COVLIAS (HDL 1) vs. MedSeg and COVLIAS (HDL 2) vs. MedSeg was 0.98 and 0.99, respectively. For the experimental data, the difference between the mean values for COVLIAS and MedSeg showed a difference of <2.5%, meeting the standard of equivalence. The average running times for COVLIAS and MedSeg on a single lung CT slice were ~4 s and ~10 s, respectively. (4) Conclusions: The performances of COVLIAS and MedSeg were similar. However, COVLIAS showed improved computing time over MedSeg.

Long-period modulated superstructures in Pd-12.5 at.%Ce and Pd-15 at.%Ce alloys

1990 ◽  
Vol 48 (4) ◽  
pp. 164-165
Author(s):  
Noriyuki Kuwano ◽  
Masaru Itakura ◽  
Kensuke Oki
Keyword(s):  
Electron Microscopy ◽  
Mean Value ◽  
Heavy Elements ◽  
Arc Furnace ◽  
X Ray ◽  
Long Period ◽  
Ultra High Purity ◽  
Heat Treated ◽  
Atomic Scattering ◽  
The Mean

Pd-Ce alloys exhibit various anomalies in physical properties due to mixed valences of Ce, and the anomalies are thought to be strongly related with the crystal structures. Since Pd and Ce are both heavy elements, relative magnitudes of (fcc-fpd) are so small compared with <f> that superlattice reflections, even if any, sometimes cannot be detected in conventional x-ray powder patterns, where fee and fpd are atomic scattering factors of Ce and Pd, and <f> the mean value in the crystal. However, superlattices in Pd-Ce alloys can be analyzed by electron microscopy, thanks to the high detectability of electron diffraction. In this work, we investigated modulated superstructures in alloys with 12.5 and 15.0 at.%Ce.Ingots of Pd-Ce alloys were prepared in an arc furnace under atmosphere of ultra high purity argon. The disc specimens cut out from the ingots were heat-treated in vacuum and electrothinned to electron transparency by a jet method.

Partition Coefficient Ratios and Tumour Perfusion Studied with 85mKr and 133Xe

1987 ◽  
Vol 26 (06) ◽  
pp. 253-257
Author(s):  
M. Mäntylä ◽  
J. Perkkiö ◽  
J. Heikkonen
Keyword(s):  
Partition Coefficient ◽  
Partition Coefficients ◽  
Regional Blood Flow ◽  
Blood Perfusion ◽  
Compartmental Analysis ◽  
Malignant Tumour ◽  
Mean Value ◽  
Perfusion Rate ◽  
Biological Variables ◽  
The Mean

The relative partition coefficients of krypton and xenon, and the regional blood flow in 27 superficial malignant tumour nodules in 22 patients with diagnosed tumours were measured using the 85mKr- and 133Xe-clearance method. In order to minimize the effect of biological variables on the measurements the radionuclides were injected simultaneously into the tumour. The distribution of the radiotracers was assumed to be in equilibrium at the beginning of the experiment. The blood perfusion was calculated by fitting a two-exponential function to the measuring points. The mean value of the perfusion rate calculated from the xenon results was 13 ± 10 ml/(100 g-min) [range 3 to 38 ml/(100 g-min)] and from the krypton results 19 ± 11 ml/(100 g-min) [range 5 to 45 ml/(100 g-min)]. These values were obtained, if the partition coefficients are equal to one. The equations obtained by using compartmental analysis were used for the calculation of the relative partition coefficient of krypton and xenon. The partition coefficient of krypton was found to be slightly smaller than that of xenon, which may be due to its smaller molecular weight.

Detection of Soluble Fibrin Monomer Complexes in Blood by Means of Protamine Sulphate Test

1968 ◽  
Vol 20 (01/02) ◽  
pp. 044-049 ◽  
Author(s):  
B Lipiński ◽  
K Worowski
Keyword(s):  
Human Subjects ◽  
Coronary Thrombosis ◽  
Mean Value ◽  
Healthy Human ◽  
Protamine Sulphate ◽  
Soluble Fibrin ◽  
Fibrin Monomer ◽  
Dog Plasma ◽  
The Mean ◽  
Precipitable Protein

SummaryIn the present paper described is a simple test for detecting soluble fibrin monomer complexes (SFMC) in blood. The test consists in mixing 1% protamine sulphate with diluted oxalated plasma or serum and reading the optical density at 6190 Å. In experiments with dog plasma, enriched with soluble fibrin complexes, it was shown that OD read in PS test is proportional to the amount of fibrin recovered from the precipitate. It was found that SFMC level in plasma increases in rabbits infused intravenously with thrombin and decreases after injection of plasmin with streptokinase. In both cases PS precipitable protein in serum is elevated indicating enhanced fibrinolysis. In healthy human subjects the mean value of OD readings in plasma and sera were found to be 0.30 and 0.11, while in patients with coronary thrombosis they are 0.64 and 0.05 respectively. The origin of SFMC in circulation under physiological and pathological conditions is discussed.

Detection of Circulating Tissue Factor and Factor VII in a Normal Population

1996 ◽  
Vol 75 (05) ◽  
pp. 772-777 ◽  
Author(s):  
Sybille Albrecht ◽  
Matthias Kotzsch ◽  
Gabriele Siegert ◽  
Thomas Luther ◽  
Heinz Großmann ◽  
...  
Keyword(s):  
Tissue Factor ◽  
Normal Population ◽  
Mean Value ◽  
Factor Vii ◽  
Significant Difference ◽  
Age Dependent ◽  
The Mean ◽  
Highly Correlated ◽  
And Gender

SummaryThe plasma tissue factor (TF) concentration was correlated to factor VII concentration (FVIIag) and factor VII activity (FVIIc) in 498 healthy volunteers ranging in age from 17 to 64 years. Immunoassays using monoclonal antibodies (mAbs) were developed for the determination of TF and FVIIag in plasma. The mAbs and the test systems were characterized. The mean value of the TF concentration was 172 ± 135 pg/ml. TF showed no age- and gender-related differences. For the total population, FVIIc, determined by a clotting test, was 110 ± 15% and the factor VIlag was 0.77 ± 0.19 μg/ml. FVII activity was significantly increased with age, whereas the concentration demonstrated no correlation to age in this population. FVII concentration is highly correlated with the activity as measured by clotting assay using rabbit thromboplastin. The ratio between FVIIc and FVIIag was not age-dependent, but demonstrated a significant difference between men and women. Between TF and FVII we could not detect a correlation.

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