scholarly journals AUTOMATED RECOGNITION OF VEGETATION AND WATER BODIES ON THE TERRITORY OF MEGACITIES IN SATELLITE IMAGES OF VISIBLE AND IR BANDS

2018 ◽  
Vol IV-3 ◽  
pp. 167-172 ◽  
Author(s):  
Dmitry k. Mozgovoy ◽  
Volodymyr V. Hnatushenko ◽  
Volodymyr V. Vasyliev
Keyword(s):  
Satellite Images ◽  
Landscape Planning ◽  
Urban Ecosystems ◽  
Water Bodies ◽  
Multispectral Images ◽  
Automated Recognition ◽  
Large Cities ◽  
Wide Range ◽  
High Degree ◽  
Ir Bands

Vegetation and water bodies are a fundamental element of urban ecosystems, and water mapping is critical for urban and landscape planning and management. A methodology of automated recognition of vegetation and water bodies on the territory of megacities in satellite images of sub-meter spatial resolution of the visible and IR bands is proposed. By processing multispectral images from the satellite SuperView-1A, vector layers of recognized plant and water objects were obtained. Analysis of the results of image processing showed a sufficiently high accuracy of the delineation of the boundaries of recognized objects and a good separation of classes. The developed methodology provides a significant increase of the efficiency and reliability of updating maps of large cities while reducing financial costs. Due to the high degree of automation, the proposed methodology can be implemented in the form of a geo-information web service functioning in the interests of a wide range of public services and commercial institutions.

scholarly journals Operational satellite monitoring vegetation and water objects in the territory of cities

2018 ◽  
pp. 18-25
Author(s):  
Dmytro Mozgovoy
Keyword(s):  
Satellite Images ◽  
High Accuracy ◽  
Satellite Monitoring ◽  
Multispectral Images ◽  
Good Separation ◽  
Large Cities ◽  
Wide Range ◽  
Automated Processing ◽  
High Degree ◽  
Efficiency And Reliability

A technique for the operational monitoring of vegetation and water objects in the territory of cities by satellite images of ultrahigh spatial resolution of the visible and IR ranges is proposed. In the process of processing multispectral images from the satellite DubaiSat-2, vector layers of recognized vegetation and water objects were obtained. The analysis of the results of the automated processing of satellite images showed a sufficiently high accuracy of distinguishing the boundaries of recognized objects and a good separation of classes. The developed methodology allows to significantly increase the efficiency and reliability of updating maps of large cities while reducing financial costs. Due to the high degree of automation, the proposed methodology can be implemented in the form of a geoinformation web service, functioning in the interests of a wide range of users.

scholarly journals Experiment of Multispectral Images using Spectral Angle Mapper Algorithm for Land Cover Classification

2019 ◽  
Vol 8 (6S4) ◽  
pp. 96-99
Keyword(s):  
Land Cover ◽  
Satellite Images ◽  
Water Bodies ◽  
Classification Algorithms ◽  
Multispectral Images ◽  
Rapid Urbanization ◽  
Spectral Angle Mapper ◽  
Time Period ◽  
Steep Decline ◽  
Spectral Angle

Urbanization plays a key role in the health of the water bodies in any region. In a rapidly growing country like India, especially Bangalore district, rapid urbanization has seen a steep decline in the number of water bodies the region is famous for. In this paper, Land Use and Land Cover change is analysed for the remotely sensed images of Bangalore District using Spectral Angle Mapper Algorithm. Data for the purpose of analysis was obtained from BHUVAN (NRSC, ISRO). The study area is Bangalore District and data was collected from the time period 2008-2016. The major classes used in the classification are Land(Built-up), water bodies (Lakes), Vegetation (Gardens), Soil (Barren and fertile). The satellite images and the accompanying classification algorithms indicate that the percentage of water bodies have drastically shrunk (from 2.9% in 2008to1.8% in 2016) in the area of study. The results of this study can be used by the civic authorities to implement decisions to conserve the water bodies in the area.

Understanding Conformational Entropy in Small Molecules

2020 ◽  
Author(s):  
Lucian Chan ◽  
Garrett Morris ◽  
Geoffrey Hutchison
Keyword(s):  
Small Molecules ◽  
Degrees Of Freedom ◽  
Absolute Error ◽  
Low Energy ◽  
Standard Entropy ◽  
Free Energies ◽  
Conformational Entropy ◽  
Wide Range ◽  
High Degree ◽  
Empirical Corrections

The calculation of the entropy of flexible molecules can be challenging, since the number of possible conformers grows exponentially with molecule size and many low-energy conformers may be thermally accessible. Different methods have been proposed to approximate the contribution of conformational entropy to the molecular standard entropy, including performing thermochemistry calculations with all possible stable conformations, and developing empirical corrections from experimental data. We have performed conformer sampling on over 120,000 small molecules generating some 12 million conformers, to develop models to predict conformational entropy across a wide range of molecules. Using insight into the nature of conformational disorder, our cross-validated physically-motivated statistical model can outperform common machine learning and deep learning methods, with a mean absolute error ≈4.8 J/mol•K, or under 0.4 kcal/mol at 300 K. Beyond predicting molecular entropies and free energies, the model implies a high degree of correlation between torsions in most molecules, often as- sumed to be independent. While individual dihedral rotations may have low energetic barriers, the shape and chemical functionality of most molecules necessarily correlate their torsional degrees of freedom, and hence restrict the number of low-energy conformations immensely. Our simple models capture these correlations, and advance our understanding of small molecule conformational entropy.

Cerebellotrigeminal Dermal Dysplasia (Gómez-López-Hernández Syndrome)

2018 ◽  
Vol 16 (05) ◽  
pp. 362-368 ◽  
Author(s):  
Federica Sullo ◽  
Agata Polizzi ◽  
Stefano Catanzaro ◽  
Selene Mantegna ◽  
Francesco Lacarrubba ◽  
...  
Keyword(s):  
De Novo ◽  
Chromosomal Rearrangements ◽  
Number Of Patients ◽  
Wide Range ◽  
Visual Problems ◽  
Neurodevelopmental Abnormalities ◽  
Clinical Triad ◽  
High Degree ◽  
Motor Handicap

Cerebellotrigeminal dermal (CTD) dysplasia is a rare neurocutaneous disorder characterized by a triad of symptoms: bilateral parieto-occipital alopecia, facial anesthesia in the trigeminal area, and rhombencephalosynapsis (RES), confirmed by cranial magnetic resonance imaging. CTD dysplasia is also known as Gómez-López-Hernández syndrome. So far, only 35 cases have been described with varying symptomatology. The etiology remains unknown. Either spontaneous dominant mutations or de novo chromosomal rearrangements have been proposed as possible explanations. In addition to its clinical triad of RES, parietal alopecia, and trigeminal anesthesia, CTD dysplasia is associated with a wide range of phenotypic and neurodevelopmental abnormalities.Treatment is symptomatic and includes physical rehabilitation, special education, dental care, and ocular protection against self-induced corneal trauma that causes ulcers and, later, corneal opacification. The prognosis is correlated to the mental development, motor handicap, corneal–facial anesthesia, and visual problems. Follow-up on a large number of patients with CTD dysplasia has never been reported and experience is limited to few cases to date. High degree of suspicion in a child presenting with characteristic alopecia and RES has a great importance in diagnosis of this syndrome.

scholarly journals Controlling Teleportation-Based Locomotion in Virtual Reality with Hand Gestures: A Comparative Evaluation of Two-Handed and One-Handed Techniques

Electronics ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 715
Author(s):  
Alexander Schäfer ◽  
Gerd Reis ◽  
Didier Stricker
Keyword(s):  
Virtual Reality ◽  
Virtual Worlds ◽  
User Preferences ◽  
Interaction Techniques ◽  
Hand Gestures ◽  
Wide Range ◽  
Effectiveness And Efficiency ◽  
High Degree ◽  
Additional Hardware ◽  
Comprehensive Study

Virtual Reality (VR) technology offers users the possibility to immerse and freely navigate through virtual worlds. An important component for achieving a high degree of immersion in VR is locomotion. Often discussed in the literature, a natural and effective way of controlling locomotion is still a general problem which needs to be solved. Recently, VR headset manufacturers have been integrating more sensors, allowing hand or eye tracking without any additional required equipment. This enables a wide range of application scenarios with natural freehand interaction techniques where no additional hardware is required. This paper focuses on techniques to control teleportation-based locomotion with hand gestures, where users are able to move around in VR using their hands only. With the help of a comprehensive study involving 21 participants, four different techniques are evaluated. The effectiveness and efficiency as well as user preferences of the presented techniques are determined. Two two-handed and two one-handed techniques are evaluated, revealing that it is possible to move comfortable and effectively through virtual worlds with a single hand only.

scholarly journals Bulk Drag Predictions of Riparian Arundo donax Stands through UAV-Acquired Multispectral Images

Water ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 1333
Author(s):  
Giuseppe Francesco Cesare Lama ◽  
Mariano Crimaldi ◽  
Vittorio Pasquino ◽  
Roberta Padulano ◽  
Giovanni Battista Chirico
Keyword(s):  
Riparian Vegetation ◽  
Vegetation Index ◽  
Arundo Donax ◽  
Water Bodies ◽  
Giant Reed ◽  
Multispectral Images ◽  
Drainage Channel ◽  
Area Index ◽  
Riparian Plants ◽  
The Impact

Estimating the main hydrodynamic features of real vegetated water bodies is crucial to assure a balance between their hydraulic conveyance and environmental quality. Riparian vegetation stands have a high impact on vegetated channels. The present work has the aim to integrate riparian vegetation’s reflectance indices and hydrodynamics of real vegetated water flows to assess the impact of riparian vegetation morphometry on bulk drag coefficients distribution along an abandoned vegetated drainage channel fully covered by 9–10 m high Arundo donax (commonly known as giant reed) stands, starting from flow average velocities measurements at 30 cross-sections identified along the channel. A map of riparian vegetation cover was obtained through digital processing of Unnamed Aerial Vehicle (UAV)-acquired multispectral images, which represent a fast way to observe riparian plants’ traits in hardly accessible areas such as vegetated water bodies in natural conditions. In this study, the portion of riparian plants effectively interacting with flow was expressed in terms of ground-based Leaf Area Index measurements (LAI), which easily related to UAV-based Normalized Difference Vegetation Index (NDVI). The comparative analysis between Arundo donax stands NDVI and LAI map enabled the analysis of the impact of UAV-acquired multispectral imagery on bulk drag predictions along the vegetated drainage channel.

Krypton 85 myocardial blood flow: precordial scintillation versus coronary sinus sampling

1965 ◽  
Vol 209 (4) ◽  
pp. 705-710 ◽  
Author(s):  
Michael D. Klein ◽  
Lawrence S. Cohen ◽  
Richard Gorlin
Keyword(s):  
Blood Flow ◽  
Myocardial Blood Flow ◽  
Coronary Sinus ◽  
Human Subjects ◽  
Radioactive Decay ◽  
Empirical Correction ◽  
Wide Range ◽  
Actual Flow ◽  
Flow Through ◽  
High Degree

Myocardial blood flow in human subjects was assessed by comparative simultaneous measurement of krypton 85 radioactive decay from coronary sinus and precordial scintillation. Empirical correction of postclearance background from precordial curves yielded a high degree of correlation between flows derived from the two sampling sites (r = .889, P < .001). Comparison of left and right coronary flows in nine subjects revealed similarity in flow through the two vessels over a wide range of actual flow values (r = .945, P < .001).

Historical Dynamics

2018 ◽  
Author(s):  
Peter Turchin
Keyword(s):  
Religious Conversion ◽  
Synthetic Approach ◽  
Dynamical Processes ◽  
Factors Affecting ◽  
Historical Processes ◽  
Wide Range ◽  
Historical Dynamics ◽  
State Breakdown ◽  
Political Economic ◽  
High Degree

Many historical processes are dynamic. Populations grow and decline. Empires expand and collapse. Religions spread and wither. Natural scientists have made great strides in understanding dynamical processes in the physical and biological worlds using a synthetic approach that combines mathematical modeling with statistical analyses. Taking up the problem of territorial dynamics—why some polities at certain times expand and at other times contract—this book shows that a similar research program can advance our understanding of dynamical processes in history. The book develops hypotheses from a wide range of social, political, economic, and demographic factors: geopolitics, factors affecting collective solidarity, dynamics of ethnic assimilation/religious conversion, and the interaction between population dynamics and sociopolitical stability. It then translates these into a spectrum of mathematical models, investigates the dynamics predicted by the models, and contrasts model predictions with empirical patterns. The book's highly instructive empirical tests demonstrate that certain models predict empirical patterns with a very high degree of accuracy. For instance, one model accounts for the recurrent waves of state breakdown in medieval and early modern Europe. And historical data confirm that ethno-nationalist solidarity produces an aggressively expansive state under certain conditions (such as in locations where imperial frontiers coincide with religious divides). The strength of the book's results suggests that the synthetic approach advocated can significantly improve our understanding of historical dynamics.

Main approaches to treatment of hypoxia in acute respiratory distress syndrome, bacterial and viral pneumonia (part III)

2021 ◽  
pp. 38-55
Author(s):  
A. V. Vlasenko ◽  
E. A. Evdokimov ◽  
E. P. Rodionov
Keyword(s):  
Respiratory Failure ◽  
Distress Syndrome ◽  
Experimental Studies ◽  
Viral Pneumonia ◽  
Medical Technologies ◽  
Clinical Observations ◽  
Wide Range ◽  
Prevention And Treatment ◽  
High Degree

The paper summarizes data on modern approaches to the diagnosis, prevention and treatment of severe acute parenchymal respiratory failure of various origins, including ARDS due to bacterial viral pneumonia. The work is based on the data of modern well-organized studies, analysis of international clinical guidelines with a high degree of evidence, as well as the results of our own long-term experimental studies and clinical observations of the treatment of patients with ARDS of various origins, including viral pneumonia of 2009, 2016, 2020. Scientifically grounded algorithms for prevention, differential diagnosis and personalized therapy of severe acute respiratory failure using innovative medical technologies and a wide range of respiratory and adjuvant treatment methods have been formulated. The authors tried to adapt as much as possible the existing current recommendations for the daily clinical practice of anesthesiologists and resuscitators.

scholarly journals Comparing of Landsat 8 and Sentinel 2A using Water Extraction Indexes over Volta River

2017 ◽  
Vol 10 (1) ◽  
pp. 1 ◽  
Author(s):  
Clement Kwang ◽  
Edward Matthew Osei Jnr ◽  
Adwoa Sarpong Amoah
Keyword(s):  
Remote Sensing ◽  
Satellite Images ◽  
Remote Sensing Data ◽  
Unsupervised Classification ◽  
Water Bodies ◽  
Water Extraction ◽  
Landsat 8 ◽  
Sensing Data ◽  
Optimal Classifier ◽  
Sentinel 2A

Remote sensing data are most often used in water bodies’ extraction studies and the type of remote sensing data used also play a crucial role on the accuracy of the extracted water features. The performance of the proposed water indexes among the various satellite images is not well documented in literature. The proposed water indexes were initially developed with a particular type of data and with advancement and introduction of new satellite images especially Landsat 8 and Sentinel, therefore the need to test the level of performance of these water indexes as new image datasets emerged. Landsat 8 and Sentinel 2A image of part Volta River was used. The water indexes were performed and then ISODATA unsupervised classification was done. The overall accuracy and kappa coefficient values range from 98.0% to 99.8% and 0.94 to 0.98 respectively. Most of water bodies enhancement indexes work better on Sentinel 2A than on Landsat 8. Among the Landsat based water bodies enhancement ISODATA unsupervised classification, the modified normalized water difference index (MNDWI) and normalized water difference index (NDWI) were the best classifier while for Sentinel 2A, the MNDWI and the automatic water extraction index (AWEI_nsh) were the optimal classifier. The least performed classifier for both Landsat 8 and Sentinel 2A was the automatic water extraction index (AWEI_sh). The modified normalized water difference index (MNDWI) has proved to be the universal water bodies enhancement index because of its performance on both the Landsat 8 and Sentinel 2A image.

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