scholarly journals Combining Segmentation Network and Nonsubsampled Contourlet Transform for Automatic Marine Raft Aquaculture Area Extraction from Sentinel-1 Images

2020 ◽  
Vol 12 (24) ◽  
pp. 4182
Author(s):  
Yi Zhang ◽  
Chengyi Wang ◽  
Yuan Ji ◽  
Jingbo Chen ◽  
Yupeng Deng ◽  
...  
Keyword(s):  
Satellite Imagery ◽  
Network Architecture ◽  
High Efficiency ◽  
Parameter Tuning ◽  
Contourlet Transform ◽  
Nonsubsampled Contourlet Transform ◽  
Large Area ◽  
Raft Culture ◽  
Marine Economy ◽  
Low Efficiency

Marine raft aquaculture (MFA) plays an important role in the marine economy and ecosystem. With the characteristics of covering a large area and being sparsely distributed in sea area, MFA monitoring suffers from the low efficiency of field survey and poor data of optical satellite imagery. Synthetic aperture radar (SAR) satellite imagery is currently considered to be an effective data source, while the state-of-the-art methods require manual parameter tuning under the guidance of professional experience. To preclude the limitation, this paper proposes a segmentation network combined with nonsubsampled contourlet transform (NSCT) to extract MFA areas using Sentinel-1 images. The proposed method is highlighted by several improvements based on the feature analysis of MFA. First, the NSCT was applied to enhance the contour and orientation features. Second, multiscale and asymmetric convolutions were introduced to fit the multisize and strip-like features more effectively. Third, both channel and spatial attention modules were adopted in the network architecture to overcome the problems of boundary fuzziness and area incompleteness. Experiments showed that the method can effectively extract marine raft culture areas. Although further research is needed to overcome the problem of interference caused by excessive waves, this paper provides a promising approach for periodical monitoring MFA in a large area with high efficiency and acceptable accuracy.

scholarly journals Use of Unmanned Aerial Vehicle Imagery and Deep Learning UNet to Extract Rice Lodging

Sensors ◽  
2019 ◽  
Vol 19 (18) ◽  
pp. 3859 ◽  
Author(s):  
Zhao ◽  
Yuan ◽  
Song ◽  
Ding ◽  
Lin ◽  
...  
Keyword(s):  
Deep Learning ◽  
Unmanned Aerial Vehicle ◽  
Optical Sensors ◽  
Network Architecture ◽  
High Efficiency ◽  
Low Cost ◽  
Digital Camera ◽  
Large Area ◽  
Image Test ◽  
Aerial Vehicle

Rice lodging severely affects harvest yield. Traditional evaluation methods and manual on-site measurement are found to be time-consuming, labor-intensive, and cost-intensive. In this study, a new method for rice lodging assessment based on a deep learning UNet (U-shaped Network) architecture was proposed. The UAV (unmanned aerial vehicle) equipped with a high-resolution digital camera and a three-band multispectral camera synchronously was used to collect lodged and non-lodged rice images at an altitude of 100 m. After splicing and cropping the original images, the datasets with the lodged and non-lodged rice image samples were established by augmenting for building a UNet model. The research results showed that the dice coefficients in RGB (Red, Green and Blue) image and multispectral image test set were 0.9442 and 0.9284, respectively. The rice lodging recognition effect using the RGB images without feature extraction is better than that of multispectral images. The findings of this study are useful for rice lodging investigations by different optical sensors, which can provide an important method for large-area, high-efficiency, and low-cost rice lodging monitoring research.

HIGH EFFICIENCY, LARGE-AREA PHOTOVOLTAIC DEVICES USING AMORPHOUS Si : F : H ALLOY

1981 ◽  
Vol 42 (C4) ◽  
pp. C4-463-C4-466
Author(s):  
A. Madan ◽  
W. Czubatyj ◽  
J. Yang ◽  
J. McGill ◽  
S. R. Ovshinsky
Keyword(s):  
High Efficiency ◽  
Photovoltaic Devices ◽  
Large Area ◽  
Amorphous Si

scholarly journals CHROMOSOMAL BASIS OF THE MEROZYGOSITY IN A PARTIALLY DIPLOID MUTANT OF PNEUMOCOCCUS

Genetics ◽  
1975 ◽  
Vol 80 (4) ◽  
pp. 667-678
Author(s):  
Mary Lee S Ledbetter ◽  
Rollin D Hotchkiss
Keyword(s):  
High Efficiency ◽  
Point Mutations ◽  
Resistant Mutant ◽  
Chromosomal Marker ◽  
Structural Abnormality ◽  
C Cells ◽  
Wild Type ◽  
Chromosomal Locus ◽  
Low Efficiency ◽  
Derivatives Of

ABSTRACT A sulfonamide-resistant mutant of pneumococcus, sulr-c, displays a genetic instability, regularly segregating to wild type. DNA extracts of derivatives of the strain possess transforming activities for both the mutant and wild-type alleles, establishing that the strain is a partial diploid. The linkage of sulr-c to strr-61, a stable chromosomal marker, was established, thus defining a chromosomal locus for sulr-c. DNA isolated from sulr-c cells transforms two mutant recipient strains at the same low efficiency as it does a wild-type recipient, although the mutant property of these strains makes them capable of integrating classical "low-efficiency" donor markers equally as efficiently as "high efficiency" markers. Hence sulr-c must have a different basis for its low efficiency than do classical low efficiency point mutations. We suggest that the DNA in the region of the sulr-c mutation has a structural abnormality which leads both to its frequent segregation during growth and its difficulty in efficiently mediating genetic transformation.

scholarly journals A Brief Review on Solvent-Free Synthesis of Zeolites

Materials ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 788
Author(s):  
Jinlin Mei ◽  
Aijun Duan ◽  
Xilong Wang
Keyword(s):  
High Efficiency ◽  
Raw Materials ◽  
Solvent Free ◽  
High Yield ◽  
Control Synthesis ◽  
Mechanical Mixing ◽  
Synthesis Mechanism ◽  
Wastewater Pollution ◽  
Low Efficiency ◽  
Solvent Free Synthesis

The traditional hydrothermal method to prepare zeolite will inevitably use a large amount of water as a solvent, which will lead to higher autogenous pressure, low efficiency, and wastewater pollution. The solvent-free method can be used to synthesize various types of zeolites by mechanical mixing, grinding, and heating of solid raw materials, which exhibits the apparent advantages of high yield, low pollution, and high efficiency. This review mainly introduces the development process of solvent-free synthesis, preparation of hierarchical zeolite, morphology control, synthesis mechanism and applications of solvent-free methods. It can be believed that solvent-free methods will become a research focus and have enormous industrial application potential.

scholarly journals Rapid Single Image-Based DTM Estimation from ExoMars TGO CaSSIS Images Using Generative Adversarial U-Nets

2021 ◽  
Vol 13 (15) ◽  
pp. 2877
Author(s):  
Yu Tao ◽  
Siting Xiong ◽  
Susan J. Conway ◽  
Jan-Peter Muller ◽  
Anthony Guimpier ◽  
...  
Keyword(s):  
High Resolution ◽  
Large Scale ◽  
Imaging System ◽  
Landing Site ◽  
Parameter Tuning ◽  
Processing Parameters ◽  
Input Image ◽  
Large Area ◽  
Laser Altimeter ◽  
Imaging Science

The lack of adequate stereo coverage and where available, lengthy processing time, various artefacts, and unsatisfactory quality and complexity of automating the selection of the best set of processing parameters, have long been big barriers for large-area planetary 3D mapping. In this paper, we propose a deep learning-based solution, called MADNet (Multi-scale generative Adversarial u-net with Dense convolutional and up-projection blocks), that avoids or resolves all of the above issues. We demonstrate the wide applicability of this technique with the ExoMars Trace Gas Orbiter Colour and Stereo Surface Imaging System (CaSSIS) 4.6 m/pixel images on Mars. Only a single input image and a coarse global 3D reference are required, without knowing any camera models or imaging parameters, to produce high-quality and high-resolution full-strip Digital Terrain Models (DTMs) in a few seconds. In this paper, we discuss technical details of the MADNet system and provide detailed comparisons and assessments of the results. The resultant MADNet 8 m/pixel CaSSIS DTMs are qualitatively very similar to the 1 m/pixel HiRISE DTMs. The resultant MADNet CaSSIS DTMs display excellent agreement with nested Mars Reconnaissance Orbiter Context Camera (CTX), Mars Express’s High-Resolution Stereo Camera (HRSC), and Mars Orbiter Laser Altimeter (MOLA) DTMs at large-scale, and meanwhile, show fairly good correlation with the High-Resolution Imaging Science Experiment (HiRISE) DTMs for fine-scale details. In addition, we show how MADNet outperforms traditional photogrammetric methods, both on speed and quality, for other datasets like HRSC, CTX, and HiRISE, without any parameter tuning or re-training of the model. We demonstrate the results for Oxia Planum (the landing site of the European Space Agency’s Rosalind Franklin ExoMars rover 2023) and a couple of sites of high scientific interest.

scholarly journals Inflight Transmission of COVID-19 Based on Experimental Aerosol Dispersion Data

2021 ◽  
Author(s):  
Zhaozhi Wang ◽  
Edwin R Galea ◽  
Angus Grandison ◽  
John Ewer ◽  
Fuchen Jia
Keyword(s):  
High Efficiency ◽  
Face Mask ◽  
Generation Rate ◽  
Aviation Industry ◽  
Filtration System ◽  
Dispersion Data ◽  
Low Probability ◽  
Meal Service ◽  
Low Efficiency ◽  
Aerosol Dispersion

Abstract Background An issue of concern to the travelling public is the possibility of in-flight transmission of COVID-19 during long- and short-haul flights. The aviation industry maintains that the probability of contracting the illness is small based on reported cases, modelling and data from aerosol dispersion experiments conducted on-board aircraft. Methods Using experimentally derived aerosol dispersion data for a B777–200 aircraft and a modified version of the Wells-Riley equation we estimate inflight infection probability for a range of scenarios involving quanta generation rate and face mask efficiency. Quanta generation rates were selected based on COVID-19 events reported in the literature while mask efficiency was determined from the aerosol dispersion experiments. Results The MID-AFT cabin exhibits the highest infection probability. The calculated maximum individual infection probability (without masks) for a 2-hour flight in this section varies from 4.5% for the ‘Mild Scenario’ to 60.2% for the ‘Severe Scenario’ although the corresponding average infection probability varies from 0.1% to 2.5%. For a 12-hour flight, the corresponding maximum individual infection probability varies from 24.1% to 99.6% and the average infection probability varies from 0.8% to 10.8%. If all passengers wear face masks throughout the 12-hour flight, the average infection probability can be reduced by approximately 73%/32% for high/low efficiency masks. If face masks are worn by all passengers except during a one-hour meal service, the average infection probability is increased by 59%/8% compared to the situation where the mask is not removed. Conclusions This analysis has demonstrated that while there is a significant reduction in aerosol concentration due to the nature of the cabin ventilation and filtration system, this does not necessarily mean that there is a low probability or risk of in-flight infection. However, mask wearing, particularly high-efficiency ones, significantly reduces this risk.

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