scholarly journals Sentinel-2 Cloud Removal Considering Ground Changes by Fusing Multitemporal SAR and Optical Images

2021 ◽  
Vol 13 (19) ◽  
pp. 3998
Author(s):  
Jianhao Gao ◽  
Yang Yi ◽  
Tang Wei ◽  
Haoguan Zhang
Keyword(s):  
Neural Network ◽  
Real Time ◽  
Sar Images ◽  
The Real ◽  
Removal Process ◽  
Optical Images ◽  
Cloud Removal ◽  
Real Time Information ◽  
Time Information ◽  
Sentinel 2

Publicly available optical remote sensing images from platforms such as Sentinel-2 satellites contribute much to the Earth observation and research tasks. However, information loss caused by clouds largely decreases the availability of usable optical images so reconstructing the missing information is important. Existing reconstruction methods can hardly reflect the real-time information because they mainly make use of multitemporal optical images as reference. To capture the real-time information in the cloud removal process, Synthetic Aperture Radar (SAR) images can serve as the reference images due to the cloud penetrability of SAR imaging. Nevertheless, large datasets are necessary because existing SAR-based cloud removal methods depend on network training. In this paper, we integrate the merits of multitemporal optical images and SAR images to the cloud removal process, the results of which can reflect the ground information change, in a simple convolution neural network. Although the proposed method is based on deep neural network, it can directly operate on the target image without training datasets. We conduct several simulation and real data experiments of cloud removal in Sentinel-2 images with multitemporal Sentinel-1 SAR images and Sentinel-2 optical images. Experiment results show that the proposed method outperforms those state-of-the-art multitemporal-based methods and overcomes the constraint of datasets of those SAR-based methods.

Real-Time Wind Measurement in Extratropical Cyclones by Means of Doppler Radar

1977 ◽  
Vol 16 (10) ◽  
pp. 1022-1028 ◽  
Author(s):  
H. W. Baynton ◽  
R. J. Serafin ◽  
C. L. Frush ◽  
G. R. Gray ◽  
P. V. Hobbs ◽  
...  
Keyword(s):  
Wind Speed ◽  
Real Time ◽  
Doppler Radar ◽  
Extratropical Cyclones ◽  
Wide Spread ◽  
The Real ◽  
Color Displays ◽  
Real Time Information ◽  
Time Information ◽  
Shaped Pattern

Abstract Color displays of the velocities of precipitation particles detected with a C-band Doppler radar in wide-spread cyclonic storms provide a variety of real-time information on the atmospheric wind field.Vertical profiles of wind speed and direction indicated by the real-time color displays agree well withrawinsonde measurements. Veering winds (or warm advection) produce a striking S-shaped pattern onthe color display and backing winds (or cold advection) produce a backward S. A maximum in the verticalprofile of wind speed is indicated by a pair of concentric colored rings, one upwind and one downwind ofthe radar. Vertically sloping velocity maxima are indicated by asymmetries in the color displays, as areconfluent and difluent winds. Divergence and convergence computed from the real-time color displays areof reasonable magnitude.

Parking Guidance Control System Based on Internet of Things

2013 ◽  
Vol 273 ◽  
pp. 641-645 ◽  
Author(s):  
Rong Chun Sun ◽  
Yan Piao ◽  
Yu Wang ◽  
Han Wang
Keyword(s):  
Control System ◽  
Internet Of Things ◽  
Real Time ◽  
The Internet ◽  
Guidance Control ◽  
Control Center ◽  
The Real ◽  
Real Time Information ◽  
Time Information ◽  
The Internet Of Things

To help drivers to quickly find a spare parking, a parking guidance control system was proposed. The principle of ultrasonic ranging was used to detect the state of a parking space, and through the internet of things the parking detector transmits the real-time information to the control center. The control center mainly is an industrial computer and is responsible for dealing with the real-time information and sending the control command by internet of things. The guidance signs at each crossroad receive the wireless commands and execute them, by which the guidance function is performed. The internet of things was realized by ZigBee star network, in which the control center is a coordinator and other parts are routers or terminal equipments. The simulation experiment results show that the parking guidance system works well, and has the value of application and promotion to some extent.

Remote Wireless Monitoring System for Wind Turbine

2013 ◽  
Vol 385-386 ◽  
pp. 614-617
Author(s):  
Lan Xin Hu ◽  
Hai Bo Feng ◽  
Hai Meng Yin
Keyword(s):  
Wind Turbine ◽  
Real Time ◽  
Monitoring System ◽  
Wind Turbines ◽  
The Real ◽  
Wireless Monitoring ◽  
Real Time Information ◽  
Time Information

This paper probes into the design of the remote wireless monitoring system for wind turbine, based on STC89C54RD+ microprocessor. TC35 produced by Siemens is used to send and receive information. Through this we can obtain the Real-time information of the temperature and vibration of the wind turbines.

Towards Real-Time Moment Tensor Inversions in a Data Rich Micro-Seismic Environment using Deep Learning

2021 ◽  
Author(s):  
Nima Nooshiri ◽  
Christopher J. Bean ◽  
Francesco Grigoli ◽  
Torsten Dahm
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Real Time ◽  
High Frequency ◽  
Moment Tensor ◽  
Source Parameters ◽  
Data Set ◽  
Real Time Information ◽  
Time Information ◽  
Current Inversion

<p>Despite advanced seismological methods, source characterization for micro-seismic events remains challenging since current inversion and modelling of high-frequency waveforms are complex and time consuming. For a real-time application like induced-seismicity monitoring, these methods are slow for true real-time information because they require repeated evaluation of the often computationally expensive forward operation. Moreover, because of the low amplitude and high-frequency content of the recorded micro-seismic signals, routine inversion procedure can become unstable and manual parameter tuning is often required. Therefore, real-time and automatic source inversion procedures are difficult and not standard. A more promising alternative to the current inversion methods for rapid source parameter inversion is to use a deep-learning neural network model that is calibrated on a data set of past and/or possible future observations. Such data-driven model, once trained, offers the potential for rapid real-time information on seismic sources in a monitoring context.</p><p>In this study, we investigate how a supervised deep-learning model trained on a data set of synthetic seismograms can be used to rapidly invert for source parameters. The inversion is represented in compact form by a convolutional neural network which yields seismic moment tensor. In other words, a neural-network algorithm is trained to encapsulate the information about the relationship between observations and underlying point-source models. The learning-based model allows rapid inversion once seismic waveforms are available. Moreover, we find that the method is robust with respect to perturbations such as observational noise and missing data. In this study, we seek to demonstrate that this approach is viable for micro-seismicity real-time estimation of source parameters. As a demonstration test, we plan to apply the new approach to data collected at the geothermal field system in the Hengill area, Iceland, within the framework of the COSEISMIQ project funded through the EU GEOTHERMICA programme.</p>

scholarly journals Optimal Interdiction of Urban Criminals with the Aid of Real-Time Information

2019 ◽  
Vol 33 ◽  
pp. 1262-1269
Author(s):  
Youzhi Zhang ◽  
Qingyu Guo ◽  
Bo An ◽  
Long Tran-Thanh ◽  
Nicholas R. Jennings
Keyword(s):  
Real Time ◽  
Urban Network ◽  
The Real ◽  
Response Strategies ◽  
Best Response ◽  
Nest Model ◽  
Suburban Cities ◽  
Realistic Problem ◽  
Real Time Information ◽  
Time Information

Most violent crimes happen in urban and suburban cities. With emerging tracking techniques, law enforcement officers can have real-time location information of the escaping criminals and dynamically adjust the security resource allocation to interdict them. Unfortunately, existing work on urban network security games largely ignores such information. This paper addresses this omission. First, we show that ignoring the real-time information can cause an arbitrarily large loss of efficiency. To mitigate this loss, we propose a novel NEtwork purSuiT game (NEST) model that captures the interaction between an escaping adversary and a defender with multiple resources and real-time information available. Second, solving NEST is proven to be NP-hard. Third, after transforming the non-convex program of solving NEST to a linear program, we propose our incremental strategy generation algorithm, including: (i) novel pruning techniques in our best response oracle; and (ii) novel techniques for mapping strategies between subgames and adding multiple best response strategies at one iteration to solve extremely large problems. Finally, extensive experiments show the effectiveness of our approach, which scales up to realistic problem sizes with hundreds of nodes on networks including the real network of Manhattan.

scholarly journals Analysis and Implementation of Threat Agents Profiles in Semi-Automated Manner for a Network Traffic in Real-Time Information Environment

Electronics ◽  
2021 ◽  
Vol 10 (15) ◽  
pp. 1849
Author(s):  
Gaurav Sharma ◽  
Stilianos Vidalis ◽  
Catherine Menon ◽  
Niharika Anand ◽  
Somesh Kumar
Keyword(s):  
Information Security ◽  
Real Time ◽  
Threat Assessment ◽  
Information Environment ◽  
Security Assurance ◽  
The Real ◽  
Threat Intelligence ◽  
Informational Environment ◽  
Real Time Information ◽  
Time Information

Threat assessment is the continuous process of monitoring the threats identified in the network of the real-time informational environment of an organisation and the business of the companies. The sagacity and security assurance for the system of an organisation and company’s business seem to need that information security exercise to unambiguously and effectively handle the threat agent’s attacks. How is this unambiguous and effective way in the present-day state of information security practice working? Given the prevalence of threats in the modern information environment, it is essential to guarantee the security of national information infrastructure. However, the existing models and methodology are not addressing the attributes of threats like motivation, opportunity, and capability (C, M, O), and the critical threat intelligence (CTI) feed to the threat agents during the penetration process is ineffective, due to which security assurance arises for an organisation and the business of companies. This paper proposes a semi-automatic information security model, which can deal with situational awareness data, strategies prevailing information security activities, and protocols monitoring specific types of the network next to the real-time information environment. This paper looks over analyses and implements the threat assessment of network traffic in one particular real-time informational environment. To achieve this, we determined various unique attributes of threat agents from the Packet Capture Application Programming Interface (PCAP files/DataStream) collected from the network between the years 2012 and 2019. We used hypothetical and real-world examples of a threat agent to evaluate the three different factors of threat agents, i.e., Motivation, Opportunity, and Capability (M, O, C). Based on this, we also designed and determined the threat profiles, critical threat intelligence (CTI), and complexity of threat agents that are not addressed or covered in the existing threat agent taxonomies models and methodologies.

Real-Time Information Capturing and Integration Framework of the Internet of Manufacturing Things

2011 ◽  
Vol 121-126 ◽  
pp. 4059-4063
Author(s):  
Ying Feng Zhang ◽  
Jun Qiang Wang ◽  
Shu Dong Sun
Keyword(s):  
Real Time ◽  
Process Management ◽  
Shop Floor ◽  
The Internet ◽  
New Paradigm ◽  
Time Data ◽  
The Real ◽  
Key Enabling Technologies ◽  
Real Time Information ◽  
Time Information

Recent developments in wireless sensors, communication and information network technologies have created a new era of the internet of things (IoT). To achieve the real-time data capturing from shop-floor front lines and the seamless dual-way connectivity and interoperability among enterprise layer, workshop floor layer and machine layer, a framework of the internet of manufacturing things (IoMT) is presented, which provides a new paradigm by extending the IoT to manufacturing field. Under this IoMT framework, the key enabling technologies such as configuration of sensor networks, sensing and capturing of manufacturing data, data processing and applications services etc. are designed and analyzed. The proposed IoMT framework and its key technologies will facilitate the real-time information driven optimum control and the operation efficiency during manufacturing execution process management.

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