Real time stabilization of long range observation system turbulent video

2007 ◽  
Author(s):  
Barak Fishbain ◽  
Leonid P. Yaroslavsky ◽  
Ianir A. Ideses ◽  
Ofer Ben-Zvi ◽  
Alon Shtern
Keyword(s):  
Real Time ◽  
Long Range ◽  
Observation System ◽  
Range Observation

scholarly journals Real-time stabilization of long range observation system turbulent video

2007 ◽  
Vol 2 (1) ◽  
pp. 11-22 ◽  
Author(s):  
Barak Fishbain ◽  
Leonid P. Yaroslavsky ◽  
Ianir A. Ideses
Keyword(s):  
Real Time ◽  
Long Range ◽  
Observation System ◽  
Range Observation

Prediction of aircraft engine emissions using ADS-B flight data

2021 ◽  
pp. 1-25
Author(s):  
A. Filippone ◽  
B. Parkes ◽  
N. Bojdo ◽  
T. Kelly
Keyword(s):  
Real Time ◽  
Water Vapour ◽  
Long Range ◽  
Aircraft Engine ◽  
Software Systems ◽  
Engine Emissions ◽  
Flight Data ◽  
Seasonal Basis ◽  
Emissions Inventories ◽  
Aviation Emissions

ABSTRACT Real-time flight data from the Automatic Dependent Surveillance–Broadcast (ADS-B) has been integrated, through a data interface, with a flight performance computer program to predict aviation emissions at altitude. The ADS-B, along with data from Mode-S, are then used to ‘fly’ selected long-range aircraft models (Airbus A380-841, A330-343 and A350-900) and one turboprop (ATR72). Over 2,500 flight trajectories have been processed to demonstrate the integration between databases and software systems. Emissions are calculated for altitudes greater than 3,000 feet (609m) and exclude landing and take-off cycles. This proof of concept fills a gap in the aviation emissions inventories, since it uses real-time flights and produces estimates at a very granular level. It can be used to analyse emissions of gases such as carbon dioxide ( $\mathrm{CO}_2$ ), carbon monoxide (CO), nitrogen oxides ( $\mathrm{NO}_x$ ) and water vapour on a specific route (city pair), for a specific aircraft, for an entire fleet, or on a seasonal basis. It is shown how $\mathrm{NO}_x$ and water vapour emissions concentrate around tropospheric altitudes only for long-range flights, and that the cruise range is the biggest discriminator in the absolute value of these and other exhaust emissions.

scholarly journals Improving the Stochastic Model of Ionospheric Delays for BDS Long-Range Real-Time Kinematic Positioning

2021 ◽  
Vol 13 (14) ◽  
pp. 2739
Author(s):  
Huizhong Zhu ◽  
Jun Li ◽  
Longjiang Tang ◽  
Maorong Ge ◽  
Aigong Xu
Keyword(s):  
Real Time ◽  
Long Range ◽  
Ionospheric Delay ◽  
Time Interval ◽  
Short Time Interval ◽  
Dual Frequency ◽  
Triple Frequency ◽  
Ambiguity Fixing ◽  
Power Spectral ◽  
Observation Noise

Although ionosphere-free (IF) combination is usually employed in long-range precise positioning, in order to employ the knowledge of the spatiotemporal ionospheric delays variations and avoid the difficulty in choosing the IF combinations in case of triple-frequency data processing, using uncombined observations with proper ionospheric constraints is more beneficial. Yet, determining the appropriate power spectral density (PSD) of ionospheric delays is one of the most important issues in the uncombined processing, as the empirical methods cannot consider the actual ionosphere activities. The ionospheric delays derived from actual dual-frequency phase observations contain not only the real-time ionospheric delays variations, but also the observation noise which could be much larger than ionospheric delays changes over a very short time interval, so that the statistics of the ionospheric delays cannot be retrieved properly. Fortunately, the ionospheric delays variations and the observation noise behave in different ways, i.e., can be represented by random-walk and white noise process, respectively, so that they can be separated statistically. In this paper, we proposed an approach to determine the PSD of ionospheric delays for each satellite in real-time by denoising the ionospheric delay observations. Based on the relationship between the PSD, observation noise and the ionospheric observations, several aspects impacting the PSD calculation are investigated numerically and the optimal values are suggested. The proposed approach with the suggested optimal parameters is applied to the processing of three long-range baselines of 103 km, 175 km and 200 km with triple-frequency BDS data in both static and kinematic mode. The improvement in the first ambiguity fixing time (FAFT), the positioning accuracy and the estimated ionospheric delays are analysed and compared with that using empirical PSD. The results show that the FAFT can be shortened by at least 8% compared with using a unique empirical PSD for all satellites although it is even fine-tuned according to the actual observations and improved by 34% compared with that using PSD derived from ionospheric delay observations without denoising. Finally, the positioning performance of BDS three-frequency observations shows that the averaged FAFT is 226 s and 270 s, and the positioning accuracies after ambiguity fixing are 1 cm, 1 cm and 3 cm in the East, North and Up directions for static and 3 cm, 3 cm and 6 cm for kinematic mode, respectively.

Industry First AI-Powered Fully Automated Safety Observation System Deployed to Global Offshore Fleet

2021 ◽  
Author(s):  
Nassima Brown ◽  
Adrian Brown ◽  
Abhijeet Degupta ◽  
Barry Quinn ◽  
Dustin Stringer ◽  
...  
Keyword(s):  
Real Time ◽  
Safety Culture ◽  
Safety Management ◽  
Digital Technologies ◽  
Observation System ◽  
Safety Program ◽  
Effective Application ◽  
Behavior Based ◽  
Global Operations ◽  
The Impact

Abstract As the oil and gas industry is facing tumultuous challenges, adoption of cutting-edge digital technologies has been accelerated to deliver safer, more efficient operations with less impact on the environment. While advanced AI and other digital technologies have been rapidly evolving in many fields in the industry, the HSE sector is playing catch-up. With the increasing complexity of risks and safety management processes, the effective application of data-driven technologies has become significantly harder, particularly for international organizations with varying levels of digital readiness across diverse global operations. Leaders are more cautious to implement solutions that are not fit-for purpose, due to concerns over inconsistencies in rolling out the program across international markets and the impact this may have on ongoing operations. This paper describes how the effective application of Artificial intelligence (AI) and Machine Learning (ML) technologies have been used to engineer a solution that fully digitizes and automates the end-to-end offshore behavior-based safety program across a global offshore fleet; optimizing a critical safety process used by many leading oil & gas organization to drive positive workplace safety culture. The complex safety program has been transformed into clear, efficient and automated workflow, with real-time analytics and live transparent dashboards which detail critical safety indicators in real time, aiding decision-making and improving operational performance. The novel behavior-based safety digital solution, referred to as 3C observation tool within Noble drilling, has been built to be fully aligned with the organization's safety management system requirements and procedures, using modern and agile tools and applications for fully scalability and easy deployment. It has been critical in sharpening the offshore safety observation program across global operations, resulting in a boost of the workforce engagement by 30%, and subsequently increasing safety awareness skill set attainment; improving overall offshore safety culture, all while reducing operating costs by up to 70% and cutting carbon footprint through the elimination of 15,000 manhours and half a million paper cards each year, when compared to previously used methods and workflows

The Copernicus global 1/12° oceanic and sea ice reanalysis

2021 ◽  
Author(s):  
Jean-Michel Lellouche ◽  
Romain Bourdalle-Badie ◽  
Eric Greiner ◽  
Gilles Garric ◽  
Angelique Melet ◽  
...  
Keyword(s):  
Sea Ice ◽  
Real Time ◽  
Sea Level ◽  
Observation System ◽  
Small Scale ◽  
Free Access ◽  
In Situ Observation ◽  
Seasonal Forecasts ◽  
Concentration Data

<p>The GLORYS12V1 system is a global eddy-resolving physical ocean and sea ice reanalysis at 1/12° resolution covering the 1993-present altimetry period, designed and implemented in the framework of the Copernicus Marine Environment Monitoring Service (CMEMS). All the essential ocean physical variables from this reanalysis are available with free access through the CMEMS data portal.</p><p>The GLORYS12V1 reanalysis is based on the current CMEMS global real-time forecasting system, apart from a few specificities that are detailed in this manuscript. The model component is the NEMO platform driven at the surface by atmospheric conditions from the ECMWF ERA-Interim reanalysis. Ocean observations are assimilated by means of a reduced-order Kalman filter. Along track altimeter sea level anomaly, satellite sea surface temperature and sea ice concentration data and in situ temperature and salinity (T/S) vertical profiles are jointly assimilated. A 3D-VAR scheme provides an additional correction for the slowly-evolving large-scale biases in temperature and salinity.</p><p>The performance of the reanalysis is first addressed in the space of the assimilated observations and shows a clear dependency on the time-dependent in situ observation system, which is intrinsic to most reanalyses. The general assessment of GLORYS12V1 highlights a level of performance at the state-of-the-art and the reliability of the system to correctly capture the main expected climatic interannual variability signals for ocean and sea ice, the general circulation and the inter-basins exchanges. In terms of trends, GLORYS12V1 shows a higher than observed  warming trend together with a lower than observed global mean sea level rise.</p><p>Comparisons made with an experiment carried out on the same platform without assimilation show the benefit of data assimilation in controlling water masses properties and their low frequency variability. Examination of the deep signals below 2000 m depth shows that the reanalysis does not suffer from artificial signals even in the pre-Argo period.</p><p>Moreover, GLORYS12V1 represents particularly well the small-scale variability of surface dynamics and compares well with independent (non-assimilated) data. Comparisons made with a twin experiment carried out at ¼° resolution allows characterizing and quantifying the strengthened contribution of the 1/12° resolution onto the downscaled dynamics.</p><p>In conclusion, GLORYS12V1 provides a reliable physical ocean state for climate variability and supports applications such as seasonal forecasts. In addition, this reanalysis has strong assets to serve regional applications and should provide relevant physical conditions for applications such as marine biogeochemistry. In a near future, GLORYS12V1 will be maintained to be as close as possible to real time and could therefore provide a relevant reference statistical framework for many operational applications.</p>

Traffic Controller for Handling Service Quality in Multimedia Network

2010 ◽  
pp. 96-112
Author(s):  
Manjunath Ramachandra ◽  
Vikas Jain
Keyword(s):  
Real Time ◽  
Long Range ◽  
Multimedia Data ◽  
Time Data ◽  
Self Similarity ◽  
Real Time Data ◽  
Data Transfers ◽  
Multimedia Network ◽  
Different Origin

The present day Internet traffic largely caters for the multimedia traffic throwing open new and unthinkable applications such as tele-surgery. The complexity of data transactions increases with a demand for in time and real time data transfers, demanding the limited resources of the network beyond their capabilities. It requires a prioritization of data transfers, controlled dumping of data over the network etc. To make the matter worse, the data from different origin combine together imparting long lasting detrimental features such as self similarity and long range dependency in to the traffic. The multimedia data fortunately is associated with redundancies that may be removed through efficient compression techniques. There exists a provision to control the compression or bitrates based on the availability of resources in the network. The traffic controller or shaper has to optimize the quality of the transferred multimedia data depending up on the state of the network. In this chapter, a novel traffic shaper is introduced considering the adverse properties of the network and counteract with the same.

Real-time long range complementary correlation optical time domain reflectometer

1989 ◽  
Vol 7 (1) ◽  
pp. 24-38 ◽  
Author(s):  
M. Nazarathy ◽  
S.A. Newton ◽  
R.P. Giffard ◽  
D.S. Moberly ◽  
F. Sischka ◽  
...  
Keyword(s):  
Real Time ◽  
Long Range ◽  
Time Domain ◽  
Optical Time Domain Reflectometer ◽  
Optical Time ◽  
Time Domain Reflectometer
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