scholarly journals Real-time data reduction at 100 Tbps: Challenge and opportunity for AI-based data reduction for next-generation large-scale nuclear physics collider experiment

2021 ◽  
Author(s):  
Ming Liu ◽  
Jin Huang ◽  
Sandeep Miryala ◽  
Yihui Ren
Keyword(s):  
Real Time ◽  
Data Reduction ◽  
Nuclear Physics ◽  
Large Scale ◽  
Next Generation ◽  
Time Data ◽  
Real Time Data ◽  
Collider Experiment

Machine Learning for Real-time Data Reduction in Cloud of Things

2020 ◽  
Author(s):  
Atheer Alahmed ◽  
Amal Alrasheedi ◽  
Maha Alharbi ◽  
Norah Alrebdi ◽  
Marwan Aleasa ◽  
...  
Keyword(s):  
Machine Learning ◽  
Real Time ◽  
Data Reduction ◽  
Time Data ◽  
Real Time Data

Next Generation of Real Time Data Acquisition, Calibration and Control System for the RatCAP Scanner

2007 ◽  
Author(s):  
Sachin S Junnarkar ◽  
Jack Fried ◽  
Sudeepti Southekal ◽  
Jean-Francois Pratte ◽  
Paul O'Connor ◽  
...  
Keyword(s):  
Control System ◽  
Data Acquisition ◽  
Real Time ◽  
Next Generation ◽  
Time Data ◽  
Real Time Data ◽  
And Control

scholarly journals An adaptive framework for real-time data reduction in AMI

2019 ◽  
Vol 31 (3) ◽  
pp. 392-402 ◽  
Author(s):  
Marwa F. Mohamed ◽  
Abd El-Rahman Shabayek ◽  
Mahmoud El-Gayyar ◽  
Hamed Nassar
Keyword(s):  
Real Time ◽  
Data Reduction ◽  
Time Data ◽  
Real Time Data ◽  
Adaptive Framework

A distributed real-time data prediction framework for large-scale time-series data using stream processing

2017 ◽  
Vol 10 (2) ◽  
pp. 145-165 ◽  
Author(s):  
Kehe Wu ◽  
Yayun Zhu ◽  
Quan Li ◽  
Ziwei Wu
Keyword(s):  
Time Series ◽  
Real Time ◽  
Large Scale ◽  
Time Series Data ◽  
Data Sources ◽  
Series Data ◽  
Time Data ◽  
Content Type ◽  
Data Prediction ◽  
Real Time Data

Purpose The purpose of this paper is to propose a data prediction framework for scenarios which require forecasting demand for large-scale data sources, e.g., sensor networks, securities exchange, electric power secondary system, etc. Concretely, the proposed framework should handle several difficult requirements including the management of gigantic data sources, the need for a fast self-adaptive algorithm, the relatively accurate prediction of multiple time series, and the real-time demand. Design/methodology/approach First, the autoregressive integrated moving average-based prediction algorithm is introduced. Second, the processing framework is designed, which includes a time-series data storage model based on the HBase, and a real-time distributed prediction platform based on Storm. Then, the work principle of this platform is described. Finally, a proof-of-concept testbed is illustrated to verify the proposed framework. Findings Several tests based on Power Grid monitoring data are provided for the proposed framework. The experimental results indicate that prediction data are basically consistent with actual data, processing efficiency is relatively high, and resources consumption is reasonable. Originality/value This paper provides a distributed real-time data prediction framework for large-scale time-series data, which can exactly achieve the requirement of the effective management, prediction efficiency, accuracy, and high concurrency for massive data sources.

Technology, Nature, Software and Networks: Materializing the Post-Romantic Landscape

Leonardo ◽  
2011 ◽  
Vol 44 (2) ◽  
pp. 101-106 ◽  
Author(s):  
Chris Welsby
Keyword(s):  
New Media ◽  
Real Time ◽  
Large Scale ◽  
Natural World ◽  
Time Data ◽  
Real Time Data ◽  
Weather Stations ◽  
Selection Of ◽  
Made In ◽  
Media Installation

The author began making films and installations in the early 1970s. Although he has worked across a range of media, he has always concentrated on one particular theme that he conceptualizes as a two-sided question: How do we see ourselves in relation to the natural world, and how should we position our selves and our technologies within it? This essay traces some of the threads of these seminal ideas through a selection of works made in the years between 1974 and 2009. The author concludes with a detailed description of Tree Studies, a large-scale new media installation powered by real-time data from weather stations around the planet.

INS real-time data processing composite system using large scale general purpose computers

1983 ◽  
Vol 213 (2-3) ◽  
pp. 317-327 ◽  
Author(s):  
Jun Kokame ◽  
Motonobu Takano ◽  
Tomoko Oshikubo ◽  
Kurazo Chiba ◽  
Kumataro Ukai ◽  
...  
Keyword(s):  
Data Processing ◽  
Real Time ◽  
Large Scale ◽  
Composite System ◽  
General Purpose ◽  
Time Data ◽  
Real Time Data ◽  
Real Time Data Processing
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