Automated Filtering on Data Streaming for Intelligence Analysis

Author(s):  
Yiming Ma ◽  
Dawit Yimam Seid ◽  
Sharad Mehrotra
Author(s):  
William Elm ◽  
Scott Potter ◽  
James Tittle ◽  
David Woods ◽  
Justin Grossman ◽  
...  

2007 ◽  
Author(s):  
Phillip J. Ayoub ◽  
Irene J. Petrick ◽  
Michael D. McNeese

Author(s):  
Manbir Sandhu ◽  
Purnima, Anuradha Saini

Big data is a fast-growing technology that has the scope to mine huge amount of data to be used in various analytic applications. With large amount of data streaming in from a myriad of sources: social media, online transactions and ubiquity of smart devices, Big Data is practically garnering attention across all stakeholders from academics, banking, government, heath care, manufacturing and retail. Big Data refers to an enormous amount of data generated from disparate sources along with data analytic techniques to examine this voluminous data for predictive trends and patterns, to exploit new growth opportunities, to gain insight, to make informed decisions and optimize processes. Data-driven decision making is the essence of business establishments. The explosive growth of data is steering the business units to tap the potential of Big Data to achieve fueling growth and to achieve a cutting edge over their competitors. The overwhelming generation of data brings with it, its share of concerns. This paper discusses the concept of Big Data, its characteristics, the tools and techniques deployed by organizations to harness the power of Big Data and the daunting issues that hinder the adoption of Business Intelligence in Big Data strategies in organizations.


2013 ◽  
Author(s):  
Christina M. Kampman ◽  
Charles A. Mangio ◽  
Melinda Marsh

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Svenja Ipsen ◽  
Sven Böttger ◽  
Holger Schwegmann ◽  
Floris Ernst

AbstractUltrasound (US) imaging, in contrast to other image guidance techniques, offers the distinct advantage of providing volumetric image data in real-time (4D) without using ionizing radiation. The goal of this study was to perform the first quantitative comparison of three different 4D US systems with fast matrix array probes and real-time data streaming regarding their target tracking accuracy and system latency. Sinusoidal motion of varying amplitudes and frequencies was used to simulate breathing motion with a robotic arm and a static US phantom. US volumes and robot positions were acquired online and stored for retrospective analysis. A template matching approach was used for target localization in the US data. Target motion measured in US was compared to the reference trajectory performed by the robot to determine localization accuracy and system latency. Using the robotic setup, all investigated 4D US systems could detect a moving target with sub-millimeter accuracy. However, especially high system latency increased tracking errors substantially and should be compensated with prediction algorithms for respiratory motion compensation.


Author(s):  
Meer Shadman Shafkat Tanjim ◽  
Shoyeb Ahammad Rafi ◽  
Ashrafun Nushra Oishi ◽  
Sourav Barua ◽  
Hridoy Chandra Dey ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document