scholarly journals ActiveSpaces: Exploring dynamic code deployment for extreme scale data processing

2014 ◽  
Vol 27 (14) ◽  
pp. 3724-3745 ◽  
Author(s):  
Ciprian Docan ◽  
Fan Zhang ◽  
Tong Jin ◽  
Hoang Bui ◽  
Qian Sun ◽  
...  
Keyword(s):  
Data Processing ◽  
Extreme Scale ◽  
Scale Data

Advanced monitoring techniques for a large‐scale data‐processing network

2008 ◽  
Vol 25 (5) ◽  
pp. 287-300 ◽  
Author(s):  
B. Martin ◽  
A. Al‐Shabibi ◽  
S.M. Batraneanu ◽  
Ciobotaru ◽  
G.L. Darlea ◽  
...  
Keyword(s):  
Data Processing ◽  
Large Scale ◽  
Monitoring Techniques ◽  
Large Scale Data ◽  
Large Scale Data Processing ◽  
Processing Network ◽  
Scale Data

BestPeer++: A Peer-to-Peer Based Large-Scale Data Processing Platform

2014 ◽  
Vol 26 (6) ◽  
pp. 1316-1331 ◽  
Author(s):  
Gang Chen ◽  
Tianlei Hu ◽  
Dawei Jiang ◽  
Peng Lu ◽  
Kian-Lee Tan ◽  
...  
Keyword(s):  
Data Processing ◽  
Large Scale ◽  
Peer To Peer ◽  
Large Scale Data ◽  
Large Scale Data Processing ◽  
Processing Platform ◽  
Scale Data

scholarly journals Medimate : Ailment Diffusion Control System with Real Time Large Scale Data Processing

2018 ◽  
Vol 7 (2.31) ◽  
pp. 240
Author(s):  
S Sujeetha ◽  
Veneesa Ja ◽  
K Vinitha ◽  
R Suvedha
Keyword(s):  
Control System ◽  
Data Processing ◽  
Real Time ◽  
Large Scale ◽  
Diffusion Control ◽  
Qr Code ◽  
Healthcare Applications ◽  
Large Scale Data ◽  
Large Scale Data Processing ◽  
Scale Data

In the existing scenario, a patient has to go to the hospital to take necessary tests, consult a doctor and buy prescribed medicines or use specified healthcare applications. Hence time is wasted at hospitals and in medical shops. In the case of healthcare applications, face to face interaction with the doctor is not available. The downside of the existing scenario can be improved by the Medimate: Ailment diffusion control system with real time large scale data processing. The purpose of medimate is to establish a Tele Conference Medical System that can be used in remote areas. The medimate is configured for better diagnosis and medical treatment for the rural people. The system is installed with Heart Beat Sensor, Temperature Sensor, Ultrasonic Sensor and Load Cell to monitor the patient’s health parameters. The voice instructions are updated for easier access.  The application for enabling video and voice communication with the doctor through Camera and Headphone is installed at both the ends. The doctor examines the patient and prescribes themedicines. The medical dispenser delivers medicine to the patient as per the prescription. The QR code will be generated for each prescription by medimate and that QR code can be used forthe repeated medical conditions in the future. Medical details are updated in the server periodically.  

A Novel Data Processing Method for Ice Pressure Statistics

2015 ◽  
Author(s):  
Karoline M. Neumann ◽  
Sören Ehlers ◽  
Bernt J. Leira ◽  
Pentti Kujala
Keyword(s):  
Data Processing ◽  
Design Parameter ◽  
Processing Method ◽  
Full Scale ◽  
Cumulative Distribution ◽  
Discrete Events ◽  
Data Processing Method ◽  
Ice Loads ◽  
Ice Pressure ◽  
Scale Data

Maritime activities in ice bound areas increase demand for design of structures to withstand ice loads. A cumulative distribution with parameter α as a function of area is published in ISO19906 [1], based on analysis of multiple different discrete full scale rams from Jordaan [2] for application on design loads of discrete impacts. Taylor [3] performs a reanalysis including more full scale data, and taking into account the effect of exposure, presents design parameter curves α-area and x0-area. These are valuable, but are to be applied for design of discrete events, and can only be obtained from discrete event data. The objective of this paper is to describe and demonstrate a data processing method based on semi-continuous ice pressure data that can be applied not only for discrete events, but also for semi-continuous interaction. A finely meshed tactile sensor is applied. Jordaan’s [2] max event method is applied on a new definition of event, based on triggered sensels that are adjacent in time and space. The method is demonstrated on a model scale data set from Aalto University, and example design parameter curves are presented. Applying the developed method on full scale data, the results can be valuable for design of semi-continuous ice loads.

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