Efficient Data Representations That Preserve Information

2003 ◽  
pp. 16-16
Author(s):  
Naftali Tishby
Keyword(s):  
Data Representations ◽  
Efficient Data

Learning Efficient Data Representations With Orthogonal Sparse Coding

2016 ◽  
Vol 2 (3) ◽  
pp. 177-189 ◽  
Author(s):  
Henry Schutze ◽  
Erhardt Barth ◽  
Thomas Martinetz
Keyword(s):  
Sparse Coding ◽  
Data Representations ◽  
Efficient Data

IoT based e-Healthcare System to Enable Remote Patient Care based on Cloud Server

2017 ◽  
Vol 7 (7) ◽  
pp. 36
Author(s):  
P.Venu Gopala Rao ◽  
Eslavath Raja ◽  
Ramakrishna Gandi ◽  
G. Ravi Kumar
Keyword(s):  
Low Cost ◽  
Vital Signs ◽  
Smart Phone ◽  
Medical Professional ◽  
Design Parameters ◽  
Cloud Server ◽  
Significant Area ◽  
Efficient Data ◽  
System Data ◽  
Remote Patient

IoT (Internet of Things) has become most significant area of research to design an efficient data enabled services with the help of sensors. In this paper, a low-cost system design for e-healthcare service to process the sensitive health data is presented. Vital signs of the human body are measured from the patient location and shared with a registered medical professional for consultation. Temperature and heart rate are the major signals obtained from a patient for the initial build of the system. Data is sent to a cloud server where processing and analysis is provided for the medical professional to analyze. Secure transmission and dissemination of data through the cloud server is provided with an authentication system and the patient could be able to track his data through a smart phone on connecting to the cloud server. A prototype of the system along with its design parameters has been discussed.

Mahakam Field Characterization Using Production Type-Curve With Business Intelligence Application

2020 ◽  
Author(s):  
P. Noverri
Keyword(s):  
Business Intelligence ◽  
Data Gathering ◽  
Production Data ◽  
Type Curve ◽  
Type Curves ◽  
Production Type ◽  
Efficient Data ◽  
Production Behavior ◽  
Factor Type ◽  
Mahakam Delta

Delta Mahakam is a giant hydrocarbon block which is comprised two oil fields and five gas fields. The giant block has been considered mature after production for more than 40 years. More than 2,000 wells have been drilled to optimize hydrocarbon recovery. From those wells, a huge amount of production data is available and documented in a well-structured manner. Gaining insight from this data is highly beneficial to understand fields behavior and their characteristics. The fields production characterization is analyzed with Production Type-Curve method. In this case, type curves were generated from production data ratio such as CGR, WGR and GOR to field recovery factor. Type curve is considered as a simple approach to find patterns and capture a helicopter view from a huge volume of production data. Utilization of business intelligence enables efficient data gathering from different data sources, data preparation and data visualization through dashboards. Each dashboard provides a different perspective which consists of field view, zone view, sector view and POD view. Dashboards allow users to perform comprehensive analysis in describing production behavior. Production type-curve analysis through dashboards show that fields in the Mahakam Delta can be grouped based on their production behavior and effectively provide global field understanding Discovery of production key information from proposed methods can be used as reference for prospective and existing fields development in the Mahakam Delta. This paper demonstrates an example of production type-curve as a simple yet efficient method in characterizing field production behaviors which is realized by a Business Intelligent application

Efficient Data Maintenance Scheme for Peer-to-Peer Storage Systems

2009 ◽  
Vol 20 (1) ◽  
pp. 80-95 ◽  
Author(s):  
Zhi YANG ◽  
Jun ZHU ◽  
Ya-Fei DAI
Keyword(s):  
Storage Systems ◽  
Peer To Peer ◽  
Efficient Data ◽  
Data Maintenance
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