Virtual Conversation with Real-Time Prediction of Body Moments/Gestures on Video Streaming Data

2020 ◽  
pp. 113-126
Author(s):  
Gopichand Agnihotram ◽  
Rajesh Kumar ◽  
Pandurang Naik ◽  
Rahul Yadav
Keyword(s):  
Real Time ◽  
Video Streaming ◽  
Streaming Data ◽  
Time Prediction

scholarly journals Regional Influenza Prediction with Sampling Twitter Data and PDE Model

2020 ◽  
Vol 17 (3) ◽  
pp. 678 ◽  
Author(s):  
Yufang Wang ◽  
Kuai Xu ◽  
Yun Kang ◽  
Haiyan Wang ◽  
Feng Wang ◽  
...  
Keyword(s):  
Social Media ◽  
Real Time ◽  
Streaming Data ◽  
Data Sampling ◽  
Timely Manner ◽  
Pde Model ◽  
Time Prediction ◽  
Twitter Data ◽  
Sampling Process ◽  
Natural Choice

The large volume of geotagged Twitter streaming data on flu epidemics provides chances for researchers to explore, model, and predict the trends of flu cases in a timely manner. However, the explosive growth of data from social media makes data sampling a natural choice. In this paper, we develop a method for influenza prediction based on the real-time tweet data from social media, and this method ensures real-time prediction and is applicable to sampling data. Specifically, we first simulate the sampling process of flu tweets, and then develop a specific partial differential equation (PDE) model to characterize and predict the aggregated flu tweet volumes. Our PDE model incorporates the effects of flu spreading, flu recovery, and active human interventions for reducing flu. Our extensive simulation results show that this PDE model can almost eliminate the data reduction effects from the sampling process: It requires lesser historical data but achieves stronger prediction results with a relative accuracy of over 90% on the 1% sampling data. Even for the more aggressive data sampling ratios such as 0.1% and 0.01% sampling, our model is still able to achieve relative accuracies of 85% and 83%, respectively. These promising results highlight the ability of our mechanistic PDE model in predicting temporal–spatial patterns of flu trends even in the scenario of small sampling Twitter data.

scholarly journals A Study of Real-Time Video Streaming Data Service on the Linux Server

2013 ◽  
Vol 17 (4) ◽  
pp. 893-901
Author(s):  
Seung-Ju Jang ◽  
Won-Yeong Heo ◽  
Hyun-Min Yoo ◽  
Chang-Hoon Lee ◽  
Woo-Ho Shin
Keyword(s):  
Real Time ◽  
Video Streaming ◽  
Streaming Data ◽  
Data Service

Human Pose Simulation and Detection in Real Time Using Video Streaming Data

2020 ◽  
Vol 1 (3) ◽  
Author(s):  
Prasanth Kumar Ponnarassery ◽  
Gopichand Agnihotram ◽  
Pandurang Naik
Keyword(s):  
Real Time ◽  
Video Streaming ◽  
Streaming Data ◽  
Human Pose

Real-time prediction of breast lesions displacement during Ultrasound scanning using a position-based dynamics approach

2019 ◽  
Author(s):  
D Dall Alba ◽  
◽  
E Tagliabue ◽  
E Magnabosco ◽  
C Tenga ◽  
...  
Keyword(s):  
Real Time ◽  
Breast Lesions ◽  
Ultrasound Scanning ◽  
Time Prediction

Opinion Mining with Real Time Ontology Streaming Data

2019 ◽  
Vol 23 (1) ◽  
pp. 346-357
Author(s):  
Vithya G ◽  
Naren J ◽  
Varun V
Keyword(s):  
Real Time ◽  
Opinion Mining ◽  
Streaming Data

Real-Time Prediction of Tropical Cyclone Intensity Using COAMPS-TC

2012 ◽  
Author(s):  
J. D. Doyle ◽  
R. M. Hodur ◽  
S. Chen ◽  
H. Jin ◽  
Y. Jin ◽  
...  
Keyword(s):  
Tropical Cyclone ◽  
Real Time ◽  
Tropical Cyclone Intensity ◽  
Cyclone Intensity ◽  
Time Prediction

scholarly journals Real-time prediction of 1H and 13C chemical shifts with DFT accuracy using a 3D graph neural network

2021 ◽  
Author(s):  
Yanfei Guan ◽  
S. V. Shree Sowndarya ◽  
Liliana C. Gallegos ◽  
Peter C. St. John ◽  
Robert S. Paton
Keyword(s):  
Neural Network ◽  
Real Time ◽  
Quantum Chemical ◽  
Organic Molecules ◽  
Chemical Shifts ◽  
13C Chemical Shifts ◽  
Time Prediction ◽  
Nmr Data ◽  
Proton Chemical Shifts

From quantum chemical and experimental NMR data, a 3D graph neural network, CASCADE, has been developed to predict carbon and proton chemical shifts. Stereoisomers and conformers of organic molecules can be correctly distinguished.

scholarly journals Real-Time Prediction of Equivalent Circulation Density for Horizontal Wells Using Intelligent Machines

ACS Omega ◽  
2020 ◽  
Author(s):  
Ahmed Alsaihati ◽  
Salaheldin Elkatatny ◽  
Abdulazeez Abdulraheem
Keyword(s):  
Real Time ◽  
Horizontal Wells ◽  
Intelligent Machines ◽  
Time Prediction
Sign in / Sign up

Export Citation Format

Share Document