COVID-19 Multi-Modal Data Analysis with Alexa Voice and Conversational AI Applications : Voice First System Tracking Novel Coronavirus

2021 ◽  
Author(s):  
Alex Kaplunovich
Keyword(s):  
Data Analysis ◽  
Modal Data ◽  
Novel Coronavirus

Multi-modal Data Analysis and Fusion for Robust Object Detection in 2D/3D Sensing

2020 ◽  
Author(s):  
Jonathan Schierl ◽  
Quinn Graehling ◽  
Theus Aspiras ◽  
Vijay Asari ◽  
Andre Van Rynbach ◽  
...  
Keyword(s):  
Data Analysis ◽  
Object Detection ◽  
Modal Data ◽  
3D Sensing

scholarly journals Multi-Modal Data Analysis Based Game Player Experience Modeling Using LSTM-DNN

2021 ◽  
Vol 68 (3) ◽  
pp. 4087-4108
Author(s):  
Sehar Shahzad Farooq ◽  
Mustansar Fiaz ◽  
Irfan Mehmood ◽  
Ali Kashif Bashir ◽  
Raheel Nawaz ◽  
...  
Keyword(s):  
Data Analysis ◽  
Modal Data ◽  
Game Player ◽  
Player Experience

scholarly journals P1-533: DEMENTIAS PLATFORM UK DATA PORTAL - MULTI-MODAL DATA ANALYSIS USING CUSTOMISED INFRASTRUCTURE

2019 ◽  
Vol 15 ◽  
pp. P474-P474
Author(s):  
Christopher Orton ◽  
John Gallacher ◽  
Sarah Bauermeister ◽  
Ronan A. Lyons ◽  
Simon Thompson ◽  
...  
Keyword(s):  
Data Analysis ◽  
Modal Data ◽  
Data Portal

scholarly journals Forecasting the Epidemiological Impact of Coronavirus Disease (COVID-19): Pre-vaccination Era

2021 ◽  
Author(s):  
Saheed Oladele Amusat
Keyword(s):  
Data Analysis ◽  
Prevention And Control ◽  
Historical Data ◽  
Secondary Data ◽  
The Novel ◽  
Intervention Method ◽  
The Us ◽  
Epidemiological Impact ◽  
Novel Coronavirus ◽  
And Control

Background: During this pandemic, many studies have been published on the virology, diagnosis, prevention, and control of the novel coronavirus. However, fewer studies are currently available on the quantitative future epidemiological impacts. Therefore, the purpose of this study is to forecast the COVID-19 morbidities and associated-mortalities among the top 20 countries with the highest number of confirmed COVID-19 cases globally prior to vaccination intervention. Method: We conducted a secondary data analysis of the prospective geographic distribution of COVID-19 cases data worldwide as of 10 April 2020. The historical data was forecasted using Exponential-Smoothing to detect seasonality patterns and confidence intervals surrounding each predicted value in which 95 percent of the future points are expected to fall based on the forecast. Results: The total mean forecasted cases and deaths were 99,823 and 8,801. Interestingly, the US has the highest forecasted cases, deaths, and percentage cases-deaths ratio of 45,338, 2 358, and 5.20% respectively. China has the lowest cases, deaths, and percentage cases-deaths ratio -267, -2, and 0.75% respectively. In addition, France has the highest forecasted percentage cases-deaths ratio of 26.40% with forecasted cases, and deaths of 6,246, and 1,649 respectively. Conclusion Our study revealed the possibility of higher COVID-19 morbidities and associated-mortalities worldwide.

scholarly journals Special issue on multimedia recommendation and multi-modal data analysis

2019 ◽  
Vol 25 (6) ◽  
pp. 591-592
Author(s):  
Xiangnan He ◽  
Zhenguang Liu ◽  
Hanwang Zhang ◽  
Chong-Wah Ngo ◽  
Svebor Karaman ◽  
...  
Keyword(s):  
Data Analysis ◽  
Special Issue ◽  
Modal Data ◽  
Multimedia Recommendation

scholarly journals Prevention- Versus Promotion-Focus Regulatory Efforts on the Disease Incidence and Mortality of COVID-19: A Multinational Diffusion Study Using Functional Data Analysis

2020 ◽  
pp. 1069031X2096656
Author(s):  
V. Kumar ◽  
Ashish Sood ◽  
Shaphali Gupta ◽  
Nitish Sood
Keyword(s):  
Data Analysis ◽  
Functional Data Analysis ◽  
Functional Data ◽  
Regulatory Focus ◽  
Disease Incidence ◽  
Data Set ◽  
Moderating Factors ◽  
Incidence And Mortality ◽  
Novel Coronavirus ◽  
Nonpharmaceutical Interventions

International marketing has rarely explored the diffusion patterns of the spread of a disease or analyzed the factors explaining the differences in the disease incidence patterns. The rapid diffusion of the novel coronavirus has engulfed the entire world in a very short time. Many countries experienced different levels of disease incidence and mortality despite implementing similar nonpharmaceutical interventions (NPIs). Drawing on the regulatory focus theory, the authors propose a framework to conceptualize and investigate the comparative efficacy of diverse NPIs that countries could adopt to prevent or curtail the diffusion of the disease incidence and mortality. They categorize these NPIs as prevention focused (containment and closures) or promotion focused (relief measures and public health infrastructure) and discuss the moderating factors that enhance or impede their effectiveness. Employing functional data analysis, the authors examine a comprehensive data set across 70 countries. They find that prevention-focused interventions inhibit disease incidence, while promotion-focused interventions enhance the nation’s ability to respond to medical emergencies and augment people’s ability to isolate themselves and slow the spread. The authors also generate insights on how a reallocation of resources between prevention- and promotion-focused efforts influence the evolution of disease incidence and mortality, with various countries falling in different clusters.

Sign in / Sign up

Export Citation Format

Share Document