Spatio-Temporal Data Models with Their Different Approaches and Their Features

Rathee, Sonia; Rishi, Rahul

doi:10.1109/acct.2015.46

Cited by 3 publications

(2 citation statements)

References 19 publications

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“…TDB are coupled with GDB giving birth to the concept of Spatio-temporal DB (STDB). Some surveys have been published on the different types of spatio-temporal data models that have been proposed (Abraham & Roddick, 1999;Rathee & Yadav, 2013). In (Li, Tong & Liu, 2008), the authors propose a new unified version spatio-temporal data model (UVSTDM).…”

Section: Versioning In Computer Sciencementioning

confidence: 99%

Using Temporal Versioning and Integrity Constraints for Updating Geographic Databases and Maintaining Their Consistency

Jaziri

Sassi

Damak

2015

Journal of Database Management

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The use of geographic data has become a widespread concern, mainly within applications related to spatial planning and spatial decision-making. Therefore, changing environments require databases adaptable to changes that occur over time. Thus, supporting geographic information evolution is essential and extremely important within changing environments. The evolution is expressed in the geographic database by series of update operations that should maintain its consistency. This paper proposes an approach for updating geographic databases, based on update operators and algorithms of constraints integrity checking. Temporal versioning is used to keep the track of changes. Every version presents the state of the geographic database at a given time. Algorithms of constraints integrity checking allow maintaining the database consistency upon its update. To implement our approach and assist users in the evolution process, the GeoVersioning tool is developed and tested on a sample geographic database.

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Section: Versioning In Computer Sciencementioning

confidence: 99%

Using Temporal Versioning and Integrity Constraints for Updating Geographic Databases and Maintaining Their Consistency

Jaziri

Sassi

Damak

2015

Journal of Database Management

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“…By January 2021, Operation Warp Speed [12] intends to distribute 300,000,000 doses of a COVID-19 vaccination that is both safe and effective. Safety issues, on the other hand, continue to slow development [13]. As potential candidates begin to prepare to enter the market, optimal distribution techniques that will reduce the pandemic as quickly as feasible will be required [14] [15].…”

Section: Introductionmentioning

confidence: 99%

Spatio-Temporal distribution characteristic of covid-19 vaccine using time series forecasting

Talan¹,

Rathee²,

Gandhi

2022

2022 12th International Conference on Cloud Computing, Data Science &Amp; Engineering (Confluence)

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Over 170 nations have been affected from Coronavirus disease 2019(COVID-19). In nearly all the afflicted countries, the number of afflicted people and dying people has been rising at a frightening rate. Our biggest option for halting the pandemic's spread is a COVID-19 vaccination. But vaccines are an exhaustible resource. Accurate prediction of vaccine distribution by already implemented policies is critical to assisting policymakers in making sufficient decisions in containing COVID-19 pandemic. Forecasting approaches can be utilized, aiding in the development of better plans and the making of sound judgments. These approaches analyze past events to make more accurate predictions about what will happen in the future according to the current implemented strategy. The effectiveness of various LSTM (Long Short-Term Memory) models as well as the ARIMA (Auto-Regressive Integrated Moving Average) model in projecting vaccine distribution for COVID-19 patients.

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