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Related Concept Videos

Virtual Work01:20

Virtual Work

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The principle of virtual work states that if a body is in static and dynamic equilibrium, then the sum of all the virtual work done by all external forces and couple moments for any given virtual displacement must be zero.
In static equilibrium, a body can experience an imaginary or virtual movement, such as displacement or rotation. The virtual work done by a force is equal to the dot product of force and virtual displacement in the direction of the force. When it comes to virtually rotating a...
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Distribution Reliability and Automation01:25

Distribution Reliability and Automation

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Distribution reliability in electrical power systems is critical for ensuring an uninterrupted power supply to consumers at minimal cost. According to IEEE Standard Terms, reliability is the probability that a device will function without failure over a specified time period or amount of usage. For electric power distribution, this translates to maintaining continuous power supply and addressing customer concerns over power outages. Several indices, as defined by IEEE Standard 1366-2012, are...
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Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

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Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
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Virtual Work for a System of Connected Rigid Bodies01:06

Virtual Work for a System of Connected Rigid Bodies

539
Virtual work is a powerful method used to solve problems involving several connected rigid bodies. When the system is in equilibrium, virtual work is zero. This allows the calculation of the resulting forces when a system undergoes a virtual displacement. When attempting to analyze such a system, first, use a free-body diagram, where an independent coordinate represents the configuration of the links, and mark its deflected position resulting from the positive virtual displacement.
Next,...
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Model Approaches for Pharmacokinetic Data: Physiological Models01:15

Model Approaches for Pharmacokinetic Data: Physiological Models

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Physiological models in pharmacokinetics are instrumental in understanding the distribution and elimination of drugs within the body. These models describe the drug concentration within target organs, influenced by factors such as drug uptake, tissue volume, and blood flow. Drug uptake is governed by the partition coefficient, which signifies the drug concentration ratio in tissue to that in the blood. The blood flow rate to a specific tissue is expressed as Qt, and the rate of change in tissue...
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Model Approaches for Pharmacokinetic Data: Compartment Models01:14

Model Approaches for Pharmacokinetic Data: Compartment Models

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Compartmental analysis is a widely adopted approach to characterizing drug pharmacokinetics. It uses compartment models that conceptualize the body as a collection of reversibly communicating compartments, each representing a group of tissues exhibiting similar drug distribution characteristics. The movement rate of the drug between these compartments is typically described by first-order kinetics.
Two primary types of compartment models are recognized: mammillary and catenary. The more...
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Automated Deployment of an Internet Protocol Telephony Service on Unmanned Aerial Vehicles Using Network Functions Virtualization
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A reference model for deploying applications in virtualized environments.

Enis Afgan1, Dannon Baker1,

  • 1Biology Department, Math & Computer Science Department, Emory University, Atlanta, GA.

Concurrency and Computation : Practice & Experience
|April 28, 2021
PubMed
Summary
This summary is machine-generated.

Deploying applications in virtual environments is simplified with a new reference model. This model enables transparent use of on-demand computational resources without application modifications, boosting infrastructure adoption.

Keywords:
application deploymentcloud computingreference model

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Area of Science:

  • Computer Science
  • Cloud Computing
  • Software Engineering

Background:

  • Modern scientific research relies on flexible computational infrastructure.
  • Virtualization enables on-demand computational resources, but adoption is hindered by usability challenges.
  • Deploying applications transparently in virtual environments is crucial for widespread acceptance.

Purpose of the Study:

  • To present a reference model for deploying applications into virtualised environments.
  • To address barriers to the adoption of virtualised computational infrastructure.
  • To enable transparent use of on-demand resources without application modification.

Main Methods:

  • Developed a reference model based on low-level components common to virtualised environments.
  • Composed dispersed components into a coherent unit for application deployment.
  • Implemented a framework for managing the overall application deployment.

Main Results:

  • Applications can be deployed into virtualised environments without modification.
  • The model imposes minimal overhead on infrastructure management.
  • Higher-level services are generated as a byproduct of component organization.

Conclusions:

  • The proposed reference model facilitates the transparent deployment of applications in virtualised environments.
  • This approach overcomes key barriers to the adoption of on-demand computational resources.
  • The model offers a scalable and efficient solution for managing applications in cloud infrastructure.