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Related Concept Videos

Reducing Line Loss01:18

Reducing Line Loss

In a three-phase circuit, line loss is an indicator of energy dissipated as heat due to the resistance of transmission lines. To address this, incorporating transformers into the system—a step-up transformer at the source and a step-down transformer at the load—is a strategic solution. Two three-phase transformers are introduced to improve this.
With a step-up transformer at the source, the voltage is increased, thereby reducing the current in the transmission lines since power loss in...
Maximum Power Flow and Line Loadability01:23

Maximum Power Flow and Line Loadability

The maximum power flow for lossy transmission lines is derived using ABCD parameters in phasor form. These parameters create a matrix relationship between the sending-end and receiving-end voltages and currents, allowing the determination of the receiving-end current. This relationship facilitates calculating the complex power delivered to the receiving end, from which real and reactive power components are derived.
Pharmacodynamic Models: Overview01:27

Pharmacodynamic Models: Overview

Pharmacodynamic (PD) responses describe the interaction between a drug and its biological target, culminating in a physiological effect. These responses can be classified into different types: continuous variables, such as blood glucose levels; categorical outcomes, like survival rates; and time-to-event metrics, such as disease progression. Understanding and modeling PD responses are critical for optimizing drug efficacy and safety.PD models describe the relationship between drug concentration...
Impact of Pharmacokinetic–Pharmacodynamic Models: Regulatory Decisions01:15

Impact of Pharmacokinetic–Pharmacodynamic Models: Regulatory Decisions

PK–PD modeling has significantly influenced FDA regulatory decisions, particularly drug approval, dosage optimization, and labeling. These models integrate pharmacokinetics (PK) and pharmacodynamics (PD) to predict drug behavior and effects, aiding in optimizing dosing regimens and enhancing the probability of clinical trial success.One notable example is Nesiritide (Natrecor®), a recombinant human brain natriuretic peptide for treating acute decompensated congestive heart failure (CHF).
Lossy Lines and Overvoltages01:22

Lossy Lines and Overvoltages

Transmission-line series resistance and shunt conductance cause three primary effects: attenuation, distortion, and power losses.
Attenuation
When constant series resistance and shunt conductance are present, voltage and current equations are modified. The propagation constant indicates that voltage and current waves consist of both forward and backward traveling components. These waves attenuate as they propagate, with the attenuation factor related to the resistance and conductance. In a...
Lossless Lines01:23

Lossless Lines

In electrical engineering, a lossless transmission line is characterized by a purely imaginary propagation constant and a resistive characteristic impedance. The ABCD parameters, which describe the relationship between the input and output voltages and currents, indicate an equivalent π circuit with an imaginary series impedance and a shunt admittance. This results in a transmission line that, when the product of the phase constant (beta) and the length of the line is less than pi, exhibits...

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Related Experiment Video

Updated: Jun 17, 2026

Automated Deployment of an Internet Protocol Telephony Service on Unmanned Aerial Vehicles Using Network Functions Virtualization
07:49

Automated Deployment of an Internet Protocol Telephony Service on Unmanned Aerial Vehicles Using Network Functions Virtualization

Published on: November 26, 2019

A versatile model for packet loss visibility and its application to packet prioritization.

Ting-Lan Lin1, Sandeep Kanumuri, Yuan Zhi

  • 1Department of Electrical and Computer Engineering, University of California at San Diego, La Jolla, CA 92093-0407, USA. tinglan@ucsd.edu

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|December 24, 2009
PubMed
Summary

This study introduces a video packet loss visibility model applicable to various video structures. It prioritizes packets to maintain visual quality during network congestion, outperforming existing methods.

Related Experiment Videos

Last Updated: Jun 17, 2026

Automated Deployment of an Internet Protocol Telephony Service on Unmanned Aerial Vehicles Using Network Functions Virtualization
07:49

Automated Deployment of an Internet Protocol Telephony Service on Unmanned Aerial Vehicles Using Network Functions Virtualization

Published on: November 26, 2019

Area of Science:

  • Computer Vision
  • Video Streaming
  • Network Engineering

Background:

  • Video packet loss significantly degrades perceived visual quality.
  • Existing packet loss models often lack generalizability across different video structures and encoding standards.
  • Understanding packet loss impact is crucial for effective network management and quality of service.

Purpose of the Study:

  • To propose a generalized linear model for video packet loss visibility.
  • To develop a packet prioritization method based on perceptual quality for video streams.
  • To evaluate the proposed model's effectiveness against existing prioritization techniques.

Main Methods:

  • Developed a generalized linear model using three subjective experiment datasets (H.264, MPEG-2).
  • Incorporated factors like scene cuts, camera motion, and reference distance for packet loss visibility.
  • Applied the visibility model to a packet prioritization strategy for congested networks.
  • Compared the perceptual-quality-based method with Drop-Tail and cumulative-MSE-based methods.

Main Results:

  • Scene cuts, camera motion, and reference distance were identified as significant factors in packet loss visibility.
  • The proposed perceptual-quality-based packet prioritization method yielded higher visual quality compared to existing methods.
  • The model demonstrated applicability across different encoding rates, despite initial development with high-rate videos.

Conclusions:

  • The generalized linear model accurately predicts video packet loss visibility across various structures.
  • Perceptual-quality-based packet prioritization effectively minimizes visual degradation during network congestion.
  • The developed model offers a robust solution for enhancing video streaming quality over unreliable networks.