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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...
107
Design Example: Analyzing Capacity Contours for Flood Risk Assessment01:17

Design Example: Analyzing Capacity Contours for Flood Risk Assessment

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Flood risk assessment involves careful planning and analysis to ensure the safety of communities near water retention structures. Capacity contours are a vital tool in this process, as they illustrate the potential spread of water at specific levels in a given area. In the context of building a bund across a small valley, these contours play a critical role in evaluating the safety of nearby residential areas.In this example, the bund is intended to store stormwater in the valley. The engineers...
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Estimation of the Physical Quantities01:05

Estimation of the Physical Quantities

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On many occasions, physicists, other scientists, and engineers need to make estimates of a particular quantity. These are sometimes referred to as guesstimates, order-of-magnitude approximations, back-of-the-envelope calculations, or Fermi calculations. The physicist Enrico Fermi was famous for his ability to estimate various kinds of data with surprising precision. Estimating does not mean guessing a number or a formula at random. Instead, estimation means using prior experience and sound...
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Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

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Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
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Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

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Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...
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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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Related Experiment Video

Updated: Aug 10, 2025

Evaluation of an Exclusive Spur Dike U-Turn Design with Radar-Collected Data and Simulation
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QCNN_BaOpt: Multi-Dimensional Data-Based Traffic-Volume Prediction in Cyber-Physical Systems.

Ramesh Sneka Nandhini1, Ramanathan Lakshmanan1

  • 1School of Computer Science and Engineering, Vellore Institute of Technology, Vellore 632014, India.

Sensors (Basel, Switzerland)
|February 11, 2023
PubMed
Summary

This study introduces a new cyber-physical system model for accurate traffic volume prediction, utilizing a quantum convolutional neural network and Bayesian optimization (QCNN_BaOpt). The advanced model achieved 99.3% accuracy in predicting traffic patterns.

Keywords:
Bayesian optimization hyper tuningcyber–physical system (CPS)quantum convolutional neural network (QCNN)traffic volume prediction

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Area of Science:

  • Cyber-physical Systems
  • Artificial Intelligence
  • Traffic Engineering

Background:

  • Urban traffic congestion is a growing problem due to economic and industrial expansion.
  • Existing computational models for traffic prediction have limitations in accuracy and scope.
  • Effective traffic guidance and control are crucial for urban mobility.

Purpose of the Study:

  • To develop an effective multi-dimensional dataset-based model for accurate traffic volume prediction.
  • To integrate quantum convolutional neural network and Bayesian optimization (QCNN_BaOpt) for enhanced predictive capabilities.
  • To evaluate the proposed model's performance against state-of-the-art methods.

Main Methods:

  • Development of a novel cyber-physical system model incorporating a quantum convolutional neural network.
  • Application of Bayesian optimization for optimal tuning of model hyperparameters.
  • Evaluation using a large-scale US accident dataset with 1.5 million records and 47 attributes.

Main Results:

  • The proposed QCNN_BaOpt model demonstrated high accuracy in traffic volume prediction.
  • The model achieved a remarkable accuracy of 99.3% in performance evaluations.
  • Comparative analysis confirmed the superiority of the proposed model over existing state-of-the-art approaches.

Conclusions:

  • The developed QCNN_BaOpt model offers a significant advancement in traffic volume prediction accuracy.
  • This cyber-physical system approach provides a robust solution for urban traffic management.
  • The model's high accuracy and validated superiority suggest its potential for real-world traffic guidance and control systems.