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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.
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Air content measurement in concrete is critical for ensuring structural integrity and durability of concrete structures, especially in environments prone to severe weather conditions. Accurate air content analysis optimizes concrete's resistance to freeze-thaw cycles and enhances its workability and strength. Several methods are standardized under ASTM guidelines to measure the air content in fresh concrete, each suitable for different concrete types and conditions.
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The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
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When a substance—isolated from its environment—is subjected to heat changes, corresponding changes in temperature and phase of the substance is observed; this is graphically represented by heating and cooling curves.
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Air entrainment in concrete significantly enhances the material's durability, especially in environments subjected to freeze-thaw cycles. Introducing small air bubbles into the concrete mix acts as internal voids that accommodate the expansion of water when it freezes, thereby alleviating internal stress and preventing structural cracks. This function is crucial in climates with significant freezing and thawing, as it protects the concrete from repeated stresses that could lead to premature...
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Related Experiment Video

Updated: Jul 24, 2025

Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption
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ACBiGRU-DAO: Attention Convolutional Bidirectional Gated Recurrent Unit-based Dynamic Arithmetic Optimization for Air

Vinoth Panneerselvam1, Revathi Thiagarajan2

  • 1Department of Computer Science and Engineering, Mepco Schlenk Engineering College, Sivakasi, India. vinoth.ttk@gmail.com.

Environmental Science and Pollution Research International
|July 6, 2023
PubMed
Summary

This study introduces a new air quality prediction model, the Attention Convolutional Bidirectional Gated Recurrent Unit based Dynamic Arithmetic Optimization (ACBiGRU-DAO), achieving 95.34% accuracy. The model effectively predicts air quality and classifies pollution levels for better environmental and health management.

Keywords:
AccuracyAir QualityAttention Convolutional Bidirectional Gated Recurrent UnitDynamic Arithmetic Optimization AlgorithmPrediction

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Area of Science:

  • Environmental Science
  • Computer Science
  • Data Science

Background:

  • Air pollution is a significant environmental and health concern, especially in developing nations.
  • Accurate air quality assessment is crucial for urban and industrial monitoring.
  • Existing prediction models require enhancement for improved accuracy.

Purpose of the Study:

  • To propose a novel air quality prediction model, ACBiGRU-DAO.
  • To enhance prediction accuracy using Attention Convolutional Bidirectional Gated Recurrent Unit (ACBiGRU) and Dynamic Arithmetic Optimization (DAO).
  • To classify air quality into six severity stages.

Main Methods:

  • Utilized Indian air quality data including AQI, PM2.5, PM10, CO, NO2, SO2, and O3.
  • Preprocessed data through missing value imputation and data transformation.
  • Developed and optimized the ACBiGRU-DAO model for prediction and classification.

Main Results:

  • The ACBiGRU-DAO approach achieved an accuracy of 95.34%.
  • Demonstrated superior performance compared to other evaluated methods.
  • Successfully predicted air quality and classified it into six AQI stages.

Conclusions:

  • The proposed ACBiGRU-DAO model offers a highly accurate solution for air quality prediction.
  • This approach can aid in monitoring and mitigating air pollution impacts.
  • Effective air quality prediction is vital for public health and environmental protection.