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Optimization Problems01:26

Optimization Problems

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Optimization problems often involve identifying maximum or minimum values under specific constraints. A well-known example is determining the longest horizontal pipe that can be moved around a right-angled corner, where a 3-meter-wide hallway meets a 2-meter-wide hallway. This scenario, common in architectural design and industrial transport, can be understood conceptually through geometric and trigonometric reasoning.To visualize the problem, consider the pipe as a straight line that touches...
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Metal ions can be separated from one another by complexation with organic ligands–the chelating agent– to form uncharged chelates. Here, the chelating agent must contain hydrophobic groups and behave as a weak acid, losing a proton to bind with the metal. Since most organic ligands used in this process are insoluble or undergo oxidation in the aqueous phase, the chelating agent is initially added to the organic phase and extracted into the aqueous phase. The metal-ligand complex is...
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Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
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Survival Tree01:19

Survival Tree

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Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
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Reducing Line Loss01:18

Reducing Line Loss

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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.
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Related Experiment Videos

Optimizing hyperparameters of YOLOv10 for arson detection using advanced optimization algorithms.

Ali Abbas Abbod1,2, Matheel E Abdulmunim1, Ismail A Mageed3

  • 1Computer Sciences college, University of Technology-Iraq, Baghdad, Iraq.

Plos One
|October 7, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a hybrid Grey Wolf-Brown Bear optimization algorithm to enhance YOLOv10 for real-time arson detection. The novel approach improves detection accuracy and efficiency in critical safety applications.

Related Experiment Videos

Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Machine Learning

Background:

  • Arson detection is vital for public safety in high-risk areas.
  • Deep learning (DL) models like YOLOv10 show promise for real-time object detection.
  • Optimizing DL hyperparameters is crucial for balancing accuracy and computational efficiency.

Purpose of the Study:

  • To propose a hybrid optimization algorithm (GWO-BBOA) for YOLOv10.
  • To enhance YOLOv10's performance for accurate and efficient arson detection.
  • To evaluate the effectiveness of the hybrid algorithm against traditional methods.

Main Methods:

  • Developed a hybrid Grey Wolf Optimization (GWO) and Brown Bear Optimization Algorithm (BBOA).
  • Applied the GWO-BBOA algorithm to optimize hyperparameters of the YOLOv10 model.
  • Evaluated the optimized YOLOv10 model using an augmented dataset of 2,182 annotated images.

Main Results:

  • The GWO-BBOA optimized YOLOv10 achieved a recall of 0.620.
  • The hybrid approach demonstrated superior performance compared to traditional optimization methods.
  • The algorithm effectively balanced exploration and exploitation, reducing iteration count.

Conclusions:

  • Hybrid metaheuristic approaches significantly enhance DL models for safety-critical tasks like arson detection.
  • The GWO-BBOA algorithm offers an effective strategy for optimizing YOLOv10.
  • Future research will focus on dataset expansion and real-time system integration.