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Avascular Necrosis (AVN) || Early Detection, Better Outcomes || ~xRay Pixy

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Avascular Necrosis (AVN) is a condition where blood flow to the bone is reduced, causing bone cells to die. This leads to pain, joint damage, and difficulty in movement, especially in the hip. Early diagnosis and proper treatment can prevent permanent bone damage and improve quality of life. Video Chapter: AVN 00:00 Introduction 00:45 What is AVN? 01:55 About Bone Tissue 02:49 AVN Causes 03:38 AVN Symptoms 04:11 AVN Diagnosis 04:56 AVN of femoral head 05:33 How AVN Develops 07:28 Conclusions #optimization #algorithm #metaheuristic #robotics #deeplearning #ArtificialIntelligence #MachineLearning #computervision #research #projects #thesis #Python #optimizationproblem #optimizationalgorithms 

Horse Herd Optimization Algorithm | Step-By-Step | ~xRay Pixy

Horse Herd Optimization Algorithm


Learn the Horse herd optimization Algorithm (HOA) Step-by-Step. - Nature Inspired Metaheuristic Optimization Algorithm - Inspired by Horse Herd Behavior. - A large number of Controlling Parameters are Used. - Used to Solve Higher Dimensional Optimization Problems in real life.

Video Chapters: Introduction: 00:00 Horse Herd Optimization Algorithm: 00:39 Horse Age Classification: 02:31 Horse Behavior: 04:28 Horse Position Update: 06:21 Horse Velocity Vectors: 08:26 Horse Grazing Vector: 09:28 Horse Hierarchy Vector: 10:38 Horse Sociability Vector: 11:45 Horse Imitation Vector: 12:30 Horse Defense Meachnism: 13:05 Horse Herd Optimization Algorithm Step: 15:06 Horse Velocity Vectors: 15:23 Horse Herd Optimization Algorithm Flowchart: 18:18 Conclusion: 19:00

A horse herd optimization algorithm is introduced in 2021. It is the nature-inspired population-based metaheuristic optimization algorithm that is basically inspired by the horse herding behavior in nature.

Disadvantage: Due to horse different behaviors, a large number of control parameters are used in this algorithm.
Advantage: We can use this algorithm to solve complex high-dimensional optimization problems.

Few Facts About Horses
  • Horse Lifespan: 15-30
  • Vision: 360 Degree
  • Brain Weight: 623 Gram
  • Male Horse Teeth: 40
  • Female Horse Teeth: 36
  • Horse Breeds: More than 300
  • Predators: Lion, Wolf, and other
Horses Behavior: Horses reveal different behavior at different ages. Different horses behavior used in this algorithm include:
  • Grazing (G)
  • Hierarchy (H)
  • Sociability (S)
  • Imitation (I)
  • Roam (R)
  • Defense Mechanism (D)
Horse Age Classification
  1. Delta Horse: Age Range Between 0-5 Years.
  2. Gama Horse: Age Range Between 5-10 Years.
  3. Beta Horse: Age Range Between 10-15 Years.
  4. Alpha Horse: Older than15 years.
Horse Herd Optimization Algorithm Pseudocode:
  1. Initialize important algorithm parameters.
  2. Initialize Population for N horses Randomly.
  3. Calculate the Fitness value for each horse in the current population.
  4. Select the best horse among all.
  5. Determine horse age: Calculate Alpha, Beta, Gama, and Delta Horse.
  6. Calculate horse velocity according to their age.
  7. Update Horse Position in the Search Space.
  8. Calculate fitness values for new solutions.
  9. Compare New Solutions with Older Solutions.
  10. Check stopping criteria.
  11. Display Best Solution Found.














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