Artificial Intelligence

Falls are a major health problem with one in three people over the age of 65 falling each year, oftentimes causing hip fractures, disability, reduced mobility, hospitalization and death. A major limitation in fall detection algorithm development is an absence of real-world falls data. Fall detection algorithms are typically trained on simulated fall data that contain a well-balanced number of examples of falls and activities of daily living. However, real-world falls occur infrequently, making them difficult to capture and causing severe data imbalance.
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This dataset is in support of my following Research papers
Preprint (Make sure you have read Caution) :
- Novel ß Transtibial Prosthetic 9-DoF Artificial Leg Adaptive Controller - Part I*
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There is related page 'Data:B-Bio Models-1' but this open-access page especially for 'Female' ß-Bio models of Self-Claimed advancements, Research papers and computer models proposed by me.. All content can be freely downloaded. Models shared only for humanitarian purposes, Can be used by Clinical Doctors or Pharmacologists or Researchers under License CC-BY. Preprints can be freely downloaded, pls.
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This is an open-access page. All content can be freely downloaded. Models shared only for humanitarian purposes, Can be used by Clinical Doctors or Pharmacologists or Researchers under License CC-BY. Preprints can be freely downloaded, pls. click on title.
I. Paper 1 : Investigating Myocardial Infarction using Novel ß-Bio Model of Circulatory System
II. Paper 2 : Investigating Myocardial Infarction using Novel ß Bio-Electro-Magnetic Radiations Model
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This dataset is in support of my research paper 'Comparative Non-Linear Flux Matrices & Thermal Losses in BLDC with Different Pole Pairs' .
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Dataset for the meta-heuristics scheduling algorithm
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A medium-scale synthetic 4D Light Field video dataset for depth (disparity) estimation. From the open-source movie Sintel. The dataset consists of 24 synthetic 4D LFVs with 1,204x436 pixels, 9x9 views, and 20–50 frames, and has ground-truth disparity values, so that can be used for training deep learning-based methods. Each scene was rendered with a clean pass after modifying the production file of Sintel with reference to the MPI Sintel dataset.
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