Research project that focuses on observing the Resilience of Delhi Road Networks to Traffic Disruptions
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Updated
Jun 18, 2024 - Jupyter Notebook
Research project that focuses on observing the Resilience of Delhi Road Networks to Traffic Disruptions
This repository provides MATLAB implementations of plfit and plpva functions for fitting power-law distributions to empirical data using maximum likelihood estimation (MLE) and statistical goodness-of-fit tests. These tools accurately model complex systems with significant tail behaviors, common in fields like physics, biology, and economics.
限られた粒径のマイクロプラスチックの実測データに当てはめたべき分布のスケールパラメタ等から、未計測の粒径範囲を含むマイクロプラスチック濃度を推定するための補正係数の計算方法
This lab focuses on image transformation techniques in OpenCV with Python. Tasks include creating mirror images using both Affine and Projective transformations, applying a Log Transformer for contrast adjustment, and implementing a Power-Law Transformer for gamma correction.
Create an array containing pseudorandom numbers drawn from a Pareto (Type I) distribution.
Create an iterator for generating pseudorandom numbers drawn from a Pareto (Type I) distribution.
Create a readable stream for generating pseudorandom numbers drawn from a Pareto (Type I) distribution.
Pareto (Type I) distributed pseudorandom numbers.
Pareto distribution (Type I) probability density function (PDF).
Natural logarithm of the probability density function (PDF) for a Pareto (Type I) distribution.
Library for rain estimation and detection built with PyTorch. This library provides an implementation of algorithms for extracting rain-rate using data from commercial microwave links (CMLs). Addinaly this project provide an example dataset with data from two CMLs and implementation of performance and robustness metrics
This repository contains projects related to various aspects of image processing, from basic operations to advanced techniques like active contours. Examples and case studies focus on applications in medical imaging.
Fits a discharge rating curve based on the power-law and the generalized power-law from data on paired water elevation and discharge measurements in a given river using a Bayesian hierarchical model as described in Hrafnkelsson et al. (2022)
South-California earthquakes data analysis.
The project for the course "Web Information Retrieval"
Modified gap statistic (gap-com) for regularization selection of sparse networks. This method is aimed for complex network estimation.
Implementation of Power Law Graph Transformer for Machine Translation and Representation Learning.
This the code of my bachelor thesis with the CG2 lab in the university of Crete.
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