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Djalma Chagas Bina's Projects

text_summarization-mmr_and_lexrank icon text_summarization-mmr_and_lexrank

Demonstration of automated summary construction with a) Maximal Marginal Relevance (MMR) as the baseline approach with an aim to reduce redundancy while maintaining query relevance in re-ranking retrieved documents and b) the introduction of sentence salience to identify most important sentences in documents with degree-based approach called LexRank to compute centrality using the similarity graphs.

textrank-keyword-extraction icon textrank-keyword-extraction

Keyword extraction using TextRank algorithm after pre-processing the text with lemmatization, filtering unwanted parts-of-speech and other techniques.

themes icon themes

Free WordPress themes made by Automattic for WordPress.org and WordPress.com.

toy-ml-pipeline icon toy-ml-pipeline

Toy example of an applied ML pipeline for me to experiment with MLOps tools.

tpot icon tpot

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

transmission_risk icon transmission_risk

Currently, there are 26.2 million COVID-19 cases in the US due to people taking lower precautions to reduce transmission at public venues. This project aims to create a tool that provides individuals with information to make a responsible decision about visiting an establishment to prevent unnecessary SARS-CoV-2 cases. A probabilistic model that predicts the risk of an individual contracting COVID-19 (transmission risk) during a visit to an establishment was created. This model was integrated into a web app built using the StreamLit framework in Python3.8. It acquired data through parsing COVID-19 databases and obtaining venue-specific data through user-inputs. The transmission risk model worked by multiplying the likelihood an individual will encounter a virus carrier (exposure risk) and the risk the individual will contract the virus if one carrier is present (contract risk). The exposure risk model was tested through the Spearman’s Rank Correlation by calculating the correlation between the model’s risk prediction for 200 random counties to new cases two weeks later of the aforementioned counties. Contract risk was tested using four different scenarios. Transmission risk was tested using these four scenarios factoring three counties with ranging incidence rates. The exposure risk model averaged a Spearman Rank correlation of 0.81, placing it in the “very strong” category. The contract and transmission risk provided sensible predictions for the scenarios provided. This model can be easily expanded to other databases and adapted to high-incidence countries. Since virus-specific aspects can apply to other illnesses, the model can be adjusted easily for other viruses.

uac-bypass icon uac-bypass

Small utility written in c++ to bypass Windows UAC prompt.

uniform-cost-search-algorithm icon uniform-cost-search-algorithm

Evolves in amplitude algorithms. The uniform cost search algorithm expands each time the node n with the lowest current path consumption g (n).

vanet icon vanet

Veins simulations of ad hoc vehicular networks.

vsgexamples icon vsgexamples

Example programs that test and illustrate how to use the VSG and optional add-on libraries

weatherapp icon weatherapp

NodeJS Weather App that takes in address and returns postal address + current temperature + apparent temperature

webassembly-example icon webassembly-example

WebAssembly (abbreviated Wasm) is a binary instruction format for a stack-based virtual machine.

webrtc icon webrtc

This is a clone of an SVN repository at http://webrtc.googlecode.com/svn/trunk. It had been cloned by http://svn2github.com/ , but the service was since closed. Please read a closing note on my blog post: http://piotr.gabryjeluk.pl/blog:closing-svn2github . If you want to continue synchronizing this repo, look at https://github.com/gabrys/svn2github

webrtc-builds icon webrtc-builds

Automated WebRTC build scripts for Linux, Windows, Mac, Android and iOS.

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