intervention

PHP Image Manipulation

WordPress plugin to configure wp-admin and application state using a single config file.

Generate avatars with initials from user names.

🌄 📐 A Laravel Nova advanced image field with cropping and resizing using Cropper.js and Intervention Image

Upload image using Laravel's build in function and resize it automatically.

Explainability of Deep Learning Models

Causal Inference with Invariant Prediction

On-demand image manipulation for WordPress via the Intervention Library.

VIPS driver for Intervention Image.

Wrapper for PHP's GD Library for easy image manipulation. Support for scaling multi-line text, shapes, filters and smart resize.

An annotated corpus of discussion forum threads from Massive Open Online Courses.

Create colored avatars with letters in PHP

Laravel Framework Important Files

Projet EMS RP est un projet open-source dont l’objectif est d’être utilisé comme aide médicale pour tous les types de rôle-play contenant des interventions d’urgence.

iReporter app enables users (citizen) to bring any form of corruption to the notice of appropriate authorities and the general public

Tu Ayuda en Tiempos de Crisis

A brief analysis on the performance of the aviation industry through indicators of cancellation rate, on-time rate, and average delay minutes, fitted by and to forecast with reasonable ARIMA models.

Reports stuff that has happened on a particular day, based on the logs.

Image Uploading via laravel 5.7 framework with help of intervention and dropzonejs

Create image with multiple sizes easily.

In this simulation, the intensity of the intervention is periodically varied over a period of time. Consider a case in which the government intervention issues a restraint or ban on going out and contact of people changes.

What is the causal impact of an intervention?

Describing and visualising baseline results of the Let's Move It intervention

Student database made with Laravel

Save images as static in real-time in different formats using Intervention Image.

Predicting outcomes of educational interventions before investing in large-scale implementation efforts in school settings is essential for educational policy-making. However, due to time and resource limitations, conducting longitudinal, large-scale experiments testing outcomes of interventions in authentic settings is difficult. Here, we introduce the deep learning method as a way to address this issue and illustrate the use of the deep learning method for the prediction of intervention outcomes through a MATLAB implementation. The presented deep learning method extracts predictable patterns from an empirical dataset to simulate large-scale intervention outcomes. Findings from our simulations suggest that the deep learning applied simulation model can predict intervention outcomes significantly more accurately compared to the traditional regression analysis methods.