📣 A fast reverse proxy written in PHP that helps to expose local services to the internet

Where ideas & concepts are born & incubated

A modern static build tool, powered by webpack

Get The Most Out Of Your CGM Transmitter

Complete Matlab pipeline for large scale calcium imaging data analysis

Fake HTTP log generator module, test if your monitor system can survive under the log spikes.

✌️ Curated entry-level jobs in the UK tech industry

Automatically Builds a Linux Distribution for FireSim/FireChip Nodes, works with FireSim's automatic workload generation.

🦀🦀🦀 Sort spikes from extra-cellular recordings using neural networks. Fully automated.

A generalizable model of spike-timing dependent plasticity for the Neural Simulation Tool (NEST).

wordpress plugin for spike

💧|> λ |> 💌 A step-by-step example/tutorial showing how to invoke AWS Lambda functions from Elixir/Phoenix Apps.

A small loader for the Stern DLLs which are part of FarSights Pinball Arcade games

Snipcart Integration with Webpack Powered Spike

[ABANDONED] The client of https://spike.cc REST api for PHP.

Spiking neural networks are biologically plausible CNNs which learn through a temporally dependent learning method known as Spike Time Dependant Plasticity (STDP)- an alternate to gradient descent. This repository contains layers built on top of Lasagne layers for spiking neural networks. This is the first implementation of spiking neural networks in any tensor based framework to the best of my knowledge. The various layers can be found in snn.py for dense layer and snn_conv.py for other layers. These layers are to be processed for each time step which is done using the Theano scan as a quick hack - in the snn class. The results can be found the ppt. Further details on how to use the code will be put up after later.

A relaxing spa day for your VPinMAME.. actually just a VPinMAME fork with support for Stern Pinball Arcade (SPA) emulation-DLLs.

LEGO Mindstorms

This is a project based on the complete genome analysis of the COVID-19 (Sars-cov2) virus, taken from the Wuhan-Hu-1 isolate sample. I cleaned the genome sample to obtain an RNA sequence and I verified the number of base-pairs in the virus. Using the concept of Kolmogorov complexity, I was able to find the lower bound size of a compressed version of the COVID-19 virus. I was able to compress it into an 8.412 kb file using the "LZMA" algorithm. Then I converted the RNA sequence into a DNA string for applying the concepts of "Codons". This helped me to find the essential 20 different types of proteins that can be used to express the genome into the Protein sequence. Further, I made a decoder to make the genome into the Reading-Frame sequence. With the help of this reading frame sequence, I was able to extract the polypeptides and long-chain polypeptides in the virus. Then, I analyzed the Open Reading Frame(ORF) for the Sars-Cov-2 virus which has 10 different proteins that are responsible for the synthesis and catalytic process of COVID-19 in a human body. At last, I was able to verify the length of all the 10 proteins(ORF1a, ORF1b, Spike Glycoprotein, Membrane, ORF6, ORF7a, ORF8, ORF10) thus this project has the proof of all the scientific foundlings using Data science concepts.

Spike Neural Network in Prolog (and Arduino)

Pipeline examples for drone.io

Step-by-Step Brian Simulation

Spike template with bootstrap 4 scss and js

A fully automated spike timer.

Just a tree to start learning Symfony with Docker

Spike-starter is a tool that helps me on my experimentation workflow.

A Matlab toolbox for creating and manipulating spike trains, and for stimulating neuromorphic hardware.