Elijah elijahc

apt hostadp does not support edimax ew-7811un

This build allows support for it

$ mkdir ~/src
$ cd ~/src
$ wget https://github.com/jenssegers/RTL8188-hostapd/archive/v1.1.tar.gz
$ tar -zxvf v1.1.tar.gz
$ cd RTL8188-hostapd-1.1/hostapd

Install hostapd and lighttpd (high performance hosting)

$ sudo apt-get install hostapd lighttpd

Edit interfaces to load your wlan interface on boot

# Add the following (and consider making a backup of interfaces):
allow-hotplug wlan1

Hardcode IP address into the boot sequence on the SD card (cmdline.txt)

dwc_otg.lpm_enable=0 console=ttyAMA0,115200 kgdboc=ttyAMA0,115200 console=tty1 elevator=deadline root=/dev/mmcblk0p2 rootfstype=ext4 rootwait ip=169.254.113.200

Try pinging the raspi

$ ping 169.254.113.200

In walking through the math to derive the equation they use in their code to maintain/model the X(t) neuron state vector I realized I was not using an appropriate time step size. After correcting the step size the model appears to make better predictions as quantified by mean Pearson Correlation Coefficient

N = 1000

214 Cells in Experiment 500964514

Using 50 cell ids: [ 7 11 26 28 40 41 45 47 49 50 54 63 68 69 70 76 77 82

##VGG19 model for Keras

This is the Keras model of the 19-layer network used by the VGG team in the ILSVRC-2014 competition.

It has been obtained by directly converting the Caffe model provived by the authors.

Details about the network architecture can be found in the following arXiv paper:

Very Deep Convolutional Networks for Large-Scale Image Recognition

K. Simonyan, A. Zisserman

Startup

$ cd /home/webapps2/vertex
$ unicorn_rails -c config/unicorn.rb
$ bundle exec sidekiq
$ sudo service nginx restart

# Redis should always be running, but in case its not and you have the permissions, I believe this is how you would start it.

$ sudo service redis start

	Download cuda-8.run file
	Download Nvidia-367.18-driver.run file

	Remove old drivers (apt remove --purge nvidia*)
	Remove old nvidia.deb packages (just in case that's necessary?)
	Remove my cuda folders (/usr/local/cuda*) (again, just in case)

	reboot
	Graphics probably won't work now (they didn't for me), so use tty (ctrl-alt-1) or ssh (might want to set that up before doing all this)
	(I might have run the Nvidia-367.18.run file here, followed with a reboot, but I can't remember)

	import json

	...

	# Parse arguments
	parser = argparse.ArgumentParser(description='RNN for modeling neuron populations')
	...
	FLAGS = parser.parse_args()
	return FLAGS

	#!/usr/bin/env python
	import json
	import urllib2
	import os
	import sys
	import pexpect
	import time

	usr,pts = str(sys.argv[1]).split('.')