Baby Don't Hertz Me

Ongoing Linux Cheatsheet

2020-01-03T11:38:00.001-04:00

Reference For Me, Reference For You?

I often find myself using certain commands on semi-regular basis. Not regular enough to remember but enough to know what I am looking for. This is my list of snippets that others might find useful. I will do my best to update this from time to time.

On a side note, I primarily use Ubuntu 18.04 (20.04 upgrade will likely happen when it comes out). I occasionally use distros other than Ubuntu but they are typically Debian based.

Variables that you want to alter will be denoted as $VAR_NAME.

Photo by Kevin Horvat on Unsplash

Connecting To Wifi Using CLI

- This uses the command line version of NetworkManager (nmcli)
- Obviously you need to know your network name and password
- Determine your network interface with 'nmcli device status'. Four columns will be displayed. Find wifi in the Type column and then the associated Device name is the interface name.

Commands:

nmcli d wifi connect $NAME password $PASSWORD iface $INTERFACE

Create Network Name Space And Move Device Into It

- Move a device into a network interface and get an IP lease.
- Network namespaces can be used to group or sandbox network devices. Docker containers use network namespaces for isolation.
- Once devices are in network namespaces you can access them using
ip netns exec $NET_NS $COMMAND

Commands:

# create network namespace
sudo ip netns add $NET_NS

# move move network interface into created ns
sudo ip link set dev $INTERFACE

# bring interface up
sudo ip netns exec $NET_NS ip link set dev $INTERFACE up

# get IP lease
sudo ip netns exec $NET_NS dhclient $INTERFACE

Get Docker Container ID and PID

- For some networking black magic there is a need to know container information. I normally use this in a script so I will be storing the results as bash variables.
- container_name is the plain, user assigned name of the container, maybe db_server or python_box, etc

Commands:

container_id=$(docker ps -aqf "name=container_name")
container_pid = $(docker inspect --format '{{ .State.Pid }}' "container_name")

Install Build Dependencies for a Package

Sometimes chasing down all the packages and the correct versions of said packages is REALLY TEDIOUS.

Commands:

sudo apt-get build-dep $PACKAGE_NAME

Linux and SSH for Noobs

2018-07-19T12:09:00.003-03:00

Since starting grad school I have gained a whole new appreciation for linux. Ubuntu has been my primary OS since 8.04 (Hardy Heron) but I hadn't really looked much at how to really streamline and optimize my workflow until this year.

At my university, all Windows computers run an antivirus program that kills performance. It runs ruthlessly and suck up a lot of computer resources. This has only reinforced my choice to use linux as the IT guys will not provide any support and will not install anything on your computer, thus allowing complete freedom. Not all workplaces may allow for this but it does make things much easier if they do.

What is SSH?

SSH is a cryptographic network protocol that allows for secure network operations over a non-secured network. What this means is that users have the ability to securely login to remote systems on almost any network.

Why should I use it?

I have known about SSH for years but never used it extensively. It has only been this year that I started using it on a daily basis. My supervisor has a computer hidden in another building on campus that we use for backing up our software repositories (I also use GitLab for an extra layer of safety) and the easiest way to access it is with SSH. SSH allows for easy control over remote computers. I can simply login, backup my files, logout and then go on with my day.

My other main excuse for using SSH is that some FPGA software that I need to use (Xilinx's Vivado) is not compatible with my version of linux. With some tweaking I might be able to get it working, but I took the alternative choice and simply installed a compatible version of linux (CentOS 7) on one of the many lab computers not in my office. Now I am able to use SSH and X11 forwarding to control the GUI of Vivado from my main machine while all the heavy lifting is done on another computer. Distributed workloads is another wonderful feature that can be easily implemented in linux using SSH.

SSH Basics

There are a lot of SSH commands but the basics are as follows:

Remote Terminal

This will allow you to login to a remote computer via a terminal.

ssh user@[IP address or computer name]

example:
ssh alex@test.comp.ca
ssh alex@192.168.0.105

Remote Terminal with Local GUIs

This will allow you to login to a remote computer via terminal and display GUIs from the other computer on your current machine. The '-X' will enable X11 forwarding. If that is not enabled on the host machine then no GUI will be displayed on your current machine.

ssh -X user@[IP address or computer name]

example:
ssh -X alex@test.comp.ca
ssh -X alex@192.168.0.105

Transferring Files To/From Remote Machine

This command will allow you to quickly transfer files from your computer to another via ssh. The source and destination must be formatted as follows: [IP address or computer name]:/path/to/file. Remove the square brackets when plugging in the information and it should work.

scp [source] [destination]

example:
scp /local/path/to/file.png alex@some.comp.uter.ca:/home/alex/Pictures/

SSH Keys

SSH keys are a fantastic way to make remote logins even easier than they already are. Instead of having to type in a password every single time you login or use an SSH command you can simply issue the command and be logged in automatically.

Generating Keys

This can be done by using ssh-keygen. This can be quickly done using the following:

ssh-keygen

This will then ask where the key should be saved, the password for the key (not using a password is less secure but more convenient). There are also a variety of other modifying commands that can be used but ssh-keygen will get the trick done for most users. The default command should be sufficient for most users.

Using Keys

In order to use the keys you need to copy your public key from the server (or computer you are looking to connect to via SSH) and store it on the computer you want to connect to.

This can be done using scp outlined above but...

DO NOT SHARE THE PRIVATE KEY!

There are many ways that the files can be shared but it is likely the safest to use scp (uses SSH to transfer the public key) or ssh-copy-id. When using scp you have to do some additional configuration so if possible use ssh-copy-id.

example:

ssh-copy-id -i ~/.ssh/key_you_want_to_use user@host

Some distros will need additional changes to settings to allow for passwordless login (CentOS 7 needed me to do this). A quick google search will give you the details on what to do for your distro.

Any feedback? Leave it down below!

Linux and Multimedia Creation

2018-07-02T19:29:00.000-03:00

Audio

Some of the earliest uses I found for my personal computers was recording audio. Though these recordings were generally low quality, in both content and equipment, I did get the "recording bug". For the first era of my creativity, I was stuck using the family computer. In order to record, I would have to lug my synthesizer over to the family computer or the family computer to my upright piano before I could begin. This made it tedious for not only myself, but my four older sisters as the family computer would then be locked down by yours truly for hours on end.

Shortly after this, my father agreed to let me have the old family computer, an old Pentium III that we installed Ubuntu 8.04 on. I remember the first recording tool I used was Rosegarden. It hasn't changed much even after 10 years but as always is a polished piece of software.

After a few equipment changes I had a beastly computer and a full digital workstation (Roland RD-700GX and various peripherals). All I needed to find was software that would allow me to work effectively and allow me to use as many of the features on my keyboard as possible. This led me to running through a large number of recording tools in quick succession.

Rosegarden

I haven't used RG in years but it still sticks in my mind as one of my favorite pieces of software for recording audio and MIDI. Over time I found myself moving from mixed type recordings (MIDI and audio that I created) to MIDI with and samples only. It has any feature that you might want for recording and is worth checking out if you are trying to get into things.

Audacity

There was a point early in my recording career (pfft, career!) where I was doing exclusively audio. In my defense I was probably 12 and had no idea how any of the software worked. I just knew that the red circle was record and the triangle was play. Audacity remains to this day my favorite audio editor. It is really simple to use and has a minimalist GUI so that new users don't feel like they are drowning in options. Audacity combined with a variety of audio effects gives you a full audio recording studio without too much complexity that can also be used for small jobs like cleaning up an audio sample to be used in another program.

A must have for any audiophile.

Ardour

I am listing Ardour not because I extensively used it but because it is a fantastic tool that I could never get myself to love. It has similar abilities to Apple's Logic Pro but is available for free if you install it through the Ubuntu Software Center or from some repositories. There is also the option to build it from the git repository but that won't be outlined here. There is also the choice to pay for the software but that is less than ideal when there is so much good software out there for free.

Ardour cleanly combines audio and MIDI in a fully-featured DAW (digital audio workstation). Out of the listed tools it is by far the most advanced. If easy access to low level control is your thing, this is likely the tool for you.

LMMS

This is one of my favorite recording tools that I have ever used. Many times I find myself trying out other DAWs only to come back to LMMS with renewed vigor. The workflow in LMMS is exactly the way that I like it. The presets for all of the synthesizers are great, if you can't find what you are looking for you can generally find a soundfont that will meet your needs.

A newer feature is the addition of VST plugins. They are pretty buggy and can cause the system to crash from time to time but if it is supported it should work just fine. That being said I still prefer SF (soundfonts). The best ones I have found so far are all on this site. I can't attest to them being bug free but they always sound great. The best saxophone sound I have ever found is in the Nice Keys Suite V1. Finally a SF sax that doesn't sound like synth.

Great tool, similar to FruityLoops except free. You won't regret this choice.

Images & Video

In the realm of photography and film I am definitely an amateur but that doesn't stop me from occasionally trying my hand at it. My main reason for filming and photography is for me to create content for my judo club. This takes the form of highlight reels for the most part but team photos also happen on a regular basis when at tournaments.

Since I am an avid linux user, obviously most of my video/image processing is done in linux. Here are the few tools that I have managed to use over the years that are relatively easy to find, easy to use, and most of all free.

Gimp

Why pay for PhotoShop when there is a really good replacement? By no means does it have as many features as PS but for most people it is more than enough. If you aren't familiar with image editing you may feel a little lost but this is at least one of the more simple to use tools so keep at it!

Pitivi / Kdenlive
I haven't used Pitivi in several years but it seems to have come a long way. Kdenlive and Pitivi are almost the exact same thing. A multi-tracked video editor is a multi-tracked video editor. They don't really vary that much from tool to tool.

I find these tools have a good workflow and intuitive GUI but in the end they are both pretty generic and are good for getting the job done when it comes to video creation.

Publishing Platforms

Take these suggestions with a grain of salt. By no means am I a popular musician or videographer, I have roughly 40k listens to my music and probably 10k views on my videos. This being said any input on better sites to publish content on is definitely appreciated so leave a comment down below!

YouTube

This is your generic publishing platform. YouTube is commonly used and popular. The main issue is that for music you will have to generate some form of visual display which can be tricky depending on what you have for available media content.

Jamendo

If you are not looking to make money off your music, Jamendo is a really great way to share. You won't get a ton of hits unless the song gets really popular but it is still worth checking out.

SoundCloud

I have mixed feelings about publishing on SoundCloud. It seems to have become a lot of mediocre trap and mumble-rap over the years so anything but those don't perform too well. I realize that is a blanket statement and that people may feel differently but that is my personal experience with the platform.

That's a wrap!

Any good linux tools that you absolutely love? Comment down below and I will check them out and add them here as I work my way through the list!

I am also thinking about doing a video AMA soon. Shoot me a message or comment below and I will address questions and topics soon!

Hindsight 20/20: University Productivity Tips and Tricks

2018-06-13T09:15:00.001-03:00

This May I started my Master's in Electrical Engineering. My supervisor is very supportive of me reading anything that might be related to my research but also things that interest me. One of my favorite things is his insistence that I read at least one paper a day. I generally end up reading more than one most days as well as reading chapters from numerous textbooks.

I enjoyed most of my undergraduate degree but found that the purpose of it was to follow a curriculum. My experience with grad school so far has been nothing but self-guided learning. In the Fall and Winter semesters I am taking some courses that are required for my studies but for the most part my learning will be managed by myself and guided by my supervisor. Due to a number of professors in department getting to take their sabbaticals in consecutive years, I will miss out on taking a few courses that I really wanted to take but my supervisor has given me access to all the course notes so I can teach myself.

Some of you may find it rather preachy to be a brand new grad student and be already giving suggestions but I have talked to a lot of grad students and personally use these tools myself. Here are some software tools that I find really help boost my productivity.

Zotero

Managing your reading sucks. Keeping notes on all the things you have read that might be relevant and being able to easily find your notes for each article is extremely tedious. I had several grad students suggest this tool to me for bibliography management and am very appreciative now that I use it.

Zotero is a bibliography management tool for Windows/Mac/Linux which then has plugins for a large number of browsers. Why Zotero is so powerful is it will synchronize your documents between installations with all the reference material. Yes, I suppose manually setting up a Google Drive folder and having a good naming scheme would work BUT that does require some manual work. With Zotero I can simply go to a journal article (IEEE or other journal), click my magically browser button, and magically my article and reference information have been imported into Zotero where I can add notes, tags or anything else I might want.

Toggl

Time tracking is something I thought was incredibly stupid until I started doing it. Who would track time without actually being clocked for work purposes? For my senior design project for my undergrad one of my group mates really insisted that we track our time for two reasons. One reason was to see where our time was being spent and the other was to ensure that we are using our time efficiently and the workload was evenly balanced.

My main use of Toggl is the same as it was before except now all the work is being done by me. I only track time that I feel I am being productive. If I am talking to another student or something else, I stop tracking, if I end up browsing the internet instead of working, I stop tracking, etc. This allows me to see how much 'productive' work time I have and try and plan my work time accordingly. Right now I am shooting for 5-7 productive hours of work a day, be it sitting at home on my couch or huddled behind my desk at work.

I ended up using Toggl at the suggestion of a professor who uses it as a time tracker for a company he is a co-owner of. The interface is intuitive and rather simple so you can simply track and get back to work without much hassle.

Git

If you have to do any coding projects that involve a large number of revisions and sharing of code between group members, you NEED to use some sort of version control tool. I am really mad that they didn't teach anybody how to Git in my undergrad (ECE profs probably didn't think it was relevant enough) because it is now a tool that I use daily. I have done or am working on four large software based projects. A control system for an antenna testing device, a home heating control system, a micro-satellite prototype, and now simulations for graduate school.

Being able to track, modify, undo, and share your changes is an incredibly powerful tool. Git is really easy to use in either terminal or the Windows desktop tool so not using Git for a complexity issue is not a valid excuse. There is lots of support online and if you have any question, feel free to reach out to me!

Spotify

Having something to put on for some background noise is pretty awesome. This is the first paid service I have bothered to get for streaming. I got in on a promo for $0.99 for 3 months and it has been great so far. After the promo is up it is half price if you are a student. Not a whole lot of money for a whole lot of music. It really helps me get through the day.

Python

Taking time to do repetitive tasks sucks. Taking time to manually process data also sucks. Why not use a free tool (programming language) that will let you do just about anything you want.

Even though my university has every MATLAB toolbox under the sun and licenses for all students I still found myself needing things that MATLAB lacks or is just overkill for. My supervisor has a shared directory for me to access all the simulation files he creates. I found myself having to go and tediously download each and every file when changes were made. Doing this multiple times a day was annoying and definitely ruined my groove (if I was in one). My solution was a script that automatically went and pulled all the files and stored them in my simulations folder.

Python may not be a perfect solution to everything you need but it is a nice scripting/programming language that it never hurts to be good at. I talk about setting it up in more detail here.

Data is Beautiful

2018-05-26T16:47:00.000-03:00

Despite all the woes around internet accessibility and net neutrality occurring in the USA in recent times, the internet remains a modern marvel. Sure, there is always the risk of your data being sold (if it isn't already) but in exchange you gain access to the majority of humankind's knowledge. All of our joy, sorrow, science and math.

The internet is an endless supply of data and learning. It isn't all about making pretty graphs like you might find on /r/dataisbeautiful but amazing stuff can be done regardless. The massive amounts of data accessible on the internet will allow for the identification of the driving forces of certain actions. As can be seen below, Bitcoin prices correlate very nicely with Google searches relating to it.

From /r/dataisbeautiful and /u/DeanLa

As my second last semester in university wraps up I realize the true power of data. In a course I took about pattern recognition and machine learning we got to see first hand what can happen with a valuable dataset, a computer, and a group of determined students. Students were paired off and told to propose and complete a project of their choosing. My partner and I decided to test the performance of traditional classifiers against neural networks for both accuracy and speed when applied to object detection and tracking. This project is discussed in more detail here. The results were actually surprisingly good as we would be able to run either system on a video stream at around 10 frames per second which surprised us both.

Seeing the projects that came out of the course was absolutely amazing. The number of interesting data sets that students were able to either generate (we made our own) or find online was amazing. Many were pulled from Kaggle, a site where a massive number of data sets is hosted, but others were taken from machine learning competitions to see if they could out-do the winners.

One group was looking at flight delays based on which airport you were coming or going to, another was looking at diagnosing certain types of cancer, some looked at hand writing for a variety of applications as well. All around there was a lot of really cool projects and a lot of potential for future development.

Go spend a few hours scrolling through Kaggle's existing analysis or /r/dataisbeautiful. You certainly won't regret it and you might even learn something!

Baremetal Drivers: RFM69HCW and FRDM-K22F

2018-03-17T11:40:00.003-03:00

Writing register level code is something I have always viewed as both a blessing and a curse. The blessing is absolute control over almost every aspect of the system while the curse is trying to understand all of the system requirements at the lowest level.

As I have previously mentioned I am working on a micro-satellite prototype for my senior electrical engineering design project. My role in the project is the communication system. I was required to select and setup the hardware and software to be able to transmit data from the satellite to the ground station with handshaking and error correction.

HopeRF RFM69HCW Transceiver Module

This is the transceiver chip that we decided to use. It is surprisingly inexpensive considering the features it includes. The version we are using is the 915 MHz model (ITU ISM band in the Americas) to avoid having our own spectrum license or to have to request usage of an amateur radio band.

One of the instructors in the course is refusing to let groups use any tools that makes the software design easier. This removes the possibility of using things like Kinetis Processor Expert or ARM Mbed. This forces us all to develop our own baremetal drivers for nearly everything.

The project started with simply getting SPI to work. I had a conceptual understanding of how SPI works but the gritty details were something I was not familiar with. I first considered using an Arduino to setup SPI so I could get some practical experience but the configuration was so highly abstracted from the hardware that it wouldn't have been much help.

Say hello to the FRDM-K22F. This board has been rather frustrating to work with but not due to NXP (Freescale)'s fault. A slow clap for Microsoft as they have Windows 10 brick the on-board K20 whenever you try to read/write to the board. I found this issue to be an excuse to use my linux partition more frequently which has made me SO sad. There is (was?) a service on Windows 10 where it will try and manage the board's memory. It decides to have a hissy fit and die.

After getting past the initial hump of SPI drivers, the task of trying to setup the RFM module to be able to transmit and receive was the next mountain. The documentation for the RFM was surprisingly readable but the complexity of programming it was still relatively high.

There are many different modes of operation (transmit, receive, sleep, standby, listen, etc.) and what feels like a thousand configuration registers and flags. To make matters worse, there is many ways to perform the same task. Reading a flag could be done through an external pin (see 0-5 on the board above) or by reading the register and masking the result for the flags you want.

After many, many, many hours I finally got a baremetal SPI driver working and then the driver to use the RFM69HCW. I have also managed to transmit an image across a room which is a major relief. The camera resolution we are using is relatively low at this time but it is on the list of things to do before the completion deadline.

Excuse the selfie quality but success just felt so good to have it working.

Successful image transmission

If you have any questions about the hardware or software I will happily discuss it with you.

Hold My Beer: An Engineering Story

2018-01-01T12:28:00.002-04:00

Canada is a wonderful place to live. Hot summers, beautiful trees in the fall, and snowy winters. As December raced away, Mother Nature decided to turn the thermostat down to -15°C. The ground was covered in a blanket of snow and going more than a few days without snow was rather shocking.

Several of my siblings live on the other side of Canada. My parents were gone to visit for the holidays. As the only child still in town, house sitting naturally was my duty. This job does come with its own perks. Instead of living in my relatively small apartment I have access to a large house and two cars. The only downside of the house is that it is across the river on the other side of town.

So the day my parents were leaving they planned to drop their SUV at my apartment building and then take a cab to the airport. I had an exam that morning and driving my parents to the airport at 3 AM was definitely out of the question.

I get up in the morning and get ready to go write my exam. On my way through the parking lot I noted they had left the SUV as planned. Once I returned home from my exam I had to run some errands with my roommate. I started the SUV and the engine started making awful noises. Cars aren't my forte but there was obviously something wrong. As there isn't much traffic at this time of day and for fear of the SUV not restarting I drove directly to my parents place to exchange the SUV for their car. After the car change I completed the errands around town and returned home for the night.

The next day I had more errands to run. So as would be expected, I go out to the car and go to st. Go to star. Go to starrrrrrrrrr the car. The engine wouldn't start. Just an incessant clicking as the car tries desperately to obey my wishes. The car previously had battery issues so I could only assume the battery was dead. The car was quite a distance from the apartment building and I don't have car battery charging equipment. At this point I was willing to try anything because getting a cab to my parents place would be rather costly.

Really long extension cord and power supply? CHECK

I give my dad a call and he provides a solution: grab a power supply and extension cord from the lab on campus. For context, my dad is an ECE prof at my university. I still have access to two labs that I worked in over the summer which he also uses for his research. It is also very convenient that I live very close to campus so I could easily grab the equipment.

The power supply was a 900W supply. Much more than we needed but hey, might as well not run a supply near the maximum. I got it connected with the help of one of my roommates. I needed him for an extra set of hands since we didn't want to have stuff touching the snowy ground or the car needlessly.

We let the battery charge for a while. After the current dropped, indicating the battery was charged, we tried to start the car. Same issue as before. The car wouldn't start, it would simply try it's best which obviously wasn't good enough.

At this point I was starting to lose sensation in my hands since it was absolutely freezing (it was now colder than the original -15°C we started working in and started to get windy). I quickly packed up the equipment and returned it to the lab, saddened that the sketchy charging setup failed.

With the battery completely dead with no capacity to hold a charge a battery replacement was the only option. Fortunately a family friend was able to lend me their car so I could go and purchase a new battery. The next afternoon, after my exam, I went and picked up the new battery. Then came the fun part of the day, swapping the battery in the parking lot of my apartment in similar conditions to the previous night.

I have a few tools around my apartment but not everything needed to make the change. I had vice grips which could be used to get some of the nuts off but, the ones that are tucked away would have been impossible to remove. Thankfully I was able to borrow some tools from the ECE department's tech shop.

Cars have never really been an interest to me so I don't have much experience working on cars. This being said a battery change seemed pretty straightforward. I looked up some videos on how to change the battery for this specific model of car. It is as straightforward as I thought. Sadly with everything in this story it can't be that simple.

I opened up the hood and start to remove the bolts holding the connectors to the battery. The nuts were stick on rather hard but they came off eventually. The real problem came from ground post having half a decade worth of dirt and grime frozen onto it. I spent at least half an hour prying the connector off the battery post. Due to the wind and cold I had to go inside every few minutes to warm my hands up. Once the cursed ground connector came off the positive lead was child's play in comparison. The new battery was installed and the car FINALLY started.

With the car back in a functioning state, the adventure was finally over.

Color Vision and Computers

2017-11-08T08:50:00.001-04:00

Humans have an enormous variety of ways to interact with the world around them. Touch, smell, taste, hearing, but most important (in my mind) is vision. Computers are presently limited in their interactions with the world. They are allowed to crunch numbers, post a Facebook status that none of your friends want to read but ultimately don't get to touch, taste, smell, or see the world around them.

One thing that I find fascinating is object recognition using neural networks. I am currently taking a class with a focus on pattern recognition and machine learning where we have to do a project of our choosing. My classmate and I are comparing performance of traditional classification and deep learning for object detection (in our case an orange hockey ball). I was extremely happy when our prof approved the usage of deep learning despite the focus of the course being more on traditional classifying techniques. The project work division is that my classmate is developing the traditional classification and tracking method while I am creating its deep learning counter-part.

Orange Hockey Ball For Tracking

Conceptually training a neural network is really easy. Have enough inputs to take in every pixel in your image and enough outputs for your objects (in our case Ball, No Ball). I expected this to be an afternoon of work for an accurate system until I realized how much data was needed for training AND how long training could take.

The first dataset we created was with my Canon Powershot G5X. It can shoot 60 FPS at 1080p so we were collecting a huge number of high quality samples. We had around 2000 good images to work with after a few minutes of filming. Ideally we would have tens of thousands of images to train a deep learning system but this was for preliminary testing so we weren't too worried.

My classmate started working on his model and I grabbed some sample networks from Matlab's tutorials and started trying to understand what exactly is going on in the system. After starting to get a rough idea I decided to train my first neural network and man was it a bad idea. I setup my inputs as 1080x1920x3 (RGB images) and output with the two options described earlier. I setup the training to run on my mid-range gaming laptop's quad-core CPU (kicking myself for not getting the NVIDIA GPU card) and after about an hour it was hardly even through the first of many epochs.

Terrible results from an early network despite good validation results.

I needed a beefier computer that I could offload the training to. Fortunately due to another project I am working on, I was able to keep access to the lab I had worked on for the summer. My workstation was a pretty powerful computer that could be run 24/7 and that I could remote desktop into to check on how the training was going. It took 24 hours to train the first network.

After the painfully long wait I decided to test the network. I opened my testing script, loaded in some images and ALL of them failed. Not a single positive result. All images returned 'No Ball'. I knew it would take too long to try and retrain with a few tweaks so I decided to try training again with black and white images (1080x1920x1) which would have a third of the inputs and data. It still took the majority of a day to train.

Ball rolling across lab bench.

Our data set was just too big to train in a reasonable amount of time. The solution was to compress all of the images to 120x160x3 (RGB images). This allowed color images to be used and for much faster training time. I was surprised with how much information is still retained when dropping the image quality down so low.

Decreased resolution of original training image.

Training is currently ongoing but is nearing completed. Performance in real-time situations is roughly 70% and improving as I work on increasing the size of the dataset. The network below is the best trained network so far. Below is the training plot of of the best network to date.

In your own personal experience how was training networks? Any performance suggestions or unwritten rules?

Artful Aardvark: Ubuntu 17.10 Tips and Tricks

2017-10-27T09:19:00.000-03:00

Every 6 months I get excited. REALLY excited. My friends and wife may roll their eyes as I approach fan girl screaming over the latest Ubuntu release. I have been using Ubuntu as my main OS since Ubuntu 8.04 (Hardy Heron). They may no longer play their beautiful login sound (listen here) but all around have dramatically improved.

17.10 is a big release. It is one of the first major change to the operating system since Canonical changed from Gnome 2 to Unity. This release has Canonical swapping Unity for Gnome 3 and I am not quite sure how I feel about it so far. I realise there will always be the "it is new just give it a try" but the new GUI just feels a lot more clunky to me so far. Out of the box I find 17.10 to be much clunkier than any recent release. At least there are some ways to improve.

1. Install Updates!

I used to get annoyed when every list ever said to update. For a young release this is really important. Normally Canonical releases really well made OSs but I have found this to be the buggiest release yet. I have had to reinstall twice already (ok, ok, one of those times was MY fault) which is a big pain since I have never had to do this.

The only way to fix bugs is to update so do it! I personally update my system through terminal (Ctrl + Alt + T) but there is an easy to use application for it with the oh so intuitive name "Software Updater". You can open up the application menu (grid at bottom left corner or by hitting the Super key) and typing in "Software", "Update" or "Software Updater" if you are feeling excessive.

Once the Software Updater is opened it will automatically update and then ask if you would like to upgrade packages as needed.

2. Set User Profile Picture

This feels like a throwback to Windows XP. Unity didn't have the option (or I was just blind). I realise a lot of other operating systems may have it but it is a nice touch to the new system. When logging in you can be greeted by a nice picture of your choosing.

This can be done opening up your "Settings". In the left menu bar you will see details at the bottom, click it. An option on the left side will now be "Users". Once in there you can change your username, password and most importantly your profile picture.

3. Get Multimedia Plugins

This can be a frustrating point for new users. Ubuntu lacks the ability to play certain media types right out of the box. This being said a real quick install from command line allows this to be resolved.

Open up your terminal (Ctrl + Alt + T) and you will see a window appear like the one above. From here you can type in the following command:

sudo apt-get install ubuntu-restricted-extras

After hitting enter you will be prompted for your password. Once you have inputted your password and hit enter the install will start and will probably ask for a Y/n to installing packages. You will need to hit Y in order to get these packages installed.

4. Get Access To Canonical Partner's Software

Source Code Check Box

This can be accessed by opening up the menu and searching for 'Software & Updates'. Check the box on the first page that says 'Source Code'. You will see a row of tabs. Click into the 'Other Software' tab. In the list you will see some checkboxes. Check the 'Canonical Partners' and 'Canonical Partners (Source Code)' boxes.

Other Software Sources

Once you have those boxes checked, click on close. They system will ask if you would like to update your sources. You will want to do this so that you can actually use the new software repositories you have now enabled.

5. Install Stacer

Just do it. You can thank me later. Stacer is a tool that will allow you to keep your system running like it is a new install for much longer. It is similar to UbuntuTweak (RIP) but definitely better. Not only does it have the same functionalities as Tweak did it is much nicer looking in my mind.

This is a trickier one to find but just as easy to install as other software. You can download it from their github here. Simply download it, click on it and Ubuntu will open the software center and as you to install it.

Take a click through and see all the cool stuff it can do!

6. Write Some Software

I love programming. I spend a lot of time programming for school (mostly for embedded systems)
but the odd time I like to pick up some OOP skills (ie not C or Assembly). I don't like Java so my choice falls to Python. I like Python since I can do data processing quite well (more about that here) and still have an entire programming language to work with.

I hate having to setup software and tools to start programming so I tend to use Anaconda. Anaconda will let you manage your Python libraries that are installed and it even comes with an IDE and some other cool tools. You can read more about it here or you can simply download it from here.

Leaf Me Alone: Pattern Recognition and Machine Learning

2017-10-17T14:42:00.001-03:00

UBUNTU 17.10 IS COMING OUT SO SOON! Short post today but I will do a longer post next week focusing on the beautiful new operating system that is getting released.

I am really sorry about the posting dry-spell of late. I have been immensely busy with school work and training. You could go so far as to describe my life with the following pseudocode:

> location = &Alex;
> self_approval = 0;
>
> if (location == school) || (location == judo);
> self_approval = 1; // hooray!
>
> else
> self_approval = 0; // GET BACK TO WORK

I finally have a course at school where I get to formally learn about Artificial Intelligence. My university has graduate level courses that are about AI for electrical engineers but until this year had no undergraduate courses for ECE students. The course is looking at pattern recognition and data processing and so far it has been fantastic.

AI has been an interest of mine for a while but I always have found it hard to get into. No matter how many question I answered the question pool always became exponentially larger. I discovered that having access to tools that simplify things for new users is really important. It allowed me to start to answer my own question rather than spending an eternity reading forums.

My first forray AI was using Google TensorFlow which is a great tool but not great for learning how to use machine learning for the first time. The concepts aren't too difficult but drowning in both syntax and concepts was a little overwhelming.

Understanding classifiers and other AI tools can be pretty tricky. A tool that has been immensely helpful has been PRTools which you can get here. This tool allows for really easy visualization of classifiers and data sets.

The courses initial plunge ended up giving the students a large data set relating to breast cancer data with 30 features and roughly 550 patients. It was by far the largest data set I have ever had to usewith around 17000 data points. After many hours of work we got a classifier together with decent accuracy (96% or so?) for detecting cancer based on the information given to us.

Second lab for the course had us dealing with leaves. We were to train a classifier to be able to identify 4 different kinds of leaves. I guess this classifier is already better than me because I don't any of those types of leaves.

CubeSat: Micro Satellites and Studies

2017-09-19T09:51:00.001-03:00

The arrival of fourth year for many engineering students at my university is either loved or loathed. Senior design is a large project that all engineering students must complete to graduate. The scale of the project is one that will be larger than any previously done for academic purposes. My group and I have a rather lofty project idea. We are going to design and hopefully build a CubeSat.

What is a CubeSat? A CubeSat is like almost any other satellite simply much smaller. The size of typical satellites can be anywhere from a dog all the way up to a car or bigger. CubeSat sizes go the opposite direction. The sizes of CubeSat are referred to as 'U'. 1U is a 10x10x10 cm size satellite while a 2U would be simply two 1U stacked making 20x10x10 cm. Our target as of right now is to design a 2U CubeSat.

The potential scope of the project is enormous and since time is limited we may not be able to complete and entire CubeSat. This being said, we are going to try our best! It would be really amazing to be able to look up at the sky and know that we helped put something up there.

The design can be split up into a few subsections which I will discuss in greater detail below.

Power

Beautiful space flower power?

Solar panels are a wonderful technology. Collecting light and convert it into electrical energy? What isn't there to love. CubeSat's typically have 3-12 months to orbit before decaying and burning up. Due to size restrictions and power requirements we won't be able to use anything like a pre-charged battery so we must power the entire mission using solar power.

What may need to happen is have the satellite orbit Earth a few times to charge an on-board battery and then have the main computer system turn on and do what is needs to. We also have to be able to power the mission equipment on-board which we are unsure of what the requirements are. This could be a tricky part of the project and is ultimately the most important.

Communication

Sadly our ground station will not be as good as commercial satellites

This is my favourite part of the entire project. Signal processing, communication systems and RF design are all things that really interest me. Fortunately this project has plenty of design work in this area to be done.

Some simple math shows that we are going to have around 130 (dB) losses on the communication channel. This is an enormous loss that we will have to try to design our antennas around. Sadly the CubeSat will have to fit into a very small containment so we will most likely need deployable antennas. I have a few ideas around what we should do with the antennas but nothing too serious until we decide what frequencies our communication channels will use.

Central Computer System

Most likely going to be an ARM based system.

Every part of the system will be controlled by the main computer system and so it is very critical that we have a good design here. Not much thought has been put into it yet but a professor involved in the project suggested that we use TCP/IP communication on the system to communicate between boards. Guess it is a good thing that I am taking a course on digital communication this semester.

Mission

At my university we have a the pleasure of having a world renown Geodesy and Geomatics department. We also have a large number of researchers in our physics department who study Earth's upper atmosphere. There have been several missions suggested so far between the two departments and the missions all seem super cool. As I mentioned already the power for the system is most likely going to be very limited. Once we have looked more at the power systems we will have a better idea of what to expect but it seems that the physics department's mission seems easier to do from a power perspective. It would also require less equipment on the CubeSat allowing us to have a larger system in the satellite that isn't the mission.

Anybody have experience with CubeSat and/or space hardware and design?

Tips, tricks and suggestions will be very much appreciated.

Slashdot: News For Nerds, Stuff That Matters

2017-09-05T20:37:00.000-03:00

Several weeks ago, the professor who is supervising me for the summer and I were talking about technology. This is to be expected since he is an ECE professor and I am an ECE student. It started as a run of the mill conversation until we somehow managed to get on the topic of why my supervisor always needed to have an RSS feed on his mobile devices. He insisted on the RSS feed to have easy access to Slashdot.

When my supervisor first mentioned Slashdot I wondered what it was. A quick google search and some reading showed that it is the eloquent sibling of Reddit. Not to bash Reddit too hard but it can sometimes be hard to wade through the heaping pile of garbage that can be collect in a Reddit thread.

There isn't an up/down-voting system but the content is definitely of a higher quality than Reddit. You can usually tell a post is of a higher quality by the number of comments. The comment counter takes the visual place of the up-vote counter on Reddit.

Slashdot may have a gaudy green-blue theme but once you get past it you will realise how great it is. The company slogan is "News for nerds, stuff that matters".

Users can browse through the Slashdot website directly or easily through Facebook, Twitter or other social media sites. Besides the great content from SlashDot, it also seems to have content being posted ahead of the curve.

Content on Slashdot does have anything from hardware to kernels and anything else tech related you can think of. AND it all comes in a nice, clean package.

Sorry for the short post this week, I am getting ready for school and trying to sort out some stuff for an exciting project I am working on. Hopefully I can talk about next week.

Embedded Systems: ARM or Arduino?

2017-08-29T10:21:00.000-03:00

As the ranks of embedded system developers swell with the hobbyists and amateurs, the question of simplicity versus precision is coming up more regularly. Should we learn to use Arduino? Should we learn to use ARM? My simple answer would be learn both but as with most technological dilemmas the answer is never that simple.

In my education I have been forced to use an ARM based micro-controller. Being tossed into a complex development environment was really great for me as a developer. I have always been enchanted by embedded systems and this experience allowed me to sink my teeth into a design problem. Designing a hardware and software solution in one clean package is satisfying.

Before beginning this comparison I would like to say that I am not looking at advanced tools for ARM like NXP's Processor Expert or other tools that simplify the design process. We will be comparing unassisted development of Arduino vs ARM.

Simplicity

Arduino UNO, one of the more commonly available boards.

Arduino definitely wins this category in my mind. Being able to pick up a micro-controller and have a simple system working in a matter of minutes is rather appealing. Users don't require such a large overhead of knowledge to understand what is happening at the lower levels. Coding for the Arduino is so simple that even children, young adults and new programmers can learn it in a matter or minutes.

If a user had spent more time using ARM based systems or had very good libraries then it would be likely that they could instantiate a similar system just as fast but the user has to know how to set that up while Arduino does it for you.

The Arduino IDE is a pretty lame IDE and lacks many features that I feel it should have but sometimes having a point and shoot development process is what is really needed.

Precision/Control

FRDM-K64F: First ARM board I used.

As the complexity of the system increases being able to control every aspect of the system become paramount. I would consider ARM and Arduino very reliable. This then becomes a question of what allows for the lowest level control.

Arduino lacks low level control that ARM allows users without much searching. Being able to configure the registers for the ADCs and DACs yourself allows you to only get what you need. Being able to adjust the read time of ADCs, the impedance of the ADC pins, built in averaging and many other features allows developers to get exactly what they need. I have found Arduino lacks this low level control. I often find myself trying to compensate in software for things like ADC averaging which eats up space. All that the controller needed was a control register getting another bit written high but instead it is now a new block of code.

Understanding what is happening at a low level also allows users to debug more accurately which leads us to our next section.

Debugging

(Arduino Mega /w Custom Shield) Writing today to avoid debugging this monstrosity.

Nobody likes debugging. You've spent days, weeks, months writing code. The smallest tweak causes everything to fail horrendously. What do you do? Beat your head against a wall? Quit? No, we have to mop up our tears and debug the monstrosity that lies before you.

In my experience with debugging Arduino I have wanted to tear my hair out. As mentioned early, Arduino fails to allow low level access into the system. This is frustrating when trying to debug. Arduino IDE lacks the feature of being able to advance step by step through your code and look at variable values. I find myself adding in never ending "Serial.println(variable_name);" to try and see where things have gone awry. This is tedious and takes so long to try and figure out what is causing the problem.

I am not a fan of Eclipse IDE. To be honest I hated it until using the NXP modified version for their micro-controllers. Debugging was almost as easy as writing the code. Sure you still have to figure out EXACTLY what is happening but it allows users to ease the pain of debugging.

One of my favourite features of the ARM based systems I have used so far is the ability to step through the code line by line and see what is happening on a register level. Many problems seem to arise from a small error in a control register and this can be checked as easily as hovering your mouse over the register name in the code while debugging (at least in Kinetis).

The improved debugging is a feature that definitely has me lean more towards wanting medium to large projects done on ARM boards.

Overview

It can be difficult to decide which system suits your needs best. For smaller applications I would almost always choose Arduino since it can be rapidly developed and troubleshot for smaller systems. As the complexity of the system increases I tend to lean towards ARM based micro-controllers due to better debugging tools and better control.

From an educational perspective, I definitely think that Arduino is a good place to start. Once developers start to become comfortable with Arduino they should migrate towards ARM based systems so they can have better control.

What are your preferences?

August 10: Beautiful Music Videos

2017-08-22T12:02:00.001-03:00

Despite usually being an auditory experience music can also come with an equally wonderful visual experience. With everybody and their dog trying to make it big on YouTube there has been a massive emergence of beautiful music videos. There are some fantastic live-action videos but for this list I am looking at animated videos only. I even decided to save you all the convenience of having to search for the videos or going link by link and made a YouTube playlist. IF you do want to thank my just comment your favourite video.

You can find the playlist here. I will also link the titles of the videos to their respective clips.

10. She Wants Me Dead by Cazzette

This song makes it on the list but just barely. I like the song and the music video is pretty good. I remember some kids shows I used to watch having a similar art-style.

9. Jenny by Studio Killers

This is the song I found to discover the Studio Killers. I like some of their other songs but this one has an interesting art style and catchy tune.

8. Anvil by Lorn

First thing that popped into my head when watching this video was TRON. Ironically I haven't seen the complete movie but I think we can all try and see the similarities in style. The story on this one is pretty weird. After watching it a few times I got some ideas but feel like I am reading too much into it.

7. The Wolf by Siamés

I swear I don't only like black and white music videos. This one just happened to have some cool animations for doges that I wanted to share. Song is great, artist is great. I was really glad that YouTube suggested this one to me.

6. Source by Fever The Ghost

WUT. IS. THIS. Song is catchy and the music video will have you saying "what the hell?" for the next ten minutes. 5/7 would watch again.

5. Delta by C2C

I wish that somebody would create a story to go with the music video because it would be really cool. There is obviously no background information on the clip but the story is still pretty meaningful.

4. Let's Go by Stuck In The Sound

Sad Asian astronaut is sad. I am always impressed with how much plot can be jammed into five minutes or less.

3. Rasputin by Boney M (Remix)

Disco music can make pretty much anybody dance. Even Putin. Boney M.'s classic Rasputin gets revamped and stuck onto a music video for a far inferior song. They technically don't belong together but I think they should be seen together.

2. Ghost by Mystery Skulls

Synchronised head bouncing meets a heart throbbing story. The characters remind me of Scooby Doo. The story is great and the music is REALLY catchy. Good luck getting this one out of your head.

1. Lone Digger by Caravan Palace

This is one of my favourite recently discovered music videos. The way the animators created all the characters is fantastic.

What is your favourite video? Leave a comment!

Ivory Coast: Undercover Anglophone

2017-08-15T11:19:00.001-03:00

No time to blog (I am in blue).

I shall start by apologizing for vanishing from the face of the earth (or at least my blog) for three consecutive weeks. One of my favorite hobbies is judo, an Olympic grappling sport that originates from Japan. I have been competing for many years and was given a spot on the Francophone Games Team. Ironically I am an anglophone attending the Francophone Games. This being said I am bilingual (english and french) so I am at least able to communicate with the locals while I am there. It was my best international result so far which has me excited but I am still sad that I didn't medal. I went 3-2 for bronze and only lost to other Canadians who are going to senior worlds in a few weeks.

From a technological perspective the Ivory Coast is an interesting topic. Africa has tended to lag far behind in technology which isn't necessarily a bad thing. The lag has allowed for some rapid jumps to newer technology. At least in the city I was in (Abidjan) there was a lot of cellphone users that all had internet through mobile networks. What surprised me most was how little mobile phone plans were.

Wireless Woes: Self Interference and Spectrum Reuse

Original Tower Configuration

After spending nearly 48 hours travelling with inconsistent internet, I was excited to be able to message my wife and friends upon landing in the Ivory Coast. I had anticipated bad internet, inconsistent and incredibly slow. Unfortunately I was entirely right.

What I had guessed was that the internet was slow due to capacity. In the Athlete Village (think compound with armed guards where all the athletes live), they had some official Francophone Games Wireless Internet services. It was free to use and an open connection for all but fortunately the range didn't extend far beyond the compound.

External people were able to get into the athlete village as approved vendors or visitors if they had the proper credentials. There was a company called J-Spot that was offering a secure wireless network to the athlete village. They were walking around the compound and trying to drum up some business with prices were pretty reasonable. I considered getting the connection until I had done some investigation as to why our official games internet wasn't working very well.

With many athletes on it I had assumed it was slow due to capacity. To confirm my theory I decided to do some investigation. Thanks to Android Developer Mode (it is called that right?) I was able to turn on verbose wifi logging and see all the panels, frequencies and their power levels. What I saw was very alarming. Looking at the frequencies for the systems in use, they were nearly all on the same frequency.

The official games networks were all running in different frequencies and seemed to have been reasonable well planned. J-Spot however was an atrocity. Be it an intentional or accidental configuration, they were causing a massive interference problem. The official games had probably 10 panels setup around the compound and weren't using excessively high power levels. J-Spot had decided to have panels everywhere with insanely high power levels relative to everything else.

Trying to use the official games wifi on 2437 MHz at around -70 dBm results in a pretty good connection. Only problem is that J-Spot was also running a panel at 2437 MHz at -50 dBm so good luck getting much through. We could get the odd burst of internet but for the most part our connections were so unstable we couldn't send as much as a Facebook message.

I addressed this concern to the Canadian-NB Mission staff and I am guessing they told the games authority since some network changes were made in a few days. Sadly they didn't really know how to address the issue and only made the interference issues worse.

Tower Configuration 2.0

It may be hard to see in the photo but they turned one of the panels 90 degrees so it is pointing at another panel and then added on the white disc (another panel) to provide a "fix" for the problem.

Fortunately an internet provider from the area called MTN came in a setup ANOTHER network for the athletes on a frequency that wasn't in use by anybody in the area. Finally all the privileged North Americans could get back to their Facebook, Twitter and Instagram.

Mobile Phones: Internet for All

Based on what I had seen I have been led to conclude that bypassing individual wired connections for users with simply having a greater wireless capacity gets more users online faster. Sure the internet wasn't particularly fast (< 1 Kbps at times) but with a low cost of plans users can get internet. In Canada, users can get a small amount of data and unlimited talk and text for $40 CAD to $50 CAD. Equivalently in the Ivory Coast or merely $22 CAD users can get equivalent or better plans.

I do realize that Canadian Dollars are a stronger currency than the Ivory Coast Francs (CFA) but the cost to provide is still much cheaper. Ivory Coast users seemed to be primarily using their phones, no TV, home-phone or internet connection besides their phone which does dramatically reduce the costs they would have for communication/entertainment.

Git Good: Hilarious Repositories

2017-08-08T10:53:00.001-03:00

This past week at work I finally had a reason to sit down and start learning how to use Git. So far this summer I have written large amounts of code for a control system which will be used to perform antenna and RF testing.

One of my room mates (and coworker) is currently working on a massive software project which is really cool. I don't want to talk to much about it since it is a work in progress but he suggested I start using git for version control. I was hesitant at first since my system for version control wasn't too bad. BUT I don't regret learning to use git. Hopefully I can have my him talk about his software project in the coming weeks.

Upon starting using GitHub to host my repository I decided to take a look around and see what I could find for interesting software. So I decided to compile a list of my top few repositories currently available.

Passwords for the Manly Man

Creating passwords can be hard. Creating secure passwords can be even more difficult. Why not have a badass sounding password that is as secure as it is cool sounding?

Some of the better generated passwords I got were:

rugged+tornado-victory~P90X

sweaty+motor+balls-22

transcendent-tiger-might-F15

iron-typhoon+leather+9MM

Next time your friends ask for your password to your Netflix account, whip out a manly password to impress them all! Watch your chesthair and beard grow with every password you change!

Check out there website here: http://dfcb.github.io/manly-man-passwords/

And their GitHub here: https://github.com/dfcb/manly-man-passwords

ArnoldC

Who doesn't want to sounds like Arnold Schwarzenegger with his signature catch phrases. We all can admit that though they were cheesy, his 80s action movies were pretty iconic. Fortunately we have been blessed with a GitHub repository that allows us to program as Arnold speaks. Bring on ArnoldC.

This beautiful repo uses Arnold's one liners for actual programming. Examples are as follows:

False: I LIED

True: NO PROBLEMO

If: BECAUSE I'M GOING TO SAY PLEASE

Else: BULLSHIT
Return: I'LL BE BACK
EndMethodDeclaration: HASTA LA VISTA, BABY

The example of hello world is given on their wiki and looks like this:

IT'S SHOWTIME

TALK TO THE HAND "hello world"

YOU HAVE BEEN TERMINATED

So all in all this makes me laugh every time I try and learn any of it or try and pretend to write some code with it. You can check out the repository to acquire this beautiful language.

GitHub Repository: https://github.com/lhartikk/ArnoldC

Put Me On A Watchlist

Ever wanted to feel special? Like somebody is watching your move because you are a person of interest? Now with a simple python script you should be able to!

In a beautiful 126 lines (in the current version, subject to change) you can start to have your internet monitored! How this script works is it will take a pre-made sketchy list of queries, some examples follow:

'how to make a dirty bomb'

'how to become a terrorist'

'how to hire contract killer'

'how to buy drugs via tor'

'buy guns on tor'

The list goes on, there is I think a total of 81 terrible searches that the script will do for you. The beauty of it being open source is that you can even add your own! Share it with your friends!

Get yourself monitored by checking it out in the link below. Maybe just from looking at this post you might get monitored?

GitHub Repository: https://github.com/neufv/put-me-on-a-watchlist

TrumpScript

Though this may seem in essence to be a similar tool to ArnoldC it still remains a very powerful tool. The slogan for the language reflects their true intentions. "Make Python great again".

This is a modified version of Python with many added features to improve functionality.

- All programs must end with 'America is great.'
- The entire language is completely case insensitive
- Instead of True and False, the keywords are Fact and Lie

This list goes on and on so I will simply show you the provided sample code from the project:

What are we in this country
Hillary speaks nothing but lies
But look at me I came to this election to make guys
believe again
believe in fact
if, all of us real lies the light; : say "VOTE TRUMP" !
but I know we should be free
else the result will be bad: all the work of George
Washington was for nothing
so this election say "Hello World" say "TRUMP FOR PRESIDENT"!
America is great.

GitHub Repository: https://github.com/samshadwell/TrumpScript

These projects I all find to be absolutely hilarious. Any other great GitHub repositories I missed? Leave a comment below!

Python: My Anaconda Don't Want None

2017-07-11T13:54:00.000-03:00

Some people last week were messaging me about what IDE and setup I was using for programming Python and so I thought I would discuss what I have been doing.

Python may be really easy to learn but it can be very tricky to configure everything properly. The vanilla installation Python is pretty simple to use. You can simply write a text file and run it from a terminal. Sadly things start to get a little hairy when you are trying to use many different libraries and can't easily get them installed. You can try installing and managing all packages manually but why not let the work be offloaded to a great piece of software. Enter Anaconda.

I discovered Anaconda completely by accident. I was going to manage libraries by myself but after struggling to install all the required software I saw mention of it on a forum. Rarely am I this pleased on an impulse install. Anaconda allowed me to have complete control over my Python and library versions and allowed me to quickly switch back and forth between configurations. On top of all this it installed Jupyter Notebooks, Spyder and some other pieces of software that I haven't had time to fully explore. Anaconda takes Python and makes it as easy as installing Matlab libraries.

My default Anaconda install on Windows 10 comes with 6 default applications. They are as follows:

- Jupyter Notebook

- Qtconsole

- Spyder

- Glueviz

- Orange3

- RStudio

As previously said I haven't played with all of the apps yet so I will only talk about Jupyter Notebook and Spyder.

Anaconda right out of the box looks so clean and inviting. Like any good software developers they clearly adhered to the saying, "if you have to explain your GUI it sucks". First let's take a look at Spyder.

I have seen Spyder almost every single time I browse through the Ubuntu Software Center looking for cool software. Sadly I also passed it up every time. Fortunately it was forced upon my with my installation of Anaconda on my work computer. Spyder is the closest IDE that I have found to be closest to Matlab. It has the workspace (variable viewer), a terminal that you can manually input code into as well as the obvious scripting window. All in all a really fantastic piece of software for number crunching with Python.

This past week I decided to up my Python game by taking an online course for data science. This is how I was introduced to Jupyter Notebook as well. I originally wondered why I would need those at all but I can really see them being a powerful tool. They are similar to Matlab reports except all the hard formatting work is done for you. It makes your code much more modular and easier to share. The course will share notebooks to you and then walk you through the notebook in an attempt to teach you. This is great for me since how I like to learn coding is from example cases and playing around with the language. I can foresee myself using these in the coming year for data analysis in my university courses.

I have yet to take any time to look at the other applications but they seem very helpful for data acquisition and processing. I am also impressed that I can install TensorFlow in Anaconda which will allow me to keep learning about neural networks and AI without having a difficult setup.

What is your favorite Python library? Most commonly used?

Data Processing: Matlab, Python or Octave?

2017-07-04T12:11:00.000-03:00

The internet is a sea of servers, data and people. Some of said people have managed to scrape out a living doing data analysis on just about anything they can get their hands on. Data scientists are being hired left right and center to try and improve performance and experience of users. By looking at trends they can determine things like what students in a university course are likely to fail based on their current test scores in the class. This would allow teachers to then help the students before it is too late and they fail courses.

The possibilities of data analysis are nearly endless. It could be loading data into neural networks for AIs to analyze, it could be optimizing website layout to increase user visit duration or anything else you can imagine.

With large amounts of data there comes many different ways to process it. You could try it in Excel (and die before you can fill everything in) or you could look to more powerful tools. In my experience with data processing and analysis I have used three of the more popular options. They are Matlab, Python and Octave.

Each language (set of software?) has pros and cons that accompany it so we will look at each option in detail. Though this isn't a complete list, I haven't encountered many other data processing tools as commonly used as these. Feel free to comment any that I left out that you would like me to cover and I will update the article.

Matlab

Matlab is pretty much the industry standard (for electrical engineering). Though it may be expensive ($2150 USD) for a personal copy it does have many useful toolboxes. The trick here is that Matlab is the EA (Electronic Arts) of the computing world. Almost all of the good toolboxes cost extra and many of the more advanced toolboxes need several other more basic ones first. A toolbox that I would like is the HDL Coder toolbox. Sneaky Matlab makes it so I have to buy three toolboxes to get it and have it be functional.

Besides the potential problems with toolbox requirements Matlab is excellent to work with. When describing it to friends I often just say a calculator on steroids. You can do control systems with Matlab but my experience with that has been through Simulink which I would consider a separate tool.

The language component of Matlab is very simple to use. If at any time a user needs help they can look up commands on either the Mathworks site or by typing help "command" into the Matlab command line. All in all the software has great community support but does come at the price of having to buy Matlab.

Expensive but gets the job done, not my first choice but is a standard piece of software for EE.

Python

I am definitely biased towards Python. Based on my experience with Python to day I will definitely be using more of it in the future. As a data processing tool Python is exceptional. It has many libraries that will assist in the number crunching. Using what is called Anaconda, a user can manage and install all of the libraries for Python that you could ever need. The best part is that all of the Python libraries are completely free.

When comparing Python to Matlab it is very similar to write the code. The command names and syntax are nearly identical. Python is slightly less user-friendly (if you don't use Anaconda) but it still manageable for new users.

One of my favorite things about Python is how diverse it is. It is really easy to run C code and a variety of langues from within Python using wrappers. I do know that Matlab can do this as well but it can be really frustrating, especially if it involves Mex files.

Despite being great for number crunching, Python is a complete programming language that is great for object oriented and beginner programming. In recent years, many universities have started switching from teaching Matlab or other data analysis tools to students and replaced it with Python. Why not kill many birds with one stone? Free, open-source and easily learned. If I could go back and start again, I would have tried to avoid Matlab and used Python instead.

GNU Octave

Octave, oh octave. Haven't used Octave in any amounts recently. The last time I used octave was when it was just starting to have the option for a GUI. I can definitely say I haven't spent enough time with it because from what I have heard it is a great piece of software but my personal experience was very underwhelming.

Octave looks and feels like Matlab, code writes almost the exact same and everything which isn't surprising since it is designed as an open-source equivalent. Like Python and Matlab, you are able to load code from C/C++, Fortran and other languages to be run from inside Octave. I have never done this with Octave but I am assuming it can be as frustrating as mex files in Matlab.

Performance

Somebody new to data analysis and trying to select what is best for them will say which one should I pick? For me this wouldn't be a particularly difficult question since Python is free, fast and does more than just data analysis.

If somebody is worried about execution speed I wouldn't worry too much about which language you choose. In my experience when using both Python and Matlab for signal processing I found Python to have a slight edge. If performance is that big of an issue once can simply implement C/C++ code into any of the above options to improve performance dramatically.

Alternatives

In recent years I have heard of some great alternatives for data processing. People have been mentioning using R. I have no experience with R but plan on investigating this more in the future.

- Sage Math

- Julia

- R

- Excel (starts bleeding internally)

What is your weapon of choice for data processing?

Photo Friday: Technology Helping Me Not Suck

2017-06-30T11:22:00.002-03:00

Forest clearing discovered on a hunt for a waterfall.

Travel is something that my wife and I love, but then again who doesn't love traveling. In order to better document our travels we decided to invest in a high quality camera. We ended up getting a Canon Powershot G5X. This camera has turned out to be worth every penny.

This camera is amazing. 1080p, 60fps, it feels beautiful on your eyes. Besides filming and taking photos while we travel, we also film our judo competitions. The camera that our team normally uses for filming fights is not bad but the G5X blew it out of the water.

Besides the great resolution, the camera is small and has pretty good battery life. When my wife and I travel around, we simply try and take as many photos as possible. Better to have too many than not enough. One problem we have experienced is that the media files become enormous. We have had to actually go out and buy extra camera memory on trips before to accommodate extensive filming.

So here are some of my favorite shots we have taken in the past few months as well as some video examples.

Unknown species of plant. Please tell me what kind of plant this is.

Diamondhead in Honolulu, Hawaii

My wife's travelling sneakers.

Buddha in a nature park in Honolulu, Hawaii

Halloween right?

Dr Dad: The Struggle of Being the Prof's Kid

2017-06-28T09:49:00.001-03:00

Good ol' chalkboard design

Towards the end of high-school people always asked me one seemingly simple question, "What are you going to study at university?". For me it wasn't always as easy a question as I originally thought. My choice of university was pretty obvious with my father being a professor at my local university, the tuition reduction was sufficient that very large scholarships from other schools would need to happen before I would even consider elsewhere.

With my university effectively picked, now all I needed to do was pick a program. I had always leaned heavily towards STEM fields. Math, science and building things had always intrigued me since I was young. This helped me narrow down my choices down to an engineering discipline.

Looking at built in waveforms from the FMCOMMS4 RF transceiver

By grade twelve I had selected either chemical or electrical engineering. At that stage it was a pretty even choice but I ended up going with chemical, the reason being that I wished to avoid having my father as a professor since he is an ECE prof.

Summer rolled around and I worried more and more about my choice of chem. eng. A few weeks before the start of the semester I emailed the enrollment office and changed to electrical. This was a choice that I wouldn't regret. Electrical is much more interesting (in my opinion).

First year flew by. Second year rolled around and a class I had been dreading came around with it. There is a numerical methods course for electrical engineering and it is taught my none other than my father.

Amplifiers getting mounted on our custom antenna.

At this point in my university experience, most of my class mates didn't know that he was my father. I wanted to keep it that way. My friends obviously knew but I tried to keep it to a minimum. In this class when I wanted to ask or answer questions I would simply raise my hand and wait. None of this "Dr Colpitts" or "Professor". I didn't want to say dad, father or anything.

It was weird at first but after a few weeks it because pretty normal. Many times my dad and I would joke about me asking my parents for help with my homework. There were always frequent complaints about this one professor. Tall, balding, teaches me numerical methods and MAN WAS HE AWFUL. Emailing my dad about the course if I was away was always amusing.

With your dad being the addressee of the email really opens up a whole new world of email signatures. My favorite was Dear Dr Dad. After enough emails addressed like that, he did start signing his emails to me in such a manner.

Lucky for me I did well in the course and wasn't disowned. Only problem was that the numerical methods course was relatively easy. The tougher course would be electromagnetic that I would have with my dad the next year. It wasn't as bad as expected. If I recall correctly my dad graded my tests during the year but had another prof compare them. I think the other prof even marked my exam and compared my answers and grade to 20+ other students from the course.

Engineers gotta be ethical right? I can guarantee the conflict of interest was dealt with. Fortunately it seems that in my city electrical engineering professors have electrical engineering children. I believe that I am the third or fourth prof's kid in the department in recent years so they were pretty comfortable with how to handle things at this point.

Radio transceiver card for our Xilinx FPGA. More on this next week (I hope)!

Update on UAV System:

We have gotten our FPGA (FINALLY) and FMCOMMS4 external radio card. I have been playing around with PN sequences, specifically Frank-Heimiller sequences since the RF card will take both I and Q signals to transmit. But now we are going to be looking at custom PN sequences with a carefully selected correlation property. Check out my last post about it here.

Flying High: UAVs, FPGAs and Ubuntu Come Together

2017-06-20T13:49:00.000-03:00

Xilinx Zybo Running Xillinux

This summer I have the privilege of working with a research team of students and professors at my university. As an electrical engineering student this has me over the moon since it will be hands on experience with industry level hardware and software design.

The goal of our project is hilariously simply to describe. We want to track insects using a UAV. Sweep a field, figure out where they are and then produce a report for the users. This does sound like relatively simple task but as with almost every design problem the devil is in the details.

One of the grad students designed a logo for our research team.

Currently the design team is comprised of two undergraduate students (one of them being me), two masters students and two professors. One professor's specialty is electromagnetics and hardware while the other leans towards signal processing and communication. I am working one the signal processing and software aspects of the project.

At this time we are at a cross roads between which FPGA to use. The choice is split between a Xilinx ZedBoard and an Altera DE10. Both need to be able to connect to an external radio comms card. The chip we are looking to use is the AD9361 from Analog Devices. The chip is a high performance radio transceiver that we are going to use to transmit at roughly 5 (GHz) which will then be mixed up to 10 (GHz). There is the ARRadio board which we would use for the Altera FPGA and there is the FMCOMMS2 which we would use with a Xilinx. Both of these boards use the AD9361.

RoBeast Update: Check out here! Finally getting wired together.

Since the external radio card uses SDR (software defined radio) running on a SoC (System on Chip) we have the ability to do most of our signal processing at a high level. Since it won't be feasible to run Matlab on the SoC we must find another way to process the data that we receive. This is where Python enters the system.

I now have a Xilinx board running Xillinux (Ubuntu 12.04 for the SoC) with the same ARM processor as the board might be using in the final design. This should allow me to do code performance testing to ensure that the system will be able to process data within the coherence time. We assume a top speed of our UAV to be around 10-15 (m/s). With that speed in mind and the custom antenna beam angles we have about 44 (ms) to process everything before collecting more data.

10 (GHz) transmit antenna without the amplifiers.

Our transmit and receiving sadly isn't as simple as transmitting at 10 (GHz) and receiving back at 20 (GHz). To improve detection of the tags we will be using we are trying to find a modulation scheme and PN (pseudo-random number) sequence that will facilitate easy processing and processing gain.

A nice feature about the SDR and the radio cards is that we simply pass the board I and Q signals which means we can use Frank Heimiller codes, or as I like to call them, Frank codes. We will be able to select our I and Q data that we transmit to be such that the correlation between our receive and the sequence will be approximately zero for all values except for when the receive signal is the PN sequence. This translates into amazing tag detection with very low chances for false-positives or errors.

A couple of the tags. Hard to get a good photo since they are so small. Essentially just a fancy piece of wire with a diode soldered across a loop.

I have been beating my head against a wall trying to get the correct versions of things installed on the SoC but progress is being made and hopefully Python can save the day!

Machine Learning: Fight Smarter Not Harder

2017-06-13T14:40:00.001-03:00

Multi-layer neural network.

Brains are cool. Computers are cool. Over the past several decades people have looked at creating a computer "brain" and boy were the researchers successful. Neural networks, or as I like to call them "computer brains" have come a long way and are something I am very interested in. Being able to add abstract learning to a computer is strange. Being able to "teach" a computer has been done for the past years without a problem but for me to sit down and try to do it is mindbogglingly complex.

Sadly I haven't had much free time to write this week and so I will only quickly skim the surface and direct you to a great video to talk about the neural networks that I am going to be studying.

I found this guy on YouTube and think his content is great. I am following along through his tutorials. Here is a link to his video and to my playlist that I am slowly building about ECE topics that interest me. You can check the videos out here.

The tools he will be using are TensorFlow by Google and python. My suggestion for a great python IDE would be PyCharm. I only recently discovered it but I am really enjoying it. Easy to setup, easy to use and looks really clean. I had previously been coding my python work using eclipse with the python plugin but it felt very clunky to me. You can check out the Community version of PyCharm for free here. It is available for Windows, Linux and Mac and it is fantastic.

I have been wanting to use neural networks for both image processing and adaptive filtering (I am a huge nerd, go ahead and laugh) since they are both things that interest me.

Over the next couple of weeks I will be learning how to use all of the software and then passing it on to you guys. If you have any specific request of things you want explained I will take a look at them!

RoBeast: Using Arduino Research Application

2017-06-06T14:14:00.001-03:00

A very official name plate.

Open source technology is a beautiful thing. Not only does it let me design more effectively it also allows me to purchase components at a cheaper cost.

In comes Arduino and every other knock off brand you can think of to claim the micro-controller market. Arduinos are fantastic devices. They are cheap, relatively powerful and easy to use. They remove a lot of the programming overhead that many ARM based micro controllers have.

Side view of Control box.

This summer I am doing research with a professor at my university. We are going to be building a UAV for insect tracking. In order to strip down the weight of the system, a grad student has designed antennas both the transmit and receive antennas to increase performance and decrease weight.

One problem is that we are having a tough time measuring antenna performance. We have an anechoic chamber for conducting antenna testing but our positioning system is currently not working properly. It isn't a terribly complex system but there are some tricky bits that need to be properly addressed otherwise the system could become even more damaged or lack the precision we need.

The RoBeast in the chamber.

The control system is affectionately called the RoBeast. It was built back in 1990 and the first control system was designed using BASIC. The amount of code used is absolutely crazy clocking in at around 33000 lines of code. The second iteration of the control system used MATLAB and serial ports on the controlling computer.

Unfortunately a few years ago the MATLAB controller system stopped working and the grad students that set it up have since left making it tricky to troubleshoot problems. There is roughly four to five thousand lines of MATLAB code that is sorely lacking in comments. It also uses what is called mex files. Imagine compiling C code with MATLAB to make things run faster and to access the parallel ports except none of the files provided to you will compile. All in all trying to troubleshoot problems with the system was a complete disaster.

Gecko Controllers on top of butchered Centroid power supply/

I spent most of a week trying to figure out what the code even does. After failing to get it working I decided to scrap the entire control software and start from scratch. This allowed me to design the system from the ground up with ease of use, ease of troubleshooting and lots of comments in mind.

This is where I was fortunately able to pick a very simple system (relative to my other options) to design the control software. I wanted to use a micro-controller that almost anybody could use without much training thus resulting in my selection of an Arduino. Due to the pin requirements (4 pins per motor controller and many limit switches) I have selected an Arduino Mega. It will most likely end up being a knock off since they are a fraction of the cost with the same performance.

Testing characteristics of the antennas.

My trusty arduino and I set off last week on rebuilding a broken system. The existing hardware is a metal frame that has screws, pulleys and stepper motors to adjust the position. What I have had to do is write the code to create a command line control system using serial communication as well as actually creating the signals to move the sy
stem.

Creating the signals for moving the system was trickier than I had originally expected. Since they are stepper motors we can know how many steps we have taken. The only problem is that if we go to fast we can slip steps. If we go too slow it will take forever to move the positioner. For rotating the top plate it takes 100 steps to move 1 degree. To move the system in and out of the chamber it takes 3000 steps for 1 inch of movement. If you do 50 steps per second it will take an incredibly long amount of time to move. So we need to create a waveform that lets it accelerate, move, decelerate and then stops. Easy conceptually but much trickier to implement.

I managed to get some of the movement functions working and so it really just comes down to perfecting the controller code. We should be able to connect the control system to our Vector Network Analyzer this week to collect some data!

On to taking measurements!

Custom made 10 GHz antenna.

Proleter and Gramatik: Free and Beautiful

2017-05-30T14:48:00.000-03:00

With everybody sporting high power computers and USB MIDI controllers everybody wants to be a musician these days, myself included. Many people try and sell what they produce regardless of the quality while others produce superb music and release it for free.

I am a strong advocate for Free and Open Source Software (FOSS) but I am also a supporter or free music. With pop music being stuck in a rut for the most part, finding good music has become harder. Fortunately the internet allows us to rapidly find a large variety of music that suits our needs.

Over the years I have used several different sites to find free or creative commons music. Soundcloud and Jamendo have been my main sites for such purposes. There is a lot of terrible music on both platforms but once you know how to look it becomes apparent that there is a lot of beautiful music available.

Throughout my digging I have found a few artist that continue to impress me to this day and they are Proleter, Gramatik and Professor Kliq. Each has a unique sound but all are pleasing to listen to (at least for me...).

Professor Kliq

Professor Kliq is sadly my least favorite of the three but I encountered him first. Even though he isn't my favorite he is still fantastic. His music is quite quirky but great for exercising to (check out his album Curriculum Vitae here). Some of his albums are much more mellow and low key like The Teragraph EP which you can get here.

Gramatik

Gramatik is a staple in my everyday listening. I like almost every single song that this guy has produced. Even better yet he gives it all away for free. His entire discography is available for download for free from his website which you can get here. Gramatik can really vary from song to song so you will just have to find what you like. My favorite album as of now is Beatz & Pieces Vol. 1 or Age of Reason.

ProleteR

I love jazz, I love electronic music. Therefore I love ProleteR. Even if you don't really like any specific component of the music there is so much good that is hard to not find yourself bobbing along to the music. This is the artist that got me interested in electroswing. Just listen to it. ALL OF IT.

Jazz, electronic music and rap. What isn't there to love about this track? There are instrumentals, rap, jazz, covers, take your pick!

Ubuntu and Snaps: Pros and Cons (Updated)

2017-05-23T09:19:00.001-03:00

Edit: Big thanks to the Google+ community for giving me direction to some good documentation on snap files. As a result I am updating this post as of June 2, 2017.

With every major upgrade, Ubuntu usually brings in a big new feature or two. Like back in 2011 when they switched from Gnome to Unity in Natty Narwhal or when they switched from Rhythmbox to Banshee and then back to Rhythmbox (I am a hardcore music fan. Don't mess with my audio player!).

With the release of Zesty Zapus, I have noticed that Canonical seems to be pushing Snaps as their new install package. With any new linux tool, lets take a look at it! Here are some of the pros and cons of snaps in my thoughts.

1. Pro: Snaps are easy to install.

I am pleased to say that this upgrade does seem like a move in the direction of making Ubuntu more accessible to the general public. One simple command in the command line and you can browse through many many snap packages. You can even download and install them from the Ubuntu Software center. I feel more comfortable from the command line with this but whatever floats your boat. Best part is they work right out of the box. No need to run around trying to find and install all the dependencies.

2. Pro: Snaps offer sandboxing.

With security being a large concern these days (yes, even for linux) people are looking to minimize interaction between different components of a system. Isolation of each individual application will help reduce if not entirely prevent security risks. The software packages are initially a read-only filesystem that will include a writable area once it has been installed.

In order for the OS and apps to communicate they must do so in a very well defined and secure policies that are controlled by the user and OS defaults.

3. Con: Not everything is available as snap yet.

This is a problem that will only continue to exist temporarily. If more and more software developers migrate to snap packages then I would expect to see nearly a complete shift away from deb and other types of linux install methods.

There are some popular apps that are now available as a snap package. To name a few there is VLC, LibreOffice, Discord, and Arduino IDE. Give it some time and probably everything will be snaps.

4. Pro: .deb files just done another way. OR IS IT!?

It was initially really hard for me to get excited about snaps. They are really just a new and improved version of deb files. They are self contained (like .deb) but they bundle most of the libraries and runtimes needed (unlike .deb). I am viewing them as .deb 2.0 at this point.

What are your thoughts on snap packages? Here to stay or only as fleeting as people's usage of Internet Explorer?