Okay, maybe not just coder’s block, but I feel like I’ve hit a wall. Every homework assignment I’m given for this class includes a “create your own problem and solve it,” element and for the first two assignments I feel like the topic sort of found me. We can talk about what those two projects were, but let’s first talk about this latest assignment.
I’ve talked about my impending deadlines a lot lately. I also mentioned that I had an experiment that I needed to do to meet a deadline, well it looks like we may or may not meet this goal. Let’s talk about the latest headaches.
Well it’s been an interesting experience. I’ve been working hard to train a binary classifier to predict the two classes in my data. There has been a lot of ups and downs and more importantly, there has been some progress. It isn’t perfect, but it’s a start, so let’s look at what I’ve got so far and where I’m headed.
Well it happened, the date for my qualifying exam has been set. I’m nervous, I’m excited, I’m mostly just anxious to get it done. Quite frankly I’m exhausted, so it will be nice to get one thing off my to-do list. Let’s look at how I need to get ready.
I don’t normally leave my computer on 24 hours a day, but it has been hard a work, so it hasn’t been off in days. Training a model can take some time, as I am finding out and while I’ve made progress on the resulting model, it’s still not where I want it. Let’s talk about what has been going on.
I’ll let you in on a secret, I’ve been doing science outreach on a regular basis for the past 3-4 years now. Specifically with Skype a scientist I’ve volunteered every term since it was pretty much first started. My secret, if not horribly kept, is this… I am ALWAYS nervous to give my talk. That doesn’t mean it isn’t worth it and let me explain why.
There I was patiently waiting for my data to finish being processed, an hour, two, time kept moving as did the little animation letting me know that the algorithm was still doing its thing. Then it was done, I had a new, more complete model and it was glorious… until it wasn’t.
If you’ve read my last post I hinted that today we would discuss filtering. Instead I think I want to take this a different direction. That isn’t to say we won’t go over filtering, we most definitely will. Today I want to cover something else though, significance. So you’ve recorded your signal, took an ensemble average, and now how do we tell if it actually means something, or if you are looking at an artificial or arbitrary separation in your data (IE two separate conditions lead to no difference in your data). Let’s look at significance.*
Noise, it can be troublesome. Whether you are studying and someone is being loud or you are trying to record something, noise is everywhere <stern look at people who talk during movies>. Interestingly enough the concept of noise in a signal recording sense isn’t all too different from dealing with talkative movie goers, so let’s talk noise!*
So you wanna use a spectrogram… but why? What does a spectrogram do that we can’t do using some other methods for signal processing? As it turns out, there is a lot of reasons you may want to use the spectrogram and today we are going to cover some of those reasons and number four may shock you! (okay not really, what do you think this is a clickbait website?)*
Well ten days in and we’ve just introduced the idea of the spectrogram. While a lot of this information is just the broad strokes, I like to think that we’ve covered enough to give you a good idea about how to use these tools and what they are used for. However, we do need to discuss a limitation to the spectrogram, something called the banana of uncertainty, okay not quite the name, but you’ll see why I keep calling it that.*
Last post we introduced a new tool in our arsenal of signal processing analysis, the spectrogram. Without knowing how to read it, it just looks sort of like a colored mess. Don’t get me wrong, it is an interesting looking colored mess, but a mess nonetheless. Well today we are going to talk about how to interpret the plot and why exactly we would ever use this seeming monstrosity.*
To (somewhat) continue with our signal processing theme that we have going on at the moment, over the next few days, let’s look at something called the spectrogram. It’s three dimensions of fun!*
Waves! We’re officially one week through 365 Days of Academia! Woo! 1 week down, 51(.142…) weeks left! Let’s wrap up this weeks theme (there wasn’t originally a theme, but it kind of ended up that way) by talking about other ways we can get to the frequency domain. Specifically, let’s stop the wave puns and let’s talk wavelets!*
Okay, if you’ve been keeping up with these posts, we know about Welch’s method, Thomson’s method, the things that make them different, and the things that make them similar. The thing that both of these transforms rely on is the Fourier transform. What is the Fourier transform? Well, something I probably should have covered first, but whatever this is my blog we do it in whatever order we feel like, so let’s dive in!*
In this digital age, with phones at our fingertips, you would think that access to constant communication would make us feel closer to one another. But a new study shows that may not be the case. In fact, cell phone use might actually lead to feeling less socially connected, depending on your gender or cell phone habits.
Conducted at the BioMag laboratory at the Helsinki University Hospital, a new patient study could open a new opportunity to rehabilitate patients with spinal cord damage. In a new study which two patients with spinal cord injuries received a form of treatment that combined transcranial magnetic stimulation with simultaneous peripheral nerve stimulation given repeatedly for nearly six months.
Tablet and laptop users beware. Using digital platforms such as tablets and laptops for reading may make you more inclined to focus on concrete details rather than interpreting information more abstractly, according to a new study. The findings serve as another wake-up call to how digital media may be affecting our likelihood of using abstract thought.
Happiness. It’s something we all strive for, but how do we measure it — as a country? A global community? Not so surprisingly, researchers are turning to social media to answer these questions and more. In a newly published study, computer scientists used two years of Twitter data to measure users’ life satisfaction, a component of happiness.
As a society we have become incredibly reliant on technology, from spell check to GPS, we are slowly being replaced by computers. Need more proof, a computer can routinely beat us at chess, an AI wrote portions of a book that went on to almost win a writing contest, and if you want scary robotics enter Boston dynamics spot. So the question is, have we outlived our place in the world? Not quite. Welcome to the front line of research in cognitive skills, quantum computers and gaming.
Rustling leaves, a creaking branch: To a mouse, these sensory impressions may, at first, seem harmless — but not if a cat suddenly bursts out of the bush. If so, they were clues of impending life-threatening danger. Researcher Robert Gütig has now found how the brain can link sensory perceptions to events occurring after a delay.