![]() ![]() So if we go and look here, I have my little sphere. And here's just one little thing that I wanted to show before I get into my other thing that I found out, that I don't know if it's working as intended or if it's just something that got snuck in. It's a renderer that I use on a daily basis. And it's really powerful, it scales really well with Cinema, and the bridge between Octane and Cinema is the nicest that I've used. It basically uses all those CUDA cores that otherwise go unused unless you're playing a video game to render things super, super fast. And if you guys aren't familiar with Octane, it's a render engine that runs off of NVidia GPUs. And this is going to bring me into the Octane renderer, standard-or nodal texturing workflow. And I'm going to select this material and hit get active matte. Let's go up here to objects, node editor. Oh, that's the Arnold Shader network, sorry. ![]() And one of the things is the Octane-I'm going to hit shift-C really quick and open up the network. Okay, so my Octane piece that I'm going to be talking about right now is just something that I kind of have hodgepodged together from working with a few other artists that use Octane, and some stuff that I figured out on my own. I'm going to do a few different things, a lot of it's going to be X-Particles-based, with a little bit of TurbulenceFD. So yeah, let's go ahead and get into some presentation stuff. ” But this isn't LA guys this is downtown. And I'm so happy every time Cigraph is in this town, because it brings a lot of the creatives from outside of LA to LA, and we get to meet and mingle and stuff and they get to tell us, “oh, LA sucks. I live here in Los Angeles, the city that never sleeps. ♪ ♪ Yay! Thank you so much Adam, I love my new reel. So, let's go ahead and watch my reel so you can see some of the junk that I've worked on. ![]() I finally have a reel that's 60 seconds and looks like an editor did it and it doesn't have weird, off musical edits that I normally have and I'm super happy to have it. You guys want to see some of my work? A bud of mine, Adam Elder, just cut this reel for me and we're going to watch it together guys. Like following Cantina's ridiculous.like their work is so impressive. ![]() I am always filled with a great sense of pride to be considered worthy of presenting next to all these people that have done, rightly so, more than I could possibly imagine doing. This work demonstrates how AI-based methods can leverage bioaerosol monitoring into predictive scenarios that building operators can use for improving indoor environmental quality in near real-time.- Hey! Thanks again to Maxon for letting me come out to another one of these. A long short-term memory model required a relatively short training time and gave the highest prediction accuracy of ∼ 60 %–80 % for bioaerosols and ∼ 90 % for PM on the testing and time series datasets from the two venues. Seven AI models were developed and evaluated using measured data from an occupied commercial office and a shopping mall. This enabled us to effectively estimate the bioaerosol (bacteria-, fungi- and pollen-like particle) and 2.5-µm and 10-µm particulate matter (PM 2.5 and PM 10) on a real-time and near-future (≤60 min) basis. In this study, we developed artificial intelligence (AI) models using physical and chemical data from indoor air quality sensors and physical data from ultraviolet light-induced fluorescence observations of bioaerosols. However, it remains challenging to monitor and determine real-time or predict near-future concentrations of airborne biological matter. Exposure to bioaerosols in indoor environments, especially public venues that have a high occupancy and poor ventilation, is a serious public health concern. ![]()
0 Comments
Leave a Reply. |