New account since lemmyrs.org went down, other @Deebsters are available.

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Joined 2 years ago
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Cake day: October 16th, 2023

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  • There’s no algorithm here, so use the different sorting options (for both posts and comments), as well as setting your favourite as default once you see what works for you.

    Voting doesn’t tune your algorithm, so I’d say only use downvoting for things that are low quality, trolling, in the wrong sub, duplicate posts, etc. Your votes aren’t private, by the way - although Lemmy itself doesn’t display voters’ names, that info is in every server’s database, and some other software in the Fediverse does show them.

    There are quite a few apps available, I like Voyager on Android and I stick to the default website on my computer.





  • DeebstertoLinux@lemmy.mlGetting used to Helix
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    15 days ago

    Not quite what you were asking for, but there is https://tomgroenwoldt.github.io/helix-shortcut-quiz/

    It’s quite good for letting you know about things you didn’t know you could do, but sometimes it tells me I’m wrong because I’d do it a different way - e.g. I’d go to line 13 by :13 but it wants 13G.

    Also, from within helix you can do space ? to get the list of commands and any bindings they’re on.

    edit: also, FYI Helix and similar are modal, not modular (although there is a plugin system on the way).





  • The latest Kindle update broke the jailbreak even if it was installed, so you’ll need to stop updates. You could just leave it in airplane mode, but not being able to use the internet to pull down books from your Calibre-web server means you may as well just send books via Calibre.

    I’m planning on getting a Kobo Clara BW when my Kindle dies (it’s currently got holes at the corners and a few dodgy-sounding rattles so soon™). Then I can use Koreader+Calibre-web to download books and sync read state like you can do with Amazon.

    So your process here is get comics -> comictagger -> upload to server and kavita, correct?

    Pretty much, apart from that I often add them and only fix if necessary, e.g. they’re not going into series properly.




  • Ebooks: I use Calibre locally and Calibre-web on the server (read-only metadata db, I overwrite with the Calibre version as tagging, etc is far easier on desktop).

    You can connect Koreader to Calibre-web and until maybe a fortnight ago you could jailbreak a Kindle and use Koreader instead of the default software. Now you’ll need to manually move files over, or use the email-to-Kindle option (probably a bad idea, but I expect Amazon can tell if you’ve side loaded pirated content anyway). Nowadays I buy from not-Amazon sources, strip any DRM and send it over.

    Manga/comics/graphic novels: I use Kavita on the server and I use comictagger on desktop to fix the metadata.

    I’m happy to use different set ups for the different types as they’re quite different experiences and specialist tools work better.



  • DeebstertoTechnology@lemmy.world*Permanently Deleted*
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    20 days ago

    I found his paper: https://iopscience.iop.org/article/10.3847/1538-3881/ad7fe6 (no paywall 😃)

    From the intro:

    VARnet leverages a one-dimensional wavelet decomposition in order to minimize the impact of spurious data on the analysis, and a novel modification to the discrete Fourier transform (DFT) to quickly detect periodicity and extract features of the time series. VARnet integrates these analyses into a type prediction for the source by leveraging machine learning, primarily CNN.

    They start with some good old fashioned signal processing, before feeding the result into a neutral net. The NN was trained on synthetic data.

    FC = Fully Connected layer, so they’re mixing FC with mostly convolutional layers in their NN. I haven’t read the whole paper, I’m happy to be corrected.