Tootfinder

"Come to mind the names of violent battles: DR-DOS, Taligent, AmigaOS, Newton OS, Windows for Pen Computing, Copland, Vino, NeXTSTEP, Novell NetWare, JavaOS, BeOS, DoJ vs Microsoft, Rhapsody, POSIX, Linux is communism, Linux is a cancer, Samizdat, Windows Vista, SCO, Symbian, Solaris, OpenSolaris, systemd, Windows Phone, MeeGo, Tizen, Firefox OS, Sailfish OS. Countless mythical man-month hours were lost. Millions of lines of code were fired."

#Queen confusing me by playing the intro to Arnold Layne again. #QueenTheLegendary1975Concert
I think this is the concert I used to use footage from in the seminar where I got my students to make one-note clarinets from cordial bottles and try and match a particular chord in Bohemian Rhapsod…

Early Detection of Furniture-Infesting Wood-Boring Beetles Using CNN-LSTM Networks and MFCC-Based Acoustic Features
J. M. Chan Sri Manukalpa, H. S. Bopage, W. A. M. Jayawardena, P. K. P. G. Panduwawala
https://arxiv.org/abs/2507.12793

Early Detection of Furniture-Infesting Wood-Boring Beetles Using CNN-LSTM Networks and MFCC-Based Acoustic Features
Structural pests, such as termites, pose a serious threat to wooden buildings, resulting in significant economic losses due to their hidden and progressive damage. Traditional detection methods, such as visual inspections and chemical treatments, are invasive, labor intensive, and ineffective for early stage infestations. To bridge this gap, this study proposes a non invasive deep learning based acoustic classification framework for early termite detection. We aim to develop a robust, scalable …