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Catch Bugs Before Your Customers DoMove from alert to fix before users notice. AppSignal monitors errors, performance bottlenecks, host health, and uptime—all from one dashboard. Instant notifications on deployments, anomaly triggers for memory spikes or error surges, and seamless log management. Works out of the box with Rails, Django, Express, Phoenix, Next.js, and dozens more. Starts at $23/month with no hidden fees.
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...Functions are organised as modules in framework independent Module Libraries and can be accessed via SAGA’s Graphical User Interface (GUI) or various scripting environments (shell scripts, Python, R, ...). Please provide the following reference in your work if you are using SAGA: Conrad, O., Bechtel, B., Bock, M., Dietrich, H., Fischer, E., Gerlitz, L., Wehberg, J., Wichmann, V., and Boehner, J. (2015): System for Automated Geoscientific Analyses (SAGA) v. 2.1.4. Geosci. Model Dev., 8, 1991-2007, https://doi.org/10.5194/gmd-8-1991-2015. For more information visit the project homepage and the wiki.
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Euler Pole Calculator (EPC)
A Matlab software to estimate Euler pole parameters
...Since version 2, the software is able to estimate or apply the Plate Translation Rates, as well. Please cite one of the following papers when you use the software: - Goudarzi, M A, Cocard, M, and Santerre, R. 2014."EPC: Matlab Software to Estimate Euler Pole Parameters". GPS Solutions 18 (1): 153–62. DOI: 10.1007/s10291-013-0354-4*. - Goudarzi, M A. 2025."Evaluating Euler Pole Parameters for the North American Terrestrial Reference Frame of 2022". Geodesy and Geodynamics. DOI: 10.1016/j.geog.2025.03.004... -
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Scalar-Defense-System
Scalar Defense using Photon Dark Photon FDM Waves
Scalar Defense leverages wave-like properties of Fuzzy Dark Matter to detect, track & deflect asteroids. Manipulating scalar fields (ϕ) & their interference patterns, system creates controlled gravitational potentials can alter asteroid trajectories. Foundation is the two-field FDM model, allows tuning density fringes via mass & velocity parameters -
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DeepSee
Visualize deep ocean biogeochemical sediment samples in 2D and 3D!
...🦑🦀🐚 🚀 For a live demo, visit: https://www.its.caltech.edu/~datavis/deepsee/ 🌱 To get started, visit our Wiki: https://sourceforge.net/p/deepsee/wiki/Home/ 🧑💻 To modify DeepSee for your own project, visit our GitHub repository: https://github.com/orphanlab/DeepSee/ --- Created by Adam Coscia, Haley M. Sapers, Noah Deutsch, Malika Khurana, John S. Magyar, Sergio A. Parra, Daniel R. Utter, Rebecca L. Wipfler, David W. Caress, Eric J. Martin, Jennifer B. Paduan, Maggie Hendrie, Santiago Lombeyda, Hillary Mushkin, Alex Endert, Scott Davidoff, and Victoria J. Orphan. Copyright (c) 2022-23 California Institute of Technology ("Caltech"). ... -
AI-generated apps that pass security reviewRetool lets you generate dashboards, admin panels, and workflows directly on your data. Type something like “Build me a revenue dashboard on my Stripe data” and get a working app with security, permissions, and compliance built in from day one. Whether on our cloud or self-hosted, create the internal software your team needs without compromising enterprise standards or control.
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i-Blue 747 / i-Blue 757 / Qstarz BT-Q1000 / i.Trek Z1 / Konet BGL-32 / Holux M-241 / ... control SW (for Java Phones, PalmOS, WinCe (PPC), Java platforms, Windows, Linux, and MacOS). Compatible with most MTK GPS Chipset based loggers.
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SPAWNN
SPatial Analysis With self-organizing Neural Networks
The SPAWNN toolkit is an innovative toolkit for spatial analysis with self-organizing neural networks which is particularily useful for spatial analysis, visualization and geographical data mining. To run the toolkit, simply download and execute (double-click) the jar-file. Please cite: - Hagenauer, J., & Helbich, M. (2016). SPAWNN: A Toolkit for SPatial Analysis With Self-Organizing Neural Networks. Transactions in GIS, 20(5), 755-775. Other related publications: - Hagenauer, J. (2016). Weighted merge context for clustering and quantizing spatial data with self-organizing neural networks. Journal of Geographical Systems, 18(1), 1-15. - Hagenauer, J., & Helbich, M. (2013). ...
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