Arcade Games Linux

 

Snes9x

sudo apt install flatpak
flatpak remote-add --if-not-exists flathub https://flathub.org/repo/flathub.flatpakrepo

flatpak install flathub com.snes9x.Snes9x 

ZSNES is a Super Nintendo Emulator that can run on Windows, Linux, FreeBSD, and DOS. It runs as a GUI interface where you can load ROM of NES games.

sudo apt install zsnes

higan is an emulator for Nintendos SNES, NES, Gameboy, Gameboy Color, and Gameboy Advance. It was formerly called bsnes and the SNES emulation is especially complete and polished.

sudo apt install higan 

 

References:

https://www.debugpoint.com/3-nes-emulators-to-play-old-nes-games-in-linux/

 

Graph tools

 

𝐓𝐨𝐨𝐥𝐬 𝐭𝐨 𝐦𝐚𝐢𝐧𝐥𝐲 𝐯𝐢𝐬𝐮𝐚𝐥𝐢𝐳𝐞 𝐧𝐞𝐭𝐰𝐨𝐫𝐤𝐬:
- Geph - https://gephi.org
- Gephisto- https://lnkd.in/diSp3BWN
- VOSviewer - https://www.vosviewer.com
- Cytoscape - https://cytoscape.org
- Kumu - https://kumu.io
- GraphInsight - https://lnkd.in/d5XnkWJr
- NodeXL - https://nodexl.com
- Orange - https://lnkd.in/dZU8Zx3D
- Graphia - https://graphia.app
- Graphistry - https://www.graphistry.com
- SocNetV - https://socnetv.org
- Tulip - https://lnkd.in/dtc_BD33


𝐍𝐞𝐭𝐰𝐨𝐫𝐤 𝐥𝐢𝐛𝐫𝐚𝐫𝐢𝐞𝐬 𝐢𝐧 𝐏𝐲𝐭𝐡𝐨𝐧:
- networkx - https://lnkd.in/dKCCXjif
- graphviz - https://lnkd.in/dtrTeqRv
- pydot - https://lnkd.in/dA46YZvy
- python-igraph - https://lnkd.in/dCGsRXh2
- pyvis - https://lnkd.in/dVrQ64nN
- ipycytoscape - https://lnkd.in/d-hJjDdG
- pygsp - https://lnkd.in/dS7s-A_v
- graph-tool - https://lnkd.in/dvytUzdu
- nxviz - https://lnkd.in/duHbKGPN
- py2cytoscape - https://lnkd.in/dWUU8TZH
- ipydagred3 - https://lnkd.in/diXgFWMD
- ipysigma - https://lnkd.in/dP55J5et
- Py3Plex - https://lnkd.in/dhwe7f_g
- net wulf - https://lnkd.in/dxrHAm2P
 

Render tools - POV Ray

Compiling

https://github.com/POV-Ray/povray/releases/tag/v3.8.0-beta.2 

configure error: Could not link against boost_

sudo apt-get install libboost-all-dev

Update Gimp

From 2.8 to 2.10 using apt-get

$ sudo add-apt-repository ppa:otto-kesselgulasch/gimp

$ sudo apt-get update

$ sudo apt-get install gimp

 

References:

https://linuxhint.com/install_gimp_210_ubuntu_1804/

ASNetwork : Breaking ambiguity

 

 

[1] Salient Object Detection Driven by Fixation Prediction https://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Salient_Object_Detection_CVPR_2018_paper.pdf

[2] Action Schema Networks https://ipc2023-learning.github.io/abstracts/asnets.pdf

Volume Fractions

Thesis

[1] Smooth Interface Reconstruction from Volume Fraction Data Using Variational
Techniques and Level Set Methods

https://escholarship.org/content/qt2466j56f/qt2466j56f_noSplash_4c9dcb1c6cacafb1bcdc4a7bab220630.pdf?t=odypru

 

Volume Fractions in Rectangular Grids

Analytical Relations Connecting Linear Interfaces and Volume Fractions in Rectangular Grids
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.536.848&rep=rep1&type=pdf
[1] Markers - A front-tracking algorithm for accurate representation of surface tension (Zaleski)
https://hal.archives-ouvertes.fr/hal-01445441/document



[2] Level Set Methods (LSM)
[2.1] Tutorial Level Set vs Marching Methods https://math.berkeley.edu/~sethian/2006/Explanations/level_set_explain.html

[2.2-1] Part I (Def) https://wiseodd.github.io/techblog/2016/11/05/levelset-method/
[2.2-2] Part II(Application for segmentation) https://wiseodd.github.io/techblog/2016/11/20/levelset-segmentation/

Deep Gan Applications

Super Resolution

[0] https://replicate.com/collections/super-resolution 

[1] https://replicate.com/nightmareai/real-esrgan  /require github account

[2] https://replicate.com/mv-lab/swin2sr (alternative) 

[3] Nightmare https://www.nightmare-ai.com/playground

Styles

[1] https://replicate.com/collections/ml-makeovers 

Restoration

[1] 5byday https://www.restorephotos.io/restore  (based on replicate)

[2] https://replicate.com/collections/image-restoration

[3] https://replicate.com/microsoft/bringing-old-photos-back-to-life

Frequence space ( Source codes )

References:

[1] Elliptic Harmonics http://www.cs.utah.edu/~jfishbau/advimproc/project3/



Resources:
 0) Discrete Fourier Transform 1D, source code c/c++/java/python and more https://www.nayuki.io/page/how-to-implement-the-discrete-fourier-transform
1) Discret Sine Tranform  https://people.sc.fsu.edu/~jburkardt/cpp_src/sine_transform/sine_transform.html
  1.1) Python version http://www-personal.umich.edu/~mejn/computational-physics/dcst.py

2) Haar Wavelet compression https://people.math.osu.edu/husen.1/teaching/wi2010/572/572.html

3) Fast Fourier Tranform 1d/2d http://www.kurims.kyoto-u.ac.jp/~ooura/fft.html
4) Elliptic Fourier Transform source code python https://github.com/hbldh/pyefd
5) Spatial Elliptical Fourier Descriptors python https://spatial-efd.readthedocs.io/en/latest/raster_link.html 

6) Morphometric in R https://github.com/MomX/Momocs/

Visual Computing

 

 

[1] Definition https://link.springer.com/content/pdf/10.1007/978-3-642-85023-3_1.pdf

Web Screen-Space methods for fluid rendering

 

[1] https://www.babylonjs.com/

Writing

[1]  Writing and Publishing Scientific Papers Image de couverture Series https://books.openbookpublishers.com/10.11647/obp.0235.pdf

AI Surfaces

 

[1] https://dsilvavinicius.github.io/nise/

Geo DataScience

Datasets

[1] Flood Mapping https://ieee-dataport.org/competitions/2024-ieee-grss-data-fusion-contest-flood-rapid-mapping

 

[1] datos https://www.datosabiertos.gob.pe/

[2] lat/long Perú https://github.com/jmcastagnetto/ubigeo-peru-aumentado

[3] variables vivienda y conocimiento https://www.redalyc.org/journal/6357/635767693004/html/

CONCLUSIONES

El conocimiento sobre dengue, las viviendas que presentan depósitos de basura y agua acumulada están relacionadas a los casos de Dengue en los distritos de Luyando y Rupa Rupa, en la provincia de Leoncio Prado. Persisten conductas de riesgo a pesar del adecuado conocimiento sobre la enfermedad. No se encontró asociación con el tipo de vivienda, género, material predominante en las viviendas, tipo de abastecimiento de agua y servicios higiénicos.

 

[4] datos amazonia https://www.dge.gob.pe/sala-situacional-dengue/#grafico27

[5] Mapas Perú .shp https://www.geogpsperu.com/2014/03/base-de-datos-peru-shapefile-shp-minam.html

[6] Información Geoespacial Perú https://www.idep.gob.pe/geovisor/descarga/visor.html

[6] Hidrografía https://data.humdata.org/dataset/hidrografia-de-peru?

   https://data.humdata.org/dataset

[7] Áreas  naturales protegidas https://geo.sernanp.gob.pe/visorsernanp/

[8] Biomasa Brasil https://mapbiomas.org/download

Processing 

[1] plotting maps https://ggplot2-book.org/maps.html

[1.1] https://community.rstudio.com/t/geom-label-with-custom-background-and-color-text/45161

[2] poly2nb https://www.rdocumentation.org/packages/spdep/versions/1.2-8/topics/poly2nb

[3] Indicadores demograficos Perú (teoria) https://www.inei.gob.pe/media/MenuRecursivo/publicaciones_digitales/Est/Lib1743/Libro.pdf

R Installation and more

 

* R installation




$sudo apt install r-base

 

* Package installation

install.packages('readr')

 

* install.packages('sf')

//Configuration failed because libudunits2.so was not found


sudo add-apt-repository ppa:ubuntugis/ubuntugis-unstable
sudo apt-get update
sudo apt-get install libudunits2-dev libgdal-dev libgeos-dev libproj-dev 

* install.packages('dplyr') //dataframe, works with R version >= 3.5

* install.packages('tidyverse') //Contains other packages (dplyr, ggplot2, etc.)  

* install.packages('spdep') //Spatial Dependence: Weighting Schemes, Statistics. A collection of functions to create spatial weights matrix objects from polygon

* install.packages('GGally') //extends 'ggplot2'

 

* install.packages('leaflet') //makes it easy to integrate and control Leaflet maps in R.

* install.packages('coda')

 

* install.packages('CARBayes')

* install.packages('CARBayesdata') 

 

* install.packages('xlsx')  

 

    dependences:

      1) java

      2) sudo apt-get install openjdk-11-jdk

      3) sudo R CMD javareconf    

      4) https://github.com/PCRE2Project/pcre2/releases  

      4.1) compilation https://www.appsloveworld.com/r/100/371/how-to-solve-lpcre2-8-error-while-installing-rjava-package-in-r


* install.packages('readxl')

 

* install.packages('tmap')


 

 

 

References:

[1] rstudio https://linuxconfig.org/rstudio-on-ubuntu-18-04-bionic-beaver-linux

[2] R 3.5 installation on Linux 18 https://rtask.thinkr.fr/installation-of-r-3-5-on-ubuntu-18-04-lts-and-tips-for-spatial-packages

[2] rstudio previous https://docs.posit.co/previous-versions/rstudio/

Latex writing

Highlighting code

[1] Custom C https://tex.stackexchange.com/questions/312789/lstdefinelanguage-cannot-handle-keywords-if-endif

Multi references

\bibliography{paper,references2019}

Soundscape works

 

[1] A pipeline for identification of bird and frog species in tropical soundscape recordings using a convolutional neural network

https://www.sciencedirect.com/science/article/pii/S1574954120300637?via%3Dihub

[2] https://www.frontiersin.org/articles/10.3389/fevo.2021.738537/full

Backtesting

 

[1] popular code https://github.com/kernc/backtesting.py/tree/master/backtesting

[2] https://blog.devgenius.io/algorithmic-trading-backtesting-a-strategy-in-python-3a136be16ece

[3]  https://towardsdatascience.com/backtest-your-trading-strategy-with-only-3-lines-of-python-3859b4a4ab44

Python Genetic Algorithms

 

[1] pyGAD https://github.com/ahmedfgad/GeneticAlgorithmPython

Transformers in Computer Vision

 

[1] Review https://sh-tsang.medium.com/review-vision-transformer-vit-406568603de0

[2] Colab ViT Tutorial https://colab.research.google.com/github/hirotomusiker/schwert_colab_data_storage/blob/master/notebook/Vision_Transformer_Tutorial.ipynb

[3] ViT pytorch https://github.com/lucidrains/vit-pytorch

[4] Vit Keras https://wandb.ai/ayush-thakur/keras_cv_vit/reports/Image-Classification-Using-Vision-Transformer-and-KerasCV--VmlldzozNTE4MzMz

[5] Fine tunning https://huggingface.co/blog/fine-tune-vit

[6] Full material https://github.com/cmhungsteve/Awesome-Transformer-Attention

Watercolor tips

 

Material

[1] https://www.nicoletalle.com/como-elegir-el-mejor-set-de-acuarelas/

Paper

[1] ...