Aesthetics. Les flux d’images de 4chan. Plusieurs articles sur 4chan parus récemment ont donné lieu à des discussions sur la nature et l’intérêt de cet ensemble d’imageboards. Le présent billet s’intéresse uniquement à la circulation des images depuis et vers 4chan, c’est-à-dire à l’origine de ces images (flux entrant) et où vont ces images après avoir transité par 4chan (flux sortant). Je ne parlerai donc pas des contenus textuels de la plate-forme et me garderai bien de donner un avis quelconque sur la qualité des productions que l’on y trouve. De surcroît, même en limitant ainsi mon sujet aux images, je ne prétends pas ici apporter quelque chose de vraiment nouveau aux débats en cours. Mon objectif est simplement de montrer à l’aide d’outil publics simples à mettre en œuvre que 4chan n’est pas le fondement (je reste poli) du Web que l’on a pu décrire, mais qu’il doit plutôt être considéré comme un espace actif où circulent et se transforment rapidement certaines productions iconographiques d’un Web plus “habituel”.
Pattern-recognition. Amorçage. Mathematics. Neural Networks. Ralf baecker | RECHNENDER RAUM. The inverted machine – Rechnender Raum (Computing Space) is a light-weight sculpture, constructed from sticks, strings and little plumbs. At the same time it is a full functional logic exact neural network (*). Through its strict geometric and otherwise very filigree construction, the observer is able to track the whole processing logic from every viewpoint around the machine.
This disclosure of the machines core is enforced by an uncommon distribution of its constructing elements: a nine angled architectural body forms a torus. In contrast to an ordinary alignment of a hidden logic and an outer user facing display its geometric basis is turned inside-out. The core of the machine, with all its computing elements, is shifted outwards on the surface, while the “display” which indicates the results of the tasks is displaced into the center of the system. (*) RR units operate similar to a very basic artifical neural network.
TechFest 2008: Real Time Rendering of Smoke Animation | Tina Woo. One would think that Real Time Rendering of Smoke Animation in this technological era would be a cake walk. Well, it isn't and here's why: Rendering of smoke presents a challenging problem in computer graphics because of its complicated effects on light propagation. Within a smoke volume, light undergoes absorption and scattering interactions that vary from point to point because of the spatial non-uniformity of smoke. In static participating media, the number and the complexity of scattering interactions lead to a substantial expense in computation. Casual Gameplay. Gamescape. Create a city while playing the game! Gamescape visualizes all playing movements as a 3D-sculpture and all movements of all players as an entire city.
Gamescape is an extension to the retro-game «l1neum» by «la1n». It is visualizing all playing movements of a player as a 3D-sculpture. While as the movements of one player make up a sculpture, all sculptures of all played games of all players are collected on a server and form an entire city: A city consisting of structures which are created by all the gamers' movements. This visualization of structures shows an ever-expanding universe of movements – finished and unfinished – and serves as a starting ground for a new game. The different shapes of the buildings can be related to the strategies of the individual players.
Finally the gamescapes can be easyly exported into 3d-software for further use. By playing the different levels of «l1neum», the player creates more and more buildings for the ever growing gamescape-city. Audio Kinematics. Guide to Getting Started in Machine Learning. Someone at work recently asked how he should go about studying machine learning on his own. So I’m putting together a little guide. This post will be a living document…I’ll keep adding to it, so please suggest additions and make comments. Fortunately, there’s a ton of great resources that are free and on the web. The very best way to get started that I can think of is to read chapter one of The Elements of Statistical Learning: Data Mining, Inference, and Prediction (2009 edition). The pdf is available online. Or buy the book on Amazon here, if you prefer. Once you’ve read the first chapter, download R.
Once you’ve installed R, maybe played around a little, then check out this page which describes the major machine learning packages in R. Oh, by the way, if you want to start playing around with machine learning in R, you’ll need data. I’d suggest next reading more of The Elements of Statistical Learning. I’ll stop here now.
Neuralnet 1. An On-Line Biology Book. How To Tell Stuff To A Computer - The Enigmatic Art of Knowledge. Imprimante 3D. Extreme Programming. RB Whitaker's Wiki: Welcome. Welcome to this website! This started out as a temporary location for my tutorials and projects, which has become quite popular, and as a result, fairly permanent. As long as Wikidot keeps cooperating with me, I'm planning on staying here. This site is designed as a place to help you get going with game development (or just software development in general) and provides you with tons of free amazing tutorials, software, and resources for you to use.
Take a look at my XNA Tutorials as well as my MonoGame Tutorials, and my Realm Factory program, which is a basic (free) level editor for XNA. Or see what other people are saying in the Forum. 9 December 2020 Can't believe it has been 11 months since I posted an update. 11 January 2020 BasicEffect fog tutorial for MonoGame has now been created, ported from the XNA version. This leaves one big tutorial in the 2D set and one big tutorial in the 3D set un-ported, but everything else in the first five MonoGame tutorial sets has now been ported! Untitled. Software for Social Network Analysis & Organizational Network Analysis If a picture is worth a thousand words, what is an interactive model of your organization, community, or industry worth? InFlow 3.1 performs network analysis AND network visualization in one integrated product -- no passing files back and forth between different programs like other tools.
What is mapped in one window is measured in the other window -- what you see, is what you measure. InFlow excels at what-if analysis -- change the network, get new metrics -- just 2 clicks of the mouse. InFlow is designed to work with Microsoft Office and the WWW. You do not need to be an expert in statistics to use InFlow.
InFlow is the only popular SNA/ONA software that has available training and personal mentoring through your first project(s). Contact us for more information on purchasing InFlow and training on how to do social & organizational network analysis. InFlow provides easy access to the most popular network metrics. Intelligence collective. Histoire.