Artist Manipulates 48 Pools Of Water With Her Mind by Beckett Mufson “Brain power” takes on a literal meaning when it comes to EEG painting, mind-responsive furniture, and the workof Lisa Park. Park combines EEG scanning with speakers and pools of water to visualize her thoughts andemotions. Last year, she exposed her brain patterns to the world with Eunoia, in which she placed five water-filled metal plates atop speakers designed to respond to her real-time brain data.
FlowStone FlowStone uses a combination of graphical and text based programming. Applications are programmed by linking together functional building blocks called components. Events and data then flow between the links as the application executes. Quantified Self Early prototype of "Quantimetric Self-Sensing" apparatus, 1996 (body sensing apparatus with Digital Eye Glass for realtime display of ECG, EEG, EVG, and other body sensing apparatus output[1]). The above-pictured "Quantimetric Self-Sensing" apparatus when removed from the body harness: Left-to-right: Respiration Sensor; ECG; EEG; Skin Conductivity; EVG (ElectroVisuoGram=Quantimetric EyeTap).[2] The Quantified Self[3] is a movement to incorporate technology into data acquisition on aspects of a person's daily life in terms of inputs (e.g. food consumed, quality of surrounding air), states (e.g. mood, arousal, blood oxygen levels), and performance (mental and physical). Such self-monitoring and self-sensing, which combines wearable sensors (EEG, ECG, video, etc.) and wearable computing, is also known as lifelogging.
E-Traces: Ballet Slippers That Make Drawings From The Dancer’s Movements If you’re like me, then you may have been accused of dispensing some questionable moves in the vicinity of the dance floor. I’ve always maintained that my critics simply couldn’t grasp the subtlety of my particular style of physical expression, and now I just may have a means of illustrating my point with an ingenious piece of wearable electronics by designer Lesia Trubat González called E-Traces. The concept of Electronic Traces is based on capturing dance movements and transforming them into visual sensations through the use of new technologies.
Eureqa Eureqa is a breakthrough technology that uncovers the intrinsic relationships hidden within complex data. Traditional machine learning techniques like neural networks and regression trees are capable tools for prediction, but become impractical when "solving the problem" involves understanding how you arrive at the answer. Eureqa uses a breakthrough machine learning technique called Symbolic Regression to unravel the intrinsic relationships in data and explain them as simple math. Using Symbolic Regression, Eureqa can create incredibly accurate predictions that are easily explained and shared with others.
NASA Posts a Huge Library of Space Sounds, And You're Free To Use Them Space is the place. Again. And SoundCloud is now a place you can find sounds from the US government space agency, NASA. In addition to the requisite vocal clips (“Houston, we’ve had a problem” and “The Eagle has landed”), you get a lot more.
Data Mining Image: Detail of sliced visualization of thirty video samples of Downfall remixes. See actual visualization below. As part of my post doctoral research for The Department of Information Science and Media Studies at the University of Bergen, Norway, I am using cultural analytics techniques to analyze YouTube video remixes.
Visualizing Our Tech Worship With Giant Webs of Circuitry Technological mandala 20 - Resonator, 2014. Leonardo Ulian <div class="slide" data-slide-id="1579293" ><img title="" alt="" width="650px" src=" data-image-width="1200" data-image-height="900" /><p class="caption">Technological mandala 20 - Resonator, 2014.<span class="credit"><img class="photo" width="650px" src=" Leonardo Ulian </span></p><div class="desc"><div class="slide-counter"></div><div>Technological mandala 20 - Resonator, 2014. For Italian artist Leonardo Ulian, this is our universe. At its center: a microchip. 5 of the Best Free and Open Source Data Mining Software The process of extracting patterns from data is called data mining. It is recognized as an essential tool by modern business since it is able to convert data into business intelligence thus giving an informational edge. At present, it is widely used in profiling practices, like surveillance, marketing, scientific discovery, and fraud detection. There are four kinds of tasks that are normally involve in Data mining: * Classification - the task of generalizing familiar structure to employ to new data* Clustering - the task of finding groups and structures in the data that are in some way or another the same, without using noted structures in the data.* Association rule learning - Looks for relationships between variables.* Regression - Aims to find a function that models the data with the slightest error.