Reservoir Computing from Ohio State

OK, mostly new to me, sounds useful. Following up. 

Scientists Develop the Next Generation of Reservoir Computing

By Ohio State University, September 22, 2021

Researchers have found a way to make reservoir computing, a machine learning approach to processing that requires small training data sets and minimal computing resources, work between 33 and a million times faster than a traditional reservoir computer.

In one test of next-generation reservoir computing, researchers solved a complex computing problem in less than a second on a desktop computer, a task that would otherwise require a supercomputer, says Daniel Gauthier, professor of physics at Ohio State University. "We can perform very complex information processing tasks in a fraction of the time using much less computer resources compared to what reservoir computing can currently do," he says.

The system is described in "Next Generation Reservoir Computing," published in the journal Nature Communications. 

Using an artificial neural network, scientists fed data on a dynamical network into a "reservoir" of randomly connected artificial neurons in a network. The network produces useful output that the scientists can interpret and feed back into the network, building a more and more accurate forecast of how the system will evolve in the future.

From Ohio State University  

The Retail Power of .99?

 A bit of retail knowledge from the research lab at Ohio State. 

This is a very insightful finding. It would be interesting to find out the effect of the price difference (99 cents vs. $1) on volume though.  Xavier Lederer

Ending prices that end in 99 cents  by Al McClain in Retailwire. With further expert comment.   

Retailers might want to rethink doing away with prices that end with “.99” if they believe the results of new research from researchers at The Ohio State University’s Fisher College of Business.  

The study found that setting prices “just below” round numbers (i.e., $19.95, $19.97 or $19.99 instead of $20) can make consumers less likely to spend to upgrade to a more expensive version or size of the product or service.

In a coffee stand experiment done on campus, the researchers changed prices hourly, offering a small coffee for 95 cents, or a larger cup for $1.20. Every other hour they would change the offering to $1 for a small cup or a larger cup for $1.25, so both sizes of coffee cost more. When using the latter pricing scheme, 56 percent of customers upgraded to the larger size, versus 29 percent who did so with the first pricing scheme.

The researchers concluded that while the just-below price makes a product seem like a bargain, it also makes the step up to the premium product seem too expensive.   ... ' 

Microphone Signature Tracking of Covid Exposure

Interesting approach,  with approval of the phone owner I assume, they could the release of such 'random tokens', and another phone within some radius, would pick it up.  Producing a map trace of exposure.  To be analyzed on a secure, trusted database.  Assuming that a significant number of people would approve.

Using Your Phone's Microphone to Track Possible Covid-19 Exposure
Ohio State News
Laura Arenschield
June 30, 2020

Researchers at The Ohio State University (OSU) have proposed a Covid-19 tracking system that would rely on signals sent and received from cellphone microphones and speakers. The system would generate random, anonymous IDs for each phone and automatically send ultrasonic signals between the microphones and speakers of phones within a certain radius. A person who has tested positive for Covid-19 would update their anonymous IDs and the timestamp when the IDs were generated in the past two weeks to a central database managed by a trusted health care authority. The data would be used for contact tracing. Said OSU's Dong Xuan, "The phone will periodically generate some kind of sound token and send that token to nearby phones—and the key advantage over other technologies is that the ultrasound could have limited range and will not penetrate obstacles such as walls."... ' 

Sharing with a Core Scientific Data Model

With data getting more complex, and havig to include many aspects of context-specific metadata, sharing it efficiently can be messy.  In our experience the integration of needed metadata can be problematic.

Simplifying How Scientists Share Data    By Ohio State News

Their system is designed to share complex datasets easily, without massive files, and without losing metadata.   Researchers have created a new open-source data-management system for scientists, in the hope the system might make collaboration easier.

Researchers at The Ohio State University, Denmark's University of Aarhus, and France's University of Orléans have developed an open-source data-management system that will help scientists share data with each other.

The system, called the "Core Scientific Data Model," is designed to share complex datasets easily, without massive files that take up a lot of bandwidth and hard drive space, and without losing metadata.

The researchers built the software, uploaded it to the web, and made the code open-source, with the goal of creating a simple, free way to combine multiple types of data into one place.

Said Ohio State researcher Deepansh Srivastava, "Instead of looking for data and plucking it from datasets, if we could simply export it as this one file type – as a core scientific data file type – we'd be able to work in a common system."

From Ohio State News