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Northeastern University Institute for Experiential AI
 
Welcome to the October 21, 2019 edition of ACM TechNews, providing timely information for IT professionals three times a week.

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Artificial Skin Creates First Ticklish Devices
University of Bristol News
October 20, 2019


Researchers at the University of Bristol in the U.K. and France's Telecomm ParisTech and Sorbonne University have developed an artificial skin-like interface that can be used to augment devices like phones, wearables, and computers. The Skin-On interface is based on a silicone membrane that emulates the layers in human skin, including a surface textured layer, a conductive electrode layer, and a hypodermis layer. Skin-On allows devices to "feel" the pressure and location of the user's grip, as well as interactions like tickling, caressing, twisting, and pinching. The researchers devised a phone case, computer touch pad, and smart watch to show how touch gestures on Skin-On can provide the ability to communicate expressively in computer-mediated exchanges with humans or virtual characters. Bristol's Anne Roudaut said, "We have seen many works trying to augment human with parts of machines, here we look at the other way around and try to make the devices we use every day more like us."

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Two people standing side by side in protective suits Computer Model Predicts Where Ebola Might Strike Next
The Verge
Justine Calma
October 15, 2019


University of Washington researchers have developed a computer model that tracks how changes in the environment and in human societies could affect the spread of the Ebola virus. The model predicts that Ebola outbreaks could become as much as 60% more likely by 2070 if the world continues on a path toward a warmer climate and a slowing economy. The model could be used to determine where to vaccinate people before an outbreak, and could also allow a government to take measures at borders where sick travelers might spread the disease. The researchers think the model also could be modified to address other diseases.

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Tool Gives Researchers Better Look at Online Anonymous Marketplaces
Carnegie Mellon University CyLab Security and Privacy Institute
Daniel Tkacik
October 18, 2019


Researchers at the Carnegie Mellon University CyLab Security and Privacy Institute have developed an algorithm that detects when seemingly disparate accounts on anonymous online marketplaces belong to the same seller. The algorithm analyzed eight years' worth of data compiled from 12 marketplaces, detecting more than 20,000 accounts belonging to approximately 15,000 individual sellers, with some operating between two and 11 accounts. The algorithm derived and compared account data, and accounts with similar properties above a certain threshold were matched to the same seller. The algorithm also extracted an account's Pretty Good Privacy key, merging this data with the earlier inferred characteristics, for more precise matches. Former CyLab student Xiao Hui Tai said, "When you're able to capture various pieces of information from different accounts and say they belong to the same person, then you can combine all of this information to help generate investigative leads."

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A Greek text inscription on a rock in Delphi DeepMind AI Beats Humans at Deciphering Damaged Ancient Greek Tablets
New Scientist
Gege Li
October 18, 2019


Yannis Assael at DeepMind and colleagues trained an artificial intelligence (AI) algorithm to guess missing words or characters from Greek inscriptions up to 2,600 years old. The Pythia algorithm learned to recognize patterns on 35,000 relics containing more than 3 million words. The patterns it identifies include the context in which different words appear, the grammar, and the shape and layout of the inscriptions. In a head-to-head test on the missing parts of 2,949 damaged inscriptions, human experts took two hours to get through 50 inscriptions, while Pythia gave its answers in seconds, and was 30% more accurate. Given an inscription with missing information, Pythia provides 20 different suggestions so experts could then select the best one.

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A robot gripping the sponge Giving Robots a Faster Grasp
MIT News
Jennifer Chu
October 17, 2019


Engineers at the Massachusetts Institute of Technology (MIT) have developed a method to significantly speed up the planning process required for a robot to adjust its grasp on an object, by pushing that object against a stationary surface. Traditional algorithms would require tens of minutes to plan a sequence of motions, while the new system takes less than a second to plan motions, due to its use of “motion cones.” The inside of the cone depicts all the pushing motions that could be applied to an object in a specific location, while the space outside represents all the pushes that would in some way cause an object to slip out of the robot's grasp. Said MIT’s Alberto Rodriquez, “This is a way to extend the dexterity of even simple robotic grippers, because at the end of the day, the environment is something every robot has around it.”

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A man with a drone in hand Los Angeles Fire Department Wants More Drones
TechCrunch
Jonathan Shieber
October 20, 2019


The Los Angeles Fire Department (LAFD), an early adopter of drones for supplementing firefighting operations, is considering adding significantly to its drone fleet, which currently numbers 11 units. Battalion Chief Richard Fields said, "Our next iteration is to start using our drones to assist our specialized resources," including crews that contend with hazardous materials, urban search and rescue, marine environments, and water rescues. The drones' chief utility so far has been using infrared sensors to balance a combination of visible and thermal readings. Fields said LAFD drone operators typically receive as much as 80 hours of training.

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Silicon Valley Takes On Amazon's Cashierless 'Go' Stores
The Wall Street Journal
Sebastian Herrera
October 14, 2019


Amazon recently opened its fourth cashierless Go convenience store in San Francisco, located within a few blocks of the other three. Nearby, two startups are each demonstrating their own technology that could power cashier-free stores across the country. This area of San Francisco is emerging as a battleground to eliminate the traditional checkout process and reinvent the way consumers shop. Amazon, along with startups Zippin and Standard Cognition, use technology equipped with camera systems powered by computer vision and machine learning software that track people as they take items off the shelves. The companies are pitching their systems to grocery chains, sports stadiums, and convenience stores, promising to automate the checkout process, reduce theft, and improve profit margins. The technology is currently only being tested in small convenience-store concepts selling packaged goods, because it is relatively expensive for a big-box retailer to adopt such systems on a wide scale.

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Computer Models Show Clear Advantages in New Types of Wind Turbines
Aarhus University
Jesper Bruun
October 17, 2019


Researchers at Aarhus University in Denmark and Durham University in the U.K. used computer modeling of fluid dynamics to determine that wind turbines with four rotors on one foundation have advantages over other designs. The researchers found that turbulence in the wake of the turbines recover much faster with multi-rotor turbines, so a turbine downwind will produce more energy and will be subjected to less load and stress, because the turbulence is correspondingly smaller. The researchers also found that multi-rotor turbines produce about 2% more energy than single-rotor turbines. Said Aarhus researcher Mahdi Abkar, "We've explored several different geometries and dynamics of multi-rotor turbines and have found that the optimum construction is a turbine with four rotors as far apart as possible."

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A robot following three guys It's Never Been Easier to Avoid Walking. A Cargo-Carrying Robot Might Change That
The Washington Post
Peter Holley
October 15, 2019


Boston-based robotics firm Piaggio Fast Forward will soon deploy a bipedal wheeled robot that hauls owners' property as it follows behind them. Piaggio Fast Forward co-founder Greg Lynn envisions the gita robot competing with last-mile transit solution, like e-scooters and ride-hailing companies. Lynn said gita's advantages over e-scooters include less congestion on sidewalks, and offers travelers the mental and physical benefits of walking the last mile. Gita follows its owner at up to six miles per hour, lugging 40 pounds of belongings within an inner compartment, storing up to four hours of battery time, and navigating via multiple cameras that scan and track the owner's leg movements. Gita communicates by sound, and buttons can activate and adjust the robot.

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Bio-Circuitry Mimics Synapses and Neurons in a Step Toward Sensory Computing
Oak Ridge National Laboratory
Ashley C. Huff
October 16, 2019


Researchers at Oak Ridge National Laboratory, the University of Tennessee, and Texas A&M University have demonstrated bio-inspired devices that bring us closer to neuromorphic, or brain-like, computing. The breakthrough is the first example of a lipid-based "memcapacitor," a charge storage component with memory that processes information much like the way synapses do in the brain. This discovery could lead to the emergence of computing networks modeled on biology for a sensory approach to machine learning. The new method uses soft materials to mimic biomembranes and simulate the way nerve cells communicate with one another. Said ORNL researcher Pat Collier, "Incorporating biology—using biomembranes that sense bioelectrochemical information—is key to developing the functionality of neuromorphic computing."

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Artificial Pancreas System Controls Blood Glucose Levels Better Than Current Technology
National Institutes of Health
October 16, 2019


A study funded by the U.S. National Institutes of Health detailed the clinical trial of an artificial pancreas system that automatically monitors and regulates blood glucose levels. The Control-IQ technology is more effective than current techniques at regulating blood glucose levels in persons with type 1 diabetes throughout the day and overnight. The closed-loop control device tracks blood glucose via a continuous glucose monitor, and automatically dispatches insulin when needed. Control-IQ is based on a system invented at the University of Virginia, Charlottesville (UVA), with an insulin pump programmed with sophisticated control algorithms based on a mathematical model that uses glucose monitoring data to automatically adjust dosage. UVA's Boris Kovatchev said, "There is a special safety module dedicated to prevention of hypoglycemia, and there is gradually intensified control overnight to achieve near-normal blood sugar levels every morning."

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TU Delft Researchers Design New Material Using AI Only
TU Delft
October 14, 2019


Researchers at Delft University of Technology (TU Delft) in the Netherlands have designed a new material solely with artificial intelligence (AI), without conducting experimental trials. TU Delft's Miguel Bessa used machine learning to guide the manufacture of two designs at different length scales, converting brittle polymers into lightweight, recoverable, and highly compressible metamaterials. The concept involves using AI to investigate new design possibilities, while keeping experimentation to a minimum. Said Bessa, "Machine learning creates an opportunity to invert the design process by shifting from experimentally guided investigations to computationally data-driven ones, even if the computer models are missing some information. The essential requisites are that 'enough' data about the problem of interest is available, and that the data is sufficiently accurate."

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Microsoft 2020 Imagine Cup
 
Northeastern University Institute for Experiential AI
 

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