Welcome to the June 19, 2020 edition of ACM TechNews, providing timely information for IT professionals three times a week.
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Inside the NBA's Plan to Use Smart Technology, Big Data to Keep Players Safe From Coronavirus
CNBC
Jessica Golden
June 17, 2020
The NBA plans to use smart technologies to protect players and staff from the coronavirus as 22 teams prepare to play games at Disney's Wide World of Sports complex in Orlando. In addition to subjecting players to extensive testing, quarantining them from their families, and imposing strict rules for social behavior, each will be given a "smart" ring, a Disney MagicBand, an individual pulse oximeter, and a smart thermometer. Oura's titanium rings can measure body temperature, respiratory functions, and heart rate and predict Covid-19 symptoms up to three days in advance with 90% accuracy. The MagicBand will act as a hotel room key, allow players to check in at security checkpoints and coronavirus screenings, and help with contact tracing. The league also is considering a small device that will set off an audio alert when the wearer is within six feet of another person for longer than five seconds.
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Capturing Moving Subjects in Still-Life Quality
EPFL News (Switzerland)
June 18, 2020
Researchers at the Swiss Federal Institute of Technology in Lausanne (EPFL) Advanced Quantum Architecture Laboratory and the University of Wisconsin-Madison (UW-Madison) Wision Laboratory have developed a method for capturing extremely clear images of moving subjects. UW-Madison's Mohit Gupta borrowed EPFL's SwissSPAD camera, which generates two-dimensional binary images at a resolution of 512 x 512 pixels. EPFL's Edoardo Charbon said SwissSPAD captures 100,000 binary images per second, as an algorithm corrects for variations; the researchers built a high-definition image of a moving subject by combining these photos. The team aims to repeat the experiment with the MegaX camera, which Charbon said "is similar to SwissSPAD in many ways; it's also a depth-sensing camera, thus it can generate [three-dimensional] images."
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Borrowing From Robotics, Scientists Automate Mapping of Quantum Systems
University of Sydney
June 16, 2020
In Australia, University of Sydney researchers have adapted algorithms from autonomous vehicles and robotics to efficiently assess the performance of quantum devices. Said the university's Riddhi Gupta, "Using this approach, we can map the 'noise' causing performance variations across quantum devices at least three times as quickly as a brute-force approach. Rapidly assessing the noise environment can help us improve the overall stability of quantum devices." The researchers adapted the simultaneous localization and mapping (SLAM) algorithms used in robotics to quantum systems. Said Gupta, "Rather than estimate the classical environment for each and every qubit, we are able to automate the process, reducing the number of measurements and qubits required, which speeds up the whole process."
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Doctor.com's Patient Survey Reveals Surprising Trends About Telemedicine Adoption Amid Reopenings
PR Newswire
June 16, 2020
A nationwide survey of 1,800 patients by healthcare marketing automation company Doctor.com found evidence of massive telemedicine adoption during the current pandemic, as well as growing demand for telemedicine services in the coming years. Most (83%) of the surveyed patients expect to use telemedicine after the pandemic, 55% are willing to use telemedicine to see new doctors, and 69% said "easy-to-use technology" would help them decide to make a telemedicine appointment. Moreover, 71% would consider using telemedicine services now, while 83% are likely to use such services after the pandemic. Doctor.com CEO Andrei Zimiles said, "As telemedicine becomes part of a 'new normal,' it is critical that providers begin shifting their long-term care strategies to incorporate virtual care and meet patients' rapidly evolving expectations for this channel."
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Massive Spying on Users of Google's Chrome Shows New Security Weakness
Reuters
Joseph Menn
June 18, 2020
Awake Security researchers said they had identified a spyware effort that attacked users through 32 million downloads of add-ons to Google's Chrome Web browser. Google said it has removed more than 70 of the malicious extensions from the official Chrome Web Store. Awake's Gary Golomb said it was the farthest-reaching malicious Chrome store campaign identified to date, based on the number of downloads. The extensions were designed to avoid detection by antivirus and security software that evaluates the reputations of Web domains, and to connect to a series of websites and transmitting information when someone used the browser to surf the Web on a home computer. It is unclear who was behind the malware campaign, as its developers used fictitious contact information when they submitted the extensions to Google.
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Digitize Your Dog Into a Computer Game
University of Bath Communications
June 16, 2020
Researchers at the University of Bath's Center for the Analysis of Motion, Entertainment Research, and Applications (CAMERA) in the U.K. have digitized the movements of 14 dog breeds, using motion-capture technology that employs just one camera and forgoes a motion-capture suit. The dogs were filmed performing a range of movements in special suits with markers, and this data was fed into a computer model that predicted and replicated the poses of dogs when filmed without the suits. The resulting model enabled the recording of three-dimensional (3D) digital information for new dogs using a single RGBD camera. CAMERA director Darren Cosker said, "Our research is a step towards building accurate 3D models of animal motion along with technologies that allow us to very easily measure their movement."
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Open-Source, Low-Cost, Quadruped Robot Makes Sophisticated Robotics Available to All
NYU Tandon School of Engineering
June 16, 2020
Researchers at the New York University Tandon School of Engineering and the Max Planck Institute for Intelligent Systems in Tübingen and Stuttgart, Germany, have developed a lower-cost quadruped robot that is easy and fast to assemble and can be upgraded and modified. The Solo 8, with an estimated price of just a few thousand euros, will give research teams on limited budgets access to sophisticated robotics technology. The use of an open-source platform also will allow researchers to compile comparative data, which could spur rapid progress in robotics. Solo 8 can perform jumping actions, walk in multiple configurations and directions, and recover orientation, posture, and stability after being overturned. All of its components can be three-dimensionally (3D)-printed or purchased, and the construction files are available online for free under the BSD 3-clause license.
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Discovery Allows 3D Printing of Sensors Directly on Expanding Organs
University of Minnesota
June 17, 2020
Mechanical engineers and computer scientists at the University of Minnesota (UMinn) have developed a three-dimensional (3D) printing method that employs motion capture technology to print electronic sensors directly on organs in motion. The technique enables more refined tracking, in order to 3D-print sensors on organs like the lungs or heart that change shape or distort. The researchers applied motion capture tracking markers to a balloon-like surface to help the 3D printer adapt its printing path to the surface's expansion and contraction movements. The team then successfully printed a soft hydrogel-based sensor directly on the surface of an artificially inflated animal lung. UMinn's Michael McAlpine said, "The broader idea ... is that this is a big step forward to the goal of combining 3D printing technology with surgical robots."
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Circular Reasoning: Spiraling Circuits for More Efficient AI
University of Tokyo
June 14, 2020
Researchers at the University of Tokyo Institute of Industrial Science in Japan stacked resistive random-access memory modules for artificial intelligence (AI) applications in a novel three-dimensional spiral. The modules feature oxide semiconductor access transistors, which boost the efficiency of the machine learning training process. The team further enhanced energy efficiency via a system of binarized neural networks, which restricts the parameters to be either +1 or -1, rather than any number, to compress the volume of data to be stored. In having the device interpret a database of handwritten digits, the researchers learned that increasing the size of each circuit layer could improve algorithmic accuracy to approximately 90%. The University of Tokyo's Masaharu Kobayashi said, "In order to keep energy consumption low as AI becomes increasingly integrated into daily life, we need more specialized hardware to handle these tasks efficiently."
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Turning Faces Into Thermostats: Autonomous HVAC System Could Provide More Comfort With Less Energy
University of Michigan News
June 16, 2020
University of Michigan (U-M) researchers developed the Human Embodied Autonomous Thermostat (HEAT) to provide more personalized climate control in homes, offices, and factories, while eliminating the need for wall-mounted thermostats. The system measures whether occupants are hot or cold by tracking their facial temperatures using a combination of thermal cameras and three-dimensional video cameras. The temperature data is fed into a predictive model that compares it with information about occupants' thermal preferences. After installing HEAT, occupants use their smartphones to provide feedback — whether they are "too hot," "too cold," or "comfortable" — which allows the system to learn their preferences and operate independently. U-M's Carol Menassa said facial temperature is a good predictor of comfort because the blood vessels expand when we're too hot and constrict when we're too cold. A residential version of the system could be on the market within five years.
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Researcher Builds Solution to Work-From-Home Cloud-Computing 'Storms'
University of Texas at San Antonio
Milady Nazir
June 12, 2020
Researchers at the University of Texas at San Antonio, the University of Georgia, the University of Virginia, and IBM’s Thomas J. Watson Research Center collaborated on an algorithm that reduces resource surges as more companies rely on work-from-home environments due to the coronavirus pandemic. These resource surges occur when demands for CPU and memory to run foreground services, like email or video meetings, interfere with critical background applications, like virus detection programs or backups. The Orchestra algorithm can respond in real time as it constantly adjusts cloud resources between foreground and background applications, requiring minimal time and effort from IT personnel to install, deploy, manage, and monitor the technology. Researchers evaluated Orchestra on the Amazon Elastic Compute Cloud but indicated that it can be used on other on-demand cloud computing platforms as well.
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Engineers Offer Smart, Timely Ideas for AI Bottlenecks
Rice University
Jade Boyd
June 11, 2020
Engineers at Rice University, Stanford University, and the University of California, Santa Barbara have demonstrated techniques for designing data-centric computing hardware and co-designing hardware with machine-learning algorithms, which enhance energy efficiency by up to two orders of magnitude. Rice's Yingyan Lin said large-scale deep neural networks consume more than 90% of the power needed to run a system in transferring data between memory and processor, which stems from the von Neumann bottleneck. Two proposed complementary data-centric processing optimization methods overcome this bottleneck. The Time-domain, In-Memory Execution, LocalitY (TIMELY) architecture removes inefficiency caused by frequent access to the main memory for managing intermediate input and output, and the interface between local and main memories. SmartExchange is an energy-efficient design combining algorithmic and accelerator hardware innovations that basically trades higher-cost memory for lower-cost computation.
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Cutting-Edge Computing Paves Way to Future of NMR Spectroscopy
Washington University in St. Louis
Shawn Ballard
June 12, 2020
Researchers at Washington University in St. Louis, Lawrence Berkeley National Laboratory, and the University of California, Berkeley have developed additional data infrastructure for an isotope of silicon, 29Si, that paves the way for the future of nuclear magnetic resonance (NMR) spectroscopy. NMR helps scientists identify and explore atomic structures but is limited by the availability of reference data to compare and identify structures. The researchers generated new datasets for 29Si and confirmed their validity using two advanced computational tools, Vienna Ab initio Simulation Package (VASP) and Cambridge Serial Total Energy Package (CASTEP). The tools enabled them to computationally generate predictions for NMR measurables, or tensors, for silicon; compare the created dataset with experimentally observed data, and systematically correct the machine-generated data. The cleaned dataset and collection of software tools are available in the shared local spectroscopy data infrastructure database via the Materials Project.
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Adding Noise for Completely Secure Communication
University of Basel
June 12, 2020
Researchers at Switzerland’s University of Basel and ETH Zurich have established the theoretical foundations for 100% secure communication, ensuring protection not just against quantum computers, but also in instances where the communication devices' operational mechanisms and trustworthiness are unknown. The protocol adds artificial noise to information about the cryptographic key, guaranteeing eavesdroppers receive so little actual data as to render the protocol unbreakable. The University of Basel's Nicolas Sangouard said, "Since the first small-scale quantum computers are now available, we urgently need new solutions for protecting privacy. Our work represents a significant step toward the next milestone in secure communications."
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