Welcome to the September 28, 2020 edition of ACM TechNews, providing timely information for IT professionals three times a week.
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Error Discovered on Georgia Touchscreens in US Senate Race
The Atlanta Journal-Constitution
Mark Niesse
September 26, 2020
Georgia election officials on Saturday said they found a programming error on the state's voting touchscreens that caused a column of candidates in the U.S. Senate special election to vanish when flipping back and forth between screens. Deputy Secretary of State Jordan Fuchs said, "Logic and accuracy testing discovered an issue where if a user flips back and forth multiple times between the Senate special election and the previous race [which is not typical], the second column would, in rare occasions, not appear." The flaw would have impacted candidates sorted alphabetically. Remedial action requires reprogramming Georgia's 30,000 new touchscreens, about 14 days before in-person early voting starts Oct. 12.
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Robots Target Coronavirus with Ultraviolet Light at London Train Station
Reuters
Ben Makori; Alistair Smout
September 23, 2020
Robots have been deployed at London's St. Pancras International train station in the U.K to kill the coronavirus with ultraviolet (UV) light. The robots sweep large areas with UV without having to chemically disinfect, and can destroy almost 100% of bacteria and viruses on surfaces and in the surrounding air in minutes, a station representative said. St Pancras International saw 34.6 million entries and exits in the year to March 2019, making it the ninth-busiest station in the U.K. "We are the first train station to bring this type of technology in because we want to allow people to use a train station with confidence, use our retail units with confidence, and slowly get back to a normal way,” said Jay Newton with the High Speed One Channel tunnel rail link.
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This Is How Much Top Hackers Are Earning From Bug Bounties
ZDNet
Steve Ranger
September 22, 2020
More than $44.75 million in bounties was awarded to hackers worldwide over the past year, up 86% annually, according to HackerOne, which operates bug bounty programs. The average bounty paid for critical vulnerabilities rose 8% over the past year to $3,650, and the average amount paid per vulnerability was $979. To date, more than 181,000 vulnerabilities have been reported, and hackers have been paid more than $100 million. Almost nine out of 10 of the hackers enrolled with HackerOne are under 35, and hacking is the only source of income for one in five of the program's hackers. HackerOne reported that, in less than a decade, nine individual hackers have been paid $1 million in total bounty earnings, more than 200 hackers have earned more than $100,000, and 9,000 hackers have earned "at least something."
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Trump Administration Signs AI Research and Development Agreement with the U.K.
The Hill
Maggie Miller
September 25, 2020
The Trump administration on Friday announced an artificial intelligence (AI) research and development agreement with the U.K., designed to advance cooperation on development and priorities for AI planning and programming. U.S. CTO Michael Kratsios said, "America and our allies must lead the world in shaping the development of cutting-edge AI technologies and protecting against authoritarianism and repression." The Declaration on Cooperation in Artificial Intelligence Research and Development stems from a 2019 meeting between President Trump and U.K. Prime Minister Boris Johnson, when a U.S.-U.K. Special Relationship Economic Working Group was formed to promote collaboration on economic growth. The agreement follows actions by the Trump administration to accelerate investment in AI and quantum computing. A bipartisan coalition of lawmakers also proposed legislation to allocate $100 million for a new National Science Foundation Directorate of Technology in order to fund AI, quantum, robotics, and cybersecurity investment.
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Fruit Flies Plug Into the Matrix
Scientific American
Sophie Bushwick; Macarena Carrizosa
September 25, 2020
University of California, Santa Barbara researchers have developed a low-cost system called PiVR, after the Raspberry Pi computer that runs its software, to generate virtual reality (VR) environments for small animals like fruit flies. PiVR allows real-time analysis of animal behavior with cameras and other sensors, as it responds to a controlled environment. Light stimulates the animal by brightening or dimming based on where it goes, with sensors tracking its reactions so investigators can examine how organisms use visual stimuli to navigate. Scientists can use PiVR to hack an animal's brain so it interprets light as a different type of sensory stimulus by putting light-sensitive proteins into its neurons. Harvard Medical School's Alexandra Moore said, "The flexibility and the affordability of the system—it's open source, it's written in a very easy programming language—can help students understand ... advanced concepts like 'How does spatial navigation work?'"
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Promising Computer Simulations for Stellarator Plasmas
Max Planck Institute for Plasma Physics
September 18, 2020
Researchers at Germany's Max Planck Institute for Plasma Physics (IPP) have created computer simulations that show promise for reducing plasma turbulence in stellarator plasmas, which could potentially boost the efficiency of future fusion power plants. They used the GENE (Gyrokinetic Electromagnetic Numerical Experiment) turbulence code, which ignores all plasma phenomena with a minor role in turbulent transport, and can describe the formation and propagation of small low-frequency plasma eddies in the plasma interior. The IPP team had to adjust GENE's code to accommodate turbulence calculation in the complex geometry of stellarator plasmas. The resulting calculations suggest the ability for fast ions to significantly reduce turbulent transport in tokamak plasmas also should be present in stellarator plasmas. IPP's Frank Jenko said the GENE-3D code, developed over nearly five years, offers a "fast and yet realistic turbulence calculation also for stellarators."
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The Smallest Particle Sensor in the World—Made in Graz
Graz University of Technology
Christoph Pelzl
September 24, 2020
A small, energy-efficient particle sensor for mobile devices has been developed by researchers at Graz University of Technology (TU Graz) in Austria, semiconductor manufacturer ams AG, and Silicon Austria Labs. The particle sensor, called the smallest in the world at 12 mm by 9 mm by 3 mm, enables smartphones, smart watches, and fitness wristbands to perform real-time measurements of ambient air quality. Elevated levels of fine dust content in the air will trigger a warning. In addition to wearables, the sensor can be integrated into applications both in the home and outdoors. Said TU Graz's Alexander Bergmann, "Close-meshed and comprehensive monitoring of air quality has so far failed due to the size, complexity, and cost of currently available measuring sensors. Our particle sensor fills a gap here."
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Stanford Researchers Combine CAT Scans, Advanced Computing to Fight Wildfires
Stanford News
Andrew Myers
September 22, 2020
Stanford University engineers have created a computer model to predict wildfires, using computerized axial tomography scanners. They developed an analytical technique using advanced X-ray Computed Tomography (XCT) to study smoldering—the state of burning without flame that often leads to fire. XCT can look inside dense materials to generate three-dimensional images of wood structures less than a millimeter in scale as they smolder and ignite. The Stanford team integrated the information about flammability of various materials with land contour data from mapping databases. Using the open source TensorFlow computing framework, Stanford's Matt Bonanni is working with Google Research to run simulations, in order to predict how different combinations affect how wildfires might spread and which are most likely to occur; such models can now run in near-real time. Bonanni said, "Once your model reaches that speed, then you can actually use it as a live model of fire burning and make strategic decisions in the firefighting process."
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Automatic Database Creation for Materials Discovery: Innovation From Frustration
Argonne National Laboratory
John Spizzirri
September 22, 2020
Scientists at the U.S. Department of Energy's Argonne National Laboratory and the U.K.'s University of Cambridge have developed a method that generates automatic databases to support specific scientific disciplines, using artificial intelligence and high-performance computing (HPC). The technique can assemble databases via natural language processing (NLP) and HPC, most of which was performed at the Argonne Leadership Computing Facility. The team built a database on both material structures and material properties, using the NLP ChemDataExtractor data-mining application. Cambridge's Jacqueline Cole said, "It's probably the first such compilation of a database on such a massive scale, with 5,380 like-for-like pairs of experimental and calculated data. And because it's such a large amount, it serves as a repository in its own right and really opens the door to predicting new materials."
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Dunkin’, Stadiums Try Checkout-Free Shopping as Social Distancing Remains a Priority
The Wall Street Journal
Katie Deighton
September 23, 2020
Mastercard's new checkout-free payment system is being tested by coffee chain Dunkin', hospitality stands at sports stadiums, and other retailers looking to speed up the payment process while minimizing social contact. Dunkin' plans to rebrand a California store as Dunkin' Dash, where customers register their credit card at an outside kiosk, receive a QR code that grants them entry, and are tracked by cameras inside as they select items. Mastercard's Shop Anywhere system, built on Accel Robotics Corp.'s computer vision technology, will allow consumers to register in less than 30 seconds. However, they will have to sign up separately with each retailer using the technology. Meanwhile, Amazon.com Inc.'s Go technology uses scanners, cameras, and software to enable shoppers to exit its Go-branded stores without stopping to pay, and Giant Eagle Inc. offers checkout-free shopping at a Pittsburgh-based convenience story via Grabango Co.'s cashier-free technology.
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AI Could Expand Healing with Bioscaffolds
Rice University
Mike Williams
September 21, 2020
Rice University engineers are using machine learning artificial intelligence to accelerate development of three-dimensionally-printed bioscaffolds that help injuries heal. Rice's Lydia Kavraki said, "We were able to give feedback on which [printing] parameters are most likely to affect the quality of printing, so when they continue their experimentation, they can focus on some parameters and ignore the others." The researchers learned print speed is the most important of five measured metrics for producing high-quality implants. The team considered two modeling methods: a classification technique that predicted whether a given set of parameters would yield a "low"- or "high"-quality scaffold, and a regression-based approach that approximated the values of print-quality metrics to reach a result. Both methods applied the random forest classical supervised learning technique, which assembles and combines multiple decision trees to produce a more accurate and stable prediction.
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Third-Party Code Bug Left Instagram Users at Risk of Account Takeover
Computer Weekly
Alex Scroxton
September 24, 2020
Security teams at Check Point and Facebook reported a third-party remote code execution flaw in the Instagram photo-sharing platform, which could have enabled malefactors to hijack accounts and use victims' devices for surveillance. Facebook calls the bug an integer overflow leading to a heap buffer overflow, and was present in Mozjpeg, an open source, third-party JPEG decoder that Instagram uses to upload images to the application. Check Point's Yaniv Balmas highlighted the risks of using third-party code libraries to build app infrastructures without checking for flaws. Although patched six months ago, the Mozjpeg bug is only being disclosed now in the hope that a sufficient number of users have updated their apps to ameliorate its impact.
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Spin Clean-Up Method Brings Practical Quantum Computers Closer to Reality
Osaka City University
September 25, 2020
Researchers at Japan's Osaka City University (OCU) have developed a quantum algorithm that eliminates spin contaminants while executing chemical calculations on quantum computers, enabling predictions of electronic and molecular behavior with precision beyond that of classical computers. Precise Schrödinger equations would take a massive amount of time on classical computers. Their quantum calculation can yield precision in a realistic time, but this requires cleansing of incorrect spins. The OCU team's algorithm enables selection of the desired spin quantum number to purify the spin, removing contaminants during each calculation. The next challenge is to develop and implement algorithms to determine the state of electrons in molecules with the same accuracy for excited- or ground-state electrons.
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