Welcome to the November 20, 2019 edition of ACM TechNews, providing timely information for IT professionals three times a week.
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Louisiana Target of Attempted Ransomware Hack, Governor Says
Bloomberg
Kartikay Mehrotra
November 18, 2019
Louisiana Gov. John Bel Edwards said attackers targeted the state with ransomware that impacted certain state servers, forcing initiation of security protocols and interruption of online services to prevent further infection. The attempted intrusion occurred during the state's voting certification process, which cybersecurity experts called the kind of threat that election administrators must prepare for, ahead of next year's U.S. presidential election. Experts recommended an auditable paper trail of ballots as the best countermeasure, but the Verified Voting nonprofit warned jurisdictions in Louisiana and 10 other states lack a paper trail. The FireEye cybersecurity company said ransomware attacks have grown in sophistication, while attacks against state and local governments have increased almost twofold this year.
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Quantum Computers Learn to Mark Their Own Work
University of Warwick
November 18, 2019
Scientists at the University of Warwick in the U.K. have developed a test to verify that a quantum computer is providing correct answers to questions outside the scope of traditional computing. This protocol enables the quantum computer to check its own answers to difficult problems, by measuring the impact of noise on its outputs. The test yields two percentages: the system's closeness to the correct result, and the user's confidence of this closeness. The computer must perform a series of easy calculations for which the answer is already known, and establish the accuracy of that output, allowing researchers to impose a statistical limit on how far the system can be from the correct answer to the problem to be solved. Said Warwick's Animesh Datta, "Our method is efficient in that it doesn't require an exponential amount of resources."
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Room-Sized LED Egg Captures Amazing 3D Models of People Inside It
TechCrunch
Devin Coldewey
November 18, 2019
Google researchers have designed a prismatic light-emitting-diode (LED) "egg," to generate remarkable three-dimensional (3D) and relightable models of people within it. The egg uses volumetric capture, in which multiple cameras in a 360-degree arrangement render a photorealistic representation of a subject in motion, while also allowing the model to be realistically illuminated by virtual light sources. This enables the model's placement in any virtual environment where lighting can change. The egg contains 331 LED lights that can produce any hue, and that shift in a specific pattern during subject capture, creating a lighting-agnostic model. When placed in the virtual setting, the models reflect the setting's lighting, and not the lighting of the egg itself.
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Algorithms to Make Virginia Judges Fairer Have Unintended Consequences
The Washington Post
Andrew Van Dam
November 19, 2019
George Mason University's Megan Stevenson and Texas A&M University's Jennifer Doleac explored the unintended consequences of human-algorithmic partnerships, analyzing algorithms intended to reduce Virginia prison populations by assigning defendants risk scores. Judges would use scores to identify the least-likely reoffenders, but this did not change incarceration rates, length of sentences, or recidivism; defendants algorithmically labeled high-risk went to jail longer than they would have, while lower-risk candidates got shorter sentences. Stevenson said risk score is largely a reflection of age, with younger lawbreakers assigned higher scores than repeat adult offenders. Younger, black defendants scored via risk assessment tended to receive harsher sentences, and sex offenders went to jail less often and got shorter sentences overall, although the algorithm was designed to only authorize longer-than-baseline sentences. The researchers think in such cases, algorithms may shield judges from backlash if the lawbreaker re-offends.
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World's Fastest Supercomputers Hit Higher Speeds with Linux
ZDNet
Steven J. Vaughan-Nichols
November 18, 2019
The latest Top500 supercomputer ratings found Linux-powered supercomputers currently average 1.14 petaflops in speed, with the Oak Ridge National Laboratory's Summit system topping the list with a High-Performance Linpack benchmark of 148.6 petaflops. Ranked second is Lawrence Livermore National Laboratory's Sierra system, with a speed of 94.6 petaflops, despite using the same Power9 central-processing units and Nvidia Tesla V100 graphic-processing units as Summit. Although China owns nearly half the world's fastest supercomputers, U.S. systems have a 37.8% aggregate performance share to China' 31.9%. The Green500 list of the most energy-efficient supercomputers ranked the A64FX prototype the top system, with 16.9 gigaflops/watt. Meanwhile, HDR InfiniBand-based machines account for 40% of the Top500's aggregate performance, and Ethernet-based systems account for 29%.
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Multimaterial 3D Printing Manufactures Complex Objects, Fast
Wyss Institute at Harvard
Lindsay Brownell
November 13, 2019
Researchers at Harvard University's Wyss Institute for Biologically Inspired Engineering and John A. Paulson School of Engineering and Applied Sciences have developed multimaterial multinozzle 3D (MM3D) printing, a three-dimensional (3D) printing technique that uses high-speed pressure valves to achieve rapid, continuous, and seamless switching between up to eight different printing materials. The new technique enables the creation of complex shapes in a fraction of the time currently required using printheads that range from a single nozzle to large multinozzle arrays. The 3D printheads themselves are created using 3D printing, which allows for rapid customization and facilitates adoption by others in the fabrication industry. Said Wyss Institute researcher Mark Skylar-Scott, "MM3D's combination of multinozzle arrays with the ability to switch between multiple inks rapidly effectively eliminates the time lost to switching printheads and helps get the scaling law down from cubic to linear, so you can print multimaterial, periodic 3D objects much more quickly."
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The Longest Yard in Football
The New York Times
Andrew Beaton
November 11, 2019
The National Football League (NFL) is starting to use tracking technology that can distinguish exact distances and measure the value of a single inch, which could dramatically change in-game strategy. Starting in 2016, the NFL placed chips in every football to try to better measures distances on the field. One of the most important ways this new data can be applied is on fourth-and-1 plays. When the NFL's director of data and analytics, Michael Lopez, examined this new data trove, he found that when teams were just inches away from the first down in 2017 and 2018, they converted 82% of the time. However, in "long" fourth-and-1 situations, the rate was much lower at just 55%. Now, Lopez is leading the NFL's second annual Big Data Bowl, in which the league challenges quantitative analysts to hunt for insights in the league's data.
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Road Warriors: Video Games Between Autonomous Cars Take Shape
Silicon Republic
Colm Gorey
November 18, 2019
Researchers at the University of Waterloo in Canada have developed three video games that could be played between passengers in autonomous cars that are near each other on the road. The games are designed for cars with Level 3 autonomy or higher, which require almost no attention on the part of the driver. The team developed a virtual reality driving simulator to render the car cabin, outside environment, and roadway with artificially controlled cars and intelligent computer-controlled players. This platform will allow for the quick prototyping of in-car games that could include full window head-up displays, head tracking, and different input methods. Said University of Waterloo researcher Matthew Lakier, "The games will be imposed on top of the actual world, so drivers won't have to take their eyes off the road."
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Raspberry Pi Promotes Computing to Girls through GBIC Program
Electronics Weekly (UK)
Alex McCarthy
November 11, 2019
In April of this year, Raspberry Pi launched its gender balance in computing (GBIC) program and started running trials within a small group of schools around the U.K. The GBIC program is a collaboration between the Raspberry Pi Foundation; STEM Learning; BCS, The Chartered Institute for IT; and the Behavioural Insights Team. Now, the company is planning to launch general recruitment for the program. The GBIC program is funded by the U.K. Department for Education, which allows Raspberry Pi to work with schools and to study different approaches to engage girls in computing. The expanded trials will run from 2019-2022 in key stages 1-4, and include more than 15,000 students from more than 550 schools.
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Nuclear Warheads? This Robot Can Find Them
Princeton Plasma Physics Laboratory
John Greenwald; Jeanne Jackson DeVoe
November 11, 2019
Researchers at the U.S. Department of Energy's Princeton Plasma Physics Laboratory (PPPL) and Princeton University have developed a swarm of autonomous, rolling robots equipped with smart detectors that can identify the source of nuclear radiation and whether it has been shielded to avoid detection. The "inspector bots" consist of a cylinder of polyethylene plastic containing three neutron counters set to 120 degrees apart and mounted on a robot with specialized wheels that enable it to move in any direction. The detectors provide both high sensitivity to the energy of detected neutrons and the direction from which neutrons are coming. Going forward, the researchers want to develop machine learning software that can guide the robots, and technology to enable them to communicate with one another during inspections.
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How Hackers Could Use Wi-Fi to Track You Inside Your Home
UChicago News (IL)
Rob Mitchum
November 14, 2019
A study by University of Chicago (UChicago) and University of California, Santa Barbara researchers demonstrated how hackers can exploit Wi-Fi receivers to remotely monitor a location for indoor movement without being detected. An attacker from outside the target site can use the receiver to measure the strength of signals broadcast from linked devices, in what the researchers call a silent surveillance attack. UChicago's Heather Zheng said, "By just listening to existing Wi-Fi signals, someone will be able to see through the wall and detect whether there's activity or where there's a human, even without knowing the location of the devices." The presence of more connected devices improves the technique's accuracy, and hackers need only avail themselves of off-the-shelf Wi-Fi sniffers to conduct this attack. The researchers suggested access points emit a "cover signal," that combines with signals from connected devices, generating false data to confuse sniffers.
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Want to Know Your Mental Health Status? There's an App for That
University of Colorado Boulder
Lisa Marshall
November 12, 2019
Researchers at the University of Colorado Boulder (CU Boulder) have developed a speech-based mobile app that uses machine learning to categorize a patient's mental health status as well as or better than human psychiatrists. The app can detect day-to-day changes in speech that hint at mental health decline. The app asks patients to answer a five- to 10-minute series of questions by talking into their phone. The questions ask users to discuss their emotional state, to tell a short story, to listen to a story and then repeat it, and they are given a series of touch-and-swipe motor skills tests. The team developed an artificial intelligence system that analyzes those speech samples, compares them to previous samples by the same patient as well as the broader population, and rates the patient's mental state.
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Algorithm May Improve Brain-Controlled Prostheses, Exoskeletons
MIT News
Stephanie Strom
November 18, 2019
Massachusetts Institute of Technology (MIT) Media Lab researchers have developed an algorithm that promises to augment concurrent tracking of magnets. MIT's Cameron Taylor said the algorithm shortens how long it takes for sensors to read the positions and orientations of magnets embedded within the body, wood, ceramics, and other materials. The algorithm rapidly identifies which direction is "warmest" before guessing a magnet's location, and addresses disruption from Earth's magnetic field by searching for that field, like it is simply another magnetic signal. The researchers tested the algorithm with a magnetometer array tracking up to four magnets; compared with advanced magnet trackers, it boosted maximum bandwidths by 336%, 525%, 635%, and 773% when employed to simultaneously track one, two, three, and four magnets, respectively. Software enabled with the algorithm could improve reflexive control of brain-controlled prostheses and exoskeletons, streamline magnetic levitation, and enhance interaction with augmented and virtual reality devices.
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