Welcome to the July 30, 2021 edition of ACM TechNews, providing timely information for IT professionals three times a week.
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What's in a Developer's Name?
University of Waterloo Cheriton School of Computer Science (Canada)
July 28, 2021
Researchers at the University of Waterloo's Cheriton School of Computer Science in Canada found a software developer's perceived race and ethnicity, based solely on their user name, can influence the assessment of their work in open source projects. The researchers analyzed more than 2 million pull requests across roughly 37,700 open source projects on the GitHub software development platform, involving almost 366,000 developers. They used the NamePrism nationality/ethnicity classification tool to estimate developers' likely perceived race and ethnicity based on their GitHub names. Cheriton's Mei Nagappan said most integrated contributions were submitted by developers perceived as white; less than 10% of accepted contributions were from developers perceived as Asian, Hispanic, and Black. Cheriton's Gema Rodriguez-Perez said this underrepresentation could "cause a lack of diverse and important contributions from being incorporated into open source projects, [and] it may also deter non-white developers from contributing to them."
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Q-CTRL, University of Sydney Devise ML Technique Used to Pinpoint Quantum Errors
HPCwire
July 29, 2021
Researchers at Australia's University of Sydney (USYD) and quantum control startup Q-CTRL have designed a method of pinpointing quantum computing errors via machine learning (ML). The USYD team devised a means of recognizing the smallest divergences from the conditions necessary for executing quantum algorithms with trapped ion and superconducting quantum computing equipment. Q-CTRL scientists assembled custom ML algorithms to process the measurement results, and minimized the impact of background interference using existing quantum controls. This yielded an easy distinction between sources of correctable "real" noise and phantom artifacts of the measurements themselves. USYD's Michael J. Biercuk said, "The ability to identify and suppress sources of performance degradation in quantum hardware is critical to both basic research and industrial efforts building quantum sensors and quantum computers."
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Biden Directs Agencies to Develop Cybersecurity Standards for Critical Infrastructure
The Wall Street Journal
Dustin Volz
July 28, 2021
U.S. President Joe Biden this week directed federal agencies to formulate voluntary cybersecurity standards for managers of critical U.S. infrastructure, in the latest bid to strengthen national defenses against cyberattacks. In a new national security memo, Biden ordered the Department of Homeland Security (DHS)'s cyber arm and the National Institute of Standards and Technology to work with agencies to develop cybersecurity performance goals for critical infrastructure operators and owners. DHS now is required to offer preliminary baseline cybersecurity standards for critical infrastructure control systems by late September, followed by final "cross-sector" goals within a year. Sector-specific performance goals also are required as part of a review of "whether additional legal authorities would be beneficial" to protect critical infrastructure, most of which is privately owned. An administration official said, "We're starting with voluntary, as much as we can, because we want to do this in full partnership. But we're also pursuing all options we have in order to make the rapid progress we need."
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Phone's Dark Mode Doesn't Necessarily Save Much Battery Life
Tech Explorist
July 29, 2021
Purdue University researchers found in a recent study that putting a smartphone in dark mode is unlikely to save significant battery life. The researchers built tools to measure more accurately how much power the phones' pixels draw, and examined six of the most-downloaded Android phone applications on Google Play; they then analyzed dark mode's effects on 60 seconds of activity within each app on the Pixel 2, Moto Z3, Pixel 4, and Pixel 5 phones. The researchers' Per-Frame OLED Power Profiler technology showed that switching from light mode to dark saves just 3% to 9% power on average for models featuring organic light-emitting diode (OLED) screens.
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Stanford ML Tool Streamlines Student Feedback Process for Computer Science Professors
Stanford News
Isabel Swafford
July 27, 2021
Stanford University researchers have developed and tested a machine learning (ML) teaching tool designed to assist computer science (CS) professors in gauging feedback from large numbers of students. The tool was developed for Stanford's Code In Place project, in which 1,000 volunteer teachers taught an introductory CS course to 10,000 students worldwide. The team scaled up feedback using meta-learning, a technique in which an ML system can learn about numerous problems with relatively small volumes of data. The researchers realized accuracy at or above human levels on 15,000 student submissions, using data from previous iterations of CS courses. The tool learned from human feedback on just 10% of the total Code In Place assignments, and reviewed the remainder with 98% student satisfaction.
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First Test of Europe's Space Brain
European Space Agency
July 28, 2021
The European Space Agency (ESA) operated a spacecraft successfully using a next-generation mission control system. Current missions are being converted to the European Ground System-Common Core (EGS-CC), which will function as the "brain" of all European spaceflight operations by 2025. Freely available to all European entities, the EGS-CC was used to monitor and control ESA's OPS-SAT Space Lab, a 30-centimeter (12-inch) satellite created to test and validate new mission control techniques and on-board systems. OPS-SAT mission manager Dave Evans said during the test, ESA's European Space Operations Center used the software to send routine commands to the spacecraft and to receive data from the mission. EGOS-CC project manager Klara Widegard said, “This has been a hugely successful validation of this new versatile control system, demonstrating the exciting future of mission control technologies and Europe’s leading position in space.”
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Malware Developers Turn to 'Exotic' Programming Languages to Thwart Researchers
ZDNet
Charlie Osborne
July 27, 2021
Cybersecurity service provider BlackBerry's Research & Intelligence team has found that malware developers are increasingly employing "exotic" coding languages to foil analysis. A report published by the team cited an "escalation" in the use of Go (Golang), D (DLang), Nim, and Rust to "try to evade detection by the security community, or address specific pain-points in their development process." Malware authors are experimenting with first-stage droppers and loaders written in these languages to evade detection on a target endpoint; once the malware has bypassed existing security controls that can identify more typical forms of malicious code, they are used for decoding, loading, and deploying malware. The researchers said cybercriminals’ use of exotic programming languages could impede reverse engineering, circumvent signature-based detection tools, and enhance cross-compatibility over target systems.
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Supercomputer-Generated Models Provide Better Understanding of Esophageal Disorders
UC San Diego News Center
Kimberly Mann Bruch
July 23, 2021
Northwestern University researchers used the San Diego Supercomputing Center (SDSC)'s Comet and the Pittsburgh Supercomputing Center's Bridges-2 supercomputers to simulate the swallowing mechanism of gastroesophageal reflux disease, which affects about 20% of U.S. citizens. Their research yielded the FluoroMech computational modeling system, which helps recognize physio-markers for accurately diagnosing esophageal disorders. The team engineered FluoroMech to predict the mechanical processes of soft tubular organs like the esophagus by analyzing fluoroscopic images and video during swallowing. Northwestern's Sourav Halder said the simulations would have been impossible to create in a reasonable amount of time without supercomputers to handle “almost five million unknowns to solve at each time step” and “large numbers of time steps that needed to be solved.” Even with supercomputers, Halder said, each model took five to seven days to generate results.
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Smartphone Screens Sense Soil, Water Contamination
University of Cambridge (U.K.)
July 22, 2021
A smartphone touchscreen could identify common ionic contaminants in soil or drinking water, according to researchers at the U.K.'s University of Cambridge. The team ran simulations, then validated them using a standalone touchscreen similar to those used in phones and tablets. The researchers deposited different liquids onto the screen to measure shifts in capacitance, and used touchscreen testing software to record the measurement of each droplet. An early use for the technique could be to detect arsenic in drinking water. Cambridge's Ronan Daly said, “In theory, you could add a drop of water to your phone before you drink it, in order to check that it’s safe.”
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Disagreement May Make Online Content Spread Faster, Further
UCF Today
Robert Wells
July 22, 2021
An analysis of posts designated as controversial on social news aggregation site Reddit suggests disagreement may cause posts to spread faster, and to a greater extent. Scientists at the University of Central Florida (UCF) reviewed over 47,000 posts about cybersecurity in a Reddit dataset compiled by the U.S. Defense Advanced Research Projects Agency (DARPA) Computational Simulation of Online Social Behavior program. The team found the posts were viewed by nearly twice as many people, and spread nearly twice as fast, as posts not labeled controversial. The posts included subjects not be deemed traditionally controversial, but which were classified that way by Reddit. UCF's Jasser Jasser said these findings emphasize the need to better understand how content labeled in Reddit as controversial proliferates, by analyzing the language used to generate controversy.
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Less Chat Can Help Robots Make Better Decisions
University of Sheffield (U.K.)
July 28, 2021
Robot swarms could cooperate more effectively if communication among members of the swarm were curtailed, according to research by an international team led by engineers at the U.K.'s University of Sheffield. The research team analyzed how a swarm moved around and came to internal agreement on the best area to concentrate in and explore. Each robot evaluated the environment individually, made its own decision, and informed the rest of the swarm of its opinion; each unit then chose a random assessment that had been broadcast by another in the swarm to update its opinion on the best location, eventually reaching a consensus. The team found the swarm's environmental adaptation accelerated significantly when robots communicated only to other robots within a 10-centimeter range, rather than broadcasting to the entire group.
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Tracking Circadian Rhythms From Your Smartwatch
University of Michigan News
July 29, 2021
The University of Michigan (U-M)'s Daniel Forger and colleagues have crafted an algorithm that extracts an individual’s circadian rhythm from heart rate data collected by their smartwatch. The program rejects data collected during sleep, concentrating on data gleaned while the person is awake, then accounts for whether their heart rate is affected by their activity, or by the stress hormone cortisol as a result of exercise, posture, or meals. Forger said, "We've shown that you can take a wearable signal and directly measure circadian rhythms in the real world, and the real world has so many things that affect circadian rhythms that you aren't going to measure in the lab."
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Cybersecurity Technique Keeps Hackers Guessing
U.S. Army DEVCOM Army Research Laboratory
July 27, 2021
Development Command's Army Research Laboratory (ARL) has designed a machine learning-based framework to augment the security of in-vehicle computer networks. The DESOLATOR (deep reinforcement learning-based resource allocation and moving target defense deployment framework) framework is engineered to help an in-vehicle network identify the optimal Internet Protocol (IP) shuffling frequency and bandwidth allocation to enable effective, long-term moving target defense. Explained ARL's Terrence Moore, "If you shuffle the IP addresses fast enough, then the information assigned to the IP quickly becomes lost, and the adversary has to look for it again." ARL's Frederica Free-Nelson said the framework keeps uncertainty sufficiently high to defeat potential attackers without incurring excessive maintenance costs, and prevents performance slowdowns in high-priority areas of the network.
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