Welcome to the May 20, 2022, edition of ACM TechNews, providing timely information for IT professionals three times a week.
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Finding the Branches on the Tree of Life
University of Waterloo Cheriton School of Computer Science (Canada)
May 18, 2022
The Deep Learning for Unsupervised Clustering of DNA Sequences (DeLUCS) technique developed by researchers at Canada's University of Waterloo and Western University draws taxonomic relationships between organisms via unsupervised machine learning. Waterloo's Lila Kari said DeLUCS determines these relationships "across a range of genetic datasets from organisms as diverse as vertebrates, bacteria, and viruses." The researchers compared genomes of organisms using frequency chaos game representation (FCGR), a graphical depiction of base sequences in DNA showing how often a particular nucleotide sequence occurs. The process generates FCGR pairs of sequences and mimics as input to an artificial neural network, "from which it finds patterns that can be used to create clusters," Kari said. "This method has an accuracy of almost 80%, and often much better."
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Two Military Satellites Communicate Using Space Lasers
Gizmodo
Passant Rabie
May 19, 2022
Two military satellites used lasers to exchange more than 200 gigabits of data across roughly 60 miles (nearly 100 km) of space, according to satellite technology contractor CACI International. The U.S. Defense Advanced Research Projects Agency launched the Able and Baker satellites last summer as part of its Blackjack project to deploy a low-Earth-orbit satellite constellation to support military operations. Able and Baker communicated for 40 minutes using CACI's CrossBeam free-space optical terminals. Said the Space Development Agency's Derek Tournear, "We demonstrated with commoditized laser communication that we could do satellite-to-satellite communication, and really demonstrated that this is no longer at the very high end, that we can actually do this with commoditized laser communication platforms and technologies."
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Researchers Can Predict Vaccine Hesitancy at Zip Code Level
USC Viterbi School of Engineering
Maya Abu-Zahra
May 16, 2022
University of Southern California (USC) researchers have developed natural language processing (NLP) software that can forecast vaccine hesitancy in specific geographies in real time. The researchers said the system uses existing algorithms to process publicly available Twitter data, outperforming local and national survey data in reflecting public views on the COVID-19 vaccine at the zip code level. USC's Sara Melotte said the software furthers the goal of making such predictions on a community level. "We show that only the text tweet and hashtags are sufficient to predict zip code-level vaccine hesitancy with reasonable accuracy, even if the tweets are not all related to the COVID-19 pandemic."
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iPhone Malware Runs Even When Device Is Off
Ars Technica
Dan Goodin
May 16, 2022
Academics at Germany's Technical University of Darmstadt (TU Darmstadt) created malware that exploits the continued operation of iPhone's Bluetooth chip, even when the device is off. The low-power mode (LPM)-targeting malware can allow attackers to track the phone’s location, or to run new features when the handset is deactivated. "Since LPM support is based on the iPhone's hardware, it cannot be removed with system updates," the researchers explained. "Thus, it has a long-lasting effect on the overall iOS security model." Real-world exploitation of these findings is limited since infections require a jailbroken iPhone, the researchers said, adding that other malware could target iOS' always-on feature.
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Microsoft Censoring Searches in U.S. for Politically Sensitive Chinese Names
The Wall Street Journal
Aaron Tilley
May 19, 2022
A report from Citizen Lab, an interdisciplinary lab at Canada’s University of Toronto, found that Microsoft's Bing search engine is blocking North American searches for politically sensitive Chinese names. Testing late last year determined that Bing would not generate autofill suggestions for search terms of the names of Chinese political dissidents and party leaders, in English or Chinese. Microsoft says it has already corrected the issue, which a spokeswoman attributed to "a misconfiguration." Last year, Microsoft suspended the autofill feature in China to abide by Chinese law, which the new report said demonstrates how such censorship could affect search results for users in North America.
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Using Everyday Wi-Fi to Help Robots See, Navigate Better Indoors
UC San Diego Jacobs School of Engineering
May 20, 2022
University of California, San Diego (UCSD) researchers have developed an inexpensive method to help robots accurately navigate indoors using Wi-Fi signals. "We are surrounded by wireless signals almost everywhere we go," explained UCSD's Dinesh Bharadia. "The beauty of this work is that we can use these everyday signals to do indoor localization and mapping with robots." The researchers built Wi-Fi sensors from commercially available transceivers, which allow robots to perceive their surroundings via radio frequency signals rather than light or visual cues; as a result, they can perceive their surroundings in low light, changing light, and repetitive environments. UCSD's Aditya Arun said, "Wi-Fi sensing could potentially replace expensive LiDARs [light detection and ranging], and complement other low-cost sensors such as cameras in these scenarios."
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This Bandage-Like Tracker Could Shed Light on Your Insomnia
CNN Business
Milly Chan
May 18, 2022
An at-home sleep tracker designed by the Israeli startup X-trodes attaches to the skin like an adhesive bandage and is equipped with sensors to track muscle activity, eye movement, and brain waves while the user sleeps. The tracker is wireless and transmits data to a smart device for analysis by the X-trodes software, with a report of its results sent to the user's physician. The device could lower the cost of sleep testing by 90% by eliminating the need for a technician to be involved and for subjects to stay overnight in a lab. X-trodes' Ziv Peremen said the home test could generate more accurate results given that factors like the user's partner, room temperature, and external noise are taken into consideration.
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Intelligent Software for 3D Printing Optimizes Plastic Components
TU Kaiserslautern (Germany)
May 19, 2022
Scientists at Germany's Technische Universität Kaiserslautern (TUK) have designed software to optimize three-dimensional (3D) printers for the production of plastic components. The software can adjust parameters like the print nozzle's temperature and printing speed, depending on the configuration of the component and the type of plastic used. Samples 3D-printed with the new software have a structure distinct from those fabricated with conventional software. "There is also a difference in the properties, especially in the tensile strength across the direction of printing," said TUK's Miaozi Huang. "This method allows the weak points in the printed products to be eliminated."
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Next-Generation Weather Reporting: Versatile, Flexible, Economical Sensors
Osaka Metropolitan University (Japan)
May 13, 2022
A team of scientists from Japan's Osaka Metropolitan University (OMU) and University of Tokyo have developed a multitasking weather sensor that measures rain volumes and wind speeds. The lightweight sensor sheet incorporates machine learning reservoir computing to analyze the output data, and can rapidly deliver localized weather data. The sensor quantifies rain volume by measuring the electrical resistance produced by raindrop impacts, and derives wind speed measurements from water droplet behavior. The sensors detect resistance changes triggered by shifting rain and wind conditions, then record them as time-series data; the researchers fed this data to the machine, which yielded rain volume and wind speed data. "The findings open up a promising economical approach to weather reporting, contributing to disaster preparedness and greater community safety," said OMU's Kuniharu Takei.
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Amphibious Drone Hitchhikes Like Suckerfish
Popular Science
Charlotte Hu
May 18, 2022
Engineers at China's Beihang University, the U.K.'s Imperial College London, and the Swiss Federal Laboratories for Materials Science and Technology in Switzerland collaborated on the modeling of an amphibious drone after the remora, or suckerfish. The drone can fly, swim, and adhere to surfaces in the air or in the water. The researchers three-dimensionally printed a prototype oval disc with a gill-like grid structure and multiple layers to mimic the remora's adhesion mechanism; they mated the disc to a hybrid aerial-aquatic quadcopter robot, which included passive morphing propellers that fold in water and unfold in air.
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Algorithms Empower Metalens Design
Harvard University John A. Paulson School of Engineering and Applied Sciences
Leah Burrows
May 16, 2022
Researchers from Harvard University and the Massachusetts Institute of Technology (MIT) have developed a method of using machine intelligence to generate designs for large-scale metasurfaces. The researchers developed a program that automatically generates metasurface designs using the foundation of physics, simultaneously designing millions to billions of parameters. The program employs an inverse design process, with researchers identifying the desired function of the metalens and the algorithm determining the best design geometries to achieve the goal. Said MIT's Steven G. Johnson, "This is an orders-of-magnitude increase in the scale of inverse design for nanostructured photonic devices, generating devices tens of thousands of wavelengths in diameter compared to hundreds in previous works, and it opens up new classes of applications for computational discovery."
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Seeing is Deceiving
University of Tokyo (Japan)
May 18, 2022
Toshihiko Yamasaki and Kaede Shiohara at Japan's University of Tokyo (UTokyo) have trained algorithms on self-blended images to better spot deepfake images and video. Typical training involves pairing unmanipulated source images with doctored images, which limits detection to certain types of visual artifacts. The UTokyo researchers used training sets comprised of synthesized images in order to control these artifacts, and to subsequently better train detection algorithms to find aberrations. They found the modified datasets improved accurate detection rates by up to 12%, depending on the original dataset to which they were compared. Yamasaki said the method works best on still images, but he envisions that "in the near future, this kind of research might work its way onto social media platforms and other service providers so that they can better flag potentially manipulated images with some kind of warning."
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