Welcome to the December 9, 2019 edition of ACM TechNews, providing timely information for IT professionals three times a week.
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Emotion-Sensing Robot Launches to Assist Space Station Astronauts
Reuters
Joey Roulette
December 5, 2019
A robot with emotion-sensing voice detectors has been launched to the International Space Station. The spherical Crew Interactive Mobile Companion 2 (CIMON 2) features microphones, cameras, and software to facilitate emotion recognition. The English-speaking robot uses algorithms from IBM and data gathered by its CIMON 1 predecessor to be more sociable with astronauts; it will test technologies that could play an essential role in future manned deep-space missions. CIMON 2 also is programmed to compensate for groupthink behavior, which may arise when teams of people are isolated and make irrational decisions. CIMON 2 lead architect Matthias Biniok said in times of conflict or disagreement, the robot would function as an "objective outsider that you can talk to if you're alone or could actually help let the group collaborate again."
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Researchers Uncover Russian-Style Information Operation Ahead of U.K. Elections
The Washington Post
Cat Zakrzewski
December 3, 2019
Graphika, a cyber-intelligence firm, discovered a campaign on Reddit and Twitter to disseminate leaked trade documents ahead of the upcoming elections in the U.K. The campaign is similar to a Russian-linked disinformation effort identified earlier this year. The online effort mostly targets British politicians, celebrities, and journalists with a portfolio of documents appearing to detail key U.S.-U.K. trade negotiations. Ben Nimmo of Graphika said it was not clear whether those behind the campaign were Russian, or just trying to imitate previous Russian information campaigns. Ultimately, said Nimmo, "Influencers, politicians, journalists need to be aware of the fact that they are going to be personally targeted by information operations."
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Hand-Tracking Tech Watches Riders in Self-Driving Cars to See If They're Ready to Take the Wheel
IEEE Spectrum
Michelle Hampson
December 5, 2019
Researchers at the University of California, San Diego developed a hand-tracking system drivers to determine how long it would take a driver to assume control of a self-driving car in an emergency. The researchers took an existing program for tracking full-body movements and adapted it to focus on the wrists and elbows of the vehicle’s driver and also a front-seat passenger, if present. The team developed and applied machine learning algorithms to train the system to support Level 3 autonomous technology, then trained it with 8,500 annotated images. The researchers found the system was able to identify the location of each of eight elbow and wrist joints of both the driver and passenger with 95% accuracy, although it had a localization error of 10% when estimating the average length of driver or passenger arms.
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A World With a Billion Cameras Watching You Is Just Around the Corner
The Wall Street Journal
Liza Lin; Newley Purnell
December 6, 2019
Industry researcher IHS Markit expects the number of cameras used for surveillance to rise above 1 billion by the end of 2021, marking an almost 30% increase from the 770 million such cameras in use today. China will continue to account for more than 50% of the total, but fast-growing, populous nations such as India, Brazil, and Indonesia also will help to drive growth in the sector. The global security camera industry has been spurred by developments in image quality and artificial intelligence (AI), technologies that allow better and faster facial recognition and video analytics. While “coverage of the surveillance market has focused heavily on China's massive deployments of cameras and AI technology,” observed IHS analyst Oliver Philippou, “future debate over mass surveillance is likely to concern America as much as China."
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Zip Software Can Calculate the Complex Physical Quantity Called Entropy
American Friends of Tel Aviv University
December 4, 2019
Researchers at Tel Aviv University (TAU) in Israel have proposed using a standard compression algorithm like zip software to calculate entropy, a measure of the molecular disorder of a system. TAU's Roy Beck said this method could deliver insights on the physical characteristics of diseased proteins by calculating their entropy values. The technique stems from researchers' modeling of standard physical systems with comparable entropy values, which determined that the simulation data file size following compression rises and falls as entropy is expected to do. The researchers found they could convert the compressed file size into a usable physical entropy value which was valid for all examined systems. Beck said the algorithm would be simple to use on any computer for a wide variety of research.
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CIT Researchers Develop System to Detect Cloud-Based Cybercrime Evidence
Purdue University News
John O'Malley
December 4, 2019
Researchers at the Purdue Polytechnic Institute's Department of Computer and Information Technology (CIT) have developed a forensic model that uses machine learning to collect digital evidence related to unlawful activities on cloud storage apps. The technology performs real-time identification and analysis of cybercrime-related incidents via transactions uploaded to the apps. An app user uploading a media file causes the system to implement deep learning models to scan images for cybercrime evidence and report illegal activities through a forensic evidence collection system. Cloud service providers can compile alert logs, block associated accounts, and notify law enforcement based on a cloud search warrant request. CIT's Fahad Salamh said, "It is important to automate the process of digital forensic and incident response in order to cope with advanced technology and sophisticated hiding techniques and to reduce the mass storage of digital evidence on cases involving cloud storage applications."
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A Few Cities Have Cornered Innovation Jobs. Can That Be Changed?
The New York Times
Eduardo Porter
December 9, 2019
A report from the Brookings Institution's Metropolitan Policy Program and the Information Technology and Innovation Foundation found that 13 innovation industries were mainly sited in a handful of urban areas in the U.S. Boston, Seattle, San Diego, San Francisco, and Silicon Valley were home to 90% of jobs created in these sectors from 2005 to 2017, while jobs in those sectors were lost by about 50% of the country's 382 metro areas. The report's authors agreed the federal government needs to propel innovation beyond the 20 currently dominant metro areas, and identified midsize cities like Pittsburgh and Columbus, OH, as feasible technology hubs. Their proposal is to choose up to 10 such cites with research universities and a critical mass of advanced degree-holders and have the federal government invest about $700 million annually in research and development in each city over a 10-year period.
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Developing a Digital Twin
Oden Institute for Computational Engineering and Sciences (University of Texas at Austin)
December 4, 2019
Researchers at the University of Texas at Austin's Oden Institute for Computational Engineering & Sciences, the Massachusetts Institute of Technology, Akselos, and Aurora Flight Sciences are developing a predictive digital twin for a custom-built unmanned aerial vehicle (UAV). The twin, described by Oden director Karen Willcox at the 2019 International Conference for High Performance Computing, Networking, Storage and Analysis (SC19), uses physics-based models that capture the details of its behavior to represent each component of the UAV, as well as its integrated whole. The twin also analyzes on-board sensor data from the UAV and integrates that with the model to create real-time predictions of the health of the vehicle. The team paired computational modeling with machine learning to produce predictions that are reliable and explainable. Learning from data "brings together the methods and the approaches from the fields of data science, machine learning, and computational science and engineering, and directs them at high-consequence applications," said Willcox.
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Designing and Repurposing Cell Receptors
EPFL News (Switzerland)
December 2, 2019
Scientists at the Swiss Federal Institute of Technology, Lausanne (EPFL) have created a computational technique for modeling and designing protein allostery to enable precise, rational engineering and repurposing of cell receptors. The researchers modeled G protein-coupled receptors (GPCRs) with molecular dynamics simulations and identified allosteric sites on the dopamine receptor. The researchers then rapidly evolved in-silico protein sequences for specific dynamic and allosteric characteristics to engineer allosteric variants of a GPCR and repurpose allosteric signaling properties. The technique supports rational design to anticipate how the new molecule's structure and dynamics will impact its behavior. EPFL's Patrick Barth said, "Our work ... sets the stage for designing signaling receptors with precise functions for cell-engineering approaches and predicting the effects of genetic variations on protein functions for personalized medicine, as well as designing new allosteric proteins and better drugs from scratch."
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Researchers Develop Tool to Predict Infectious Disease Spread
iTWire
Peter Dinham
December 5, 2019
Researchers at Australia’s Commonwealth Scientific and Industrial Research Organization, Queensland University of Technology, and Queensland Health have developed a tool to forecast the spread of human infectious diseases like dengue, as well as tracing them to their source. The tool taps data from the International Air Transportation Association and dengue incidence rates from the Global Health Data Exchange to map how disease travels internationally, and calculates infections that are imported into different countries every month. Queensland Health's Cassie Jansen said, "This provides a useful tool to assist public health authorities with dengue preparedness. It can also help authorities to identify those locations where new dengue outbreaks may occur, following the arrival of infected passengers."
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3D Printing Offers Hope of Building Human Organs From Scratch
Financial Times
Michael Pooler
December 8, 2019
This year has witnessed advances in three-dimensional (3D) printing of organic tissue, including an announcement from scientists in Israel of the creation of perfusable cardiac tissue that was able to beat. This achievement involved reprogramming fatty-tissue cells into pluripotent stem cells cultured into cardiac muscle via growth-factor molecules. Meanwhile, researchers at the U.K.'s University of Edinburgh have been designing bioprinted implantable tissue to treat diseased livers by converting stem cells into spherical material that can survive in culture for more than a year; the ultimate goal is an implantable graft. Edinburgh's David Hay expects 3D-printed skin to become the first clinically established bioprinting application.
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A Trick for Taming Terahertz Transmissions
Research at Osaka University
December 2, 2019
Researchers at Osaka University (OU) in Japan have unveiled a terahertz detector that allows rapid wireless data communication and sensitive radar via a complex frequency range. The detector facilitated a record 30-gigabit-per-second error-free transmission in real time, which could clear a path for 6G cellular network technology. The device employs a resonant tunneling diode whose specific resonant voltage yields the peak current rather than currents that rise at larger voltages, as with conventional electronics; the researchers synchronize the terahertz signals with an internal electronic oscillator, then partition the data from the carrier wave to augment sensitivity. OU's Masayuki Fujita said, "This technology can be put to work in a wide range of applications, in addition to next-generation 6G wireless communication. These include spectroscopic sensing, non-destructive inspection, and high-resolution radar."
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