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Welcome to the November 17, 2021 edition of ACM TechNews, providing timely information for IT professionals three times a week.

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Rice University’s Ashumali Shrivastava (left) and Ben Coleman discovered an inexpensive way to implement rigorous personal data privacy when using or sharing large databases for machine learning. Big Data Privacy for ML Just Got 100 Times Cheaper
Rice University News
Jade Boyd
November 16, 2021


Rice University's Anshumali Shrivastava and Ben Coleman have developed RACE (repeated array of count estimators), an inexpensive technique to ensure personal data privacy when using or sharing large databases for machine learning (ML). The researchers applied locality sensitive hashing to generate abstracts or "sketches" of a huge database of sensitive records. Coleman said RACE sketches are safe for public release and useful for algorithms that employ kernel sums, and for ML programs that execute common tasks like classification, ranking, and regression analysis. Said Shrivastava, "RACE changes the economics of releasing high-dimensional information with differential privacy. It's simple, fast, and 100 times less expensive to run than existing methods."

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Researchers Develop Rapid Computer Software to Track Pandemics as They Happen
Georgia State University
November 16, 2021


The Scalable PHylogEny with Recurrent mutations (SPHERE) algorithm developed by Georgia State University (GSU) scientists can help countries track and analyze pandemics as they happen, in real time. The researchers said the algorithm can process more than 200,000 novel virus genomes in under two hours, then plot a visual evolutionary tree of the strains and their propagation. When applied to genomes from the global GISAID database, the SPHERE approach proved highly reliable in tracking the spread of the SARS-CoV-2 virus. GSU's Alexander Zelikovsky said, "We can see how the mutations spread from country to country and region to region. We can determine how lockdowns and closures impact spread."

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IBM has made a 127-qubit quantum computer. IBM Creates Largest Superconducting Quantum Computer
New Scientist
Matthew Sparkes
November 15, 2021


IBM said it has built the world's largest superconducting quantum computer, capable of assembling 127 superconducting quantum bits (qubits) through its new Eagle processor. The system is more than double the size of Google's 54-qubit Sycamore processor and the University of Science and Technology of China's 60-qubit Zuchongzhi processor. IBM's Bob Sutor said, "With Eagle, we're demonstrating that we can scale, that we can start to generate enough qubits to get on a path to have enough computation capacity to do the interesting problems. It's a stepping stone to bigger machines."

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Randomly Connected Neural Network for Self-Supervised Monocular Depth Estimation
Imperial College London (U.K.)
Erh-Ya Tsui
November 15, 2021


Researchers at the U.K.'s Imperial College London (ICL) designed a self-supervised monocular depth estimation technique using a randomly connected neural network. ICL's Sam Tukra said the random network connections "can attain a unique powerful architecture for the specific task,” such as depth estimation in surgery. The researchers modeled the networks as graphs and linked nodes using a random graph generator algorithm. They rendered the graphs into a neural network within a deep learning library, and the resulting framework can augment the use of deep semantic features in encoder feature maps. The researchers also formulated a new loss function to enhance image reconstruction quality; performance evaluation on surgical datasets confirmed the technique's efficacy.

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By systematically testing 40 devices, researchers from the ETH Computer Security Group and partners discovered a serious hardware vulnerability affecting mobile phones, PCs, and laptops. Security Vulnerabilities in Computer Memories
ETH Zurich (Switzerland)
Oliver Morsch
November 15, 2021


A team of researchers from the Swiss Federal Institute of Technology, Zurich (ETH Zurich), the Netherlands' Vrije Universiteit Amsterdam, and semiconductor manufacturer Qualcomm Technologies identified major security flaws in dynamic random-access memory (DRAM) devices. ETH Zurich's Kaveh Razavi said the Rowhammer vulnerability in DRAMs, exploited by hackers to induce bit errors and access restricted areas inside the computer, remains unaddressed. Countermeasures designed to neutralize Rowhammer merely detect simple attacks. Razavi said the researchers' Blacksmith software, which systematically applies complex hammering patterns, found a successful exploit in each of 40 DRAM memories tested. This means current DRAM memories could remain hackable by Rowhammer attacks for years to come.

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As Ji Hyun Nam slowly tosses a stuffed cat toy into the air, real-time video captures the playful scene. Real-Time Video of Scenes Hidden Around Corners Now Possible
University of Wisconsin-Madison News
Eric Hamilton
November 11, 2021


Researchers at the University of Wisconsin-Madison (UW) and Italy's Polytechnic University of Milan have created a non-line-of-sight imaging technique that can display video of hidden scenes in real time. The technique combines ultra-fast and highly sensitive light sensors with an advanced video reconstruction algorithm. The method captures information about a scene by bouncing light off a surface and detecting the echoes of that light as it bounces back; it sees around corners by detecting the reflections of those echoes. UW’s Andreas Velten said, “It’s basically echolocation, but using additional echoes—like with reverb.”

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Supercomputer Simulations Provide Clue to Missing Planets Mystery
SciTechDaily
November 14, 2021


Multi-institutional researchers in Japan used the world's most powerful astronomical supercomputer to simulate a planet moving away from its initial formation site, adding credibility to a theory about missing planets in ring formation. The National Astronomical Observatory of Japan's ATERUI II system generated the simulation, from which the researchers identified three distinct phases of planetary migration affecting rings of gas and dust in the protoplanetary disks of young stars. The results offer clues as to why planets are rarely observed near the outer rings, and the phases within the models correspond with patterns seen in actual rings.

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UBC Researchers Train Computers to Predict Next Designer Drugs
University of British Columbia (Canada)
November 15, 2021


Scientists at Canada's University of British Columbia (UBC) have trained computers to predict designer drugs, to help law enforcement agencies worldwide identify and regulate them faster. UBC's Michael Skinnider and colleagues trained a deep neural network on drug structure using a global database of known psychoactive drugs supported by forensic laboratories worldwide. The model produced about 8.9 million potential designer drugs, which were tested against 196 new substances that emerged on the black market afterward; over 90% were within the generated set. Said Skinnider, "Essentially, our software gives law enforcement agencies and public health programs a head start on the clandestine chemists, and lets them know what to be on the lookout for."

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Redefine Meat Brings 3D-Printed Vegan Cuts to Restaurants
Financial Times
Emiko Terazono
November 16, 2021


Israeli startup Redefine Meat has unveiled a three-dimensionally (3D)-printed plant-based meat and is making whole “cuts” of the foodstuff available in restaurants in Israel and Europe. The company can 3D-print 10 kilograms (22 pounds) of vegan meat per hour, using soy and pea protein, chickpeas, beetroot, yeast, and coconut fat as ingredients. Redefine Meat’s Eschar Ben-Shitrit said, “Most of the crops produced go to animal feed. We have a genuine solution that today, not in 2030, preserves all the culinary aspects of meat we know and love, but eliminates cattle as a means of production.”

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University of California, Irvine’s Peter Tseng (left) and Amirhossein Hajiaghajani show the innovative fabric that enables digital communication between wearers and nearby devices. UCI Invention Lets People Pay with a High-Five
UCI News
November 16, 2021


A battery-free body area network engineered by University of California, Irvine (UCI) researchers integrates advanced metamaterials into flexible textiles to facilitate communication between garments and nearby devices. "You could potentially keep your phone in your pocket, and just by brushing your body against other textiles or readers, power and information can be transferred to and from your device," said UCI's Peter Tseng. The researchers extended the network's signal reach beyond four feet using passive magnetic metamaterials built from etched copper-aluminum foils. UCI's Amirhossein Hajiaghajani said the network could enable secure payments with a single touch or swipe of a sleeve.

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Stanford Researchers Using AI to Create Better VR Experiences
Stanford News
Allison Gasparini
November 12, 2021


Stanford University researchers have combined optics and artificial intelligence to improve holographic displays for virtual and augmented reality experiences. The researchers developed a technique for reducing speckling distortion typical of laser-based holographic displays, and proposed a method to more realistically portray the physics of a virtual three-dimensional scene as if it were actual. The neural holographic display required the training of a neural network to mimic the real-world physics of what the display depicted and achieve real-time images. The researchers combined this with camera-in-the-loop calibration to deliver near-instantaneous feedback, resulting in more realistic-looking visuals with enhanced color, contrast, and clarity.

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DHS Program to Attract, Retain Cybersecurity Talent
The Hill
Maggie Miller
November 15, 2021


The U.S. Department of Homeland Security (DHS) has launched a program to find and hire cybersecurity professionals. The federal agency will use the Cyber Talent Management System (CTMS) to simplify and screen the application process. Candidates hired through CTMS will join the DHS Cybersecurity Service, focused on shielding critical infrastructure from cyberattacks. The program will be used to fill vacancies at DHS' Cybersecurity and Infrastructure Security Agency and the DHS Office of the Chief Information Officer, and will help to fill vacancies at other DHS entities starting next year. Said DHS Secretary Alejandro Mayorkas, "This new system will enable our department to better compete for cybersecurity professionals and remain agile enough to meet the demands of our critical cybersecurity mission."

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Algorithms Advance Computing Power of Early-Stage Quantum Computers
Ames Laboratory
November 9, 2021


Newly developed computational quantum algorithms can produce highly accurate models of static and dynamic properties in quantum systems. Scientists at the U.S. Department of Energy's Ames Laboratory developed the algorithms to operate on existing and near-future quantum computers, in order to solve complex materials science challenges. The algorithms harness existing quantum computer capabilities by adaptively producing and customizing the number and variety of educated guesses the computer must make to accurately describe a system's lowest-energy state and evolving quantum mechanics. The scalable algorithms can simulate larger systems accurately with existing error-prone quantum computers and their near-future successors. Ames' Peter Orth said the long-term goal "is to reach 'quantum advantage' for materials—to utilize quantum computing to achieve capabilities that cannot be achieved on any supercomputer today."

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