Welcome to the August 4, 2021 edition of ACM TechNews, providing timely information for IT professionals three times a week.

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Do You Hear What I Hear? A Cyberattack.
Carnegie Mellon University CyLab Security and Privacy Institute
Daniel Tkacik
July 30, 2021

Carnegie Mellon University's Yang Cai and colleagues have designed a method of making abnormal network traffic audible by rendering cybersecurity data musically. The researchers explored several sound mapping algorithms, converting numeral datasets into music with diverse melodies, harmonies, time signatures, and tempos. They produced music using network traffic data from an actual malware distribution network, and presented it to non-musicians, who could accurately identify pitch shifts when played on different instruments. Said the researchers, "We are not only making music, but turning abstract data into something that humans can process." Said Cai, “The process of sonification—using audio to perceptualize data—is not new, but sonification to make data more appealing to the human ear is.”

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Running Quantum Software on a Classical Computer
EPFL (Switzerland)
Nik Papageorgiou
August 3, 2021

Researchers at the Swiss Federal Institute of Technology Lausanne (EPFL) in Switzerland and Columbia University have developed a method of using a traditional computer to simulate the Quantum Approximate Optimization Algorithm (QAOA). The approach employs a classical machine learning algorithm that acts like near-term quantum computers. The researchers used an artificial neural network previously co-developed by EPFL's Giuseppe Carleo to simulate QAOA, which is considered a promising candidate for "quantum advantage" in near-term quantum computers. Said Carleo, "This does not mean that all useful quantum algorithms that can be run on near-term quantum processors can be emulated classically. In fact, we hope that our approach will serve as a guide to devise new quantum algorithms that are both useful and hard to simulate for classical computers."

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Lawrence Livermore National Laboratory engineers have 3D-printed carbon flow-through electrodes from graphene aerogels. LLNL Optimizes Flow-Through Electrodes for Electrochemical Reactors with 3D Printing
Lawrence Livermore National Laboratory
August 2, 2021

Lawrence Livermore National Laboratory (LLNL) scientists three-dimensionally (3D) printed carbon flow-through electrodes (FTEs) for electrochemical reactors from graphene aerogels. The researchers demonstrated the ability to customize FTE flows and drastically enhance reactant transfer from electrodes onto reactive surfaces, optimizing electrochemical reactions. Said LLNL's Swetha Chandrasekaran, "By 3D-printing advanced materials such as carbon aerogels, it is possible to engineer macroporous networks in these materials without compromising the physical properties such as electrical conductivity and surface area." LLNL's Anna Ivanovskaya said the method should enable engineers "to design and manufacture structures optimized for specific processes."

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A reconstruction of cells from the MICrONS data set shows the complexity of shapes and branching axons and dendrites in a mouse brain. Scientists Share Wiring Diagram Tracing Connections for 200,000 Mouse Brain Cells
Alan Boyle
July 29, 2021

A multi-institutional team of neuroscientists spent five years and $100 million developing a high-resolution model detailing the connections between 200,000 mouse brain cells. Created under the federally-funded Machine Intelligence From Cortical Networks (MICrONS) program, the dataset encompasses 120,000 neurons and about 80,000 other types of brain cells in a cubic millimeter of a mouse brain's visual neocortex. The researchers recorded neural activity patterns as the mouse watched images or films of natural scenes, then captured 150 million images of fractionated brain tissue using electron microscopes. Each cell and its internal structure were mapped using machine learning techniques. R. Clay Reid at Seattle’s Allen Institute for Brain Science said, "The final step is to interpret this network, at which point we may be able to say we can read the brain's program."

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A Census worker in the midst of an interview. Census Data Change to Protect Privacy Rattles Researchers, Minority Groups
The Wall Street Journal
Paul Overberg; Sarah Chaney Cambon
August 2, 2021

The U.S. Census Bureau will use a complex algorithm to adjust 2020 Census statistics to prevent the data from being recombined to disclose information about individual respondents. The bureau's Ron Jarmin said it will use differential privacy, an approach it has long employed in some fashion, which involves adding statistical noise to data. Small random numbers, both positive and negative, will be used to adjust most of the Census totals, with inconsistent subtotals squared up. The Bureau indicated that for most groups and places, this will result in fairly accurate totals, although distortion is likely to be higher for smaller groups and areas like census blocks. This has raised concerns among local officials, as population-based formulas are used to allocate billions of dollars in federal and state aid. University of Minnesota researchers said after a fifth test of the method that "major discrepancies remain for minority populations."

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A worker operates a metal cutting machine at Gent Machine Co.'s factory in Cleveland, OH. Robot Apocalypse Hard to Find in America's Small, Mid-Sized Factories
Timothy Aeppel
August 2, 2021

Although analysts have warned that millions of blue-collar jobs in the U.S. industrial heartland will soon be displaced by robots, that is not yet the case at small and medium-sized factories. Massachusetts Institute of Technology (MIT) researchers studied 34 companies with 500 or fewer employees in Ohio, Massachusetts, and Arizona, and found just one had acquired a significant number of robots in the past five years. MIT's Anna Waldman-Brown said, "The bulk of the machines we saw were from before the 1990s," and many older machines were upgraded with new computer controllers. Other companies have purchased advanced equipment like computer-guided cutting machines and inspection systems, but not robots, the researchers found, because smaller companies lack the money for robots or the skilled workers necessary to operate them.

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Insulator-Conductor Transition Points Toward Ultra-Efficient Computing
IEEE Spectrum
Dexter Johnson
July 30, 2021

A team of researchers has imaged the movement of atoms in a computer switch turning on and off in real time, which could help lead to super-efficient computing. Researchers at the U.S. Department of Energy's SLAC National Accelerator Laboratory, Stanford University, Hewlett Packard Labs, Pennsylvania State University, and Purdue University used the method to detect a short-lived transition stage between insulator-conductor flipping in a vanadium dioxide switch. The ultrafast electron diffraction technique uses electrical rather than optical pulses to supply the impulsive atomic excitation, exposing atomic-scale motions on fast timescales and measuring current through the device. Stanford's Aditya Sood said, "We now have a direct way to correlate very fast atomic movements at the angstrom scale with electronic flow across device length scales."

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The algorithm’s deconstruction of a wooden stool. AI Carpenter Can Recreate Furniture From Photos
New Scientist
Krista Charles
July 29, 2021

An algorithm developed by University of Washington (UW) researchers can render photos of wooden objects into three-dimensional (3D) models with enough detail to be replicated by carpenters. The researchers factored in the geometric limitations of flat sheets of wood and how wooden parts can interlock. They captured photos of wooden items with a smartphone, and the algorithm generated accurate plans for their construction after less than 10 minutes of processing. Said UW's James Noeckel, "It doesn’t really require that you observe the object completely because we make these assumptions about how objects are fabricated. We don’t need to take pictures of every single surface, which is something you would need for a traditional 3D reconstruction algorithm to get complete shapes."

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Developers Reveal Programming Languages They Love, Dread
Liam Tung
August 3, 2021

Programmer online community Stack Overflow's 2021 survey of 83,439 software developers in 181 countries found the vast majority (86.69%) named Mozilla's Rust their "most loved" language. Those respondents cited Rust as the language they worked with the most in the past year, and with which they most want to work with next year. Rust is popular for systems programming, and is under consideration for Linux kernel development, partly because it can help remove memory-related security flaws. Though deemed most loved, Rust was nominated to the survey by just 5,044 developers, while 18,711 respondents nominated Microsoft's TypeScript, the third most "loved" language; TypeScript compiles into JavaScript and helps developers more efficiently program large front-end Web applications. More developers dreaded (66%) than loved (39.56%) the widely-used C language, while Java also had fewer champions (47%) than those opposed dreading its use (52.85%).

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Apps That Are Redefining Accessibility
Bloomberg CityLab + Equality
Hadriana Lowenkron
July 29, 2021

Some estimate less than 10% of websites are accessible, meaning they provide assistance in accessing their content to people with visual disabilities. Some companies are tackling the issue by rolling out apps that can be used by anyone, regardless of visual capabilities. One example is Finnish developer Ilkka Pirttimaa, whose BlindSquare app incorporates Open Street Map and Foursquare data to help the visually impaired navigate streets; the app also integrates with ride-hailing apps like Uber. The Be My Eyes app connects visually impaired individuals to sighted volunteers via live video calls for assistance with everyday tasks, while the AccessNow app and website map and reviews locations on their accessibility. AccessNow’s Maayan Ziv said, “Accessibility is one more way in which you can invite people to be part of something, and it really does touch every kind of industry.”

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Security Bug Affects Nearly All Hospitals in North America
Anthony Spadafora
August 2, 2021

Researchers at security firm Armis identified nine critical vulnerabilities in the Nexus Control Panel that powers all current models of Swisslog Healthcare's Translogic pneumatic tube system (PTS) stations. The Translogic PTS system is used in 3,000 hospitals worldwide and 80% of major hospitals in North America to deliver medications, blood products, and lab samples across multiple hospital departments. Hackers can exploit the vulnerabilities, dubbed PwnedPiper, to gain control over a hospital's pneumatic tube network, with the potential to launch ransomware attacks. Armis' Ben Seri said his firm had told Swisslog of the vulnerabilities at the beginning of May, “and has been working with the manufacturer to test the available patch and ensure proper security measures will be provided to customers."

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Platform Teaches Nonexperts to Use ML
Cornell Chronicle
Louis DiPietro
July 28, 2021

An interactive machine learning (ML) platform developed by Cornell University scientists is designed to train nonexperts to use algorithms effectively, efficiently, and ethically. Cornell's Swati Mishra said, "If we design machine learning tools correctly and give enough agency to people to use them, we can ensure their knowledge gets integrated into the machine learning model." Said Cornell's Jeff Rzeszotarski, "While our eventual goal is to help novices become advanced machine-learning users, providing some 'training wheels' through transfer learning can help novices immediately employ machine learning for their own tasks." Added Mishra, “We as researchers and designers have to mitigate user perceptions of what machine learning is. Any interactive tool must help us manage our expectations.”

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