MS In Computer Science
Welcome to the June 16, 2021 edition of ACM TechNews, providing timely information for IT professionals three times a week.

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BSC Researcher Receives HPDC Achievement Award 2021
June 15, 2021

The International ACM Symposium on High-Performance Parallel and Distributed Computing (HPDC) named Rosa M. Badia of Spain's Barcelona Supercomputing Center (BSC) recipient of the HPDC Achievement Award 2021. Badia, the first researcher working in Europe to receive the award, is considered a key innovator in parallel programming models for multicore and distributed computing, thanks to her work with task-based programming models. As manager of BSC's Workflows and Distributed Computing research group, Badia supervises investigation into PyCOMPSs/COMPSs, a parallel task-based programming distributed computing model, and its application to the development of large heterogeneous workflows integrating high-performance computing (HPC), big data, and machine learning. Badia also coordinates the EuroHPC project eFlows4HPC, which she said focuses on "making easier the development of applications for complex computing platforms."

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WWW Code That Changed the World Up for Auction as NFT
Guy Faulconbridge
June 15, 2021

Computer scientist Tim Berners-Lee's original source code for what would become the World Wide Web now is part of a non-fungible token (NFT) that Sotheby's will auction off, with bidding to start at $1,000. The digitally signed Ethereum blockchain NFT features the source code, an animated visualization, a letter by Berners-Lee, and a digital poster of the code from the original files, which include implementations of the three languages and protocols that Berners-Lee authored: Hypertext Markup Language (HTML), Hypertext Transfer Protocol (HTTP), and Uniform Resource Identifiers. Berners-Lee said the NFT is "a natural thing to do ... when you're a computer scientist and when you write code and have been for many years. It feels right to digitally sign my autograph on a completely digital artifact."

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National Science Foundation director Sethuraman Panchanathan. U.S. Task Force to Study Opening Government Data for AI Research
The Wall Street Journal
Ryan Tracy
June 10, 2021

The Biden administration’s new National Artificial Intelligence Research Resource Task Force is tasked with developing a strategy for making government data available to artificial intelligence (AI) scientists. The task force's 12 members hail from academia, government, and industry, and are supervised by officials at the White House Office of Science and Technology Policy (OSTP) and the U.S. National Science Foundation. The panel's strategy could provide researchers with secure access to anonymized data about Americans, as well as to the computing power needed to analyze the data. OSTP's Lynne Parker said the group intends to provide Congress with guidance for establishing a standard AI research infrastructure for non-governmental personnel.

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A rosy wolf snail marked and equipped with a Michigan Micro Mote computer system in the Fautaua-Iti Valley site in Tahiti. Snails Carrying World's Smallest Computer Help Solve Mass Extinction Survivor Mystery
University of Michigan News Service
Katherine McAlpine; Catharine June
June 15, 2021

University of Michigan (U-M) biologists and engineers used the world's smallest computer to learn how the South Pacific Society Islands tree snail Partula hyalina survived a mass extinction. Former U-M researcher Inhee Lee adapted the Michigan Micro Mote (M3) sensor to test the theory that P. hyalina survived the deliberate introduction of the predatory rosy wolf snail to its environment as attributable to its light-reflecting white shell. The researchers deployed 50 M3s in Tahiti, gluing some to rosy wolf snails while others were stuck on leaves harboring the P. hyalina, which rests in daytime. Lee wirelessly downloaded data from each M3 at the end of the day. Based on that data, the researchers suspect P. hyalina avoids predation because the rosy wolf snail will not venture far into its sunlight-heavy habitat.

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DNA-Based Storage System with Files and Metadata
Ars Technica
John Timmer
June 15, 2021

A new DNA-based system for storing images created by researchers at the Massachusetts Institute of Technology (MIT) and the Broad Institute encapsulates data-encoding DNA file sequences within silicon-dioxide glass beads that are surface-labeled with fluorescent single-stranded DNA tags. The tagged beads are blended into a data library that benefits from long-term stability and zero-energy maintenance. The researchers stored a keyword-associated archive of images in the DNA, with each keyword encoded in the DNA attached to the bead's surface. The system permits Boolean searches of multiple terms, and since each tag can be viewed as a piece of metadata about the DNA-stored image, the beads collectively function as a metadata-driven image database.

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Combining Classical, Quantum Computing Opens Door to Discoveries
University of Waterloo News (Canada)
June 15, 2021

Researchers at the University of Waterloo's Institute for Quantum Computing in Canada and Austria's University of Innsbruck have developed a resource-efficient technique for combining classical computing's reliability with quantum computing's robustness. The method couples a standard computer's processor and a quantum computer’s co-processor in a feedback loop to meet difficult computing challenges, using small quantum states customized to specific types of problems. The process utilizes an algorithm designed to execute hybrid quantum-classical computation by conducting a sequence of measurements on an entangled quantum state. The program has high error tolerance, and is applicable across a broad spectrum of quantum systems.

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A Big Step Towards Cybersecurity's Holy Grail
Carnegie Mellon University CyLab Security and Privacy Institute
Daniel Tkacik
June 15, 2021

Carnegie Mellon University (CMU) scientists have unveiled a provably secure computing environment that employs users' device communications to grant them immunity from compromised components. The researchers proposed an input/output (I/O) separation model that precisely describes mechanisms to safeguard the communications of isolated applications running on often-vulnerable operating systems like Windows, Linux, or MacOS. The CMU team said this is the first mathematically-proven model that enables communication separation for all types of I/O hardware and I/O kernels. CMU's Virgil Gilgor said, "Business, government, and industry can benefit from using this platform and its VDI [Virtual Desktop Infrastructure] application because of the steady and permanent shift to remote work and the need to protect sensitive applications from future attacks. Consumers can also benefit from adopting this platform and its VDI clients to secure access banking and investment accounts, perform provably secure e-commerce transactions, and protect digital currency."

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An impressionist painting by Worthington Whittredge. Computers Predict People's Tastes in Art
California Institute of Technology
Whitney Clavin
June 15, 2021

Researchers at the California Institute of Technology (Caltech) used a program to predict people's art preferences. The team recruited more than 1,500 volunteers via Amazon's Mechanical Turk crowdsourcing platform to rate paintings in various genres and color fields, then fed this data to the program. The researchers taught the computer to deconstruct a painting's visual properties into low-level features (contrast, saturation, and hue) and high-level features that require human evaluation. Caltech's Kiyohito Iigaya said the program combines these features to calculate how much a specific feature is accounted for when deciding on the artwork's appeal; afterwards, the computer can accurately forecast a person's preference for a previously unseen work of art. Caltech's John O'Doherty said the research reveals insights about the underpinnings of human aesthetic judgments, "that people appear to use elementary image features and combine over them."

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UW Researchers Can Turn a Single Photo into a Video
University of Washington News
Sarah McQuate
June 14, 2021

A new deep learning method can convert a single photo of any flowing material into an animated video running in a seamless loop. University of Washington (UW) researchers invented the technique, which UW's Aleksander Holynski said requires neither user input nor additional data. The system predicts the motion that was occurring when a photo was captured, and generates the animation from that information. The researchers used thousands of videos of fluidly moving material to train a neural network, which eventually was able to spot clues to predict what happened next, enabling the system to ascertain if and in what manner each pixel should move. The team's “systemic splatting” method forecasts both the future and the past for an image, then blends them into one animation.

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Eunice Santos, dean of the School of Information Sciences at the University of Illinois at Urbana-Champaign Model Helps Predict, Analyze Decision-Making on Adopting Type 2 Diabetes Medical Guidelines
University of Illinois News Bureau
Jodi Heckel
June 14, 2021

Researchers at the University of Illinois at Urbana-Champaign (UIUC), California State Polytechnic University, the University of Chicago, and the Illinois Institute of Technology have engineered a novel computational modeling and simulation framework to review decision-making and determine effective dissemination approaches for medical guidance. The Culturally Infused Agent Based Model (CI-ABM) embeds interactions and influences among healthcare workers, and other medical decision-making factors, to model and analyze a broad spectrum of real-world scenarios. The system can simulate real-world events and offer a way to account for uncertainty in human behavior. When they employed the model to analyze still-unadopted guidelines for individualized glycemic-control of Type 2 diabetes dating from 2012, the UIUC team found that healthcare workers' specialties, patient volume, and experience were factors contributing to their potential acceptance of such guidance.

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The digital twin of a delivery drone that suffers some minor wing damage. Creating 'Digital Twins' at Scale
MIT News
Becky Ham
June 14, 2021

The Massachusetts Institute of Technology (MIT)'s Michael Kapteyn and colleagues have designed a model for generating digital twins—precise computer simulations—at scale. The researchers tested the probabilistic graphical model in scenarios involving an unpiloted aerial vehicle (UAV). The model mathematically characterizes a pair of physical and digital dynamic systems connected via two-way data streams as they evolve; the parameters of the UAV's digital twin are initially aligned with data collected from the physical counterpart, to accurately reflect the original at the onset. This ensures the digital twin matches any changes the physical asset undergoes over time, and can anticipate the physical asset's future changes. Kapteyn said this simplifies the production of digital twins for a large number of similar physical assets.

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App Tracks Human Mobility, COVID-19
University of Miami
Deserae E. del Campo
June 14, 2021

The COVID-19 vs. Human Mobility Web application can map the coronavirus pandemic's global impact on human movement. The University of Miami's Shouraseni Sen Roy and Christopher Chapin based the interactive app on Apple Maps' dataset on human movement through walking, driving, and public transit; Oxford University's COVID-19 Government Response Tracker, detailing government policies deployed during the pandemic; and Johns Hopkins University's compiled global cases of COVID-19. Users can choose a country, or a U.S. state or county, and compare human mobility and coronavirus cases over time, as well as data on government policies associated with COVID-19's spread. Sen Roy said, "Understanding historic mobility patterns, both under normal circumstances and in response to extreme events like a pandemic or a natural disaster, is surely needed for policymakers to make informed decisions regarding transportation systems and more.”

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ML Can Reduce Worry About Nanoparticles in Food
Texas A&M Today
Vandana Suresh
June 15, 2021

Texas A&M University scientists used two machine learning (ML) algorithms to assess the properties of metallic nanoparticles that make their absorption by plants more likely. The team trained an artificial neural network and gene-expression programming on a database culled from previous research on metallic nanoparticles and the plants in which they had collected. The algorithms can accurately predict a given metallic nanoparticle's likelihood to accumulate in a plant species, and how its chemical composition influences the tendency for absorption among plants in a nutrient-rich or hydroponic medium. Texas A&M's Xingmao Ma said, "It is quite understandable that people are concerned about the presence of nanoparticles in their fruits, vegetables, and grains. But instead of not using nanotechnology altogether, we would like farmers to reap the many benefits provided by this technology but avoid the potential food safety concerns."

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