Welcome to the January 29, 2021 edition of ACM TechNews, providing timely information for IT professionals three times a week.

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Prashant Shenoy of the University of Massasachusetts Amherst. Shenoy Named ACM SIGEnergy Founding Chair
University of Massachusetts Amherst
January 27, 2021

University of Massachusetts Amherst (UMass Amherst) Distinguished Professor and associate dean in the College of Information and Computer Sciences Prashant Shenoy has been named founding chair of the new ACM Special Interest Group on Energy (SIGENERGY). ACM SIGENERGY, created by the conversion of ACM’s Emerging Interest Group on Energy Systems and Informatics (EIGEnergy) to a full-fledged Special Interest Group late last year, will assemble researchers from multiple computing disciplines to address the challenges of future energy systems and their impact on society. The group will manage two long-running research conferences—ACM e-Energy and BuildSys—as well as promoting energy-focused workshops and developing an energy informatics model curriculum. Said Shenoy, "We envision SIGENERGY as an interdisciplinary forum for researchers and practitioners who use computational methods and technologies to help decarbonize our society."

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A COVID-19 vaccination card Paper Cards, Digital Codes Target Vaccination Chaos
IEEE Spectrum
Jeremy Hsu
January 25, 2021

A coalition led by the Massachusetts Institute of Technology (MIT) has introduced an augmented vaccination card that works with or without online apps to ease the Covid-19 inoculation process. The card would feature quick response codes that can be applied as stickers to existing cards already circulated by the U.S. Centers for Disease Control and Prevention. These codes would incorporate encrypted data necessary for each vaccination stage that can be scanned by the relevant authorities—without storing personally identifiable information in central databases to protect privacy. The MIT team thinks the card could accelerate the process by removing paperwork needed to check on vaccination eligibility and status at pharmacies and clinics. MIT's Sanjay Sarma said, "The beauty of this is you let the logistics people do the logistics, and you let the issuing authority give you your coupon independently, and each can do it in a decoupled way."

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Starship Technologies delivery robots in the field. Robot Delivers the Dough on College Campuses
Greg Nichols
January 27, 2021

Delivery robot manufacturer and service provider Starship Technologies recently expanded its robot-based food delivery services to the campuses of the University of California, Los Angeles and Bridgewater State University in Massachusetts. Deals with college campuses allow the company to implement delivery services on behalf of on-campus dining options, with Starship using the campuses as testbeds while the schools promote their cutting-edge technology uptake. Starship’s iOS and Android apps lets users choose food or beverage items, then identify where they want the delivery sent; they can watch the robot's position on an interactive map. Upon the robot's arrival, customers use the app to unlock a secure compartment in the robot to get their order.

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U.S. Leading Race in AI, with China Rising: Survey
Times of India
January 25, 2021

A study of 2020 data by the Information Technology and Innovation Foundation confirmed the U.S. leads the world in the development and use of artificial intelligence (AI), with China rapidly gaining ground, and the European Union trailing. Analysis of metrics including human talent, research activity, commercial development, and hardware and software investment on the survey gave America a score of 44.6 points out of 100, with China following with a score of 32, and the EU scoring just 23.3. The U.S. is outspending rivals in startup investment and research and development funding, while China controls more of the world's 500 most powerful supercomputers (214) compared to the U.S. (113) and Europe (91). The foundation's Daniel Castro said both the U.S. and Europe should respond to China's progress, "because nations that lead in the development of and use of AI will shape its future and significantly improve their economic competitiveness."

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Honeywell’s quantum computer. BMW Takes First Steps Into Quantum Computing Revolution
Stephen Shankland
January 27, 2021

BMW is using a Honeywell quantum computer to determine which vehicle components to purchase from which supplier at what time, in order to maintain its production schedules while holding down costs. The quantum computer optimizes the automaker’s choices from numerous options and suboptions. While this marks one of the first real-world uses of quantum computing, BMW's Julius Marcea noted, "Our experts anticipate that it will take some more years until real quantum computers can be used for commercial benefit." Honeywell's Tony Uttley said within the next two years, quantum computers will be able to solve optimization problems classical computers cannot handle.

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Crowdsourced Maps Will Show Exactly Where Surveillance Cameras Are Watching
Fast Company
Mark Sullivan
January 26, 2021

Human rights organization Amnesty International plans to create a crowdsourced map pinpointing every surveillance camera enabled for facial recognition in New York City. Beginning in May, volunteers will be able to use an app on their smartphones to identify facial recognition cameras within their view; the app integrates Google Street View and Google Earth to help tag and affix geolocation data to those entries. The map will be part of Amnesty’s "Ban the Scan" campaign, designed to spread awareness worldwide on the civil rights perils of facial recognition. The organization hopes to launch similar crowdsourced mapping projects in New Delhi, the West Bank, and Ulaanbaatar, Mongolia, in the coming months.

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A fruit fly. Fruit Fly Brain Hacked for Language Processing
January 28, 2021

Yuchan Liang at the Rensselaer Polytechnic Institute, working with colleagues at that institution and at the MIT-IBM Watson AI Lab, hacked a fruit fly's neural network for tasks that include natural language processing. The team used a computer program to reconstruct the network on which the fruit fly brain's mushroom body sensory structure relies—projection neurons feeding data to roughly 2,000 Kenyon cells. The researchers then trained the network to identify correlations between words in text, and found its performance is comparable to that of artificial learning networks in natural language processing, while consuming fewer computational resources. The researchers said, "We view this result as an example of a general statement that biologically inspired algorithms might be more compute-efficient compared with their classical [non-biological] counterparts."

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A heat map superimposed on a NASA satellite image of Iceland. Anonymous Cellphone Data Can Quantify Behavioral Changes for Flu-Like Illnesses
Emory University
Carol Clark
January 26, 2021

A study by Emory University computer scientists found cellphone data routinely collected by telecommunications providers can expose behavioral changes in people diagnosed with flu-like illnesses, while also shielding their anonymity. In partnership with an Icelandic cellphone service provider and public health officials, the Emory team analyzed data for more than 90,000 encrypted phone numbers, constituting about 25% of Iceland's population. The researchers were allowed to link the encrypted cellphone metadata to 1,400 anonymous individuals diagnosed with a flu-like illness during the 2009 H1N1 outbreak. Individuals receiving a flu-like diagnosis changed their cellphone usage behavior an average of one day pre-diagnosis and two to four days afterward, making fewer calls from fewer unique locations and spending more time than usual on calls made the day following diagnosis. Emory's Ymir Vigfusson said, "Our work contributes to the discussion of what kinds of anonymous data lineages might be useful for public health monitoring purposes."

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An infographic illustrating how the Anveshak smart tracking platform works. Computer Vision Researchers Develop City-Scale Smart Tracking Platform
Jeremy Horwitz
January 25, 2021

The Anveshak (Hindi for "investigator") software platform developed by computer vision researchers at the Indian Institute of Science (IISc) is designed to track an object moving through a city without straining that city's limited computing resources. Anveshak can pinpoint the locations and overlap points of 1,000 camera feeds around a city, as well as the possible trajectories an object or person could follow through those feeds. The platform creates a "spotlight" on the tracked subject, dynamically adjusting its size based on known gaps in camera coverage, and can automatically degrade video quality to reduce bandwidth rather than stalling or stopping tracking. Anveshak also runs multiple wide-area networks that cities and enterprises are using, and lets users employ tailored tracking strategies, computer vision tools, and reusable algorithms.

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A 3D view of a multi-fault rupture from a synthetic earthquake. Simulating 800,000 Years of California Earthquake History to Pinpoint Risks
Texas Advanced Computing Center
Aaron Dubrow
January 25, 2021

Researchers at the University of Southern California's Southern California Earthquake Center (SCEC) have spent the past decade developing a framework to predict earthquake likelihood and impact, in order to determine risk. SCEC's Kevin Milner and Columbia University's Bruce Shaw evaluated the prototype Rate-State earthquake simulator (RSQSim) that models 800,000 years of seismic activity in California. RSQSim converts mathematical representations of earthquakes' geophysical forces into algorithms, then solves them using supercomputers at the Texas Advanced Computing Center. When paired with the CyberShake code, the RSQSim calculates the amount of shaking that would occur for each quake, and the results correlate well with historical temblors and outcomes of other methods, while displaying realistic distribution of quake probabilities. Milner said, "The hope is that these types of models will help us better characterize seismic hazard so we're spending our resources to build strong, safe, resilient buildings where they are needed the most."

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A deuteron shows the bound state of a proton (red) and neutron (blue). Supercomputers Aid Scientists Studying the Smallest Particles in the Universe
Oak Ridge National Laboratory
January 25, 2021

A team of scientists used the Oak Ridge National Laboratory's Summit supercomputer to measure quark interactions in hadrons, and applied the approach to simulations using quarks with close-to-physical masses. Oak Ridge's Bálint Joó used the Chroma software suite for lattice quantum chromodynamics and NVIDIA's QUDA library to generate snapshots of the strong-force field in a cube of space-time, weighting them to describe what the quarks were doing in the vacuum. These snapshots were used to simulate what would happen as quarks moved through the strong-force field. The team used more than 1,000 snapshots over three different quark masses in cubes with lattices ranging from 323 to 643 points in space. Said Joó, "Algorithmic improvements like multigrid solvers and their implementations in efficient software libraries such as QUDA, combined with hardware that can execute them, have made these kinds of simulations possible."

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Estonia Leads World in Making Digital Voting Reality
Financial Times
Patrick Mulholland
January 25, 2021

Estonia's i-Voting online voting system was used to cast more than 40% of ballots in its March 2019 parliamentary elections. Anett Numa at the e-Estonia innovation hub said the system's success relies on having a pre-established digital infrastructure, without which people would lack trust in accessing public services online. I-Voting was developed partly to grow participation and keep young people engaged with politics, as roughly 200,000 Estonians live abroad. Numa said i-Voting has not boosted voter turnout, but rather offers an additional avenue for voter engagement. The system uses encryption to address cybersecurity issues, allowing voters to cast ballots across a platform that routes to a central database following authentication.

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Smart Algorithm Cleans Up Images by Searching for Clues Buried in Noise
Texas A&M Today
Vandana Suresh
January 25, 2021

Researchers at Texas A&M University (TAMU) have developed a machine learning-based algorithm that can cut graininess in low-resolution images and expose details otherwise concealed by noise. TAMU's Shuiwang Ji said the smart algorithm can identify pixel patterns that may be diffused across the entire image and boost its denoising capability. The researchers applied augmented microscopy, a hardware/software method for image quality enhancement that superimposes a regular microscope image on a computer-generated digital image. The TAMU team's global voxel transformer networks (GVTNets) deep learning algorithm can dynamically change the size of the receptive field, and needs less training data and can adapt easily to other applications in addition to denoising. Said Ji, "Deep learning algorithms such as ours will allow us to potentially transcend the physical limit posed by light that was not possible before."

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