Welcome to the September 18, 2020 edition of ACM TechNews, providing timely information for IT professionals three times a week.

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An overhead view of Howard University IBM Establishes First Quantum Education, Research Initiative for Historically Black Colleges, Universities
September 17, 2020

IBM on Thursday announced the establishment of its first IBM Quantum education and research initiative for Historically Black Colleges and Universities (HBCU), led by Howard University and 12 more HBCUs. The IBM-HBCU Quantum Center will provide access to its quantum computers, and collaborate on academic, education, and community outreach efforts. The initiative aims to prepare and cultivate talent at HBCUs from all science, technology, engineering, and math fields for the quantum era. IBM’s Carla Grant Pickens said, "Diversity and inclusion is what fuels innovation, and students from HBCUs will be positioned to play a significant part of what will drive innovations for the future like quantum computing, cloud, and artificial intelligence."

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Data Processing Module Makes Deep Neural Networks Smarter
NC State News
September 16, 2020

Artificial intelligence researchers at North Carolina State University (NC State) have enhanced deep neural network performance by integrating feature normalization and feature attention modules into a hybrid attentive normalization (AN) module. This module improves system accuracy, while consuming negligible additional computation power. The team tested the AN module by plugging it into four popular neural network architectures: ResNets, DenseNets, MobileNetsV2, and AOGNets. Testing these networks against the ImageNet-1000 classification and the MS-COCO 2017 object detection and instance segmentation benchmarks demonstrated improved performance. NC State's Tianfu Wu said, "We have released the source code and hope our AN will lead to better integrative design of deep neural networks."

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A voter at a polling station. House Passes Legislation to Boost Election Security Research
The Hill
Maggie Miller
September 16, 2020

The U.S House of Representatives on Wednesday passed the Election Technology Research Act, which would establish and fund a Center of Excellence in Election Systems at the National Institute of Standards and Technology (NIST). This center would test the security and accessibility of election-related hardware. The legislation also authorizes NIST and the National Science Foundation to research further securing election technology, focusing on and addressing cybersecurity and other issues to ensure the safety and reliability of election systems. Said Rep. Zoe Lofgren (D-CA), "This research will help to inform our efforts to modernize voting systems and strengthen election practices." The timing for consideration of the legislation in the Senate is unclear.

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How to Train a Machine to See 3D in the Dark
Australian National University
September 16, 2020

Researchers at the Australian National University (ANU) have developed a method that uses machine learning to generate a close-to-perfect optical hologram in near-darkness. Three-dimensional (3D) holograms typically appear grainy in low light due to the shot noise limit, but ANU’s Holo-UNet was trained over thousands of learning cycles to master the appearance of an ideal hologram. Once trained, the researchers would show the Holo-UNet a hologram with missing optical information. ANU's Zhiduo Zhang said, "Much like a master painter, the machine 'remembers' how to digitally fill in those missing photons and so restore the hologram to near-perfect conditions." The researchers said their development will permit the use of holograms for purposes ranging from security to real-time imaging of living cells, with far less light than was previously required.

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Illustration of the Phish scale. The Phish Scale: NIST-Developed Method Helps IT Staff See Why Users Click on Fraudulent Emails
September 17, 2020

Researchers at the U.S. National Institute of Standards and Technology (NIST) have developed the Phish Scale, which could help organizations better train their employees to avoid being deceived by seemingly trustworthy emails. The scale is designed to help information security officers better comprehend click-rate data, in order to gauge phishing training programs' effectiveness more accurately. NIST's Michelle Steves said, "The Phish Scale is intended to help provide a deeper understanding of whether a particular phishing email is harder or easier for a particular target audience to detect." The scale employs a rating system based on message content in a phishing email, highlighting five elements rated on a 5-point scale associated with the scenario's premise. Trainers use the overall score to analyze their data and rank the phishing exercise's difficulty level as low, medium, or high.

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Police Drones Take to U.K. Skies
Daphne Leprince-Ringuet
September 15, 2020

U.K. police agencies are trying out the use of aerial drones to support ground-based forces in scenarios where helicopter or aircraft deployments may be less practical. The National Police Air Service (NPAS) launched initial trials at West Wales Airport using the Hermes 900 drone from Israel’s Elbit Systems. The Hermes, which can fly at 140 miles per hour, also was used in recent trials by the U.K.'s Maritime and Coastguard Agency to assess drone applicability in search and rescue missions. NPAS' Ollie Dismore said, "If this technology enables us to fulfill our national remit more efficiently and either as or more effectively than with our current assets, then it will be considered as part of a future national police air service fleet."

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Smart Transportation Systems Need to Reckon with Rogues
Gary Werner
September 17, 2020

Arizona State University (ASU) engineers have come up with an algorithm that manages autonomous vehicle traffic through intersections safely, under real-life conditions. Developed by researchers at ASU's Make Programming Simple Laboratory, the robust and resilient intersection management (R2IM) algorithm deals with scenarios in which any car can start accelerating or braking at any time relative to traversing an intersection. ASU's Mohammad Khayatian said, "Our approach uses a surveillance system, such as cameras mounted at an intersection, that can detect if a vehicle is not following its expected trajectory beyond a tolerance limit. If that's the case, the intersection manager declares that vehicle as 'rogue,'" then alerts all approaching vehicles so they react accordingly.

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Image of a brain cancer chromosome. Algorithms Uncover Cancers' Hidden Genetic Losses, Gains
Princeton Engineering News
Molly Sharlach
September 17, 2020

Princeton University computer scientists have developed algorithms that enable researchers to identify chromosomal losses or duplications in cancerous tissue more accurately. Such mutations are hard to detect with current DNA sequencing technologies, which cannot read entire chromosomes from one end to the other. Princeton's Ben Raphael and Simone Zaccaria developed the HATCHet and CHISEL algorithms to allow scientists to search vast databases of DNA snippets and uncover any missing pieces or copies. Zaccaria said, "All the cells you are sequencing come from the same evolutionary process, so you can put the sequences together in a way that leverages this shared information." The Princeton team is working with cancer researchers to apply the algorithms to sequences from different types of patient samples and experimental models.

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An electrical power plant. AI Helps Researchers Up-Cycle Waste Carbon
Express Computer (India)
September 11, 2020

Researchers at University of Toronto in Canada and Carnegie Mellon University used artificial intelligence to speed up the search for better catalysts to convert carbon dioxide into ethylene. There are millions of potential material combinations, and the researchers demonstrated machine learning is an efficient way to narrow down the list of promising candidates. Using a combination of machine learning models and active learning strategies, the new algorithms predicted the kinds of products likely to be produced by a given catalyst without a detailed modeling of the material itself. The algorithms were used to screen more than 240 different materials, identifying four promising candidates. A test of the best-performing catalyst material (an alloy of copper and aluminum) found its "faradaic efficiency," the proportion of electrical current used to make the desired product, reached a record 80%.

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Automated Mobility District 'Digital Twin' Provides Insights for Urban Transportation Systems
National Renewable Energy Laboratory
September 15, 2020

At the U.S. Department of Energy-funded National Renewable Energy Laboratory, researchers have developed a modeling and simulation toolkit to help researchers and city planners determine the extent of specific advantages and disadvantages of urban transportation systems. The Automated Mobility District (AMD) toolkit delivers a mathematical model of emerging mobility in select urban districts, a digital twin that permits an analysis of how those systems impact mobility and energy. The toolkit was initially used to quantify the impact of low-speed shared automated vehicles (SAVs) in geofenced districts at Clemson University's International Center for Automotive Research in Greenville, SC. AMD analysis determined that adding electrified SAVs to provide shared mobility services would boost fuel savings from 11% to 38% by satisfying regional travel demand.

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A graph of zero-bias peaks. Microsoft, University of Copenhagen Collaboration Yields Promising Material for Quantum Computing
University of Copenhagen
September 15, 2020

Researchers at the Microsoft Quantum Materials Laboratory and the University of Copenhagen in Denmark have created a material that shows potential for use in future quantum computing devices. The material combines a semiconductor, superconductor, and ferromagnetic insulator into a triple hybrid device that forms a topological superconductor at low temperature. The material uses a thin layer of europium sulfide, whose internal magnetism naturally aligns with the axis of the nanowire to generate an effective magnetic field in the superconductor and semiconductor elements, which seems sufficient to induce the topological superconducting phase. The University of Copenhagen's Charles Marcus said, "This gives us a new path to making components for topological quantum computing, and gives physicists a new physical system to explore."

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Semantic Web For The Working Ontologist, Third Edition: Effective Modeling In RDFs And Owl
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