MS in Data Science
Welcome to the February 10, 2020 edition of ACM TechNews, providing timely information for IT professionals three times a week.

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Lockport High School in Lockport that has adopted a facial recognition system for security Facial Recognition Moves Into a New Front: Schools
The New York Times
Davey Alba
February 6, 2020

The adoption of facial recognition by a New York school district is fueling opposition, while public officials cite safety as the motivator for its deployment. New York's Lockport City School District implemented facial recognition to track people at eight schools, opening a new front in the tool's U.S. proliferation. Lockport's Aegis software studies images of faces captured by 300 newly installed cameras and calculates whether those faces match a "persons of interest" database compiled by school administrators; if the system finds a match, it alerts security staff who vet the image for confirmation. Advocates argue facial recognition helps prevent crimes like mass shootings and sexual predation, while opponents warn of potential racial profiling, privacy infringement, and inaccuracy. The New York Civil Liberties Union's Stefanie Coyle said, "Reminding people of their greatest fears is a disappointing tactic, meant to distract from the fact that this product is discriminatory, unethical, and not secure."

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System Uses Machine Learning, Curiosity-Driven 'Honeypots' to Stop Cyberattackers
Purdue University News
Chris Adam
February 6, 2020

Purdue University researchers have developed a system to flag cyberattacks that can adapt to different environments through lifelong learning. The LIDAR (lifelong, intelligent, diverse, agile, and robust) system can be used in computer systems and networks, and uses preprocessing components designed to withstand adversarial attacks, as well as a cross-layer feature extraction mechanism for wireless networks. LIDAR integrates supervised and unsupervised machine learning with rule-based learning that can judge potential attack validity. The system also utilizes a curiosity-driven honeypot that lures attackers without allowing infiltration.

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Australia Focusing on Blockchain Potential with New Roadmap
Asha Barbaschow
February 7, 2020

Australia's government has released a blockchain roadmap outlining a strategy to facilitate job creation, economic growth, more cost-efficient business, and higher productivity in that country. The roadmap concentrates on the areas of regulation and standards; skills, capability, and innovation; and international investment and collaboration, outlining 12 steps the governments hopes to complete before 2026. The roadmap highlights use cases that include blockchain's application to the agriculture, education, and financial sectors, and the establishment of a team of government blockchain users to brainstorm efficient government services using international examples. The roadmap also seeks industry and educational institutions’ cooperation to "develop common frameworks and course content for blockchain qualifications."

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The Canadian startup General Fusion’s prototype compression system includes a ‘mini sphere’ and 14 full-size pistons Fusion Startups Step in to Realize Decades-Old Clean Power Dream
The Wall Street Journal
Daniel Michaels
February 6, 2020

Startups are trying to make clean fusion-generated electricity a reality by designing systems for squeezing atoms together, partly enabled by computing innovations. First Light Fusion founder Nick Hawker uses advanced computer modeling to find fusion solutions, inspired by his work at the U.K.'s University of Oxford. Hawker employed sophisticated algorithms and powerful processors to demonstrate how forceful bubble implosions could trigger massively high temperatures for fusion, and his company is building machines to test those models and develop a prototype generator. First Light uses computers to plan reactors that use physical compression to trigger the collapsing bubbles, simulating super-fast shockwaves through advances in processing power, modeling, and machine learning. Said Hawker, "Just a bigger computer isn't enough."

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Algorithm Analyzes Social Media Data to Help Brands Improve Marketing
University of Tokyo
February 4, 2020

Researchers at the University of Tokyo in Japan have created an algorithm that predicts consumer purchases from data on consumers’ social media activity, which brands could use to refine their marketing strategies. The algorithm integrates statistical modeling and machine learning-based image recognition. The researchers assessed the algorithm against purchase history and questionnaires, and learned that credit card or point (loyalty) card companies could accurately forecast customers' past purchasing patterns, while their program could accurately predict customers' willingness to try new brands. Said the university’s Toshihiko Yamasaki, “People might say that professionals already ‘see’ these kinds of patterns, but being able to show the similarity between brands numerically and objectively is a new innovation. Our algorithm is demonstrably more effective than judging these things based on intuition alone.”

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Computer Simulation for Understanding Brain Cancer Growth
Newcastle University (UK)
February 6, 2020

Researchers at Newcastle University and University College London in the U.K., the University of Cyprus, and CERN (the European Organization for Nuclear Research, based in Switzerland) have developed a three-dimensional (3D) simulation that combines the macroscopic scale of tissue with the microscopic scale of individual cells to realistically model the mechano-biology of cancer. The freely available BioDynaMo platform includes the role of cell migration and adhesion, the influence of the extracellular matrix, the effects of oxygen and nutrient availability, and the signaling triggered by chemical cues and growth factors. Newcastle's Jean de Montigny said, “The advantage for scientists and medics is that BioDynaMo can be used on standard laptops or desktop computers and provides a software platform which can be used to easily create, run, and visualize 3D agent-based biological simulations."

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Deep Learning Model Can Identify Sleep Stages
University of Eastern Finland
February 3, 2020

Researchers at the University of Eastern Finland have developed a deep learning model that can identify sleep stages as accurately as an experienced physician. Using polysomnographic recording data from both healthy people and those with suspected obstructive sleep apnea (OSA), the researchers found that in healthy individuals, the system was able to identify sleep stages with 83.7% accuracy when using a single frontal electroencephalography channel (EEG), and with an 83.9% accuracy when supplemented with electrooculogram (EOG). In patients with suspected OSA, the model reached accuracies of 82.9% for a single EEG channel and 83.8% for combined EEG and EOG channels.

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Two men carrying a radar-equipped drone out to its launch site during NASA tests of an integrated system designed to enable a drone to autonomously detect and avoid other aircraft Testing Shows Drones Can Use Autonomous Technology to Dodge Other Air Traffic
Virginia Tech News
Eleanor Nelson
February 5, 2020

Virginia Polytechnic Institute and State University (Virginia Tech) researchers are testing an "end-to-end" detect-and-avoid system for drones through the Virginia Tech Mid-Atlantic Aviation Partnership (MAAP). The U.S. Federal Aviation Administration designated MAAP as one of seven test sites to spearhead research on integrating drones into national airspace. The autonomous collision-avoidance tests were part of a year-long MAAP-National Aeronautics and Space Administration (NASA) project investigating ways to detect and avoid drone collisions. Said MAAP’s John Coggin, “We’re just now getting to the point where these three components — the detect, alert, and avoid piece — are mature enough to be able to assemble them and get good results.”

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Robot Submarine Snaps First Images at Foundation of Antarctic Glacier
Georgia Tech College of Sciences
Ben Brumfield
January 29, 2020

A robotic submarine engineered by Georgia Institute of Technology (Georgia Tech) researchers has captured the first-ever images of the foundations on the ocean floor of the Thwaites Glacier in Antarctica, in the hope of assessing the glacier's condition and its potential to contribute to rising sea levels. The Icefin robotic submarine traveled more than 15 kilometers (9.3 miles) round trip during five missions in which it took photos of the glacier's grounding line (foundations) as part of the International Thwaites Glacier Collaboration. Said Georgia Tech's Britney Schmidt, “It's the first time anyone has done that or has ever even seen the grounding zone of a major glacier under the water, and that’s the place where the greatest degree of melting and destabilization can occur.”

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An officer from the National Integrated Identity Management system (NIIMS) seen taking a photo of Mr. Charles Chepkwony to process his biometric data in Kenya Countries Debate Openness of Future National IDs
IEEE Spectrum
Lucas Laursen
January 30, 2020

More than half of African countries are developing some form of biometric or digital national identification (ID) in response to major international calls to establish legal IDs for the nearly 1 billion people who currently lack them. However, this ID boom often moves faster than data protection laws. For countries that move forward with digital ID laws, opportunistic vendors can lock them into their products. For example, Kenya is using software that is only accessible to government agencies and contractors, a fact that is concerning to some critics. Meanwhile, India's Modular Open Source Identity Platform (MOSIP) may not solve all the security issues associated with early national ID ecosystems, but it could empower governments to expect more from the vendors that support future national IDs.

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A new dataset will enable engineers to test and refine new algorithms for self-driving cars that can overcome the perception challenges posed by snowy weather Research Data Puts Self-Driving Cars to the Ultimate Test: Canadian Winter
U of T News
Tyler Irving
February 3, 2020

Researchers at Canada's universities of Toronto (U of T) and Waterloo collaborated with San Francisco-based artificial intelligence (AI) infrastructure firm Scale AI to create a dataset for training future autonomous vehicles to drive in winter conditions. The Canadian Adverse Driving Conditions dataset uses real-world scans of icy, snow-covered Canadian roads as a virtual training course for self-driving cars' algorithms. U of T's Steven Waslander said most driving datasets are collected in summer, and self-driving algorithms trained on such data tend to be confounded in adverse conditions. Waslander and Waterloo's Krzysztof Czarnecki compiled the new dataset over the past two winters, using a Lincoln MKZ hybrid equipped with cameras, a LiDAR scanner, and a global-positioning system tracker to record conditions across more than 1,000 kilometers (621 miles) of roads. Scale AI labeled the data through computer and human image recognition, and further analysis and processing converted the data into a software-parsable format.

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Flaw Lurking in Sudo for 9 Years Hands Over Root Privileges
Ars Technica
Dan Goodin
February 4, 2020

Sudo, a utility found in Unix-like operating systems, has received a patch for a potentially serious vulnerability permitting unprivileged users to obtain root privileges on certain systems. The vulnerability, called CVE-2019-18634, is caused by a stack-based buffer-overflow bug found in versions 1.7.1 through 1.8.25p1. The bug can trigger when an administrator or downstream operating system enables an option known as pwfeedback. When pwfeedback is turned on, the vulnerability can be exploited by users not listed in sudoers, a file that contains rules users must follow when using the sudo command. Systems or software using a vulnerable version should move to version 1.8.31; those who cannot update right away can prevent exploits by disabling pwfeedback.

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