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Welcome to the April 29, 2020 edition of ACM TechNews, providing timely information for IT professionals three times a week.

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Researchers Use ML-Based Analysis to Quickly Classify Novel Pathogens
University of Waterloo Cheriton School of Computer Science
April 27, 2020


A multidisciplinary team at the University of Waterloo's Cheriton School of Computer Science and Western University in Canada has come up with a computational method that can identify and classify viruses in minutes. Cheriton's Lila Kari said the team used an alignment-free method in combination with machine learning to identify the COVID-19 virus and classify its taxonomic relationship to other viruses. Said Kari, "Within minutes, a few hours at most, we can determine what species a given pathogen is and to which other pathogens it is most closely related — critical taxonomic information that, when coupled with already known concerns, could alert us as to how alarmed we should be."

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Lead author Joseph DelPreto controls a Muscle Signals Can Pilot a Robot
MIT News
Rachel Gordon
April 27, 2020


Researchers at the Massachusetts Institute of Technology Computer Science and Artificial Intelligence Laboratory (CSAIL) have invented a system that taps human muscle signals from wearable sensors to pilot a robot. Conduct-A-Bot uses electromyography and motion sensors worn on the user's biceps, triceps, and forearms to quantify muscle signals and movement, and processes that data with algorithms to identify gestures in real time. The researchers used Conduct-A-Bot with a Parrot Bebop 2 drone, translating user actions like rotational gestures, clenched fists, and tensed arms into drone movement. The drone correctly responded to 82% of roughly 1,500 human gestures when remotely piloted to fly through hoops, and correctly identified about 94% of cued gestures when not being piloted.

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Device Simulates Feel of Walls, Solid Objects in VR
Carnegie Mellon University School of Computer Science
Byron Spice
April 28, 2020


Carnegie Mellon University (CMU) researchers have created a shoulder-mounted device that uses strings attached to the user's hand and fingers to simulate the feel of objects in virtual reality (VR). For example, by locking the strings when the hand is near a virtual wall, the device simulates the sense of touching the wall; the string mechanism also allows users to feel the contours of a virtual object, or to perceive resistance when pushing on the object. CMU's Cathy Fang said the use of lightweight spring-loaded strings helps keep down the weight of the device, reduce its power requirements, and keep its cost down. User evaluations of the device found it offers more realistic touch-sense than other haptic techniques, which typically use motors.

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Do Privacy Controls Lead to More Trust in Alexa? Not Necessarily, Research Finds
Penn State News
Jessica Hallman
April 23, 2020


Researchers at Penn State University have found that giving smart assistant users the option to adjust settings for privacy or content delivery, or both, does not necessarily increase their trust in the device. For some users, having such control could have an unfavorable effect. The team found that trust in Amazon Alexa increased for regular users who were given the option to adjust their privacy and content settings. However, for those users whose skills and expertise are more advanced than others—known as power users—trust decreased when they were given the opportunity to adjust privacy settings. The researchers also found that users who were sensitive about their privacy found content less credible when given the option to customize their privacy settings.

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People waiting on line while wearing masks Why Voting Online Is Not the Way to Hold an Election in a Pandemic
The Economist
April 28, 2020


The COVID-19 pandemic's disruption to elections worldwide has rekindled interest in voting online, but experts warn it would be too vulnerable to breaches and cyberattacks. A paper by the nonprofit International Foundation for Electoral Systems warns against launching online voting during a pandemic. Rigging elections by falsifying millions of paper ballots would be a massive undertaking, but any malefactor who finds a bug in an electronic voting system can theoretically exploit it at a large scale. A lack of unified auditing measures compounds the problem, as any suspicion of interference by an outside power can cast doubt on the entire electoral process. Estonians trust their online voting system partly because state-issued electronic identification and smartcards ensure authentication, but Jeremy Epstein of ACM’s U.S. Technology Policy Committee said, "Because of the pathological fear of government intrusion, this would never fly in the U.S."

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Europe's Privacy Law Hasn't Shown Its Teeth, Frustrating Advocates
The New York Times
Adam Satariano
April 27, 2020


Lax enforcement of Europe's General Data Protection Regulation (GDPR) is disappointing proponents who hoped the law would rein in major technology companies' data collection without user consent. Since the law's 2018 enactment, only one fine of 50 million euros (nearly $55 million) has been levied against a big tech company—Google—amounting to about a tenth of its daily sales revenue. Privacy lobbyist Johnny Ryan said Europe's challenges in enforcing GDPR threaten to undermine efforts to fortify privacy rules elsewhere. Backers said forthcoming rulings involving large tech firms will constitute GDPR's biggest challenge, with Twitter expected to be penalized in an Irish case related to data breaches, while Facebook's WhatsApp messaging service could be punished for sharing data with other Facebook services. Critics argued that penalties have come too late and companies' legal appeals could stall actions, while limited government funding for data protection may discourage authorities from pursuing more complex cases.

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Pakistan's Younger Women Riding Digital Wave in Drive for Better Jobs
Reuters
Zofeen T. Ebrahim
April 27, 2020


Social enterprises like Circle have initiated programs to improve women's job prospects in Pakistan's information technology sector. One such course, called TechKaro, teaches students coding, Web development, and digital marketing, as well as job interview skills. Circle CEO Sadaffe Abid said about half of the course’s graduates, a majority of whom are women, have found employment in software companies. Abid also said, "Our aim is to scale this up to thousands of young women, for in their success is Pakistan's prosperity." Similar initiatives include the CodeGirls Pakistan boot camp, which trains girls from middle- and low-income families in programming and business skills.

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Electrical and computer engineering professor emeritus Thomas Huang. Thomas Huang, Pioneer in Image Compression, Has Died
University of Illinois at Urbana-Champaign News Bureau
April 20, 2020


Image-compression pioneer and educator Thomas Huang has died at 83. Huang, a researcher and professor emeritus at the University of Illinois at Urbana-Champaign (UUIC), was recognized for his contributions to signal processing, pattern recognition, and computer vision. One of Huang's key image-compression achievements was designing a technique for deriving a relationship between two-dimensional (2D) and three-dimensional (3D) imaging, and his work was foundational to recent innovations in 3D urban-modeling programs like Google's StreetView. UIUC's Zhi-Pei Liang said Huang made unmatched contributions to technical standards for international fax, image, and video compression, without which "it simply would not be possible for us to store and transmit the huge amounts of multimedia data that all of us encounter on a daily basis."

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Companies’ Use of Thermal Cameras to Speed Return to Work Sparks Worries About Civil Liberties
The Washington Post
Drew Harwell
April 27, 2020


The business community in America is anxious to re-open, and company leaders are rushing to install emerging technologies as part of an effort to flag the potential risks of COVID-19's spread. These technologies range from standard thermometer guns to “social distancing detectors” and thermal cameras, some of which may be used in combination with facial recognition software. Security officials can use these systems to track and identify those suspected of having the virus, but civil liberties experts are concerned automated systems will monitor crowds of people who may not know or consent to being watched. While such surveillance systems might be necessary during the ongoing public health crisis, advocates worry such systems will become an accepted feature of American life that will last long after the outbreak ends. Daniel Putterman of Kogniz said his company’s facial recognition technology, enhanced with the heat-detecting components of thermal cameras, "can help bring things back to normalcy. I don’t believe body temperature is a piece of private information anymore."

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Researchers Develop Sleep, Health Monitor
UGA Today
Mike Wooten
April 21, 2020


Researchers at the University of Georgia College of Engineering and Chongqing University in China have developed a sensor system to improve care for the elderly by providing real-time safety and health monitoring while they sleep. BedDot continuously observes a person's sleep patterns and vital signs, and notifies loved ones or caregivers of changes in real time. BedDot features a smart seismometer capable of computing and communication, and the device connects to a bed frame and transmits data to the cloud via Wi-Fi. Users and caregivers can see movement patterns and other physical indicators through a graphic interface, and BedDot also can link to smart home systems and automatically summon emergency assistance.

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Speedy Drones Helping Ghana Test for Coronavirus
Popular Science
Rob Verger
April 23, 2020


In Ghana, winged, high-speed electric drones from the Zipline company are flying saliva samples to two company distribution facilities, where they are routed to facilities where they can be tested for the novel coronavirus. Each unmanned drone is launched by catapult, then cruises on autopilot toward its destination on one propeller, with a second propeller held in reserve in the event the drone runs into strong winds. To ensure that the sample is dropped via parachute at the desired site, the drone must live-estimate wind speed, direction, and magnitude, and compensate accordingly.

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A forest. Researcher to Receive Top Global Forestry Award From Swedish King
Oregon State University News
Steve Ludeberg
April 28, 2020


Oregon State University professor emeritus Richard Waring will share this year's Marcus Wallenberg Prize, to be presented by Swedish King Carl Gustav XVI, for his role in developing a computer model to predict forest growth amid climate change. Waring and Australian colleagues and co-honorees Joe Landsberg and Nicholas Coops designed the Physiological Principles Predicting Growth model, which incorporates satellite imagery to show how different environmental conditions impact the world's forests. Said Waring, "By the late 1990s, enough was published that we thought a simplified model could be built that could help foresters as well as ecologists predict how stands of a given composition of tree species might respond to changing environments." Waring and Landsberg first presented the model in 1997, and Coops' addition of satellite imagery in 1998 enabled large forest areas to be surveyed, and forest growth and carbon storage to be predicted on a larger scale.

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Finding bugs in code. AI Spots Critical Microsoft Security Bugs 97% of the Time
VentureBeat
Kyle Wiggers
April 16, 2020


Microsoft says it has developed an artificial intelligence system that correctly distinguishes between security and non-security software bugs 99% of the time. The software giant said the model also accurately identifies critical, high-priority security bugs 97% of the time. The system was trained on a dataset of 13 million work items and bugs from 47,000 developers at Microsoft stored in the AzureDevOps and GitHub repositories. As the model was created, security experts approved the training data and used statistical sampling to provide a manageable amount of data. Wrote Microsoft's Scott Christiansen and Mayana Pereira in a blog post, “We discovered that by pairing machine learning models with security experts, we can significantly improve the identification and classification of security bugs."

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