Online Graduate Programs in Systems Engineering
 
Welcome to the October 25, 2019 edition of ACM TechNews, providing timely information for IT professionals three times a week.

ACM TechNews mobile apps are available for Android phones and tablets (click here) and for iPhones (click here) and iPads (click here).

To view "Headlines At A Glance," hit the link labeled "Click here to view this online" found at the top of the page in the html version. The online version now has a button at the top labeled "Show Headlines."

social media users, illustration Algorithm Can Help Boost Popularity of Social Media Posts
UTokyo Focus (Japan)
October 23, 2019


Computer scientists at the University of Tokyo in Japan have developed an algorithm that recommends suitable tags for social media posts, in order to improve their popularity. The team started with 60,000 publicly available images with their associated tags, number of views, and user data from photo website Flickr, and from this built a system for scoring and numerically valuing different user/image details. The team applied this data to rank the effective success of a particular tag in contributing to the images' view count. Successful tags recommended via this process caused a post's popularity to increase 20%. Tokyo's Xueting Wang said the user-aware folk popularity rank algorithm demonstrated that carefully chosen tags reflecting emotional impressions are more effective in boosting views than only literal representations of image content.

Full Article

medical person pushing hospital bed Researchers Find Racial Bias in Hospital Algorithm
The Wall Street Journal
Melanie Evans; Anna Wilde Mathews
October 24, 2019


Researchers at the University of California, Berkeley, the University of Chicago Booth School of Business, and Partners HealthCare in Boston have found that a predictive hospital algorithm from UnitedHealth Group health services arm Optum was more likely to choose white patients to receive additional medical assistance than black patients. The algorithm assigned healthier white patients the same ranking as black patients who had an additional chronic ailment, along with worse laboratory results and vital signs. The researchers said this was the result of the algorithm’s use of cost to rank patients; black patients' healthcare spending was found to be lower than that of white patients with similar illnesses. The researchers developed a substitute algorithm to boost the percentage of black patients identified for extra medical help by prioritizing patients based on their total chronic conditions, instead of on cost.

Full Article
*May Require Paid Registration
Geoffrey C. Fox Named Recipient of 2019 ACM-IEEE CS Ken Kennedy Award
Association for Computing Machinery
Jim Ormond
October 23, 2019


ACM and the IEEE Computer Society (IEEE CS) have named Indiana University Bloomington's Geoffrey C. Fox to receive the 2019 ACM-IEEE CS Ken Kennedy Award for fundamental contributions to parallel computing methodology, algorithms and software, and data analysis, and their convergence with wide-ranging application categories. Fox's achievements in high-performance computing (HPC) include identifying underlying precepts of decomposition and efficient message passing employed in early multiple instruction, multiple data hypercubes, which spearheaded app development on parallel systems. Fox's recent work at the intersection of HPC and data-intensive computing led to the Scalable Parallel and Interoperable Data-intensive Application Library project, which supports a broad array of diverse data-intensive apps on HPC platforms. Fox also worked with the National Association for Equal Opportunity in Higher Education to find computing research opportunities for students and staff of minority-serving institutions, and was principal investigator of the FutureGrid cyberinfrastructure test aimed at developing new scientific computing approaches.

Full Article

facial images reconstructed from brain scans Someday a Computer May Use Brain Scans to Identify You
The New York Times
Gina Kolata
October 23, 2019


Mayo Clinic investigators said facial recognition software could be used to match photos of people to facial reconstructions derived from magnetic resonance imaging (MRI) scans of their heads. The University of Pennsylvania's Aaron Roth warned this technique eventually will be used to compromise stored medical data. The University of California, San Francisco's Michael Weiner said the Mayo Clinic's findings represent a threat to privacy, citing the Alzheimer's Disease Neuroimaging Initiative as a potential target. The Initiative has MRI brain scans that include participants' faces, with identifying data removed; Weiner suggested attackers could match those MRIs to images of study subjects elsewhere online.

Full Article
*May Require Paid Registration
Prevention Better Than Cure at Keeping Young Users From Getting Involved in Cybercrime
University of Cambridge
Sarah Collins
October 21, 2019


Researchers at the U.K.'s universities of Cambridge and Strathclyde assessing law enforcement interventions for countering participation of young gamers in cybercrime found that high-profile arrests and sentencing of cybercriminals resulted in a short-term decline in cyberattack incidence rates, while removal of infrastructure and targeted-messaging campaigns encouraged a longer-term reduction. Access to booter-service websites, where users can buy targeted denial-of-service (DoS) attacks, only costs a few dollars; booter services and their relative ease of use make DoS attacks a popular form of retaliation on gaming sites, with collateral damage like system take-downs a common result. The U.S. Federal Bureau of Investigation took down some booter infrastructure late last year, which “reshaped the market,” according to Cambridge’s Ben Collier, who observed, “now there’s really just one large booter service provider, and you’re starting to see a few smaller ones start to come back.”

Full Article

drone in palm of hand Swarm of Tiny Drones Explores Unknown Environments
Delft University of Technology
October 23, 2019


A swarm of tiny drones that can explore unknown environments on their own was created by researchers from the Netherlands’ Delft University of Technology (TU Delft) and Radboud University of Nijmegen, and the U.K.'s University of Liverpool. The camera-equipped, 33-gram drones navigate autonomously, with limited sensing and computational capabilities. A proof of concept for search-and-rescue operations demonstrated that a six-drone swarm could investigate about 80% of open rooms, and swarming added redundancy so data otherwise lost by one malfunctioning drone could be supplied by others. A wireless communications chip installed in each drone allows them to detect and avoid each other by reading signal strength between the chips. Delft’s Kimberly McGuire said, “The main advantages of this method are that it does not require extra hardware on the drone and that it requires very few computations.”

Full Article

Inmates of the Parnell Correction Facility listen to Google employee discuss imposter syndrome. Coding Classes Help Inmates Prepare for Productive Life Outside Prison
The Detroit News
James David Dickson
October 24, 2019


About 20 inmates at Michigan's Parnall Correctional Facility have been learning the basics of front-end Web design for the last two months through a program provided by The Last Mile corrections educational nonprofit. Last Mile co-founder Chris Redlitz said training required construction of a self-contained “fake Internet” based on cloud technology, which allows trainees to access and review lessons remotely, then apply their knowledge. Redlitz said applicants must have a "desire" to learn, as well as a clean disciplinary record, to take part; convicted cybercriminals are not accepted, for security reasons. The Last Mile currently operates in five states, with about 250 participating inmates; its graduates (some of whom now earn six-figure salaries) number in the hundreds.

Full Article

Image of traffic sign with graffiti over it. Driving School for Computers
Ruhr-University Bochum
Meike Drießen
October 24, 2019


Researchers at Ruhr-University Bochum (RUB)'s Neural Computation Institute in Germany have devised a technique to automatically generate traffic signs that computers can employ to practice vision. The method involves two algorithms: one is fed simple pictograms of road signs, then is tasked with rendering them into photo-like images. The second algorithm must decide if the rendered image is an actual or created photo. RUB's Sebastian Houben said, "Moreover, the second algorithm indicates to the first one in what way the selection process could be made even more difficult." After several days of this algorithmic sparring, the researchers check the resulting signs' realism, and refine the software if necessary. Both algorithms were able to outperform humans in recognizing images.

Full Article

Trimbot in a garden. Meet Edinburgh's 'Trimbot,' the Rose Pruning, Bush Trimming Auto-Gardening Robot
The Scotsman (UK)
Conor Matchett
October 24, 2019


Researchers have developed a self-guiding gardening robot that navigates via five pairs of cameras and three-dimensional (3D) mapping. The eight partner teams that contributed to the research during the four-year project funded by the EU’s Horizon 2020 program included scientists from the University of Edinburgh in the U.K.; Wageningen University & Research and the universities of Amsterdam and Groningen in the Netherlands; the German University of Freiburg; ETH Zurich in Switzerland; and technology company Bosch. The Trimbot, which must be preprogrammed with a rough scheme of the garden it must maintain, employs algorithms to compare overgrown bushes with desired final shapes as it cuts, and uses automated secateurs (pruning shears) to prune roses at precise positions on each plant’s stem. Edinburgh's Bob Fisher said the researchers “developed new robotics and 3D computer-vision technology to enable it to work outdoors in changing lighting and environmental conditions."

Full Article

A bird’s-eye view of a huge crowd of people. AI Could Help Count How Many People are in Large Crowds
New Scientist
Chris Stokel-Walker
October 21, 2019


German Aerospace Center researchers have developed an artificial intelligence (AI) system that can accurately count the number of people in large crowds. The researchers hand-counted nearly 250,000 people in 33 images of a large crowd taken from planes, drones, and helicopters, then used this data to train an algorithm called MRCNet. The algorithm divides each image into small squares and analyzes how many people are in each. The algorithm’s results were at least 15% more accurate than those of other AI-powered crowd estimation systems. The system is much faster than hand counting, taking 0.03 milliseconds to compute the number of people in each square.

Full Article
Microsoft 2020 Imagine Cup
 
Northeastern University Institute for Experiential AI
 

Association for Computing Machinery

1601 Broadway, 10th Floor
New York, NY 10019-7434
1-800-342-6626
(U.S./Canada)



ACM Media Sales

If you are interested in advertising in ACM TechNews or other ACM publications, please contact ACM Media Sales or (212) 626-0686, or visit ACM Media for more information.

To submit feedback about ACM TechNews, contact: [email protected]