Welcome to the October 7, 2019 edition of ACM TechNews, providing timely information for IT professionals three times a week.
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Teen Hackers Try to Convince Parents They Are Up to Good
The Wall Street Journal
Julie Jargon
October 1, 2019
Teenagers across the U.S. are forming hacking clubs and attempting to persuade their parents and teachers that hacking is not necessarily a malign vocation. For example, the TeenHacks LI club of Long Island, NY, arranges hackathons, and 15-year-old executive director Snigdha Roy had to convince her parents these activities were innocuous, and even beneficial. Hacking club and hackathon participants said these activities go outside traditional education, allowing them to learn programming from peers instead of from teachers in classrooms. More extensive organizations include Hack Club, which provides high school students with a curriculum, helps participants connect and ask technical questions, and trains them on raising money and attracting corporate sponsors for hackathons. Hack Club founder Zach Latta said the goal of such efforts is to create "more thoughtful, unconventional problem solvers" to address world challenges like climate change, which can be traced to technology.
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System Helps Smart Devices Find Their Position
MIT News
Rob Matheson
October 2, 2019
Researchers at the Massachusetts Institute of Technology (MIT), the University of Southern California, the University of Ferrara in Italy, and the Basque Center of Applied Mathematics in Spain have developed a system that helps networks of smart devices find their positions in environments where GPS usually fails. In simulations of these "harsh" scenarios, the system operates significantly better than traditional methods, consistently performing near the theoretical limit for localization accuracy. The method leverages many signal features and contextual information to create a probability distribution of all possible distances, angles, and other metrics. The team used machine learning techniques to help the system learn a statistical model describing possible positions from measurements and contextual data. Said MIT’s Moe Win, “Our soft information method is particularly robust in … harsh wireless environments.”
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App Detects Eye Disease in Personal Photos
IEEE Spectrum
Emily Waltz
October 2, 2019
Baylor University researchers have developed a free smartphone app that uses machine learning to flag eye disease from personal photos, as much as a year ahead of clinical diagnosis. The White Eye Detector sifts through casual portraits on a phone for the appearance of a white reflection in the pupil—a symptom of leukocoria, which could indicate the presence of retinoblastoma or other eye disorders. The team applied the app to nearly 53,000 photos of 40 children, half with healthy eyes and half diagnosed with a leukocoria-related disorder; ages varied from birth to several years old, allowing the detector to determine the age at which the disease developed. The app identified leukocoria in photos taken an average of 1.3 years before diagnosis in 16 out of 20 children with eye disease. The detector also spotted leukocoria in subjects with retinoblastoma more than nine months before diagnosis, on average.
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Facial Recognition Technology Needs Controls on Its Use, World Economic Forum Says
CNBC
Saheli Roy Choudhury
October 3, 2019
A report by the World Economic Forum (WEF) said governments must ensure facial recognition technology protects citizens' privacy through fair and transparent use. WEF's Kay Firth-Butterfield said both government and corporate use of facial recognition compound this challenge, warning that the massive volume of information the technology can compile on individuals raises privacy issues. The report also expressed concern over the possibility of governmental use of facial recognition to infringe on civil liberties, citing studies demonstrating facial recognition technology's ability to collect data on people without their knowledge, while some such systems have exhibited bias against women and people with darker skin. The WEF called on governments to develop policies to shield individual rights, and channel development of the technology into socially beneficial areas.
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Network Science Reveals Secrets of World’s Best Soccer Team
Technology Review
October 4, 2019
Researchers at Universidad Rey Juan Carlos in Spain have used network science to analyze the style of the F.C. Barcelona soccer club. The researchers combined different network metrics to extract the specific signature of the Barcelona team, which is considered one of the best in history. They represent each player on a team as a node, and created links between players with each pass between them. At the end of a game, this network becomes a powerful record of the links between players and the way the game evolved. Said the researchers, “We are able to identify those network metrics that enhance the probability of scoring/receiving a goal, showing that not all teams behave in the same way and how the organization Guardiola’s F.C. Barcelona is different from the rest.”
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That Music You’re Dancing To? It’s Code
The New York Times
Luke Winkie
October 4, 2019
Sonic Pi is a coding language that may be used to construct melodies in real time at live coding shows, which are sometimes called "algoraves." The language can find middle C, summon the Amen Break, and play dozens of synth sounds with just a few commands, making it a favorite among DJs at these live events. Sonic Pi was developed by University of Cambridge researcher Sam Aaron to be a teaching aid. Aaron wanted to combine the work of programming with the joy of music, with the overall goal of inventing a coding environment that functioned as an instrument, allowing users to type out rhythm and melody. Said Aaron, "In the same way we can read and write poems and lyrics, we need to understand that code can have that expressive quality as well."
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Titan Supercomputer, Spallation Neutron Source Unite to Probe Inner Workings of C-SRC Kinase
Oak Ridge Leadership Computing Facility
Coury Turczyn
October 3, 2019
Oak Ridge National Laboratory (ORNL) researchers used the Titan supercomputer and the Spallation Neutron Source at ORNL to create the most accurate three-dimensional model yet of an intrinsically disordered protein (IDP). The team chose to study the N-terminal domain of c-Src kinase, a major signaling protein in humans. The researchers combined neutron scattering experiments with enhanced sampling molecular dynamics (MD) simulations. The simulations use physics to determine how proteins move. Key to the team's success was running many MD simulations in parallel on Titan, allowing the simulations to communicate with each other and exchange information. Said ORNL's Loukas Petridis, “Validation of the simulations by comparison to neutron scattering experiments is essential to have confidence in the simulation results. The validated simulations can then provide detailed information that is not directly obtained by experiments."
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3D Printing Technique for Biomaterials
University of Birmingham
October 2, 2019
Researchers at the University of Birmingham in the U.K. have developed a new technique for three-dimensionally (3D) printing soft biomaterials for artificial medical implants. The Suspended Layer Additive Manufacturing (SLAM) technique employs a polymer-based hydrogel in which the particles have been engineered to generate a self-healing gel. Liquids or gels can be directly injected into this material, and accumulated in layers to compose a 3D shape. Particles in this gel can be twisted so they separate, but still maintain linkage to facilitate a self-healing effect, allowing the gel to support the printed material so objects can be precisely constructed, without leakage or sagging. Cambridge's Liam Glover said, "[SLAM] has huge potential for making replacement biomaterials such as heart valves or blood vessels, or for producing biocompatible plugs that can be used to treat bone and cartilage damage."
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NYU Tandon Data Scientists Launch Tool to Analyze Facebook Political Advertising in Canada
NYU Tandon School of Engineering
October 2, 2019
Researchers at the New York University (NYU) Tandon School of Engineering have launched a website that analyzes all Canadian Facebook political advertising, in the run up to that country's October 21 elections. The interactive website lets users explore the data and analyze advertising spending based on party, target demographic, region, and other factors. The data was collected using machine learning and data scraping tools, and expands on the team's 2018 political advertising analysis. Said NYU’s Damon McCoy, "We hope our website will help the media better understand political ad spend and targeting, and we plan to continue to build this platform with data from additional countries and platforms."
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IBM Hackathon Winner Helps Fight Rash of Wasted Food
ZDNet
Greg Nichols
October 4, 2019
A group called FreShip was named the winner of IBM’s Food Waste Developer Challenge, a hackathon that tasked U.S. developers to create food-waste-combating solutions from open source technology. IBM and hackathon organization AngelHack hosted the challenge with the goal of supporting a more transparent and real-time supply chain to monitor food sales and fulfillment, with waste reduction paramount. Participants were asked to create solutions, using IBM code patterns and datasets, and tools including IBM Watson Visual Recognition, IBM Blockchain, and chatbot application-programming interfaces. Hackathon winner FreShip integrated software and hardware to minimize waste via constant monitoring, in parallel with a smart e-commerce platform that allows otherwise wasted food to be resold. The system deploys Arduino and Narrowband-Internet-of-Things solutions in food shipping containers to rate food freshness by photo analysis, with blockchain deploying smart bidding contracts.
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Decade of Cybersecurity Data Could Predict Future Malicious Online Activity
CSIRO (Australia)
Chris Chelvan
October 3, 2019
Researchers from Australia’s Commonwealth Scientific and Industrial Research Organization (CSIRO) Data61 digital research network and Macquarie University, in collaboration with Nokia Bell Labs and the University of Sydney, have developed a comprehensive dataset of the global cybersecurity threat landscape from 2007 to 2017. The purpose of the FinalBlacklist dataset is to help cybersecurity specialists derive new insights on cybersecurity threats, and potentially predict future malicious online activity. The team collected 51.6 million reports of such malicious online activity involving 662,000 unique IP addresses worldwide. The data was categorized using machine learning techniques into six classes: malware, phishing, fraudulent services, potentially unwanted programs, exploits, and spamming. Said Macquarie University’s Dali Kaafar, "Our analysis revealed a consistent minority of repeat offenders that contributed a majority of the mal-activity reports. Detecting and quickly reacting to the emergence of these mal-activity contributors could significantly reduce the damage inflicted.”
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