Welcome to the August 26, 2019 edition of ACM TechNews, providing timely information for IT professionals three times a week.
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Artificial Muscles Bloom, Dance, Wave
KAIST
August 22, 2019
Researchers at the Korea Advanced Institute of Science and Technology (KAIST) in South Korea have developed an ultrathin artificial muscle, also called an actuator, for soft robotics. The researchers demonstrated the new technology with a robotic blooming flower brooch, dancing robotic butterflies, and fluttering leaves on a kinetic work of art. The actuator looks like a strip of paper about an inch long and is made up of MXene, a class of compounds that have layers only a few atoms thick. The researchers found the actuator moved in response to low voltage very quickly, and was able to move continuously for more than five hours.
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Here's the No. 1 Highest-Paid, Most In-Demand Job in Every State
MarketWatch
Quentin Fottrell
August 22, 2019
A study by online employment website CareerBuilder found software developers to be among the highest-compensated and fastest-growing jobs in every U.S. state, according to data from the U.S. Bureau of Labor Statistics. Developers usually need a bachelor's degree, and programming skills like Java, JavaScript, SQL, C Sharp, Cascading Style Sheets, and NET Framework. Their median annual salary last year was $105,590, or $50.77 an hour, and the profession's job-growth outlook is higher than average. The study predicts the number of jobs for software developers will rise 24% nationwide from 2016 to 2026. An independent study by U.S. News & World Report found software developer was the best job in terms of work-life balance and career development.
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Using Wall Street Secrets to Reduce the Cost of Cloud Infrastructure
MIT News
Rob Matheson
August 18, 2019
Researchers at the Massachusetts Institute of Technology (MIT) and Microsoft have developed a "risk-aware" mathematical model that could improve the performance of cloud computing networks around the world. The TeaVar model (whose code is freely available on GitHub) accounts for failure probabilities of links between datacenters worldwide, similar to predicting the volatility of stocks. Then, TeaVar runs an optimization engine to allocate traffic through optimal paths to minimize loss while maximizing overall usage of the network. While conventional methods keep links idle to handle unexpected traffic shifts resulting from link failures, TeaVar guarantees that for a targeted percentage of time the network can handle all data traffic, so there is no need to keep any links idle. During testing based on real-world data, the model supported three times the traffic throughput of traditional traffic-engineering models, while maintaining the same high level of network availability.
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Router Guest Networks Lack Adequate Security, According to BGU Researchers
Ben-Gurion University of the Negev (Israel)
August 15, 2019
A study by researchers at Israel’s Ben-Gurion University of the Negev (BGU) found routers made by leading manufacturers are vulnerable to cross-router data leakage via an attack on one of the separate host and guest networks. The researchers noted the presence of different levels of cross-router covert channels, which can be integrated and taken advantage of to either direct a malicious implant or to exfiltrate data. These flaws in certain cases can be patched as a software bug, but more pervasive and concealed cross-channel communication is impervious to prevention unless data streams are partitioned on different hardware. Said BGU's Adar Ovadya, "A hardware-based solution seems to be the safest approach to guaranteeing isolation between secure and non-secure network devices."
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Faced with Data Deluge, Astronomers Turn to Automation
Scientific American
Anil Ananthaswamy
August 21, 2019
Researchers hope to use algorithms to improve multimessenger astronomy, and more precisely simulate evolutionary cosmic phenomena by automating certain discovery phases, and filtering massive datasets with optimal speed and efficiency. For example, signals of gravitational waves collected by the Laser Interferometer Gravitational-Wave Observatory must be matched by supercomputers against hundreds of thousands of templates of potential wave signatures. Scientists at the University of Illinois at Urbana-Champaign's National Center for Supercomputing Applications used convolutional neural networks (CNNs) for real-time detection/decryption of gravitational-wave signals. The team then scaled up the initiative with supercomputer-trained deep learning algorithms, which search through a larger series of parameters to identify overlooked signals. Meanwhile, Harvard University researchers developed a CNN to analyze x-ray images of galaxy clusters, and applied a technique allowing the network's observations to be visualized to give users a better idea of how the CNN was operating.
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Girls Now More Than 20% of Computing GCSE Entries
ComputerWeekly.com
Clare McDonald
August 22, 2019
The number of girls in the U.K. choosing to take computing at the General Certificate of Secondary Education (GCSE) level increased from 15,046 in 2018 to 17,158 this year, with girls now making up 21.4% of U.K. GCSE computing entries. In higher-level grades in computing, girls outperformed boys, with 24.9% of girls receiving a 7/A grade in the subject compared to 20.8% of boys. Said Russ Shaw, founder of Tech London Advocates and Global Tech Advocates, "What is particularly significant is the increase in girls studying STEM subjects, which paints an optimistic future for the tech industry, which has struggled to increase its gender diversity."
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Tools to Minimize Risks in Shared AR Environments
UW News
Sarah McQuate
August 20, 2019
University of Washington security researchers have developed a prototype toolkit that lets developers incorporate collaborative and interactive features into augmented reality (AR) apps while maintaining users' privacy and security. The ShareAR toolkit for the Microsoft HoloLens helps apps produce, share, and monitor objects shared by users. Testing with case study apps revealed that the most computationally rigorous actions were creating objects, and changing permission settings within apps. However, ShareAR took no longer than 5 milliseconds to complete a task—and less than 1 millisecond in most cases—even when researchers intentionally strained the system, with large numbers of users and shared objects.
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Computer Model Could Help Test Sickle Cell Drugs
News from Brown
Kevin Stacey
August 22, 2019
Brown University researchers have created a computer model to simulate the process by which sickle cell disease distorts red blood cells, which could be used in preclinical drug screening. The researchers created biophysical models of each stage of the sickling (deformation) of cells, including a simulated red blood cell function called OpenRBC, and a supercomputer model of sickle cell fiber formation. The end-product was a kinetic model of the sickling process, with supercomputer-derived data fed into a streamlined iteration enveloping key sickling dynamics, which can run on a laptop. The team demonstrated that the model could replicate the results of earlier experiments, both in the laboratory and in humans. The model allows users to enter the mode of action by which a drug is presumed to function, to view its potential effects on the cells.
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Ions Clear Another Hurdle Toward Scaled-Up Quantum Computing
Joint Quantum Institute
E. Edwards
August 16, 2019
Researchers at the University of Maryland's Joint Quantum Institute (JQI) used laser pulses to simultaneously create quantum connections between different pairs of qubits, marking the first time these kinds of parallel operations have been executed in an ion trap. This breakthrough illustrates that advancing ion trap quantum processors is not limited by the physics of qubits, but rather tied to the engineering of their controllers. The new ion trap is made from gold-coated electrodes, which carry the electric fields that confine Ytterbium ions. The ions are caught in the middle of the trap where they form a line, each separated from its neighbor by just a few microns. This configuration allows researchers to control individual ions and set them up as qubits.
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Google AI's New Algorithm Will Let Smartphones Read Sign Language
International Business Times
Rishabh Jain
August 20, 2019
Google researchers have developed an algorithm that will allow smartphones to perceive hand movements and shapes across a variety of platforms, including reading sign language using augmented reality. The algorithm uses machine learning to learn patterns, remember them, and create data modalities. The system infers 21 three-dimensional keypoints on hands in every frame. The algorithm is made up of three models that work together: a palm detector; a hand detector, and gesture recognition. Rather than tracking the whole hand, the system merely tracks the palm to read overall hand movements. In addition, the position of every finger is analyzed separately to create proper interpretations. Google says it has opened the source code so other researchers can build on its achievement.
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