Welcome to the May 14, 2018 edition of ACM TechNews, providing timely information for IT professionals three times a week.

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Marco Zambelli shows prosthetic hand Italian Researchers Develop Lighter, Cheaper Robotic Hand
Colleen Barry; Francesco Sportelli
May 10, 2018

The Hennes robotic hand developed by Italian scientists streamlines the mechanical design of other myoelectric prosthetics, using sensors that respond to the brain's electrical stimuli to the muscles, according to researcher Lorenzo De Michieli with the Italian Institute of Technology’s Rehab Technologies Lab. The Hennes' single motor directs the movement of all five fingers, making the prosthesis lighter, more affordable, and more adaptable to the shapes of objects. "This can be considered low-cost because we reduce to the minimum the mechanical complexity to achieve, at the same time, a very effective grasp, and a very effective behavior of the prosthesis," De Michieli says. "We maximized the effectiveness of the prosthetics and we minimized the mechanical complexity." Italian retiree and hand amputee Marco Zambelli has been testing the Hennes hand for several years; with it he can remove bills from an automated teller machine, grip a pencil, and drive a stick-shift car.

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maze Google DeepMind's AI Learns Human Navigation Skills
The Guardian
Ian Sample
May 9, 2018

Google's DeepMind unit has developed an algorithm that outperforms people in solving a virtual maze, after noting that it spontaneously generated electrical activity similar to that of "grid cells" governing human navigational skills. The scientists first built a deep neural network and taught it navigation fundamentals, inputting the types of signals that encode speed and direction in the brains of foraging rats. Feedback caused the network to improve its predictions of its location as it navigated a virtual environment. The team observed that 25 percent of the artificial neurons in one network layer had begun firing like organic grid cells. They then assembled a more refined network and applied it to the maze game. Tests revealed that the algorithm not only employed grid cells for position tracking, but also to formulate the direction and distance to its objective so it could follow the most direct pathway.

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dividing info between systems, illustration Protecting Confidentiality in Genomic Studies
MIT News
Larry Hardesty
May 7, 2018

Researchers at the Massachusetts Institute of Technology and Stanford University have unveiled a system for shielding the privacy of people who contribute their data to genomic studies. The system's central mechanism is secret sharing, a process that diffuses sensitive data across multiple servers, none of which can deduce the data by themselves. One server in the new system is committed to generating and secretly sharing Beaver triples (three random numbers), and although it must transmit these figures without associated random numbers to the proper servers, it does not have to relay the numbers themselves. It instead shares the number it uses to "seed" a pseudorandom number generator, enabling recipient servers to produce the random numbers on their own, and consuming much less communication bandwidth. When executing multiplications, the system employs random projection to narrow down the genomic database's million-by-million matrix while preserving the accuracy of the final computation outcomes.

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W&M Society of Women in Computing board members W&M Computing Mentorship for Girls Wins National Service Award
College of William & Mary
Adrienne Berard
May 10, 2018

The College of William & Mary's Society of Women in Computing (SWC) has earned the ACM Outstanding Community Service Award for its work engaging with middle school girls to encourage participation in computing. SWC president Wendy Guo says the society's founders decided to concentrate on community engagement, "with the main goal in mind of starting a mentorship program." Last summer, SWC developed weekly lesson plans for a robotics mentorship program in partnership with Berkeley Middle School, designing coding projects oriented around female students, such as creating music and drawing with microbots. The mentors refined the lesson plans to find projects in tune with students' preferences. "The way we chose what projects to do was based on a lot of research about how to retain girls in computer science," Guo says.

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Tech Bends Light More Efficiently, Offers Wider Angles for Light Input
NC State News
Michael Escuti; Xiao Xiang; Matt Shipman
May 8, 2018

North Carolina State University (NCSU) researchers have created a new diffraction grating that boosts light input and efficiency, potentially leading to more-immersive augmented reality display systems. Previous gratings required a light source be directed into them within an arc of 20 degrees, says NCSU's Michael Escuti. The new grating increases that window to 40 degrees, providing users with a broader field of view and a more immersive experience. The new grating diffracts 75 percent of light input in the intended direction, compared to an average of 30 percent with previous gratings. The researchers integrated a layer of molecules arranged at a “slant” to capture 20 degrees of angular bandwidth with a layer arranged at a different “slant;” superimposing the layers promotes increased angular bandwidth, and higher efficiency. As a next step, the researchers will apply the gratings to a new generation of augmented reality hardware.

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New Chip Can Detect Drugs Within Minutes
R&D Magazine
Kenny Walter
May 8, 2018

University of Buffalo researchers have developed a chemical sensing nanostructured chip that could be used in the creation of a portable drug detector. The chip features gold and silver nanoparticles at its edges, which trap light. When biological or chemical molecules land on the chip's surface, some of the captured light interacts with the molecules and is scattered into patterns that identify the compounds present. The chip includes a sheet of dielectric material, sandwiched between a silver mirror and a hybrid nanomaterial made from gold and silver nanoparticles. Once light strikes the structure for testing, the silver mirror and the dielectric layer serve as an optical cavity that harnesses the light to increase the photons at the surface of the wafer, boosting the scattering signature of compounds being detected. The researchers suggest the chip could be integrated into a portable device that could detect drugs in biological samples.

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A HyperTools visualization of the content of 3,000 randomly chosen Wikipedia articles. Software Transforms Complex Data Into Visualizable Shapes
Dartmouth College
May 7, 2018

HyperTools is an open source software package developed by Dartmouth College researchers that leverages a suite of mathematical techniques to understand high-dimensional datasets via the underlying geometric structures they reflect. HyperTools can be used to convert data into visualizable shapes or animations, which can then be employed to compare different datasets; intuitively gain insights into underlying patterns; generalize across datasets; and develop and test theories relating to big data. "Our tool turns complex data into intuitive 3D [three-dimensional] shapes that can be visually examined and compared," says Dartmouth's Jeremy R. Manning. The researchers demonstrated their work with HyperTools visualizations of brain activity in response to movie frames, of changes in temperature measurement across the Earth between 1975 and 2013, and of the content of political tweets by Hillary Clinton and Donald Trump during the 2016 presidential campaign. HyperTools can also be used to guide the development of new machine learning algorithms.

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Lemurs at the Duke Lemur Center. Monkey Face Recognition App Can Help Spot Endangered Primates
New Scientist
Chris Baraniuk
May 4, 2018

Anil Jain and colleagues at Michigan State University have developed a mobile application that can identify and track primates in the wild, identifying individual animals from facial photos. The team captured about 3,000 photos of the primates at North Carolina's Duke Lemur Center, in addition to thousands of images of golden monkeys and chimpanzees provided by conservationists. A neural network learned to differentiate the primates' facial features, and proved especially effective at identifying lemurs; it achieved more than 80-percent accuracy even when it had to infer a specific animal could not be recognized because it was not included in the training dataset. Jain says the researchers also determined the accuracy for recognizing chimpanzees was lower, despite a larger training dataset, due to the poorer quality of those images.

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Civil Engineers Develop Technique to Model Material-Aging Process
UCI News Center
May 3, 2018

University of California, Irvine (UCI) researchers have developed a numerical method to model the molecular aging process in amorphous materials such as concrete and glass, a breakthrough that could help scientists better understand how materials deteriorate with age and develop new materials that maintain their strength for longer periods of time. UCI researchers Mohammad Javad Abdolhosseini Qomi and Ali Morshedifard used an incremental stress-marching method to subject each material's molecular structure to cyclic stress fluctuations, and monitored the material's response. "Hydrated cement is composed of disk-like globules at the nanoscale," Morshedifard says. "We serendipitously found that these globules gradually deform under sustained load, but the deformation comes to a stop after a certain period." Going forward, the team plans to apply this technique to examine the relationship between the composition and texture of structural materials and their time-dependent behavior.

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Facebook Helped Create an AI Scavenger Hunt That Could Lead to the First Useful Home Robots
Technology Review
Will Knight
May 2, 2018

Researchers at Facebook and the Georgia Institute of Technology (Georgia Tech) have developed a scavenger hunt that could help artificial intelligence (AI) programs develop common sense. The challenge asks AI programs to search for objects inside virtual homes filled with simulated coffee tables, couches, lamps, and other everyday things. The contest requires the AI programs to look for something in the simulated homes after being presented with a natural-language question, the answer to which requires an agent to understand the question and then explore the virtual space in search of the relevant object. The project relies on reinforcement learning, a form of machine learning inspired by animal behavior, as well as imitation learning, a technique that enables algorithms to learn by observation. The overall goal is to develop an intelligent system that can see, talk, plan, and reason, says Georgia Tech’s Devi Parikh.

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