Welcome to the April 17, 2017 edition of ACM TechNews, providing timely information for IT professionals three times a week.

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Manga ray soft robot Robot Ray Swims Using High-Voltage Artificial Muscles
IEEE Spectrum
Evan Ackerman; Celia Gorman
April 16, 2017


Researchers from Zhejiang University in China have developed a robotic ray that is propelled by soft, flapping wings made of dielectric elastomers, which bend when electricity is applied to them. The researchers note the robotic ray is almost entirely transparent, with its body, fins, tail, and elastomer muscles completely see-through. In addition, a 450-mAh, 3.7-volt battery can keep the robot swimming at 1.1 centimeters per second for three hours 15 minutes while carrying a tiny camera. The ray's maximum untethered speed is 6.4 centimeters a second, and the robot can function in water temperatures ranging from slightly above freezing to nearly 75 degrees Celsius. The researchers have yet to suggest any specific applications for the robot, making it simply a proof of concept of the technologies, and leaving a practical robot for future generations.

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AI Can Predict Heart Attacks More Accurately Than Doctors
Engadget
Andrew Tarantola
April 16, 2017


Researchers from the University of Nottingham in the U.K. have developed four computer-learning algorithms that significantly outperform American College of Cardiology/American Heart Association guidelines for predicting heart attacks or strokes. The neural network algorithms achieved 74.5-percent to 76.4-percent accuracy, beating existing guidelines by 7.6 percent while raising 1.6-percent fewer false alarms. The researchers trained the algorithms on data from 378,256 patients in the U.K., using about 295,000 records to generate the internal predictive models. The researchers then used the remaining records to test and refine the algorithms. Out of the 83,000-patient set of test records, the new system could have saved 355 extra lives, according to the researchers. In addition, the artificial intelligence systems identified a number of risk factors and predictors not covered in existing guidelines, such as severe mental illness and the consumption of oral corticosteroids.

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4D Printing Gets Simpler and Faster
Singapore University of Technology and Design
Melissa Koh
April 12, 2017


A team of researchers from the Georgia Institute of Technology, the Singapore University of Technology and Design (SUTD), and Xi'an Jiaotong University and Zhejiang University in China have developed a new approach that significantly simplifies and increases the potential of four-dimensional (4D) printing by incorporating the mechanical programming post-processing step directly into the three-dimensional (3D) printing process. The method enables high-resolution 3D-printed components to be designed by computer simulation, 3D printed, and directly and rapidly transformed into new permanent configurations via the use of heat. The researchers found the new approach can help save printing time and materials by up to 90 percent, while completely eliminating the mechanical programming process from the design and manufacturing workflow. "Our approach involves printing composite materials where at room temperature one material is soft but can be programmed to contain internal stress, and the other material is stiff," says SUTD's Zhen Ding.

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Biased Bots: Human Prejudices Sneak Into Artificial Intelligence Systems
Princeton University
April 13, 2017


Researchers at Princeton University have demonstrated how machines can be reflections of their creators' biases. They determined common machine-learning programs, when fed ordinary human language available online, can obtain cultural prejudices embedded in the patterns of wording. "We have a situation where these artificial intelligence [AI] systems may be perpetuating historical patterns of bias that we might find socially unacceptable and which we might be trying to move away from," warns Princeton professor Arvind Narayanan. The team experimented with a machine-learning version of the Implicit Association Test, the GloVe program, which can represent the co-occurrence statistics of words in a specific text window. The test replicated the broad substantiations of bias found in select Implicit Association Test studies over the years that relied on human subjects. Coders might hope to prevent the perpetuation of cultural stereotypes via development of explicit, math-based instructions for machine-learning programs underpinning AI systems.

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Supercomputer Simulation Offers Peek at the Future of Quantum Computers
Technology Review
April 11, 2017


Researchers from the Swiss Federal Institute of Technology Zurich (ETH Zurich) in Switzerland have used the fifth-most powerful supercomputer in the world to simulate the behavior of a 45-qubit quantum computer. "To our knowledge, this constitutes a new record in the maximal number of simulated qubits," says ETH Zurich's Thomas Haner and Damian Steiger. In addition, the researchers show how more powerful simulations should be possible. Haner and Steiger say the ETH Zurich breakthrough reduces the overhead so the simulation can run more than an order of magnitude faster than before. The researchers applied these improvements to a set of simulations on the Cori II supercomputer at the Lawrence Berkeley National Laboratory. Cori II consists of 9,304 nodes, each containing a 68-core processor running at 1.4 gigahertz, which leads to a peak performance of 29.1 petaflops with one petabyte of memory.

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Helping Students Learn by Sketching
Northwestern University Newscenter
Amanda Morris
April 14, 2017


Northwestern University professor Ken Forbus and his team have developed Sketch Worksheets, software that helps students learn via sketching exercises and also provides on-the-spot feedback by analyzing sketches and comparing them to the instructor's drawings. The software is founded on CogSketch, an artificial intelligence platform previously developed in Forbus' lab that employs visual-processing algorithms to automatically replicate and understand human-drawn sketches. Sketch Worksheets' comparisons of student and instructor sketches are conducted by an analogy model, in which students and instructors apply conceptual labels to their sketches to represent relationships among the drawings' different components. Forbus says CogSketch uses analogy to compare labels and give feedback. Geoscientists at the University of Wisconsin-Madison used Sketch Worksheets to devise a set of 26 sketches that cover topics in introductory classes. "This is a step in creating software that can communicate with people as flexibly as we communicate with each other," Forbus says.

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A simulation of a transporter protein Simulation by Stanford Researchers Shows How Transporter Proteins Do Their Work in Cells
Stanford News
Shara Tonn
April 13, 2017


Researchers at Stanford University have created the first-ever realistic computer model of a transporter protein moving a sugar molecule across a cell membrane, which could enhance drug development. Crystallography images of a transporter in different stages of the transport process were used as the start point for the simulation, and the researchers encoded the physical forces between atoms, then permitted the simulated atoms to move spontaneously. The simulation uncovered structures that match the other crystallographic states, while also supporting the airlock theory of transporter function. The model showed the forces between the atoms are such that the protein is most stable with only one or the other of the two doors open, or with both closed, but not with both open. "Now that we have a better understanding of how transporters work we can break down the process and see what's actually important," says Stanford professor Liang Feng.

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ASU Team Connects Humans, Robots Through Common Language
ASU Now
Joe Kullman
April 12, 2017


Three Arizona State University (ASU) doctoral candidates in computer science have formed AEffective Robotics, one of 12 teams that will compete next week in Seattle, WA, in the U.S. finals of the 2017 Microsoft Imagine Cup, an international competition that is widely considered the "Olympics of Technology." The team, which aims to make it easier for humans and robots to communicate, is vying for a spot in the top six, which would earn them a place in the international finals in Seattle in July, where they would compete for the top prize of $100,000, in addition to support to launch a startup. The ASU team's project, "Cloudy with a Chance of Synergy," includes a concept for the operations of what the team describes as a "factory of the future," in which robots and humans would be connected through a networking system, enabling them to effectively "share a brain."

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A graphene field-effect transistor Graphene 'Phototransistor' Promising for Optical Technologies
Purdue University News
Emil Venere
April 12, 2017


Researchers at Purdue University, the University of Michigan, and Pennsylvania State University integrated graphene with a larger silicon carbide substrate to create light-activated graphene field-effect transistors, an important step toward advanced imaging, displays, sensors, and high-speed communications. "Our approach could make possible a very sensitive camera where you have relatively few pixels but still have high resolution," notes University of Michigan professor Igor Jovanovic. The researchers demonstrated the device is responsive to light even when the silicon carbide is illuminated at distances far from the graphene, and performance can increase 10-fold depending on which part of the material is illuminated. The phototransistor also can ascertain where light is coming from. "This is the first time anyone has demonstrated the use of a small piece of graphene on a large wafer of silicon carbide to achieve non-local photodetection, so the light doesn't have to hit the graphene itself," says Purdue professor Yong Chen.

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Your Phone's Power Use Can Give Hackers an Opening
New York Institute of Technology
Karen Marie Belnap
April 11, 2017


Researchers at the New York Institute of Technology (NYIT) have shown even without a data cable, hackers can analyze a device's power needs to access users' private information, with speed and accuracy depending on several factors. These side-channel attacks are successful because "Web pages have a signature that reflects the way they load and consume energy," according to NYIT professor Paolo Gasti. The study involved using power use signatures previously identified and tested under various conditions. After collecting power traces via a range of smartphones browsing popular websites, the researchers launched attacks and checked the accuracy with which their algorithms could determine which sites were visited while the phones were plugged in. Regardless of the conditions, the researchers determined even the slower and less accurate attempts at penetration were still accurate within six seconds about 50 percent of the time.

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The Dark Secret at the Heart of AI
Technology Review
Will Knight
April 11, 2017


Some experts warn deep-learning artificial intelligence (AI) technologies cannot be adopted without reservations if their creators cannot understand how they reason, or guarantee accountability for users. "You don't want to just rely on a 'black box' method," says Massachusetts Institute of Technology (MIT) professor Tommi Jaakkola. As AI technology progresses, the possibility looms of taking a leap of faith in using it. Some researchers are attempting to introduce "explainability" to AI to instill trust. MIT professor Regina Barzilay thinks human-machine collaboration will go a long way toward implementing explainability, and one project in this area seeks to develop a deep-learning algorithm that can detect early signs of breast cancer in mammograms. However, this strategy cannot avoid the fact that explanations are simplified, meaning some information could be lost along the way. University of Wyoming professor Jeff Clune speculates some aspects of machine intelligence will always be instinctual or inscrutable.

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A mosaic of social media logos Social Media Tools Can Reinforce Stigma and Stereotypes
Oregon State University News
David Stauth
April 10, 2017


Researchers at Oregon State University (OSU) have developed new software to analyze social media comments, and better understand attitudes that can cause emotional pain, stigmatize people, and reinforce stereotypes. The researchers focused on comments and sentiments expressed about Alzheimer's disease and other forms of dementia. The study showed 51 percent of tweets by private users of Twitter accounts contained stigma, when making reference to this condition and the people who deal with it. The new system could be applied to a range of other social science research questions, and highlights the fact that many people do not adequately appreciate the power of social media to greatly transcend the type of interpersonal, face-to-face communication to which humans are most accustomed. The research is part of a six-year, $2.3-million project funded by the U.S. National Science Foundation to train graduate students in aging sciences.

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MIT Advances in CAD for Manufacturing
 
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