Welcome to the April 28, 2017 edition of ACM TechNews, providing timely information for IT professionals three times a week.
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Flexible Tactile Sensor Lets Robots Feel
EE Times Asia
April 27, 2017
Researchers at the Korea Advanced Institute of Science and Technology (KAIST) have developed a tactile sensor composed of silicon and carbon materials that can serve as a skin for robots, absorb shocks, and differentiate between various forms of touch. The researchers combined silicon and carbon nanotubes to produce a composite, which was paired with a medical-imaging technique called electrical impedance tomography. The team says the new material can distinguish between the location and the size of various forms by touch. In addition, it can withstand strong force, as well as function as a three-dimensional computer interface and tactile sensor. The researchers also note it can be reused even after partial damage to the sensor by filling and hardening the damaged region with composite. "This technology will contribute to the soft robot industry in the areas of robot skin and the field of wearable medical appliances," says KAIST professor Jung Kim.
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Rice's Lydia Kavraki Wins ACM Athena Lecturer Award
Rice News
Jade Boyd
April 26, 2017
Rice University professor and ACM Fellow Lydia Kavraki will receive this year's ACM Athena Lecturer Award for her invention of randomized motion-planning algorithms in robotics and robotics-inspired techniques for bioinformatics and biomedicine via analysis of the motion, shape, and flexibility of molecules. "Planning the motion of objects in a three-dimensional space has been a central challenge in the robotics field for a long time," says ACM president Vicki Hanson. "Lydia Kavraki's Probabilistic Roadmap Method has had a tremendous impact. It is now widely used in robotics applications in industry and is a foundational idea for numerous researchers in the field." Kavraki also helped create the open source Open Motion Planning Library, which is used in more than 30 robotics systems worldwide. In addition, Kavraki previously has received ACM's Grace Murray Hopper Award, the Anita Borg ABIE Technical Leadership Award, and Rice's Presidential Award for Mentoring.
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Spyware That Can Identify What Films You Are Watching
The Economist
April 27, 2017
Researchers at Tel Aviv University in Israel and Cornell University have developed neural network-based detection algorithms that can read what movies people who use streaming services are viewing, even when they cannot directly monitor the stream of bits delivering them, or access the device on which users are watching them. The technique identifies the video "fingerprint" of streaming content mined from a pattern of information "bursts" derived from the streaming service's application of variable bit-rate compression. The researchers say they can determine with up to 99-percent accuracy the video fingerprint by comparing a pre-assembled library of prints the hacker has compiled from videos whose viewers they might want to surveil. A hacker only has to plant a small amount of JavaScript code in a Web browser on a personal computer or smartphone attached to the same Wi-Fi network as the viewer's device.
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Two Leading Singapore Universities Announce Initiatives to Strengthen Research and Development in Data Science & Artificial Intelligence
OpenGov Asia
Priyankar Bhunia; Dean Koh
April 28, 2017
Nanyang Technological University (NTU) and the National University Singapore (NUS) are partnering with industry to bolster research and development in data science and artificial intelligence (AI) and develop innovative solutions and products for Singapore's society and economy. NTU says its new Data Science & Artificial Intelligence Research Center will have 60 scientists, and focus on projects that include crowd-sensing via light-emitting devices and an undertaking with NVIDIA to develop a deep-learning model for detecting software bugs and vulnerabilities in sophisticated computing systems. Meanwhile, NUS will rename its Interactive and Digital Media Institute the NUS Smart Systems Institute (SSI), which will concentrate on building strong capabilities and expertise in AI and big data analytics. SSI research also will include augmented reality, virtual reality, the Internet of Things, and media technologies, as well as participating in NUS' Smart Nation Research Cluster.
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Can Early Experiences With Computers, Robots Increase STEM Interest Among Young Girls?
UW Today
Kim Eckart
April 27, 2017
Six-year-old girls exposed to a computer-programming activity had more interest in technology and more positive outlooks about their own skills compared to non-participants, according to a study from the University of Washington's Institute for Learning & Brain Sciences (I-LABS). I-LABS researcher Allison Master says the study suggests a desire and an opportunity for teaching computer science in elementary school. The study involved boys and girls participating in several activities, including programming a robot's movements, which significantly reduced the gender gap in tech interest and self-efficacy. "If you give them equal access to the same opportunities, then girls and boys have the same response--equal interest and confidence," Master notes. I-LABS co-director Andrew Meltzoff notes bringing the girls' interest and motivation in science, technology, engineering, and math up to the level of the boys is the most significant finding. However, despite the activities, children's stereotypical perception of boys as more tech-adept than girls was not altered.
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Wireless Power Could Enable Ingestible Electronics
MIT News
Anne Trafton
April 27, 2017
Researchers at the Massachusetts Institute of Technology (MIT), Brigham and Women's Hospital, and the not-for-profit Charles Stark Draper Laboratory have developed a method for wirelessly powering ingestible electronic devices. The technique employs wireless power transfer from an outside antenna to another antenna within the gastrointestinal (GI) tract. The researchers say by staying in the digestive tract indefinitely, the device could monitor physiological functions or changes, or deliver drugs. Research team member Abubakar Abid says using midfield transmission enabled the delivery of 100 to 200 microwatts of power to the device, which is more than sufficient to run small electronics. A study involving pigs demonstrated the method held no danger of tissue damage, with the outside antenna transferring power in a 2-cm to 10-cm range. "It's really a proof of concept in establishing an alternative to batteries for the powering of devices in the GI tract," says MIT's Giovanni Traverso.
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TCD Scientists Develop System for Emergency Services
RTE.ie
April 26, 2017
Researchers at Trinity College Dublin (TCD) in Ireland have developed Slandail, a social media-monitoring system designed to help emergency responders. The system gathers information from social networks and feeds it into the emergency management software used by police, firefighters, paramedics, and other emergency responders. The system can incorporate a wide range of text, image, and video content posted by people involved in accidents or disasters on social media platforms. The software then uses text and image analytics and machine learning to understand the data before feeding it into other programs used by disaster management services. The system also can monitor cross-border disasters because it was built to support English, German, and Italian. "We have produced a prototype solution that allows these teams to drown out the unhelpful noise and instead systematically capture useful information spread via social media to assist disaster management as efficiently as possible," says TCD professor Khurshid Ahmad.
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A Substantial Boost for Easily and Safely Producing New Online Apps
CORDIS News
April 25, 2017
SwellRT is a framework for the development of collaborative decentralized apps. Originally developed as part of the European Union-funded P2PVALUE project, SwellRT's codebase is now being hosted by the Apache Software Foundation. The major benefit of SwellRT is its apps and their users are not dependent on one central server controlled by the service provider. The decentralized design is necessary for the growth of a commons-based peer production (CBPP) economic model that aims to coordinate the creative energy of large numbers of individuals. SwellRT is the only backend-as-a-service (BaaS) technology capable of working in a decentralized manner due to an open protocol to interconnect services and exchange data in real time. Decentralization enables SwellRT applications to offer greater freedom for users when deciding where to store their data and with which organizations and people they want to share it. In addition, decentralization offers higher levels of app resilience and interoperability.
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When Artificial Intelligence Evaluates Chess Champions
CNRS
April 24, 2017
The ELO system for measuring chess players has been used since the 1970s, ranking players according to the result of their games. The best players have the highest ranking, and the difference in ELO points between two players predicts the probability of either player winning a given game. However, this method does not account for the quality of the moves played during a game, and is therefore unable to reliably rank players who have played at different times. Jean-Marc Alliot at the Computer Science Research Institute of Toulouse in France has developed a new system that directly ranks players based on the quality of their chess moves. The system, which runs on the OSIRIM supercomputer, computes the difference between the move actually played and the move that would have been selected by Stockfish, the best chess program currently available.
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New System Detects Hate Speech in Tweets via Deep Learning
The Stack (UK)
John Bensalhia
April 26, 2017
Researchers at IIIT-Hyderabad's Informational and Retrieval Extraction Lab (IREL) in India have developed a system that uses artificial intelligence chatterbots to detect the presence of hate speech in tweets. The researchers say the chatterbots can identify instances of racist or sexist speech, or abusive language, and flag offensive content. In addition, the system can analyze public sentiment in order to find the cause of the problems via user-generated content. The system employs supervised learning, in which an algorithm is fed several examples of text used in tweets of a racist or sexist nature to detect the presence of hate speech. The IREL researchers say the algorithm is designed to "learn" when it examines data. After the algorithm is finished, the program then uses neural networks to detect the presence of racist or sexist language in text.
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DNA, the Ultimate in Data Memory
EE Times
Ron Neale
April 20, 2017
Researchers at Columbia University and the New York Genome Center have demonstrated the ability to store an operating system, a movie, and other files totaling more than 2 megabytes in DNA molecules. They accomplished this by upgrading the method's efficiency and reliability. The process relies on a technique based on "Fountain" codes, in which instead of repeating the transmission when an erroneous piece of a data stream is received, sufficient bytes are relayed to permit the correct data to be extracted. The researchers added a selection or screening process to maximize the efficacy of the process and to fully realize each nucleotide's coding potential. They suggest DNA would provide a memory density of 215 petabytes per gram.
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Internet of the Future: Massive Mobile Antennae Technology
Aalborg University
Jakob Brodersen
April 20, 2017
Researchers at Aalborg University in Denmark are developing a new Multiple-Input Multiple-Output-based antenna technology involving mobile base stations for 5G solutions that will consist of hundreds of small antennas. The base system is designed to meet the increasing need for data transmission capability due to the proliferation of the Internet of Things. The system is used to transmit and receive data between a large number of connected devices and users at the same time. In conventional mobile base stations, each unit might have a maximum of eight antennas that point in different directions, spreading data transmission over a large area. However, the Aalborg team is working on a base station unit that incorporates several hundred antennas, making it possible to connect much more precisely to each mobile unit. In addition, the new system should improve the security of the data transmission.
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Sensor-Filled Glove Could Help Doctors Take Guesswork Out of Physical Exams
UCSD News (CA)
Daniel Kane
April 20, 2017
Researchers at the University of California, San Diego's (UCSD) California Institute for Telecommunications and Information Technology (Qualcomm Institute) and Rady Children's Hospital have developed new wearable sensors and robotics technology that could be used to accurately measure muscle stiffness during physical exams. "Our goal is to create a system that could augment existing medical procedures by providing a consistent, objective rating," says Harinath Garudadri, the project's lead investigator. The researchers created a glove equipped with sensors that will enable doctors to establish objective, accurate, and consistent number ratings when evaluating spasticity in patients undergoing treatment. The glove has more than 300 pressure sensors that measure the amount of force required to move a patient's limb. In addition, a motion sensor taped on the back measures how fast the limb is being moved. Data from the sensors are transmitted to a computer, where they are integrated, processed, and mapped using signal-processing algorithms.
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