Welcome to the February 13, 2017 edition of ACM TechNews, providing timely information for IT professionals three times a week.

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abstract network environment, illustration UTS to Launch Programming Environment for the Quantum Era
Computerworld Australia
George Nott
February 13, 2017

Researchers at the University of Technology Sydney (UTS) in Australia say they will soon unveil a quantum-era programming environment at the UTS Center for Quantum Software and Information (UTS:QSI). The environment integrates research into a quantum programming language and quantum compilers featuring verification and analysis tools that prove the correctness of the quantum program. UTS:QSI director Runyao Duan says the center is forward-looking and will construct interfaces that are "independent of the architecture and more flexible" for far more complicated machines with hundreds or thousands of quantum bits that are not yet built. "Designing and implementing a quantum programming language and environment...takes years," notes UTS:QSI research director Minsheng Ying. "If we wait until the machine is there, other people will definitely be there." The center's staff is already discussing training a new type of software engineer and envisioning quantum computers communicating with each other over a quantum Internet.

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The Internet and Your Brain Are More Alike Thank You Think, illustration The Internet and Your Brain Are More Alike Than You Think
Salk News
February 9, 2017

Researchers at the Salk Institute say they have found parallels between an Internet algorithm and human brain activity that improve the understanding of engineered and neural networks, with potential insight into learning disabilities. Internet users' ability to find their "sweet spot" in which to channel data while avoiding congestion is enabled by the additive increase, multiplicative decrease (AIMD) algorithm. As computers in a network employ this approach, the entire system can constantly maximize efficiency by adapting to changing conditions. Salk professor Saket Navlakha and Duke University's Jonathan Suen mathematically modeled neural activity using the AIMD template, as the algorithm efficiently maintained smooth information flow, adjusting traffic rates whenever pathways got too clogged. AIMD also could best explain what was occurring in neurons experimentally, and Suen says both the brain and the Internet follow simple rules facilitating global stability.

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AI Learns to Solve Quantum State of Many Particles at Once
New Scientist
Jennifer Ouellette
February 9, 2017

To simulate a quantum system consisting of billions of atoms, an artificial neural network is applying techniques similar to those used to calculate the massive numbers of possible positions in Go. The rules of quantum mechanics dictate that a quantum particle's precise location cannot be known at every point in time. Quantum particles also have a property called "spin," which can be either up or down. Researchers at ETH Zurich in Switzerland and Microsoft built a neural network to demonstrate whether the technique could perform calculations to more easily simulate spins. The network was designed to reconstruct the wave function of a multi-body quantum system and calculate its lowest energy or ground state. The researchers found the technique outperformed other tools that had been applied to many-body systems when testing it on sample problems with known solutions.

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Connected Vehicles in Ohio, Artificial Intelligence With UMass, Northwestern
Network World
Bob Brown
February 8, 2017

The state of Ohio, Ohio State University, and JobsOhio are investing $45 million into the expansion of the Transportation Research Center's (TRC) Smart Mobility Advanced Research and Test (SMART) Center. The research will focus on connected and driverless vehicles. The first phase of the SMART expansion will include the industry's largest high-speed intersection, an urban network of intersections, a rural network that includes wooded roads, and a neighborhood network for slower speeds. TRC often partners with other organizations in Ohio, including along a Smart Mobility Corridor, which is equipped with fiber-optic cabling and sensors. Meanwhile, University of Massachusetts (UMass) Amherst and Northwestern University researchers are working to make the artificial intelligence (AI) process easier, including studies on swarm intelligence/emergent behavior, adaptive AI, transfer learning, and meta-learning. In addition, UMass Amherst recently launched Gypsum, a cluster of 400 graphical-processing units for processing datasets via neural network algorithms.

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A University of Maryland Researcher Helped Create an App to Measure Cellphone Security
The Diamondback (MD)
Rachel Kuipers
February 12, 2017

Researchers at the University of Maryland (UM) helped developed MADCAP, an application to determine when people are most vulnerable to cybercrimes involving their smartphones. MADCAP securely tracks users' locations and the other apps they are using to determine when and where users' phones are most susceptible. The researchers want to address physical security, such as threats from a stolen phone or a criminal eavesdropping on banking login information, as well as cyberthreats. The project aims to understand how people apply security on their smartphones, says UM professor David Maimon. He notes consumers do not seem to realize cellphones are just as insecure as laptops, because many individuals do not use any type of virus protection on their mobile devices. "We know that you are...using your smartphone to log into the Internet, and log into your email account, bank account, so on and so forth," Maimon says.

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MSensors embedded in a baseball Sensors Embedded in Sports Equipment Could Provide Real-Time Analytics to Your Smartphone
University of Illinois News Bureau
August Schiess
February 8, 2017

Researchers at the University of Illinois at Urbana-Champaign (UIUC) Coordinated Science Laboratory are experimenting with Internet of Things devices that can be embedded into sports equipment, as well as in wearable devices, in an effort to make data analytics more accessible to the sports industry. The researchers have devised advanced motion-tracking algorithms for the various incomplete and noisy measurements of inertial measurement unit sensors and wireless radios, fitted within a ball and players' shoes. The tiny sensors utilize inferencing algorithms that can track movement within a few centimeters. Real-time analytics should be possible anytime and anywhere if the technology gains momentum. The researchers say the data also could help detect and analyze player injuries. "We've truly scratched the surface for applications with these sensors," says UIUC Ph.D. candidate Mahanth Gowda. "The algorithms provide extremely fine-grained detail and accuracy in measurements, but use common measuring tools that can be found in any smartphone."

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Inside the Far-Out Glass Lab
Technology Review
Katherine Bourzac
February 2, 2017

Engineers at Corning's research lab in New York are developing new materials in their quest to expand the capabilities of glass. The manufacture of flexible, lightweight, and unbreakable glass could create new product categories ranging from rollable or foldable cellphones and tablets to curved touchscreen displays. Although the bulk of Corning's research focuses on new fabrication processes and gradual enhancements to existing products such as Gorilla Glass, some projects are more experimental. Potential new products are subjected to all types of rough treatment, such as repeated bending, to test their durability and strength. The pressure required to fracture glass is measured by fractography experts, who study the crack patterns for clues about mechanical forces in order to make the glass more resilient. In addition, Corning develops new processes for handling glass, which can help device makers produce custom pieces for new types of electronics.

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New Software for Increasingly Flexible Factory Processes
February 9, 2017

Researchers at the Fraunhofer Institute for Production Technology in Germany have developed software that enables each individual component to carry the information and manufacturing history necessary to complete its manufacturing process. Industrial manufacturing typically follows tightly scheduled and inflexible processes, causing problems when devices fail or unscheduled components need to be processed. Fraunhofer researchers are developing a service-oriented architecture for adaptive and connected manufacturing, which would create a production system in which every component carries the necessary data about the manufacturing steps it needs for completion. Within the Fraunhofer production system, each component stores the outline of its required production steps. Once a processing step is pending, the system selects one of the machines with appropriate capabilities that is available immediately. A record is kept for each production step, detailing what task was executed and which tool was used.

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New system tracks bitcoin transactions New System Makes It Harder to Track Bitcoin Transactions
Matt Shipman
February 8, 2017

Researchers at North Carolina State University, Boston University, and George Mason University have developed TumbleBit, a program that could make it more difficult for observers to track any single bitcoin transaction. TumbleBit utilizes the "mixing service" concept, in which different parties pay an intermediary "tumbler," which then pays the receiving parties. The more parties that are involved, the harder it is to determine which specific parties are involved in any one transaction. However, if an outside observer can compromise the tumbler, it could learn who was paying whom. The researchers say TumbleBit solves this problem with a three-phased approach. The first phase, called escrow, operates on the public blockchain. The second phase involves using cryptographic tools to pay the correct parties without knowing which parties are involved. In the third phase, called cashout, all of the transactions are conducted simultaneously, making it difficult to identify which parties are involved in a transaction.

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Automated Rescue
The Battalion (TX)
Alex Sein
February 6, 2017

The Texas A&M University Center for Robot-Assisted Search and Rescue (CRASAR) builds robots that can work with first responders in search-and-rescue operations. The robots were first deployed during the World Trade Center response and have assisted in operations following Hurricane Katrina and the Fukushima nuclear reactor meltdown. The Emergency Integrated Lifesaving Lanyard (EMILY) is used to reach places where a manned boat or lifeguard cannot, says CRASAR's Grant Wilde. He also notes EMILY can carry various payloads depending on what is needed. Fellow CRASAR participant Jan Dufek says the CRASAR team currently is designing a "smart" EMILY that can navigate autonomously. Equipped with autopilot, a global-positioning system, and telemetry radio, the smart EMILY will be able to navigate waterways on its own and return home autonomously if summoned. Researchers implemented a way for EMILY to be led home by an unmanned aerial vehicle, which also can carry various payloads and is used for navigating in tight spaces.

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Computer Trained to Predict Which AML Patients Will Go Into Remission, Which Will Relapse
IUPUI Newsroom
Richard Schneider; Cindy Fox Aisen
February 9, 2017

Indiana University-Purdue University Indianapolis (IUPUI) researchers say they have developed the first computer machine-learning model to accurately predict which patients diagnosed with acute myelogenous leukemia (AML) will go into remission following treatment for the disease and which will relapse. The researchers trained the system using bone marrow data and medical histories of AML patients, as well as blood data from healthy individuals. The researchers fed the computer new cases that had no information associated with them, which the algorithm evaluated by applying knowledge about similar cases in the database. The researchers found the system was able to predict remission with 100-percent accuracy and relapse with 90-percent accuracy. IUPUI professor Murat Dundar says the work creates and underlies a clinical-decision support system that recognizes the presence of tiny, leftover amounts of malignant cells of any AML type in bone marrow samples, enabling early identification of the change in direction of disease progression.

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AI Systems Are Learning to Communicate With Humans
Sarah Marquart
February 7, 2017

Carnegie Mellon University professor Manuela M. Veloso's CoBots research project is designed to further the development of human-robot interaction. CoBots are mobile indoor service robots that use autonomous navigation and localization. Veloso's team is focused on making CoBots capable of recording their experiences and converting their route data into natural language so they can communicate with humans. Veloso notes the complexity of asking an autonomous robot to express an explanation non-numerically, as the answer can yield many levels of detail. Her team seeks to ease human-robot communication by enabling CoBots to adjust the level of detail they provide based on a person's requests. "We are trying to understand how to empower the robots to be more trustable through these explanations, as they attend to what the humans want to know," Veloso says. She thinks "trustability" in artificial-intelligence systems will benefit from humans' ability to converse, query, and correct their autonomy.

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