Welcome to the July 12, 2017 edition of ACM TechNews, providing timely information for IT professionals three times a week.
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China Trial Paves Way for 'Unhackable' Communications Network
Financial Times
Yuan Yang
July 10, 2017
Researchers in Jinan, China, have successfully tested an "unhackable" communications network, a breakthrough that could lead to the world's first wide-scale commercial application of quantum communications. The trials involved sending highly secure information between 200 different terminals in Jinan over a network covering several hundred square kilometers (km). "We plan to use the network for national defense, finance, and other fields, and hope to spread it out as a pilot that, if successful, can be used across China and the whole world," says Jinan Institute of Quantum Technology assistant director Zhou Fei. The network will be part of the Beijing-Shanghai quantum network, which is currently under construction, and will rely on Jinan, which is between the other two cities, as an inter-city hub to route messages. The Beijing-Shanghai network will host the world's longest land-based quantum communications channels, stretching more than 2,000 km.
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Bangalore Taps Tech Crowdsourcing to Fix 'Unruly' Gridlock
Bloomberg
Saritha Rai
July 9, 2017
India's Gridlock Hackathon aims to find solutions to the congested roads that cost the economy billions of dollars. Although the prize totals just $5,500, the contest is attracting major international technology companies, as well as local startups. The online contest is crowdsourcing solutions for Bangalore, India, which is struggling with inadequate roads, unprecedented growth, and overpopulation. The ideas put forth at the hackathon include using artificial intelligence and big data on traffic flows, as well as true moonshots, such as flying cars. The contest has drawn more than 1,000 teams, including those from Seattle, WA, Atlanta, GA, and Dubai, United Arab Emirates. The Gridlock Hackathon is the type of contest Indian cities desperately need, according to Biocon chairman Kiran Mazumdar-Shaw. "Only innovative thinkers can come up with technology solutions for the problems that plague cities nationwide," she says.
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Human Pose Estimation for Care Robots Using Deep Learning
Toyohashi University of Technology
July 10, 2017
Researchers at Toyohashi University of Technology in Japan have developed a method of pose recognition using only depth data that could be applied to home care robots. Although there are currently available methods and instruments for identifying poses such as upright positions and sitting positions, home care robots must be able to identify other poses, such as a recumbent position and a crouching position, which have been more difficult to develop until now. The researchers have established a method to generate a large amount of training data for these positions by combining computer graphics (CG) technology and motion-capture technology. The new method first creates CG data of various body shapes. It then adds information on each body part, including skeleton information for each joint position, which makes it possible to make CG models take arbitrary poses by giving the joint angles using a motion-capture system.
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Dutch Database Design Drives Practical Innovation
ComputerWeekly.com
Jasper Bakker
July 10, 2017
Martin Kersten has become just the third citizen of the Netherlands to be recognized as an ACM Fellow, following previous recipients Edsger Dijkstra (also recipient of the 1972 ACM A.M. Turing Award) and Andrew Tanenbaum (also recipient of the 1994 ACM Karl V. Karlstrom Outstanding Educator Award). Kersten, a professor at Centrum Wiskunde & Informatica (CWI), says the award signifies international recognition for CWI and the country as a whole. Kersten's 2016 ACM Fellow Award was for a wide range of database design work, and specifically for his work on the design and implementation of column store and main memory database systems. In-memory databases are now commonly used in the information technology field, as is column storage of information databases. In traditional databases, the database administrator needs to make or choose indexes of the data. However, that is not the case for column-based databases, which enables much faster processing of certain queries for specific applications, according to Kersten.
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Neural Network Poetry Is So Bad We Think It's Written by Humans
New Scientist
Matt Reynolds
July 7, 2017
A neural network trained on poetry has attempted to write its own lines that mimic certain forms of verse. Its best efforts can convince people they are reading the words of a human poet. The poetic bot was developed by Jack Hopkins while he was a researcher at the University of Cambridge. It can be programmed to write in a particular rhythm or write poems on specific themes and can be endlessly tweaked to generate various forms. For example, Hopkins says it could write about Brexit in the style of a Greek epic or rewrite parts of Romeo and Juliet while mimicking a rapper. The AI poet was trained on more than 7 million words of 20th-century English poetry, most of it from poetry books found online. Hopkins also instructed the neural network to keep checking to make sure some of the words in each line relate to the selected theme.
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11,000 Girls Compete in International Mobile App Challenge
THE Journal
Richard Chang
July 6, 2017
Girls from around the world are competing in the Technovation Challenge, a global effort by Iridescent, a nonprofit promoting science, technology, engineering, and math education, which has invited girls ages 10-18 to learn and apply technology to try to solve problems in their communities. This year, 11,000 girls worked in teams of one to five to develop mobile applications and address the United Nations Sustainable Development Goals (SDG). The projects were required to address at least one issue within the SDG focus areas: quality education, poverty elimination, good health and well-being, climate action, peace and justice, and gender equality. The teams were supported by more than 2,000 mentors, who helped the participants use professional-style business planning to launch the apps. Twelve teams of finalists will be flown to Silicon Valley Aug. 7-11 where they will compete at the World Pitch Summit and pitch their ideas for $145,000 in seed funding and scholarships.
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Luna Brings Visual Development to Functional Programming
InfoWorld
Paul Krill
July 6, 2017
The Luna functional language seeks to enable application assembly by clicking and dragging visual elements together. Its compiler will produce native code for the developer's choice of Linux, MacOS, Windows, or JavaScript. The team behind Luna is seeking candidates for a private alpha release. They note software can have thousands of lines of code distributed across hundreds of files, which can impede the implementation of visual data flow and application architecture. As a result, Luna features both visual and textual representations. Developers can maintain their coding habits while also having a graphical whiteboard-like interface. Luna uses prototyping and visual profiling to understand performance bottlenecks and gathers information on computation time, memory allocation, network transfer, and threading model. Developers also will be able to create a "foreign" node and paste in Python, Haskell, JavaScript, and C++ programming, but their source code cannot be represented graphically like Luna code can.
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UW's Lip-Syncing Obama Demonstrates New Technique to Turn Audio Clips Into Realistic Video
GeekWire
Kurt Schlosser
July 10, 2017
University of Washington (UW) researchers have developed a system that can take audio clips from one speech and sync them with video clips from another speech, creating realistic-looking lip-synced videos. The researchers say the technology could be used to apply a moving face to historic audio recordings, or to improve videoconferencing. In a demonstration of the technology, the researchers used video of former U.S. President Barack Obama from a range of appearances and combined it with audio spoken in separate instances. A recurrent neural network, trained on many hours of Obama's weekly address footage, learned the mapping from raw audio features to mouth shapes. "These type of results have never been shown before," says UW professor Ira Kemelmacher-Shlizerman. The researchers note the technology also could lead to better video chat performance. The system will be presented at the upcoming ACM SIGGRAPH 2017 conference in Los Angeles, CA.
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Why Do Some Neighborhoods Improve?
MIT News
Larry Hardesty
July 6, 2017
Researchers at the Massachusetts Institute of Technology (MIT) and Harvard University have used a four-year-old computer vision system to quantify the physical improvement or deterioration of neighborhoods in five U.S. cities. The system originally was developed to analyze street-level photos taken in urban neighborhoods in order to measure how safe the neighborhoods would appear to human observers. The new system compared 1.6 million pairs of photos taken seven years apart. The researchers used those comparisons to determine that the density of highly educated residents, the proximity to central business districts and other physically attractive neighborhoods, and the initial safety score assigned by the system all correlate strongly with improvement in physical condition. The machine-learning system that assigned the safety ratings was trained on hundreds of thousands of examples, which were rated by human volunteers. The researchers validated the system's analyses by presenting it with 15,000 randomly selected pairs of images and compared its results with those of humans on Amazon's Mechanical Turk; they agreed 72 percent of the time.
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Building a Secure OS From the Ground Up
Government Computer News
Patrick Marshall
July 6, 2017
Texas A&M University professor Guofei Gu is leading a team of researchers, including colleagues from Clemson University, the University of Colorado, the University of North Carolina, and the University of Texas, to build S2OS, a new operating system with security as the primary consideration. The researchers have received $3 million from the U.S. National Science Foundation to develop S2OS, a software-defined hypervisor that creates and manages virtual machines. The technology is being designed to centrally manage networking, storage, and computing resources. Gu notes developing an OS as a software-designed infrastructure that supports virtual machines delivers advantages that older operating systems lack. For example, since the OS is running as a virtual machine, it is protected from attacks at the application layer. In addition, if the system operates as a hypervisor, it sits above all program and network activity and is more protected from malware.
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Stanford Computer Scientists Develop an Algorithm That Diagnoses Heart Arrhythmias With Cardiologist-Level Accuracy
Stanford News
Taylor Kubota
July 6, 2017
Stanford University researchers say they have developed an algorithm that can sift through hours of hearth rhythm data generated by wearable monitors to find possibly life-threatening irregular heartbeats, known as arrhythmias. The algorithm performs better than trained cardiologists, and can analyze data from remote locations where people do not have routine access to cardiologists. The researchers set out to develop a deep-learning algorithm to detect 14 types of arrhythmia from electrocardiogram (ECG) signals. They collected a dataset of approximately 30,000 30-second clips from various patients representing a variety of arrhythmias, which they used to train a deep neural network model. The researchers tested the accuracy of the algorithm by presenting a group of three cardiologists with 300 undiagnosed clips and asking them to agree on any arrhythmias present in the recordings. The algorithm used the annotated clips to predict how those cardiologists would label other ECGs.
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A Computer That Reads Body Language
Carnegie Mellon News
Byron Spice
July 6, 2017
Researchers at Carnegie Mellon University's (CMU) Robotics Institute have developed a computer capable of understanding body poses and movements of multiple people from video in real time, including the pose of each individual's fingers. The team says they used a two-story dome with 500 embedded video cameras, and the insights gained from experiments in that facility can enable the identification of a pose of a group of people using one camera and a laptop. The researchers first localized all the body parts in a scene, and then associated those elements with specific individuals. CMU's Hanbyul Joo says the multi-camera dome was useful in not only capturing views of each individual's hands from every conceivable angle, but also for automatically annotating the hand position. CMU professor Yaser Sheikh notes as research moves to transition from two-dimensional models of humans to three-dimensional models, this automatic annotation generation capability will become essential.
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An Emotionally Intelligent Cognitive Assistant to Help People With Alzheimer's Disease
University of Waterloo
June 29, 2017
Researchers at the University of Waterloo in Canada have developed ACT@Home, a prototype emotionally intelligent assistant that interprets the dynamics of human interaction and then responds accordingly. ACT@Home is an automated assistance technology that combines artificial intelligence with mathematical models of affect control theory (ACT), a sociological framework that proposes people conduct themselves in a way to generate feelings that are appropriate to the situation or context, according to Waterloo professor Jesse Hoey. The researchers say the technology could be used by people with Alzheimer's disease. Hoey and his team have been conducting qualitative interviews of people with Alzheimer's and their caregivers to better understand the disease. "Our goal is to take the findings from these interviews to develop an inexpensive home-based emotionally intelligent cognitive assistant that helps people with Alzheimer's disease while lightening the burden on their caregivers," Hoey says.
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