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Welcome to the July 24, 2019 edition of ACM TechNews, providing timely information for IT professionals three times a week.

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A crowd of people 'Anonymized' Data Can Never Be Totally Anonymous, says Study
The Guardian
Alex Hern
July 23, 2019


Researchers at Université catholique de Louvain (UCLouvain) in Belgium and Imperial College London in the U.K. have developed a model to estimate how easy it would be to deanonymize an arbitrary dataset. For example, they said a dataset with 15 demographic attributes "would render 99.98% of people in Massachusetts unique." The model requires fewer attributes for smaller populations, and the researchers said if town-level data were included with those 15 demographic attributes, "it would not take much to re-identify people living in Harwich Port, MA, a city of fewer than 2,000 inhabitants." The researchers said their results demonstrate that anonymization is not sufficient for private companies to avoid conflicts with laws such as Europe's General Data Protection Regulation, and the California Consumer Privacy Act. They stressed the need “to move, from a legal and regulatory perspective, beyond the deidentification release-and-forget model.”

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Sam Altman With $1 Billion from Microsoft, an AI Lab Wants to Mimic the Brain
The New York Times
Cade Metz
July 23, 2019


Microsoft has made a $1-billion investment in OpenAI, the artificial intelligence lab created by Elon Musk and Sam Altman in 2015. Musk left the nonprofit last year, and Altman has since transformed OpenAI into a for-profit company so it could more aggressively pursue financing. OpenAI researchers will use the funding to develop artificial general intelligence (AGI), which would match the capabilities of the human brain. Said Geoffrey Hinton, a Google researcher and co-recipient of the 2018 ACM A.M. Turing Award, “It's too big a problem. I'd much rather focus on something where you can figure out how you might solve it.”

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Utah County to Pilot Blockchain-Based Mobile Voting
Computerworld
Lucas Mearian
July 23, 2019


Utah County, UT, is the third U.S. county to test an application based on blockchain to allow voting via smartphones for military members and their dependents. The Voatz app uses a permissioned blockchain based on the HyperLedger framework. In an election, verified validating nodes are used, split evenly between Amazon Web Services and Microsoft Azure, each of which are geographically distributed. Authentication requires voters to scan their state driver license or a passport, then take a facial snapshot, and finally they must touch the fingerprint reader on the smartphone, which ties the device to that specific voter. Once a voter is authenticated, the app matches the voter's snapshot to the facial picture on their identification and confirms eligibility by checking the state's voter registration database. A recent report by ACM’s U.S. Technology Council observed that until there is a fundamental technological breakthrough in Internet security, the best method of protecting election integrity remains mailed paper ballots.

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Picture of a microchip Microchip Aims to Stump Hackers with a Constantly Moving Target
Technology Review
Martin Giles
July 17, 2019


Researchers at the University of Michigan have developed a prototype of a defensive cybersecurity approach that aims to frustrate hackers trying to gain control of microchips by presenting them with a moving target. Morpheus works by repeatedly randomizing elements of the code attackers need access to in order to compromise the hardware. The researchers designed the chip's code to "churn" every 50 milliseconds, so even if hackers find a vulnerability, the information needed to exploit it disappears before they can do so. As a result, the technology can defend against a wide range of cyberattacks. A team of U.S. national security experts plans to test the chip to see if they can compromise its defenses, and some of Morpheus's code will be posted online so other researchers can try to find any flaws within it.

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Erol Gelenbe speaking as French Minister of Higher Education Gelenbe Decreed a Commander of the National Order of Merit of France
NYU Tandon School of Engineering
July 3, 2019


Erol Gelenbe, a professor in the Department of Electrical and Electronic Engineering at Imperial College, London, an ACM Fellow, and recipient of the ACM SIGMETRICS Achievement Award in 2008, was awarded the insignia of the Commander of the National Order of Merit of France, for his services to higher education and research. Gelenbe designed and patented the packet-voice telephone switch, and designed and built the first random access Local Area Network using fiber-optic connections. He also developed the mathematical models known as G(elenbe)-networks to analyze and optimize communication networks (used in applications like traffic re-routing and network optimization), and invented the Random Neural Network.

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Computers Are the New Basketball Coaches
The Wall Street Journal
Ben Cohen
July 19, 2019


Professional basketball teams are starting to use computers and advanced data analytics to help perfect players' jump shots. Computerized systems such as HomeCourt, RSPCT, and Noah keep a comprehensive record of a range of data about every basketball shot taken. For example, the National Basketball Association (NBA) uses Noah at the draft combine to evaluate players. Noah relies on a machine learning algorithm, trained on more than 20 million shots, to make reliable predictions from limited samples. If a player takes just 50 shots at the combine, a three-dimensional profile of those shots reveals more about the players ability than simply their shooting percentage. Said John Carter, CEO of Noah Basketball, “The most common quote I hear, whether it's a middle-school coach, high-school coach, college or NBA, is that today's players will not argue with a computer."

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Research group of professor Insik Shin Flexible User Interface Distribution for Ubiquitous Multi-Device Interaction
KAIST
July 20, 2019


Researchers at the Korea Advanced Institute of Science & Technology (KAIST) in South Korea have developed a mobile software platform that allows a mobile application to be executed simultaneously and more dynamically on multiple smart devices. The FLUID platform can flexibly distribute the user interfaces (UIs) of an app to several other devices in real time without needing any modifications. The technology provides single-device virtualization, ensuring that the interactions between the distributed UI elements across multiple devices remain intact. FLUID can support 5G multi-view apps, allowing the user to watch an event from different viewpoints on multiple devices without switching viewpoints on a single screen.

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Knight Foundation Invests $50 Million in Research on Tech's Impact on Democracy
The Washington Post
Cat Zakrzewski
July 22, 2019


The nonprofit John S. and James L. Knight Foundation will spend $50 million to fund research at 11 universities in how social media and technology impacts democracy. The organization has been trying to address trends that are changing journalism, such as how fake news undermines trust online. The funding will be put towards long-term research on the intersection of technology and politics at five universities, with shorter-term research projects at six other institutions. Said foundation president Alberto Ibarguen, “It's our modern-day Gutenberg moment. Even as we embrace the benefits of the Internet, we need to grapple with its effect on our democracy."

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Israeli Researchers Develop Algorithm to Predict Infectious Diseases
Jerusalem Post
Eytan Halon
July 22, 2019


Researchers at the Weizmann Institute of Science in Israel have developed a method which they say can predict the onset of infectious diseases such as tuberculosis. The researchers used this method to sequence gene activity in real meetings between thousands of immune cells and Salmonella bacteria. The method allowed the researchers to see cells’ responses to the bacteria, and map each cell’s activation profile. The team identified different responses and patterns from the initial meetings between the cells and bacteria and their later outcomes, from which they developed an algorithm based on deconvolution to get similar data on the properties of individual cells from standard blood test data sets. Said Institute researcher Noa Bossel Ben Moshe, "The algorithm we developed can not only define the ensemble of immune cells that take part in the response, it can reveal their activity levels and thus the potential strength of the immune response."

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Application of ML in the Discovery of New Polymers
Tokyo Tech News
July 19, 2019


Researchers in Japan used machine learning (ML) to design and verify polymers with high thermal conductivity, a property that would be vital to heat management in 5G mobile communications technologies. The researchers drew on a dataset of polymeric properties from PoLyInfo, the largest database of polymers in the world. However, PoLyInfo has a limited amount of data on the heat transfer properties of polymers. The researchers developed ML models on proxy properties to predict the heat transfer properties from the limited data. The team used this method to identify three polymers that showed the most promise, based on their ease of synthesis and processing. Said Junko Morikawa of the Tokyo Institute of Technology, "We would like to try to create an ML-driven high-throughput computational system to design next-generation soft materials for applications going beyond the 5G era."

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Harvard Data Science Review
 
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