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Welcome to the September 23, 2019 edition of ACM TechNews, providing timely information for IT professionals three times a week.

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The aftermath of an El Nino event in Peru Predicting El Niño Up to 18 Months in Advance
Warren Cornwall
September 18, 2019

Researchers at Chonnam National University in South Korea have found that artificial intelligence (AI) can forecast the El Niño storm system 18 months in advance. The AI used was a convolutional neural network trained on global images of historic sea surface temperatures and deep ocean temperatures to ascertain how they correlated to the future generation of El Niño storms. The researchers fed the network recreations of historic ocean conditions produced by reputable climate models often used to investigate climate change, including several thousand simulations of historic data. The AI forecast El Niño states as far ahead as 18 months when tested against actual data from 1984 to 2017, and was more capable of locating which region of the Pacific would experience the highest rise in temperature. Retired researcher William Hsieh said this is a clever approach for bypassing the shortage of El Niño data that limits other forecasting models.

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ACM Forms Global Technology Policy Council
Peter Dinham
September 23, 2019

ACM has established a new Technology Policy Council to coordinate its policy initiatives worldwide, positioning the group to function as a hub of engagement with government organizations, the computing community, and the public on information technology and computing issues. Said ACM president Cherri M. Pancake, "ACM's new Technology Policy Council will provide a space in which computing professionals come together to offer global perspectives on global challenges." Pancake added that ACM's U.S. and European Technology Policy Committees will be folded into the new council. ACM Technology Policy Council chair Lorraine Kisselburgh said the group's mission is to bolster and advance ACM's policy efforts globally. ACM said the council will publish a series of bimonthly technical briefs that summarize emerging technologies and research, and offer nonpartisan views on their policy ramifications to decision-makers, the media, and the general public.

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Tool Advances the Art of Busting Hidden Software Bugs
University of Texas at Dallas
September 23, 2019

Researchers at the University of Texas at Dallas (UTD), working with computer scientists at the University of Texas at Austin, the University of Maryland, and the University of Central Florida, developed a framework to detect variability bugs that appear only when software is configured to work with certain hardware. UTD's Austin Mordahl compared the effort to ordering a pizza, where the initial code base for a program is all the topping options available, and the final product contains selected elements. "If you don't select the part of the code that has a bug in it to be included in the final product — let's say you skipped the anchovies — then no matter how good your off-the-shelf tool is, it will never find the issue because the bug simply doesn't exist in your executable.” The researchers tested 1,000 configurations across three programs, detecting and confirming 77 bugs, 52 of which were variability bugs.

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A man working next to a robot World Record Sales for Robots as Sector Reaches $16.5 Billion in Investment
Greg Nichols
September 20, 2019

The International Federation of Robotics' (IFR) World Robotics Report found that 422,000 robotic units were shipped globally in 2018, an increase of 6% compared to 2017. Among the takeaways from the report was an increase of 23% in annual installations of collaborative robots from 2017 to 2018. China continues to be the world's largest industrial robot market, accounting for 36% of total units installed. Robot installations in the U.S. reached about 40,300 units in 2018, 22% more than the year prior. The report highlighted the growing use of robotics in sectors like construction, mining, and healthcare, as technology developers respond to labor crunches following strong global economies. Said Junji Tsuda, president of IFR, "We saw a dynamic performance in 2018 with a new sales record, even as the main customers for robots—the automotive and electrical-electronics industry—had a difficult year".

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The Santo Antonio hydropower dam AI Helps Shrink Amazon Dams' Greenhouse Gas Emissions
Cornell Chronicle (NY)
Melanie Lefkowitz
September 19, 2019

A model developed by a Cornell University (CU)-led team of researchers uses artificial intelligence (AI) to find the most promising configurations of dam sites to reduce greenhouse gas emissions in the Amazon basin, and could eventually be used to gauge environmental impacts of other power sources in other regions. Using the AI model, the researchers can identify the combination of dams that would produce the lowest amounts of greenhouse gases for a given energy output target. The analysis found that dams built at high elevations tend to have lower greenhouse gas emissions per unit of power output than dams in the lowlands. Said CU’s Alex Flecker, “You have to consider the tradeoffs between generating hydropower and the environmental impact, so society can make the decisions it deems acceptable."

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These States Benefit Most From the Software Industry
U.S. News & World Report
Casey Leins
September 19, 2019

A report by the Software.org:BSA Foundation found that the U.S. software industry is growing twice as fast as the nation's economy, and that California, Nevada, South Dakota, and Wyoming are among the states benefiting most from the increase, each seeing job growth of more than 30% since 2016. Overall, the number of jobs directly created by the industry in the U.S. grew 7.3% from 2016 to 2018 to reach 3.1 million jobs, according to the report. The software industry contributed $1.6 trillion to the U.S. in 2018, a 19% increase from 2016; the average wage for software jobs was $114,000 last year.

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Two men’s faces getting scanned World Catching Up With China on Surveillance Tech
The Wall Street Journal
Ryan Tracy
September 17, 2019

China is the global leader in surveillance technologies, although other countries are catching up, according to a study by the Carnegie Endowment for International Peace. At least 75 nations, including the U.S., support the use of technology to monitor their citizens, with China's Huawei Technologies exporting its surveillance products to 50 countries. In many cases, governments are using U.S. technology in parallel to Huawei's, with IBM the lead U.S. surveillance provider with its smart-city solutions. Report author Steven Feldstein identified 64 countries where government agencies have procured facial recognition technology that uses cameras and photo databases, 56 that have purchased smart-city products, and 53 where authorities employ smart policing systems to analyze data and predict crimes. Said Feldstein, "There is ample time to initiate a much-needed public debate about the proper balance between technology, government surveillance, and the privacy rights of citizens."

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A self-driving Frod car U.S. Gives 3 States Grants for Self-Driving Car Research
Sean Szymkowski
September 16, 2019

The U.S. Department of Transportation has issued Michigan, Ohio, and Virginia its first three Automated Driving Systems Demonstration Grants to research and develop autonomous vehicles. Michigan and Ohio will receive $7.5 million each, and Virginia will receive $15 million. Michigan's grant will be used for general testing and research of self-driving technology, and development of processes to assess autonomous vehicle safety. Smart-vehicle project accelerator DriveOhio said Ohio's grant will be used to fund automated driving projects for rural roads and highways, with deployment handled by the state's Transportation Research Center. Virginia's grant will be allocated to a study of autonomous vehicle communication/interaction in an ideal environment, and a study of self-driving systems for trucks.

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Shape-shifting robot Shape-Shifting Robot Built from 'Smarticles' Shows New Locomotion Strategy
Georgia Tech Research Horizons
September 18, 2019

Georgia Institute of Technology (GIT) researchers have constructed a robot from smaller robots called smart active particles (smarticles) to explore a potential new approach to locomotion. Each three-dimensionally-printed two-armed smarticle flaps its appendages; five smarticles corralled in a circle can nudge each other to form a supersmarticle, which can move by itself. Adding a light or sound sensor enables the supersmarticle to move in response to stimulus and to become sufficiently controllable to navigate a maze. By providing mechanical control over very small robots, the smarticle architecture could eventually support a locomotion/control strategy for small shape-shifting machines. The U.S. Army has expressed interest in this research because it could lead to new robotic systems capable of changing shapes, modalities, and functions.

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Introducing a Virtual Planet Simulator for Modeling Distant Worlds Across Time
UW News
Peter Kelley
September 19, 2019

The University of Washington's Rory Barnes has developed software for modeling planetary evolution over time, with an overarching goal of locating potentially habitable worlds. According to Barnes and colleagues, the VPLanet simulator is designed to model newly discovered exoplanets to measure their potential to support surface liquid water, simulate various planetary and star systems to gain knowledge about their characteristics and history, and facilitate transparent and open scientific research to assist the search for extraterrestrial life. The first VPLanet iteration features modules for internal and magnetic evolution of planets, climate, atmospheric escape, tidal forces, orbital evolution, rotational effects, stellar evolution, planets orbiting binary stars, and gravitational perturbations from passing stars. Barnes said, "This is a tool that allows us to ask: 'How do various properties of a planetary system evolve over time?'"

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Neural Nets Probe Dark Matter in the Universe
ETH Zurich
Oliver Morsch
September 18, 2019

Researchers at ETH Zurich in Switzerland used machine learning algorithms to estimate the amount of dark matter in the universe. The ETH Zurich researchers taught deep artificial neural networks to extract the greatest amount of information from mass maps of the sky showing where dark matter is located by feeding the networks computer-generated data that simulates the universe. By analyzing iterations of the dark matter maps, a neural network learned to extract the desired data, coming up with values 30% more accurate than those obtained by human-made statistics. The scientists then used their trained neural network to analyze actual dark matter maps. Said ETH Zurich researcher Alexandre Refregier, “Facebook uses its algorithms to find eyes, mouths, or ears in images; we use ours to look for the tell-tale signs of dark matter and dark energy."

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