MS in Data Science
Welcome to the February 24, 2020 edition of ACM TechNews, providing timely information for IT professionals three times a week.

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A woman wearing a mask to prevent the coronavirus uses her mobile phone at a shopping district in Seoul, South Korea Mapping Coronavirus: South Koreans Turn to Online Tracking as Cases Surge
Sangmi Cha
February 24, 2020

Private software developers have launched websites and apps to help people in South Korea track cases of coronavirus and avoid places where infected people have been. The South Korean government, having been criticized for how it handled past disease outbreaks, initially released very detailed information on confirmed cases of coronavirus, including the age, gender, and daily routes infected people took before being quarantined. While identities were not published with the data, web developers were able to use the information to create detailed maps tracking the movements of those infected. One of the sites,, receives more than 300,000 views daily, while another,, shows a real-time tally of coronavirus infections, deaths, and discharged patients in South Korea and around the world.

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A self-driving car driving in a snow filled road This Self-Driving Car Looks Under the Road for Safety Boost in Rain, Snow
Charlie Osborne
February 24, 2020

Academics at the Massachusetts Institute of Technology (MIT)'s Computer Science and Artificial Intelligence Laboratory have proposed a method to improve driverless car safety by circumventing cameras and LiDAR navigation. The system uses localizing ground-penetrating radar (LGPR) to emit electromagnetic pulses under the road, measuring the composite soil, roots, and rock there to generate an alternative "map" of the ground's makeup. This map can help orient the vehicle, even in bad weather. MIT's Teddy Ort said, "LGPR can quantify the specific elements there and compare that to the map it's already created, so that it knows exactly where it is, without needing cameras or lasers."

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AI Algorithm Better Predicts Corn Yield
I Illinois ACES
Lauren Quinn
February 20, 2020

An interdisciplinary research team at the University of Illinois at Urbana-Champaign has developed a convolutional neural network (CNN) that generates crop yield predictions, incorporating information from topographic variables such as soil electroconductivity, nitrogen levels, and seed rate treatments. The team worked with data captured in 2017 and 2018 from the Data Intensive Farm Management project, in which seeds and nitrogen fertilizer were applied at varying rates across 226 fields in the Midwest U.S., Brazil, Argentina, and South Africa. In addition, on-ground measurements were combined with high-resolution satellite images from PlanetLab to predict crop yields. Said Illinois's Nicolas Martin, while "we don’t really know what is causing differences in yield responses to inputs across a field … the CNN can pick up on hidden patterns that may be causing a response.”

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An elephant next to a “No Poaching” sign Coding for Uncertainty Increases Security
Harvard University John A. Paulson School of Engineering and Applied Sciences
Leah Burrows
February 20, 2020

Computer scientists at Harvard University’s John A. Paulson School of Engineering and Applied Sciences (SEAS) designed an algorithm to combat poaching in wildlife preserves by causing surveillance drones to strategically signal, in the hope they can fool poachers into thinking they have been spotted. The scientists engineered the GUARDSS algorithm to account for uncertainties, so if a ranger is not near when the drone spots a poacher, the software's calculations will determine whether the drone signals or not. The drone also may signal even if it sees nothing, to account for uncertainty. Said SEAS' Haifeng Xu, "Such bluffing tactics can also be rigorously computed and implemented as algorithms for the purpose of social good, like to combat illegal poaching."

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Facebook Offers to Pay Users for Voice Recordings
Financial Times
Tim Bradshaw
February 21, 2020

Facebook is offering to pay users for their personal information, including recordings of their own voices. The tech giant's offer is a rare example of Internet companies directly compensating people for collecting their data. The social media giant’s offer applies to voice recordings made through the company's new market research app Viewpoints. The recordings reportedly will be used to help train the speech recognition system that powers Facebook's Portal devices. Facebook, Amazon, Apple, Google, and other makers of smart speakers faced criticism last year after it emerged that they routinely sent users' voice recordings to human moderators without first obtaining consent.

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Sign of Boston Scientific More Manufacturers Bet on Simulation Software
The Wall Street Journal
Angus Loten
February 20, 2020

Manufacturers increasingly are using simulation software to test new or revamped production lines prior to operation. Market research firm ABI Research estimated roughly 110,000 companies worldwide will employ simulation software within the next five years. ABI's Michael Larner said manufacturers use simulation software to assess how planned production-line changes will likely impact production. The software integrates computer-aided design apps, business process management software, and other systems to test changes before implementation. Said Jodi Euerle Eddy with medical-devices manufacturer Boston Scientific, "Simulation software allows us to improve our capabilities and optimize spend, enabling faster problem-solving and continuous improvement."

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Study Finds Quarter of Climate Change Tweets From Bots
BBC News
February 22, 2020

A study by Brown University researchers found 25% of 6.5-million Twitter posts about climate change were likely produced by bots, giving the impression of widespread climate change denial. The tweets were posted during the period surrounding President Trump's June 2017 announcement that the U.S. was withdrawing from the Paris climate accord, with most denying global warming or repudiating climate science. The researchers used an Indiana University tool called Botometer to gauge the likelihood of tweets' posting by bots or humans; posts about "fake science" were identified as coming from bots 38% of the time, as were 28% of tweets about oil company Exxon. Only 5% of tweets supporting action against climate change came from bots. The University of Southern California's Emilio Ferrara said, "If someone is manipulating the messages that we consume online, then there is a reason to be concerned that they are changing people's perceptions or beliefs."

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Mixed-Signal Hardware Security Thwarts Electromagnetic Attacks
Purdue University News
Chris Adam
February 19, 2020

Researchers at Purdue University have developed technology that addresses physical-layer vulnerabilities in Internet-connected devices with physical-layer solutions. The researchers developed the system to use mixed signal circuits to embed the crypto core within signature attenuation hardware with lower-level metal routing. This means the critical signature is suppressed even before it reaches the higher-level metal layers and the supply pin, significantly reducing electromagnetic and power information leakage. Purdue's Debayan Das said side-channel attacks "are becoming a significant threat to resource-constrained edge devices that use symmetric key encryption with a relatively static secret key like smart cards.” She added, “Our protection mechanism is generic enough that it can be applied to any cryptographic engine to improve side-channel security."

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Computers Scour Satellite Imagery to Unveil Madagascar's Mysteries
Penn State News
February 17, 2020

Pennsylvania State University (Penn State) researchers collaborated with the Universite de Toliara and the Morombe Archaeological Project in Madagascar to delve into the African country's anthropological and archaeological history by analyzing satellite imagery with an algorithm. The researchers used freely downloadable imagery from the European Space Agency, and trained their software using the best theoretical assumptions on human settlement, which the algorithm compared with the current landscape to choose high-, medium-, or low-probability areas of evidence of human habitation. Penn State's Dylan Davis said, "We were able to systematically scan over 20 square miles of land per hour. This exponentially increases the rate of survey and discovery of archaeological deposits when compared to traditional ground-based methods."

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The TerraSentia robot can navigate under dense crop canopies. A Growing Presence on the Farm: Robots
The New York Times
Knvul Sheikh
February 13, 2020

Agronomists are using new autonomous robots to help them breed better crops. One example is the TerraSentia robot developed by the University of Illinois at Urbana-Champaign's Girish Chowdhary. The wheeled machine is equipped with a camera, and navigates by laser-scanning its environment in order to collate a wealth of information on crop fields and automate measurement of plant phenotypes. By making plant phenotyping more reliable, researchers hope TerraSentia and similar machines can optimize crop yields with greater efficiency than humans. Said Neil Hausmann at Corteva, a spin-off of agricultural giants Dow Chemical and DuPont, “There’s definitely a niche for this kind of robot. It provides standardized, objective data that we use to make a lot of our decisions. We use it in breeding and product advancement, in deciding which product is the best, which ones to move forward, and which ones will have the right characteristics for growers in different parts of the country.”

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AI Finds Disease-Related Genes
Linkoping University
Karin Söderlund Leifler
February 14, 2020

Researchers at Linköping University in Sweden have developed an artificial neural network that can reveal patterns in gene expression data and discover groups of disease-related genes. The team used a database with information about the expression patterns of 20,000 genes in a large number of people. The researchers did not give the artificial neural network information about which gene expression patterns were from people with diseases, and which were from healthy individuals. The team found that the model could find relevant patterns that agree well with biological mechanisms in the body. Said Linköping researcher Mika Gustafsson, "We believe that our method gives models that are easier to generalize and that can be used for many different types of biological information."

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Chip Brings Ultra-Low Power Wi-Fi Connectivity to IoT Devices
University of California, San Diego
Liezel Labios
February 17, 2020

Researchers at the University of California, San Diego (UCSD) have developed an ultra-low-power Wi-Fi radio that enables Internet of Things (IoT) devices to communicate with existing Wi-Fi networks using 5,000 times less power than conventional Wi-Fi. The new device, housed in a chip smaller than a grain of rice, consumes just 28 microwatts of power while transmitting data at a rate of two megabits per second over a range of up to 21 meters. The Wi-Fi radio transmits data via backscattering—a technique that takes incoming Wi-Fi signals, modifies the signals, and encodes its own data onto them, before reflecting the new signals onto a different Wi-Fi channel to another device or access point. UCSD’s Dinesh Bharadia said, “You can connect your phone, your smart devices, even small cameras or various sensors to this chip, and it can directly send data from these devices to a Wi-Fi access point near you. You don’t need to buy anything else. And it could last for years on a single coin-cell battery.”

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