Sharing your general location with someone is easy. Unfortunately, thanks to location tracking errors, getting someone’s precise location isn’t always accurate, especially in dense urban areas. Google is aware of these limitations and today unveiled steps they’ve taken to improve urban GPS tracking on Android phones.
As part of the latest Pixel Feature Drop, Google is rolling out version 2 of its 3D mapping aided GPS corrections to the Pixel 5 and Pixel 4a 5G, which features accuracy in urban areas that “improves spectacularly” over what’s currently available.
The issue with locating someone in an urban area is due to the density of buildings. Google explains that GPS systems are based on line-of-sight operation from satellites. In cities, most signals reach devices through non-line-of-sight reflections, because direct signals are blocked by buildings. “The GPS chip assumes that the signal is line-of-sight and therefore introduces error when it calculates the excess path length that the signals traveled,” Google said.
Palantir Technologies Inc. won a deal with the U.S. Food and Drug Administration to help power drug reviews and inspections, further expanding the company’s government business as it hustles to hit a raised revenue target for 2020.
The three-year deal is worth $44.4 million and will allow the FDA’s Center for Drug Evaluation and Research and the Oncology Center of Excellence to use Palantir software to integrate and analyze data. The software will help the agency approve drugs, including possible Covid-19 treatments, and monitor the safety of items like hand sanitizer. Earlier this year, the FDA warned the public that hand sanitizers containing wood alcohol were toxic.
A significant challenge facing a wide variety of disciplines is the ability to reproduce research results. Researchers across the University of Michigan are working together to develop best practices that promote reproducible data science. [video, 3:21]
Bike race coverage has changed a lot in recent years. Gone are the days of simply sitting down to watch a basic race feed. Nowadays, we have more information at our fingertips than ever before, helping to augment the viewing experience. We have second-screen apps that allow us to track the position of every rider throughout a race, and we have on-screen data showing riders’ speed, heart rate and power output, all in real time.
Now, a group of researchers in Belgium is trying to push the envelope even further.
Steven Verstockt and Jelle De Bock are part of the IDLab research group at Ghent University, a group that uses machine learning, data mining, and computer vision techniques to help bridge the gap between data and storytelling. They’ve got projects in a number of areas but sport is of particular interest. And given De Bock is an elite cyclocross racer, it’s little surprise the research group has spent considerable effort focusing on the world of cycling.
A Cornell-led COVID-19 patient registry, organized by Weill Cornell Medicine physicians and scientists in response to surging cases earlier this year in New York City, continues to be a source of medical insight into the workings of the new coronavirus and treatment of infected patients.
Illustrating the power of interdisciplinary cross-campus collaboration, a team of Weill Cornell Medicine physicians and PhD scientists based in New York City, along with student statisticians collaborating remotely from Ithaca, NY, and elsewhere, have built a secure database with medical data on more than 4,000 patients who had clinical symptoms of COVID-19 and were seen at one of three NewYork-Presbyterian Hospital campuses. From this registry, medical professionals are learning more about how to treat patients with COVID, which has thus far claimed 1.5 million lives around the world, according to latest statistics.
A top exercise researcher and colleagues at the School of Medicine have launched an ambitious effort to understand the whole-body benefits of exercise so that doctors can use that information to prevent and treat disease.
Zhen Yan, PhD, and his collaborators aim to identify the sources, functions and targets of the molecules that provide exercise’s well-documented health benefits. By understanding this, doctors will better understand how exercise helps fend off disease, and they may be able to design drugs to mimic those benefits for people who cannot exercise, such as those with limited mobility. The cutting-edge research could open new doors both for preventing and treating many common illnesses, the researchers hope.
Predictive modelers told California regulators on Thursday that the state’s antiquated rules for calculating wildfire risk when setting property insurance rates discourage innovative mitigation measures that could ultimately reduce losses.
Nancy P. Watkins, a principal and consulting actuary for Milliman, said during a webcast on “home hardening” hosted by the state Department of Insurance that California is one of only three states that doesn’t allow insurers to use catastrophe modeling to determine wildfire risk. Rates must be based on historical losses.
When the University of California’s Board of Regents got a close look at the numbers in September, it was the visual equivalent of a thunderclap. The massive university system, with 10 campuses and more than 285,000 students, was hemorrhaging money — $2.2 billion in lost revenue and additional costs, mostly due to the pandemic.
While some of those losses came from medical centers that temporarily gave up high-paying elective procedures in order to treat COVID patients, the bigger picture was as vexing as it was simple: In the age of pandemic-induced remote learning, the campuses were largely deserted. And when students aren’t living on campus, schools stop making money. Fast.
“Colleges and universities get very high premiums on their housing. It’s a big revenue space for them,” said Dr. Jorge Nieva of the University of Southern California’s Keck School of Medicine. “But for many, many schools right now, they just can’t operate in person.”
In late February, as coronavirus took hold in Europe, governments around the world were still resisting lockdowns. In Facebook’s artificial intelligence lab in Paris, data scientists and machine learning researchers were dumbstruck.
“I mean, they are data nerds, right?” Antoine Bordes, managing director of Facebook AI Research, told Protocol. “There [were] really a lot of people [here], heads down in the data, who knew this [pandemic] was coming.”
One researcher, Bordes recalls, skeptical of governmental responses to the pandemic, decided to do some modeling on the weekend using data grabbed from a New York Times COVID-19 tracker. He recalled their response on returning to the office: “Hmm, it doesn’t look good.”
So those researchers did what researchers do: They dug into the data, they played around and they started working out what could be usefully done. “I mean 60 people, roughly, they dropped what they were doing to start [COVID-19] projects,” Bordes said.
Half a century ago, high-altitude balloon experiments paved the way for astronauts and orbiting telescopes. Now, high-tech balloons are giving astronomers a reason to keep their instruments a little closer to Earth.
There were seven interesting and varied invited talks at NeurIPS this year. Here, we summarise the first three, which were given by Charles Isbell (Georgia Tech), Jeff Shamma (King Abdullah University of Science and Technology) and Shafi Goldwasser (UC Berkeley, MIT and Weizmann Institute of Science).
The Lancet Digital Health, Andrew A S Soltan et al.
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The early clinical course of COVID-19 can be difficult to distinguish from other illnesses driving presentation to hospital. However, viral-specific PCR testing has limited sensitivity and results can take up to 72 h for operational reasons. We aimed to develop and validate two early-detection models for COVID-19, screening for the disease among patients attending the emergency department and the subset being admitted to hospital, using routinely collected health-care data (laboratory tests, blood gas measurements, and vital signs). These data are typically available within the first hour of presentation to hospitals in high-income and middle-income countries, within the existing laboratory infrastructure. [full text]
Harvard’s Undergraduate Council launched a weeklong campaign last month to support a project aimed at explaining how the University collects and uses student data.
The campaign — dubbed the Transparency Project — started as a final project created by Yousuf Bakshi ’23 and Anjali Chakradhar ’23 in the class Computer Science 105: “Privacy and Technology.” Bakshi and Chakradhar are Council members who represent Mather House and Cabot House, respectively.
The project aimed to bolster student awareness about data privacy, Chakradhar said.
“We want to help build the next generation of data-aware citizens who can then go on to advocate for themselves and other people,” Chakradhar said. “We thought that the best place to start was right here.”
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Data is the lifeblood of science. It provides scientists with a way to prove, refine, or disprove our ideas about how the world works. Data from the University of Alaska Fairbanks is providing valuable information for oil spill response, public safety and economic development efforts in the 49th state.
UAF passed a remarkable milestone this month, when scientists from the College of Fisheries and Ocean Sciences completed a half-century of regular observations at a Gulf of Alaska oceanographic station. Station GAK-1 is located near Seward at the mouth of Resurrection Bay, and it has the longest set of sustained measurements of surface-to-seafloor temperature and salinity in all of Alaska’s coastal and offshore waters.
What does this mean for our state? GAK-1 is providing data to drive good decision-making and help us evaluate risks to Alaska’s marine ecosystem and economy as the ocean becomes warmer and more acidic due to climate change. This monitoring contributes to our understanding of melting glacier runoff in the ocean, variations in Alaska’s commercial fisheries, and the population status of marine mammals.
“We are organizing a special issue on “User Experience of AI in Games” as part of IEEE Transaction in Games. @IEEETxnOnGames” Deadline for submissions is February 28, 2021.
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The eScience Institute’s Data Science for Social Good program is now accepting applications for student fellows and project leads for the 2021 summer session. Fellows will work with academic researchers, data scientists and public stakeholder groups on data-intensive research projects that will leverage data science approaches to address societal challenges in areas such as public policy, environmental impacts and more. Student applications due 2/15 – learn more and apply here. DSSG is also soliciting project proposals from academic researchers, public agencies, nonprofit entities and industry who are looking for an opportunity to work closely with data science professionals and students on focused, collaborative projects to make better use of their data. Proposal submissions are due 2/22.
Microsoft, Facebook, Reddit, Insomnia Cookies. We’ve all heard the success stories: A college student, usually a prodigy, has a brilliant idea and works day and night, drops out of college and makes it big. But you don’t have to be a prodigy and you don’t have to drop out to be successful.
