Filtered back projection (FBP) is the most widely used method for image reconstruction in X-ray computed tomography (CT) scanners. The presence of hyper-dense materials in a scene, such as metals, can strongly attenuate X-rays, producing severe streaking artifacts in the reconstruction. These metal artifacts can greatly limit subsequent object delineation and information extraction from the images, restricting their diagnostic value. This problem is particularly acute in the security domain, where there is great heterogeneity in the objects that can appear in a scene, highly accurate decisions must be made quickly. The standard practical approaches to reducing metal artifacts in CT imagery are either simplistic non-adaptive interpolation-based projection data completion methods or direct image post-processing methods. These standard approaches have had limited success. Motivated primarily by security applications, we present a new deep-learning-based metal artifact reduction (MAR) approach that tackles the problem in the projection data domain. We treat the projection data corresponding to metal objects as missing data and train an adversarial deep network to complete the missing data in the projection domain. The subsequent complete projection data is then used with FBP to reconstruct image intended to be free of artifacts. This new approach results in an end-to-end MAR algorithm that is computationally efficient so practical and fits well into existing CT workflows allowing easy adoption in existing scanners. Training deep networks can be challenging, and another contribution of our work is to demonstrate that training data generated using an accurate X-ray simulation can be used to successfully train the deep network when combined with transfer learning using limited real data sets. We demonstrate the effectiveness and potential of our algorithm on simulated and real examples.

MOSCOW - The Russian Defense Ministry has deployed a surveillance drone with an artillery division to a group of islands controlled by Russia but claimed by Japan, a Russian newspaper reported on Monday. The drone will be used for patrolling coastal areas and surrounding waters, as well as for rescue operations, according to the newspaper, Izvestia. The artillery unit is stationed on two of the four Russian-controlled islands off the coast of Hokkaido, known in Japan as Etorofu and Kunashiri. The Orlan-10 drone, the same type as those sent by Russia to Syria, is able to operate within a 120-kilometer radius for up to 14 hours while transmitting images from a mounted camera, the Russian paper said.

There has, for years, been one thing that just about all of the tech industry agrees on: regulation is coming. Recently, they have even realised that it's necessary. But if there is one thing that has split tech behemoths, politicians and the public apart more than perhaps any other issue, it's what that regulation should look like. Now the UK government thinks it has alighted on an answer, offering perhaps the first comprehensive attempt to limit the harm that technology companies are doing to the people – in particular the children – who use them. For the most part, the solution they have chosen focuses on shifting the responsibility for content that appears on the site onto the people who run them.

New York's bid to identify road-going terrorists with facial recognition isn't going very smoothly so far. The Wall Street Journal has obtained a Metropolitan Transportation Authority email showing that a 2018 technology test on New York City's Robert F. Kennedy Bridge not only failed, but failed spectacularly -- it couldn't detect a single face "within acceptable parameters." An MTA spokesperson said the pilot program would continue at RFK as well as other bridges and tunnels, but it's not an auspicious start. The problem may be inherent to the early state of facial recognition at these speeds. Oak Ridge National Laboratory achieved more than 80 percent accuracy in a study that spotted faces through windshields, but that was at low speed.

The history of AI is often told as the story of machines getting smarter over time. What's lost is the human element in the narrative, how intelligent machines are designed, trained, and powered by human minds and bodies. In this six-part series, we explore that human history of AI--how innovators, thinkers, workers, and sometimes hucksters have created algorithms that can replicate human thought and behavior (or at least appear to). While it can be exciting to be swept up by the idea of super-intelligent computers that have no need for human input, the true history of smart machines shows that our AI is only as good as we are. At 10:30pm on 29 October 1969, a graduate student at UCLA sent a two-letter message from an SDS Sigma 7 computer to another machine a few hundred miles away at the Stanford Research Institute in Menlo Park. The student had meant to send "LOGIN," but the packet switching network supporting the transmission of the message, the ARPANET, crashed before the whole message could be typed out.

A moon base could be constructed remotely. Japan's space agency wants to create a moon base with the help of robots that can work autonomously, with little human supervision. The project, which has racked up three years of research so far, is a collaboration between the Japan Aerospace Exploration Agency (JAXA), the construction company Kajima Corp., and three Japanese universities: Shibaura Institute of Technology, The University of Electro-Communications and Kyoto University. Recently, the collaboration did an experiment on automated construction at the Kajima Seisho Experiment Site in Odawara (central Japan). A 7-ton autonomous backhoe went through its paces at the site, going through procedures such as driving a specified distance and repeating routine operations, JAXA officials said in a statement.

Hera uses infrared to scan impact crater. Judging by the valuations of companies such as Waymo, Lyft and Uber, humanity is placing a big bet on self-driving cars as the future of transportation. But the future of humanity itself may rest on the hopes of self-driving spacecraft. The European Space Agency is currently developing a self-driving craft for its Hera planetary defense mission to the Didymos asteroid, which could happen as soon as 2023. "If you think self-driving cars are the future on Earth, then Hera is the pioneer of autonomy in deep space," Paolo Martino, lead systems engineer of ESA's proposed Hera mission, said in a statement.

Supply chain leaders have earned a seat at the strategic planning table. With modern technology, such as Artificial Intelligence (AI) and the Internet of Things (IoT), intelligence-driven supply chain management can intensify the impact of supply chain processes, from forecasting demand to optimizing cash flow. Such strategic applications are more important than ever as companies strive to maintain growth – despite global economic uncertainty. International trade agreements, tariffs, demanding customer expectations, and today's high-tech products further magnify the importance of being intelligence-driven. With C-level commitment and advanced IT solutions in place, enterprises can turn supply chain management into a strategic differentiator – one that builds customer loyalty for years to come.

Less than one week after Google scrapped its AI ethics council, the European Union has set out its own guidelines for achieving "trustworthy" artificial intelligence. On Monday, the European Commission released a set of steps to maintain ethics in artificial intelligence, as companies and governments weigh both the benefits and risks of the far-reaching technology. "The ethical dimension of AI is not a luxury feature or an add-on," said Andrus Ansip, EU vice-president for the digital single market, in a press release Monday. "It is only with trust that our society can fully benefit from technologies." The EU defines artificial intelligence as systems that show "intelligent behavior," allowing them to analyze their environment and perform tasks with some degree of autonomy.

The Slovenian government has announced plans, with official backing from UNESCO, to set up Europe's first international artificial intelligence research center. The Department of Intelligent Systems at the Jožef Stefan Institute (JSI) in Ljubljana will convert into a center that focuses on the governance and policies surrounding artificial intelligence (AI). At an event celebrating the 70th anniversary of the institute, Slovenia's Prime Minister, Marjan Šarec, said: "All of this Slovenian know-how which has been applied for all these years, and all the knowledge that we possessed in the past and that we still possess today is undoubtedly a reason for us, or should I say you, to be proud," Slovenia has a history and dedication to the field of AI- having embraced it as far back as 1972 when research at the JSI and the University of Ljubljana first began. In the 90s, there was a continued expansion of Slovenian AI research, starting with'heuristic search' into areas like machine learning and qualitative reasoning. As a result, this period provoked an increase in the presence of Slovenian researchers and publications in academia.