Machine learning and, more specifically, deep learning algorithms have seen remarkable growth in their popularity and usefulness in the last years. This is arguably due to three main factors: powerful computers, new techniques to train deeper networks and larger datasets. Although the first two are readily available in modern computers and ML libraries, the last one remains a challenge for many domains. It is a fact that big data is a reality in almost all fields nowadays, and geosciences are not an exception. However, to achieve the success of general-purpose applications such as ImageNet - for which there are +14 million labeled images for 1000 target classes - we not only need more data, we need more high-quality labeled data. When it comes to the Oil&Gas industry, confidentiality issues hamper even more the sharing of datasets. In this work, we present the Netherlands interpretation dataset, a contribution to the development of machine learning in seismic interpretation. The Netherlands F3 dataset acquisition was carried out in the North Sea, Netherlands offshore. The data is publicly available and contains pos-stack data, 8 horizons and well logs of 4 wells. For the purposes of our machine learning tasks, the original dataset was reinterpreted, generating 9 horizons separating different seismic facies intervals. The interpreted horizons were used to generate approximatelly 190,000 labeled images for inlines and crosslines. Finally, we present two deep learning applications in which the proposed dataset was employed and produced compelling results.

For effective recognition, we developed a recognition component, combining kinematic vessel streams with library of maritime patterns in close collaboration with domain contextual (geographical) knowledge for real-time vessel activity experts. We present a thorough evaluation of the system and the detection. To improve the accuracy of the system, we collaborated, patterns both in terms of predictive accuracy and computational in the context of this paper, with domain experts in order to construct efficiency, using real-world datasets of vessel position streams and effective patterns of maritime activity. Thus, we present a contextual geographical information.

It will be much harder than we have realised to blow up an asteroid and save the planet, scientists have warned. Experts have repeatedly warned that it is a question of when not if the Earth will be hit by the arrival of a potentially disastrous asteroid. But films have suggested a simple if high-tech response: launching heroes into space to blow it up before it ever gets here. In real life, however, those asteroids could be far more difficult to destroy than we knew. That is according to a new study from scientists at Johns Hopkins, who simulated the ways that an asteroid collision might happen and how such a space rock would fracture.

SpaceX's new Crew Dragon capsule has arrived at the International Space Station, acing its second milestone in just over a day. No one was on board the capsule launched on Saturday on its first test flight, only an instrumented dummy. But the three station astronauts had front-row seats as the Dragon neatly docked on Sunday morning and became the first American-made, designed-for-crew spacecraft to pull up in eight years. If the six-day demo goes well, SpaceX could launch two astronauts this summer under NASA's commercial crew programme. Both astronauts were at SpaceX Mission Control in California, observing all the action.

By 2025, augmented analytics will have a far-reaching impact, especially on the US economy. This shortage along with the higher hiring cost will demand for the use of citizen data science. It will permit businessman to leverage data without having earlier experience or expertise. "Through 2020, the number of citizen data scientists will grow five times faster than the number of expert data scientists. Organizations can use citizen data scientists to fill the data science and machine learning talent gap caused by the shortage and high cost of data scientists," said an official from renowned organization.

Nasa-funded scientists have developed a new kind of DNA-like structure that can store and transmit information – and could lead to new ways of finding alien life. The breakthrough discovery suggests there might be alternative, unimagined forms of DNA-based life as we know it on Earth. Life on other worlds might be built using different molecular systems of the kind the researchers developed in the lab, Nasa experts have suggested. The new molecular system will allow scientists who are looking for life elsewhere in the universe to re-think what they are actually looking for, researchers said. DNA is a complex molecule that allows the genetic information that makes us who we are to be stored and then transmitted.

Boaty McBoatface may be better known for its name than for its oceangoing prowess. But the autonomous underwater vehicle and darling of the internet is headed to greater things: embarking on the longest journey of an AUV by far, with an uninterrupted, roughly 2,000-mile crossing of the Arctic Ocean. The submersible robot got its moniker when it became the consolation prize in a 2016 publicity stunt. The United Kingdom's Natural Environmental Research Council had created an online poll to name the country's new polar research ship. The public picked "Boaty McBoatface" (suggested by a BBC radio announcer), but the British government nixed the idea and named the ship after naturalist David Attenborough.

Nasa engineers said goodbye to the Opportunity rover with a touching final message. The little robot spent 15 years exploring the surface of Mars, sending back unprecedented amounts of information to engineers back on Earth. But months ago the signals it was sending back started to look worrying. It told Nasa its batteries were running low and it was getting dark – before it was swallowed by a dust storm that took over the entire planet. Since then, Nasa has been sending messages to the rover in the hope of waking it up and bringing it back to life.

The Stellar Daisy, a massive South Korean tanker that sank in March 2017, was spotted on the floor of the South Atlantic Ocean nearly two years later, the CEO of an ocean exploration company revealed Sunday. This discovery could shed new light on exactly what caused the vessel to tilt and sink and provide some closure to the families of the 22 crew members who died. "We are pleased to report that we have located Stellar Daisy, in particular for our client, the South Korean Government, but also for the families of those who lost loved ones in this tragedy," Ocean Infinity CEO Oliver Plunkett said. "Through the deployment of multiple state of the art (autonomous underwater vehicles), we are covering the seabed with unprecedented speed and accuracy." The Stellar Daisy sank on March 31, 2017, nearly 2,500 miles east of Uruguay, while transporting iron ore from Brazil to China.

The technology coupled with hands-on work and measurements is used to create a forest management plan. The Duncannon Borough Watershed is a 1,600-acre property key to generating money in the local community. "In 300 spots, we measured every tree for a tenth of an acre," said Josh Parrish, the director of the Working Woodlands program at the Nature Conservancy. Understanding what you have is important in moving forward. So, the Nature Conservancy is doing just that by working with a company that uses artificial intelligence.