Satellite communication is a key technology in our modern connected world. With increasingly complex hardware, one challenge is to efficiently configure links (connections) on a satellite transponder. Planning an optimal link configuration is extremely complex and depends on many parameters and metrics. The optimal use of the limited resources, bandwidth and power of the transponder is crucial. Such an optimization problem can be approximated using metaheuristic methods such as simulated annealing, but recent research results also show that reinforcement learning can achieve comparable or even better performance in optimization methods. However, there have not yet been any studies on link configuration on satellite transponders. In order to close this research gap, a transponder environment was developed as part of this work. For this environment, the performance of the reinforcement learning algorithm PPO was compared with the metaheuristic simulated annealing in two experiments. The results show that Simulated Annealing delivers better results for this static problem than the PPO algorithm, however, the research in turn also underlines the potential of reinforcement learning for optimization problems.

Los Angeles, California – The United States military shot down a flurry of objects this month: a large object it identified as a Chinese surveillance balloon followed by three smaller objects that the government said might be "benign". The airborne objects were drifting through airspace increasingly crowded with commercial and amateur balloons, drones and possible aerial surveillance craft belonging to adversaries. Their rising numbers pose a challenge to aviators and government agencies. Experts say that while heavy commercial balloons must meet strict Federal Aviation Administration (FAA) regulations, lighter amateur balloons are exempt from most rules, and the FAA might not be able to track them. Military and intelligence officials found no evidence that the three smaller objects were conducting surveillance for another country, and they were not sending communication signals, National Security Council spokesman John Kirby said at a White House briefing on Monday.

On a bluff south of San Francisco overlooking the Pacific Ocean, an electric motor whips a drone built by startup Zipline off a catapult launch ramp beside me and into the air on a test flight. The aircraft, with a fixed-wing design resembling that of a conventional airplane, pilots itself north, plans its approach based on the wind direction, makes a sweeping turn and drops a box of Band-Aids, Advil and Tums by parachute onto the grass a few yards in front of me. Drone deliveries could be dropping into your life, too, as the technology involved matures and expands beyond isolated test projects. In 2023, drones could replace vans and your own trip to the store when you need medicine, takeout dinners, cordless drill batteries or dishwasher soap. Today, Alphabet Wing drones reach hundreds of thousands of people in Australia, Finland and Texas and will expand its service in 2023, according to Jonathan Bass, who runs marketing for the business.

We first learned that it was a missile that took down a Ukrainian airliner over Iran because of this video showing the moment of impact. All 176 people on board were killed. To find out what happened to Flight 752 after it left Tehran airport on Jan. 8, we collected flight data, analyzed witness videos and images of the crash site, to paint the clearest picture yet of that disastrous seven-minute flight. We'll walk you through the evidence, minute by minute, from the plane's takeoff to the moment it crashed. Iran has just launched ballistic missiles at U.S. military targets in Iraq in retaliation for an American drone strike that killed Iranian military leader Qassim Suleimani.

The airport had been closed for over a day after a drone repeatedly flew nearby. The airport had been closed for over a day after a drone repeatedly flew nearby. There's no shortage of ideas about how to stop a drone, but as the past few days at London's Gatwick Airport show, the reality is far more difficult. From Wednesday night to Friday morning, flights in and out of Gatwick were halted after a small drone, or perhaps multiple drones, were spotted over the airfield. Hundreds of flights were canceled and thousands of passengers saw their holiday travel plans grounded.

I recently read an article (paywall) in the WSJ about Paul Allen's Vulcan initiative to curb illegal fishing. It's insightful and sheds light on Big Data techniques to address societal problems. After thinking on the story, it struck me that it could be used as a pedagogical tool to synthesize data science with domain knowledge. To me, this stands as the biggest limitation of what I refer to as'data science thinking'– letting technical skills drive the analysis, only later incorporating domain understanding. This post somewhat reads like a case note from business school and the idea is to get data scientists, product managers and engineers talking earlier on in the process.

The article references "anticollision transponders," which is the AIS used by maritime traffic to monitor/track all passenger ships and most cargo. Then there's the bit about "statistical models" which I suppose is some flavor of machine learning to estimate when a transponder is turned off and a vessel is engaged in nefarious activity. How the "notification system alerts authorities when suspected pirate vessels…arrive at ports" if AIS is not active is unclear.

Researchers are learning more than ever before about the effects humans are having on global fish stocks. It's all thanks to a website -- funded in part by actor Leonardo DiCaprio's foundation -- that tracks ships and uses a type of artificial intelligence to figure out incredible detail in worldwide fishing patterns. Kristina Boerder, a PhD student in marine biology at Dalhousie University, is one of the researchers working with Global Fishing Watch and a co-author on a study published this week in the journal Science. She said humans have been fishing for 42,000 years but we've been "rather in the dark" about where and how much fishing activity is happening. "This is really a problem because this is a resource that is not infinite," Boerder told the CBC's Mainstreet.

Cycling fans will be able to get deeper insights into one of the most popular races, Tour de France, with the introduction of machine learning algorithm. The race, which began in Düsseldorf, Germany on July 1, finishes at the Champs-Élysées in Paris on July 23. The new data analytics platform combines live and historical race data, and also enables fans to benefit from rider profiles to understand better the environments and circumstances in which riders perform best. At the core of the live tracking and data analytics solution are GPS transponders installed under the saddles of each bike. The data collected from these transponders is combined with external data about the course gradient and prevailing weather conditions to generate insights such as live speed and the location of individual riders, distance between riders, and composition of groups within the race.

Amaury Sport Organisation (A.S.O.), organizers of the Tour de France, and Dimension Data, the Official Technology Partner of the Tour de France, announced the introduction of machine learning technologies at this year's Tour de France to give cycling fans across the globe an unprecedented experience of this year's event. The race begins in Düsseldorf on Saturday and finishes at the Champs-Élysées in Paris on 23 July. This year, Dimension Data's data analytics platform, which was developed in partnership with A.S.O., incorporates machine learning and complex algorithms that combine live and historical race data to provide even deeper levels of insight as the race unfolds. Fans will also benefit from rider profiles to understand more about environments and circumstances in which riders perform best. As part of a new pilot this year, A.S.O. and Dimension Data are exploring the role of predictive analytics technologies to assess the likelihood of various race scenarios, such as whether the peloton will catch the breakaway riders at certain stages of the race.