Fox News chief Washington correspondent Mike Emanuel reports on an Iranian warship intercepting American drones only to return them the following morning on'Special Report.' Iran has armed 51 cities and towns with a civil defense system aimed to respond to any foreign attack as tensions with the U.S. have mounted in recent weeks. The defenses will enable Iran's arms forces to "identify and monitor threats by using round-the-clock software according to the type of the threat and risk," Deputy Defense Minister General Mehdi Farahi said Saturday, according to a Reuters report. "These days, depending on the strength of countries, the form of battles has become more complicated," he added. Farahi did not name any specific countries Tehran could be targeted by but noted that conventional warfare has largely been replaced by cyber, biological and radioactive attack tactics.

In that case, the Navy said it spotted an Iranian Islamic Revolutionary Guard Corps naval support ship towing a Saildrone Explorer. The American seamen told the Iranians that the drone was U.S. government property and asked for it back. With a U.S. Fifth Fleet MH-60S Sea Hawk helicopter hovering above, the Iranians disconnected the towing line they had attached to that drone and eventually departed the area, according to a U.S. Navy release at the time. The Navy resumed operations "without incident," the release said. The United States and Iran often tangle in the Persian Gulf -- which the United States calls the Arabian Gulf -- and in the Red Sea and the Arabian Sea.

Iran's navy has released two American surface drones hours after seizing them in the Red Sea, accusing the unmanned vessels of jeopardising maritime safety, Iranian state television reports, in the second such incident this week. "The [Iranian navy] frigate Jamaran seized the two vessels on Thursday to prevent any possible accident after issuing warnings to the US fleet. After international shipping lanes were secured, the two vessels were released in a safe area," the state TV reported on Friday. Footage appeared to show more than a dozen Iranian navy personnel pushing two drones into the sea from the deck of their vessel – the latest maritime incident involving the United States Navy's new drone fleet in the Middle East as negotiations over Tehran's nuclear deal with the world powers hang in the balance. The state TV said an Iranian naval flotilla found "several unmanned spying vessels abandoned in the international maritime routes" and "after warning an American destroyer twice, seized the two drone vessels to prevent possible accidents".

Iran's Islamic Revolutionary Guard Corps (IRGC) has seized an American sea drone in the Gulf and tried to tow it away, only releasing the unmanned vessel when a US Navy warship and helicopter approached, US officials have said. The incident on Tuesday marks the first time the Navy's Middle East-based 5th Fleet's new drone task force has been targeted by Iran. While the interception ended without incident, it comes amid growing tensions between the United States and Iran as negotiations over the tattered Iranian nuclear deal hang in the balance. The U.S. Navy prevented a support ship from Iran's Islamic Revolutionary Guard Corps Navy (IRGCN) from capturing an unmanned surface vessel operated by the U.S. 5th Fleet in the Arabian Gulf, Aug. 29-30. The IRGC's Shahid Baziar warship attached a line to the Saildrone Explorer in the central part of the Gulf in international waters late Monday night, said Commander Timothy Hawkins, a 5th Fleet spokesman.

An Iranian ship seized an American military unmanned research vessel in the Gulf but released it after a US Navy patrol boat and helicopter were deployed to the location, the Pentagon said Tuesday. The US Central Command's 5th Fleet said a support ship from Iran's Islamic Revolutionary Guard Corps Navy, the Shahid Baziar, was spotted towing the seven-meter (23-foot) Saildrone Explorer unmanned surface vessel (USV) late Monday. The US naval drone, equipped with an array of sensors, radars and cameras, was in international waters collecting navigation and other unspecified data, the 5th Fleet said in a statement. When the Iranian vessel was seen towing the unmanned boat, US forces sent the USS Thunderbolt coastal patrol ship, which was operating nearby, to the scene. In addition, an MH-60S Sea Hawk helicopter based in Bahrain flew to the location.

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. The U.S. Navy stopped an Iranian ship from taking an American sea drone in the Arabian Gulf Monday night. The Iranian Revolutionary Guard Corps Navy was in the process of towing the drone, which belongs to the U.S. Navy's 5th Fleet at 11 p.m. local time when the American Navy immediately sent out the nearby Navy coastal ship USS Thunderbolt. The 5th Fleet also repeatedly called Iranian officials, who then let the drone go.

Wind speed retrieval at sea surface is of primary importance for scientific and operational applications. Besides weather models, in-situ measurements and remote sensing technologies, especially satellite sensors, provide complementary means to monitor wind speed. As sea surface winds produce sounds that propagate underwater, underwater acoustics recordings can also deliver fine-grained wind-related information. Whereas model-driven schemes, especially data assimilation approaches, are the state-of-the-art schemes to address inverse problems in geoscience, machine learning techniques become more and more appealing to fully exploit the potential of observation datasets. Here, we introduce a deep learning approach for the retrieval of wind speed time series from underwater acoustics possibly complemented by other data sources such as weather model reanalyses. Our approach bridges data assimilation and learning-based frameworks to benefit both from prior physical knowledge and computational efficiency. Numerical experiments on real data demonstrate that we outperform the state-of-the-art data-driven methods with a relative gain up to 16% in terms of RMSE. Interestingly, these results support the relevance of the time dynamics of underwater acoustic data to better inform the time evolution of wind speed. They also show that multimodal data, here underwater acoustics data combined with ECMWF reanalysis data, may further improve the reconstruction performance, including the robustness with respect to missing underwater acoustics data.

Similar to many Machine Learning models, both accuracy and speed of the Cluster weighted models (CWMs) can be hampered by high-dimensional data, leading to previous works on a parsimonious technique to reduce the effect of "Curse of dimensionality" on mixture models. In this work, we review the background study of the cluster weighted models (CWMs). We further show that parsimonious technique is not sufficient for mixture models to thrive in the presence of huge high-dimensional data. We discuss a heuristic for detecting the hidden components by choosing the initial values of location parameters using the default values in the "FlexCWM" R package. We introduce a dimensionality reduction technique called T-distributed stochastic neighbor embedding (TSNE) to enhance the parsimonious CWMs in high-dimensional space. Originally, CWMs are suited for regression but for classification purposes, all multi-class variables are transformed logarithmically with some noise. The parameters of the model are obtained via expectation maximization algorithm. The effectiveness of the discussed technique is demonstrated using real data sets from different fields.

Over the weekend, debris from an out-of-control Chinese rocket crashed to Earth over the Indian and Pacific oceans. There had been fears that pieces of the 23-tonne Long March 5B booster could come down over a populated area, but experts had said the probability of this was extremely low. Nevertheless, NASA hit out at China by accusing Beijing of not sharing the'specific trajectory information' needed to calculate where possible debris might fall. Elsewhere at the weekend, a 10ft (3m) piece of space junk – thought to be from one of Elon Musk's spacecrafts – crashed into a farmer's property in Australia at around 15,500mph (25,000km/h). The object, believed to be part of the SpaceX Crew-1 craft, was found in a sheep paddock by a farmer living on a large property in the Snowy Mountains in New South Wales.

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. The U.S. says Russian officials visited an Iranian airfield multiple times in recent weeks to view attack-capable drones it is looking to obtain for its attack against Ukraine. Iran showed the drones to Russian officials at Kashan Airfield on June 8 and July 15, the White House said. The Biden administration has published satellite imagery showing Shahed-191 and Shahed-129 drones flying at the airfield at the same time a Russian delegation transport plane was on the ground.