Automatic language identification is a challenging problem. Discriminating between closely related languages is especially difficult. This paper presents a machine learning approach for automatic language identification for the Nordic languages, which often suffer miscategorisation by existing state-of-the-art tools. Concretely we will focus on discrimination between six Nordic languages: Danish, Swedish, Norwegian (Nynorsk), Norwegian (Bokm{\aa}l), Faroese and Icelandic.

Check out what's clicking on Foxnews.com. Russia stepped up its missile and drone attacks against Ukraine on Wednesday, killing students and other civilians, in a violent follow-up to dueling high-level diplomatic missions aimed at bringing peace after 13 months of war. "Russia is shelling the city with bestial savagery," President Volodymyr Zelenskyy wrote in a Telegram post accompanying video showing what he said was a Russian missile striking a nine-story apartment building on a busy road in the southeastern city of Zaporizhzhia. "Residential areas where ordinary people and children live are being fired at." At least one person was killed in the attack shown in the Zaporizhzhia video, apparently recorded by closed circuit TV cameras.

Former U.S. Amb. to NATO Kurt Volker says the Russian fighter jet collision was'intentional' and requires a'firm response' from the U.S. The Biden administration blasted Russia for honoring two pilots for downing a U.S. drone in international airspace while saying the aviator who crashed into the drone was "at best, just an idiot." Last week, the Kremlin issued state awards to the fighter jet pilots responsible for downing the U.S. MQ-9 Reaper drone over the Black Sea earlier the week prior. In an official statement, the Ministry of Defense commended the pilots for preventing the drone from "violating the boundaries of the temporary airspace regime established for the special military operation." U.S. European Command said a Russian Su-27 fighter jet colliding with a U.S. MQ-9 Reaper drone over the Black Sea. A screenshot shows a jet dumping fuel.

This paper proposes a methodology for discovering meaningful properties in data by exploring the latent space of unsupervised deep generative models. We combine manipulation of individual latent variables to extreme values outside the training range with methods inspired by causal inference into an approach we call causal disentanglement with extreme values (CDEV) and show that this approach yields insights for model interpretability. Using this technique, we can infer what properties of unknown data the model encodes as meaningful. We apply the methodology to test what is meaningful in the communication system of sperm whales, one of the most intriguing and understudied animal communication systems. We train a network that has been shown to learn meaningful representations of speech and test whether we can leverage such unsupervised learning to decipher the properties of another vocal communication system for which we have no ground truth. The proposed technique suggests that sperm whales encode information using the number of clicks in a sequence, the regularity of their timing, and audio properties such as the spectral mean and the acoustic regularity of the sequences. Some of these findings are consistent with existing hypotheses, while others are proposed for the first time. We also argue that our models uncover rules that govern the structure of communication units in the sperm whale communication system and apply them while generating innovative data not shown during training. This paper suggests that an interpretation of the outputs of deep neural networks with causal methodology can be a viable strategy for approaching data about which little is known and presents another case of how deep learning can limit the hypothesis space. Finally, the proposed approach combining latent space manipulation and causal inference can be extended to other architectures and arbitrary datasets.

Incorporating the dynamics knowledge into the model is critical for achieving accurate trajectory prediction while considering the spatial and temporal characteristics of the vessel. However, existing methods rarely consider the underlying dynamics knowledge and directly use machine learning algorithms to predict the trajectories. Intuitively, the vessel's motions are following the laws of dynamics, e.g., the speed of a vessel decreases when turning a corner. Yet, it is challenging to combine dynamic knowledge and neural networks due to their inherent heterogeneity. Against this background, we propose MSTFormer, a motion inspired vessel trajectory prediction method based on Transformer. The contribution of this work is threefold. First, we design a data augmentation method to describe the spatial features and motion features of the trajectory. Second, we propose a Multi-headed Dynamic-aware Self-attention mechanism to focus on trajectory points with frequent motion transformations. Finally, we construct a knowledge-inspired loss function to further boost the performance of the model. Experimental results on real-world datasets show that our strategy not only effectively improves long-term predictive capability but also outperforms backbones on cornering data.The ablation analysis further confirms the efficacy of the proposed method. To the best of our knowledge, MSTFormer is the first neural network model for trajectory prediction fused with vessel motion dynamics, providing a worthwhile direction for future research.The source code is available at https://github.com/simple316/MSTFormer.

Former U.S. Amb. to NATO Kurt Volker says the Russian fighter jet collision was'intentional' and requires a'firm response' from the U.S. The United States has resumed its normal flights through international waters over the Black Sea following the crash of a drone due to Russian interference. U.S. officials said Friday that a RQ-4 Global Hawk flew through the region -- the first U.S. aircraft to do so since the skirmish, according to Reuters. An RQ-4 Global Hawk takes off from Andersen Air Force Base, Guam (U.S. Air Force photo/Senior Airman Nichelle Anderson) Military officials assured the public that the Russian harassment of the US drone on Tuesday would not affect regular operations in the region. Defense Secretary Lloyd Austin summarized the incident Wednesday in a press conference, saying, "Two Russian jets dumped fuel on an unmanned U.S. MQ-9 aircraft conducting routine operations in international airspace. And one Russian jet intercepted and hit our MQ-9 aircraft, resulting in a crash."

Russia has conferred state awards on the two fighter pilots involved in the downing of a US surveillance drone that crashed into the Black Sea, the Russian Defence Ministry said, while United States officials announced that its spy flights in the region have resumed. Presenting the awards on Friday to the Su-27 jet fighter pilots, Russia's Defence Minister Sergei Shoigu lauded their achievement in preventing the drone from flying into an area near Crimea to which Moscow has banned access. "The drone flew with its transponders off, violating the boundaries of the area of the temporary airspace usage regime established for the special military operation [and] communicated to all users of international airspace," Russia's defence ministry said in a statement, according to The Moscow Times. Pro-Kremlin political analyst Sergei Markov said the awards for the pilots were "a clear sign that Russia will keep downing" US drones. "This decision will receive a strong support from the Russian society that wants the government to toughen its policy," Markov wrote in a commentary. Russia's presentation of the awards comes a day after the US military released a declassified 42-second video clip showing the Russian Su-27 fighter jets intercepting the drone and making close passes while dumping fuel in an apparent bid to damage the drone's optical and other hi-tech instruments.

Rep. Nick LaLota, R-N.Y., reacts to new video showing a Russian jet hitting a U.S. drone and weighs in on the border crisis. EXCLUSIVE: Several Republican senators are calling on Congress to exercise its oversight authority after a Russian fighter jet downed a U.S. drone over international waters earlier this week – an incident that has many worried about more direct conflict between the two superpowers as the Ukraine war enters its second year. "We need a hearing on it. We've asked the Pentagon for hearing, of course, they're probably a little bit busy right now," Sen. Tommy Tuberville, R-Ala., a member of the Armed Services Committee, told Fox News Digital this week. When asked if he was concerned about Russian officials' announcement that Moscow will try to retrieve the debris, Tuberville said, "Yeah, we should all be."

Mark Kelly, D-Ariz., weighs in on challenges Border Patrol faces as more migrants flood the southern border on'Special Report.' The crash between a Russian fighter jet and a U.S. drone likely resulted from the pilot's aggression and "incompetence," according to former astronaut and Navy captain, Sen. Mark Kelly. "Look at the level of incompetence – I mean when we saw the flanker yesterday, which basically had a midair with the MQ-9 [drone], with a reaper … I spent 15 years in the astronaut office, I used to fly with Russian fighter pilots in the backseat of my plane," Kelly, D-AZ., told Fox News chief political anchor and host of "Special Report with Brett Baier" during an interview Thursday. "The level of incompetence in the Russian pilots that I flew with was shocking to me." Russia has denied that its plane crashed into the U.S. drone despite video evidence showing the plane make at least two fly-bys, including one in which it appeared to dump fuel on the drone before the feed abruptly cut off, and the drone crashed into the Black Sea. On Friday, Russian Minister of Defense Sergei Shoigu reportedly presented the pilots responsible for crashing the drone with state awards, saying the pilots prevented the drone from "violating the boundaries of the temporary airspace regime established for the special military operation," referring to the invasion of Ukraine.

Kyiv, Ukraine – It looked like a deliberate manoeuvre by a skilled pilot that led to the first direct military clash between the United States and Russia since Moscow invaded Ukraine. Two Russian fighter jets approached a US drone flying in the cloudless, azure sky over international waters in the Black Sea on Tuesday morning. One of the Russian Su-27s released a stream of jet fuel on the MQ-9 Reaper drone, causing its cameras to shut off. Then the Su-27 hit the Reaper's propeller, causing it to tumble into the sea, the Pentagon said. It said the Reaper was a "reconnaissance drone" and carried no arms, although the unmanned aircraft with a wingspan of 26 metres (85 feet) was designed as a "hunter-killer" armed with laser-guided bombs and missiles.