Every year, tropical hurricanes affect North and Central American wildlife and people. The ability to forecast hurricanes is essential in order to minimize the risks and vulnerabilities in North and Central America. Machine learning is a newly tool that has been applied to make predictions about different phenomena. We present an original framework utilizing Machine Learning with the purpose of developing models that give insights into the complex relationship between the land–atmosphere–ocean system and tropical hurricanes. We study the activity variations in each Atlantic hurricane category as tabulated and classified by NOAA from 1950 to 2021. By applying wavelet analysis, we find that category 2–4 hurricanes formed during the positive phase of the quasi-quinquennial oscillation. In addition, our wavelet analyses show that super Atlantic hurricanes of category 5 strength were formed only during the positive phase of the decadal oscillation. The patterns obtained for each Atlantic hurricane category, clustered historical hurricane records in high and null tropical hurricane activity seasons. Using the observational patterns obtained by wavelet analysis, we created a long-term probabilistic Bayesian Machine Learning forecast for each of the Atlantic hurricane categories. Our results imply that if all such natural activity patterns and the tendencies for Atlantic hurricanes continue and persist, the next groups of hurricanes over the Atlantic basin will begin between 2023 ± 1 and 2025 ± 1, 2023 ± 1 and 2025 ± 1, 2025 ± 1 and 2028 ± 1, 2026 ± 2 and 2031 ± 3, for hurricane strength categories 2 to 5, respectively. Our results further point out that in the case of the super hurricanes of the Atlantic of category 5, they develop in five geographic areas with hot deep waters that are rather very well defined: (I) the east coast of the United States, (II) the Northeast of Mexico, (III) the Caribbean Sea, (IV) the Central American coast, and (V) the north of the Greater Antilles.

The invasion of Ukraine has put the U.S. and Europe on a wartime mission to abandon Russian fossil fuels. This series looks at speeding up zero-carbon alternatives by lowering political and financial barriers. Sign up here to get the next story sent to your inbox. Trying to attach a million-dollar, 60-ton wind turbine blade to its base is challenging in any circumstance -- getting the angle wrong by even a fraction of a degree could affect the machine's ability to generate power. Now imagine trying to do it in the middle of the North Sea, one of the world's windiest spots, with waves swelling around you. It's like tying a thread to a kite at the beach and then trying to put it through the eye of a needle.

National security and military analyst Dr. Rebecca Grant provides the latest on the Russia-Ukraine conflict as Putin's military continues to wither. The war in Ukraine has been driven by artillery and drone capabilities Western defense officials have advised, but according to the U.K.'s Ministry of Defense Saturday, Russia may be running low on "pivotal" unmanned aerial vehicles (UAV). The defense ministry said UAVs have proven vulnerable to both Ukrainian and Russian forces. But while Kyiv has relied on allied nations to continue providing military aid in its war against Moscow, heavy sanctions have prevented Russian forces from maintaining its drone needs. The drone was found to have a number of DIY modifications.

Western countries have been ramping up weapons and ammunition shipments to Ukraine as Kyiv fights off a Russian invasion, but arms trade experts warn some of the lethal assistance could end up falling into the wrong hands. Ukraine in particular has a history as a hub of the arms trade during the 1990s, setting off alarm bells for those who study illicit flows. "There are very significant risks associated to the proliferation of weapons in Ukraine at the moment, in particular regarding small arms and light weapons," said Nils Duquet, a researcher and director of the Flemish Peace Institute. Western nations, above all the US, have announced successive shipments of both light and heavy weapons for Kyiv's forces since Russian troops crossed the Ukrainian border on February 24. Washington alone has delivered or promised military gear including hundreds of Switchblade kamikaze drones, 7,000 assault rifles with 50 million rounds of ammunition, laser-guided missiles and radar systems to detect enemy drones and incoming artillery fire.

Fox News correspondent Chad Pergram has the latest on the Biden admin's response to the Russia-Ukraine conflict on'Special Report.' Fighting continues over Ukraine's Zmiinyi Island, also known as Snake Island, as Russia looks to reinforce its troops on the small body of land located just off the southwest Ukrainian coastline in the Black Sea, officials warned Wednesday. The island became a symbol of Ukraine's resistance immediately following Russia's invasion in late February after Ukrainian soldiers famously stood up to a Russian warship. The United Kingdom's defense ministry warned that Russia is "repeatedly trying to reinforce its exposed garrison" located on the island. Snake Island, though tiny, has proven strategically important in Ukraine's war against Russia as it is located roughly 30 miles from Ukraine's most southern region.

This content can also be viewed on the site it originates from. A video posted toward the end of February on the Facebook page of Valerii Zaluzhnyi, the commander-in-chief of Ukraine's armed forces, showed grainy aerial footage of a Russian military convoy approaching the city of Kherson. Russia had invaded Ukraine several days earlier, and Kherson, a shipbuilding hub at the mouth of the Dnieper River, was an important strategic site. At the center of the screen, a targeting system locked onto a vehicle in the middle of the convoy; seconds later, the vehicle exploded, and a tower of burning fuel rose into the sky. The Bayraktar TB2 is a flat, gray unmanned aerial vehicle (U.A.V.), with angled wings and a rear propeller.

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. Ukraine's defense ministry on Saturday claimed it had sunk a Russian Serna-class landing boat off of the now-famous Snake Island which has stood as a symbol of resistance since the beginning of the war. Undated video footage posted to social media appears to show an airstrike hitting a landing vessel that had soldiers on board. Spokesman for the Odesa Regional Military Administration, Serhii Bratchuk, told Ukrainian news outlet Pravda that Zmiinyi Island – also known as Snake Island – has become "a symbol of our rock-hard endurance and our ability to shatter the enemy's most persistent efforts."

This survey article assesses and compares existing critiques of current fairness-enhancing technical interventions in machine learning (ML) that draw from a range of non-computing disciplines, including philosophy, feminist studies, critical race and ethnic studies, legal studies, anthropology, and science and technology studies. It bridges epistemic divides in order to offer an interdisciplinary understanding of the possibilities and limits of hegemonic computational approaches to ML fairness for producing just outcomes for society's most marginalized. The article is organized according to nine major themes of critique wherein these different fields intersect: 1) how "fairness" in AI fairness research gets defined; 2) how problems for AI systems to address get formulated; 3) the impacts of abstraction on how AI tools function and its propensity to lead to technological solutionism; 4) how racial classification operates within AI fairness research; 5) the use of AI fairness measures to avoid regulation and engage in ethics washing; 6) an absence of participatory design and democratic deliberation in AI fairness considerations; 7) data collection practices that entrench "bias," are non-consensual, and lack transparency; 8) the predatory inclusion of marginalized groups into AI systems; and 9) a lack of engagement with AI's long-term social and ethical outcomes. Drawing from these critiques, the article concludes by imagining future ML fairness research directions that actively disrupt entrenched power dynamics and structural injustices in society.

The trustworthiness of neural networks is often challenged because they lack the ability to express uncertainty and explain their skill. This can be problematic given the increasing use of neural networks in high stakes decision-making such as in climate change applications. We address both issues by successfully implementing a Bayesian Neural Network (BNN), where parameters are distributions rather than deterministic, and applying novel implementations of explainable AI (XAI) techniques. The uncertainty analysis from the BNN provides a comprehensive overview of the prediction more suited to practitioners' needs than predictions from a classical neural network. Using a BNN means we can calculate the entropy (i.e. uncertainty) of the predictions and determine if the probability of an outcome is statistically significant. To enhance trustworthiness, we also spatially apply the two XAI techniques of Layer-wise Relevance Propagation (LRP) and SHapley Additive exPlanation (SHAP) values. These XAI methods reveal the extent to which the BNN is suitable and/or trustworthy. Using two techniques gives a more holistic view of BNN skill and its uncertainty, as LRP considers neural network parameters, whereas SHAP considers changes to outputs. We verify these techniques using comparison with intuition from physical theory. The differences in explanation identify potential areas where new physical theory guided studies are needed.

A robotic recreation of the 17th century Mayflower ship has set sail for US shores once more after a failed first attempt last year. Mayflower Autonomous Ship (MAS) – a 50-foot-long autonomous research vessel piloted by artificial intelligence (AI) – departed from Plymouth, England on Wednesday (April 27). If all goes to plan, the £1 million ($1.3 million) ship will reach Virginia in about three weeks, and in the process become the largest autonomous vessel to ever cross the Atlantic. With no humans on board the ship, it relies on AI to make decisions and look out for potential obstacles in the water. MAS was built to recreate the original Mayflower's historic journey from England to the New World more than 400 years ago.