Latest news with #Daramola
Yahoo
25-06-2025
- Science
- Yahoo
Researchers develop game-changing tool to predict deadly natural disasters: 'Of paramount importance'
A recent study published in the Water Resources Research journal discussed using a new deep learning framework — known as Long Short-Term Memory Station Approximated Models, or LSTM-SAM — to predict the state of water levels during extreme weather events, in order to better forewarn and evacuate nearby civilians. With Atlantic hurricane seasons lending themselves to more frequent and intense storm surges over the past decade, the impact of today's hurricanes could prove devastating for individuals and homes that aren't prepared. In particular, the coastal flooding associated with many hurricanes in the Southern U.S. has a history of endangering lives, buildings, and ecosystems. Led by environmental engineering Ph.D. candidate Samuel Daramola, the researchers used a "transfer learning" technique to quickly and accurately make predictions with LSTM-SAM. While conventional storm prediction models rely on large bodies of weather and ocean data that are inefficient and expensive to assemble, LSTM-SAM estimates flood levels based on broader flood patterns recorded in the past. One unique appeal of LSTM-SAM, per news, is the fact that accurate, high-efficiency storm predictions no longer need to be limited geographically to regions that have access to powerful data-processing facilities. Since LSTM-SAM bases its predictions on storm-flood patterns as a whole, the technology isn't locale-specific and can be applied to regions with minimal prior storm data. "Other studies have relied on repetitive patterns in the training data," Daramola told "Our approach is different. We highlight extreme changes in water levels during training, which helps the model better recognize important patterns and perform more reliably in those areas." More Atlantic hurricanes than ever are making landfall, which means the devastation wreaked by these storms cannot be understated. In fact, according to a 2023 report by the Front Page, rainfall flooding was responsible for more than half of the casualties caused by tropical cyclones. "The need for reliable flood prediction frameworks is of paramount importance," continued. "Advanced deep learning tools like LSTM-SAM could become essential in helping coastal communities prepare for the new normal, opening the door to smarter, faster, and more accessible flood predictions associated with tropical cyclones." While we can't prevent hurricanes altogether, cutting-edge predictive innovations can help minimize the safety risks and allow residents time to plan for an evacuation. Meanwhile, since planet-warming carbon pollution considerably supercharges seasonal storms, we can take small steps to reduce our unfriendly contributions, such as installing home solar panels, repurposing household waste, and switching to an electric vehicle. What would you do if natural disasters were threatening your home? Move somewhere else Reinforce my home Nothing This is happening already Click your choice to see results and speak your mind. Join our free newsletter for good news and useful tips, and don't miss this cool list of easy ways to help yourself while helping the planet.
Yahoo
22-03-2025
- Yahoo
Off-duty Prince George's County officer charged with driving while impaired
The Brief An off-duty Prince George's County Police patrol officer was charged with driving while impaired. Officer Simeon Daramola's police powers have since been suspended. PRINCE GEORGE'S COUNTY, Md. - A Prince George's County Police patrol officer was charged with driving while impaired. According to officials, Officer Simeon Daramola was off-duty at the time of the incident and driving his marked police cruiser. Officers with the Laurel City Police Department located Officer Daramola on Fourth Street in Laurel, Maryland on Saturday morning at around 2:15 a.m. He was issued DWI-related citations. Daramola's police powers have since been suspended. An administrative investigation has been launched into this incident. Daramola joined the agency in 2023 and is currently assigned to the Bureau of Patrol.
Yahoo
22-03-2025
- Yahoo
Off-duty PGPD officer accused of driving police cruiser while impaired in Laurel
PRINCE GEORGE'S COUNTY, Md. () — A Prince George's County Police Department (PGPD) officer was charged early Saturday after they were allegedly driving their police cruiser while impaired overnight. According to the Prince George's County Police Department (PGPD), at around 2:15 a.m., officer Simeon Daramola was driving on Fourth Street in Laurel when officers from the Laurel City Police Department stopped him. He was off-duty at the time but was driving his marked police cruiser. PGPD: Person dies, child hurt after crash linked to police pursuit in Prince George's County Officers issued Daramola, who joined the agency in 2023 and is currently assigned to the Bureau of Patrol, DWI-related citations. The officer's [Daramola's] police powers have been suspended,' said PGPD. 'The PGPD's Internal Affairs Division has opened an administrative investigation into this incident.' Copyright 2025 Nexstar Media, Inc. All rights reserved. This material may not be published, broadcast, rewritten, or redistributed.
Washington Post
22-03-2025
- Washington Post
Prince George's police officer charged with DWI in patrol car
A Prince George's County police officer was charged with driving his marked cruiser while impaired early Saturday in Laurel, county police officials said. Officer Simeon Daramola was off-duty but driving the patrol car on Fourth Street, where Laurel police located him about 2:15 a.m., according to a statement by county police. Daramola, a patrol officer who joined the agency in 2023, was 'issued DWI-related citations,' the statement said.
