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'Special Report' All-Star Panel reacts to a federal judge declaring public transportation mask mandates unlawful. The mystery surrounding the Boeing plane crash in China last month lingers despite authorities recovering the plane's two black boxes and extensive investigations at the crash site. A Boeing 737 jet crashed into a hillside in Southern China on March 21, killing 132 people on board. China Eastern Airlines flight MU5735 was completing a domestic flight when the crash happened. The Civil Aviation Administration of China (CAAC) has led the investigation over the past month, but Wednesday reported that officials found no evidence of systematic failure aboard the plane at the time of the crash.
Sardar Vallabhbhai Patel International Airport (SVPIA) has introduced an indigenously developed artificial intelligence (AI) based surveillance service, Desk of Goodness, to help flyers through smart detection techniques. Desk of Goodness aims to serve passengers like senior citizens, women with infants, and passengers in need of a wheelchair. This desk is manned by goodness champions equipped with smart tabs, which keep them updated on possible sites where passengers need support. "Sardar Vallabhbhai Patel International Airport continues to improve infrastructure and services to enhance the passenger experience," said Jeet Adani, Director, Adani Airport Holdings. "AI-based video content analytics plays a crucial role in reaching out to flyers in emergencies. Analytics-based learnings will allow us to set new benchmarks in operational intelligence and increasing situational awareness, thereby improving safety, security and efficiency."
Pangiam, in collaboration with Google Cloud, has announced details of Project DARTMOUTH, an initiative to transform airport security operations by looking for threats concealed within baggage and other shipments at the airport. This technology will be tested within the security facilities of AGS Airport Ltd, owners and operators of Aberdeen, Glasgow, and Southampton Airports in the UK. Project DARTMOUTH is intended to make air travel safer by integrating AI into airport baggage security and screening operations. The technology will in the first instance be focused on rapidly identifying potential threats in baggage, providing increased throughput at security checkpoints, addressing critical friction points in air travel as well as supporting security teams. In later phases the technology will scale to help tackle other pressure points in security and wider airport operations.
Flying into Dallas Fort Worth International Airport from Mexico in December, I queued in the immigration line for US citizens and was taken aback when – rather than request my passport – the Customs and Border Protection (CBP) agent simply instructed me to look at the camera and then pronounced my first name: "Maria?" Feeling an abrupt violation of my entire bodily autonomy, I nodded – and reckoned that it was perhaps easy to lose track of the rapid dystopian devolution of the world when one had spent the past two years hanging out on a beach in Oaxaca. A CBP poster promoting the transparent infringement on privacy was affixed to the airport wall, and featured a grey-haired man smiling suavely into the camera along with the text: "Our policies on privacy couldn't be more transparent. In my case, the process was not so fast, as I had to hand over my passport for physical scrutiny after I raised the agent's suspicions by being unable to answer in any remotely coherent fashion the ...
General real-time runway occupancy time prediction modelling for multiple airports is a current research gap. An attempt to generalize a real-time prediction model for Arrival Runway Occupancy Time (AROT) is presented in this paper by substituting categorical features by their numerical equivalences. Three days of data, collected from Saab Sensis' Aerobahn system at three US airports, has been used for this work. Three tree-based machine learning algorithms: Decision Tree, Random Forest and Gradient Boosting are used to assess the generalizability of the model using numerical equivalent features. We have shown that the model trained on numerical equivalent features not only have performances at least on par with models trained on categorical features but also can make predictions on unseen data from other airports.
Autonomous robots were a major focus this year at CES, from roaming device demonstrations on the exhibit floor to virtual presentations discussing emerging trends in the space. Autonomous-delivery startup Ottonomy used the Las Vegas event to spotlight its Ottobot, the company's newly named delivery robot capable of navigating "crowded and unpredictable environments" and working indoors as well as outside. Two of Ottonomy's autonomous delivery robots, or ADRs, are operating inside Cincinnati/Northern Kentucky International Airport, where the bots make food, beverage and retail deliveries to passengers waiting to board flights. The autonomous robots, which resemble high-tech coolers on wheels, have a range of 2.5 miles and can operate for six to eight hours before needing to be recharged. The speed of the Ottobots is limited to 5 to 10 mph for safety reasons.
An NPC might wander across a city block and face-plant into a streetlamp, and then maybe vanish the next block over. NPCs leap into player-characters' punches or commit to kicking a wall 400 times, never learning that the wall won't kick back. Unity Technologies is in the business of NPCs. Founded in 2004, Unity makes an eponymous game engine that provides the architecture for hundreds of video games using its real-time 3D computer graphics technology. Unity also provides countless tools integrated with that game engine, including AI tools.
A suspected drone attack by Yemen's Houthi rebels targeting a key oil facility in Abu Dhabi killed three people and started a separate fire at Abu Dhabi's international airport, police said. Police in the United Arab Emirates identified the dead as two Indian nationals and one Pakistani. "Small flying objects" were found as three petrol tanks exploded in an industrial area and a fire was ignited at the airport, police said, as Houthi rebels announced "military operations" in the UAE. The UAE which had largely scaled down its military presence in Yemen in 2019, continues to hold sway through the Yemeni forces it armed and trained. Drone attacks are a hallmark of the Houthis' assaults on Saudi Arabia, the UAE ally that is leading the coalition fighting for Yemen's government in the grinding civil war.
This content can also be viewed on the site it originates from. On a cloudless morning last May, a pilot took off from the Niagara Falls International Airport, heading for restricted military airspace over Lake Ontario. The plane, which bore the insignia of the United States Air Force, was a repurposed Czechoslovak jet, an L-39 Albatros, purchased by a private defense contractor. The bay in front of the cockpit was filled with sensors and computer processors that recorded the aircraft's performance. For two hours, the pilot flew counterclockwise around the lake.
Anomalies, or outliers, can be a serious issue when training machine learning algorithms or applying statistical techniques. They are often the result of errors in measurements or exceptional system conditions and therefore do not describe the common functioning of the underlying system. Indeed, the best practice is to implement an outlier removal phase before proceeding with further analysis. In some cases, outliers can give us information about localized anomalies in the whole system; so the detection of outliers is a valuable process because of the additional information they can provide about your dataset. There are many techniques to detect and optionally remove outliers from a dataset.