Understanding how air traffic controllers construct a mental 'picture' of complex air traffic situations is crucial but remains a challenge due to the inherently intricate, high-dimensional interactions between aircraft, pilots, and controllers. Previous work on modeling the strategies of air traffic controllers and their mental image of traffic situations often centers on specific air traffic control tasks or pairwise interactions between aircraft, neglecting to capture the comprehensive dynamics of an air traffic situation. To address this issue, we propose a machine learning-based framework for explaining air traffic situations. Specifically, we employ a Transformer-based multi-agent trajectory model that encapsulates both the spatio-temporal movement of aircraft and social interaction between them. By deriving attention scores from the model, we can quantify the influence of individual aircraft on overall traffic dynamics. This provides explainable insights into how air traffic controllers perceive and understand the traffic situation. Trained on real-world air traffic surveillance data collected from the terminal airspace around Incheon International Airport in South Korea, our framework effectively explicates air traffic situations. This could potentially support and enhance the decision-making and situational awareness of air traffic controllers.

Path-finding is one of the most popular subjects in the field of computer science. Pathfinding strategies determine a path from a given coordinate to another. The focus of this paper is on finding the optimal path for the bus transportation system based on passenger demand. This study is based on bus stations in Incheon, South Korea, and we show that our modified A* algorithm performs better than other basic pathfinding algorithms such as the Genetic and Dijkstra. Our proposed approach can find the shortest path in real-time even for large amounts of data(points).

A young boy communicating with a robot that is on display at Incheon International Airport in Seoul ... [ ] / South Korea. Artificial Intelligence is going to transform the world, changing a lot of things for all categories of people in the process; children will be among the most affected. "You and I live in an age where we're starting to be impacted, but we've spent a lot of our lives not really having interacted with AI. We're also adults that have some volition and agency. For children, it's different," Erica Kochi, co-founder of UNICEF Innovation Unit, tells me.

Our company mainly focuses on building services to facilitate a better understanding of what event is taking place in the environmental sound scene (e.g. The conference on INTERSPEECH, one of the biggest conferences on the science and technology of spoken language processing, was held at Songdo ConvensiA, in Incheon, South Korea, from Sep. 18 to 22, 2022. Integrating two previous series of conferences (EUROSPEECH and ICSLP), the first INTERSPEECH was held in 2000, in Beijing. Since then, INTERSPEECH has gained popularity and held the 23rd event this year, 2022. Despite a small discrepancy between our main focus and the conference theme, because our company primarily concentrates on nonverbal audio signals other than speech itself, many papers from INTERSPEECH have aided our research so far.

I'm bringing you all some of the AI-related news and developments I found most interesting over the past week. Read on to learn more about neural networks, a cooperative AI infrastructure, AI crypto trading bots, and AI/human visual processing. A team of researchers at Los Alamos National Laboratory has developed a novel approach for comparing neural networks. According to the team, this new approach looks within the "black box" of artificial intelligence, and it helps them understand neural network behavior. A team of scientists at Incheon National University in South Korea has designed a cooperative infrastructure for artificial intelligence (AI)-assisted aerial and ground operations by using UAVs and mobile robots.

I interviewed nine of the most brilliant minds in the AI space. Each of them possesses a unique perspective, vastly different paths to the world of AI, and one-of-a-kind approaches and principles on how AI can be used ethically to bring about positive change. What if we were able to take beliefs, values, best processes, and experiences from each of them to create one singular AI mind? Would that mind create a roadmap leading us to the light we all seek? INCHEON AIRPORT, SEOUL, SOUTH KOREA - 2018/06/12: Airport visitors are communicating with a robot ... [ ] that is on display at Incheon International Airport in Seoul / South Korea.

Incheon, South Korea – Kim, 35, did not explicitly object when his wife started investing in art three years ago – but he had his reservations. "I told her that I'm fine as long as you want it," the video game designer, who asked to be identified by his last name only, told Al Jazeera. "But I was secretly thinking, why not just invest that money into stocks or something?" But as time passed, Kim began to appreciate how art could offer an escape from the COVID-19 pandemic and the monotony of work. Last year, he joined her in collecting fine art.

The COVID-19 pandemic took the world by storm in early 2020 and has become since then the leading cause of death in several countries, including China, USA, Spain, and the United Kingdom. Researchers are working extensively on developing practical ways to diagnose COVID-19 infections, and many of them have focused their attention on how artificial intelligence (AI) could be leveraged for this purpose. Several studies have reported that AI-based systems can be used to detect COVID-19 in chest X-ray images because the disease tends to produce areas with pus and water in the lungs, which show up as white spots in the X-ray scans. Although various diagnostic AI models based on this principle have been proposed, improving their accuracy, speed, and applicability remains a top priority. Now, a team of scientists led by Professor Gwanggil Jeon of Incheon National University, Korea, has developed an automatic COVID-19 diagnosis framework that turns things up a notch by combining two powerful AI-based techniques.

A young boy communicating with a robot that is on display at Incheon International Airport in Seoul / South Korea. Artificial Intelligence is going to transform the world, changing a lot of things for all categories of people in the process; children will be among the most affected. "You and I live in an age where we're starting to be impacted, but we've spent a lot of our lives not really having interacted with AI. We're also adults that have some volition and agency. For children, it's different," Erica Kochi, co-founder of UNICEF Innovation Unit, tells me.

Never mind airport security, artificial intelligence (AI) may also be rooting through your luggage in the near future at Incheon International Airport. Incheon International Airport Corporation said Wednesday it will incorporate AI into its security systems in a bid to improve accuracy in screening passenger luggage for prohibited items. The airport has already started working on the project to develop an AI-based X-ray screening system to be tested in the second half of next year. Instead of the existing system that relies on X-ray scanning, manual image checking by security officers and a final physical check, artificial intelligence will crosscheck the X-ray scan and the analysis will be available to officers along with the X-ray image. The first-stage AI scan is expected to complement and improve the accuracy of the security check as an officer will continue to be responsible for the final call to physically inspect luggage.