MultiLabel Learning (MLL) [1] is one of the most common machine learning tasks today. It is based on the idea that each data sample is associated with a certain subset of labels. The full set of labels can be large, in many cases even having more labels than input features. As a result, it is common for some labels to occur in only a few samples, while others occur much more frequently. The label imbalance [2] in MLL is almost always present, and it is a serious obstacle to training good classifiers. Class imbalance is a very well-known problem in traditional learning tasks such as binary and multiclass classification. Hundreds of articles [3, 4, 5], conference papers [6] and books [7] have been devoted to studying it and proposing possible solutions. The most popular are data resampling, cost-sensitive learning and mixtures of these approaches [8, 9]. However, imbalanced learning in the MLL field presents some specific aspects that make it more difficult to deal with this problem.

ABSTRACT Currently, research in robotics, artificial intelligence and drones are advancing exponentially, they are directly or indirectly related to various areas of the economy, from agriculture to industry. With this context, this project covers these topics guiding them, seeking to provide a framework that is capable of helping to develop new future researchers. For this, we use an aerial vehicle that works autonomously and is capable of mapping the scenario and providing useful information to the end user. This occurs from a communication between a simple programming language (Scratch) and one of the most important and efficient robot operating systems today (ROS). This is how we managed to develop a tool capable of generating a 3D map and detecting objects using the camera attached to the drone. Although this tool can be used in the advanced fields of industry, it is also an important advance for the research sector. The implementation of this tool in intermediate-level institutions is aspired to provide the ability to carry out high-level projects from a simple programming language.

ABSTRACT: Commercial drones are not yet dimensioned to perform indoor autonomous tasks, since they use GPS for their location in the environment. When it comes to a space with physical obstacles (walls, metal, etc.) between the communication of the drone and the satellites that allow the precise location of the same, there is great difficulty in finding the satellites or it generates interference for this location. This problem can cause an unexpected action of the drone, a collision and a possible accident can occur, The work to follow presents the development of a drone capable of operating in a physical space (indoor), without the need for GPS. In this proposal, a prototype of a system for detecting the distance (lidar) that the drone is from the walls is also developed, with the aim of being able to take this information as the location of the drone.

This work focuses on drones or UAVs (Unmanned Aerial Vehicles) for use in industry in general. These vehicles have a large number of uses and potential in the industry, as a tool for civil engineering, medicine, mining, among others. However, this vehicle is limited for use indoors due to the need for GPS and it does not work indoors. In this way, this work presents a UAV that works without GPS, thus being able to be used in closed spaces for example and have good precision. The work is based on an approach that uses computer vision and GPS.

Universidad Tecnológica del Uruguay, Rivera, Uruguay 2 ABSTRACT The implementation of robots to enhance some processes has become popular in recent years due to the accelerated way of production in some factories. Within this context was where robotics has emerged, firstly with stationary robots and more recently mobile robots, namely aerial and terrestrial robots. They can be used for delimited processes within a function, mainly the stationary robots, but also for research in wider areas and even competition. This work summarizes the construction of a model of terrestrial mobile robot that makes the use of artificial intelligence for the purpose of research and competitions, all of that with the basic sensing that can be used in industry. (Rovas, 2015).

Earlier this year, at the famed La Romareda stadium in Zaragoza, Spain, EA Sports organised two football matches, one each for male and female pro players. During these competitive 90-minute fixtures, all participants, including subs and officials, wore advanced Xsens motion capture suits that recorded their every movement, shot, tackle and celebration. Involving more than 70 people it was, according to gameplay producer Sam Rivera, the largest number of players ever motion-captured in a single session. Every year, the developers of Fifa tell us that their key aim is authenticity. This year, Fifa 23 – the final product of EA Sports and Fifa's 30-year partnership – is about making key moments more intelligible, detailed and dramatic, zooming in ever closer to the action at pitch level.

Intel is known mainly for its dominance in the market for central processing units, the brains behind personal computers and the servers that run corporate networks and the internet. But it has lost some of its sheen for investors over the past decade as Nvidia gobbled up the market for chips specifically designed for AI purposes, especially chips that train AI models. Nvidia now accounts for about 80% of revenue from AI-specific computation in big data centers, according to Informa PLC's Omdia unit, a British research and consulting firm, although that doesn't account for any AI calculations done on Intel's general-purpose CPUs. That dominance in AI-specific chips helped Nvidia surpass Intel as the most valuable chip company in the U.S. by market capitalization two years ago. AI chips are a relatively small but rapidly growing segment of the overall chip market.

Larry Niven's 1970 novel Ringworld is a beloved classic that received the Hugo, Nebula, and Locus awards. But science fiction author Rajan Khanna says the book has some major shortcomings for a modern reader. "I think that what this novel becomes is basically two thought experiments that get sandwiched together," Khanna says in Episode 505 of the Geek's Guide to the Galaxy podcast. "The characters are there to help explain these parts of the thought experiments, but they don't really--for me--become fully fledged, likable, relatable, or even interesting characters." Ringworld is currently being adapted for television by Akiva Goldsman, with Game of Thrones director Alan Taylor slated to direct the pilot.

As Sam Rivera explained it to me, the success of FIFA 22's new animation technology will be seen in what wasn't recorded during a groundbreaking motion-capture session -- involving 22 players all playing a start-to-finish game of soccer -- earlier this year. "We started working on an algorithm about three years ago," explained Rivera, FIFA 22's lead gameplay producer at EA Vancouver. "What that algorithm is doing is learning from all the data for that motion capture shoot -- how the players approach the ball, how many steps do they do to get to the ball, is it three long steps and one short step; what is the proper angle, with the proper cadence, to properly hit that ball?" Then, Rivera says, "it creates that solution, it creates the animation in real time. That is very, very cutting-edge technology. This is basically the beginning of machine learning taking over animation."

To bring more realism to "FIFA 22," EA Sports went to extremes on the pitch – and brought inclusivity to its announcing team. The video game publisher had 22 players put on Xsens motion capture suits and then play competitive matches in Spain. All that data – more than 8.7 million frames of advanced match capture, EA Sports says – will be used to create real-time soccer gameplay animations as players mash controller buttons. And the game maker also is bringing its first female announcer to the game: Alex Scott, who played for the English national team and Arsenal of the Women's Super League. "This is a big moment for FIFA, for football and women and girls across the world," she said on Twitter and Instagram.