This work addresses the problem of path tracking control of a suspended load using a tilt-rotor UAV. The main challenge in controlling this kind of system arises from the dynamic behavior imposed by the load, which is usually coupled to the UAV by means of a rope, adding unactuated degrees of freedom to the whole system. Furthermore, to perform the load transportation it is often needed the knowledge of the load position to accomplish the task. Since available sensors are commonly embedded in the mobile platform, information on the load position may not be directly available. To solve this problem in this work, initially, the kinematics of the multi-body mechanical system are formulated from the load's perspective, from which a detailed dynamic model is derived using the Euler-Lagrange approach, yielding a highly coupled, nonlinear state-space representation of the system, affine in the inputs, with the load's position and orientation directly represented by state variables. A zonotopic state estimator is proposed to solve the problem of estimating the load position and orientation, which is formulated based on sensors located at the aircraft, with different sampling times, and unknown-but-bounded measurement noise. To solve the path tracking problem, a discrete-time mixed $\mathcal{H}_2/\mathcal{H}_\infty$ controller with pole-placement constraints is designed with guaranteed time-response properties and robust to unmodeled dynamics, parametric uncertainties, and external disturbances. Results from numerical experiments, performed in a platform based on the Gazebo simulator and on a Computer Aided Design (CAD) model of the system, are presented to corroborate the performance of the zonotopic state estimator along with the designed controller.

Bogota - Carmenza Gomez was planning a surprise Christmas dinner in the winter of 2008 to celebrate having her eight children back together under one roof in their home in an impoverished suburb in Bogota, the capital of Colombia. That summer, the family had finally been reunited after years apart due to the sons' military service. It was months away, but Carmenza wanted to throw an elaborate dinner to share their first Christmas together in years. But just days after the last of her sons arrived home, 23-year-old Victor Fernando, her third youngest, disappeared. "I didn't tell any of them what I was planning [for Christmas]," Carmenza recalled nearly a decade later.

One candidate fled the violence of Colombia with her mom at age nine. Another fled the Taliban at age six. A third says his parents were almost deported from the United States. Catalina Cruz and Safiya Wazir won their primary elections in New York and New Hampshire respectively last week, while William Tong is campaigning to become Connecticut's first Asian American attorney general. They're representative of a surge of minority candidates in this year's midterm elections, in which more women and people of color are not only running for office--but also winning votes and unseating entrenched politicians.

There has only ever been on question to ask about each year's Fifa: is it worth getting? And there's usually been far more than one answer, all kinds of caveats about the kind of features you use and player you are. This year the answer is as simple as the question. The changes are subtle but they are everywhere, and offer something for every kind of player. If you're a fan of authenticity the Champions League will be worth it alone, but if you want silliness like games with no fouls then there's plenty of that too.

Another option is at the very least to cooperate in order to increase the power of negotiation. A lot of the development of AI is based on the accumulation of enormous amount of data. This data is being accumulated from throughout the world, from countries like India, Brazil or Mexico, and is centralized in places like California or China. You can say that to some extent what we see today in the world is a kind of data colonization. Just as in the 19th century (when) raw material from South America, Africa, Asia, was used to fuel the industrial revolution in Europe and the countries that provided the raw material gained almost nothing in return, a similar thing may be happening now with data.

This decade has seen us move our notion and application of Artificial Intelligence (AI) forward in dramatic terms. Fuelled by continual advances in computer processing and data analytics, the Machine Learning (ML) that goes to help create AI brains (often called'software agents') has been the subject of much debate in both technical and human cultural circles. As soon as we started to realize that AI and ML are actually going to change our world, we immediately wanted to know how, when, where and by how much. There has been widespread concern over which human jobs would be made redundant by AI; although that furore appears to be abating now that humans understand that AI will more likely take away the'grunt work' and help to create new higher-value jobs. Quite apart from the technical arguments (could hackers use quantum computing and AI to create a computing mega virus, for example), we have also concerned ourselves with the human cultural aspects of AI.

After half a century of hype and false starts, artificial intelligence may finally be starting to transform the U.S. economy. An example is machine translation, as we found when analyzing eBay's deployment in 2014 of an AI-based tool that learned to translate by digesting millions of lines of eBay data and data from the Web. The aim is to allow eBay sellers and buyers in different countries to more easily connect with one another. The tool detects the location of an eBay user's Internet Protocol address in, say, a Spanish-speaking country and automatically translates the English title of the eBay offering. After eBay unveiled its English-Spanish translator for search queries and item titles, exports on eBay from the United States to Latin America increased by more than 17 percent.

Machines and algorithms in the workplace are expected to create 133 million new roles, but cause 75 million jobs to be displaced by 2022 according to a new report from the World Economic Forum (WEF) called "The Future of Jobs 2018." This means that the growth of artificial intelligence could create 58 million net new jobs in the next few years. With this net positive job growth, there is expected to be a major shift in quality, location and permanency for the new roles. And companies are expected to expand the use of contractors doing specialized work and utilize remote staffing. In 2025, machines are expected to perform more current work tasks than humans compared to 71% being performed by humans as of now.

Erik Brynjolfsson is the director of the MIT Initiative on the Digital Economy and co-author, with Andrew McAfee, of "Machine/Platform/Crowd." Xiang Hui is an assistant professor of marketing at Washington University, where Meng Liu is a visiting assistant professor of marketing; both are research fellows at the MIT initiative. After half a century of hype and false starts, artificial intelligence may finally be starting to transform the U.S. economy. An example is machine translation, as we found when analyzing eBay's deployment in 2014 of an AI-based tool that learned to translate by digesting millions of lines of eBay data and data from the Web. The aim is to allow eBay sellers and buyers in different countries to more easily connect with one another. The tool detects the location of an eBay user's Internet Protocol address in, say, a Spanish-speaking country and automatically translates the English title of the eBay offering.

"If agriculture goes wrong, nothing else will have a chance to go right in the country" M. S. Swaminathan Agriculture has evolved with mankind through centuries. Today, agriculture contributes 3.8% to the world's GDP, although the contribution of individual nations across the spectrum varies widely, between 0%-60%. Over the years, while its share in the world economy has reduced vis-à-vis manufacturing and services, the importance of agriculture hasn't. The demand for food is never ending and is projected to increase by 70% by 2050 with limited natural resources at disposal. This situation throws up unique challenges; advanced technologies may be a solution.