The Internet of Things (IoT) is a paradigm characterized by a network of embedded sensors and services. These sensors are incorporated to collect various information, track physical conditions, e.g., waste bins' status, and exchange data with different centralized platforms. The need for such sensors is increasing; however, proliferation of technologies comes with various challenges. For example, how can IoT and its associated data be used to enhance waste management? In smart cities, an efficient waste management system is crucial. Artificial Intelligence (AI) and IoT-enabled approaches can empower cities to manage the waste collection. This work proposes an intelligent approach to route recommendation in an IoT-enabled waste management system given spatial constraints. It performs a thorough analysis based on AI-based methods and compares their corresponding results. Our solution is based on a multiple-level decision-making process in which bins' status and coordinates are taken into account to address the routing problem. Such AI-based models can help engineers design a sustainable infrastructure system.

It needs to be through engineering and design. If you don't do your chores, the company won't succeed. No task is too menial. If you get up in the morning and think the future is going to be better, it is a bright day. I take the position that I am always to some degree wrong and the aspiration is to be less wrong.

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The graph represents a network of 1,896 Twitter users whose tweets in the requested range contained "tech4good", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Saturday, 25 December 2021 at 19:29 UTC. The requested start date was Saturday, 25 December 2021 at 01:01 UTC and the maximum number of days (going backward) was 14. The maximum number of tweets collected was 7,500. The tweets in the network were tweeted over the 13-day, 13-hour, 25-minute period from Saturday, 11 December 2021 at 01:07 UTC to Friday, 24 December 2021 at 14:32 UTC.

In the moon-like landscape of northern Sudan, informal gold miners toil with spades and pickaxes to extract their prize from shallow pits that pockmark the terrain. Mining ore in the sweltering heat of the Nubian desert is the first stage of an illicit network that has exploded in the past 18 months following a pandemic-induced spike in the gold price. African governments desperate to recoup lost revenue are looking to Dubai to help stop the trade. Interviews with government officials across Africa reveal smuggling operations that span at least nine countries and involve tons of gold spirited over borders. That's a cause for international concern because the funds from contraband minerals dealing in Africa fuel conflict, finance criminal and terrorist networks, undermine democracy and facilitate money laundering, according to the Organisation for Economic Cooperation and Development. While it's impossible to say precisely how much is lost to smugglers each year, United Nations trade data for 2020 show a discrepancy of at least $4 billion between the United Arab Emirates' declared gold imports from Africa and what African countries say they exported to the UAE.

The year 2021 was filled with numerous challenges and ups and downs but despite these, I emerged a better and stronger person. When I started my career in tech, I was inclined to the hardware part. However, on getting into the software space, I developed a keen interest in AI and wanted to get to learn the skill but I was confused and lost. I had no idea where and how to start. But, I took the leap of faith towards my path of interest.

We propose to model matrix time series based on a tensor CP-decomposition. Instead of using an iterative algorithm which is the standard practice for estimating CP-decompositions, we propose a new and one-pass estimation procedure based on a generalized eigenanalysis constructed from the serial dependence structure of the underlying process. A key idea of the new procedure is to project a generalized eigenequation defined in terms of rank-reduced matrices to a lower-dimensional one with full-ranked matrices, to avoid the intricacy of the former of which the number of eigenvalues can be zero, finite and infinity. The asymptotic theory has been established under a general setting without the stationarity. It shows, for example, that all the component coefficient vectors in the CP-decomposition are estimated consistently with the different error rates, depending on the relative sizes between the dimensions of time series and the sample size. The proposed model and the estimation method are further illustrated with both simulated and real data; showing effective dimension-reduction in modelling and forecasting matrix time series.

As the world reopened cautiously in 2021, our correspondents seized the chance to venture out in search of stories that would astonish, delight, provoke and enlighten. We went from the heights of a Himalayan ski slope to the ocean depths off the Philippines where amiable giants dive, and from a rugged island where a whistling language is still used to an Italian atelier where robots carve the sculptures. If the pandemic often kept our reporters confined to urban settings in 2020, this year afforded them the chance to explore deep into the countryside. We observed a (bogus) diamond rush in rural South Africa and accompanied Indigenous hunters in Taiwan. We trekked to Canada's beaver dams, swam in a contested stream in northern Israel and returned home to a Tuscan village sliding back in time.

This is just one of a series of posts giving our valued community a review of our 2021 achievements… and a small peek at what comes next! This Roadmap End-of-Year Review Series will be followed up next year with an in-depth series on the Roadmap plans for 2022 in January/February. Don't miss the rest of this series! Mindplex is developing a media platform and AI accessories to decentralize and democratize media. The Mindplex Content Factory will match content creators and content consumers based on an AI-driven reputation system, combined with tokenomics, to help the platform to be more decentralized, community-led, and merit-based.

This year at Future Tense Fiction we've spent a lot of time thinking about how, in many ways, 2021 has felt a lot like 2020. But at the same time, so much has changed--how we work and think, how we commute, how we interact with animals, technology, and our fellow humans. This year we published 11 stories (we took December off!) that touch upon relationships, transportation, right to repair and supply chain shortages, communication, information overload and scarcity, and much, much more. We broadly explored themes like learning futures, with Simon Brown's "Speaker" (where humans learn to communicate with other species and struggle to overcome the assumption of human excellence), Leigh Alexander's "The Void" (about the struggle with information scarcity in an information-overloaded world) and Shiv Ramdas' "The Trolley Solution" (about a university attempting to automate how it teaches its students), as well as ideas of mobility--a theme we're continuing into 2022, so stay tuned--with Linda Nagata's "Ride" (about a neighborhood that's embraced an algorithm to run all of its traffic and transit patterns). We began publishing fiction back in 2016 and made it monthly as of January 2018.