Things to Do in L.A. Tap to enable a layout that focuses on the article. A Woodland Hills nursery is turning into a cemetery. Aerial view of where groves will turn to graves in Woodland Hills, where a developer has plans to redevelop Boething Treeland Nursery into a cemetery. This is read by an automated voice. Please report any issues or inconsistencies here .

The collaboration between communities and scientists aims to restore baobab forests in Madagascar to this natural state. Six of the world's eight baobab species are indigenous to Madagascar, where the distinctive trees with giant trunks have historically grown in huge forests. But these forests are threatened by slash-and-burn agriculture – 4,000 hectares of baobab forest in Madagascar are destroyed every year. Baobab trees can live for 1,000 years and one hectare of land can support eight fully grown baobab trees. But many have been left orphaned – standing alone in barren areas with no contact with the wild animals that spread their seeds, helping the baobabs to reproduce.

Real-time and accurate information on fine-grained changes in crop cultivation is of great significance for crop growth monitoring, yield prediction and agricultural structure adjustment. Aiming at the problems of serious spectral confusion in visible high-resolution unmanned aerial vehicle (UAV) images of different phases, interference of large complex background and salt-and-pepper noise by existing semantic change detection (SCD) algorithms, in order to effectively extract deep image features of crops and meet the demand of agricultural practical engineering applications, this paper designs and proposes an agricultural geographic scene and parcel-scale constrained SCD framework for crops (AGSPNet). AGSPNet framework contains three parts: agricultural geographic scene (AGS) division module, parcel edge extraction module and crop SCD module. Meanwhile, we produce and introduce an UAV image SCD dataset (CSCD) dedicated to agricultural monitoring, encompassing multiple semantic variation types of crops in complex geographical scene. We conduct comparative experiments and accuracy evaluations in two test areas of this dataset, and the results show that the crop SCD results of AGSPNet consistently outperform other deep learning SCD models in terms of quantity and quality, with the evaluation metrics F1-score, kappa, OA, and mIoU obtaining improvements of 0.038, 0.021, 0.011 and 0.062, respectively, on average over the sub-optimal method. The method proposed in this paper can clearly detect the fine-grained change information of crop types in complex scenes, which can provide scientific and technical support for smart agriculture monitoring and management, food policy formulation and food security assurance.

Anyone who's ever had children will know that every parent needs a break at some point - but a recently resurfaced video from the 1960s seemed to take that idea to new extremes. The footage, taken in 1960 as part of a news report, shows a nurse operating some'High-Tec' baby care equipment in a state-of-the-art nursery in Budapest, Hungary, which was run by the Communist-regime at the time. The video was produced as a prediction of what could be expected from childcare in the future. The imagined equipment can not only move babies from one crib to another at the touch of a button, but can also feed them by lowering a bottle into their arms, leaving no need for mum and dad. The invention is just a prototype, though, with the nursery being used as a demonstration of how robotics could help care for babies.

As awareness of the capabilities of Artificial Intelligence (AI) increases, workers in all roles and all industry sectors are being prompted to ask themselves a scary-sounding question: could AI take over your job? It's a question that's usually asked from a position of fear, with the assumption that our potential replacement by an algorithm is something almost completely outside of our control. Individual human beings are usually portrayed as sitting ducks, helpless before the inevitable disruption, fretting as we study predictions of the future and try to figure out if our role will be left standing at the end of it all. It can feel like a particularly urgent question when you work in marketing. Our industry is a committed early adopter and the speed with which automation and data-driven decision-making has moved into the marketing mainstream is quite breathtaking.

When my wife and I became parents, the most important weapon in our childcare arsenal was an A5-size notebook. In this mighty tome we wrote out every single data point relating to our new baby, from the quantity of milk she drank and duration of sleep through to the volume of excreta. It was, after all, only with this information that we were able, in our sleep-deprived and confused state, to coordinate how to meet her needs. Devices like Nanit's artificially intelligent baby monitor are designed to outsource much of that brainwork. It's a $349 night-vision camera that hangs over a cot, using computer vision and deep learning to monitor your little one's sleep. The little gadget is relatively small, but it packs a microphone, speaker, camera, nightlight and temperature sensor inside its body.