--This paper focuses on the development and modification of a beehive monitoring device and V arroa destructor detection on the bees with the help of hyperspectral imagery while utilizing a U-net, semantic segmentation architecture, and conventional computer vision methods. The main objectives were to collect a dataset of bees and mites, and propose the computer vision model which can achieve the detection between bees and mites. Bees are one of the most important creatures in the world, so humanity has to protect them. One of the bee diseases is varroosis, which is caused by V arroa destructor . Overpopulation of this mite in beehive can ruin a whole beehive.

Dynamic Graph Neural Networks (DyGNNs) have garnered increasing research attention for learning representations on evolving graphs. Despite their effectiveness, the limited expressive power of existing DyGNNs hinders them from capturing important evolving patterns of dynamic graphs. Although some works attempt to enhance expressive capability with heuristic features, there remains a lack of DyGNN frameworks with provable and quantifiable high-order expressive power. To address this research gap, we firstly propose the k-dimensional Dynamic WL tests (k-DWL) as the referencing algorithms to quantify the expressive power of DyGNNs. We demonstrate that the expressive power of existing DyGNNs is upper bounded by the 1-DWL test. To enhance the expressive power, we propose Dynamic Graph Neural Network with High-order expressive power (HopeDGN), which updates the representation of central node pair by aggregating the interaction history with neighboring node pairs. Our theoretical results demonstrate that HopeDGN can achieve expressive power equivalent to the 2-DWL test. We then present a Transformer-based implementation for the local variant of HopeDGN. Experimental results show that HopeDGN achieved performance improvements of up to 3.12%, demonstrating the effectiveness of HopeDGN.

When computer science students and faculty at Carnegie Mellon University's Institute for Software Research returned to campus in the summer of 2020, there was a lot to adjust to. The department had moved into a brand-new building, complete with experimental super-sensing devices called Mites. Embedded in more than 300 locations throughout the building, these light-switch-size devices measure 12 types of data--including motion and sound. The Mites had been installed as part of a research project on smart buildings, and was quickly met with resistance from students and faculty who felt the devices would subject them to experimental surveillance without their consent. The conflict has deteriorated into a bitter dispute, complete with accusations of bullying, vandalism, misinformation, and workplace retaliation.

Varroa destructor is a deadly stowaway that port authorities are determined to keep away from the bee population in the southeast Australian state of Victoria. Artificially intelligent beehives are being installed at Victorian ports to detect pests as they arrive at ships rapidly. "The Varroa mite is extremely destructive; it kills bees very rapidly," said Mary-Anne Thomas, the Victorian agriculture minister. "I would look forward to a project like the Purple Hive rolling out across the country. Purple Hive was launched on March 29 at the Port of Melbourne -- a solar-powered device that detects Varroa destructor, a mite that feeds on honey bees. Using artificial intelligence and cameras, Purple Hive provides alerts in real-time and has been trialed in New Zealand, where the mite is established. The technology scans each honey bee entering the Purple Hive to determine if Varroa mite is present. The hive is colored purple because it attracts bees. Thomas tweeted a picture of a hive being installed. "At #BegaCheese, we're absolutely buzzing with excitement to announce that B honey's Purple Hive has officially found its first home at the Port of Melbourne, as we join forces with @VicGovAg to help protect honey bee populations from Varroa destructor," read the tweet of Jimmy Coleman, marketing manager of digital and communications, Bega Cheese. "Varroa destructor is the world's most devastating pest of Western honey bees, Apis mellifera Linnaeus," as per the website of the University of Florida. "Accurate estimates of the effect of Varroa on the apiculture industry are hard to find, but it is safe to assume that the mites have killed hundreds of thousands of colonies worldwide, resulting in billions of dollars of economic loss." The adult female mites are reddish-brown to dark brown and oval. Adult males are yellowish with light tan legs and have a spherical body shape. Varroa destructor, the most significant single driver of the global honey bee health decline, was detected on a ship that entered the Port of Melbourne in 2018, but authorities stopped it from becoming an outbreak. "Australia is the only populated country in the world that the Varroa destructor hasn't impacted.

The Varroa destructor mite is one of the most dangerous Honey Bee (Apis mellifera) parasites worldwide and the bee colonies have to be regularly monitored in order to control its spread. Here we present an object detector based method for health state monitoring of bee colonies. This method has the potential for online measurement and processing. In our experiment, we compare the YOLO and SSD object detectors along with the Deep SVDD anomaly detector. Based on the custom dataset with 600 ground-truth images of healthy and infected bees in various scenes, the detectors reached a high F1 score up to 0.874 in the infected bee detection and up to 0.727 in the detection of the Varroa Destructor mite itself. The results demonstrate the potential of this approach, which will be later used in the real-time computer vision based honey bee inspection system. To the best of our knowledge, this study is the first one using object detectors for this purpose. We expect that performance of those object detectors will enable us to inspect the health status of the honey bee colonies.

Bega Cheese has launched a network of smart beehives that can automatically detect parasites in a bid to safeguard Australian honey production. The Purple Hive Project uses 3D printed components to house 360 degree cameras that feed into an artificial intelligence algorithm that is capable of identifying healthy bees from those carrying the deadly varroa destructor mite. The solar-powered devices immediately send an alert to beekeepers to quarantine the affected hive to contain the spread of the mite, which has devastated bee colonies on every other continent. An initiative from Bega Cheese's B Honey brand, the devices can be fixed to existing beehives for round the clock monitoring at high-risk entry points to Australia, saving beekeepers from having to perform manual inspections. Unchecked infestations of varroa mites can cripple and even kill off entire hives within three to fours years, industry group BeeAware said.

In life, bacteria are everywhere. Even on the cleanest sheets and pillowcases, bacteria are there. You can't see them with the naked eye but that does not mean they can not harm you. They cause you to get colds, viral infections, and put your life at risk. How can one get rid of these bacteria? ROCKUBOT: Sterilizing Robot is here to help.

Machine learning and all its related forms of "AI" are being used to work on just about every problem under the sun, but even so, stemming the alarming decline of the bee population still seems out of left field. In fact it's a great application for the technology and may help both bees and beekeepers keep hives healthy. The latest threat to our precious honeybees is the Varroa mite, a parasite that infests hives and sucks the blood from both bees and their young. While it rarely kills a bee outright, it can weaken it and cause young to be born similarly weak or deformed. Over time this can lead to colony collapse.

Listen, you're kinda spooked about the rise of artificial intelligence, and I get that. It's a tremendously powerful technology that promises to transform the very nature of work, inevitably leading to the automation of certain white-collar jobs. But AI also promises to make human labor smarter and more efficient, even something as traditional as small-scale farming. To that end, researchers have developed a smartphone-based program that can automatically detect diseases in the cassava plant--the most widely grown root crop on Earth--with darn near 100 percent accuracy. The most impressive bit about the technology is that the neural network that powers it runs entirely on the smartphone, no cloud computing or hulking processors required, as the researchers detail in a preprint paper to be published in Frontiers in Plant Science.

Psoroptes cuniculi mites are non-burrowing parasites that chew the skin in the ear canal of rabbits. Kitchen sponges can accumulate food and microbes when used for long periods of time and are not thoroughly cleaned. Millions of dust mites inhabit the home, feeding on dead human skin that are common in house dust. Pseudoscorpions are generally beneficial to humans since they prey on moth larvae, carpet beetle larvae, booklice and mites. Watch video Raging bull destroys car with horns at Spanish festival Watch video Wes Anderson gets festive for H&M 2016 Christmas collection Watch video Meet Reagan and Little Buddy whose friendship inspired a book Watch video Three pen tricks explained in this amazing magic tutorial Watch video Angry Trump supporter goes on wild'racist' rant inside store Watch video Hilarious moment baby boy joins in with twerking girls Watch video Shanghai Jiao Tong researchers test facial recognition software Watch video Man films the moment after woman jumps out the plane by the gate Watch video Moment Dolphins and 49ers fans start massive brawl in the stands Watch video LOVE Magazine's Hype Williams advent teaser for Christmas 2016 Watch video Aleexandra is'selling her virginity' to the highest bidder Watch video Road rage attack shows driver smashing lorry window with spade Watch video Angry Trump supporter goes on wild'racist' rant inside store Watch video Hilarious moment baby boy joins in with twerking girls Watch video Shanghai Jiao Tong researchers test facial recognition software Watch video Man films the moment after woman jumps out the plane by the gate Watch video Angry Trump supporter goes on wild'racist' rant inside store Watch video Hilarious moment baby boy joins in with twerking girls Watch video Shanghai Jiao Tong researchers test facial recognition software Watch video Man films the moment after woman jumps out the plane by the gate Watch video Angry Trump supporter goes on wild'racist' rant inside store Angry Trump supporter goes on wild'racist' rant inside store Watch video Moment Dolphins and 49ers fans start massive brawl in the stands Watch video LOVE Magazine's Hype Williams advent teaser for Christmas 2016 Watch video Aleexandra is'selling her virginity' to the highest bidder Watch video Road rage attack shows driver smashing lorry window with spade Watch video Moment Dolphins and 49ers fans start massive brawl in the stands Watch video LOVE Magazine's Hype Williams advent teaser for Christmas 2016 Watch video Aleexandra is'selling her virginity' to the highest bidder Watch video Road rage attack shows driver smashing lorry window with spade Watch video Aleexandra is'selling her virginity' to the highest bidder Aleexandra is'selling her virginity' to the highest bidder The scans were taken by scientists Steve Gschmeissner, who is one of the world's leading scanning electron microscopists in the world and award winning photo-micrographer Dennis Kunkel.