Updated Facial recognition technology is being employed in more UK schools to allow pupils to pay for their meals, according to reports today. In North Ayrshire Council, a Scottish authority encompassing the Isle of Arran, nine schools are set to begin processing meal payments for school lunches using facial scanning technology. The authority and the company implementing the technology, CRB Cunninghams, claim the system will help reduce queues and is less likely to spread COVID-19 than card payments and fingerprint scanners, according to the Financial Times. Speaking to the publication, David Swanston, the MD of supplier CRB Cunninghams, said the cameras verify the child's identity against "encrypted faceprint templates", and will be held on servers on-site at the 65 schools that have so far signed up. He added: "In a secondary school you have around about a 25-minute period to serve potentially 1,000 pupils. So we need fast throughput at the point of sale."

Chris Rogers earned his B.S., M.S., and Ph.D. in mechanical engineering at Stanford University, where he worked with Professor John Eaton on his thesis on particle motion in a boundary layer flow. Rogers joined the Department of Mechanical Engineering at Tufts School of Engineering in 1989. He is involved in a number of research areas, including particle-laden flows (a continuation of his thesis), telerobotics and controls, the slurry flows in chemical-mechanical planarization, the engineering of musical instruments, measuring flame shapes of couch fires, measuring fruit-fly locomotion, and engineering education (kindergarten to college). At Tufts, Rogers has exercised his strong commitment to teaching by exploring a number of new directions, including teaching robotics with LEGO bricks and teaching manufacturing by building musical instruments. His teaching work extends to the elementary school level, where he talks with over 1,000 teachers around the world every year on methods of introducing young children to engineering.

Privacy campaigners have raised concerns about the use of facial recognition technology on pupils queueing for lunch in school canteens in the UK. Nine schools in North Ayrshire began taking payments for school lunches this week by scanning the faces of their pupils, according to a report in the Financial Times. More schools are expected to follow. The company supplying the technology claimed it was more Covid-secure than other systems, as it was cashless and contactless, and sped up the lunch queue, cutting the time spent on each transaction to five seconds. With break times shortening, schools are under pressure to get large numbers of students through lunch more quickly.

My life has always involved centering the voices of those historically marginalized in order to foster equitable communities. Growing up, I lived in a small suburb just outside of Cleveland, Ohio and I was fortunate enough to attend Laurel School, an all-girls school focused on encouraging young women to think critically and solve difficult world problems. But my lived experience at school was so different from kids who lived even on my same street. I was grappling with watching families around me contend with an economic recession, losing any financial security that they had and I wanted to do everything I could to change that. Even though my favorite courses at the time were engineering and African American literature, I was encouraged to pursue economics.

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Apple's second fall product event kicks off later today at 1 PM ET. We've laid out what to expect, but it's not the only big tech event week. Spare a thought for some of our staff, who will go straight from Apple reportage into Google. Yep, Tuesday October 19th is Google's Pixel 6 event. While we know what the phone will look like -- and some of its specifications -- expect to see some software surprises.

Schools in Scotland are trialling facial recognition to allow pupils to pay for their lunches from Monday. The software is to be trialled across nine schools in North Ayrhsire, and hopes to speed up lunchtime sales by scanning the faces of pupils when at tills. Many schools already use biometric software, such as fingerprint recognition, to take payments but facial recognition is billed as being quicker and more Covid-secure. David Swanston, the manging director of CBR Cunninghams, who installed the software, said it was "the fastest way of recognising someone at the till." "In a secondary school you have around about a 25-minute period to serve potentially 1,000 pupils. So we need fast throughput at the point of sale, he told the Financial Times. MPs and peers urge education secretary to rethink plans to scrap most BTECs Covid cases near peak of second wave as schoolchildren fuel rise Schools reminded to allow absences arising from Covid'in exceptional circumstances' Schools reminded to allow absences arising from Covid'in exceptional circumstances' Mr Swanston said the software cut the average transaction time five seconds per pupil. But the new system has been criticised by privacy campaigners who say it normalises facial recognition software where there is little need for and was often operated without clear consent from the user. Silkie Carlo, of the civil liberties campaign group Big Brother Watch, said: "It's normalising biometric identity checks for something that is mundane.

It is important for socially assistive robots to be able to recognize when a user needs and wants help. Such robots need to be able to recognize human needs in a real-time manner so that they can provide timely assistance. We propose an architecture that uses social cues to determine when a robot should provide assistance. Based on a multimodal fusion approach upon eye gaze and language modalities, our architecture is trained and evaluated on data collected in a robot-assisted Lego building task. By focusing on social cues, our architecture has minimal dependencies on the specifics of a given task, enabling it to be applied in many different contexts. Enabling a social robot to recognize a user's needs through social cues can help it to adapt to user behaviors and preferences, which in turn will lead to improved user experiences.

In this paper, we present a hypergraph--based machine learning algorithm, a datastructure--driven maintenance method, and a planning algorithm based on a probabilistic application of Dijkstra's algorithm. Together, these form a goal agnostic automated planning engine for an autonomous learning agent which incorporates beneficial properties of both classical Machine Learning and traditional Artificial Intelligence. We prove that the algorithm determines optimal solutions within the problem space, mathematically bound learning performance, and supply a mathematical model analyzing system state progression through time yielding explicit predictions for learning curves, goal achievement rates, and response to abstractions and uncertainty. To validate performance, we exhibit results from applying the agent to three archetypal planning problems, including composite hierarchical domains, and highlight empirical findings which illustrate properties elucidated in the analysis.

Speech representation learning plays a vital role in speech processing. Among them, self-supervised learning (SSL) has become an important research direction. It has been shown that an SSL pretraining model can achieve excellent performance in various downstream tasks of speech processing. On the other hand, supervised multi-task learning (MTL) is another representation learning paradigm, which has been proven effective in computer vision (CV) and natural language processing (NLP). However, there is no systematic research on the general representation learning model trained by supervised MTL in speech processing. In this paper, we show that MTL finetuning can further improve SSL pretraining. We analyze the generalizability of supervised MTL finetuning to examine if the speech representation learned by MTL finetuning can generalize to unseen new tasks.