The proliferation of Internet of Things (IoT) devices equipped with acoustic sensors necessitates robust acoustic scene classification (ASC) capabilities, even in noisy and data-limited environments. Traditional machine learning methods often struggle to generalize effectively under such conditions. To address this, we introduce Q-ASC, a novel Quantum-Inspired Acoustic Scene Classifier that leverages the power of quantum-inspired transformers. By integrating quantum concepts like superposition and entanglement, Q-ASC achieves superior feature learning and enhanced noise resilience compared to classical models. Furthermore, we introduce a Quantum Variational Autoencoder (QVAE) based data augmentation technique to mitigate the challenge of limited labeled data in IoT deployments. Extensive evaluations on the Tampere University of Technology (TUT) Acoustic Scenes 2016 benchmark dataset demonstrate that Q-ASC achieves remarkable accuracy between 68.3% and 88.5% under challenging conditions, outperforming state-of-the-art methods by over 5% in the best case. This research paves the way for deploying intelligent acoustic sensing in IoT networks, with potential applications in smart homes, industrial monitoring, and environmental surveillance, even in adverse acoustic environments.

It looks like enough of us believe in fairies after all, but it's not Tinkerbell who is flying this time. Scientists from Tampere University in Finland have developed a 0.2-inch (4 mm) robot that uses wind and light energy to soar through the air. Their'flying aero-robot based on light-responsive materials assembly' - FAIRY - weighs just 1.2 milligrams, meaning it can be blown about by even a gentle breeze. It resembles a dandelion seed or'pappus', with super-fine bristles poking from two wings which gently flap when activated with light. The'flying aero-robot based on light-responsive materials assembly' (pictured) - FAIRY - weighs just 1.2 milligrams so can be blown about by even a gentle breeze.

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Scandit is a high-growth tech scaleup from Switzerland with offices in Zurich, Boston, Warsaw, London, Singapore, Tokyo, and Tampere. Our market-leading smart data capture technology enables businesses to use any standard mobile phone to extract data from barcodes, ID documents, text, and objects. To see our software in action, check out our videos. The barcode decoding team at Scandit builds cutting edge decoding solutions. Our mission is to replace every laser scanner in the world with a Scandit powered mobile app.

TAMPERE, Finland--(BUSINESS WIRE)--Tampere, one of Finland's largest cities, is the first in Europe to introduce the Liveable Well-Being City indicators, which Japan uses to measure well-being factors from the perspective of residents in its 27 cities. The indicators will provide important information to support knowledge management on the state of the urban environment, the quality of services and the well-being of citizens. The co-operation between Tampere and Japan will start with the application of the indicators developed in co-operation between Smart City Institute Japan and several research institutes and universities. The model utilises both objective and subjective data collected from urban residents to improve well-being and streamline everyday life. The data is an important foundation for knowledge management: it enables cities to identify their success points and development needs from the residents' perspective.

Scandit is a high-growth tech scaleup from Switzerland with offices in Zurich, Boston, Warsaw, London and Tampere. Our technology for recognizing any barcode with any standard mobile phone is leading in the market today. To see our software in action, check out our videos. We are now looking for a new colleague to join our passionate team of computer vision engineers and help us make the next steps. Together with the other team members, you will be responsible for further improving our scanning performance and making it work in even more challenging conditions by applying and optimizing computer vision and deep learning algorithms.

A self-driving service has begun in Finland to test autonomous vehicles in cold weather conditions including snow. Sensible 4's service has started in Tampere, Finland, with two Toyota Proaces using the company's autonomous technology to transport locals as a last-mile service to the tramline. The pilot is part of Tampere's goal of smart city development. "Self-driving cars are an incredible opportunity for us to build a smooth, sustainable and smart city," said Anna-Kaisa Ikonen, mayor of Tampere. "In the future, autonomous vehicles can complement public transport in many ways, for example in tram feeder traffic. The service trial will give us a lot more information about this, and hopefully, many passengers will get an exciting car ride experience."

Researchers at Tampere University have successfully used artificial intelligence to predict nonlinear dynamics that take place when ultrashort light pulses interact with matter. This novel solution can be used for efficient and fast numerical modeling, for example, in imaging, manufacturing and surgery. The findings were published in the prestigious Nature Machine Intelligence journal. Artificial intelligence can distinguish different types of laser pulse propagation, just as it recognizes subtle differences of expression in facial recognition. The newly found solution can make it simpler to design experiments in fundamental research and will allow algorithms to be embedded in the next generation of laser systems to ensure real-time optimization.

BEGIN ARTICLE PREVIEW: According to a new study by Tampere University in Finland, making eye contact with a robot may have the same effect on people as eye contact with another person. The results predict that interaction between humans and humanoid robots will be surprisingly smooth. With the rapid progress in robotics, it is anticipated that people will increasingly interact with so called social robots in the future. Despite the artificiality of robots, people seem to react to them socially and ascribe humane attributes to them. For instance, people may perceive different qualities – such as knowledgeability, sociability, and likeability – in robots based on how they look and/or behave. Previous surveys have been able to shed light on people’s perceptions of social robots and their characteristics, but the very central question of what kind of automatic reactions social robots evoke in us humans has remained unanswered. Does interacting wi

A Finnish soldier stands in front of a seized BA-10 armored vehicle. In a new international cross disciplinary study, researchers have used artificial intelligence to analyse large amounts of historical photos from WW2. Among other things, the study shows that artificial intelligence can recognise the identity of photographers based on the content of photos taken by them. Artificial Intelligence (AI) is now able to identify photographers based on the content of images they've taken. This is the conclusion of a new study at AU Engineering, Aarhus University, where, in collaboration with Tampere University and the Finnish Environment Institute, researchers have used state-of-the-art artificial intelligence to trawl through photographs taken by 23 well-known Finnish photographers during the Second World War.