Research on computing hardware and its future. Covers quantum error-correction, cyber defense, novel materials, and AI frameworks.
A new e-nose prototype, NOS.E, can distinguish between six whiskies by brand names, regions, and styles in under four minutes, with 100% accuracy for region detection and 96.15% for brand name identification. The technology has applications beyond whisky, including counterfeiting detection in perfume and wine.
Behunin's project targets challenges in practical quantum computing by controlling noise and its impact on qubits. By manipulating sound waves, he hopes to quiet the noise that corrupts information stored in quantum computers.
A new brain-computer interface device has been found safe in a small study of people with ALS, allowing participants to communicate through text and perform daily tasks. Researchers have also developed a machine-learning decoder that enables independent computer control without eye tracking.
A team of scientists created a powerful new method for generating protein drugs by designing molecules that can target important proteins in the body. The research yielded candidate medicines for cancer, diabetes, infection, inflammation, and beyond, offering a paradigm shift in drug development.
Scientists have discovered a speed limit for computer chips, with one petahertz being the maximum frequency for signal transmission. The research uses ultra-short laser pulses to create electrical currents in dielectric materials, allowing for faster data transmission.
Researchers at the University of Innsbruck have proposed a method to solve optimization problems using neutral atoms and four-qubit operations. The algorithm can be realized on existing quantum hardware by optimizing laser pulse durations in a feedback loop.
Scientists have achieved efficient quantum coupling between two distant magnetic devices, which can host magnons and exchange energy and information. This achievement may be useful for creating new quantum information technology devices.
Researchers from the University of Seville have conducted a groundbreaking experiment demonstrating quantum contextuality without loopholes. The study uses atomic ions to show that certain probabilities have a limit, contradicting previous findings.
Researchers developed a new reading method for SOT-RAMs that can nullify the readout disturbance, reducing it by at least 10 times. The method involves creating a bi-directional read path, cancelling out the disturbances produced by spin currents.
The MagTrack study successfully completed a collaboration between Georgia Tech and Brooks Rehabilitation, creating a user-ready version of the assistive technology. Participants showed improved performance in controlling their power wheelchairs and connected devices with ease and comfort.
A new study by University of Cologne researchers reveals that computer games can significantly boost educational success when used effectively in the classroom. The study found that personal characteristics of pre-service teachers play a crucial role in their intention to adopt digital game-based learning, with perceived effectiveness ...
Researchers at Texas A&M University develop new touchscreen technology that can simulate virtual shapes through temperature variation. The approach increases friction at the finger-device level, allowing for immersive and accurate touch experiences.
Researchers at HKUST and UChicago have designed the basic elements needed for logic operations using liquid crystals, paving the way for novel computing methods. The team controlled topological defects to perform operations like amplification and switching, opening the door to potential applications in robotics and sensing.
Researchers at Goethe University Frankfurt have grown crystals with rare-earth atoms that exhibit surprising fast magnetic properties. The team found that the strength of these reactions can be adjusted by choosing different atoms, opening up possibilities for optimizing spintronics components.
GIST researchers propose a new strategy for crime prevention using artificial intelligence, trained on a large-scale dataset of deviant incident reports and corresponding images. The model, called DevianceNet, can accurately classify and detect deviant places, making it a useful tool in urban safety development.
Researchers developed DAGguise, a scheme that shapes memory requests into a predefined pattern to prevent contention attacks and enable faster computation. The technique represents programs' memory access requests as a graph, where each request is stored in a node, and the edges are time dependencies between requests.
Researchers explore the intersection of technology, social sciences, and narratives to combat disinformation. Experts discuss how technical solutions can be coupled with social interventions to effectively address the issue.
Researchers analyzed 60 billion tweets to understand vaccine hesitancy on social media. They found that anti-vaxxer profiles often share links to YouTube videos and commercial sites selling alternative health products, highlighting the spread of misinformation in echo chambers.
Researchers developed a system using facial expressions to manipulate objects in virtual reality environments, outperforming handheld controllers in terms of immersion. The technique has potential applications for people with disabilities, including amputees and those with motor neurone disease, allowing hands-free interactions.
Researchers developed a novel method of measuring aortic growth, called vascular deformation mapping, which outperforms standard manual rating methods. The technique uses high-resolution CT imaging to calculate three-dimensional changes in the aortic wall, achieving an accuracy of less than 1 millimeter.
A Swedish research team developed a simple hydrocarbon molecule that changes form and becomes conductive when exposed to electric potential. This breakthrough could lead to the creation of miniature transistors and new mechanical systems at the single-molecule level.
A €16 million project, PhotonQ, is developing a photonic quantum processor to process qubits and reduce error rates. The processor will enable rapid scaling to relevant qubit numbers for practical applications.
A team of researchers from Ritsumeikan University developed an unprecedented stream cipher using chaos theory to create highly secure cryptographic systems. The new system is resistant to statistical attacks and eavesdropping, even against quantum computers, making it a promising solution for post-quantum era cryptosystems.
Researchers at OHSU are developing a new approach to scientific imaging to study the dynamic organization of cells by examining how tiny molecules make cells work. The W. M. Keck Foundation has awarded $1 million to develop a one-of-a-kind imaging and computational system.
A study by Michigan Medicine reveals that 25% of young American men experience both delivering and receiving technology-facilitated abuse. Healthcare providers should consider addressing this issue, as men who have mental health care visits are more likely to be involved in abusive relationships.
Cornell researchers have successfully trained various physical systems, including mechanical, optical, and electrical systems, to perform machine learning tasks. The developed training algorithm enables diverse systems to be chained together for efficient processing.
Researchers at the University of Bristol have reduced simulation time for an optical quantum computer from 600 million years to just a few months, achieving a one-billion-fold speedup. This breakthrough paves the way for future studies on quantum advantage and computational power.
Researchers developed an AI system that can analyze retinal scans to identify patients at high risk of a heart attack over the next year. The system uses deep learning techniques and achieves an accuracy of 70-80%, revolutionizing the way patients are screened for signs of heart disease.
A team of NTU Singapore scientists has developed a predictive computer programme using wearable technology data to detect depression risk. The programme, Ycogni model, achieves an accuracy of 80% in detecting individuals at high or low risk of depression.
A new approach uses reinforcement learning algorithm to help robotic knee mimic intact human knee in walking, achieving 100% success rate on even ground. The technology also adapts to uneven terrain and changes in walking pace, promising a more comfortable experience for prosthetic users.
Researchers developed a novel robotic replica of a human spine with an artificial disc implant and soft magnetic sensor array. The system can classify five different postures of the spine with 100% accuracy, providing physiologically relevant data before invasive surgeries.
Researchers have created a compact and affordable device for recording brain activity, offering research-grade signal quality and customizable configuration. The device has the potential to help people with epilepsy detect impending seizures and those with limited mobility regain control over their limbs.
A study by the University of Texas at Austin found that software development teams given greater autonomy are more productive and have higher customer satisfaction rates. The researchers tested 461 projects over 50 months and found a 39% increase in value added for autonomous teams compared to traditional teams.
The University of Surrey researchers have developed a method to generate up to 3.1% biaxial strain and 8.5% uniaxial strain in single-crystal silicon using ion implantation, which could lead to the development of germanium lasers and near-infrared sensors for smartphones.
A team of researchers has developed a new technique to embed single atoms in silicon wafers, mirroring methods used to build conventional devices. The technique creates large-scale patterns of controlled atoms that can be manipulated and read out, enabling the construction of large-scale quantum devices.
Researchers discovered a new method to control spin-lattice interaction with ultrashort terahertz pulses, potentially revolutionizing ultrafast data processing and storage. This breakthrough could address the growing energy demands of data storage centers.
Researchers developed a new hand gesture recognition algorithm that surpasses current methods in accuracy, complexity, and applicability. The algorithm combines adaptive hand type classification and a shortcut feature for efficient real-time recognition.
The University of Texas at El Paso has received a $4 million grant from the National Science Foundation and Department of Homeland Security to support highly qualified computer science students. The program aims to enhance the regional and national cybersecurity workforce with an emphasis on Hispanic and female students.
Scientists at Sandia National Labs invent a new yardstick for benchmarking performance of quantum computers. The mirror-circuit method is faster and more accurate than conventional tests, revealing the true potential and limitations of quantum processors.
A Curtin University study found that mobile devices helped families strengthen relationships and bond over online activities, such as video calls and games. However, some participants reported devices as a source of distraction, disrupting family interactions.
Researchers developed an algorithm to differentiate life-threatening gunshot events from non-life-threatening plastic bag explosion events. The study found that 75% of plastic bag pop sounds were misclassified as gunshot sounds, highlighting the need for a diverse dataset of similar sounds.
Researchers at Trinity College Dublin have developed mathematical equations explaining how individual randomness can give rise to synchronisation, applicable to systems like clocks, fireflies and metronomes. The findings provide a basis for new types of computer technology using light signals.
A new study by the University of Plymouth has demonstrated the potential of gait authentication to protect smartphones from cyber crime. The system achieved an average accuracy rate of around 85% in recognizing individuals' stride patterns, with rates rising to almost 90% when participants were walking normally and fast.
A new AI algorithm, APOLLO, accurately predicts microprocessor power consumption by analyzing just 100 signals out of millions, offering potential to improve efficiency and develop new processors. The technique has been validated on high-performance microprocessors and could help designers inform future chip design.
A recent study used computer vision algorithms to analyze nearly 9,400 Flickr photos taken along Colorado's Front Range, identifying preferred outdoor landscapes with moderate accuracy. The algorithm performed well for images of water, structures, and agricultural lands, but struggled with forests. Combining social media data with on-s...
Researchers at University of Helsinki have developed a new method to speed up calculations on quantum computers, reducing the number of measurements required and increasing efficiency. This breakthrough could lead to faster and more sustainable quantum computing.
A team of researchers, including those from Rensselaer Polytechnic Institute and the University of Washington, have developed a neural network that can predict protein shapes with high accuracy. The network was trained on random protein sequences and generated 2,000 new proteins, many of which were successfully produced in the lab.
A recent study by the University of Cincinnati found that tweens spent more time using media during the 2020 pandemic summer, highlighting the need to reassess notions of 'too much' screen time. The research suggests that media use can have both positive and negative effects on children's lives, with some finding connection with peers ...
Researchers at the University of Gothenburg have successfully combined a memory function with a calculation function in the same component, enabling more efficient technologies like mobile phones and self-driving cars. The discovery opens the way for brain-like computers that can perform tasks effectively and energy efficiently.
Researchers developed an algorithm predicting COVID-19 patient outcomes based on individual data, achieving high accuracy (over 90%) for up to ten days. This innovation enables hospitals to allocate staff and resources efficiently, potentially saving lives during future pandemic waves.
A new 'image analysis pipeline' called TDAExplore gives scientists rapid insight into how cells are changed by disease, using a combination of microscopy, topology, and artificial intelligence. This approach can provide objective information on cell changes, such as the movement of proteins like actin, even with limited training data.
The WVU-led Dolly Sods GPU cluster enables researchers to accelerate computational research in fields like drug development, interstellar phenomena, and biometrics. The cluster will facilitate the analysis of massive datasets and enable real-time processing of signals from satellites in space.
Researchers developed EDS-HAT, an AI-powered system combining machine learning and whole genome sequencing to detect clusters of similar infections in real-time. The system identified 99 clusters of infections and prevented potential transmissions in 65.7% of cases, saving the hospital $692,500.
Researchers at Penn State created a nanocomputing agent that controls protein function involved in cell movement and cancer metastasis. The logic gate, embedded in the focal adhesion kinase (FAK) protein, demonstrates ability to control conditional operations, introducing possibilities for precision therapeutics.
Researchers from Okayama University developed an AI-powered image classifier to simplify and speed up the task of image analysis in cell biology. The system achieved high detection accuracy for mitotic cells in plant species, demonstrating its potential for non-experts to use.
A team of researchers has developed a simple and efficient method of quantum encryption using single photons, which can detect any attempt to hack the message. The breakthrough brings us closer to securing our data against quantum computers' potential attacks.
Researchers trained an artificial intelligence algorithm to predict the next designer drugs before they are even on the market, allowing law enforcement agencies to identify and regulate new versions of dangerous psychoactive drugs. The model was tested against 196 new designer drugs and found nearly all were present in its generated set.
A team of Canadian researchers has successfully simulated baryons on a quantum computer, marking an important step towards more complex simulations. This breakthrough enables scientists to study neutron stars, the earliest moments of the universe, and the revolutionary potential of quantum computers.
Researchers developed AfriBERTa, a neural network model that achieves state-of-the-art results for low-resource African languages. The model works with 11 languages spoken by over 400 million people and requires only one gigabyte of data, compared to thousands for existing models.
A team of computer scientists has developed a secure identity verification method based on zero-knowledge proof, ensuring that information cannot be replicated by hackers. The new method uses two physically separated prover-verifier pairs to confirm identities, eliminating the possibility of collusion and increasing security.