Articles tagged with Signal Processing
The researchers have demonstrated significant improvements for chip-based sensing devices that can detect or analyze substances across widely varying concentrations. They developed signal-processing techniques that enable seamless fluorescence detection of a mixture of nanobeads in concentrations across eight orders of magnitude.
Researchers found that mice with Alzheimer's Disease lacked TLR4 in their central nervous system, leading to reduced joint inflammation and immune cell response. This study suggests potential therapeutic targets for chronic pain treatment and raises awareness about underreported pain in AD patients.
A research team from Taiwan has found a way to massively speed up aerial image simulations using wavelength scaling and fast Fourier transformation. The new algorithm improves computation speed by 4000-5000 times while maintaining only a slight intensity deviation.
Researchers have developed a groundbreaking photonic integrated circuit chip that combines light source, modulator, photodiode, waveguide, and Y-branch splitter on a single substrate. The GaN-on-silicon platform reduces fabrication complexity and cost, enabling compact and high-performing devices.
A study by the Helmholtz-Zentrum Dresden-Rossendorf team demonstrates efficient conversion of high-frequency signals into visible light using graphene-based materials. The mechanism involves a thermal radiation process, and the conversion is ultrafast and tunable.
Researchers created a small device that captures, processes, and stores visual information in a similar way to humans. This technology uses analog processing, reducing energy consumption and enhancing performance, with potential applications in bionic vision, autonomous operations, and advanced forensics.
Researchers have created a 19-core optical fiber with a standard cladding diameter, achieving a record transmission capacity of 1.7 petabits per second over 63.5 km. This design uses randomly coupled multi-core fibers and MIMO digital signal processing to minimize power consumption.
Researchers at Mount Sinai have discovered a previously unknown way in which the brain and immune system interact in multiple sclerosis. They found that the inflammatory protein interleukin-3 (IL-3) coordinates this communication, inciting the recruitment of immune cells to the brain and exacerbating brain inflammation.
A deep neural network developed by researchers at the University of California - Santa Cruz has been shown to accurately classify particle signals with 99.8% accuracy in real-time. The system can identify weak or noisy signals and pinpoint their source, making it suitable for point-of-care applications.
Researchers at Princeton University developed a new device called mmWall that can steer millimeter-wave (mmWave) signals to reach all corners of a large room. The device uses an accordion-like array of panels to reflect and refract radio waves, allowing for efficient beam steering and alignment with transmitters and receivers.
Researchers at UTHealth Houston identified two brain networks involved in reading, working together to integrate word meanings. The study used electroencephalography recordings from patients with epilepsy to measure neural activity while reading complex sentences.
Researchers at the University of Washington developed GlucoScreen, a new system that leverages smartphone capacitive touch sensing to measure blood glucose levels. The system's accuracy is comparable to standard glucometer testing, making it potentially less costly and more accessible for widespread screening.
A new method using brain signal processing has been developed to categorize different types of depression. The study achieved a 91% accuracy rate in detecting anxious and non-anxious depression, showing promise for improved diagnosis and treatment.
Researchers at Pohang University of Science & Technology have created a high-performance AI semiconductor device using IGZO, achieving over 98% accuracy in handwritten data classification. The new device's design enables efficient linear and symmetric programming, making it suitable for large-scale AI applications.
The Indian Institute of Science researchers developed a full-duplex antenna system that cancels out self-interference, enabling faster and more efficient data transfer. The compact design eliminates the need for bulky components, making it suitable for integration into devices.
Researchers achieved optical switching of a light signal at attosecond speeds, exceeding data transfer speeds by 1 million times. This breakthrough enables the development of ultrafast optical electronics and could increase data processing speed in long-distance communications.
MIT researchers have developed a receiver chip that targets and blocks unwanted signals without hurting device performance. The chip uses a mixer-first architecture and block digital filtering to remove harmonic interference, enabling it to handle high-power signals effectively.
The NERVE Center has developed test methods and metrics for various robots, identifying limitations to improve systems. The center's success grew its research capabilities through partnerships with NIST and the U.S. Army.
Researchers from New York Institute of Technology have made significant findings on how the sense of smell is impacted in individuals with autism. The study analyzed a mouse model of autism and found that scent processing was impaired at a later step, after signals were processed at the olfactory bulb input.
Researchers at Aston University have discovered a new approach to process LDF light signals, allowing for more precise measurement of blood flow in specific areas of the vascular bed. This innovation has shown significant improvement in diagnostic accuracy for detecting microvascular changes in patients with type 2 diabetes and age-spe...
Engineers at Tokyo Institute of Technology have developed a technique to support the classification performance of neural networks operating on sensor time series by feeding recorded signals into elementary non-linear dynamical systems. This approach increases the classification performance by augmenting the data through additional tim...
Researchers have discovered a biological pathway that governs the life and death of stem cells, which may lead to new treatments for cancer and regenerative therapies. By manipulating cell signaling, scientists can normalize the creation of new cells, preventing excessive growth and ensuring proper tissue regeneration.
Jay W. McDaniel, assistant professor at the University of Oklahoma, receives a CAREER Award to develop a custom UAV-based radar suite for measuring snow depth and distribution. The project aims to improve understanding of snow characteristics and their impact on thermal balance between terrain and atmosphere.
Researchers discovered that ketamine increases background noise, impairing the function of thalamo-cortical neurons and affecting sensory perception. This finding may contribute to a better understanding of psychosis in schizophrenia.
Researchers developed an iEMG classifier framework for detecting myopathy and neuropathy, achieving high accuracy in three muscle types and low computational time. The study showed promise for real-time implementation, aiding clinicians in making quick and accurate diagnoses.
New signal-processing algorithms have been shown to help mitigate the impact of turbulence in free-space optical experiments. The researchers achieved record results using commercially available photonic lanterns and a spatial light modulator to emulate turbulence.
Researchers at Incheon National University have developed an IoT-enabled, real-time object detection system for autonomous vehicles. The YOLOv3-based model achieved high accuracy (>96%) in detecting 2D and 3D objects, outperforming other state-of-the-art detection models.
Scientists successfully transmit and switch 15-mode multiplexed signals over a 6.1 km long multi-mode fiber ring in Italy, demonstrating a new approach to increasing fiber network capacity. This achievement is significant for future communication systems beyond 5G.
Researchers found that SEUSS condensates rapidly form upon hyperosmotic stress, enabling Arabidopsis to tolerate salt and drought. Loss of SEU dramatically compromises stress-tolerance gene expression.
Researchers demonstrate world's first 55-mode transmission at 1.53 petabits per second, outperforming previous records by three times in spectral efficiency. The technology holds promise for future high-capacity backbone networks and the development of Beyond 5G infrastructure.
Kyusang Lee's new sensor system uses artificial intelligence to process different types of signals, mimicking human biology, and can detect viruses. The system meets challenges of data bottlenecks, energy consumption, and data protection, making it a breakthrough in the Internet of Things.
Researchers at Kyushu University counted electric charges in individual platinum nanoparticles down to the electron level, revealing net charge with high precision. This breakthrough enables better understanding and development of catalysts for breaking down pollutants.
The NTU-developed wind harvester generates a voltage of three volts at wind speeds as low as two meters per second, powering commercial sensor devices. The device can also store excess charge for extended periods in the absence of wind, serving as an alternative to smaller lithium-ion batteries.
Researchers developed an algorithm to decode brain scans and identify epilepsy types based on electrical signal patterns. The Cumulative Sharp Count and areas under spike and sharp curves were used as parameters to detect epilepsy, with high accuracy rates in blind validation studies.
Researchers at Queen Mary University of London have invented a new application of perovskites as single-crystal optical fibers with exceptional stability, efficiency, and durability. These high-performance fibers could revolutionize broadband delivery, improve medical imaging, and even enable solar-powered clothing.
Long-term monitoring data reveals previously undetected diurnal patterns in narwhal behavior, including changes in surface activity and diving patterns influenced by sea ice and squid migration. The study's method can be applied to assess the challenges faced by narwhals and other Arctic animals due to climate change.
Researchers from UMass Amherst have created a tiny sensor that can simultaneously measure electrical and mechanical cellular responses in cardiac tissue. This breakthrough device has the potential to lead-edge applications in cardiac-disease experiments and improve health monitoring for cardiac disease studies.
Researchers developed a wireless system called Contactless Moisture Estimation (CoMEt) that estimates soil moisture in agricultural fields at multiple depths using radio signals. CoMEt can assess soil moisture without requiring in-ground sensors, making it more cost-effective and convenient for farmers.
A team led by Professor Song Min Kim developed a system that can support concurrent communications for tens of millions of IoT devices using backscattering millimeter-level waves. The system offers internet connectivity on a mass scale to IoT devices at a low installation cost.
Researchers from Tokyo University of Science found that short PPG signals can be used to estimate dynamical properties like determinism, predictability, and complexity with good accuracy. However, shorter signals may not be sufficient for estimating divergence.
The new AI system uses associative learning to detect similarities in datasets, reducing processing time and computational cost. By leveraging optical parallel processing and light signals, the system can identify patterns and associations more efficiently than conventional machine learning algorithms.
Researchers at NICT developed an organic electro-optic polymer for visible light, significantly improving efficiency and miniaturization. The new modulator has lower absorption loss and higher electro-optic coefficient in visible light compared to conventional optical modulators.
By using the brain's visual response as feedback, researchers can reconstruct images of simple objects in real-time. The technique has potential applications in augmenting human capabilities and could one day be used to bring together human and artificial intelligence.
A new method allows for the separation of signals generated by mining activity from background seismic noise, enabling real-time monitoring of seismic events and structural integrity. This approach could be applied to various environments, including mines, volcanoes, and oil extraction sites.
A new robotic system, FuseBot, has been developed to efficiently retrieve buried objects in piles. The system uses radio frequency signals and computer vision to reason about the probable location and orientation of objects under the pile, enabling it to find more hidden items than a state-of-the-art robotics system in half the time.
Cong Shen earns CAREER award to develop 6G wireless communications systems supporting machine learning and AI technologies. His research aims to boost the performance of machine-learning models driving the Internet of Things while protecting data privacy.
The Collaborative Research Centre Hearing Acoustics is developing smart hearing aids that use artificial intelligence to adjust to different environments. The project, which aims to create more adaptable hearing devices, has received $8.1 million in funding for another four years.
A new distributed learning technique, GD-SEC, reduces communication requirements in wireless architecture, improving efficiency and reducing computational cost. The method employs data compression to transmit only meaningful, usable data, enhancing the impact of machine learning while minimizing its limitations.
Researchers from Rice University and Brown University demonstrate a DIY method to hack 6G frequency using office paper, inkjet printer, metallic foil transfer, and laminator. The 'metasurface-in-the-middle' attack can redirect part of a high-frequency transmission between two users, threatening the security of next-gen wireless networks.
Researchers create a new method for detecting diagnostic markers of epilepsy using EEG and MEG, enabling precise localisation of epileptogenic cortical structures. The biomimetic algorithm improves the effectiveness of neurosurgical interventions for epilepsy patients with resistant treatment.
Researchers from Tokyo University of Science have designed a tunable physical reservoir device based on dielectric relaxation at an electrode-ionic liquid interface. The system can store and process analog signals, enabling real-time processing of signals in living environments.
Researchers used terahertz imaging to uncover a hidden inscription on a 16th-century lead funerary cross, revealing the Lord's Prayer. The technique allowed for non-destructive examination of the corrosion layer, enabling the team to restore and enhance images containing the text.
The conference features over 2,000 technical presentations, plenary speakers Dana Anderson, Hui Cao, Peter Delfyett, and Michal Lipson, and showcases market-ready technologies in lasers and photonics. Industry-leading companies demonstrate new products and technologies
Researchers integrated biological signals with gold-standard machine learning methods to create emotionally intelligent speech dialog systems. The study found that combining language information with biological signal information improved the AI's performance, making it comparable to human-like emotional recognition.
A study suggests that smartwatch heart rate measurement algorithms are less effective in people with darker skin tones due to increased melanin absorption. Researchers emphasize the need for diverse population inclusion and explore alternative light wavelengths for more accurate readings.
The newly developed KANPHOS database provides comprehensive information on kinase-associated protein phosphorylation, facilitating research into neural signaling pathways. The database contains information on phosphoproteins, phosphorylation sites, and participant kinases, allowing for searches based on various parameters.
Australian researchers have mapped the visual systems of hoverflies to detect drones' acoustic signatures, showing a 30-49% improvement in detection rates compared to traditional methods. The technology has potential applications for aviation safety and combatting IED-carrying drones.
Researchers have identified an important element for electrical communication in plants: the ion channel TPC1. The study reveals how this channel is switched on and off, controlling electrical excitation in plant cells. Understanding TPC1-dependent processes can help better understand similar mechanisms in animal cells.
A new study has discovered that as brains mature, the precise ways in which two key memory regions communicate make us better at forming lasting memories. The findings also suggest how brains learn to multitask with age, with slower oscillations in older participants and faster oscillations in younger ones.
Researchers at City University of Hong Kong have developed a novel droplet manipulation method called WRAP, which can transport micro-sized droplets using electromagnets or programmable electromagnetic fields. The method overcomes challenges in traditional magnetic actuation, such as contamination from added magnetic particles.