Articles tagged with Data Compression
Landsat 10 will process up to 1.8 gigabits of compressed data per second, capturing detailed images of the Earth's surface with unmatched radiometric precision. SwRI is developing control technology and operational simulators to regulate instrument temperature and position camera mirrors.
Researchers developed a new approach to compressing X-ray imaging data in real time, achieving compression ratios exceeding 8,000 times. This method operates directly on high-throughput data streams and preserves scientific information, enabling real-time operation at high data rates.
A University of Houston professor has found that tree-like thin films release heat at least three times better than traditional methods, enabling more efficient cooling in AI data centers. The discovery demonstrates the power of physics-aware AI design for validating high-impact cooling solutions.
Researchers have demonstrated altermagnetism in RuO₂ thin films, a promising new magnetic material for high-speed, high-density memory devices. The discovery overcomes limitations of conventional ferromagnets and has the potential to enable more energy-efficient information processing.
A team of researchers developed a reliable method to create donut-like, topologically rich spin textures called skyrmion bags in thin ferromagnetic films. The success rate of generating such textures using single laser pulses is significantly higher than magnetic-field-driven approaches.
The Los Angeles Rams have partnered with the American Heart Association to bring lifesaving CPR training to 22 local schools. The initiative aims to enhance community preparedness for cardiac emergencies. By providing resources and education, the partnership seeks to increase the number of people confident in performing CPR.
The Off the Field National Football League Wives Association partnered with the American Heart Association and other organizations to promote water safety skills among children. The event, held in New Orleans, provided Hands-Only CPR and automated external defibrillator education.
The American Heart Association and Arizona Cardinals partnered with 12 local schools for CPR and AED training, aiming to improve cardiac emergency outcomes. The training equipped schools with lifesaving skills and resources, increasing the community's capacity to respond in cardiac emergencies.
New algorithm CALDERA enables leaner LLMs with improved performance, reducing costs, energy consumption and privacy risks. This allows organizations to adapt models to their specific needs without sharing sensitive data, enhancing user privacy.
Research highlights that 911 telecommunicators play a critical role in increasing the chances of receiving bystander CPR for women, who are less likely to receive this lifesaving treatment. The study's findings support the importance of community emergency response and advocate for reducing known sex disparities.
The New York Jets and American Heart Association trained representatives from 12 local schools in cardiopulmonary resuscitation (CPR) and automated external defibrillator (AED) techniques. This partnership aims to improve cardiac emergency outcomes and increase the chances of survival for those experiencing cardiac arrest.
The Oklahoma State University men's basketball team participated in an American Heart Association Hands-Only CPR training to learn the correct rate and depth of CPR compressions. This event supports the Nation of Lifesavers movement, which aims to double survival rates from sudden cardiac arrest by 2030.
A nationwide cohort study revealed a higher risk of placental problems, premature births, and severe bleeding in subsequent deliveries following uterine artery embolization. Babies born to mothers who underwent UAE also had a higher chance of major birth defects, particularly heart problems.
A novel approach to overcome limitations of traditional methods, NeuPh uses local conditional neural fields to reconstruct high-resolution phase information from low-resolution measurements. It provides robust resolution enhancement and outperforms existing models in accuracy.
Researchers developed a real-time stream-based data compression technology that automatically detects frequently occurring data patterns and compresses them to minimize data volume. This innovation enables high-speed, compact data compression modules in hardware without additional processors or memory.
A new study from the University of Tsukuba introduces an algorithm that determines the application ratio of various compression methods for minimizing data amount in CNNs. This leads to a 28 times smaller model and 76 times faster computation compared to previous models.
Researchers from Shibaura Institute of Technology develop new methodology to accurately simulate soil behavior in rigid state, leveraging MSP method and Bingham fluid biviscosity model. The study highlights the impact of parameters on simulation accuracy and computational costs.
A global study has identified evidence-based approaches to prevent breast cancer-related arm lymphoedema (BCRAL) by addressing risk factors and implementing surveillance programs. The research provides a clinical guide for healthcare teams worldwide to adopt a proactive approach in preventing this irreversible complication.
A team at Peking University developed an analog in-memory computing module for one-step matrix-matrix-vector multiplication, solving compressed sensing recovery in real-time. The circuit outperforms digital approaches and has been demonstrated to recover various types of signals and images.
A team led by Dr. Zixiang Xiong at Texas A&M University aims to understand the fundamental limits of learned source coding, a machine learning-based data compression method. They hope to develop more powerful compression methods for efficient use of wireless communication and less energy consumption by mobile devices.
Researchers developed a new spectropolarimetric imaging technique called DIP-SP, which integrates a passive polarization modulator into an imaging spectrometer. This approach enables high-dimensional information capture from incomplete measurements and significantly improves image quality.
Researchers develop innovative data compression scheme to facilitate multispeckle diffuse correlation spectroscopy with high pixel resolutions, enabling non-invasive measurement of brain blood flow. The scheme uses field-programmable gate array compression to alleviate computational burdens and expand the use of SPAD cameras in biomedi...
Researchers identify potential application of quantum compression in edge computing, which could save storage space and network bandwidth. Quantum compression, a new concept, is being explored as an enabling tool for edge applications, with classical techniques compared to quantum approaches.
A team of researchers has created a new method for fabricating nanodevices by shrinking hydrogels to create 3D patterns. This technique uses ultrafast two-photon lithography and can produce high-resolution patterns up to 13 times larger than the original size, enabling the creation of complex nanostructures.
FeRh, a metal with antiferromagnetic and ferromagnetic phases, has its phase transition kinetics measured using ultrafast techniques. The study reveals new insights into the ultrafast dynamics of magnetic materials.
A UVA researcher has earned a prestigious NSF CAREER award to develop new models and data compression algorithms that will make the storage and analysis of large data sequences more efficient and accurate. The goal is to tackle the challenges of data storage capacity, particularly for genomic data.
A study found that the brain uses data compression to eliminate irrelevant information and adopt temporary 'tunnel vision' for optimal performance. This principle extends beyond sensory processing to cognitive functions.
Researchers developed a methodology to compress extensive genetic data libraries, reducing their size while preserving essential information.
A new technique uses compression to reduce data transmission size, allowing for efficient federated learning on wireless devices. The approach has been shown to condense data packets by up to 99%, making it suitable for areas with limited bandwidth.
Researchers have developed a novel data storage method using mixtures of fluorescent dyes, which can store binary information at high density with fast read/write speeds. The technique encodes sequences of 0s and 1s into dye molecules, allowing for the storage of digital information for thousands of years or longer.
A Texas A&M team led by Dr. Byung-Jun Yoon has received $2.4 million to develop new computational techniques for reducing the size of large scientific data sets. The goal is to preserve quantities of interest while minimizing data storage and processing needs.
West Virginia University engineers are working on a $750,000 award from NASA to improve data transfer efficiency during space exploration. The team is developing AI-based algorithms that can compress data while retaining maximum information content, which could enable more efficient NASA missions and sustain Earth and solar observations.
Researchers at MIT have developed a novel data-compression technique that leverages object-based compression to reduce memory usage and improve performance. The 'Zippads' technique compresses objects across the memory hierarchy, reducing memory consumption by half and improving computation speeds.
Joachim Weickert's new technique uses a phenomenon from the heat equation to store only a few important pixels, achieving excellent compression ratios and potentially surpassing established methods like JPEG. The challenge now is to determine the ideal combination of pixels for storage while developing more efficient algorithms.
A new open-source software will put digitized biomedical data at the fingertips of healthcare professionals, enabling quicker second opinions and diagnoses. The software compresses images up to 100 times without losing detail or resolution.
New grant funds development of efficient genomic data compression software to handle large volumes of genomic data, addressing challenges in data storage and transfer. The project aims to identify commonalities in compression strategies across different types of genomic data.
A new data compression method, inspired by physics and the arts, has been developed to reduce big-data bottlenecks. The technique, called anamorphic stretch transform (AST), reshapes data in a way that preserves sharp features while compressing coarse ones.
Researchers are creating a multimedia system that uses multiple 3-D cameras to create avatars of humans in two different places, allowing them to interact. The system could enable physical therapists to work with patients remotely and receive real-time feedback on their exercises.
Scientists have developed a microscope that utilizes compression sensing to gather molecular vibration information with increased resolution and reduced time. The new method has been applied to sum frequency generation microscopes, resulting in images with 16 times more pixel density than traditional scanning techniques.
Researchers aim to speed up data processing applications such as internet searching, data compression, and image recognition. They plan to utilize the spin degree of freedom to store and process information in a single chip.
A Princeton scientist has recast two well-known math problems as physics questions, providing new tools for solving challenges in data compression, gravitational waves, and more. The reformulation offers insights into the role of randomness and disorder.
University of Idaho engineers have developed unique new technology that will be used in NASA's Landsat Data Continuity Mission and Magnetospheric Multiscale Mission. The technology includes advanced data compression and channel coder algorithms, increasing science data return and protecting data fidelity.
A new wireless sensor network system will be developed to monitor bridge safety and performance in real-time, providing critical information for emergency responders. This system uses advanced algorithms and data compression techniques to minimize data transfer time, ensuring that vital data is transmitted quickly and efficiently.
Compressing coronary angiograms for delivery over telephone or computer lines can lead to diagnostic errors, according to researchers. Image quality is progressively lost with increasing compression, making it difficult for clinicians to detect subtle diagnostic features.
Researchers at Purdue University have developed an invisible digital watermark to protect copyrights for images on the web. The technique, tailored for Web-based imaging, embeds the watermark in pixels, allowing for verification and detection of unauthorized copies.