Articles tagged with Algorithms
Scientists have discovered biomarkers predicting chronological and physiological age in nematode worms, with implications for human anti-aging therapies. The study's findings, published in Aging Cell, suggest that examining biomarkers over time can provide a scientific baseline for clinical trials.
A team of Carnegie Mellon researchers has developed a new computational model that sheds light on the brain's processing of natural scenes. The model analyzes patterns in images and statistically characterizes them to determine which patterns are most likely associated with each other, enabling the brain to make sense of visual stimuli.
A new computer program trains itself to predict genes in fungal DNA sequences, improving accuracy and efficiency. The program uses a probabilistic mathematical model to pinpoint boundaries between coding and non-coding sequences.
Researchers from Michigan Tech and U. Michigan develop innovative quantitative analysis to distinguish fibromyalgia patients from healthy controls, suggesting potential clinical relevance in sleep stage dynamics. The study's findings may lead to improved assessments and reduced costs for sleep studies.
Computer scientists develop algorithm to accurately capture hairstyle shape and appearance using multiple cameras and light sources. The method enables photo-realistic images of hairstyles from any angle, creating realistic highlights and animations.
Researchers developed an algorithm that finds symmetries in equations, speeding up solutions to fundamental computer science problems. The new method can capture millions of symmetries in under a half-second, whereas previous methods took days or minutes.
A team of UC San Diego computer scientists has developed a groundbreaking algorithm for 3D reconstruction from 2-D images, solving the long-standing problem of autocalibration. This technology has vast potential in various applications, including virtual product showcases and augmented-reality walkthroughs.
Researchers developed a new approach to image enhancement using PSO algorithm, which intelligently boosts contrast and detail in an image. The method outperforms existing approaches in terms of computational time and objective evaluation, making it suitable for various applications such as CCTV images and lower quality camera photos.
A Carnegie Mellon study identifies specific brain regions activated by familiar objects, such as tools and dwellings. The researchers used machine learning algorithms to extract patterns from brain activation scans, revealing that different brains exhibit common patterns for representing the same object.
Researchers from Carnegie Mellon and Pitt describe a mechanism called dynamic connectivity, where neuronal circuits are rewired in response to specific patterns of stimuli. This process allows for more keenly sensed stimuli, such as recognizing scents, by filtering out noise and enhancing contrast.
A versatile algorithm called Cascades, developed by Carnegie Mellon researchers, identifies the best 100 blogs to read for early access to news. The algorithm also helps design efficient sensor networks in water supply systems by balancing cost and information collection.
Researchers at MIT have created an algorithm to convert brain signals into action in patients with paralysis or amputations, unifying disparate approaches to neural prosthetic devices. The technique provides a common framework for various measurement techniques and brain regions.
Computer scientists at UC San Diego create a new algorithm to generate annotated Internet router graphs, mimicking key features of the Internet. The technique allows researchers to experiment with different network topologies and test the sensitivity of various techniques.
Researchers at UCSD have designed a new algorithm that enables distributed rate limiting to enforce global bandwidth rate limits and dynamically shift allocations based on current network demand. The flow proportional share algorithm uses TCP to estimate bandwidth demand, providing fairness and practicality for deployment nationwide.
Scientists have developed algorithms to enable the 19 individual mirrors of NASA's James Webb Space Telescope to function as one telescope, allowing for sharper images and detection of distant galaxies. The 'Wavefront Sensing and Controls' system was tested successfully on a scale model and through computer simulations.
Researchers at the University of Washington developed software that allows for real-time visualization of air flow around speeding cars, creating a new effect for racing coverage. The technology uses Navier-Stokes equations to simulate complex systems quickly, enabling interactive simulations in video games and other applications.
A research team led by Dr. Benoit Coulombe has developed a powerful proteomics approach to infer putative functions of previously uncharacterized proteins by identifying their interaction partners. The study reveals an intricate network of protein interactions that connect together 436 different proteins.
A new algorithm for personalized ovarian stimulation therapy has been developed, demonstrating improved pregnancy rates in women undergoing fertility treatment. The formula, based on four easily measured patient characteristics, was tested in a prospective clinical study involving 161 patients.
A study from Colorado State University reveals that circadian rhythms regulate the function of all genes in mammals, influencing metabolism and health. Researchers analyzed data from thousands of genes using advanced algorithms to identify patterns of oscillation.
A new algorithm developed by Carnegie Mellon University researchers can create matches for three- and four-way kidney exchanges, increasing the efficiency of kidney exchanges. The algorithm has already been used by the Alliance for Paired Donation, a kidney exchange program, to identify potential transplants and improve transplant rates.
Dr. Andrew Stuart was awarded the 2007 SIAM Activity Group on Dynamical Systems J.D. Crawford Prize for his work on stochastic differential equations and their applications in physical models and Kalman-Bucy filters. The prize recognizes his outstanding contributions to the fields of stochastic ordinary and partial differential equations.
Ron Fedkiw's work on physically based simulation has improved realism in feature films, such as Poseidon and Pirates of the Caribbean: Dead Man's Chest. He designed new algorithms to simulate complex phenomena like water and fire, enabling unprecedented special effects.
Researchers at Virginia Tech have developed models and algorithms that enable the simulation of cell division using the university's System X supercomputer. By characterizing protein interactions regulating the cell cycle, they aim to understand reproduction in human cells and combat cancer, tissue regeneration, and pathogens.
A new system uses machine-learning methods to identify authors based on similar names, affiliations, and publication data, achieving 90.6% accuracy in a large-scale test. The algorithm will be integrated into the next generation of CiteSeer, the largest academic search engine.
A recent UCSD graduate has won an award for his work on human functional brain imaging, specifically analyzing competing Bayesian approaches for source localization. His research may lead to improvements in existing algorithms used in magnetoencephalography (MEG) and electroencephalography (EEG) techniques.
Mathematicians Brams, Jones, and Klamler describe a new method for cutting a cake called SP (Surplus Procedure), which ensures both parties feel they get approximately 65% of what they want. The article discusses potential uses of this method in dispute resolution and land division, and highlights its strategy-proof nature.
Stevens professor Rustam Stolkin has published a paper in the Institute of Physics Publishing's journal, Measurement Science and Technology. He and his collaborators used a robot arm to film video sequences, which were then used to test and validate robotic vision algorithms.
Researchers at Cardiff University developed an innovative algorithm inspired by honey bees' waggle dance to maximize results in manufacturing processes. The Bees Algorithm enables companies to efficiently adjust basic elements of their operations, resulting in significant cost savings.
A new mathematical method provides a better way to analyze noise by visualizing areas with no sound. Researchers credit this approach for its ability to tease out specific sounds from complex white noise.
The recipients of the 2006 Lagrange Prize are recognized for their groundbreaking papers on nonlinear programming without a penalty function and global convergence of a filter-SQP algorithm. These works introduced the filter idea, which has led to the development of effective nonlinear optimization codes.
Dr. Éva Tardos received the George B. Dantzig Prize for her groundbreaking work on network-flow algorithms, approximation algorithms, and combinatorial auctions. Her research focuses on efficient methods for solving optimization problems in graphs and networks.
A Florida State University researcher is creating unmanned ground vehicles to patrol areas without putting soldiers in harm's way. The Center for Intelligent Systems, Control, and Robotics is also working on algorithms that enable autonomous devices, such as wheelchairs and self-parking cars.
Researchers used a technique to analyze political book sales and blog networks, finding distinct communities and cohesion within groups. The algorithm identified left- and right-wing book groups and blogs, with rare connections between them, suggesting polarization and factional strength.
Indiana University researchers have created an Inauthentic Paper Detector (IPD) that uses compression algorithms to identify and distinguish between meaningful and meaningless technical texts. The system was inspired by a 2004 prank where MIT students submitted fake research papers, which were accepted without review.
Researchers develop two mathematical tools to analyze and optimize tensegrity systems in various applications. The optimization algorithm helps maximize strength while minimizing weight, leading to potential breakthroughs in bridge, building, and aircraft design.
Computer science has a profound impact on various scientific fields, including biology and physics. Chazelle emphasizes the importance of understanding algorithms in capturing complex realities, rather than traditional mathematical formulas.
A new algorithm called Automatic Distillation of Structure (ADIOS) has been developed to learn complex patterns in raw texts, including transcripts of parents' speech directed at young children. The algorithm can generate grammatical new sentences and prove useful in fields like bioinformatics.
Researchers from the California Institute, led by Professor Henrik Wann Jensen, unveiled innovative computer graphics techniques at SIGGRAPH. Their work includes a new method for real-time relighting of scenes illuminated by local light sources and an efficient technique to account for diffusion in multi-layered translucent materials.
The Common Message Authentication Code (CMAC) is a new authentication mechanism that uses block ciphers to verify the integrity of digital data. Developed by Japanese scientists Tetsu Iwata and Kaoru Kurosawa, CMAC is part of NIST's ongoing effort to update block cipher-based algorithms.
Artificial tactile sensors are being developed to mimic human fingers, providing detailed information on object shape and texture. The new technology could enable robots to handle delicate objects with increased precision and force control.
A study by Purdue University researchers found that pi's randomness is acceptable for data encryption and physics problems, but not always the best. Some commercially available random number generators outperformed pi in certain tests, suggesting that the quality of the algorithm used can impact randomness.
A national matching program for kidney donors and recipients can significantly increase the number of transplants, improve match quality and survival rates, while reducing travel costs.
A new algorithm could significantly improve transplant matches for patients with end-stage kidney disease, with a national program resulting in 47.7% more transplants and better graft survival rates compared to regional programs. The study also found that highly sensitized patients would benefit six-fold from the optimized algorithm.
Researchers from the University of Toronto developed a new method for predicting mammalian gene function by analyzing RNA expression patterns. They used a support vector machine algorithm to analyze over 40,000 known mouse mRNAs and predicted functions for thousands of genes, with high accuracy.
A team of researchers has discovered that microRNA miR-375 regulates insulin secretion, opening up new avenues for understanding and treating diabetes. The study's findings define a biological function for a mammalian microRNA gene and highlight the importance of collaboration between computation and experiment in modern biology.
Researchers have developed a mathematical algorithm called TANGO that can predict the likelihood of proteins sticking together incorrectly. This could lead to new diagnostic techniques for diseases caused by misfolded proteins, such as Alzheimer's and Parkinson's, and more efficient production of therapeutic proteins.
A Stanford researcher has devised a method to identify potential drug compounds using a network of over 150,000 home computers and innovative algorithms. The method accurately predicts how well molecules will bind to a given protein, which is crucial in drug development.
The three-year funding supports a joint effort to apply Multiple Dirichlet Series to analytic number theory, a central area of modern mathematics. This could lead to new insights into long-standing problems in number theory.
A study found that enzymes in plant cells can produce different products based on their location within the cell. The research, conducted by Brookhaven National Laboratory scientists, suggests that modifying an address signal on these enzymes could change their product output.
Researchers found that depression is often associated with an underlying autoimmune process affecting the thyroid gland. The study used thyroid function indicators to predict patients' responsiveness to antidepressants, achieving an almost 90% success rate.
Researchers developed an algorithm, Q5, using PCA and LDA to differentiate between healthy and diseased blood samples. The algorithm achieved virtually 100% accuracy for ovarian cancer and approximately 95% accuracy for prostate cancer.
Researchers at the University of Illinois at Urbana-Champaign have developed a geometric cluster algorithm that accelerates simulations of complex fluids. The new method can efficiently capture the motions of particles of different sizes, resolving a long-standing challenge in fluid simulation.
The ADOPT-A trial demonstrates the effectiveness of the AF Suppression algorithm in reducing symptomatic atrial fibrillation (AF) burden. The study found a significant 25% reduction in symptomatic AF episodes in patients using the algorithm compared to those with standard pacemaker indications.
Engineers at Ohio State University have developed a new software algorithm that models translucent objects and fluids to create soft, realistic shadows. The algorithm, called splatting, uses volume elements and 2D footprints to generate accurate shadows with minimal data storage requirements.
The University of California, San Diego (UCSD) has received a $600,000 grant from the Technical Support Working Group (TSWG) to develop advanced video surveillance systems for public safety. The project aims to improve the ability to detect and track potential terrorists using 'smart' cameras that can adapt to various lighting conditions.
A Stanford team has developed three techniques to speed up computing Google-style Web rankings, with speeds of up to five times faster than current methods. The techniques, including extrapolation, BlockRank, and Adaptive PageRank, can reduce computation time by 50-300% in realistic conditions.
A new method, KL clustering, has been identified as more effective than hierarchical clustering in separating gene expression data into dense clusters. The approach uses a novel measure of similarity to create well-separated clusters, offering insights into gene-gene interactions and biological processes.
Arjun Heimsath and Hany Farid developed a new method to create 3D models of remote regions using 2D photographs, making it easier for researchers to predict landslides and erosion rates. The technique has limitations, such as requiring clear images of the ground surface and a good point of view.
The new software tool analyzes engine models and extracts information on mechanically sound designs, enabling faster prediction of jet engine performance. By using an optimization algorithm, the tool calculates worst-case vibration levels, allowing engineers to determine the reliability of their designs quickly.
Scientists from the University of Minnesota and Duke University developed computer techniques that can automate image inpainting, restoring lost regions with neighboring available information. This technology has applications in surveillance images, enabling faster recovery of lost information and potential super resolution.