Articles tagged with Algorithms
A new computational imaging method identifies letters printed on the first 9 pages of a stack of paper, demonstrating the feasibility of reading closed books. The MIT system exploits the unique properties of terahertz radiation to penetrate surfaces and analyze materials in thin layers.
A new study explores the potential use of artificial intelligence to analyze complete lung function tests and improve diagnosis accuracy. The algorithm simulates complex reasoning to provide a standardized and objective diagnosis, removing bias.
Researchers at MIT have developed programmable routers that can implement diverse traffic management schemes, improving network resilience. The new design allows for flexible traffic management without compromising operating speeds, enabling innovation and rapid prototyping.
A study published in the American Journal of Roentgenology suggests that nephron-sparing treatment for small renal masses can improve life expectancy in patients with mild or moderate chronic kidney disease. The study developed a framework for incorporating tumor imaging features and renal function into treatment selection, providing a...
Researchers have developed a cost-effective method using the Microsoft Kinect to evaluate gait abnormalities in multiple sclerosis patients. The device detects movement and computer algorithms quantify walking patterns, reducing human error. The technology shows promise for diagnosing gait pathology and tracking treatment effects.
Bernd Bickel's algorithm improves technical modelling of planar-rod structures for optimal stability and efficiency in manufacturing. The software has applications in art, wire sculptures, and rapid prototyping.
Researchers at University of California - San Diego create method to improve light interaction with small details called glints on surfaces, enabling accurate rendering of materials with metallic finishes and injection-molded plastics. The new algorithm is 100 times faster than current methods and can be used in animations.
A new character animation technique has been developed by Disney Research, eliminating unsightly artifacts that occur when bending joints in computer animations. The method uses pre-computed centers of rotation to calculate skin deformation, minimizing volume losses and bulging.
Biologists have developed an algorithm predicting protein cluster structure, enabling faster understanding of cellular functions and potential treatments. The new method is up to 100 times faster than previous methods, taking just 15 minutes to run on a personal computer.
The NIST Ballistics Toolmark Research Database provides a statistical foundation for reliably linking bullets to the guns that fired them. The database uses 3D topographic surface maps to analyze bullet markings, allowing researchers to quantify uncertainty and develop more accurate bullet-matching algorithms.
Researchers from Binghamton University and Stevens Institute of Technology found that smartwatches can crack private PINs with 80-percent accuracy on the first try. The study used data from embedded sensors in wearable devices to break codes without contextual information, highlighting security vulnerabilities in these devices.
Researchers tested facial recognition algorithms on a dataset of one million images from around the world and found that accuracy rates dropped significantly when confronted with more distractions. Google's FaceNet performed strongest, but other algorithms struggled to maintain high accuracy rates at scale.
A team of researchers has developed a method to identify different subtypes of neurons in the human brain, revealing unique characteristics that can lead to differences in cellular function. The study provides a unified framework to analyze individual neurons and could help diagnose and treat brain disorders.
Researchers from MIT's CSAIL present a new chip design called Swarm that makes parallel programs run many times faster and requires one-tenth the code. The chip has extra circuitry to prioritize tasks and handle synchronization between cores, making it easier for programmers to adapt sequential algorithms.
Researchers at North Carolina State University developed a new image segmentation technique that improves object identification and separation in images. The technique, called Consensus-Based Image Segmentation via Topological Persistence, aggregates data from multiple algorithms to create a new version of the image.
A new mathematical framework developed by Robert Saye accurately resolves intricate fluid dynamics near evolving interfaces, allowing for the study of complex phenomena like bubble aeration and propeller blade optimization. High-order methods outperform low-order methods in accuracy and computing power.
A new computer algorithm enables scientists to use satellite data to determine groundwater levels across larger areas than ever before. The technique, developed at Stanford University, could lead to better models of groundwater flow and monitoring in agricultural regions. The team was able to calculate surface deformations and groundwa...
Researchers developed an algorithm that can stitch together astronomical measurements from around the globe, producing the first images of black holes. The algorithm uses a technique called interferometry and preserves continuity in the image by using a mathematical model inspired by rubber sheets and plastic wrap.
Researchers found that 60% of Amazon sellers using algorithmic pricing have prices higher than the lowest price for a product. The study also revealed that algorithmic pricing leads to significant volatility in prices, with some products changing price over 8 times per day.
Two studies found that a high-sensitivity cardiac troponin I assay can accurately diagnose or rule out heart attacks in patients with chest pain. The tests identified 19% of patients as potentially suitable for immediate discharge and had high diagnostic performance in excluding heart attacks. A new algorithm using this test showed rap...
Researchers at Binghamton University have developed an algorithm using Singular Spectrum Analysis (SSA) to quickly detect and locate power grid faults, providing a promising solution for authorities to remotely identify issues before they cause prolonged outages or equipment damage.
Researchers show that Super Mario Brothers' level completion can be constructed to be PSPACE-hard, a class of problems considered even harder than NP. This suggests that completing a difficult level in Super Mario Brothers may require an exponential amount of time and computational effort.
A clinical study confirmed a strong correlation between minor heart rate irregularities and the survival prospects of heart attack patients. The new method, measuring respiratory sinus arrhythmia, produces a specific picture of the body's functional condition.
Scientists at the Australian National University have created a new algorithm that can accurately predict tsunamis by analyzing real-time ocean sensor data. The Time Reverse Imaging Method takes data from sensors to recreate what the tsunami looked like when it was born, allowing for better predictions of its trajectory.
A novel technique called model predictive path integral control (MPPI) helps autonomous vehicles maintain stability at the edge of handling limits. By leveraging advanced algorithms and onboard computing, MPPI enables vehicles to optimize their trajectories in real-time, reducing the risk of accidents on hazardous roads.
Researchers at University of Notre Dame develop a new algorithm to more accurately represent complex dependencies in data, leading to better predictions for invasive species, shipping networks and infectious diseases. The approach can also be applied to other fields such as social media, telecom companies and urban planning.
Researchers at George Mason University are working on a new method called 'shuffling' to quickly separate hackers from legitimate users and isolate bad actors. The approach aims to prevent denial-of-service attacks that can cripple online businesses with downed websites, financial losses, and damaged client relationships.
Researchers developed a platform for autonomous aerial refueling of UAVs, utilizing binocular vision-based sensor and navigation system. The system allows the tanker UAV to capture images of the receiver UAV and estimate its pose, then control the boom towards the receptacle for refueling.
A University of Washington team developed a highly capable five-fingered robot hand that can perform dexterous manipulation and learn from its own experience. The hand uses machine learning algorithms to model physics and plan actions, allowing it to adapt to new tasks without human intervention.
The algorithms enable a computer to act like a human when encountering an unknown word, looking up words in a dictionary and associating them with context. This development paves the way for computers to perform tasks such as translating texts, summarizing articles, and finding similar documents
A University of Michigan robot, MARLO, can now walk down steep slopes and uneven ground using a novel feedback control algorithm. The algorithm's potential benefits extend to powered prosthetic legs and other two-legged robots.
An experimental study found that readers prefer articles attributed to real journalists, but rate computer-generated texts as more credible. The study suggests that readers' expectations and limited experience with computer-based reports contribute to these differing assessments.
Researchers developed SpiroCall, a system that can accurately measure lung function using a standard phone call, regardless of smartphone availability. The tool's results were within 6.2% of clinical spirometer readings, making it suitable for monitoring chronic lung diseases at home.
Researchers have created a new machine-learning algorithm that reduces timing uncertainties in changing events by up to 300 times, allowing for more accurate dating and analysis of past events. The tool has applications in various fields, including geology, metrology, chemistry, biology, and astronomy.
A computer algorithm can recognize human emotions with high accuracy, transferring players' emotions to avatars or communicating with other players. The emotion detector system uses mathematical processing to analyze eyebrow position, eye openness, and mouth shape to correlate with basic human emotions.
A new decentralized planning algorithm for teams of robots factors in moving obstacles, reduces communication bandwidth, and preserves strong mathematical guarantees. The algorithm allows robots to operate in a world with static and dynamic obstacles while retaining their local and global objectives.
A team of researchers has identified new privacy concerns by demonstrating that geotagged posts on just two social media apps are enough to link accounts held by the same person. The study found that individuals can be identified with a high degree of confidence by matching their movements across two data sets.
Researchers at Southwest Jiaotong University developed an improved algorithm to estimate lithium ion phosphate battery state of charge by separately measuring charging and discharging states. This allows for more accurate estimation amidst initial inaccuracies and varying dynamic characteristics among batteries in series.
A novel approach, called machine unlearning, enables the removal of data without retraining a computer learning system from scratch. This method is crucial for increasing security and protecting user privacy, especially in the face of cyber-attacks and data breaches.
The Allen Institute will reconstruct over 1,000 brain connections using electron microscopes and machine learning algorithms. The project aims to advance artificial intelligence by reverse-engineering the brain's algorithms.
Researchers developed an algorithm that sorts and edits video footage into picturesque highlights for a vacation reel. The approach analyzes images with ideal artistic properties, considering factors like geolocation, composition, symmetry, and color vibrancy.
A new prediction tool developed by MIT engineers can detect rogue waves in calm waters, giving sailors a 2-3 minute warning. The algorithm analyzes wave groups and predicts the probability of a rogue wave developing based on their length and height.
Researchers at MIT developed a new model to reduce unnecessary communication in human-robot teams, enabling them to work together more effectively. The system has been tested on computer simulations and shows promise for improving team performance.
Researchers found that symmetrical RNA structures are harder to design, contradicting conventional thinking. The study uses data from over 100,000 players of the Eterna online game to develop a new rating scale for RNA-design difficulty.
A new planning algorithm generates backup plans efficiently and provides mathematical guarantees on its risk of failure, while also identifying conditions that trigger a switch to a particular contingency plan. The algorithm uses probabilistic pruning and optimistic heuristics to make the problem tractable.
Researchers developed AI software to teach a quadrocopter to autonomously recognize and follow forest trails. The drone was able to find the correct direction in 85% of cases, outperforming humans who guessed correctly 82% of the time. This breakthrough enables drones to complement rescue teams and accelerate searches for missing people.
A new algorithm combines traditional computer vision classification with deep learning models to improve pedestrian detection speed and accuracy. The technology has the potential to be used in smart vehicles, robotics, and image/video search systems.
Researchers will use insights from neural circuitry and learning methods to create more human-like computer vision and machine learning algorithms. The CMU-led team aims to unlock the brain's secret algorithms in learning and inference with a massive database of neural activity.
The Wyss Institute is leading a $21 million IARPA-funded brain mapping consortium to map neural circuits with unprecedented fidelity. The project aims to discover the brain's learning rules and synaptic circuit design, furthering neurally-derived machine learning algorithms.
Researchers develop a new algorithm to simulate electron trajectories in complex magnetic fields, significantly reducing simulation time. The method is applied to multipoles such as quadrupoles or sextupoles, yielding precise results and improving the stability of electron orbits.
A team of UMass Amherst computer scientists designed an algorithm to rapidly remove inventor ambiguity from patent records, improving searches. The winning approach will be incorporated into the USPTO's new online platform, PatentsView, providing users with more efficient and effective search capabilities.
Researchers apply shape optimization methods to enhance electric motor performance, achieving a 27% decrease in cost functional. The approach identifies optimal motor geometries that cannot be imagined beforehand, resulting in smoother rotation patterns and improved overall efficiency.
Researchers create a new method for generating training images to simulate natural variability, allowing for more accurate predictions and decision-making in various activities such as environmental cleanup and oil drilling. By analyzing a series of images using the demon algorithm, scientists select representative snapshots that captu...
Researchers developed a Bayesian Program Learning framework that captures human learning abilities, allowing computers to recognize and generate new visual concepts. The algorithm achieved impressive results in visual Turing tests, with only 25% of judges performing better than chance.
A new study leverages Statistics Canada data to identify prescription opioid-related deaths, providing a crucial gap in information for public health. The research algorithm shows high sensitivity and specificity, offering a valuable tool for researchers across Canada.
Researchers are studying how online dating technologies affect romantic connections, self-concepts, and decision-making processes. The project explores the social implications of updated online dating systems and their design features.
MIT researchers developed a new algorithm that reduces computation time for complex models by 200 times, using probability distributions and relevant data. The 'shrinking bull's-eye' algorithm can apply to various fields, including engineering, geophysics, and subsurface modeling.
Researchers developed a system that sends highly compressed images to servers, which then process the images and send back modified files with reduced bandwidth consumption. The technique reduces bandwidth usage by over 98% and energy consumption by up to 85%, making it ideal for mobile image processing applications.
A new study by Emilio Ferrara and Zeyao Yang found that positive emotions spread virally through Twitter feeds, with about 20% of users deemed highly susceptible to 'emotional contagion'. These users were four times more likely to produce positive tweets than negative ones.
Researchers at MIT have developed techniques to amplify minute motions in digital video, as well as smooth out small variations in digital images. The techniques can produce more polished images for graphic-design projects, while also disclosing structural defects and camouflaged objects.