Articles tagged with Algorithms
Osaka University researchers developed an algorithm for numerical calculation of EM noise in electric circuits, reducing interference caused by transmission lines. The new method allows for more practical calculations and demonstrates the reduction of EM noise using symmetric 3-line configurations.
MIT engineers have developed an algorithm that enables autonomous underwater vehicles to weigh the risks and potential rewards of exploring unknown regions. The algorithm assesses risk levels and reward probabilities in real-time, allowing AUVs to take calculated risks when justified by potential scientific rewards.
A novel model developed by MIT and Microsoft researchers identifies instances where autonomous systems learn from examples that don't match the real world, leading to dangerous errors. The model uses human feedback to pinpoint situations where more information is needed to act correctly.
Researchers developed an AI-powered method to correct errors in single-cell RNA sequencing, enabling precise data for every cell. The algorithm, called kBET, quantifies differences between experiments and facilitates comparison of correction results.
Dr. Eric Baumer aims to develop participatory methods for human-centered design of algorithmic systems, incorporating diverse experts and users in the design process. He will work with nonprofits AEquitas and ProPublica to create interactive tools that better align with users' existing practices.
Researchers developed a machine learning algorithm to optimize lab test ordering in ICU patients, reducing testing by up to 44% and improving treatment timing. The approach aims to maximize patient rewards while minimizing costs and risks.
A recent study from the University of Waterloo found that measuring AI's ability to learn is challenging due to the complexity of tasks. The researchers discovered that no mathematical method can determine whether an AI-based tool can handle a task or not, even with precise task descriptions.
The Mathematical Association of America (MAA) recognizes Tom Leinster for his outstanding expository article 'Rethinking Set Theory' with the MAA Chauvenet Prize. Cathy O'Neill wins the MAA Euler Book Prize for her book 'Weapons of Math Destruction', tackling data science's social and political implications.
Machine learning helps detect epigenetic features in genomes and identifies similarities between phenotypes and gene modifications.
Researchers at University of Notre Dame have developed a new mathematical approach to solve NP-hard problems using analog computing. The 'solver' has the potential to find better and possibly faster solutions than digital computers for complex optimization problems.
A new algorithm that combines experimental data with machine learning reduces the time needed to find optimal peptide sequences, allowing for faster discovery and synthesis. This method has the potential to revolutionize how peptides are designed and could lead to breakthroughs in materials science, chemistry, and medicine.
Researchers at RIT are developing an advanced visual tracking system using deep learning and artificial intelligence to refine object location and movement. The system has potential applications in autonomous navigation, drones, traffic monitoring, safety, security, disaster response, and human-computer interaction.
Researchers at the Salk Institute discovered a framework that mimics how fruit flies detect novel odors, using a Bloom filter-like data structure. This new approach improved accuracy for detecting duplicates or anomalies in large datasets.
A novel scale-free mechanism guides the search of an artificial bee colony algorithm, improving its exploitation ability and maintaining population diversity. This enables a better balance between exploration and exploitation, leading to enhanced search ability in real-world optimization problems.
Researchers used network analysis to rank films and their creators based on references in subsequent movies. The study found that influential films were mostly produced before 1980 and featured top US directors like Hitchcock, Spielberg, and Kubrick.
A new algorithm computes and enables realistic movement and distortion of 3D surfaces, including gravity, contact, and friction. The method allows users to freely design garments around a 3D character without worrying about physics.
A RIT researcher is developing new signal processing solutions to improve data analysis efficiency and reliability. The project aims to reduce the impact of faulty measurements in complex sensing systems by creating algorithms that can detect and mitigate corrupted data.
Researchers have developed a new method to replicate complex natural tessellations on surface meshes using layered fields and sparse linear algebra kernels. The algorithm is platform-independent, concise, and achieves considerable performance gains over existing serial Voronoi diagram codes.
A new machine learning algorithm combined with a handheld smartphone device can accurately estimate the gestational age of premature newborns. The technology has the potential to aid healthcare workers in remote and low-income countries, where preterm births are a leading cause of child mortality.
Researchers identify potential causes of bias in machine learning systems and demonstrate how changing data collection methods can reduce bias without compromising accuracy. They suggest identifying clusters of patients with high disparities in accuracy to inform data collection decisions.
A team of researchers is using a $820,000 DARPA grant to design a new kind of chip that can automatically match software with hardware, significantly reducing the time it takes. The chip, called DASH-SoC, aims to achieve this in just five nanoseconds.
The Orcasound project has developed a web application that enables citizen scientists to listen to livestreaming audio from hydrophones, complementing computer algorithms in analyzing data. The app aims to bring synergy between human listeners and sophisticated algorithms, saving audio data to online cloud storage for later analysis.
A University of Pittsburgh researcher is using video games to test and improve artificial intelligence algorithms. The goal is to create AIs that can learn from their mistakes in complex, uncertain environments. By analyzing gameplay data, the algorithm can refine its strategies for optimal decision-making.
Researchers developed a new approach to interpret machine learning algorithms, revealing how they can produce nonsensical answers even when given meaningful inputs. By reducing inputs to the bare minimum required for correct answers, the method provides insights into algorithmic limitations and potential solutions.
A study published in EPJ Data Science found that algorithms predicting crimes more accurately than existing models, with significant improvements in predictions for assaults and drug offences. The system used location and activity data from Foursquare users to make predictions.
Researchers at Dartmouth College used the Bible to develop an algorithm that can convert written works into different styles for different audiences. The study, published in Royal Society Open Science, trained on over 1.5 million unique pairings of source and target verses from various versions of the sacred texts.
A computational tool using machine learning and optimization algorithms matches refugees to host communities with the best resources for success. Annie MOORE predicts refugee employment likelihood and guides resettlement workers in finding suitable placements, improving integration outcomes.
A machine-learning model provides risk assessment for complex nonlinear systems, identifying the types of extreme events likely to occur. The technique simulates wave forces and stresses on structures, offering a faster and more accurate risk assessment than traditional methods.
Researchers at MIT have developed a software tool that automatically generates maps of favorable landing sites on Mars, taking into account scientific priorities and engineering constraints. The program uses fuzzy logic to deal with imprecision in the data and can explore different landing and exploratory scenarios.
A new clinical algorithm has been developed to identify eligible patients with uncomplicated staphylococcal bloodstream infections who can take antibiotics for fewer days. This reduction in antibiotic duration is significant and could help reduce antibiotic resistance on a broader scale, benefiting individual patients and public health.
New research reveals that AI can accurately interpret respiratory symptoms and diagnose lung diseases, surpassing human specialist results. The study trained an AI algorithm using high-quality data and found it to be more consistent and accurate than doctors in interpreting test results and suggesting diagnoses.
Researchers created a model of hybrid system with two unreliable servers, finding that heterogeneity improves data transmission speed and reliability. The new reliability measurement is introduced as the distribution function of failures within a given operation period.
Researchers created an algorithm using physics of panel degradation to analyze solar farm data, providing a portable EKG for solar farms. The approach can inform better panel designs, prolong lifespan, and cut electrical bills, ultimately transforming the industry's diagnosis and decision-making processes.
Researchers at Samara University have developed an algorithm that increases internet speed up to 50% by providing fast and reliable access to powerful data processing centers. The algorithm, called 'The Neighborhoods Method', can enable scientists to participate in experiments on the hadron collider level.
Researchers created a lensless camera by connecting a digital sensor to a plexiglass window, which acts as a makeshift lens. The system can capture recognizable images with computer algorithms decoding the pixelated data. This innovation opens up possibilities for various applications, including augmented reality goggles and biometric ...
Computer vision algorithms have made significant progress in tasks such as object identification and categorization. However, they struggle with determining whether two objects in an image are the same or different. Researchers at Brown University found that this limitation stems from the inability of these algorithms to individuate ob...
A KAIST team introduced Agile 3D Sketching with Air Scaffolding, combining hand motions and pen-based sketching to create 3D shapes. The technique allows designers to reduce time while enhancing accuracy in defining proportion and scale of products.
Researchers developed an Ensemble Poisson Kalman Filter (EnPKF) algorithm that combines urban crime data and ETAS model for real-time forecasts on crime rates and predicted hotspots. The algorithm has been tested on over 1000 violent gang crimes in Los Angeles, showing promise as a tool to support law enforcement
A study from University of Helsinki reveals that sudden cold spells occurred during the Eemian interglacial period, lasting hundreds of years and impacting northern European climate. The research suggests that disturbances in North Atlantic circulation contributed to these shifts, highlighting the sensitivity of this oceanic system.
Researchers from the Santa Fe Institute developed a new algorithm called SpringRank that analyzes wins and losses in networks to predict outcomes. The algorithm outperformed others in efficiency and accuracy, even when applied to diverse datasets such as NCAA basketball teams and animal social behaviors.
Artificial neural networks can now be trained directly on an optical chip, paving the way for less expensive, faster, and more energy-efficient AI. This breakthrough enables complex tasks like speech or image recognition to be performed more efficiently.
An international team of researchers developed a new computational method to predict the functions of thousands of microbial genes. The method, based on machine learning algorithms, analyzes 'big data' from human microbiomes and other environments to identify evolutionary signals that can assign biological roles to unknown genes.
A researcher at MSU developed an algorithm to improve information security tools by reducing the complexity of scalar multiplication in elliptical curve transformations. The new algorithm achieves a 5% reduction in precomputation stage complexity and a 4% reduction in main stage complexity.
The researchers developed a novel synaptic architecture that could lead to a new class of information processing systems inspired by the brain. Prototype chips containing over one million nanoscale memristive devices were used to implement a neural network for detecting hidden patterns and correlations in time-varying signals.
The Cheetah 3 robot can navigate staircases littered with debris and recover its balance when yanked or shoved, thanks to two new algorithms developed by MIT engineers. The contact detection algorithm helps the robot determine the best time for a leg to switch from swinging in the air to stepping on the ground.
Researchers at the Higher School of Economics have developed a new method for recognizing people on video using only one photo, achieving higher recognition accuracy compared to existing methods. The algorithm uses information on how reference photos are related to correct errors in video frame recognition.
Computer scientists at Harvard SEAS developed a new algorithm that exponentially speeds up computation by reducing parallel steps required to reach a solution. The algorithm samples directions in parallel and discards low-value directions, enabling real-world summarization processes to be developed at unprecedented scale.
Researchers developed an algorithm that accelerates the registration of 3D medical images by learning from previous registrations, reducing processing time to minutes or seconds. The 'VoxelMorph' algorithm uses convolutional neural networks and achieves comparable accuracy to state-of-the-art systems.
Researchers at Princeton University have improved a proteomics method to accurately count proteins in cells under different circumstances. The new approach, TMTc+, uses a combination of cell sample preparation and computer algorithm changes to provide superior measurement accuracy and precision compared to existing methods.
A new algorithm developed by researchers at UCLA Medical Center can predict hypotension in surgical patients with high accuracy, enabling physicians to take proactive measures. The algorithm uses machine learning to analyze physiological data and identifies subtle signs of impending hypotension, reducing the risk of serious complications.
Researchers developed an algorithm to determine the optimal caffeine dosage and timing for maximum alertness during sleep loss. The 2B-Alert app uses a validated mathematical model and optimization algorithm to provide personalized caffeine-dosing strategies, improving alertness by up to 64%.
Researchers at MIT developed an algorithm to prioritize and transmit data from sensors in real-time, ensuring the freshest possible data is received by a network. The algorithm calculates an 'index' based on data age, channel reliability, and node priority, guaranteeing optimal decision-making without overloading wireless channels.
Researchers from Rice University and Duke University developed a new method to accurately estimate the number of identified victims killed in the Syrian civil war. Using 'hashing with statistical estimation,' they produced real-time estimates with a lower margin of error than existing methods.
A newly developed algorithm determines ideal caffeine dosage and timing for optimal alertness. The algorithm improves neurobehavioral performance by up to 64% using the same total amount of caffeine, or reduces caffeine consumption by up to 65% while maintaining equivalent improvements in alertness.
Researchers developed a new algorithm, GDP-ADMM, to further enhance the capabilities of SHARP in reconstructing high-resolution images from ptychographic datasets. The new framework takes advantage of state-of-the-art mathematical aspects to improve data acquisition and image resolution.
Scientists developed a machine learning approach to predict microbial pathways, allowing for faster design and development of biofuels. The method accurately predicted biofuel production profiles, outperforming traditional kinetic models.
Researchers at St. Jude Children's Research Hospital have identified a hidden driver, kinases Mst1 and Mst2, that regulates the function of different dendritic cell subsets and primes anti-tumor T cells. This discovery provides clues for new treatment strategies by modulating dendritic cell activity to shape the immune response.
The Swiss State Secretariat for Migration and the Immigration Policy Lab (IPL) are testing a new data-driven method to assign asylum seekers to cantons across Switzerland. The algorithm aims to maximize job chances, and its recommendations will be compared to those of randomly allocated individuals over several years.
A NIST study reveals that facial recognition experts achieve maximum accuracy when working with artificial intelligence, rather than another human. Trained professionals outperformed untrained control groups and algorithms performed comparable to top-performers.
A new algorithm developed by Tufts University researchers enables the self-localization of IoT devices on 5G networks, eliminating the need for centralized anchors and improving location-based services. This scalable solution can meet the demands of a projected 50 billion connected products by 2020.