Articles tagged with Algorithms
Comprehensive exploration of living organisms, biological systems, and life processes across all scales from molecules to ecosystems. Encompasses cutting-edge research in biology, genetics, molecular biology, ecology, biochemistry, microbiology, botany, zoology, evolutionary biology, genomics, and biotechnology. Investigates cellular mechanisms, organism development, genetic inheritance, biodiversity conservation, metabolic processes, protein synthesis, DNA sequencing, CRISPR gene editing, stem cell research, and the fundamental principles governing all forms of life on Earth.
Comprehensive medical research, clinical studies, and healthcare sciences focused on disease prevention, diagnosis, and treatment. Encompasses clinical medicine, public health, pharmacology, epidemiology, medical specialties, disease mechanisms, therapeutic interventions, healthcare innovation, precision medicine, telemedicine, medical devices, drug development, clinical trials, patient care, mental health, nutrition science, health policy, and the application of medical science to improve human health, wellbeing, and quality of life across diverse populations.
Comprehensive investigation of human society, behavior, relationships, and social structures through systematic research and analysis. Encompasses psychology, sociology, anthropology, economics, political science, linguistics, education, demography, communications, and social research methodologies. Examines human cognition, social interactions, cultural phenomena, economic systems, political institutions, language and communication, educational processes, population dynamics, and the complex social, cultural, economic, and political forces shaping human societies, communities, and civilizations throughout history and across the contemporary world.
Fundamental study of the non-living natural world, matter, energy, and physical phenomena governing the universe. Encompasses physics, chemistry, earth sciences, atmospheric sciences, oceanography, materials science, and the investigation of physical laws, chemical reactions, geological processes, climate systems, and planetary dynamics. Explores everything from subatomic particles and quantum mechanics to planetary systems and cosmic phenomena, including energy transformations, molecular interactions, elemental properties, weather patterns, tectonic activity, and the fundamental forces and principles underlying the physical nature of reality.
Practical application of scientific knowledge and engineering principles to solve real-world problems and develop innovative technologies. Encompasses all engineering disciplines, technology development, computer science, artificial intelligence, environmental sciences, agriculture, materials applications, energy systems, and industrial innovation. Bridges theoretical research with tangible solutions for infrastructure, manufacturing, computing, communications, transportation, construction, sustainable development, and emerging technologies that advance human capabilities, improve quality of life, and address societal challenges through scientific innovation and technological progress.
Study of the practice, culture, infrastructure, and social dimensions of science itself. Addresses how science is conducted, organized, communicated, and integrated into society. Encompasses research funding mechanisms, scientific publishing systems, peer review processes, academic ethics, science policy, research institutions, scientific collaboration networks, science education, career development, research programs, scientific methods, science communication, and the sociology of scientific discovery. Examines the human, institutional, and cultural aspects of scientific enterprise, knowledge production, and the translation of research into societal benefit.
Comprehensive study of the universe beyond Earth, encompassing celestial objects, cosmic phenomena, and space exploration. Includes astronomy, astrophysics, planetary science, cosmology, space physics, astrobiology, and space technology. Investigates stars, galaxies, planets, moons, asteroids, comets, black holes, nebulae, exoplanets, dark matter, dark energy, cosmic microwave background, stellar evolution, planetary formation, space weather, solar system dynamics, the search for extraterrestrial life, and humanity's efforts to explore, understand, and unlock the mysteries of the cosmos through observation, theory, and space missions.
Comprehensive examination of tools, techniques, methodologies, and approaches used across scientific disciplines to conduct research, collect data, and analyze results. Encompasses experimental procedures, analytical methods, measurement techniques, instrumentation, imaging technologies, spectroscopic methods, laboratory protocols, observational studies, statistical analysis, computational methods, data visualization, quality control, and methodological innovations. Addresses the practical techniques and theoretical frameworks enabling scientists to investigate phenomena, test hypotheses, gather evidence, ensure reproducibility, and generate reliable knowledge through systematic, rigorous investigation across all areas of scientific inquiry.
Study of abstract structures, patterns, quantities, relationships, and logical reasoning through pure and applied mathematical disciplines. Encompasses algebra, calculus, geometry, topology, number theory, analysis, discrete mathematics, mathematical logic, set theory, probability, statistics, and computational mathematics. Investigates mathematical structures, theorems, proofs, algorithms, functions, equations, and the rigorous logical frameworks underlying quantitative reasoning. Provides the foundational language and tools for all scientific fields, enabling precise description of natural phenomena, modeling of complex systems, and the development of technologies across physics, engineering, computer science, economics, and all quantitative sciences.
A study using computer vision algorithms examines millions of Google Street View images to measure urban change, finding that high density and education are key drivers of improvement. The research also supports three classical theories of urban change, highlighting the importance of human capital and education in shaping cities.
Researchers developed a model to explain human moral behavior in simulated scenarios, showing that machines can adopt human-like moral decision-making. The study has significant implications for self-driving cars and other autonomous systems, sparking debate about the role of morality in machine behavior.
Researchers matched would-be carpoolers with people driving to work based on social media data and found that compatibility increased satisfaction and reduced car use by 57% in Rome and 40% in San Francisco. This approach could lead to a dent in gridlock, reduce pollution and make commuting more enjoyable.
A universal algorithm for folding origami shapes guarantees a minimum number of seams, producing more practical and sturdy structures. The new method preserves the boundaries of the original piece of paper, allowing users to choose where seams meet.
Researchers at Numenta have developed an online sequence memory algorithm called Hierarchical Temporal Memory (HTM) that can detect anomalies in real-time streaming data without supervision. The technique is based on the principles of how the brain works and has been tested using the Numenta Anomaly Benchmark.
New simulations reveal DNA's constant motion enables rapid transcription factor diffusion, contradicting the long-held assumption of rigid DNA. The findings have significant implications for understanding cell processes and potentially boost speed and accuracy in biological and medical research.
A new method using microphones has been developed to track pollinating bees, which could save farms money by predicting bee activity and pollination services. The researchers recorded bee buzzing sounds using inexpensive equipment and compared them to visual counts, achieving high accuracy.
A recent Stanford University School of Medicine study found that fitness trackers generally accurately measure heart rate but struggle with calculating energy expenditure, which is often used to track calories burned. The study evaluated seven devices and found that six were accurate in measuring heart rate within 5% error, while none ...
Researchers at Duke University have developed new algorithms that enable analysis of sensitive data while guaranteeing individual privacy. The tools use a customized definition of privacy similar to differential privacy, injecting just enough noise to satisfy regulations and uphold the law.
Researchers developed a personalized algorithm that predicts the impact of particular foods on an individual's blood sugar levels. The Glucoracle app allows users to upload food and blood measurements, providing real-time predictions of post-meal blood sugar levels.
A NJIT graduate student has won an IBM fellowship to develop computer systems that mimic the human brain's architecture. The goal is to raise computers' learning and inference capabilities while lowering energy consumption.
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 study published in PLOS Computational Biology found that humans' ability to make random choices peaks around age 25 and declines thereafter. The researchers assessed over 3,400 participants and used online tasks to evaluate their algorithmic randomness.
Researchers at Stanford University have created a deep learning algorithm that can accurately predict the toxicity of chemicals and associate drugs with side effects using just six data points. This breakthrough could help chemists choose promising candidates and accelerate drug development.
Researchers at Silicon Studio developed an algorithm that uses 'ensemble' and survival analysis methods to predict when users will leave a mobile game. The model can automatically adapt to different games and data, enabling companies to understand user needs and design more entertaining games.
Physicists have developed a new feedback controller to control fusion plasma energy and rotation. The algorithm uses sensors, algorithms, and actuators to modify the plasma's rotation profile and stored energy.
A new algorithm allows users from different network providers to pair up and make better use of the available wireless spectrum, reducing inefficiency in wireless technology. The 'blind' matching algorithm uses a simple learning process and converges to a stable-matching state, enabling mutually beneficial partnerships.
Researchers developed an algorithm that uses Deep Learning to predict the decision of hematopoietic stem cells to become a certain cell type. This enables earlier detection and analysis of blood cell development, paving the way for new treatments and insights into developmental traits.
Researchers discovered that an algorithm called additive increase, multiplicative decrease (AIMD) is used both in engineered systems like the Internet and biological networks like the human brain. This finding sheds light on how the brain manages information and potentially helps understand learning disabilities.
Scientists at the University of Luxembourg developed Equihash, a memory-hard problem algorithm that resolves Bitcoin's centralization issue. This allows for more democratic digital currencies like Zcash, where users can contribute to mining with standard hardware, reducing investment costs and increasing decentralization.
Researchers tested automated approaches to analyze large linguistic datasets, finding that some methods detected cognates correctly with high accuracy. The study suggests a promising future for combining algorithms and expert knowledge to uncover human prehistory and cultural evolution.
MIT researchers incorporated human strategies into automatic planners, achieving significant improvements in performance. By encoding high-level strategies from skilled human planners, they improved the performance of competition-winning algorithms on complex planning problems.
Researchers developed machine learning algorithms to reconstruct 3D protein structures using microscopic images, enabling faster discovery of new drugs for diseases like Alzheimer's and cancer. The approach eliminates prior knowledge requirements, making it possible to study previously inaccessible proteins.
Researchers at Lawrence Berkeley National Laboratory have developed a machine learning algorithm to predict point defects in intermetallic compounds with high accuracy. This method accelerates research on new advanced alloys and lightweight materials for various industries.
Researchers at MIT's Sloan Neuroeconomics Lab have developed a new method to extract correct answers from large groups of people, reducing errors in crowd wisdom surveys. The 'surprisingly popular' algorithm uses the variation between individual responses and predicted popular opinion to identify the correct answer.
A Stanford-developed deep learning algorithm accurately diagnoses skin lesions as well as board-certified dermatologists, with potential to provide life-saving smartphone diagnosis. The algorithm was trained on a database of nearly 130,000 images and tested against 21 dermatologists in identifying malignant carcinomas and melanomas.
Researchers at Cornell University developed an artificial Ms. Pac-Man player that achieved a laboratory score of 43,720, surpassing the existing high score for computerized play. The player uses a decision-tree approach and demonstrates accuracy in predicting ghost movements with 94.6-percent accuracy.
Researchers found that attackers can crack Android Pattern Lock within 5 attempts using video and computer vision algorithm software. Complex patterns are actually easier to crack than simple ones, making shorter, simpler patterns a more secure option.
Researchers develop a treatment algorithm for bionic hand reconstruction in patients with severe nerve damage, offering improved hand function and reduced chronic pain. The study's five patients show significant improvements in hand function, including increased sensitivity and motor control.
Researchers developed a novel-machine learning method to distinguish people with common names, focusing on relational features, text features, and venue features. The new approach is an improvement over existing methods, enabling the identification of previously unencountered individuals.
Researchers created tools called disturbance observers using fractional calculus, which estimate and eliminate disturbances in systems. The new approach outperformed existing methods, particularly when combined to handle highly fluctuating disturbance signals.
Researchers developed an algorithm that extracts diverse subsets from large data sets, improving machine learning efficiency and diversity. The new method is 1 billion times faster than existing algorithms, enabling real-time analysis of vast amounts of data.
Researchers have combined CRISPR gene editing with single-cell genomic profiling to understand nuanced cellular processes. The new technology enables precise manipulation of genes in individual cells, revealing previously unknown functions and advancing the field of genetic engineering.
The UCLA team implanted a spinal stimulator in a California man who broke his neck in a dirt-biking accident, showing early promise in returning hand strength and movement. The device bypasses the injury by training the spinal cord to find alternate pathways, allowing patients to regain mobility in their hands.
The Jefferson Lab-NVIDIA collaboration uses Titan's supercomputer to simulate QCD interactions, achieving speedups of seven- to tenfold for calculations. This enables researchers to explore exotic mesons and advance QCD theory.
Game theory and algorithms improve security by randomizing patrols to evade attackers' predictions. Real-world applications have led to measurable improvements in security for US Coast Guard ferry protection since 2011.
A new recommendation algorithm allows individuals and items to belong to multiple overlapping groups, making it more realistic than existing models. The algorithm's predicted ratings proved more accurate than those from existing systems on five large datasets.
Researchers developed a machine-learning model that can distinguish between pathological hypertrophic cardiomyopathy (HCM) and physiological changes in athletes' hearts, enabling easier diagnoses. The model demonstrated superior diagnostic ability comparable to conventional 2D echocardiographic and Doppler-derived parameters.
Researchers found a universal principle underlying human intelligence, enabling complex brain computations and generalization of knowledge. The Theory of Connectivity proposes a simple mathematical logic guiding neural connections and communications.
Researchers have developed an algorithm to detect fake reviews on ecommerce sites, analyzing behavior and content features to identify deceptive posters. The method outperforms earlier detection algorithms, providing a more accurate picture of product ratings.
Researchers have developed a new algorithm that can efficiently fit probability distributions to high-dimensional data, even when the dataset contains corrupted entries. The algorithm relies on two insights: selecting an appropriate metric for measuring distance from distributions and identifying regions where cross-sections should begin.
Researchers at Northeastern University have proposed a way to optimize power exchange between the main grid and multiple microgrids using consensus-based algorithms. These algorithms allow decentralized generators to communicate with each other and with the main grid, ensuring reliable and cost-effective energy distribution.
The UnBias project aims to establish a system of auditability and build trust in the internet by studying user experience and algorithm design. Researchers will also produce educational materials to support youth understanding about online environments.
Researchers at Sandia National Laboratories explore neural computing applications, including adaptive learning, dynamical systems, and spiking network algorithms. These approaches aim to overcome the static learning bottleneck and enable precise computations.
Researchers construct networks of organelle functional modules in Arabidopsis using a soft thresholding approach. The algorithm identifies strongly co-expressed genes and links them to infer the function of unknown genes.
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.