Articles tagged with Computer Modeling
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.
Researchers developed a new benchmark for health care using reinforcement learning, which shows promise in managing chronic or psychiatric diseases. However, current methods are data-hungry and fail to perform accurately when tested on real-world data.
Researchers from Florida Atlantic University developed an AI system that accurately detects and tracks American Sign Language alphabet gestures using computer vision. The model achieved a detection process with high accuracy, recognizing complex hand gestures with an F1 score of 99% and mAP of 98%.
The Mcity Test Facility's first open-source digital twin enables researchers to test autonomous algorithms in a virtual environment. The digital twin introduces real-world data and simulated safety-critical events, accelerating the development of connected and automated vehicle software.
A new AI tool called PlacentaVision can rapidly evaluate placentas at birth to detect abnormalities associated with infection and neonatal sepsis. This could lead to improved health outcomes for both mothers and babies, particularly in areas with limited medical resources.
A research team led by USC aims to create comprehensive maps of retinal nerve connections to understand and combat retinitis pigmentosa, a progressive eye disease affecting 2 million people globally.
Scientists have developed a new technique to study faults, which can improve earthquake forecasts by determining the origins and directions of past rupture events. By analyzing curved scratches left on the fault plane, researchers can pinpoint where earthquakes start and spread, providing valuable insights for modeling future scenarios.
Researchers at Graz University of Technology developed a new database to improve speech recognition of Austrian German using speech data from 38 speakers. They found that traditional HMM-based systems are more robust for short sentences and dialectal language, while transformer-based models excel with longer sentences and context.
A new study estimates that India will see over 62.4 million cases of tuberculosis in the next two decades, posing a significant burden on the country's health and economy. Scaling up existing treatment regimens could generate at least $28 billion in GDP gains, highlighting the need for increased investment in TB control measures.
A team of researchers has developed a novel technique to steal artificial intelligence (AI) models by monitoring electromagnetic signals. The method allows attackers to recreate the high-level features of an AI model with 99.91% accuracy, potentially undermining intellectual property rights and exposing sensitive data.
A new technique identifies and removes specific points in a training dataset that contribute most to a model's failures on minority subgroups. This approach maintains the overall accuracy of the model while improving its performance regarding underrepresented groups.
A new AI model developed at the University of Georgia predicts nearby traffic movements and incorporates innovative features for planning safe vehicle movements. This approach helps reduce crashes and near-misses by consolidating two steps: predicting surrounding traffic movements and planning a self-driving car's motion.
A new system, EXPLINGO, enables AI models to generate readable narratives explaining their predictions, helping users make better decisions. The system, developed by MIT researchers, uses large language models to transform complex explanations into plain language and automatically evaluate their quality.
Researchers at Tokyo University of Science have developed a new method called black-box forgetting, which enables selective removal of unnecessary information from large pre-trained AI models. This approach enhances model efficiency and improves privacy by reducing computational resources and information leakage.
A new research paper published in Oncotarget introduces an innovative AI tool combining CT scans and body composition data to predict severe liver problems in primary sclerosing cholangitis (PSC) patients. The model achieved impressive results, correctly identifying at-risk patients with 97% accuracy.
Researchers develop innovative hybrid control strategy to improve product yields in biosynthetic processes. The new approach combines model-based optimization with in-cell feedback control, outperforming traditional methods and promising reduced costs and environmental impact.
Dartmouth researchers propose a new way of thinking about masking and social distancing rules using game theory, considering them as two distinct actions. The study finds that people respond differently to these measures based on their perception of the disease's severity, trending towards masking or no protective action over time.
Evo, a generative AI model, uses patterns in microbial genomes to write new genetic code, expanding the length of sequences models can process and improving resolution. Researchers use Evo to understand microbial and viral genomes, fashion new proteins, and reprogram microbes for remarkable tasks.
Researchers propose FTI-SLAM to maintain system performance while addressing critical privacy and communication concerns. It leverages federated learning, reducing data transmission and improving generalisation capabilities.
Researchers observed microfiber plastics tumbling, rolling, and getting stuck in soil particles, revealing slow movement and potential trapping. The study improves understanding of exposure risks and possible health impacts of widespread plastic pollutants.
A new study reveals that children's awareness of famous computer scientists is dominated by white men, with few women and people from diverse backgrounds represented. The researchers argue that this lack of diversity limits the relevance and usefulness of computer science for underrepresented communities.
The Polymathic AI team has released two massive datasets for training artificial intelligence models to find and exploit transferable knowledge between seemingly disparate fields. The datasets include data from dozens of sources, covering astrophysics, biology, acoustics, chemistry, fluid dynamics, and more.
Scientists at MIT developed a fully integrated photonic processor that can perform all key computations of a deep neural network optically on the chip. The device completed machine-learning classification tasks in under half a nanosecond while achieving over 92% accuracy, similar to traditional hardware.
Experts from UTHealth Houston and Baylor College of Medicine developed a pragmatic approach to monitor and manage AI systems in healthcare organizations. The guidance emphasizes the need for robust governance systems, testing processes, and transparency with patients to ensure safe AI adoption.
The National Center for Supercomputing Applications (NCSA) has received the Readers' Choice Award: Best HPC Collaboration and Editors' Choice: Best Use of HPC in Physical Sciences. This is the 14th consecutive year NCSA has been honored with an HPCwire award.
A novel no-code prototype, Auto-DSM, generates design structure matrices (DSMs) using large language models. It improves productivity and accuracy compared to traditional methods, with speeds of up to four minutes per DSM generation.
Researchers at MIT have introduced a new algorithm that strategically selects the best tasks for training an AI agent, resulting in improved performance and reduced training costs. The technique outperforms existing methods by five to 50 times, making it more efficient and effective.
The winning team presented an exascale climate emulator that addresses the growing computational and storage requirements of high-resolution Earth System Models. This innovation enables more advanced climate modeling capabilities, holding significant potential for advancing climate research and policy-making.
A team of researchers led by Jeff Zacks used computer models to analyze over 25 hours of video footage of people performing everyday tasks. They found that the models were most accurate when responding to uncertainty, suggesting a more complex role for prediction errors in human cognition. Additionally, another researcher, Maverick Smi...
A novel deep learning model called Co-Plane Attention Across MRI Sequences (CoPAS) has been developed to assist with classifying 12 common types of knee abnormalities. The model achieved high classification accuracy comparable to that of radiologists, improving diagnostic efficiency and reducing errors.
Researchers developed an AI-powered model called FastGlioma that can detect residual tumor tissue with high accuracy in 10 seconds. The technology outperformed conventional methods, reducing the risk of missed tumors by nearly 75%. This innovation could change the field of neurosurgery and minimize reliance on radiographic imaging.
Researchers developed a novel machine-learning model to identify and measure causal interactions that vary over time. The Temporal Autoencoders for Causal Inference (TACI) model performed well on synthetic and real-world datasets, detecting changes in strength and direction of causal relationships.
Researchers at Lehigh University are using advanced algorithms and cross-domain data to help cities predict human movement patterns, enabling better planning and preparedness for events and emergencies. The model will account for variations in data streams from different sources, such as cell towers, GPS, and financial transactions.
A new crowdsourcing system, FireLoc, uses a network of low-cost mobile phones to detect wildfires minutes—even seconds—after they ignite. The system prioritizes privacy and accurately maps wilderness fires to within 180 feet of their origin.
A team of MIT engineers has developed a new computational method for analyzing complex biological systems, including the immune system's response to tuberculosis vaccination. The approach uses probabilistic graphical networks to identify key interactions and mechanisms, shedding light on how vaccines induce immunity.
Researchers developed an optimized model for defibrillation that reduces energy consumption by 1,000 times, minimizing cardiac tissue damage and pain. The new approach exploits the sensitivity of fibrillation to small changes in electrical field profiles.
Despite their ability to provide turn-by-turn driving directions in New York City with near-perfect accuracy, generative AI models do not form a coherent internal map of the city. The researchers developed new metrics to test a transformer's world model and found that only one generated a coherent world model for Othello moves.
A computer modeling study found that glacial isostatic adjustment caused downward movements in the eastern US, while upward movements occurred in eastern Canada, contributing to relative sea-level rise. The research will help generate maps for aquifer management and inform decisions on sea-level rise impacts.
A team of MIT engineers developed an algorithm to identify causal links in complex systems, taking data from various sources and analyzing interactions between variables. The method generates a causality map linking variables with likely cause-and-effect relationships, including synergistic and redundant links.
Researchers developed a new index combining human comfort and social vulnerability with heat island mitigation strategies. Trees were found to provide the best relief from heat in vulnerable areas, while cool roofs and green roofs were preferred in less vulnerable neighborhoods.
A new study reveals that ocean eddies off the leeward side of Hawaiian Islands supply nutrients to both sides of the island chain, stimulating blooms of phytoplankton and boosting biological productivity. This mechanism may also impact fisheries near Hawaii and other nutrient-poor regions.
A computer model uses camera pose estimation and phototourism data to reconstruct the 3D scene of Antarctic penguin colonies, allowing for their identification and tracking. This innovative approach enables researchers to study and monitor penguin populations more effectively.
Researchers developed a method to assess which patients with metastatic triple-negative breast cancer can benefit from immunotherapy. The tool uses predictive biomarkers and machine learning-based approaches to identify patients who are likely to respond to treatment.
A new study used the 2023 Texas-Louisiana heat wave as a test case to establish processes for evaluating extreme weather events. The researchers found that the heat wave was directly related to climate change and will see even hotter heat waves in the future.
MIT researchers developed a versatile technique that combines diverse data from various sources into a shared language for generative AI models. This approach outperformed traditional techniques by 20% in simulation and real-world experiments.
Researchers at Wayne State University are developing new AI-powered methods to design and develop new drugs, including carbohydrate-based treatments for cancer. The study aims to improve the accuracy of simulations and machine learning models to predict the behavior of complex biological molecules.
Researchers discovered that Titan's icy surface is warmed by an insulating layer of methane clathrate ice, which relaxes the impact craters' shape. This finding helps explain Titan's unique hydrological cycle and climate.
A team of University of Houston engineers developed an AI tool to predict and control pandemic spread by analyzing international air travel. The analysis found that reducing flights in Western Europe can lead to fewer global COVID-19 cases, making it a key strategy for controlling the pandemic.
Researchers found that restoring coastal marshes can significantly help protect coastlines at a reasonable cost. A study by MIT graduate student Ernie I. H. Lee and professor Heidi Nepf shows that enhancing salt marshes in front of protective seawalls can reduce construction costs while still providing adequate protection from storms.
Researchers found that verified users with entrenched opinions can trigger echo chambers, while centrist ideologues may actually facilitate consensus. The study used a computational model to simulate how people post and receive messages on social media platforms.
A new tool, SymGen, enables users to verify AI model responses more quickly and easily by displaying data citations. This speeds up the manual validation process by 20 percent, making it easier for users to spot errors in LLMs deployed in various real-world situations.
A team of researchers developed a wearable camera system that uses artificial intelligence to detect potential medication delivery errors. The AI achieved high sensitivity and specificity in identifying vial-swap errors, making it a critical safeguard in operating rooms, intensive-care units, and emergency-medicine settings.
A new study suggests that Betelgeuse's pulsing is due to an orbiting companion star known as the 'Betelbuddy'. The star acts like a snowplow, pushing light-blocking dust out of the way and making Betelgeuse appear brighter. Researchers used computer simulations to confirm this hypothesis, ruling out other possible causes.
A team of scientists and experts led by PNNL has developed a cloud computing approach to democratize access to emerging resources. They demonstrated that cloud computing can provide an agile complement to high-performance computing facilities, enabling complex chemistry workflows to be completed in days instead of months. The initiativ...
A UVA professor has developed a new computational algorithm to find tightly connected clusters, or triangle-dense subgraphs, within large networks. This breakthrough can help uncover suspicious activity in fraud detection and identify community dynamics on social media with greater precision.
A new project, 'Crowd-Assisted Human-AI Teaming with Explanations,' aims to develop an interactive AI system that leverages the collective strengths of human crowd workers and machine learning models. The researchers will use crowdsourcing platforms to recruit experts and non-experts to perform tasks, making the system more robust and ...
Researchers at UVA have developed an AI-driven system that optimizes manufacturing processes, improving speed and quality while reducing waste. The system uses Multi-Agent Reinforcement Learning to coordinate tasks in real-time, leading to faster production and reduced downtime across various industries.
Researchers at UVA's School of Engineering and Applied Science have developed an AI-driven intelligent video analyzer capable of detecting human actions with unprecedented precision and intelligence. The system, called SMAST, promises to transform industries such as surveillance, healthcare, and autonomous driving.
Researchers at Chung-Ang University developed a novel GAN model, PMF-GAN, to address stability and efficiency issues. The model utilizes kernel functions and histogram transformations to improve the generator's ability to produce diverse outputs, reducing mode collapse and gradient vanishing.
Researchers designed custom-fit PAP masks using computational modelling to reduce air leakage and increase comfort. The masks were tested against commercially available ones, showing promising results.
The two-year study aims to explore biases in AI systems and develop a 'human-in-the-loop' framework for quality data discovery. It will investigate how humans can be involved as labelers, prompters, and validators to improve data sets and user interfaces.