Articles tagged with Computer Modeling
Researchers have developed a simulation of how people behave on roads based on cognitive theories, accurately reproducing pedestrian and driver behaviors in common scenarios. The model predicts complex underlying cognitive mechanisms that contribute to the difficulty in creating self-driving vehicles.
A virtual reality project, Qikiqtaruk: Arctic at Risk, visualizes the impacts of climate change in the Canadian Arctic. The project, created by National Geographic Explorers and local communities, uses immersive technology to transport users to an island experiencing rapid thawing and environmental changes.
The UK is investing £11 million to improve forecast accuracy for extreme weather events like storms, floods and droughts. Scientists are focusing on atmospheric turbulence to create more detailed models.
A team of researchers from Syracuse University and Texas A&M University applied a machine learning model to explore the sources of salinization and alkalinization in U.S. watersheds. The study found that human activities, such as road salt application, were major contributors to salinity, while natural processes dominated alkalinity.
A study by Dartmouth's Geisel School of Medicine found that Medicare fraud in home healthcare billing spread rapidly across U.S. regions between 2002 and 2009, driven by characteristics such as shared patients, high expenditures, and rapid growth in the number of home health agencies. The researchers developed a novel network analysis ...
The study uses neural recordings and computer modeling to show that phonetic information is encoded differently when speech stands out versus being drowned out. This finding could help develop more accurate hearing aids.
A recent study has found that microbes play a crucial role in storing carbon in the soil, with a four-fold greater importance than other processes. This breakthrough could lead to improved soil health and increased food security through targeted farm management practices.
Researchers updated their protein localization prediction model, MULocDeep, to provide more targeted predictions for biological discoveries. The tool helps researchers design more effective experiments and advance scientific discoveries related to drug development and treating diseases like epilepsy.
A new research effort aims to provide decision-makers with better information to understand supply chain risks, vulnerabilities, and resilience through visual analytics. The project will create a comprehensive computational and visual analytic environment to identify patterns and interdependencies in supply-demand systems.
A new Danish research project, CP-SENS, aims to develop a digital twin platform for the mechanical and construction industries. The project will provide companies with access to intelligent IT systems tailored to their needs, enabling them to adopt digital twins without significant financial investment.
A recent study published in the Proceedings of the National Academy of Sciences found that officers' first 45 words during a vehicle stop with a Black driver can indicate how the stop will end. The study discovered a unique 'linguistic signature' that characterizes escalated stops, where officers give an order without stating the reaso...
Researchers used AI to identify a compound that kills Acinetobacter baumannii, a bacterium responsible for many drug-resistant infections. The new antibiotic shows promise in combating this growing public health threat.
Researchers at MIT have developed a new approach to match 3D shapes by mapping volumes to volumes, resulting in more accurate animations and CAD designs. This method represents shapes as tetrahedral meshes that include the mass inside a 3D object, allowing for better modeling of fine parts and avoiding common artifacts.
Hanna Kokko, a renowned theoretical evolutionary biologist, has been awarded the Alexander von Humboldt Professorship for her groundbreaking research on the interplay between evolutionary and ecological factors. She will receive EUR 3.5 million to establish her research team and obtain necessary equipment and facilities.
Researchers developed AI model QUADL that can create online assessment questions indistinguishable from human-written ones. Instructors found QUADL's questions as effective as those written by humans in assessing student learning objectives. The study suggests QUADL can be a useful tool for instructors and course developers.
Researchers discovered that certain bacterial species, including lactic acid bacteria, correlate with high levels of Candida yeasts in the gut microbiome. This suggests a complex interaction between these microorganisms, where lactic acid bacteria may favor Candida proliferation while making the fungus less virulent.
Researchers develop chitosan-based coating to preserve avocados and create imaging technique to predict shelf life. The coating delays ripening, and the imaging method accurately estimates remaining shelf life, potentially improving avocado quality and availability.
Researchers used AI to analyze speech patterns of patients with Parkinson's disease, finding they spoke in shorter sentences with more verbs and fewer common nouns. The study suggests potential early detection methods for the condition through conversational analysis.
Researchers used AI to study how the hippocampus produces varied replay types efficiently and their purpose. The model showed that sequences are prioritized stochastically according to familiarity and reward positions.
The new model maximizes coverage area and minimizes response time, accounting for hot spots. It outperformed existing techniques in computational testing, improving response times regardless of traffic size.
Researchers at UChicago found a surprising connection between photosynthesis and exciton condensates, a state that allows frictionless energy flow. The discovery could lead to more efficient materials and technologies, such as superconductors.
Researchers identified three novel dual-purpose therapeutic targets using PandaOmics, which could treat both aging and glioblastoma multiforme. The target hypotheses include cyclic nucleotide gated channel subunit alpha 3 (CNGA3), glutamate dehydrogenase 1 (GLUD1) and sirtuin 1 (SIRT1).
A team of researchers from Carnegie Mellon University has developed an AI-based system to help clinicians make decisions quickly and precisely in the ICU. The system, called the AI Clinician Explorer, provides recommendations for treating sepsis based on data from over 18,000 patients.
Researchers at Cedars-Sinai created computational models to bridge the gap between
A study at Kyoto University has demonstrated the computational power of ecological networks, providing a new direction for rapidly developing AI technologies. The researchers developed two types of ecological reservoir computing that efficiently process information and can be utilized as a computational resource.
The new CALANGO software helps untangle genetic factors associated with shared characteristics, such as antibacterial resistance and agricultural improvements. It enables scientists to explore vast amounts of genomic data across thousands of organisms.
Researchers propose a 'state space' approach to reframe farming planning questions, enabling analytics and machine learning to explore optimal crop combinations and simulate different scenarios. This framework allows farmers to design diverse agricultural landscapes based on natural ecosystems, increasing crop yield and sustainability.
Researchers used computational modeling to identify ultrastable MOF structures, which could be useful for gas storage and catalysis. The study found that about 10,000 of the predicted structures were stable enough for these applications, with high deliverable capacities for methane.
Max Planck scientists explore the possibilities of artificial intelligence in materials science, discussing how combining physics-based modeling with AI can unlock complex material designs. The research focuses on overcoming limitations of traditional methods and handling sparse, noisy data.
A new model of DNA flexibility has been developed, providing results of unprecedented quality and characterizing precision and efficiency at the computational level. The study presents a systematic and comprehensive analysis of DNA movement correlations and introduces a new method to capture them.
A WPI-led team used computational modeling to create a detailed picture of the SARS-COV-2 virus envelope, revealing its elliptical shape and changing structure. This discovery could lead to more effective therapies and vaccines, as well as a better understanding of the virus's properties.
A recent study from Brigham Young University proves that artificial intelligence can respond to complex survey questions just like a real human. The researchers found high correspondence between how AI and humans voted in 2012, 2016, and 2020 U.S. presidential elections.
Researchers at NIST have developed a new method of digitally simulating hurricanes using AI techniques, accurately representing the trajectory and wind speeds of real storms. The simulations can help develop improved guidelines for building design in hurricane-prone regions.
Researchers found that fish in large schools are more willing to take risks and tune down their sensitivity to social cues, reducing the likelihood of responding to false alarms. This dynamic adjustment allows individuals to maintain control over their behavior, suggesting a potential evolutionary advantage in coping with misinformation.
A new study found that repeated requests for personal data increase disclosure, despite unchanged concerns about privacy. Researchers suggest practical measures to reduce this effect and encourage mutually beneficial sharing.
Researchers at the Human Brain Project present novel clinical uses of advanced brain modelling methods, enabling clinicians to simulate epileptic seizures and identify target areas. The approach has broad applicability in neuroscience, medicine, and neurotechnology, with potential improvements in data resolution and patient specificity.
Researchers developed a computer model based on human brain mechanisms to improve speech comprehension. The model extracts multilevel information from ongoing speech and uses non-linguistic knowledge for disambiguating word meanings. This approach is more human-like than existing language models like ChatGPT.
Richard McIndoe is leading a national research initiative to advance understanding of diabetes and obesity through the National Centers for Metabolic Phenotyping in Live Models of Obesity and Diabetes (MPMOD). The MPMOD initiative provides access to advanced testing services, including bariatric surgery on mice, to enable new insights ...
QUT researchers have solved a long-held geological conundrum about how diamonds formed in the deep roots of the earth's ancient continents. The study used computer modeling on an ancient rock sample to determine that diamonds are rare today and were always rare, challenging the existing explanation.
Researchers develop unsupervised machine learning algorithm to classify osteosarcoma at diagnosis based on gene expression modules. This approach enables personalized treatment strategies for osteosarcoma patients.
ISB researchers constructed a biological body mass index that offers a more accurate representation of metabolic health. The team found that even with no weight loss, individuals can be getting healthier biologically through positive lifestyle changes.
Antimicrobial resistance poses a major threat to human health, with an estimated 4.95 million deaths worldwide in 2019. Researchers identified four research priorities to improve predictive models for antimicrobial-resistant organisms, including better communication and data collection.
Researchers developed an economic-epidemiological model to assess the impact of no closures. The study found that California's unemployment rate would have been lower, but deaths and hospitalizations from COVID-19 would have increased significantly, exacerbating current inequities.
Researchers at University of Birmingham develop AI diagnostic tool to predict ulcerative colitis flare-ups with 89% accuracy. The system identifies markers of inflammation and healing, providing analytical support for clinicians in managing the disease.
Researchers at Cornell University developed a new model called swarmalators, which can simulate swarming behaviors and synchronized timing in microrobots. The model mimics diverse emergent phenomena, such as aggregation, dispersion, and vortices, and can be used for precision medicine and drone applications.
Researchers seek to develop algorithms providing meaningful explanations for AI decision-making, enabling higher human trust and adoption in fields like science. The project focuses on symbolic reasoning and estimating explanation accuracy, addressing the need for transparent AI systems.
A review of 25 years of AI health tech research found that only 24% of studies include patient-reported outcomes, but there has been an increase in recent years. Experts emphasize the importance of integrating patient voices into AI models to support personalized care and prevent digitalization of healthcare.
Researchers employed computer vision to extract social behaviors and linked them to brain synchronization patterns in a novel approach. During cooperative play, brain synchronization was strongest when participants shared gaze, while individual play showed increased within-brain synchronization.
Researchers studied lithospheric fluids billions of years ago to infer the presence of metals that could have supported life. Manganese was found to be a likely candidate, while copper was not detected in high concentrations. The study provides new insights into the origin of life and will inform future experiments.
A new study reveals that glaciers in Greenland move through a complex system involving basal temperate ice and varied landscapes. The research uses computer modeling to better understand the movement of the world's second-largest ice sheet, which could lead to more accurate predictions of sea-level rise.
Researchers tested three common techniques to make algorithms fairer and found that one approach didn't reduce social norm bias at all. They proposed a new technique: a formula to directly measure social norm bias in an algorithm so it can be corrected. This bias can persist even after overt discrimination is removed.
The University of Texas at El Paso has received a $1.25 million grant from the US Department of Energy to create a pipeline of scientists and engineers from underrepresented groups with expertise in modeling and simulation. The project aims to recruit, train, and develop diverse talent for advanced research and development in M&S.
Researchers found that small, disconnected wetlands are twice as effective in catching pollutants like nitrogen and phosphorus. These isolated wetlands can protect lake or river ecosystems from pollution, improving water quality and biodiversity.
Researchers developed BirdFlow, a predictive model that utilizes eBird data and machine learning to forecast migratory patterns. The model was tested on 11 species of North American birds and found to outperform other models in tracking migration flows.
The University of Kansas has established the International Center for Avian Influenza Pandemic Prediction and Prevention (ICAIP3) with $1 million in NSF funding. The center aims to predict and prevent future avian influenza pandemics by monitoring viral strains and identifying potential outbreak areas.
Researchers have developed a novel type of analogue quantum computer that can tackle hard physics problems beyond current digital capabilities. The new Quantum Simulator architecture uses hybrid metal-semiconductor components to simulate quantum materials and behaviors.
A UAB researcher discovered a new definition of Petri nets that reconciles two longstanding mathematical approaches, allowing for the reconciliation of geometric and algebraic semantics. This breakthrough has been used in epidemiological modeling, including COVID-19 research.
University of Illinois scientists developed a way to accurately map tilled land in real-time using ground, airborne, and satellite imagery. The method increased mapping accuracy by 67% compared to upscaling directly from the ground to the satellite.
Engineers at MIT and Georgia Tech have developed a faster and simpler way to model intrusion through any soft, flowable material. The new method uses Resistive Force Theory (RFT) and adapt it to 3D, predicting forces needed to push objects through sand, gravel, or other soft media in real-time.
Researchers used computer modeling to simulate a nuclear explosion and found that high airspeeds remain a considerable hazard inside buildings. The tight spaces can increase airspeed, causing severe injuries or fatalities.