Articles tagged with Computer Modeling
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 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.
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.
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 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.
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.
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 ...
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 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.
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.
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.
A new study finds that autonomous vehicles could consume enough energy to generate significant greenhouse gas emissions, highlighting the need for rapid advancements in hardware efficiency. To mitigate this, researchers recommend more efficient autonomous vehicles with smaller carbon footprints.
A new study from Pusan National University explores the use of collaborative artificial intelligence models in fashion design, finding that human designs offer unique originality and creativity. The researchers propose a human-AI collaborative network to produce novel designs, which can also be used as a learning tool for non-experts.
Researchers at the University of Arkansas have developed computer models to determine a drug candidate's binding affinity to proteins. The models use computational physics and experimental data to estimate the effective energy of the ligand at every grid point, allowing for accurate estimation of binding affinity.
Researchers at Rensselaer Polytechnic Institute developed a model to predict cryptocurrency scams using Benford's Law and found that scam addresses deviated from the law. They also advocated for robust blockchain interoperability to provide stability in decentralized systems.
Researchers at Indiana University found that the average age of human conception is around 26.9 years, with fathers averaging 30.7 years and mothers averaging 23.2 years over the past 250,000 years. The study also suggests that the age gap between fathers and mothers has narrowed in recent times.
A team of researchers from The University of Tokyo created a computer simulation to study the phase separation of counter-rotating particles in a fluid. They found that nonlinear turbulent effects lead to the sudden separation of particles into regions of clockwise and counterclockwise collections.
Researchers tracked tweets about two invasive insects, spotted lanternfly and Tuta absoluta, on Twitter and in news stories. They found that activity patterns on these platforms aligned with official surveys, providing insights into pest spread timing and location.
Researchers at MIT's Picower Institute found that the brain stores information in working memory by making short-lived changes in neural connections, contradicting the traditional idea of sustained neuronal activity. This new insight sheds light on the sophisticated flexibility of thought and its dynamic nature.
Researchers found no evidence of a critical mass needed to start and maintain new research fields. Instead, pioneering regions with early investment can establish dominance. However, late-comers face significant costs to catch up, as seen in China's semiconductor science, where strategic interventions over decades led to a dominant role.
A predictive model developed by University of Groningen researchers can identify cows at risk of dystocia before insemination. The model, which uses machine learning on a large dataset, suggests that it could roughly halve the risk of calving problems.
A study reveals that big dynorphin, an endogenous opioid peptide, protects neurons against β-amyloid accumulation. The research suggests that big dynorphin can hinder the interaction between β-amyloid and form aggregates, promoting a neuroprotective effect.
Researchers discovered that enterococci, a type of antibiotic-resistant bacteria, can make C. difficile more potent and dangerous by producing amino acids. This understanding could help doctors identify patients at risk and develop new treatments for the deadly infection.
A pilot study conducted at Brigham and Women's Hospital found that a low-cost computer vision system was feasible and well-received by employees. The system accurately detected mask adherence 100% of the time, with most participants experiencing a positive interaction.
A new computational tool can generate an optimal design for a complex fluidic device without requiring manual assumptions about its shape. The system uses anisotropic materials to represent tiny voxels, allowing it to create smooth curves and intricate designs that other methods cannot.
A new coupled computer modeling approach can accurately predict compound flooding events, such as the one caused by Hurricane Florence in 2018. This technique combines ocean and river models to better capture the interactions between storm surges and rain-induced flooding.
Researchers at Rutgers University simulated climate change's impact on allergenic pollens, finding significant increases in airborne pollen loads by 2050. The study predicts earlier start times and longer durations for pollen seasons across the US, with notable regional shifts.
A computer model simulates virtual groups of migrating animals and finds that sticking together is key to finding a destination, even when the magnetic compass is unreliable. The model showed that more than 70% of animals made it home simply by joining with others and following their lead.
A team of researchers from the University of Pennsylvania has developed a new algorithm, metadynamics, that can navigate high-dimensional energy landscapes to find low-energy configurations. This breakthrough has the potential to revolutionize fields such as protein folding and machine learning.
A new deep learning model using conditional generative adversarial networks (cGANs) has been developed to diagnose bowel ischemia. The model achieved an accuracy of over 93% in segmenting ischemic intestine images, surpassing current subjective methods.
A new model reveals that warmer Arctic Ocean evaporation transports moisture south, leading to increased snowfall in northern Eurasia. The study sheds light on the mechanism of this phenomenon and its impact on severe weather events.
A team of researchers used AI pattern recognition to re-analyze footprints from the Dinosaur Stampede National Monument and concluded that they were made by an ornithopod dinosaur, a herbivorous species. The results contradicted the long-held assumption of a vicious dinosaur predator.
The DUNE project uses deep learning techniques and distributed computing to improve indoor positioning accuracy. The system combines various sensor technologies and adapts to different industrial needs, providing real-time updates and reducing margins of error.
Researchers developed an intelligent compaction technology that integrates into a road roller, assessing real-time the quality of road base compaction. This improves road construction, reducing potholes and maintenance costs, leading to safer and more resilient roads.
Researchers used machine learning to track turbulent structures in fusion reactors, gaining detailed information on their behavior and heat flows. The approach enables more accurate engineering requirements for reactor walls and could lead to improved energy efficiency.
Researchers from the University of Tokyo's Interactive Intelligent Systems Laboratory developed a new system called LookHere that incorporates natural hand gestures into the teaching process. This approach eliminates extraneous details and provides better input data for machines to create models, resulting in improved efficiency and ac...
A study using contract tracing data in New York City found the city's program was efficient, producing data that informs neighborhood-level interventions like vaccination and reactive restriction. The researchers also identified large heterogeneity in reported close contacts and secondary infections across neighborhoods.
Researchers at UVA Children's will use a sophisticated computer model to better understand and treat Crohn's disease, which can have lifelong consequences for young patients. The team hopes to identify biological markers or metabolic signatures that can be used for early diagnosis and personalized medicine.
Researchers at Kyushu University developed a new method to create highly detailed 3D models of plants and animals. Over 1,400 models are now publicly available for use in education, research, and virtual exploration.
A new study published in iScience found that humans tend to follow a two-step process when in a crowd, with an initial reflexive imitation followed by a more deliberate strategic decision. The research suggests this influence affects not only social norms but also immediate actions and underlies behaviors such as rioting and mass panic.
Researchers developed an AI-based model that combines artificial intelligence and weather forecast models to predict extreme wildfire danger with high accuracy. The new method can produce forecasts of extreme fire danger out to one week at finer scales (4km x 4km resolution), increasing its utility for fire suppression and management.
A new study found that increasingly complex mathematical models can produce more uncertain estimates, limiting their usefulness for informing real-world policy decisions. Researchers recommend reassessing the drive to create detailed models and suggest calculating the model's effective dimensions before adding complexity.
A new $1.328M grant will help assess and improve the reporting quality in randomized clinical trial protocols and result publications using NLP methods. The goal is to promote high reporting standards, synthesizing evidence, and open science practices throughout the scientific ecosystem.