Articles tagged with Computer Modeling
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.
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.
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 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...
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.
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 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.
A new genome imaging technique captures the structure of the human genome at unprecedented resolution, revealing how individual genes fold and work. This technique, called Modeling immuno-OligoSTORM (MiOS), combines high-resolution microscopy and advanced computational modeling to provide a detailed picture of gene shape and function.
Researchers developed computational models to identify massage businesses at risk of violating laws related to sex and labor trafficking. The models provide probability scores on the likelihood that a business is engaged in illegal activity, allowing law enforcement and organizations to prioritize investigations.
A breakthrough computer model from Chalmers University of Technology reveals the properties of an atomic nucleus, providing insights into the strong force that governs neutron star behavior. The model predicts a surprisingly thin neutron skin, which could lead to increased understanding of heavy element creation in neutron stars.
Researchers created living brain cells in a dish that can perform goal-directed tasks and adapt to changes, opening doors for new understanding of brain function. The study also raises possibilities for alternative animal testing and biomimetic research.
Researchers from McGill University and MIT developed an AI system that can learn the rules and patterns of human languages on its own. The model automatically generates higher-level language patterns that can be applied to different languages, achieving better results.
A new study led by PSU researchers finds that climate models can accurately simulate large-scale weather patterns over the Pacific Northwest. The study uses data from the state-of-the-art CMIP6 model and machine learning techniques to compare model outputs with historical observed data, finding a strong match between the two.
Researchers from the University of Tokyo simulated fracture in amorphous solids to better understand material fatigue. They found that the critical strain for irreversible deformation is the same for both fatigue and monotonic fractures.
Researchers at North Carolina State University developed a blueprint for incorporating ethical guidelines into AI decision-making programs. The new mathematical formula, based on the Agent, Deed, and Consequence (ADC) Model, considers intent, character, and consequences of actions to make more informed decisions.
New research highlights the dangers of AI-powered recruitment tools that claim to remove discrimination from hiring. The tools reduce race and gender to trivial data points and often rely on personality analysis that is
Scientists at the University of Pittsburgh create microcapsules that exhibit life-like autonomy through self-generated motion and chemical signals. The system mimics protocell behavior, showcasing the potential for simple mechanisms to produce complex biological functions.
A new study proposes a powerful computer-modeling approach to cell simulations, reaching unprecedented simulation timescales at all-atom resolution. The technique combines advantages of protein docking and molecular simulations, enabling faster and more precise treatment of human disease.
Researchers developed a new technique that enables on-device training using less than a quarter of a megabyte of memory, reducing the need for powerful computers and central servers. This approach preserves privacy by keeping data on the device, making deep learning more accessible for low-power edge devices.
Researchers mapped the spread of pathogens in wild macaque populations near human settlements, finding that monkeys with high human interactions cause larger outbreaks. The study used computer simulations to predict disease transmission and identified key factors influencing outbreak size.
Researchers used advanced imaging techniques to understand the structure of bacterial propellers, which are made of a single protein. The study reveals that bacteria push themselves forward by coiling these appendages into corkscrew shapes, and that similar structures have evolved independently in archaea.
Researchers suggest special blood vessels called 'retia mirabilia' reduce brain pressure pulses, preventing damage. Computer modeling supports theory, which could be applied to other animals and humans.
A new study reveals that just five US universities have trained 1-in-8 tenure-track faculty members, highlighting the dominance of academic pedigree in academia. The research also shows that academics from less prestigious schools are more likely to leave the field and face limited job opportunities at elite institutions.
Researchers developed a machine learning algorithm that can generate a continuous 3D model of cells from a partial set of 2D images. The neural field network learns a mapping from spatial coordinates to physical quantities, allowing for smooth zooming and no pixelation.
University of Rochester researchers have quantified the energy of ocean currents larger than 1,000 kilometers using a coarse-graining technique. The most energetic current is the Antarctic Circumpolar Current, spanning 9,000 kilometers.
A new study developed an analytical model that can predict Lyme disease bacteria distribution and abundance on the landscape. The research found that climate and habitat disturbance were key factors in determining infectivity rates.
Researchers developed a unified machine learning model that analyzes data from patients with and without treatment, predicting depression outcomes better than separate models. The approach enables personalized medicine by designing treatment plans specific to each patient's needs.
The AI model, trained with end-to-end and multi-task manners, achieves best drivability in a standard simulation environment, outperforming recent models. It extracts useful information from a single RGBD camera and uses sensor fusion techniques to enhance performance.
Researchers at Drexel University have developed a computer model that uses machine learning algorithms to analyze the genetic sequence of the COVID-19 virus and predict the severity of new variants. The model provides an early warning system for public health officials, allowing them to prepare accordingly.
Researchers at Chalmers University of Technology developed a computer model to predict enzyme efficiency. This helps find efficient cell factories for producing biotech products like biofuels and medicines, and studies difficult diseases.
Scientists modeled how different coronavirus shapes affect rotational diffusivity, impacting transmission and infective success. The study found that more elongated shapes result in slower rotation rates, potentially improving attachment to cells.
A researcher will combine ARM data and fine-scale modeling datasets to understand marine boundary layer aerosol-cloud-precipitation interactions. The goal is to improve climate models' portrayal of cloud-processing of aerosols and address uncertainty in global climate models.
Researchers at the University of Oldenburg and Fraunhofer IWES collaborate on a new project to develop more accurate wind flow simulations using artificial intelligence. The goal is to reduce computing times and enhance precision, ultimately accelerating innovation in wind turbine design.
Researchers at MIT developed an AI model that can detect Parkinson's disease from breathing patterns, using a neural network to assess the presence and severity of the condition. The device is non-invasive and can be used in patients' homes without any bodily contact.
Researchers found that non-growing season nitrous oxide emissions in the Midwest can account for up to 60% of annual emissions. Environmental factors such as precipitation and temperature drive these emissions, with more intensive freezing causing increased emissions in the southeastern Midwest.