Articles tagged with Network Modeling
Researchers developed a theoretical framework to understand cooperation in competing populations, applying it to consensus votes and epidemic models. The model shows that long-range spatial correlations affect switching between cooperative and non-cooperative behavior.
Researchers develop mathematical model of animal social networks, finding that newborns copy their mother's connections to form social relationships. The study captures key properties of observed networks in four diverse species, suggesting a simple 'social inheritance' mechanism drives social structure.
A new multi-type queuing network analysis method can effectively allocate server resources in outpatient departments, reducing delays and improving patient treatment. The model considers different types of patients visiting service nodes in varying orders, providing a more accurate representation of real-world scenarios.
Researchers developed an electronic version of a logistic map that can interact with multiple maps, making it scalable. The model allows for the comparison of previous computer simulations with experimental results using state-of-the-art technology.
A new cloud software tool called EucaTool estimates eucalyptus production in Galicia. It allows users to calculate growth and future production by measuring four stand variables.
A Polish team has developed an analytical method to predict the h-index, a key scientific measurement, using bibliometric data. The study provides an exact formula to calculate external citations and self-citations for each paper written by an author, opening doors for growth analysis in social networks and different scientific fields.
Scientists at Los Alamos National Laboratory developed a new method to detect underground nuclear explosions by coupling seismic models with gas-flow models. The research improves the accuracy of predicting radionuclide gas transport through fracture networks, enabling better detection and concentration of gases.
New research using computer modeling shows that memory of one individual can indirectly influence another via shared social connections. Collaborative inhibition occurs when groups converge on similar information, limiting overall learning.
Terrence Sejnowski receives the Swartz Prize for his significant cumulative contribution to theoretical models and computational methods in neuroscience. He has made major research discoveries, including learning models for birdsong and neuroeconomics.
The Cornell Prison Education Program will expand to provide classes and degree programs in four regional prisons, establishing a model college-in-prison network. With a $1 million grant from The Andrew W. Mellon Foundation, the program aims to create a constructive pathway for incarcerated students.
A team of scientists has discovered that gene regulatory networks are inherently unstable, leading to aging and disease. Stabilizing these networks could lead to therapies against age-related diseases and increased lifespan.
Researchers propose a new mechanism to explain how financial crises happen, focusing on debt priorities and multiplex networks. They find that at least 50% of debts in the market should be senior debts to minimize systemic risk.
A recent article by Michael K. Gusmano and Frank J. Thompson examines the success of Medicaid's Delivery System Reform Incentive Payment Initiatives (DSRIP), finding mixed evidence on its effectiveness. The authors conclude that while DSRIP has potential, its effectiveness is still unclear.
A team of researchers from Indiana University and Switzerland used data mapping methods to track the spread of information on social networks and apply them to the human brain. The study reveals specific connections and nodes in the brain that may be responsible for higher forms of cognition.
A study analyzing classical music networks reveals the evolution of cultural styles and predictions for the recording market. The research, published in EPJ Data Science, uses modern data techniques to understand how composers collaborate and influence each other.
Researchers found a decline in cross-party voting and an increase in party-line voting among Congressional representatives over the past 60 years. The study used network modeling to identify patterns at the individual level, revealing that geography had little influence on voting behavior.
The study focuses on improving seismic monitoring data transmission speed and reducing response time to provide timely warnings for the region. Key findings include increasing station coverage, particularly in urban areas like Portland, Oregon, and strategically placing coastal stations to mitigate megathrust fault earthquakes.
A new model by Anna Nagurney adds a way to examine the value of stolen data over time, helping policymakers plan against future cyber attacks. The model captures network economics of cybercrime activity and permits policy evaluation of interventions.
The University of Texas at Austin's Center for Transportation Research is using advanced models to understand and visualize alternative solutions for traffic issues. A collaboration with the Texas Advanced Computing Center (TACC) has enabled faster simulations, allowing researchers to better analyze spatial data and gain clarity into t...
A $2.3 million network will investigate molecular mechanisms of rare diseases in yeast, worms, flies, fish, mice and humans. The goal is to understand disease mechanisms and identify therapeutic pathways for treatment.
Researchers at Notre Dame designed a highly accurate traffic prediction model that considers both time-based and distance-based costs. The model outperformed previous models when predicting commuter flows, demonstrating its potential to predict the impact of network disruptions.
The Carnegie Mellon team developed an algorithm that generates robust architectures for computer networks by analyzing the evolution of molecular connections in yeast cells. This approach can help understand how networks respond to cascading failures and external threats, offering insights into designing secure systems.
Researchers discovered that stroke patients' brains exhibit more complex functional network connectivity than healthy controls. The study also identified a compensation loop in the brain's functional network following stroke, suggesting its role in rehabilitation.
Researchers from Queen Mary University of London used mathematical models to analyze the resilience of European natural gas networks. They found that countries in Eastern Europe are less resilient to crises than their counterparts in Western Europe, with Ukraine and Belarus facing significant challenges.
Researchers used physical models to tackle the challenge of finding a suitable weekend for both parents in a recomposed family to see all their children at the same time. They found that minimizing energy in a material model is equivalent to maximizing parent-child time, and developed an algorithm to achieve this.
The Ecuadorian Ministry of Health is scaling up an essential obstetric and newborn care (EONC) model, improving maternal and newborn health services across the country. The model, piloted in Cotopaxi province, has yielded significant improvements in practices to improve the health of mothers and newborns.
Researchers developed a new framework to analyze ad hoc networks with fluctuating link quality, providing mathematical bounds on message propagation efficiency. The framework describes algorithms that can achieve maximal efficiency using randomness and adversarial relationships.
Brazilian physicists Thiago Silva and Diego Amancio devised a method to disambiguate words with multiple meanings by analyzing their connections in literary classics. Their approach, based on deterministic tourist walks, showed significant accuracy rates comparable to traditional semantic-based methods.
A mathematical model analyzes the spread of energy-efficient technologies in a community, highlighting the role of social networks and personal factors. The study provides tools for local authorities to assess the success of intervention strategies and reduce household energy bills and carbon emissions.
Researchers are using engineering control theory to create complex brain models that can simulate neurological diseases. By simplifying these models and fusing them with real system measurements, they aim to develop more accurate treatments for conditions such as epilepsy and Parkinson's disease.
A new approach uses partial differential equations to model pollution spread and identify potential contamination sources. The method provides fast solutions, but more complex models are needed for realistic networks.
Researchers at North Carolina State University have developed a new method for forecasting seasonal hurricane activity that outperforms traditional techniques by 15%. The approach identifies key combinations of factors most predictive of hurricane activity and provides a probability scale for the forthcoming season. With an 80% accurac...
Biologists at Caltech created a computational model of gene networks that control the development of sea-urchin embryos. The model accurately reproduces experiments and allows for virtual experiments, revealing unprecedented detail about gene regulatory networks.
A new model ranks US airports in terms of their spreading influence, with Honolulu surprisingly ranking third due to its location and connections. The study could inform vaccine allocation strategies and national security agencies.
The MU researcher's network model can analyze complex networks to identify the most damaging cyber attacks, protect critical infrastructure, and halt disease epidemics. By understanding network resilience, officials can prevent future problems and make informed decisions for conservation projects.
Scientists have discovered that even slight stimuli can change the information flow in the brain by altering the temporal pattern of communication between brain areas. This reorganisation can be triggered at the right time, allowing for rapid changes in perception.
Research on funding models in primary care practices found no association with superior preventive care delivery. Instead, female physicians, smaller patient loads, and electronic reminders were linked to better health outcomes.
Researchers develop an integrated statistical framework to model multiple relationships of different types on a common set of actors. The study found that common factors determined the likelihood of relationship formation, including geographical proximity and online popularity. The model accurately predicted relationships in networks, ...
Researchers at Case Western Reserve University have developed virtual brain models that reveal structural differences among healthy and ill brains. The models show that complex network connections are associated with normal EEG patterns, while simpler networks are linked to neurological disorders such as epilepsy and schizophrenia.
Archaeologist C. Michael Barton is revolutionizing the field of archaeological modeling by integrating new methods with a radical shift in thought. His research suggests that even small communities can experience significant environmental impacts from practices like shifting cultivation and grazing.
A EUREKA-backed project, TRAMMS, aimed to solve Internet bottlenecks by monitoring traffic over three years. The team gained insight into user behavior and accurately measured network traffic, enabling service providers to avoid bottlenecks and improve web browsing quality.
Researchers used data from Bureau Van Dijk and the SIR model to identify countries with greatest potential to cause a global crash. The top twelve countries include Belgium and Luxembourg alongside more obviously impactful economies.
A new tool has been developed to tackle tuberculosis by integrating genomic and metabolic data, enabling cell-scale simulations and biological strain design. The probabilistic regulation of metabolism (PROM) algorithm accurately predicts knockout phenotypes 95% of the time, paving the way for targeted research during dormancy.
The NSF has announced four new projects worth up to $8 million each to explore new internet architectures that can meet the challenges of the 21st century. The projects will focus on developing a more trustworthy and scalable network architecture.
The Virginia Bioinformatics Institute's COPASI software package has been made open source, allowing global access and use. The new license agreement enables commercial users to freely use the software, while also enhancing its compatibility with other academic programs.
USC neuroscientists use new method to trace brain circuits, revealing a distributed network that overcomes local damage and has alternate pathways. The study suggests the brain may be more like the Internet than previously thought.
The Systems Biology Markup Language (SBML) has been widely adopted by the scientific community for sharing and evaluating models of biological processes. SBML's popularity is a validation of its usefulness, with over 500 citations in an online academic database.
Researchers at Kansas State University developed a predictive model to forecast the spread of foot-and-mouth disease. Their study found that preemptive vaccination is effective in halting the disease's spread when an outbreak is not in its epidemic stage.
A new computer security approach, called 'swarm intelligence,' uses digital ants to search for threats in large networks, adapting to changes and attracting human operators to investigate. This method promises to transform cyber security by rapidly responding to emerging threats and improving overall defense.
Researchers created a complete model of the bacterium Thermotoga maritima's central metabolic network, including three-dimensional protein structures. This breakthrough could help identify positive and adverse drug reactions and engineer bacteria to produce clean energy.
Researchers created a comprehensive model of the bacterium's central metabolic network, including protein structures and interactions. The study reveals essential protein shapes and connections to unique metabolites.
A VBI researcher has received $786,797 to develop high-performance computer models for studying infectious diseases. These simulations can provide important information before an outbreak happens, aiding policymakers in making informed decisions.
The Systems Biology Graphical Notation (SBGN) provides a standardized visual language for representing biological information, making it easier to exchange complex information. The new standard will benefit systems biologists working on various biochemical processes, including gene regulation, metabolism, and cellular signaling.
Researchers highlight algebraic models as a crucial tool for undergraduate biologists, allowing them to integrate mathematical modeling into their coursework. These models focus on the logic of network connections, making them accessible to students with limited mathematical background.
A rapid face recognition method has been developed that can accurately identify individuals despite disguises and varying lighting conditions. The new algorithm reduces computer power requirements without compromising accuracy, making it suitable for real-world applications such as border crossings and automated banking.
Researchers at the Virginia Bioinformatics Institute aim to create a petascale computational modeling environment to simulate billions of individuals in large social and information networks. This project seeks to improve agent-based modeling applications on 100,000+ processor architectures.
Researchers have discovered a new phenomenon in which super-connectivity is significantly delayed due to the introduction of randomness. The transition becomes instantaneous once it occurs, like crystallizing ice.
Researchers found that small habitat patches, when connected in a network, can support species requiring larger habitats and facilitate movement between patches. This approach offers a promising tool for preserving ecological functions in fragmented landscapes.
Researchers have developed a synthetic biology advance that creates a stable, fast and programmable genetic clock in E. coli cells. The clock's blink rate changes when temperature, energy source or other environmental conditions change, enabling the detection of environmental information.
Researchers create computer simulation that accurately predicts fish species diversity in river basins, identifying 'hot spots' for conservation. The model uses rainfall measurements and river network structure to forecast species abundance.