Sentences with phrase «network modelling systems»

Not exact matches

QNX, which made more than 60 % of the core software inside the world's car infotainment systems in 2011, has partnered with The Weather Network to send location - based weather data to drivers, and the intelligent dashboard system in many of Nissan's 2013 models, for instance, will feed drivers real - time local fuel prices, flight - status information, and points of interest supplied by Google.

At Thunderhill, teams tested two technological approaches: Systems based on so - called neural networks modeled after the human brain and those based on computer vision.

Knight Point Systems can help by providing flexible pricing models that require no capital money, and which allow for scalability and flexible usage for compute, storage, networking, and software infrastructure.

«I was attracted to CMIT Solutions» innovative business model, comprehensive back - end training and support system, and expansive franchise network.

Shivom's comprehensive business model leverages game theory and network effects to establish a fully integrated healthcare service system with long - term sustainability and the possibility for users to monetize their data, by charging for usage»

Topics include word embeddings, recurrent neural network models, encoder - decoder architectures, attention models, architectures with external memories, and multimodal learning, including image and video captioning systems.

The infrastructure would ensure that programs are high quality, true to their intended model, and linked to other critical early childhood systems, thereby creating a seamless and holistic network of support for at risk families.

Ultimately we built a mathematical model of the mammalian circulatory system from scratch, working from basic physical laws that described networks, flow, and so on.

«We were able to develop this system once we made the breakthrough in using deep neural network models to separate speech.»

Fussenegger's group developed the genetic network; Professor of Biosystems Engineering Andreas Hierlemann and his team tested the acidity sensor with the aid of microfluidic platforms; and Jörg Stelling, a professor of computational systems biology, modelled it in order to estimate the dynamics of the insulin production.

Not surprisingly, the research is diverse, with projects ranging from neural network - based modeling of various systems to pulsed electric field treatment of food products.

«I wanted to do modeling of molecular biology and find out how we should put these networks of genes together conceptually to understand living systems.

One of Dozier's evolutionary computation projects uses the human immune system to model a network security system.

«Spin models are not only used in physics, but also to model other complex systems, such as neural networks, proteins or social networks.

We are next hoping to transfer this model to more complex food systems, such as batters for crêpes or puff pastry, in which dozens of chemical compounds come into play and affect the formation and properties of these networks of rigidity.

Along with my weekly issue of Science, I read books on management, social network analysis, and system - science modeling.

Their model uses computer learning systems called neural networks to spot promising fossil sites from satellite data.

It is my belief that novel insights regarding how such a network stabilizes, what is the magnitude and interaction of the different components and an ability to model such a system can help us sustain the oceanic wealth for the future generations.

Neural networks have been used for machine translation since at least 2010, and other features of the system have been employed in other models in the last several years.

In Remodeling of the Mononuclear Phagocyte Network Underlies Chronic Inflammation and Disease Progression in Heart Failure: Critical Importance of the Cardiosplenic Axis, Prabhu and colleagues showed that immune cells that are stored in the spleen were intricately involved in the heart failure that follows a heart attack, or infarction, in a mouse - model system.

... Accessing systems... cataloging human genomic data... compiling... analyzing... detecting essential genes... learning... modeling... accessing literature... tracking pathogens... outbreaks... viral interactions... RNAi... CRISPR... learning... modeling... analyzing social networks... crypto mining... ordering synthetic biopolymers... sending... waiting...

Now, developers are looking into bendable or foldable touch screens, systems that run solely on wi - fi networks, better battery life and solar - powered models.

«Network model of the musculoskeletal system predicts compensatory injuries: The authors» simplified musculoskeletal model could lead to clinical developments for testing therapeutic responses to injury.»

Network models of financial systems are useful for understanding the inter-connectedness of banks and the fragility of the banking system...

They have now modelled six neural networks, including one found in the insect olfactory system.

Using multiple model systems, they found that the low levels of DTNBP1 resulted in dysfunctional interneurons and over-activated neuronal network activity.

The approach combined experimental synthetic biology led by Mark Isalan, now Reader in Gene Network Engineering at the Department of Life Sciences of Imperial College London with computational modelling led by James Sharpe, ICREA Research Professor and head of the Multicellular Systems Biology lab at the CRG.

We then successfully developed a synthetic network engineering system and, finally, we confirmed all the new experimental data by fitting it to a single mathematical model» explains the corresponding author James Sharpe.

His lab's «empirical dynamic modeling» techniques use time - series data to look at the invisible ways these complicated systems are connected: like plucking one string out of a jumbled network and seeing which other strings echo back.

In models of Parkinson's disease, this system is thrown out of balance, leading to unidirectional changes in plasticity that could underlie network pathology and symptoms.

It is also the first to demonstrate that a deep convolutional neural network — a computing system modelled after the neuron activity in animal brains that can basically learn on its own — can effectively differentiate between similar plants with an amazing accuracy of nearly 100 %.

Current networks only model the «feedforward» projections from the retina to the IT cortex, but there are 10 times as many connections that go from IT cortex back to the rest of the system.

The article, which is authored by an interdisciplinary group of scientists from the fields of economics and banking, ecology, epidemiology, physics, computer science and sociology argues that applications of complex networks, agent - based models and laboratory experiments offer great potential to better grasp complex financial economic systems.

-- In silico basic and systems biology: We develop innovative approaches to reverse engineer biological networks from omics data, model tumor progression at the genomic, transcriptomic and epigenetic level, automatically annotate new proteins and functional elements through integration of complex and heterogeneous data, including data obtained from high - throughput sequencing or time - lapse video - microscopy.

These network models will help us to predict the functional effect of genetic variation, design interventions and therapies, and understand how living systems respond to changes in their environment.

We seek to elucidate the mechanistic underpinnings of state transitions and tipping points through multiscale characterizations of networks within model systems (organisms and communities).

In addition, the group has studied venation of tree leaves as a model system of a complex biological network with interesting topological and geometrical features, and has recently created methods to section whole rodent livers and reconstruct their three - dimensional vascular structure in unprecedented detail.

Our global aim is to reconstruct such networks by focusing on individual components (cells, soluble factors, membrane receptors), or by integrating multiple components using systems biology and modeling.

On the basis of analysis of this system, we proposed a model for filopodial formation in which actin filaments of a preexisting dendritic network are elongated by inhibition of capping and subsequently cross-linked into bundles by fascin.

These findings are consistent with the Interactive Brain Hypothesis and suggest a model of neural specializations for communication that links eye - to - eye contact and language systems via frontal, central, and temporal - parietal networks.

Networks exist in electrical circuits as well, so if we can model proteins using electrical circuits then we can better understand and predict behaviors of the biological systems.

In a paper published in 1987, he and his colleagues went on to unravel the details of a core network of interacting interneurons in the lamprey as a vertebrate model system.

As such, my group is highly interdisciplinary, combining immunology, pathology, genomics, bioinformatics, mathematical modeling, computer science, engineering, network analysis, and control systems.

In the P4 model, systems biology thinking and social networks will be key and the implications will be striking (including turning around the escalating costs of health care).

An Open Source CSG solid modeling system with ray tracing support for rendering and geometric analysis, network distributed framebuffer support, image

Actually, Netflix's business model proves the outdatedness of the network system, because in addition to the cast of «Orange,» Netflix knocked it out of the park with «House of Cards,» where even the good guys oozed moral ambiguity and made questionable decisions all while holding our attention (for some of us, holding our attention for 12 straight hours).

Using a deterministic (peer - to - peer) network model enables the game's synchronized gameplay animation, but requires parity on both systems.

Semantic models include «production systems, active structural networks, and propositional network» (Saettler, 2004, p. 327).

It may not, for example, be realistic to swap out all of a school's existing CCTV system for new models or to upgrade the capacity of a school's network for IP surveillance solutions.

What conditions (political, social, etc.) and strategies can districts and school networks pursue to foster the creation and spread of innovative, learner - centered models (learning environments / «schools») throughout their system?