Sentences with phrase «data modeling methods»

Not exact matches

These methods clearly need rich data about customers, which can form the basis for modeling.

The highlight was working on a whole - of - life data project that involved constructing networks of environmental monitoring stations in the Australian outback, and then using the collected data to empirically model groundwater dynamics — which doesn't sound all that interesting, but was actually quite a departure from the generally accepted contemporary methods.

It simply applies rational methods in taking and analyzing data, following certain rules to assure that data are as free from error as possible, and checking the logic of our models to make sure they are self - consistent.

Indeed, both the level of organization of our major denominations and the method in which data are collected argue for societal models.

Griffin & Sherburne, New York: The Free Press, 1978, 5) Natural science uses this method applying paradigms or models derived from some special discipline to interpret larger vistas of data.

History based on the social - scientific interpretation of data is based on historical information along with comparative sociology and social psychology, cultural anthropology and any other cross-cultural methods that produce models based on inductive studies.

We all use fairly similar methods but with some differences in modelling assumptions and scope of data sources.

The best GPS fish finder models combine satellite data with other mapping methods so you can easily find areas that are clear of tangling weeds and debris and full of fish again and again.

Different modeling methods will require different kinds of data.»

With the aid of complex statistical techniques, he and his collaborators were able to identify the optimal evolutionary model, given the nature of the available data, and they employed a new method to correct for systematic errors.

«We need both, realistic model simulations and long - term data records, and really sophisticated analysis methods to produce reliable climate predictions.

This field data is used by the physicists to model typical disturbance scenarios and to train the system with the aid of complex mathematical methods.

By combining data on optometry patient's eyes with advanced computational methods, Indiana University researchers have created a virtual tissue model of diabetes in the eye.

To develop a more accurate method, Higgins and colleagues designed a mathematical model of glucose chemistry and red blood cell turnover and combined it with large data sets of patient glucose measurements.

French used numerical simulations to compute all components of the seismic waves, such as their scattering and diffraction, and tweaked the model repeatedly to fit recorded data using a method similar to statistical regression.

The method combines a model for systems such as weather or climate with real - world data points to develop predictions about the future.

«We will develope a series of computational methods for drug combination prediction, modeling and data analysis.

Replacement alternative methods include the use of data concerning the physicochemical properties of chemicals; predictions based on structure - activity relationships, including the use of qualitative and quantitative mathematical models; the biokinetic modelling of physiological, pharmacological, and toxicological processes; experiments on lower organisms not classed as?

The discrepancy in data from the Planck satellite with data from other methods may be just a mistake, or it may require adjusting the cosmological model of the universe, as Tom Siegfried explained in «Cosmic question...

Research areas include species for comparative research; phenotypic characterization; fitness, genome stability and lateral gene transfer; control of organismal traits; monitoring and surveillance; modeling and standardization of methods and data.

The study establishes a method for estimating UHI intensities using PRISM — Parameter - elevation Relationships on Independent Slopes Model — climate data, an analytical model that creates gridded estimates by incorporating climatic variables (temperature and precipitation), expert knowledge of climatic events (rain shadows, temperature inversions and coastal regimes) and digital elevaModel — climate data, an analytical model that creates gridded estimates by incorporating climatic variables (temperature and precipitation), expert knowledge of climatic events (rain shadows, temperature inversions and coastal regimes) and digital elevamodel that creates gridded estimates by incorporating climatic variables (temperature and precipitation), expert knowledge of climatic events (rain shadows, temperature inversions and coastal regimes) and digital elevation.

In the spirit of Lombardy's open innovation model, the Forum will feature professionals from diverse areas: responsible research and innovation; science and technology studies; public communication of science; participative and deliberative methods; public engagement; social innovation; social impact and its assessment; sociology of risk; sociology of science; technology assessment and governance; open innovation, science, and data; data ethics; and bioethics.

Researchers at Indiana University have predicted the popularity of new faces to the world of modeling with over 80 percent accuracy using advanced computational methods and data from Instagram.

While studying for his doctorate with the study's senior author, UC Berkeley Prof. Barbara Romanowicz, Lekic developed a method to more accurately model waveform data while still keeping computer time manageable, which resulted in higher - resolution images of the interaction between the layers of Earth's mantle.

«Scientists use Instagram data to forecast top models at New York Fashion Week: Method is 80 percent accurate in identifying most popular models for the following season.»

Previous methods for performing this type of tuning have either required extensive manual labor, or a large amount of very accurate observation data, which has limited the applicability of these models until now,» Doctoral student Antti Kangasrääsiö from Aalto University explains.

«We designed ASTM E3012 - 16 to let manufacturers virtually characterize their production processes as computer models, and then, using a standardized method, «plug and play» the environmental data for each process step to visualize impacts and identify areas for improving overall sustainability of the system,» Lyons said.

We developed a computational model that learns from the limited data we already have, and then allows us to screen potential candidates from a massive database of materials about a million times faster than current screening methods.»

«Our results show that the uncertainty estimates of greenhouse gas inventories depend on the calculation method and on how the input data for the model, such as weather and litterfall data, have been averaged,» says Aleksi Lehtonen, researcher at the Natural Resources Institute Finland (Luke).

Our new method enables learning accurate models for example using data on user devices without the need to reveal private information to any outsider,» Assistant Professor Antti Honkela of the University of Helsinki says.

Jiang and his team confirmed that the methods used to downscale each of the models had little to no effect on the data.

BLOOMINGTON, Ind. — By combining data on optometry patients» eyes with advanced computational methods, Indiana University researchers have created a virtual tissue model of diabetes in the eye.

Kamiel and Wei Yang and Yaolin Lin, associate professors at the Wuhan University of Technology in China developed a holistic and integrated model which considered the building enclosure, the mechanical systems, the external environment, the proportion of window opening and the shading factor based on data collected from 270 households including single and multiple units, as well as different heating methods.

The model was obtained with the help of magnetic field data measured at the Sun's surface and a high resolution adaptive calculation method.

Bato and her collaborators are among the first to test whether data assimilation, a method used to incorporate new measurements with a dynamical model, can also be applied in volcano studies to make sense of such satellite data.

Method development comprises construction and analysis of mathematical models that describe complex scientific, technical as well as socio - economic processes, the development of efficient algorithms for simulation or optimization of such models, accompanying development of visualization, large scale data management and data analysis techniques, and transfer of algorithms into efficient software and high performance computing techniques.

Our group gathers multi-disciplinary expertise aiming at developing methods and algorithms for extracting, analysing, and modeling spatial data from biological images.

These methods make use of modelling of the 3D structures of proteins and their ligands, and of original statistical approaches to the increasing amount of data on structures and interactions (Figure 1).

To investigate whether person - to - person spread of an infectious agent could fit the observed data, a simple susceptible — exposed — infected — recovered (SEIR) population disease model was built (SI Data and Methodata, a simple susceptible — exposed — infected — recovered (SEIR) population disease model was built (SI Data and MethoData and Methods).

Further research topics are statistical / computational methods to study complex experimental data (e.g. cellular genealogies) and image analysis procedures (e.g. model - based segmentation algorithms in the context of automatic single cell tracking).

Methods: Researchers Drs. Samson M. Hagos and L. Ruby Leung, atmospheric scientists at PNNL, surveyed tropical divergence in three global climate models, three global reanalyses (models corrected with observational data), and four sets of field campaign soundings.

The public disclosure of this expanded collaboration coincides with the publication in the peer reviewed journal Nature Methods of data showing new capabilities of the Lung - Chip technology to achieve accurate modeling of the human lung small airways.

Methods: The study combines computer modeling with satellite data over the Southern Ocean, the vast sea surrounding Antarctica.

Since joining McLean in 2011, Dr. Mintzopoulos has been developing and implementing MRS and MRI protocols for in vivo studies relevant to models of psychiatric / addiction and neurological conditions, as well as data processing and analysis methods.

Day 1 focused on methods for modeling transcriptional regulation, whilst day 2 examined techniques for analysing and visualising time series data.

By linking imaging methods to rock physics, and by discovering, understanding and modelling relations to other geological data, we will reduce the uncertainty associated with exploration through cover.

We focus on developing computational methods and tools for (a) analyzing large - scale gene expression data related to human cancer in search for gene markers and disease sub-categories, (b) identifying regulatory elements such as miRNA precursors and their targets in whole genomes of plants and mammals, (c) building theoretical models of gene regulatory networks.

Because the drug's mode of action was known and patients» response to treatment could be precisely monitored, Michor and colleagues used modeling methods and data from patients in a large clinical trial to identify a group of copiously self - renewing stem cells, which persist within the tumor, resist the drug, and sustain the cancer.

The method goes beyond what previous mathematical models were capable of by applying evolutionary information and using cell - based data.

Standardized exploration of physiological functions, scientific and ethical considerations, study design, analysis and data management, alternative imaging method tests / Preclinical approaches with mouse models, a first step toward the man, interest and limits