Intelligent Solutions Inc.

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Intelligent Solutions Inc.

United States

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News Article | May 4, 2017
Site: www.PR.com

Xamarin recognizes Saviant as its Premier Consulting Partner, as it has demonstrated the best-in-class capabilities & expertise in the field of Mobility. North Port, FL, May 04, 2017 --( Saviant specializes in developing Xamarin mobile apps across iOS, Android and Windows using Xamarin Native, Xamarin Forms and Xamarin Mac. It has demonstrated the capabilities and expertise necessary to design, develop & deploy cross-platform mobile solutions for enterprise customers across industries. Hence, secured its spot amongst the very few Xamarin Premier Consulting Partners in US. Saviant combines the best practices, principles, and learnings to develop enterprise-grade mobile apps that help provide better customer service and enhance business growth. This new partnership with Xamarin is significant for the continued success of delivering robust cross-platform Xamarin mobile solutions to the enterprises globally. Thus, helping enterprises achieve better customer experience, enhance operational efficiency, maximize asset utilization, and real-time analytics for better decision making. About Saviant Consulting Saviant is 'The Intelligent Solutions company' and the Gold Cloud Platform & Gold Data Analytics Partner for Microsoft. We have pioneered innovative solutions leveraging Cloud, Mobility, Analytics & IoT to help Enterprises transform and modernize their business. We work with enterprises globally to define their technology road map & implementation strategy using multi-tenant SaaS applications, Native Mobile Apps, Big Data Analytics, IoT solutions & Azure PaaS Development. About Xamarin Xamarin is a California-based software company, recently acquired by Microsoft. It provides tools to develop native iOS, Android and Windows apps, allowing to share code across various platforms. Over 1 Mn+ developers are leveraging this platform to develop Xamarin mobile apps that provide world-class user experience. Some of the latest acquisitions by Xamarin include Visual Studio Extensibility Division, RoboVM AB, Clarius Consulting and LessPainful. North Port, FL, May 04, 2017 --( PR.com )-- Saviant announced that it has been recognized as a Xamarin Premier Consulting Partner. This achievement came soon after Saviant has attained the Microsoft Gold competency for Data Analytics. Xamarin Premier consulting partner program highlights the partners that have proven expertise in delivering Xamarin mobile solutions.Saviant specializes in developing Xamarin mobile apps across iOS, Android and Windows using Xamarin Native, Xamarin Forms and Xamarin Mac. It has demonstrated the capabilities and expertise necessary to design, develop & deploy cross-platform mobile solutions for enterprise customers across industries. Hence, secured its spot amongst the very few Xamarin Premier Consulting Partners in US.Saviant combines the best practices, principles, and learnings to develop enterprise-grade mobile apps that help provide better customer service and enhance business growth. This new partnership with Xamarin is significant for the continued success of delivering robust cross-platform Xamarin mobile solutions to the enterprises globally. Thus, helping enterprises achieve better customer experience, enhance operational efficiency, maximize asset utilization, and real-time analytics for better decision making.About Saviant ConsultingSaviant is 'The Intelligent Solutions company' and the Gold Cloud Platform & Gold Data Analytics Partner for Microsoft. We have pioneered innovative solutions leveraging Cloud, Mobility, Analytics & IoT to help Enterprises transform and modernize their business. We work with enterprises globally to define their technology road map & implementation strategy using multi-tenant SaaS applications, Native Mobile Apps, Big Data Analytics, IoT solutions & Azure PaaS Development.About XamarinXamarin is a California-based software company, recently acquired by Microsoft. It provides tools to develop native iOS, Android and Windows apps, allowing to share code across various platforms. Over 1 Mn+ developers are leveraging this platform to develop Xamarin mobile apps that provide world-class user experience. Some of the latest acquisitions by Xamarin include Visual Studio Extensibility Division, RoboVM AB, Clarius Consulting and LessPainful. Click here to view the list of recent Press Releases from Saviant Consulting


Ye X.,University of Pennsylvania | Chen J.,University of Pennsylvania | Engel M.,University of Michigan | Millan J.A.,University of Michigan | And 8 more authors.
Nature Chemistry | Year: 2013

Progress in nanocrystal synthesis and self-assembly enables the formation of highly ordered superlattices. Recent studies focused on spherical particles with tunable attraction and polyhedral particles with anisotropic shape, and excluded volume repulsion, but the effects of shape on particle interaction are only starting to be exploited. Here we present a joint experimental- computational multiscale investigation of a class of highly faceted planar lanthanide fluoride nanocrystals (nanoplates, nanoplatelets). The nanoplates self-assemble into long-range ordered tilings at the liquid-air interface formed by a hexane wetting layer. Using Monte Carlo simulation, we demonstrate that their assembly can be understood from maximization of packing density only in a first approximation. Explaining the full phase behaviour requires an understanding of nanoplate-edge interactions, which originate from the atomic structure, as confirmed by density functional theory calculations. Despite the apparent simplicity in particle geometry, the combination of shape-induced entropic and edge-specific energetic effects directs the formation and stabilization of unconventional long-range ordered assemblies not attainable otherwise. © 2013 Macmillan Publishers Limited.


Patent
Intelligent Solutions Inc. and University of Pennsylvania | Date: 2015-10-08

Monodisperse particles having: a single pure crystalline phase of a rare earth-containing lattice, a uniform three-dimensional size, and a uniform polyhedral morphology are disclosed. Due to their uniform size and shape, the monodisperse particles self assemble into superlattices. The particles may be luminescent particles such as down-converting phosphor particles and up-converting phosphors. The monodisperse particles of the invention have a rare earth-containing lattice which in one embodiment may be an yttrium-containing lattice or in another may be a lanthanide-containing lattice. The monodisperse particles may have different optical properties based on their composition, their size, and/or their morphology (or shape). Also disclosed is a combination of at least two types of monodisperse particles, where each type is a plurality of monodisperse particles having a single pure crystalline phase of a rare earth-containing lattice, a uniform three-dimensional size, and a uniform polyhedral morphology; and where the types of monodisperse particles differ from one another by composition, by size, or by morphology. In a preferred embodiment, the types of monodisperse particles have the same composition but different morphologies. Methods of making and methods of using the monodisperse particles are disclosed.


Patent
University of Pennsylvania and Intelligent Solutions Inc. | Date: 2011-10-03

Monodisperse particles having: a single pure crystalline phase of a rare earth-containing lattice, a uniform three-dimensional size, and a uniform polyhedral morphology are disclosed. Due to their uniform size and shape, the monodisperse particles self assemble into superlattices. The particles may be luminescent particles such as down-converting phosphor particles and up-converting phosphors. The monodisperse particles of the invention have a rare earth-containing lattice which in one embodiment may be an yttrium-containing lattice or in another may be a lanthanide-containing lattice. The monodisperse particles may have different optical properties based on their composition, their size, and/or their morphology (or shape). Also disclosed is a combination of at least two types of monodisperse particles, where each type is a plurality of monodisperse particles having a single pure crystalline phase of a rare earth-containing lattice, a uniform three-dimensional size, and a uniform polyhedral morphology; and where the types of monodisperse particles differ from one another by composition, by size, or by morphology. In a preferred embodiment, the types of monodisperse particles have the same composition but different morphologies. Methods of making and methods of using the monodisperse particles are disclosed.


Mohaghegh S.D.,Intelligent Solutions Inc. | Mohaghegh S.D.,West Virginia Universities
Journal of Natural Gas Science and Engineering | Year: 2011

In this paper a new class of reservoir models that are developed based on the pattern recognition technologies collectively known as Artificial Intelligence and Data Mining (AI&DM) is introduced. The workflows developed based on this new class of reservoir simulation and modeling tools break new ground in modeling fluid flow through porous media by providing a completely new and different angle on reservoir simulation and modeling. The philosophy behind this modeling approach and its major commonalities and differences with numerical and analytical models are explored and two different categories of such models are explained. Details of this technology are presented using examples of most recent applications to several prolific reservoirs in the Middle East and in the Gulf of Mexico.AI-based Reservoir Models can be developed for green or brown fields. Since these models are developed based on spatio-temporal databases that are specifically developed for this purpose, they require the existence of a basic numerical reservoir simulator for the green fields while can be developed entirely based on historical data for brown fields. The run-time of AI-based Reservoir Models that provide complete field responses is measured in seconds rather than hours and days (even for a multi-million grid block reservoir). Therefore, providing means for fast track reservoir analysis and AI-assisted history matching are intrinsic characteristics of these models. AI-based Reservoir Models can, in some cases, completely substitute numerical reservoir simulation models, work side by side but completely independent or be integrated with them in order to increase their productivity.Advantages associated with AI-based Reservoir Models are short development time, low development cost, fast track analysis and practical capability to quantify the uncertainties associated with the static model. AI-based Reservoir Model includes a novel design tool for comprehensive analysis of the full field and design of field development strategies to meet operational targets. They have open data requirement architecture that can accommodate a wide variety of data from pressure tests to seismic. © 2011 Elsevier B.V.


A computer system, comprising: one or more processors; and a memory coupled to the one or more processors, wherein the computer system is programmed with a set of computer-readable instructions configured to implement a method for determining a drill site in a shale, tight gas sands, coal bed methane or other unconventional well field for an oil or gas well and one or more parameter settings therefore, the computer-readable instructions comprising: one or more data mining instructions for data mining of a first part of a set of measurement or objective data parameters from existing oil or gas wells in the well field that, when executed, produce a ranking of each parameter and its respective effect on oil or gas well production from the well field; one or more training instructions that, when executed, produce a model comprising an artificial neural network (ANN) trained with the first part of the set of measurement or objective data parameters and/or the ranking that is useful for producing a group of optimized settings for one or more of the parameters for an estimated maximum output from one or more locations in the well field; and one or more calibration and/or validation instructions that, when executed, calibrate and/or validate the model using a second part of the set of measurement or objective data parameters from existing oil or gas wells in the well field.


Patent
Intelligent Solutions Inc. and Leiden University | Date: 2016-06-06

New methods and assays for multiplexed detection of analytes using phosphors that are uniform in morphology, size, and composition based on their unique optical lifetime signatures are described herein. The described assays and methods can be used for imaging or detection of multiple unique chemical or biological markers simultaneously in a single assay readout.


Patent
Intelligent Solutions Inc. | Date: 2012-10-05

This invention relates to a transparent or translucent transaction card having a base comprising a core of substantially transparent or translucent material with a plurality of coats, including optically recognizable ink comprising one or more infrared blocking dyes and other nanoparticles, such as rare earth nanophosphors and other metal nanoparticles, and/or optically recognizable film comprising nanoparticles, such as rare earth nanophosphors, and other metal oxide and/or non-oxide complexes, and methods for their preparation.


Patent
Intelligent Solutions Inc. | Date: 2015-10-23

This invention relates to a transparent or translucent transaction card having a base comprising a core of substantially transparent or translucent material with a plurality of coats, including optically recognizable ink comprising one or more infrared blocking dyes and other nanoparticles, such as rare earth nanophosphors and other metal nanoparticles, and/or optically recognizable film comprising nanoparticles, such as rare earth nanophosphors, and other metal oxide and/or non-oxide complexes, and methods for their preparation.


Patent
Intelligent Solutions Inc. | Date: 2014-07-28

This invention relates to a transparent or translucent transaction card having a base comprising a core of substantially transparent or translucent material with a plurality of coats, including optically recognizable ink comprising one or more infrared blocking dyes and other nanoparticles, such as rare earth nanophosphors and other metal nanoparticles, and/or optically recognizable film comprising nanoparticles, such as rare earth nanophosphors, and other metal oxide and/or non-oxide complexes, and methods for their preparation.

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