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    Measurement of Steam Quality Using Multiple Broadband Lasers
    31.
    发明申请
    Measurement of Steam Quality Using Multiple Broadband Lasers 有权
    使用多个宽带激光测量蒸汽质量

    公开(公告)号：US20070069132A1

    公开(公告)日：2007-03-29

    申请号：US11162969

    申请日：2005-09-29

    申请人： Chayan Mitra ,  Mark Woodmansee ,  Ayan Banerjee

    发明人： Chayan Mitra ,  Mark Woodmansee ,  Ayan Banerjee

    IPC分类号： G01J5/02

    CPC分类号： G01N21/39 ,  G01N21/3504 ,  G01N2021/354

    摘要： Determination of steam quality by passing one or more laser beams through steam in a steam chamber and directly determining a total number of vapor molecules and a total number of water molecules based on absorption of radiation in the one or more laser beams by the water vapor phase and the liquid water phase in the steam. Specific volumes of water vapor phase and liquid water phase in the steam using the total numbers of water vapor and liquid water molecules are determined and the quality of the steam is calculated based on the specific volumes of the water vapor phase and the liquid water phase in steam. One embodiment comprises a narrow linewidth laser for measuring steam quality and another embodiment comprises multiple broadband lasers for measuring steam quality.

    摘要翻译： 通过使一个或多个激光束通过蒸汽室中的蒸汽来确定蒸汽质量，并且基于通过水蒸气相在一个或多个激光束中的辐射的吸收直接确定蒸汽分子的总数和总分子数 和蒸汽中的液态水相。 确定蒸汽中水蒸气相和液态水相的体积，使用水蒸汽和液态水分子的总数，并根据水汽相和液态水相的体积计算蒸汽的质量 蒸汽。 一个实施例包括用于测量蒸汽质量的窄线宽激光器，另一个实施例包括用于测量蒸汽质量的多个宽带激光器。

    MOBILE MEDICAL APPLICATIONS WITH SEPARATED COMMUNICATION AND DEVELOPMENT ENVIRONMENT FOR THE SAME
    37.
    发明申请
    MOBILE MEDICAL APPLICATIONS WITH SEPARATED COMMUNICATION AND DEVELOPMENT ENVIRONMENT FOR THE SAME 有权
    移动医疗应用具有相同的通信和开发环境

    公开(公告)号：US20150309773A1

    公开(公告)日：2015-10-29

    申请号：US14694152

    申请日：2015-04-23

    申请人： Sandeep Gupta ,  Ayan Banerjee

    发明人： Sandeep Gupta ,  Ayan Banerjee

    IPC分类号： G06F9/44

    CPC分类号： G06F8/36 ,  G06F8/447 ,  G06Q50/22

    摘要： Systems and methods are provided for a mobile medical application operating environment and automated/semi-automated systems for creating application software for the operating environment. In the operating environment, all data storage and communication with external devices relating to sensitive medical data and operations is handled by a data manager application concurrently running with the medical application on a mobile device. Multiple medical applications can be run concurrently on the mobile device with reduced risk of data failure, thereby simplifying the design and release process for mobile medical applications.

    摘要翻译： 提供了用于移动医疗应用操作环境和用于为操作环境创建应用软件的自动/半自动化系统的系统和方法。 在操作环境中，与敏感医疗数据和操作有关的所有数据存储和与外部设备的通信由与移动设备上的医疗应用同时运行的数据管理器应用程序来处理。 多个医疗应用可以在移动设备上同时运行，降低数据故障的风险，从而简化了移动医疗应用的设计和发布过程。

    Model guided deep learning approach towards prediction of physical system behavior
    39.
    发明授权
    Model guided deep learning approach towards prediction of physical system behavior 有权

    公开(公告)号：US11443218B2

    公开(公告)日：2022-09-13

    申请号：US16226461

    申请日：2018-12-19

    申请人： Sandeep Gupta ,  Ayan Banerjee

    发明人： Sandeep Gupta ,  Ayan Banerjee

    IPC分类号： G06N7/00 ,  A61B5/00 ,  A61B5/145 ,  G06N3/08 ,  G06N20/10 ,  G06N3/04

    摘要： Systems and methods are provided for controlling predictive medical monitoring. A non-linear-predictive-guide model estimates a patient parameter that is used as a guide in a deep neural network for improving accuracy of estimation by the deep neural network. The guide model generates a guiding first estimated patient parameter based on the guide model and patient input data. The deep neural network generates a second estimated patient parameter based on the deep neural network, the patient input data, and the guiding first estimated patient parameter. The deep neural network includes an input layer that receives the guiding first estimated patient parameter, and hidden layers including respective artificial neurons configured to perform a linear or nonlinear transformation on output of at least one artificial neuron from an adjacent layer in the deep neural network. An output layer receives at least one output from a hidden layer.