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    METHODS, SYSTEMS, AND COMPUTER PROGRAM PRODUCTS FOR OPTIMIZATION OF PROBES FOR SPECTROSCOPIC MEASUREMENT IN TURBID MEDIA
    71.
    发明公开
    METHODS, SYSTEMS, AND COMPUTER PROGRAM PRODUCTS FOR OPTIMIZATION OF PROBES FOR SPECTROSCOPIC MEASUREMENT IN TURBID MEDIA 审中-公开
    方法，系统和计算机程序，以优化探针光谱测量在混浊介质

    公开(公告)号：EP1907825A2

    公开(公告)日：2008-04-09

    申请号：EP06800300.3

    申请日：2006-07-25

    Applicant: Duke University ,  WISCONSIN ALUMNI RESEARCH FOUNDATION

    Inventor： PALMER, Gregory, M. ,  RAMANUJAM, Nimala

    IPC: G01N21/47

    CPC classification number: G01N21/4738 ,  G01N2021/4742 ,  G01N2021/4752 ,  G01N2201/1296

    Abstract: The presently disclosed subject matter provides methods, systems, and computer program products for optimizing a probe geometry for spectroscopic measurement in a turbid medium. A probe geometry comprising one emitting entity for emitting electromagnetic radiation into a turbid medium and at least one collecting entity for collecting the electromagnetic radiation that has interacted with the turbid medium is selected. A simulation is performed with inputs of the probe geometry and a plurality of sets of optical property values associated with the turbid medium to generate output comprising optical parameter values measured by the probe geometry for each set of input optical property values. The measured optical parameter values are input to an Inversion algorithm to produce corresponding optical properties as output and are compared to reference values. The simulation and inversion steps are repeated and compared for a plurality of additional probe geometries and an optimal geometry is selected.

    PARALLEL OPTICAL THIN FILM MEASUREMENT SYSTEM FOR ANALYZING MULTIANALYTES
    73.
    发明公开
    PARALLEL OPTICAL THIN FILM MEASUREMENT SYSTEM FOR ANALYZING MULTIANALYTES 审中-公开
    并行光学薄膜测量系统分析多茴香醛

    公开(公告)号：EP3066595A1

    公开(公告)日：2016-09-14

    申请号：EP13899361.3

    申请日：2013-12-20

    Applicant: Halliburton Energy Services, Inc.

    Inventor： SKINNER, Neal G.

    IPC: G06F19/00

    CPC classification number: G01N21/31 ,  G01J3/00 ,  G01J3/2803 ,  G01J3/32 ,  G01J2003/1226 ,  G01N21/255 ,  G01N21/27 ,  G01N21/314 ,  G01N21/552 ,  G01N2201/06113 ,  G01N2201/062 ,  G01N2201/12 ,  G01N2201/1296 ,  G02B5/285

    Abstract: Optical computing devices including a light source that emits electromagnetic radiation into an optical train extending from the light source to a detector, a substance arranged in the optical train and configured to optically interact with the electromagnetic radiation and produce sample interacted radiation, a processor array arranged in the optical train and including a plurality of ICE arranged on a substrate and configured to optically interact with the electromagnetic radiation. The detector receives modified electromagnetic radiation generated through optical interaction of the electromagnetic radiation with the substance and the processor array. A weighting device is coupled to one or more of the ICE to optically apply a weighting factor to the modified electromagnetic radiation prior to being received by the detector, wherein the detector generates an output signal indicative of a characteristic of the substance based on beams of modified electromagnetic radiation.

    Abstract translation: 光学计算设备，其包括将电磁辐射发射到从光源延伸到检测器的光学系统中的光源，布置在光学系统中并被配置为与电磁辐射光学相互作用并产生样品相互作用的辐射的物质， 在光学系统中并且包括布置在基板上并被配置为与电磁辐射光学相互作用的多个ICE。 检测器接收通过电磁辐射与物质和处理器阵列的光学相互作用产生的修改的电磁辐射。 加权装置与ICE中的一个或多个耦合，以在由检测器接收之前将加权因子光学地应用于修改后的电磁辐射，其中检测器基于修改后的光束生成指示物质特性的输出信号 电磁辐射。

    DISCRIMINANT ANALYSIS USED WITH OPTICAL COMPUTING DEVICES
    74.
    发明公开
    DISCRIMINANT ANALYSIS USED WITH OPTICAL COMPUTING DEVICES 审中-公开
    判别与光计算机设备使用

    公开(公告)号：EP2984470A1

    公开(公告)日：2016-02-17

    申请号：EP13886539.9

    申请日：2013-06-07

    Applicant: Halliburton Energy Services, Inc.

    Inventor： PERKINS, David ,  CHEN, Dingding ,  JONES, Christopher, Michael ,  SHEN, Jing

    IPC: G01N21/17 ,  G06F19/00

    CPC classification number: G01V8/10 ,  G01N21/31 ,  G01N2201/1296

    Abstract: Disclosed are systems and methods that use discriminant analysis techniques and processing in order to reduce the time required to determine chemical and/or physical properties of a substance. One method includes optically interacting a plurality of optical elements with one or more known substances, each optical element being configured to detect a particular characteristic of the one or more known substances, generating an optical response from each optical element corresponding to each known substance, wherein each known substance corresponds to a known spectrum stored in an optical database, and training a neural network to provide a discriminant analysis classification model for an unknown substance, the neural network using each optical response as inputs and one or more fluid types as outputs, and the outputs corresponding to the one or more known substances.

    Classification and examination device of particles in fluid
    79.
    发明授权
    Classification and examination device of particles in fluid 失效
    在einerFlüssigkeit的Klassifikation undPrüfvorrichtungfürTeilchen

    公开(公告)号：EP0644414B1

    公开(公告)日：2001-11-21

    申请号：EP94112122.0

    申请日：1994-08-03

    Applicant: Hitachi, Ltd.

    Inventor： Asai, Hideki ,  Horiuchi, Hideyuki ,  Yabe, Ryohei ,  Oowada, Norio

    IPC: G01N15/14 ,  G01N15/00

    CPC classification number: G01N15/14 ,  G01N2201/1296 ,  G06F19/00 ,  G06K9/00127 ,  G06K9/2027 ,  Y10S706/924

    Abstract: A particle image in a sample 63 is formed at an imaging position 56 by an objective lens 55 of a microscope, projected on the image picking up plane of a TV camera 58 via projection lens 57 and is subjected to photo-electric conversion. Image signals from the TV camera 58 are supplied to an image memory 75 via an A/D converter 74 as well as to an image processing control unit 76. Image signals outputted from the image memory 75 are supplied to a characteristic picking out unit 78 and there a plurality of characteristics of the particle concerned are picked out. The picked-out characterstics are supplied to the classification unit 79 and there classification of the sediment components is performed via a neural network with a learning capability. Accordingly, the classification unit 79 performs provisionally an automatic classification of the objective sediment components by making use of the inputted characteristic parameters. Whereby the device which allows accurate and fast automatic component particle analysis even for patient specimens containing a variety of components in high concentration is realized.

    Abstract translation: 样品63中的颗粒图像通过显微镜的物镜55在成像位置56处通过投影透镜57投影在TV摄像机58的图像拾取面上并进行光电转换。 来自TV摄像机58的图像信号经由A / D转换器74以及图像处理控制单元76提供给图像存储器75.从图像存储器75输出的图像信号被提供给特征选择单元78和 选择有关颗粒的多个特征。 所选择的特征被提供给分类单元79，并且通过具有学习能力的神经网络执行沉积物分量的分类。 因此，分类单元79通过使用输入的特征参数临时执行目标沉积物成分的自动分类。 由此实现了即使对于含有高浓度的各种组分的患者标本也能进行准确和快速的自动组分颗粒分析的装置。

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