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    • 4. 发明申请
    • SELF-HEALING ELECTRICAL COMMUNICATION PATHS
    • 自助电气通讯系统
    • US20100122832A1
    • 2010-05-20
    • US12272616
    • 2008-11-17
    • Leonid BukshpunRanjit PradhanKang S. LeeThomas ForresterTomasz Jannson
    • Leonid BukshpunRanjit PradhanKang S. LeeThomas ForresterTomasz Jannson
    • H01B3/00A41D1/00
    • A41D1/005
    • Self-healing electrical garments and self-healing electrical conductors and components for use in electrical garments are provided. A communication medium of various forms is integrated into a garment seam that is used to join two or more portions of a garment. The communication media can be used to provide electrical or other electromagnetic connection for coupling among a plurality of electrical devices associated with the garment. The self-healing electrical conductor may be used as part of a garment portion or may be used as a joining fiber in a variety of techniques to join garment portions together. The self-healing electrical conductor comprises an electrical conductor, a conductive polymer immediately surrounding or adjacent to the electrical conductor, an insulator enclosing the electrical conductor and the conductive polymer.
    • 提供自愈式电气服装和自愈电导体和用于电气服装的部件。 将各种形式的通信介质集成到用于连接衣服的两个或更多个部分的衣服缝中。 通信介质可用于提供用于在与服装相关联的多个电气设备之间耦合的电气或其它电磁连接。 自修复电导体可以用作衣服部分的一部分,或者可以以各种技术用于连接衣服部分的连接纤维。 自修复电导体包括电导体,直接围绕或邻近电导体的导电聚合物,封闭电导体和导电聚合物的绝缘体。
    • 7. 发明申请
    • Lobster eye X-ray imaging system and method of fabrication thereof
    • 龙虾眼X射线成像系统及其制造方法
    • US20070025512A1
    • 2007-02-01
    • US11191095
    • 2005-07-27
    • Michael GertsenshteynThomas ForresterTomasz JannsonKang LeeGajendra Savant
    • Michael GertsenshteynThomas ForresterTomasz JannsonKang LeeGajendra Savant
    • G01N23/201
    • G01N23/203G21K1/06
    • A Lobster Eye X-ray Imaging System based on a unique Lobster Eye (LE) structure, X-ray generator, scintillator-based detector and cooled CCD (or Intensified CCD) for real-time, safe, staring Compton backscatter X-ray detection of objects hidden under ground, in containers, behind walls, bulkheads etc. In contrast to existing scanning pencil beam systems, Lobster Eye X-Ray Imaging System's true focusing X-ray optics simultaneously acquire ballistic Compton backscattering photons (CBPs) from an entire scene irradiated by a wide-open cone beam from one or more X-ray generators. The Lobster Eye X-ray Imaging System collects (focuses) thousands of times more backscattered hard X-rays in the range from 40 to 120 keV (or wavelength λ=0.31 to 0.1 Å) than current backscatter imaging sensors (BISs), giving high sensitivity and signal-to-noise ratio (SNR) and penetration through ground, metal walls etc. The collection efficiency of Lobster Eye X-ray Imaging System is optimized to reduce emitted X-ray power and miniaturize the device. This device is especially advantageous for and satisfies requirements of X-ray-based inspection systems, namely, penetration of the X-rays through ground, metal and other material concealments; safety; and man-portability. The advanced technology disclosed herein is also applicable to medical diagnostics and military applications such as mine detection, security screening and a like.
    • 基于独特龙虾眼(LE)结构的龙虾眼X射线成像系统,X射线发生器,基于闪烁体的检测器和冷却CCD(或强化CCD),用于实时,安全,凝视康普顿反向散射X射线检测 隐藏在地下的物体,容器,墙壁,舱壁等等。与现有的扫描笔束系统相比,龙虾眼X射线成像系统的真正的聚焦X射线光学器件同时从整个场景中获得弹道康普顿后向散射光子(CBP) 由来自一个或多个X射线发生器的宽开口锥形束照射。 龙虾眼X射线成像系统收集(聚焦)数千倍的背散射硬X射线,范围为40至120 keV(或波长λ= 0.31至0.1Å),比当前的后向散射成像传感器(BIS)高得多 灵敏度和信噪比(SNR),穿透地面,金属墙壁等。龙虾眼X射线成像系统的采集效率得到优化,可以减少放射X射线功率,使设备小型化。 该装置特别有利于并满足基于X射线的检测系统的要求,即通过地面,金属和其他材料隐藏穿透X射线; 安全; 和人的便携性。 本文公开的先进技术也适用于医疗诊断和军事应用,如矿山检测,安全检查等。
    • 8. 发明授权
    • Method of contaminant prediction
    • 污染物预测方法
    • US08914312B2
    • 2014-12-16
    • US13497145
    • 2010-09-24
    • Michael John McLaughlinSean Thomas ForresterLeslie Joseph Janik
    • Michael John McLaughlinSean Thomas ForresterLeslie Joseph Janik
    • G06F15/18G01N21/35G01N33/24
    • G01N21/359G01N21/3563G01N33/241G01N2201/129
    • Method of selectively predicting hydrocarbon concentration in a sample of unknown hydrocarbon concentration, by (i) separately subjecting two or more samples of known hydrocarbon concentration to infrared (IR) radiation, (ii) separately detecting an IR signal from the samples of known hydrocarbon concentration, (iii) analyzing the IR signals using a multivariate chemometric technique to produce a training data set, (iv) generating a predictive model for hydrocarbon concentration based on the training data set, (v) subjecting the unknown sample to infrared (IR) radiation, (vi) detecting an IR signal from the unknown sample, (vii) applying the predictive model to the IR signal from the unknown sample. Thereafter, as step (viii), hydrocarbon concentration in the unknown sample is selectively predicted.
    • 通过以下方式选择性地预测未知烃浓度的样品中的烃浓度的方法:(i)将已知烃浓度的两个或多个样品分别经受红外(IR)辐射,(ii)分别检测来自已知烃浓度的样品的IR信号 (iii)使用多变量化学计量技术分析IR信号以产生训练数据集,(iv)基于训练数据集生成烃浓度的预测模型,(v)将未知样品经受红外(IR)辐射 (vi)检测来自未知样品的IR信号,(vii)将该预测模型应用于来自未知样品的IR信号。 此后,作为步骤(viii),选择性地预测未知样品中的烃浓度。