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    • 52. 发明授权
    • Mössbauer spectroscopy system for applying external magnetic field at cryogenic temperature using refrigerator
    • 使用冰箱在低温下应用外部磁场的Mössbauer光谱系统
    • US08433380B1
    • 2013-04-30
    • US13338871
    • 2011-12-28
    • Chul-Sung KimBong-Yeon Won
    • Chul-Sung KimBong-Yeon Won
    • H01F39/00
    • G21K1/12
    • A Mössbauer spectroscopy system for applying an external magnetic field at cryogenic temperature using a refrigerator is provided. A Mössbauer spectrum can be obtained by applying the external magnetic field while changing the temperature of a superconducting magnet and a sample from a cryogenic temperature using the refrigerator, the external magnetic field can be applied while cooling the superconducting magnet using the refrigerator without the need for use of a liquid helium, thereby saving the operation cost according to consumption of the liquid helium, the mounting of a sample which it is desired to measure is easy, thereby minimizing a possibility that a worker will be exposed to gamma rays, and a convenience in use of a user can be improved.
    • 提供了一种使用冰箱在低温下施加外部磁场的莫斯堡分光系统。 通过在使用冰箱从低温温度改变超导磁体和样品的温度的同时施加外部磁场可以获得Mössbauer光谱,可以在使用冰箱冷却超导磁体的同时施加外部磁场,而不需要 使用液氦,从而根据液氦的消耗节省操作成本,因此希望测量的样品的安装容易,从而最小化了工作人员将会暴露于γ射线的可能性,并且方便 在使用中可以改善用户。
    • 57. 发明授权
    • Reliability measures for statistical prediction of geophysical and geological parameters in geophysical prospecting
    • 地球物理勘探地球物理和地质参数统计预报的可靠性测度
    • US06442487B2
    • 2002-08-27
    • US09729576
    • 2000-12-04
    • Chul-Sung Kim
    • Chul-Sung Kim
    • G01V150
    • G01V1/50G01V1/32
    • A method for assessing reliability of a prediction model constructed from N training data attribute vectors and N associated observed values of a specified parameter. Each training data attribute vector includes seismic attributes obtained from seismic data traces located at or near a well and each associated observed value is obtained from well log or core data from the well. A predicted value of the specified parameter is determined for each of the N training data attribute vectors, from the training data attribute vectors and the prediction model. A residual is determined for each of the N training data attribute vectors, as the difference between the associated observed value and the predicted value of the specified parameter for the training data attribute vector. An attribute vector for the designated location is determined.
    • 一种用于评估由N个训练数据属性向量和指定参数的N个相关观察值构建的预测模型的可靠性的方法。 每个训练数据属性向量包括从位于井或井附近的地震数据轨迹获得的地震属性,并且每个相关联的观测值从井的井测井或岩心数据获得。 根据训练数据属性向量和预测模型,针对N个训练数据属性向量中的每一个确定指定参数的预测值。 确定N个训练数据属性向量中的每一个的残差作为训练数据属性向量的相关观测值与指定参数的预测值之间的差。 确定指定位置的属性向量。