The Experts below are selected from a list of 1224 Experts worldwide ranked by ideXlab platform
Moore, Nicholas J. - One of the best experts on this subject based on the ideXlab platform.
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One Baptism Once: The Origins of the Unrepeatability of Christian Baptism
'Mohr Siebeck', 2020Co-Authors: Mills Lynn, Moore, Nicholas J.Abstract:This article questions the assumption that the uniqueness of Christian baptism goes back to the baptism of John. Against the backdrop of Jewish immersion baths, John's baptism was probably Repeatable. A two-stage development of Christian baptism, first to a one-time initiation rite and then to a non-Repeatable Event, is most likely based on the sources
Mills Lynn - One of the best experts on this subject based on the ideXlab platform.
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One Baptism Once: The Origins of the Unrepeatability of Christian Baptism
'Mohr Siebeck', 2020Co-Authors: Mills Lynn, Moore, Nicholas J.Abstract:This article questions the assumption that the uniqueness of Christian baptism goes back to the baptism of John. Against the backdrop of Jewish immersion baths, John's baptism was probably Repeatable. A two-stage development of Christian baptism, first to a one-time initiation rite and then to a non-Repeatable Event, is most likely based on the sources
David L. Brown - One of the best experts on this subject based on the ideXlab platform.
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Time Scale Re-Sampling to Improve Transient Event Averaging
2014Co-Authors: Jason R. Blough, Susan M. Dumbacher, David L. BrownAbstract:As the drive to make automobiles more noise and vibration free continues, it has become necessary to analyze transient Events as well as periodic and random phenomena. Averaging of transient Events requires a Repeatable Event as well as an available trigger Event. Knowing the exact Event time, the data can be post-processed by re-sampling the time scale to capture the recorded Event at the proper instant in time to allow averaging. Accurately obtaining the Event time is difficult given the sampling restrictions of current data acquisition hardware. This paper discusses the ideal hardware needed to perform this type of analysis, and provides analytical examples showing the transient averaging improvements using time scale re-sampling. These improvements are applied to noise source identification of a single transient Event using an arrayed microphone technique. With this technique, the averaging is performed using time delays between potential sources and microphones in the array. As a result, the relative time information needed is contained within the measured data and a separate trigger Event and Event time are not required
Jason R. Blough - One of the best experts on this subject based on the ideXlab platform.
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Time Scale Re-Sampling to Improve Transient Event Averaging
2014Co-Authors: Jason R. Blough, Susan M. Dumbacher, David L. BrownAbstract:As the drive to make automobiles more noise and vibration free continues, it has become necessary to analyze transient Events as well as periodic and random phenomena. Averaging of transient Events requires a Repeatable Event as well as an available trigger Event. Knowing the exact Event time, the data can be post-processed by re-sampling the time scale to capture the recorded Event at the proper instant in time to allow averaging. Accurately obtaining the Event time is difficult given the sampling restrictions of current data acquisition hardware. This paper discusses the ideal hardware needed to perform this type of analysis, and provides analytical examples showing the transient averaging improvements using time scale re-sampling. These improvements are applied to noise source identification of a single transient Event using an arrayed microphone technique. With this technique, the averaging is performed using time delays between potential sources and microphones in the array. As a result, the relative time information needed is contained within the measured data and a separate trigger Event and Event time are not required
Susan M. Dumbacher - One of the best experts on this subject based on the ideXlab platform.
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Time Scale Re-Sampling to Improve Transient Event Averaging
2014Co-Authors: Jason R. Blough, Susan M. Dumbacher, David L. BrownAbstract:As the drive to make automobiles more noise and vibration free continues, it has become necessary to analyze transient Events as well as periodic and random phenomena. Averaging of transient Events requires a Repeatable Event as well as an available trigger Event. Knowing the exact Event time, the data can be post-processed by re-sampling the time scale to capture the recorded Event at the proper instant in time to allow averaging. Accurately obtaining the Event time is difficult given the sampling restrictions of current data acquisition hardware. This paper discusses the ideal hardware needed to perform this type of analysis, and provides analytical examples showing the transient averaging improvements using time scale re-sampling. These improvements are applied to noise source identification of a single transient Event using an arrayed microphone technique. With this technique, the averaging is performed using time delays between potential sources and microphones in the array. As a result, the relative time information needed is contained within the measured data and a separate trigger Event and Event time are not required