Event counting

In waveform recovery mode the boxcar averager operates rather like a sampling device, with the gate delay being swept over a range of values while the output is recorded (the gate width should be sufficiently narrow to match the temporal variation in the waveform to be studied). The result is a point-by-point record of the input signal waveform. 

Event counting techniques, readily applicable to particle or photon counting measurements, offer several advantages in the measurement of extremely low signal levels (using suitable amplification electronics, single photons, electrons or ions can be detected). 

Commercial preamplifier-discriminator combinations come in both fixed threshold and variable threshold versions the former is normally optimized by the manufacturer. In practice, a discriminator threshold level of 2-20 mV offers optimal performance at a lower threshold the electronics would become susceptible to electric-noise interference, and higher thresholds would require higher gain to be achieved by the detector itself and by the preamplifier stage. 

Note that, since the pulse height Vjn is proportional to the detector gain (photomultiplier and channeltron alike), the setting of G will determine the fraction of the pulse height distribution that will exceed the threshold voltage, and hence the measured count rate. Thus, for example, for Vin to surpass typical discriminator thresholds in practice either the gain needs to be increased, or a xlO preamplifier is required (for the cited numerical example of a 2-20 mV signal). 

To avoid electrical interference, the amplifier and discriminator are best integrated into one electronic module, and the connection to the photon/particle detector should be as short as possible and well shielded. 

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Here the Any Event counts are placed before the body system and preferred term counts so that they appear first in the summary. At this point, the percentages are calculated by using n0, nl, and nt as denominators. The columns (coll-col3) are created and formatted as XXX (XXX%). Finally, the system and term variable is created as an index to keep the data grouped by preferred term in the output. 

This distribution function is shown in Figure 18.26. Note the most probable time between events is zero. Random events (counts, natural disasters, etc.) occur in bunches. ... 

O.H.W. Siegmund, J.V. Vallerga, A. Martin, et al., A high spatial resolution event counting neutron detector using microchannel plates and cross delay line readout. Nucl. Instrum. Methods, Sect. A 579, 188-191, (2007)... 

Since the TDC is a time counting device, when two or more ions arrive at the detector simultaneously in one flight cycle, the system counts them as one ion. In the same way, when two ions arrive at the detector in sequence within a certain interval, the system does not count the latter ion because the TDC is unable to register another count during the period after each ion event (counting dead time). Consequently, the dynamic range of this... 

Metadata(count) =data Metadata with data with event count Systolic BP(20) =140... 

Metadata(count) =timestamp Data with event count and metadata with universal timestamp. Systolic BP (20) =1984.64325... 

We assume that the event count from each study follows a binomial distribution. 

Several methods have been found adequate for low event count situations. For odds ratio summary measures, the Mantel-Haenszel, Peto, and exact methods appear to work well. The commonly used method in meta-analysis based on inverse variance weights does not perform well in low event count situations because the weights are not stable with low event counts. The Mantel-Haenszel risk difference appears to work well as well. This method has the added benefit in that unlike the methods for the odds ratio, this... 

If we embrace an abundant conception of properties, then there is a substantive question of which properties are such that they are constitutive properties of events. For example, if disjunction is a property-forming operation, and so there are disjunctive properties, it by no means follows that disjunctive properties can be constitutive properties of events. Also, even if complementation is a property-forming operation, and so there are negative properties, it is a nontrivial question whether negative properties can be constitutive properties of events — whether, that is, omissions are events. 1 will recur to these matters later. The point to note for now is that on an abundant conception of properties, no extant property exemplification account of events counts literally every property as such that it can be a constitutive (or essential) property of an event. One might embrace quantification as a property-forming operation but reject it as an eventforming operation and so reject the claim that functional properties can be constitutive properties of events. Whether functional properties can be constitutive properties of events, and so whether there are functional events in the sense in question, is a controversial issue. The issue, moreover, as I see, is inseparable from the issue of whether such entities would be causes. 

There is clear now that the Green function formalism do not automatically solve the initial Schrodinger problem, but replaces it with a more general one when also the causality of events counts. The passage from the retarded to advanced Green function equation can be easily made though the previously stipulated recipe. 

The efficiency is the quotient of the number of events (counts) registered by the detector and the number of gamma photons of given energy emitted by the radiation source. 

Section 11,6 reports on AE measurements in laboratory studies on rock specimens whose typical dimensions are in the centimetre or decimetre range. After an extensive overview about AE measurements on rock specimens (Subsection 11.6.1), fundamental relationships found from simple AE event counting will be presented in Subsection 11.6.2. Subsection... 

A Event counting, inelastic deformation, statistical analysis, Kaiser effect... 

Brown and Singh [1966] Bedford sandstone. Crab Orchard limestone, Chelmsford granite Uniaxial tension loading. Event counting, static fatigue... 

Soholz [1968b] Westerly granite, Rutland quartzite, Calcite marble, Colorado rhyolite tuff, Pottsville sandstone, San Marcos gabbro Uniaxial compression, Triaxial compression Event counting, statistic of AE... 

Alheid and Rummel [1977] Sandstone, Marble Triaxial compression Event counting, frictional sliding... 

Rong[1979] Jinan gabbro, Changpin granite Triaxial compression Event counting, fracture strength... 

Hirata [1987] Murata basalt Triaxial compression Event counting, statistic of AE... 

Glaser and Nelson [1992] Dolostone Granite Bending Event counting, event classification... 

Hashida and Takahashi[1993] lidate granite Fracture toughness lest Event counting, fracture toughness... 

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