Gets or sets the details of a column that stores the number of skipped (empty) levels between each member and its parent. Source Gets or sets the source of the attribute. TokenizationBehavior Gets or sets the tokenization behavior for this property. Translations Gets the collection of Transla...
<xsd:complexType name="Dimension"> <xsd:all> <!--These elements are common to each MajorObject--> <xsd:element name="Name" type="xsd:string" /> <xsd:element name="ID" type="xsd:string" minOccurs="0" /> <xsd:element name="CreatedTimestamp" type="xsd:dateTime" minOccurs="0" /...
The SkippedLevelsColumn property contains the column or attribute for the parent attribute that stores the number of skipped levels between each member and its parent member. This allows parent-child hierarchies that are based on the parent attribute to skip levels between members. The values ...
being the value of the quarter level. This behavior occurs because the grain of the data in the fact table is at the quarter level and the grain of the Date dimension is also at the quarter level. In Lesson 6, you will learn how to allocate the quarterly amount proportionally to each ...
Table 1 Signed percent variance in depressivity and anxiousness accounted for by AA at each electrode, bandwidth and measure split by gender. Full size table HFD predicts anxiousness A high level of inter-correlation of HFD between channels was observed. Due to this, a principle components analysi...
Now, if there are \(C_n\) cores on each node then each core on a particular node search for \(\frac{G}{N\cdot C_n}\) features if any of them intersect with the coastline vector. If the time taken to process G features using a single node with \(C_n\) cores is T then ...
'For Each' on type '<typename>' is ambiguous because the type implements multiple instantiations of 'System.Collections.Generic.IEnumerable(Of T)' For loop control variable '<variablename>' already in use by an enclosing For loop 'For' loop control variable already in use by an enclosing '...
For each sample-pair, n1 individuals X=(X1,…,Xn1) (sample 1) and n2 individuals Y=(Y1,…,Yn2) (sample 2) were generated according to p-dimension normal distribution N(μ1,Σ) and N(μ2,Σ), respectively. In this study, p=200 or 1000; n1=n2=50; Σ=Σa,b=(σij), where...
each other (Supplementary FigureS1). This finding indicated that the cell size was a more important correlate of the green fluorescence than was therfpexpression level. Therefore we removed this correlate from the green fluorescence data by subtracting a small correction, proportional to the cell ...
As computed tomography and related technologies have become mainstream tools across a broad range of scientific applications, each new generation of instrumentation produces larger volumes of more-complex 3D data. Lagging behind are step-wise improvement