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This paper presents experimental results conducted on six ideation components (Provocative Stimuli, Suspend Judgment, Flexible Representation, Frame of Reference Shifting, Incubation, and Example Exposure).
In Figure 3b, each block of the block representation frame R t for I t is labeled in four different gray levels.
A 'block representation frame' stores information and tracks information fluxes along the whole process and plant life cycle and on different 'realization levels' from laboratory studies over miniplant validation to production plant design and operation.
Besides the Dirac dictionary, other three sparse dictionaries including Db6 wavelets, Sym4 wavelets and cubic B-spline functions can also accurately identify both the single and double impact forces from highly noisy responses in a sparse representation frame.
Then, the initial modeled background frame B ^ t (t = 2,3,…,19) is obtained based on the "updated" modeled background frame B t 1 (see Section 2.3) and the block motion representation frame R ^ t.
Figure 3 An illustrated example of block representation: (a) the current video frame; (b) the block representation frame; (c) templates for different blocks in (b). Figure 4 The flowchart of the proposed block representation approach.
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Figure 7 An illustrated example of background updating for two "moving object" blocks: (a) and (d) are two original video frames; (b) and (e) are the corresponding block representation frames; (c) and (f) are the corresponding modeled background frames.
Figure 2 An illustrated example of initial modeled background processing: (a - f) the origina - fdeo frames; (g)-(k) the bloriginalon representation frames; (l)-(q) the initial modeled background frames.
By extension, such representations frame rural LGBT youth as inherently "lacking" or "incomplete".
Such media representations frame a cultural paradigm in which there is an expectation that men may feel shame about or strive to conceal EDs, potentially contributing to men with EDs delaying help-seeking, gaining late access to treatments and reducing chances of successful outcomes.
Motivated by this observation, we model CU splitting decision as a binary classification problem. Figure 2 RDO on CU size in HM. Figure 3 CU representation of frame 40 of sequence "BasketballDrill" optimized by HM5.2.
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