Finally, the general framework given by (16) combines low- and high-level techniques.
In the second step, HL-KAOG employs the hybrid low- and high-level techniques to classify the test instances.
Cui, Jiang, Huang, Xu, Gui, and Zhang in "POS: A High-Level System to Simplify RealTime Stream Application Development on Storm" focus on efficient and high-level techniques for processing streaming data.
Two common approaches are often used, one based on low-level techniques to detect each object size, position and velocity, and other based on high-level techniques that deal with object appearance.
The science behind batteries, their quality testing, the prediction of their limits of use, safety features, calendar, and cycle life all require the establishment of well-defined and high-level techniques and procedures.
Part of the challenge with the higher-level techniques is that they involve not just universal teaching practices but actual math.
Thus, the proposed high-level technique works on the components instead of whole classes.
Thus, the high-level technique proposed here considers components instead of classes.
HL-KAOG takes advantages provided by the K-associated optimal graph and the high-level technique for data classification.
Again, considering Figure 1, the high-level technique is able to detect the pattern formed by gray cycle class and put the test instance into it.
For this reason, we propose a non-parametric network formation method based on the KAOG to work together with the high-level technique.
