Exact(2)
Experimental results on the downsampled KTH datasets (Tables 1 and 2) and the HMDB low-quality subsets (Table 4) showed that the combination of the robust BSIF-TOP dynamic textural feature with the base features (STIP or iDT) can surpass the recognition capability of combining with deeply learned object features.
It also suggests that this ability is likely rooted in a generalization process, based on the perceived similarity between the transformed and the originally learned object views.
Similar(58)
The relationship of learning object to learning objective is 1−1.
To test this, we used a virtual reality [7, 11, 26 28] task where participants learned object-location associations within two distinct virtual reality environments.
The nucleus of a learning object is a learning objective.
The data analysis showed that reflection tools, to a large extend, assist learning objective design decisions in learning object development.
When the learner clicks on any recommended learning object link then the learning object get opened.
Table 5 Task specification check learning object Task: check learning object Purpose: verification of learning object Responsible: Scrum Master Input Productct work: learning object developed Description: verification of learning object developed Output Product work: learning object Description: checking if the learning object is according to requirements.
SCORM LOM, namely learning object metadata, facilitates the indexing and searching of learning objects in a learning object repository through extended sharing and searching features.
Fig. 2 LODPRO: learning object's development process.
See Fig. 5 Fig. 5 Learning object structure.
Write better and faster with AI suggestions while staying true to your unique style.
Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com