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This solution adopt a double-layer index framework.
For simplicity, the compressed Octree is also called Octree in our cloud index framework.
Therefore, building a dynamic cloud storage index framework for multidimensional data is necessary.
Furthermore, an IT convergence index framework was developed for objectively analyzing the extent of IT convergence.
This study proposes a dynamic index framework for multidimensional data in a cloud environment called Skip-Octree.
This study provided a new multidimensional data index framework, called Skip-Octree, which combines the best features of two well-known data structures: Octree and skip lists.
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In this work, we introduce a main and total effect indices framework of global reliability sensitivity.
In this study, a new double-layer cloud indexing framework based on Octree and skip list is proposed.
In order to deal with transcription errors and OOV words, some modifications of the traditional vector space model (VSM) indexing framework [21] are proposed: confidence measures are taken into account in the index term weights, and a phonetic-based document retrieval technique, enabling to retrieve in a transcript the proper nouns contained in a synopsis, is also considered.
In this paper, we describe a user-centered design of an automated multifaceted concept-based indexing framework which analyzes the semantics of the Web image contextual information and classifies it into five broad semantic concept facets: signal, object, abstract, scene, and relational; and identifies the semantic relationships between the concepts.
The core components include the Assets Catalogue (for storing or linking to data, models and protocols), the Yellow Pages directory of consortium members and their expertise, the access control and versioning framework, the Investigations, Studies and Assays (ISA) infrastructure, the harvesting and indexing framework, and the APIs, interfaces and links to external systems biology resources.
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