Matches in SemOpenAlex for { <https://semopenalex.org/work/W4294891799> ?p ?o ?g. }
Showing items 1 to 78 of
78
with 100 items per page.
- W4294891799 endingPage "15" @default.
- W4294891799 startingPage "1" @default.
- W4294891799 abstract "The importance of vocational efficiency has gradually grown in stature as a result of rapid population expansion, rapid urbanization, rising competitiveness in the labor market, and the growing requirement for specialist workforce. Around the world, there are several overarching trends in vocational education and training, including increased use of technology, increased relevance of information and communications systems and changes in country demographics. The main aim of this paper is to discuss a resource mining algorithm for vocational literacy-oriented civics courses. The exploratory data comes from a nearby vocational database partitioned into three segments: a record database, a data database, and a video database. The data sublibrary stores data like word-related types, collections, characters, archives, and photographs, though the video sublibrary stores general media data from the play. Indexes for both the data and video sublibraries can be found in the index sublibrary. In our proposed strategy for gathering vocational literacy resources on an organization stage, we have consolidated RFID remote sensor innovation with a remote organization convention stack. We utilized QGA to order the vocational literacy resources on the organization stage in light of the discoveries of the resource assortment. Besides, in the stage’s vocational literacy materials, we joined the fluffy property highlight ID strategy with the semantic affiliation elements of successive examples. The trial results show that this approach outflanks customary techniques as far as resource mining time, mining result breadth, and mining result exactness, demonstrating that this strategy has useful application esteem." @default.
- W4294891799 created "2022-09-07" @default.
- W4294891799 creator A5033798348 @default.
- W4294891799 date "2022-09-07" @default.
- W4294891799 modified "2023-09-26" @default.
- W4294891799 title "Resource Mining Algorithm and IoT Applications for Career Literacy Oriented Civics Courses" @default.
- W4294891799 cites W2050641370 @default.
- W4294891799 cites W2064640691 @default.
- W4294891799 cites W2169261845 @default.
- W4294891799 cites W2506364036 @default.
- W4294891799 cites W2532521045 @default.
- W4294891799 cites W2806778556 @default.
- W4294891799 cites W2953437648 @default.
- W4294891799 cites W2967097864 @default.
- W4294891799 cites W2992477483 @default.
- W4294891799 cites W3011588983 @default.
- W4294891799 cites W3080792179 @default.
- W4294891799 cites W3088678836 @default.
- W4294891799 cites W3093482340 @default.
- W4294891799 cites W3120231327 @default.
- W4294891799 cites W3121421997 @default.
- W4294891799 cites W3144651643 @default.
- W4294891799 cites W3155362250 @default.
- W4294891799 cites W3176632458 @default.
- W4294891799 cites W3216229089 @default.
- W4294891799 cites W3217110271 @default.
- W4294891799 cites W381354287 @default.
- W4294891799 cites W4200287842 @default.
- W4294891799 cites W4200351163 @default.
- W4294891799 cites W70755430 @default.
- W4294891799 cites W2119693557 @default.
- W4294891799 doi "https://doi.org/10.1155/2022/2957193" @default.
- W4294891799 hasPublicationYear "2022" @default.
- W4294891799 type Work @default.
- W4294891799 citedByCount "1" @default.
- W4294891799 countsByYear W42948917992023 @default.
- W4294891799 crossrefType "journal-article" @default.
- W4294891799 hasAuthorship W4294891799A5033798348 @default.
- W4294891799 hasBestOaLocation W42948917991 @default.
- W4294891799 hasConcept C144024400 @default.
- W4294891799 hasConcept C149923435 @default.
- W4294891799 hasConcept C19417346 @default.
- W4294891799 hasConcept C206345919 @default.
- W4294891799 hasConcept C2908647359 @default.
- W4294891799 hasConcept C31258907 @default.
- W4294891799 hasConcept C41008148 @default.
- W4294891799 hasConcept C547764534 @default.
- W4294891799 hasConcept C668760 @default.
- W4294891799 hasConcept C77088390 @default.
- W4294891799 hasConceptScore W4294891799C144024400 @default.
- W4294891799 hasConceptScore W4294891799C149923435 @default.
- W4294891799 hasConceptScore W4294891799C19417346 @default.
- W4294891799 hasConceptScore W4294891799C206345919 @default.
- W4294891799 hasConceptScore W4294891799C2908647359 @default.
- W4294891799 hasConceptScore W4294891799C31258907 @default.
- W4294891799 hasConceptScore W4294891799C41008148 @default.
- W4294891799 hasConceptScore W4294891799C547764534 @default.
- W4294891799 hasConceptScore W4294891799C668760 @default.
- W4294891799 hasConceptScore W4294891799C77088390 @default.
- W4294891799 hasLocation W42948917991 @default.
- W4294891799 hasOpenAccess W4294891799 @default.
- W4294891799 hasPrimaryLocation W42948917991 @default.
- W4294891799 hasRelatedWork W2126324482 @default.
- W4294891799 hasRelatedWork W2333699922 @default.
- W4294891799 hasRelatedWork W2349586403 @default.
- W4294891799 hasRelatedWork W2350548254 @default.
- W4294891799 hasRelatedWork W2354916129 @default.
- W4294891799 hasRelatedWork W2358178702 @default.
- W4294891799 hasRelatedWork W2365886438 @default.
- W4294891799 hasRelatedWork W2374354055 @default.
- W4294891799 hasRelatedWork W2392084717 @default.
- W4294891799 hasRelatedWork W3215543389 @default.
- W4294891799 hasVolume "2022" @default.
- W4294891799 isParatext "false" @default.
- W4294891799 isRetracted "false" @default.
- W4294891799 workType "article" @default.