Group photo of the crew team: Row one: Deb Bartle, Suzzanne Moore, Jen Voigt, Melissa Casperson, Kim Wilson, Khoo Guan Soon, Peter Hall, Elizabeth Beuson Row two: Jason Aults, Kim Arnold, Leilani Lehmann, Katie Spence, Christy Herrmann, Jenny Wunderle, Jeff Zangara, Coach Ted Swinford Row three: Donna Lepp, Mackeniz Pfeife, Jen Ellsworth, Mike Schaefer, Dan Scheib, Wayne Sorvels, Jen Fasnacht.

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Crew

Arnone, Ernest Nicholas · ScholarWorks (Central Washington University) · 1938

https://digitalcommons.cwu.edu/arnone/1122/thumbnail.jpg

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Crew

Peter W. Rea, David K. Irving · 2015

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Crew

, · Scholarly Commons - Susquehanna University Research (Susquehanna University) · 1997

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Crew

Swissair, Fotograf · 2016

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Crew

Bulletin of Miscellaneous Information (Royal Gardens Kew)

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Crew

Chen Liu, Beng Chin Ooi, Anthony K. H. Tung et al. · 2010

In Web 2.0, users have generated and shared massive amounts of resources in various media formats, such as news, blogs, audios, photos and videos. The abundance and diversity of the resources call for better integration to improve the accessibility. A straightforward approach is to link the resources via tags so that resources from different modals sharing the same tag can be connected as a graph structure. This naturally motivates a new kind of information retrieval system, named cross-modal resource search, in which given a query object from any modal, all the related resources from other modals can be retrieved in a convenient manner. However, due to the tag homonym and synonym, such an approach returns results of low quality because resources with the same tag but not semantically related will be directly connected as well. In this paper, we propose to build the resource graph and perform query processing by exploiting Wikipedia. We construct a concept middle-ware between the layer of tags and resources to fully capture the semantic meaning of the resources. Such a cross-modal search system based on Wikipedia, named Crew, is built and demonstrates promising search results.

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Crew

Phidal · Bulletin of Miscellaneous Information (Royal Gardens Kew) · 2004

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Crew

Bulletin of Miscellaneous Information (Royal Gardens Kew)

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VOCABULARY ELEMENTS IN CARTOONS "RAFADAN CREW, DIGITAL CREW, TRAFFIC CREW"

Beyza Nur KAPLAN, Fulya TOPÇUOĞLU ÜNAL · ZEITSCHRIFT FÜR DIE WELT DER TÜRKEN / JOURNAL OF WORLD OF TURKS · 2023

In this study, it is aimed to discuss how cartoons can benefit students to enrich their vocabulary by making determinations on the vocabulary in the cartoon series "Rafadan Crew, Digital Crew and Traffic Crew" and to make recommendations on the subject. The object of study of the study consists of the first five episodes of the three cartoon series, which are the continuation of each other, on the TRT Children's channel, which broadcast free-to-air on Turkish televisions between the years 2014 2023. These cartoons were chosen among the most watched cartoons by children in Turkey. Documentary scanning method was used to collect detailed data about cartoons and vocabulary. In the analysis of the collected data, frequency and content analyzes of the data analysis used in qualitative studies were used. For content analysis, vocabulary was defined as the main theme, terms, slang expressions, proverbs, idioms, reduplications, foreign words, stereotypes, and stereotypes (relationship) were defined as sub-themes. The data of the themes are expressed as frequency values according to the parts of the cartoon series. Then, the data related to the themes were formatted as tables. As a result, it was observed that the cartoon series preferred as the research group in this study would have a positive effect in terms of supporting students' vocabulary. Keywords: Vocabulary, cartoon, Rafadan Crew, Digital Crew, Traffic Crew.

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THE CREW Camera crew Sound crew Costume and make-up

2012

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