The document is a questionnaire that asks respondents about their music preferences and consumption habits. It asks about their gender, age, preferred music genre, where they listen to music, what they expect from music videos of their preferred genre, how important album art is, whether they want to see artists in music videos, if they would buy a magazine with their favorite artist on the cover, how they would describe music videos of their preferred genre, if they like remixes of artists' music, and their monthly disposable income.
My life as a social radio presenter rick oshea rte @ Radio 2.0 2015ACTUONDA
My life as a social radio presenter for RTÉ
Rick O’Shea (animateur RTÉ, Irlande)
V rencontres Radio 2.0 - Mardi 13 octobre 2015
'La radio 2.0 et vous ? Raconte-moi une histoire'
www.rr20.fr
50 intervenants / 10 keynotes / 4 tables rondes / 7 workshops / 4 études exclusives
Grands Prix Radio 2.0 / La Radio des Rencontres
- Organisateurs : Nicolas Moulard / Actuonda, Xavier Filliol / Editions de l'Octet, Sacem Université, INA
- Partenaires Platinum : Mediametrie
- Partenaires Grand Prix : Scam, Multivote
- Partenaires Gold : Spotify, Deezer, Hyperworld, Musicovery, Targetspot, Triton Digital
- Partenaires Média : CBNews, La Lettre Pro de la Radio, RadioPub, Media +, Edition Multimedia, Satellinet, French Web, La Correspondance de la Publicité
- La Radio des Rencontres : Broadcast Associés, Radioline, Glowbl
My life as a social radio presenter rick oshea rte @ Radio 2.0 2015ACTUONDA
My life as a social radio presenter for RTÉ
Rick O’Shea (animateur RTÉ, Irlande)
V rencontres Radio 2.0 - Mardi 13 octobre 2015
'La radio 2.0 et vous ? Raconte-moi une histoire'
www.rr20.fr
50 intervenants / 10 keynotes / 4 tables rondes / 7 workshops / 4 études exclusives
Grands Prix Radio 2.0 / La Radio des Rencontres
- Organisateurs : Nicolas Moulard / Actuonda, Xavier Filliol / Editions de l'Octet, Sacem Université, INA
- Partenaires Platinum : Mediametrie
- Partenaires Grand Prix : Scam, Multivote
- Partenaires Gold : Spotify, Deezer, Hyperworld, Musicovery, Targetspot, Triton Digital
- Partenaires Média : CBNews, La Lettre Pro de la Radio, RadioPub, Media +, Edition Multimedia, Satellinet, French Web, La Correspondance de la Publicité
- La Radio des Rencontres : Broadcast Associés, Radioline, Glowbl
Opendatabay - Open Data Marketplace.pptxOpendatabay
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Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
Algorithmic optimizations for Dynamic Levelwise PageRank (from STICD) : SHORT...
Music questionnaire2015
1. Questionnaire
What is your gender?
• Female
• Male
What is your age?
• Under 15
• 16 – 25
• 26 – 35
• 36 – 45
• 46 and over
What is your preferred genre of music?
• Rock
• Indie
• Pop
• Rap
• Jazz
• Musicals
• RNB
• Reggae
• EDM
• Others (please specify) ………………………………
Where do you listen to your preferred genre of music? (please tick)
• Music store
• Radio
• Internet
• TV
• From friends
• Others (please specify) ………………………………
What do you expect to see in a music video of your preferred genre ?
…………………………………………………………………..
How important is the album art on the cover CD? (Please circle)
Insignificant 1 2 3 4 5 Very important
2. Would you want to see the artists within the music video?
• Yes
• No
Would you purchase a magazine if your favourite artist was on the cover?
…………………………………………………………………………
Describe how your specified genres video is? (Please circle)
Exciting 1 2 3 4 5 Dull
Sexy 1 2 3 4 5 Non-sexy
Happy 1 2 3 4 5 Depressing
Up-beat 1 2 3 4 5 Slow
Colourful 1 2 3 4 5 Pain
Bouncy 1 2 3 4 5 Flat
Meaningful 1 2 3 4 5 Meaningless
Do you like remix productions of artist’s music?
• Yes
• No
What is your monthly disposable income?
……………………………………………………….
