Results 191 to 200 of about 412,797 (290)
Deep learning model using squeezenet and promoted ideal gas molecular motion for music genre classification from audio spectrograms. [PDF]
Sci RepXue M.
europepmc +1 more source
Children &Society, EarlyView.ABSTRACT The dominance of technology in the daily lives of modern‐day children has raised much concern about the impacts on their wellbeing. However, there are also many advantages and opportunities transpiring. This paper asks whether technology is an aid or an obstacle to a child's wellbeing and school life.
Sarah Holmes +4 more
wiley +1 more source
Body maps of the sensation of musical groove. [PDF]
PNAS NexusWitek MAG +3 more
europepmc +1 more source
‘We Teach Kids About It So They Don't Get Addicted’: Gender, Porn and Sex Education in New Zealand
Children &Society, EarlyView.ABSTRACT This research sought to explore young people's and teachers' understandings of porn. Drawing on a qualitative content analysis of small focus group interview data with 106 young people aged 12–16 years old and semi‐structured interviews with six teachers in Aotearoa, New Zealand, I examine their perceptions of porn and the place of porn in sex
Claire Meehan
wiley +1 more source
The price of fame? Mortality risk among famous singers. [PDF]
J Epidemiol Community HealthHepp J +3 more
europepmc +1 more source
Categorizing music by genres. [PDF]
Ann N Y Acad SciLange EB, Gernandt E, Merrill J.
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Music emotion classification based on random swap algorithm. [PDF]
Sci RepWiafe A, Sieranoja S, Fränti P.
europepmc +1 more source
"RaagaDhvani: A novel augmented multi-feature dataset: Advancing emotion recognition in Carnatic music with multimodal features and hybrid deep learning". [PDF]
Data BriefPriyadarshini A, Divakarla U.
europepmc +1 more source
Seventy-Five Years of the International Dental Journal: A Diamond Jubilee of Vision, Growth and Global Leadership. [PDF]
Int Dent JSamaranayake L, Sharkov N, Bondioni E.
europepmc +1 more source