Digital manufacturing technologies (DMTs) have the potential to transform industry productivity, but their introduction into workplace is often a complex process, requiring not only technical expertise also an awareness of ethical and societal challenges surrounding human–system integration. Concerns about new technology been prevalent throughout history, exploring public perceptions these can ...

In the ESP tradition, genre is often defined as “structured communicative events engaged in by specific discourse communities whose members share broad communicative purposes.” ESP genre research has generated numerous descriptions and explanations of discipline-specific genre exemplars and has produced various pedagogical proposals. However, what learners learn from these genre descriptions an...

We investigate the uses and limitations of MFCC analysis for feature extraction from music files in the domain of genre recognition. Intra-genre and Inter-genre classification is explored. We implement a method of genre classification based on MFCC extraction, K-means clustering, and KNN analysis. We demonstrate the efficacy of our method through testing, yielding a 99% accuracy rate.

This paper contributes to a facet from the area of Web Information Retrieval that has recently received much attention: The satisfaction of a user’s personal information need with respect to text type, presentation type, or information quality. We imply that such properties can be quantified for all kinds of Web documents, and we subsume them under the term “Web genre” or “genre”. Recent survey...

Existing systems for automatic genre classification follows a supervised framework that extracts genre-specific information from manually-labeled music data and then identifies unknown music data. However, such systems may not be suitable for personal music management, because manually labeling music based on individually-defined genres can be labor intensive and subject to inconsistence from t...