scholarly journals Web Radio Automation for Audio Stream Management in the Era of Big Data

Information ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 205 ◽  
Author(s):  
Nikolaos Vryzas ◽  
Nikolaos Tsipas ◽  
Charalampos Dimoulas
Keyword(s):  
Digital Media ◽  
Speaker Recognition ◽  
Web Application ◽  
Clustering Algorithms ◽  
Radio Station ◽  
Classification Model ◽  
Speaker Diarization ◽  
Stream Management ◽  
Media Ecosystem ◽  
Audio Data

Radio is evolving in a changing digital media ecosystem. Audio-on-demand has shaped the landscape of big unstructured audio data available online. In this paper, a framework for knowledge extraction is introduced, to improve discoverability and enrichment of the provided content. A web application for live radio production and streaming is developed. The application offers typical live mixing and broadcasting functionality, while performing real-time annotation as a background process by logging user operation events. For the needs of a typical radio station, a supervised speaker classification model is trained for the recognition of 24 known speakers. The model is based on a convolutional neural network (CNN) architecture. Since not all speakers are known in radio shows, a CNN-based speaker diarization method is also proposed. The trained model is used for the extraction of fixed-size identity d-vectors. Several clustering algorithms are evaluated, having the d-vectors as input. The supervised speaker recognition model for 24 speakers scores an accuracy of 88.34%, while unsupervised speaker diarization scores a maximum accuracy of 87.22%, as tested on an audio file with speech segments from three unknown speakers. The results are considered encouraging regarding the applicability of the proposed methodology.

Curating the urban music festival: Festivalisation, the ‘shuffle’ logic, and digitally-shaped music consumption

2021 ◽  
pp. 136754942110086
Author(s):  
Paulo Nunes ◽  
Carolyn Birdsall
Keyword(s):  
Digital Media ◽  
Urban Space ◽  
Cultural Policy ◽  
Urban Environments ◽  
Radio Station ◽  
City Branding ◽  
Music Festivals ◽  
Music Festival ◽  
Urban Music ◽  
Cultural Intermediaries

In recent years, music festivals have grown in significance within local cultural policy, city branding and tourism agendas. Taking the Mexefest festival in Lisbon as a case in point, this article asks how, in the digital streaming era, music festivals in urban environments are framed, curated and experienced. Drawing on ethnographic fieldwork, our analysis examines how music festival programmers curate the urban festival experience, for both locals and tourists alike. First, we identify the emergence of urban music festivals in recent decades, and how modern festival programmes have adopted the cultural technique of the ‘shuffle mode’ as an influential principle. Second, we investigate the work of festival programmers through the lens of ‘cultural intermediaries’, and ask how their programming strategies, particularly through digital mobile media (such as music playlists), contribute to an aestheticised experience of the city during the festival. Third, we focus on how the Mexefest festival events are staged in tandem with brand activation by sponsors like mobile phone company Vodafone and their radio station Vodafone FM. In doing so, we highlight the participation of festival-goers through their embodied engagements with digital media, music listening and urban space, and evaluate the heuristic value of ‘shuffle curation’ as a tool for the understanding of music festivals as a distinctly global and networked form of leisure consumption in urban culture.

scholarly journals Cloud based Agile Methodology Test Automation for Web Application by Using Tanh Activated Clustering and Classification Model (TACC) in Machine Learning

Webology ◽  
2021 ◽  
Vol 18 (Special Issue 05) ◽  
pp. 1137-1157
Author(s):  
V. Vamsi Krishna ◽  
G. Gopinath
Keyword(s):  
Web Application ◽  
Web Applications ◽  
Cost Effective ◽  
Daily Basis ◽  
Automatic Testing ◽  
Classification Model ◽  
Test Case ◽  
Test Automation ◽  
The Status ◽  
Clustering And Classification

Automatic functional tests are a long-standing issue in software development projects, and they are still carried out manually. The Selenium testing framework has gained popularity as an active community and standard environment for automated assessment of web applications. As a result, the trend setting of web services is evolving on a daily basis, and there is a need to improve automatic testing. The study involves to make the system to understand the experiences of previous test cases and apply new cases to predict the status of test case using Tanh activated Clustering and Classification model (TACC). The primary goal is to improve the model's clustering and classification output. The outcomes show that the TACC model has increased performance and demonstrated that automated testing results can be predicted, which is cost effective and reduces manual effort to a greater extent.

scholarly journals ORFhunteR: an accurate approach for the automatic identification and annotation of open reading frames in human mRNA molecules

2021 ◽  
Author(s):  
Vasily V. Grinev ◽  
Mikalai M. Yatskou ◽  
Victor V. Skakun ◽  
Maryna K. Chepeleva ◽  
Petr V. Nazarov
Keyword(s):  
Single Molecule ◽  
Web Application ◽  
R Package ◽  
Nucleotide Sequences ◽  
Open Reading Frames ◽  
Classification Model ◽  
Automatic Identification ◽  
Large Set ◽  
Link Type ◽  
Reading Frames

AbstractMotivationModern methods of whole transcriptome sequencing accurately recover nucleotide sequences of RNA molecules present in cells and allow for determining their quantitative abundances. The coding potential of such molecules can be estimated using open reading frames (ORF) finding algorithms, implemented in a number of software packages. However, these algorithms show somewhat limited accuracy, are intended for single-molecule analysis and do not allow selecting proper ORFs in the case of long mRNAs containing multiple ORF candidates.ResultsWe developed a computational approach, corresponding machine learning model and a package, dedicated to automatic identification of the ORFs in large sets of human mRNA molecules. It is based on vectorization of nucleotide sequences into features, followed by classification using a random forest. The predictive model was validated on sets of human mRNA molecules from the NCBI RefSeq and Ensembl databases and demonstrated almost 95% accuracy in detecting true ORFs. The developed methods and pre-trained classification model were implemented in a powerful ORFhunteR computational tool that performs an automatic identification of true ORFs among large set of human mRNA molecules.Availability and implementationThe developed open-source R package ORFhunteR is available for the community at GitHub repository (https://github.com/rfctbio-bsu/ORFhunteR), from Bioconductor (https://bioconductor.org/packages/devel/bioc/html/ORFhunteR.html) and as a web application (http://orfhunter.bsu.by).

Urban Region Function Mining Service Based on Social Media Text Analysis

2021 ◽  
Vol 31 (04) ◽  
pp. 563-586
Author(s):  
Yanchun Sun ◽  
Hang Yin ◽  
Jiu Wen ◽  
Zhiyu Sun
Keyword(s):  
Social Media ◽  
Text Analysis ◽  
Human Activities ◽  
Web Application ◽  
Classification Model ◽  
Urban Region ◽  
Urban Regions ◽  
Social Media Text ◽  
Urban Function ◽  
High Level

Urban region functions are the types of potential activities in an urban region, such as residence, commerce, transportation, entertainment, etc. A service which mines urban region functions is of great value for various applications, including urban planning and transportation management, etc. Many studies have been carried out to dig out different regions’ functions, but few studies are based on social media text analysis. Considering that the semantic information embedded in social media texts is very useful to infer an urban region’s main functions, we design a service which extracts human activities using Sina Weibo ( www.weibo.com ; the largest microblog system in Chinese, similar to Twitter) with location information and further describes a region’s main functions with a function vector based on the human activities. First, we predefine a variety of human activities to get the related activities corresponding to each Weibo post using an urban function classification model. Second, urban regions’ function vectors are generated, with which we can easily do some high-level work such as similar place recommendation. At last, with the function vectors generated, we develop a Web application for urban region function querying. We also conduct a case study among the urban regions in Beijing, and the experiment results demonstrate the feasibility of our method.

scholarly journals Impact on Social Networking Sites Among the Women Undergraduate Students

2019 ◽  
Vol 8 (11S) ◽  
pp. 770-775
Keyword(s):  
Social Networking ◽  
Digital Media ◽  
Undergraduate Students ◽  
Social Networking Sites ◽  
Web Application ◽  
The Internet ◽  
Online Study ◽  
Undergraduate Women ◽  
Information Interaction ◽  
The Impact

The study has been used to explore the impact of social networking sites amongst the undergraduate women students. In the framework of existing digital media, social networking sites have been known as individuals, by means of the Internet and web application to converse in previously unfeasible ways. It can be predominantly effect of a culture-wide impression shift in the uses and potential of the internet itself. The objectives of the study are to ascertain the different type of social networking sites used by women undergraduate students to scrutinize the level of usage, reason of using social networking sites, to settle on the advantages of using social networking sites and to make out the dangers associated with social networking and to submit strategies to restructure such dangers. The descriptive design has been in use to get responses from a sample size of 115 women undergraduate students who were selected via random sampling techniques. The 115 respondents completed and returned the questionnaire precisely indicating 100% response rate. The outcome of the study discloses that all the women undergraduate students uses social networking sites to expand information, interaction with friends, connecting to their classmates for online study, discussing serious national issues and watching movies etc. There are many advantages of using social networking sites and their menaces combined with social networking and such dangers can be restructured using the strategies available in the work. From the findings, it was recommended that women undergraduate students should attend various awareness program to update on the negative aspects of social networking sites etc. Based on the findings suitable suggestions were also made

scholarly journals The genre repertoires of Norwegian beauty and lifestyle influencers on YouTube

2021 ◽  
Vol 42 (2) ◽  
pp. 168-184
Author(s):  
Aleksander Torjesen
Keyword(s):  
New Media ◽  
Digital Media ◽  
Qualitative Content Analysis ◽  
Genre Theory ◽  
User Generated Content ◽  
New Rhetoric ◽  
Cultural Phenomenon ◽  
Communicative Functions ◽  
Media Ecosystem ◽  
Production Practices

Abstract YouTube represents an increasingly popular cultural phenomenon in the contemporary Norwegian media landscape. Since the inception of the digital video platform over 15 years ago, personal videoblogging has emerged as one of its dominant types of user-generated content. In this article, I draw from New Rhetoric genre theory and netnographic approaches to explore the beauty and lifestyle sphere on YouTube, in which several emergent genres are situated within a new media ecosystem. Through a qualitative content analysis of seven established Norwegian YouTube channels, a total of 17 individual genres were identified. Furthermore, I elaborate upon how informational, instructional, and confessional communicative functions are utilised in audiovisual publications through conventionalised digital media production practices.

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