28,224 research outputs found
Online Collaborative Editor
“Online collaborative editor” is a node.js based browser application that provides real time collaborative editing of files and improves pair programming. Current real time editors fail to provide simultaneous viewing and editing of files within the server and results in a complex version controlling system. Such systems are also vulnerable to deadlocks and race conditions. This project provides a platform for real time collaborative editors, which can support simultaneous editing and viewing of files and handle concurrency problems by using locking mechanism. The experiment results showed that node.js platform provides good performance for collaborative editing
Who Spoke What? A Latent Variable Framework for the Joint Decoding of Multiple Speakers and their Keywords
In this paper, we present a latent variable (LV) framework to identify all
the speakers and their keywords given a multi-speaker mixture signal. We
introduce two separate LVs to denote active speakers and the keywords uttered.
The dependency of a spoken keyword on the speaker is modeled through a
conditional probability mass function. The distribution of the mixture signal
is expressed in terms of the LV mass functions and speaker-specific-keyword
models. The proposed framework admits stochastic models, representing the
probability density function of the observation vectors given that a particular
speaker uttered a specific keyword, as speaker-specific-keyword models. The LV
mass functions are estimated in a Maximum Likelihood framework using the
Expectation Maximization (EM) algorithm. The active speakers and their keywords
are detected as modes of the joint distribution of the two LVs. In mixture
signals, containing two speakers uttering the keywords simultaneously, the
proposed framework achieves an accuracy of 82% for detecting both the speakers
and their respective keywords, using Student's-t mixture models as
speaker-specific-keyword models.Comment: 6 pages, 2 figures Submitted to : IEEE Signal Processing Letter
The Minimized Face of Internal Communication: An Exploration of How Public Relations Agency Websites Frame Internal Communication and its Connection to Social Media
Internal communication is increasingly vital to organizational success due to the influence of social media, yet it remains understudied within public relations research. Using a qualitative content analysis of 181 websites, this study examines how leading public relations agency websites frame the value of internal communication and its connection to social media. Findings reveal internal communication is largely missing from the frame. When explicitly referenced, it is mostly framed as synonymous with employee communication as a means for management to communicate to employees, though some portrayals are more robust. Websites frame internal communication’s value as enhancing financial outcomes by improving workplace culture, employee engagement, and workers’ willingness to support management’s preferred organization brand or reputation. Social media are disconnected from internal communication and are mostly framed as tools that require additional employee training to use in order to reach external audiences. A handful of agencies urge organizations to include social media and internal stakeholders within the internal communication function. Recommendations are made for future internal communication research and practice
Survivability in Time-varying Networks
Time-varying graphs are a useful model for networks with dynamic connectivity
such as vehicular networks, yet, despite their great modeling power, many
important features of time-varying graphs are still poorly understood. In this
paper, we study the survivability properties of time-varying networks against
unpredictable interruptions. We first show that the traditional definition of
survivability is not effective in time-varying networks, and propose a new
survivability framework. To evaluate the survivability of time-varying networks
under the new framework, we propose two metrics that are analogous to MaxFlow
and MinCut in static networks. We show that some fundamental
survivability-related results such as Menger's Theorem only conditionally hold
in time-varying networks. Then we analyze the complexity of computing the
proposed metrics and develop several approximation algorithms. Finally, we
conduct trace-driven simulations to demonstrate the application of our
survivability framework to the robust design of a real-world bus communication
network
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