Distributing Real Time Data From a Multi-Node Large Scale Contact Center Using Corba

This thesis researches and evaluates the current technologies available for developing a system for propagation of Real-Time Data from a large scale Enterprise Server to large numbers of registered clients on the network. The large scale Enterprise Server being implemented is a Contact Centre Server, which can be a standalone system or part of a multi-nodal system. This paper makes three contributions to the study of scalable real-time notification services. Firstly, it defines the research of the different technologies and their implementation for distributed objects in today\u27s world of computing. Secondly, the paper explains how we have addressed key design challenges faced when implementing a Notification Service for TAO, which is our CORBA-compliant real-time Object Request Broker (ORB). The paper shows how to integrate and configure CORBA features to provide real-time event communication. Finally, the paper analyzes the results of the implementation and how it compares to existing technologies being used for the propagation of Real-Time Data

Bivariate Interval-Censored Failure Time Data

This is the peer reviewed version of the following article: Cook, R. J., Zeng, L. and Lee, K.-A. (2008), A Multistate Model for Bivariate Interval-Censored Failure Time Data. Biometrics, 64: 1100–1109. doi: 10.1111/j.1541-0420.2007.00978.x, which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1111/j.1541-0420.2007.00978.x/abstract. This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving. The definitive version is available at http://onlinelibrary.wiley.com/doi/10.1111/j.1541-0420.2007.00978.x/abstract’Interval-censored life-history data arise when the events of interest are only detectable at periodic assessments. When interest lies in the occurrence of two such events, bivariate-interval censored event time data are obtained. We describe how to fit a four-state Markov model useful for characterizing the association between two interval-censored event times when the assessment times for the two events may be generated by different inspection processes. The approach treats the two events symmetrically and enables one to fit multiplicative intensity models that give estimates of covariate effects as well as relative risks characterizing the association between the two events. An expectation-maximization (EM) algorithm is described for estimation in which the maximization step can be carried out with standard software. The method is illustrated by application to data from a trial of HIV patients where the events are the onset of viral shedding in the blood and urine among individuals infected with cytomegalovirus.Natural Sciences and Engineering Research Council of Canada (RGPIN 155849); Canadian Institutes for Health Research (FRN 13887); Canada Research Chair (Tier 1) – CIHR funded (950-226626