A framework for distributed intelligent automation systems developments

This chapter proposes a simple and pragmatic framework that has been developed for classifying and analyzing developments in distributed automation and information systems - especially those that have been labelled intelligent systems for different reasons. The framework dissects the different stages in the standard feedback process and assesses distribution in terms of the level of granularity of the organization that is being considered. The framework has been found to be useful in comparing and assessing different distributed industrial control paradigms and also for examining common features of different development projects - especially those that might be sourced from different sectors or domains. © Springer-Verlag Berlin Heidelberg 2013.

Uncooled DBR laser directly modulated at 3.125 Gb/s as athermal transmitter for low-cost WDM systems

An uncooled three-section tunable distributed Bragg reflector laser is demonstrated as an athermal transmitter for low-cost uncooled wavelength-division-multiplexing (WDM) systems with tight channel spacing. A ±0.02-nm thermal wavelength drift is achieved under continuous-wave operation up to 70 °C. Dynamic sidemode suppression ratio of greater than 35 dB is consistently obtained under 3.125-Gb/s direct modulation over a 20 °C-70 °C temperature range, with wavelength variation of as low as ±0.2 nm. This indicates that more than an order of magnitude reduction in coarse WDM channel spacing is possible using this source. © 2005 IEEE.

Scaling the iHMM: Parallelization versus Hadoop

This paper compares parallel and distributed implementations of an iterative, Gibbs sampling, machine learning algorithm. Distributed implementations run under Hadoop on facility computing clouds. The probabilistic model under study is the infinite HMM [1], in which parameters are learnt using an instance blocked Gibbs sampling, with a step consisting of a dynamic program. We apply this model to learn part-of-speech tags from newswire text in an unsupervised fashion. However our focus here is on runtime performance, as opposed to NLP-relevant scores, embodied by iteration duration, ease of development, deployment and debugging. © 2010 IEEE.