Brian J. d'Auriol, Ph.D.

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The Parameterized (LARPBS(p)) and The All-optical (OLARPBS) Linear Array with a Reconfigurable Pipelined Bus System Optical Bus Parallel Computing Model,

CSE 600 Research Seminar Talk, Friday, June 3, 2016, Academic Building B, Room 204, SUNY Korea.

Abstract Computing technologies and capabilities vary depending on computing eras, as exemplified from the 19th century mechanical computers to the 20th century electromechanical and electronic computers to the present day commercially ubiquitous microelectronic computers. Beyond microelectronics, optoelectronic technologies are already deployed in communications. Optical communications provide higher bandwidth, longer distance, decreased energy consumption, unregulated usage hence increased convenience and increased security over electrical-based systems. And, when combined with traditional computer interconnection networks, enable powerful communication intensive computing. Yet, optoelectronic computing suffers limitations due to signal conversion. All optical computing that combines optical communications with optical processing elements eliminates such limitations, but introduces a unique set of computing issues. This talk describes the two recently proposed models by the author: the Parameterized (LARPBS(p)) (2005) and The All-optical (OLARPBS) (2016) Linear Array with a Reconfigurable Pipelined Bus System Optical Bus Parallel Computing Model. This talk covers historical background, architectural and algorithmic details as well as current on-going research supplemented by recent results from SUNY Korea researchers together with future work with emphasis on the impact of computing in future optoelectronic and optical computing eras.


Engineering Insightful Serviceable Visualizations,

CSE 600 Research Seminar Talk, Friday, June 10, 2016, Academic Building B, Room 204, SUNY Korea.

Abstract The quest for knowledge and understanding underlies human curiosity. Knowledge and understanding acquisition is provided through perception of human sensory information; of which, human vision is singularly significant. A rich research and development history in visualization and related fields have provided models, techniques and systems aimed at harnessing the potential of human visual capability to facilitate increased learning and insight. The Engineering Insightful Serviceable Visualizations (EISV) model, proposed by the author in 2015 (currently under review) is based on investigating question-answer pairs and emphasizes understanding and knowledge acquisition achieved via insight and learning but which is impeded by confusion brought on by in-appropriateness, incoherence, anacolutha and non-sequiturs. The EISV model is widely applicable in any endeavor that couples human knowledge and understanding with information display. The EISV model consists of an integrated insightful model and a serviceable model and includes a visualization metric that relates insight, learning and confusion with characteristics of how much and how fast understanding and knowledge are acquired. The model entails two connected processes: a visualization process based on visualization media componentization followed by a human process consisting of perception, interpretation, understanding and knowledge acquisition. This talk firstly introduces a modern perspective of visualization in the context of knowledge and understanding, insight and learning. Next, details of the EISV model are discussed with examples. Lastly, as the EISV model forms the umbrella project under which many additional specific projects are currently under investigation, brief comments about the following projects are included: 1. Visualization Advanced Relation Model with applications in Korean-English translations, 2. Geometric Representation of Programs with applications in software design and coding, 3. Complex Dynamic System Visualization with applications in power grid failure modeling, 4. Art Fusion Visualization with applications in studying impression and emotional aspects, and 5. Visualization Experience with applications in studying human sensations arising during visualizations.

Last Updated: 2016.06.01