This document summarizes a thesis defense presentation. The presentation covered improving modeling notations so that non-IT readers can better understand models. Specifically, it discussed improving the SEAM notation through qualitative empirical research involving interviews of 200 participants. Based on feedback, the presentation proposed recommendations for model creation focusing on relation to reality, providing rationale, and telling a story through multiple model instances. It concluded the research was interdisciplinary and original in understanding readers' conceptualizations to create improved models. Future work could involve applying the recommendations to other contexts and notations or refining SEAM models.
Deep learning networks can be successfully applied to big data for knowledge discovery, knowledge application, and knowledge-based prediction. In other words, deep learning can be a powerful engine for producing actionable results.
This presentation is for my Computer Ed class and is about Emerging Technologies. The three technologies highlighted here are podcast, photo story and graphic organizers.
Computer vision is a prominent subset of artificial intelligence that can analyse and make sense of image and video data. Dr Tian Jing, Senior Lecturer & Consultant, Artificial Intelligence Practice will expand on recent advanced computer vision developments and key use cases in the new normal, such as social distancing in surveillance, hand hygiene monitoring in healthcare and more. This talk will also demonstrate examples of practice module projects of Intelligent Sensing Systems Graduate Certificate, offered by NUS-ISS in the past semesters.
My keynote talk at the 2007 IA Konferenz in Stuttgart, Germany, I argued we need to create fewer final designed artifacts and more tools to help everyone design. The audio can be downloaded from here: http://www.iavoice.com/2007/11/27/ia-konferenz-2007-keynote-english/
Traction User Group 2010 - Brian Tullis Presentationbtullis
Traction User Group 2010 meeting at Newport, RI. I gave this presentation on Observable Work, detailing my personal thoughts and showing examples within my organization. Be sure to view the speaker notes. Also check Twitter tags #Owork and #TUG2010.
Deep learning networks can be successfully applied to big data for knowledge discovery, knowledge application, and knowledge-based prediction. In other words, deep learning can be a powerful engine for producing actionable results.
This presentation is for my Computer Ed class and is about Emerging Technologies. The three technologies highlighted here are podcast, photo story and graphic organizers.
Computer vision is a prominent subset of artificial intelligence that can analyse and make sense of image and video data. Dr Tian Jing, Senior Lecturer & Consultant, Artificial Intelligence Practice will expand on recent advanced computer vision developments and key use cases in the new normal, such as social distancing in surveillance, hand hygiene monitoring in healthcare and more. This talk will also demonstrate examples of practice module projects of Intelligent Sensing Systems Graduate Certificate, offered by NUS-ISS in the past semesters.
My keynote talk at the 2007 IA Konferenz in Stuttgart, Germany, I argued we need to create fewer final designed artifacts and more tools to help everyone design. The audio can be downloaded from here: http://www.iavoice.com/2007/11/27/ia-konferenz-2007-keynote-english/
Traction User Group 2010 - Brian Tullis Presentationbtullis
Traction User Group 2010 meeting at Newport, RI. I gave this presentation on Observable Work, detailing my personal thoughts and showing examples within my organization. Be sure to view the speaker notes. Also check Twitter tags #Owork and #TUG2010.
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3) Climax
Are these models useful for you when create models with other people?
ü Before, during and after workshop - communication of business strategy
ü Identity of the notation - important for designer and modelers, not readers
ü Implicit elements - useful to learn about readers’ perceptions
ü Trade-off between abstraction (modelers) and concreteness (readers)
Prof. Alain Wegmann, Professor at EPFL and Consultant
Dr. Gil Regev, Senior Researcher at EPFL and Knowledge Manager at ITECOR
Mr. Didier Rey Marchetti, Vice-President for Information Systems Delegate at EPFL
Mr. Giorgio Anastopoulos, Head of Information Systems Architecture at EPFL
Mr. Olivier Hayard, Vice-President Head of Knowledge Management at ITECOR
Mr. Gaël de Fourmestraux, Head of Geneva Office at ITECOR
Discussion of Recommendations