Toward an understanding of the neural mechanisms underlying dual-task performance: Contribution of comparative approaches using animal models

The study of dual-task performance in human subjects has received considerable interest in cognitive neuroscience because it can provide detailed insights into the neural mechanisms underlying higher-order cognitive control. Despite many decades of research, our understanding of the neurobiological basis of dual-task performance is still limited, and some critical questions are still under debate. Recently, behavioral and neurophysiological studies of dual-task performance in animals have begun to provide intriguing evidence regarding how dual-task information is processed in the brain. In this review, we first summarize key evidence in neuroimaging and neuropsychological studies in humans and discuss possible reasons for discrepancies across studies. We then provide a comprehensive review of the literature on dual-task studies in animals and provide a novel working hypothesis that may reconcile the divergent results in human studies toward a unified view of the mechanisms underlying dual-task processing. Finally, we propose possible directions for future dual-task experiments in the framework of comparative cognitive neuroscience

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

Digital Forensics AI: on Practicality, Optimality, and Interpretability of Digital Evidence Mining Techniques

Digital forensics as a field has progressed alongside technological advancements over the years, just as digital devices have gotten more robust and sophisticated. However, criminals and attackers have devised means for exploiting the vulnerabilities or sophistication of these devices to carry out malicious activities in unprecedented ways. Their belief is that electronic crimes can be committed without identities being revealed or trails being established. Several applications of artificial intelligence (AI) have demonstrated interesting and promising solutions to seemingly intractable societal challenges. This thesis aims to advance the concept of applying AI techniques in digital forensic investigation. Our approach involves experimenting with a complex case scenario in which suspects corresponded by e-mail and deleted, suspiciously, certain communications, presumably to conceal evidence. The purpose is to demonstrate the efficacy of Artificial Neural Networks (ANN) in learning and detecting communication patterns over time, and then predicting the possibility of missing communication(s) along with potential topics of discussion. To do this, we developed a novel approach and included other existing models. The accuracy of our results is evaluated, and their performance on previously unseen data is measured. Second, we proposed conceptualizing the term “Digital Forensics AI” (DFAI) to formalize the application of AI in digital forensics. The objective is to highlight the instruments that facilitate the best evidential outcomes and presentation mechanisms that are adaptable to the probabilistic output of AI models. Finally, we enhanced our notion in support of the application of AI in digital forensics by recommending methodologies and approaches for bridging trust gaps through the development of interpretable models that facilitate the admissibility of digital evidence in legal proceedings

Technology and Australia's Future: New technologies and their role in Australia's security, cultural, democratic, social and economic systems

Chapter 1. Introducing technology -- Chapter 2. The shaping of technology -- Chapter 3. Prediction of future technologies -- Chapter 4. The impacts of technology -- Chapter 5. Meanings, attitudes and behaviour -- Chapter 6. Evaluation -- Chapter 7. Intervention -- Conclusion - adapt or wither.This report was commisioned by Australian Council of Learned Academies

“Scholarly Communications at Duke” Blog, December 2006-April 2016

This work contains all of the blog posts spanning the years 2006-2016 from the "Scholarly Communications @ Duke" blog by Kevin L. Smith, M.L.S, J.D. It is being made available in both PDF and XML formats to facilitate use of the material.The "Scholarly Communications at Duke" blog addressed current issues in scholarly communications, and also tried to provide information, from the most basic to complex issues, about how copyright law impacted higher education as it moved more fully into a digital age