A Framework to Manage the Complex Organisation of Collaborating: Its Application to Autonomous Systems

In this paper we present an analysis of the complexities of large group collaboration and its application to develop detailed requirements for collaboration schema for Autonomous Systems (AS). These requirements flow from our development of a framework for collaboration that provides a basis for designing, supporting and managing complex collaborative systems that can be applied and tested in various real world settings. We present the concepts of "collaborative flow" and "working as one" as descriptive expressions of what good collaborative teamwork can be in such scenarios. The paper considers the application of the framework within different scenarios and discuses the utility of the framework in modelling and supporting collaboration in complex organisational structures

Gesture Recognition and Control for Semi-Autonomous Robotic Assistant Surgeons

The next stage for robotics development is to introduce autonomy and cooperation with human agents in tasks that require high levels of precision and/or that exert considerable physical strain. To guarantee the highest possible safety standards, the best approach is to devise a deterministic automaton that performs identically for each operation. Clearly, such approach inevitably fails to adapt itself to changing environments or different human companions. In a surgical scenario, the highest variability happens for the timing of different actions performed within the same phases. This thesis explores the solutions adopted in pursuing automation in robotic minimally-invasive surgeries (R-MIS) and presents a novel cognitive control architecture that uses a multi-modal neural network trained on a cooperative task performed by human surgeons and produces an action segmentation that provides the required timing for actions while maintaining full phase execution control via a deterministic Supervisory Controller and full execution safety by a velocity-constrained Model-Predictive Controller

Discovering phase and causal dependencies on manufacturing processes

Discovering phase and causal dependencies on manufacturing processes. Keyword machine learning, causality, Industry 4.

Trust economics feasibility study

We believe that enterprises and other organisations currently lack sophisticated methods and tools to determine if and how IT changes should be introduced in an organisation, such that objective, measurable goals are met. This is especially true when dealing with security-related IT decisions. We report on a feasibility study, Trust Economics, conducted to demonstrate that such methodology can be developed. Assuming a deep understanding of the IT involved, the main components of our trust economics approach are: (i) assess the economic or financial impact of IT security solutions; (ii) determine how humans interact with or respond to IT security solutions; (iii) based on above, use probabilistic and stochastic modelling tools to analyse the consequences of IT security decisions. In the feasibility study we apply the trust economics methodology to address how enterprises should protect themselves against accidental or malicious misuse of USB memory sticks, an acute problem in many industries

Migrating Successful Student Engagement Strategies Online: Opportunities and Challenges Using Jigsaw Groups and Problem-Based Learning

Online courses may be criticized for failing to engage students. Faculty members teaching in the classroom often employ a number of strategies that capture the interest of students, but may find the migration to the online environment a daunting prospect. This paper describes the transitioning of two common strategies to engage students in the classroom – jigsaw groups and problem-based learning – from face-to-face to online courses in sociology and soil science, respectively. The paper discusses the challenges and opportunities that were found to be common to the implementation of both these strategies online, and provides suggestions for faculty considering this transition

TEAC 413M: Teaching Multilingual Learners in Content Areas – A Peer Review of Teaching Benchmark Portfolio

The purpose of this benchmark portfolio was to trace the process of designing, teaching and assessing TEAC 413M: Teaching Multilingual Learners in Content Areas, a required course for the B.Ed secondary education major. My objectives for this portfolio are to: a) document the impacts of different instructional strategies employed in TEAC 413M, and to b) reflect on the course success and shortcomings and develop pathways for the future course design and development. A secondary goal was to examine translation of course content into students’ own teaching and planning for their students through a variety of activities and assessments throughout the semester. Specific instructional procedures for the TEAC 413M included lecture-discussion method, biweekly reflections, jigsaws, search for and discussion of teaching materials that are linguistically and culturally appropriate for diverse learners, charting, small group discussions and asynchronous discussions. Assessment procedures included pre and post course surveys, inquiry activities, planning instruction and portfolios. Qualitative analysis of the collected data was carried out through content analysis. Results show substantial growth in different course focus areas as demonstrated in students work/artifacts

Robot-Assisted Minimally Invasive Surgical Skill Assessment—Manual and Automated Platforms

The practice of Robot-Assisted Minimally Invasive Surgery (RAMIS) requires extensive skills from the human surgeons due to the special input device control, such as moving the surgical instruments, use of buttons, knobs, foot pedals and so. The global popularity of RAMIS created the need to objectively assess surgical skills, not just for quality assurance reasons, but for training feedback as well. Nowadays, there is still no routine surgical skill assessment happening during RAMIS training and education in the clinical practice. In this paper, a review of the manual and automated RAMIS skill assessment techniques is provided, focusing on their general applicability, robustness and clinical relevance