Visual analytics of flight trajectories for uncovering decision making strategies

In air traffic management and control, movement data describing actual and planned flights are used for planning, monitoring and post-operation analysis purposes with the goal of increased efficient utilization of air space capacities (in terms of delay reduction or flight efficiency), without compromising the safety of passengers and cargo, nor timeliness of flights. From flight data, it is possible to extract valuable information concerning preferences and decision making of airlines (e.g. route choice) and air traffic managers and controllers (e.g. flight rerouting or optimizing flight times), features whose understanding is intended as a key driver for bringing operational performance benefits. In this paper, we propose a suite of visual analytics techniques for supporting assessment of flight data quality and data analysis workflows centred on revealing decision making preferences

Knowledge-based System to Support Architectural Design. Intelligent objects, project net-constraints, collaborative work

The architectural design business is marked by a progressive increase in operators all cooperating towards the realization of building structures and complex infrastructures (Jenckes, 1997). This type of design implies the simulta-neous activity of specialists in different fields, often working a considerable dis-tance apart, on increasingly distributed design studies. Collaborative Architectural Design comprises a vast field of studies that em-braces also these sectors and problems. To mention but a few: communication among operators in the building and design sector; design process system logic architecture; conceptual structure of the building organism; building component representation; conflict identification and management; sharing of knowledge; and also, user interface; global evaluation of solutions adopted; IT definition of objects; inter-object communication (in the IT sense). The point of view of the research is that of the designers of the architectural arte-fact (Simon, 1996); its focus consists of the relations among the various design operators and among the latter and the information exchanged: the Building Objects. Its primary research goal is thus the conceptual structure of the building organ-ism for the purpose of managing conflicts and developing possible methods of resolving them

Virtual Organizational Learnign in Open Source Software Development Projects

We studied the existence of virtual organizational learning in open source software (OSS) development projects. Specifically, our research focused on learning effects of OSS projects and factors that affect the learning process. The number and percentage of resolved bugs and bug resolution time of 118 SourceForge.net OSS projects were used to measure the learning effects> Projects were characterized by project type, number and experience of developers, number of bugs, and bug resolution time. Our results provide evidence of virtual organizational learning in OSS development projects.Virtual organizational leraning: Organizational learning curve: Virtual organization: Open source software development: Project performance

Towards Autonomous Aviation Operations: What Can We Learn from Other Areas of Automation?

Rapid advances in automation has disrupted and transformed several industries in the past 25 years. Automation has evolved from regulation and control of simple systems like controlling the temperature in a room to the autonomous control of complex systems involving network of systems. The reason for automation varies from industry to industry depending on the complexity and benefits resulting from increased levels of automation. Automation may be needed to either reduce costs or deal with hazardous environment or make real-time decisions without the availability of humans. Space autonomy, Internet, robotic vehicles, intelligent systems, wireless networks and power systems provide successful examples of various levels of automation. NASA is conducting research in autonomy and developing plans to increase the levels of automation in aviation operations. This paper provides a brief review of levels of automation, previous efforts to increase levels of automation in aviation operations and current level of automation in the various tasks involved in aviation operations. It develops a methodology to assess the research and development in modeling, sensing and actuation needed to advance the level of automation and the benefits associated with higher levels of automation. Section II describes provides an overview of automation and previous attempts at automation in aviation. Section III provides the role of automation and lessons learned in Space Autonomy. Section IV describes the success of automation in Intelligent Transportation Systems. Section V provides a comparison between the development of automation in other areas and the needs of aviation. Section VI provides an approach to achieve increased automation in aviation operations based on the progress in other areas. The final paper will provide a detailed analysis of the benefits of increased automation for the Traffic Flow Management (TFM) function in aviation operations

Growing a Tree in the Forest: Constructing Folksonomies by Integrating Structured Metadata

Many social Web sites allow users to annotate the content with descriptive metadata, such as tags, and more recently to organize content hierarchically. These types of structured metadata provide valuable evidence for learning how a community organizes knowledge. For instance, we can aggregate many personal hierarchies into a common taxonomy, also known as a folksonomy, that will aid users in visualizing and browsing social content, and also to help them in organizing their own content. However, learning from social metadata presents several challenges, since it is sparse, shallow, ambiguous, noisy, and inconsistent. We describe an approach to folksonomy learning based on relational clustering, which exploits structured metadata contained in personal hierarchies. Our approach clusters similar hierarchies using their structure and tag statistics, then incrementally weaves them into a deeper, bushier tree. We study folksonomy learning using social metadata extracted from the photo-sharing site Flickr, and demonstrate that the proposed approach addresses the challenges. Moreover, comparing to previous work, the approach produces larger, more accurate folksonomies, and in addition, scales better.Comment: 10 pages, To appear in the Proceedings of ACM SIGKDD Conference on Knowledge Discovery and Data Mining(KDD) 201

Collaborative Gaze Channelling for Improved Cooperation During Robotic Assisted Surgery

The use of multiple robots for performing complex tasks is becoming a common practice for many robot applications. When different operators are involved, effective cooperation with anticipated manoeuvres is important for seamless, synergistic control of all the end-effectors. In this paper, the concept of Collaborative Gaze Channelling (CGC) is presented for improved control of surgical robots for a shared task. Through eye tracking, the fixations of each operator are monitored and presented in a shared surgical workspace. CGC permits remote or physically separated collaborators to share their intention by visualising the eye gaze of their counterparts, and thus recovers, to a certain extent, the information of mutual intent that we rely upon in a vis-à-vis working setting. In this study, the efficiency of surgical manipulation with and without CGC for controlling a pair of bimanual surgical robots is evaluated by analysing the level of coordination of two independent operators. Fitts' law is used to compare the quality of movement with or without CGC. A total of 40 subjects have been recruited for this study and the results show that the proposed CGC framework exhibits significant improvement (p<0.05) on all the motion indices used for quality assessment. This study demonstrates that visual guidance is an implicit yet effective way of communication during collaborative tasks for robotic surgery. Detailed experimental validation results demonstrate the potential clinical value of the proposed CGC framework. © 2012 Biomedical Engineering Society.link_to_subscribed_fulltex

The 'what' and 'how' of learning in design, invited paper

Previous experiences hold a wealth of knowledge which we often take for granted and use unknowingly through our every day working lives. In design, those experiences can play a crucial role in the success or failure of a design project, having a great deal of influence on the quality, cost and development time of a product. But how can we empower computer based design systems to acquire this knowledge? How would we use such systems to support design? This paper outlines some of the work which has been carried out in applying and developing Machine Learning techniques to support the design activity; particularly in utilising previous designs and learning the design process