Towards Reversible Sessions

In this work, we incorporate reversibility into structured communication-based programming, to allow parties of a session to automatically undo, in a rollback fashion, the effect of previously executed interactions. This permits taking different computation paths along the same session, as well as reverting the whole session and starting a new one. Our aim is to define a theoretical basis for examining the interplay in concurrent systems between reversible computation and session-based interaction. We thus enrich a session-based variant of pi-calculus with memory devices, dedicated to keep track of the computation history of sessions in order to reverse it. We discuss our initial investigation concerning the definition of a session type discipline for the proposed reversible calculus, and its practical advantages for static verification of safe composition in communication-centric distributed software performing reversible computations.Comment: In Proceedings PLACES 2014, arXiv:1406.331

Scientific Visualization Using the Flow Analysis Software Toolkit (FAST)

Over the past few years the Flow Analysis Software Toolkit (FAST) has matured into a useful tool for visualizing and analyzing scientific data on high-performance graphics workstations. Originally designed for visualizing the results of fluid dynamics research, FAST has demonstrated its flexibility by being used in several other areas of scientific research. These research areas include earth and space sciences, acid rain and ozone modelling, and automotive design, just to name a few. This paper describes the current status of FAST, including the basic concepts, architecture, existing functionality and features, and some of the known applications for which FAST is being used. A few of the applications, by both NASA and non-NASA agencies, are outlined in more detail. Described in the Outlines are the goals of each visualization project, the techniques or 'tricks' used lo produce the desired results, and custom modifications to FAST, if any, done to further enhance the analysis. Some of the future directions for FAST are also described

Co-ordinating distributed knowledge: An investigation into the use of an organisational memory

This paper presents an ethnographically informed investigation into the use of an organisational memory, focusing in particular on how information was used in the performance of work. We argue that understanding how people make use of distributed knowledge is crucial to the design of an organisational memory. However, we take the perspective that an ‘organisational memory’ is not technology dependant, but is an emergent property of group interaction. In this sense, the technology does not form the organisational memory, but provides a novel means of augmenting the co-ordination of collaborative action. The study examines the generation, development and maintenance of knowledge repositories and archives. The knowledge and information captured in the organisational memory enabled the team members to establish a common understanding of the design and to gain an appreciation of the issues and concerns of the other disciplines. The study demonstrates why technology should not be thought of in isolation from its contexts of use, but also how designers can make use of the creative flexibility that people employ in their everyday activities. The findings of the study are therefore of direct relevance to both the design of knowledge archives and to the management of this information within organisations

Analyze Large Multidimensional Datasets Using Algebraic Topology

This paper presents an efficient algorithm to extract knowledge from high-dimensionality, high- complexity datasets using algebraic topology, namely simplicial complexes. Based on concept of isomorphism of relations, our method turn a relational table into a geometric object (a simplicial complex is a polyhedron). So, conceptually association rule searching is turned into a geometric traversal problem. By leveraging on the core concepts behind Simplicial Complex, we use a new technique (in computer science) that improves the performance over existing methods and uses far less memory. It was designed and developed with a strong emphasis on scalability, reliability, and extensibility. This paper also investigate the possibility of Hadoop integration and the challenges that come with the framework