Tasks, cognitive agents, and KB-DSS in workflow and process management

The purpose of this paper is to propose a nonparametric interest rate term structure model and investigate its implications on term structure dynamics and prices of interest rate derivative securities. The nonparametric spot interest rate process is estimated from the observed short-term interest rates following a robust estimation procedure and the market price of interest rate risk is estimated as implied from the historical term structure data. That is, instead of imposing a priori restrictions on the model, data are allowed to speak for themselves, and at the same time the model retains a parsimonious structure and the computational tractability. The model is implemented using historical Canadian interest rate term structure data. The parametric models with closed form solutions for bond and bond option prices, namely the Vasicek (1977) and CIR (1985) models, are also estimated for comparison purpose. The empirical results not only provide strong evidence that the traditional spot interest rate models and market prices of interest rate risk are severely misspecified but also suggest that different model specifications have significant impact on term structure dynamics and prices of interest rate derivative securities.

Autonomic Cloud Computing: Open Challenges and Architectural Elements

As Clouds are complex, large-scale, and heterogeneous distributed systems, management of their resources is a challenging task. They need automated and integrated intelligent strategies for provisioning of resources to offer services that are secure, reliable, and cost-efficient. Hence, effective management of services becomes fundamental in software platforms that constitute the fabric of computing Clouds. In this direction, this paper identifies open issues in autonomic resource provisioning and presents innovative management techniques for supporting SaaS applications hosted on Clouds. We present a conceptual architecture and early results evidencing the benefits of autonomic management of Clouds.Comment: 8 pages, 6 figures, conference keynote pape

Tasks, cognitive agents, and KB-DSS in workflow and process management

The purpose of this paper is to propose a nonparametric interest rate term structure model and investigate its implications on term structure dynamics and prices of interest rate derivative securities. The nonparametric spot interest rate process is estimated from the observed short-term interest rates following a robust estimation procedure and the market price of interest rate risk is estimated as implied from the historical term structure data. That is, instead of imposing a priori restrictions on the model, data are allowed to speak for themselves, and at the same time the model retains a parsimonious structure and the computational tractability. The model is implemented using historical Canadian interest rate term structure data. The parametric models with closed form solutions for bond and bond option prices, namely the Vasicek (1977) and CIR (1985) models, are also estimated for comparison purpose. The empirical results not only provide strong evidence that the traditional spot interest rate models and market prices of interest rate risk are severely misspecified but also suggest that different model specifications have significant impact on term structure dynamics and prices of interest rate derivative securities.

The business process modelling ontology

In this paper we describe the Business Process Modelling Ontology (BPMO), which is part of an approach to modelling business processes at the semantic level, integrating knowledge about the organisational context, workflow activities and Semantic Web Services. We harness knowledge representation and reasoning techniques so that business process workflows can: be exposed and shared through semantic descriptions; refer to semantically annotated data and services; incorporate heterogeneous data though semantic mappings; and be queried using a reasoner or inference engine. In this paper we describe our approach and evaluate BPMO through a use case

Enabling quantitative data analysis through e-infrastructures

This paper discusses how quantitative data analysis in the social sciences can engage with and exploit an e-Infrastructure. We highlight how a number of activities which are central to quantitative data analysis, referred to as ‘data management’, can benefit from e-infrastructure support. We conclude by discussing how these issues are relevant to the DAMES (Data Management through e-Social Science) research Node, an ongoing project that aims to develop e-Infrastructural resources for quantitative data analysis in the social sciences

Activity-Centric Computing Systems

• Activity-Centric Computing (ACC) addresses deep-rooted information management problems in traditional application centric computing by providing a unifying computational model for human goal-oriented ‘activity,’ cutting across system boundaries. • We provide a historical review of the motivation for and development of ACC systems, and highlight the need for broadening up this research topic to also include low-level system research and development. • ACC concepts and technology relate to many facets of computing; they are relevant for researchers working on new computing models and operating systems, as well as for application designers seeking to incorporate these technologies in domain-specific applications

Using a Model-driven Approach in Building a Provenance Framework for Tracking Policy-making Processes in Smart Cities

The significance of provenance in various settings has emphasised its potential in the policy-making process for analytics in Smart Cities. At present, there exists no framework that can capture the provenance in a policy-making setting. This research therefore aims at defining a novel framework, namely, the Policy Cycle Provenance (PCP) Framework, to capture the provenance of the policy-making process. However, it is not straightforward to design the provenance framework due to a number of associated policy design challenges. The design challenges revealed the need for an adaptive system for tracking policies therefore a model-driven approach has been considered in designing the PCP framework. Also, suitability of a networking approach is proposed for designing workflows for tracking the policy-making process.Comment: 15 pages, 5 figures, 2 tables, Proc of the 21st International Database Engineering & Applications Symposium (IDEAS 2017

Model-driven design, simulation and implementation of service compositions in COSMO

The success of software development projects to a large extent depends on the quality of the models that are produced in the development process, which in turn depends on the conceptual and practical support that is available for modelling, design and analysis. This paper focuses on model-driven support for service-oriented software development. In particular, it addresses how services and compositions of services can be designed, simulated and implemented. The support presented is part of a larger framework, called COSMO (COnceptual Service MOdelling). Whereas in previous work we reported on the conceptual support provided by COSMO, in this paper we proceed with a discussion of the practical support that has been developed. We show how reference models (model types) and guidelines (design steps) can be iteratively applied to design service compositions at a platform independent level and discuss what tool support is available for the design and analysis during this phase. Next, we present some techniques to transform a platform independent service composition model to an implementation in terms of BPEL and WSDL. We use the mediation scenario of the SWS challenge (concerning the establishment of a purchase order between two companies) to illustrate our application of the COSMO framework