172,304 research outputs found
Business process modelling and visualisation to support e-government decision making: Business/IS alignment
© 2017 Springer-Verlag. The final publication is available at Springer via https://doi.org/10.1007/978-3-319-57487-5_4.Alignment between business and information systems plays a vital role in the formation of dependent relationships between different departments in a government organization and the process of alignment can be improved by developing an information system (IS) according to the stakeholders’ expectations. However, establishing strong alignment in the context of the eGovernment environment can be difficult. It is widely accepted that business processes in the government environment plays a pivotal role in capturing the details of IS requirements. This paper presents a method of business process modelling through UML which can help to visualise and capture the IS requirements for the system development. A series of UML models have been developed and discussed. A case study on patient visits to a healthcare clinic in the context of eGovernment has been used to validate the models
Should the advanced measurement approach be replaced with the standardized measurement approach for operational risk?
Recently, Basel Committee for Banking Supervision proposed to replace all
approaches, including Advanced Measurement Approach (AMA), for operational risk
capital with a simple formula referred to as the Standardised Measurement
Approach (SMA). This paper discusses and studies the weaknesses and pitfalls of
SMA such as instability, risk insensitivity, super-additivity and the implicit
relationship between SMA capital model and systemic risk in the banking sector.
We also discuss the issues with closely related operational risk
Capital-at-Risk (OpCar) Basel Committee proposed model which is the precursor
to the SMA. In conclusion, we advocate to maintain the AMA internal model
framework and suggest as an alternative a number of standardization
recommendations that could be considered to unify internal modelling of
operational risk. The findings and views presented in this paper have been
discussed with and supported by many OpRisk practitioners and academics in
Australia, Europe, UK and USA, and recently at OpRisk Europe 2016 conference in
London
Digital service analysis and design : the role of process modelling
Digital libraries are evolving from content-centric systems to person-centric systems. Emergent services are interactive and multidimensional, associated systems multi-tiered and distributed. A holistic perspective is essential to their effective analysis and design, for beyond technical considerations, there are complex social, economic, organisational, and ergonomic requirements and relationships to consider. Such a perspective cannot be gained without direct user involvement, yet evidence suggests that development teams may be failing to effectively engage with users, relying on requirements derived from anecdotal evidence or prior experience. In such instances, there is a risk that services might be well designed, but functionally useless. This paper highlights the role of process modelling in gaining such perspective. Process modelling challenges, approaches, and success factors are considered, discussed with reference to a recent evaluation of usability and usefulness of a UK National Health Service (NHS) digital library. Reflecting on lessons learnt, recommendations are made regarding appropriate process modelling approach and application
Decline and repair, and covariate effects
The failure processes of repairable systems may be impacted by operational and environmental stress factors. To accommodate such factors, reliability can be modelled using a multiplicative intensity function. In the proportional intensity model, the failure intensity is the product of the failure intensity function of the baseline system that quantifies intrinsic factors and a function of covariates that quantify extrinsic factors. The existing literature has extensively studied the failure processes of repairable systems using general repair concepts such as age-reduction when no covariate effects are considered. This paper investigates different approaches for modelling the failure and repair process of repairable systems in the presence of time-dependent covariates. We derive statistical properties of the failure processes for such systems
Modelling thermomechanical behaviour of Cr-Mo-V steel
This paper presents a mechanism-based approach for modelling the thermomechanical behaviour of a Cr-Mo-V steel. A set of unified viscoplastic constitutive equations were employed to model dislocation density, recrystallisation and grain size during deformation. The evolution of dislocation density accounts for the build-up of dislocations due to plastic strain, the static and dynamic recovery and the effect of recrystallisation. Recrystallisation occurs when a critical dislocation density is reached after an incubation time, and grain size becomes smaller after such event. Gleeble compression tests were used to obtain Stress-strain curves and evaluate the microstructural evolution at different temperature and strain rate, and the material constants for the model were determined from the experimental data. Copyright © 2010 MS&T10®
A brief history of long memory: Hurst, Mandelbrot and the road to ARFIMA
Long memory plays an important role in many fields by determining the
behaviour and predictability of systems; for instance, climate, hydrology,
finance, networks and DNA sequencing. In particular, it is important to test if
a process is exhibiting long memory since that impacts the accuracy and
confidence with which one may predict future events on the basis of a small
amount of historical data. A major force in the development and study of long
memory was the late Benoit B. Mandelbrot. Here we discuss the original
motivation of the development of long memory and Mandelbrot's influence on this
fascinating field. We will also elucidate the sometimes contrasting approaches
to long memory in different scientific communitiesComment: 40 page
A Framework for Evaluating Model-Driven Self-adaptive Software Systems
In the last few years, Model Driven Development (MDD), Component-based
Software Development (CBSD), and context-oriented software have become
interesting alternatives for the design and construction of self-adaptive
software systems. In general, the ultimate goal of these technologies is to be
able to reduce development costs and effort, while improving the modularity,
flexibility, adaptability, and reliability of software systems. An analysis of
these technologies shows them all to include the principle of the separation of
concerns, and their further integration is a key factor to obtaining
high-quality and self-adaptable software systems. Each technology identifies
different concerns and deals with them separately in order to specify the
design of the self-adaptive applications, and, at the same time, support
software with adaptability and context-awareness. This research studies the
development methodologies that employ the principles of model-driven
development in building self-adaptive software systems. To this aim, this
article proposes an evaluation framework for analysing and evaluating the
features of model-driven approaches and their ability to support software with
self-adaptability and dependability in highly dynamic contextual environment.
Such evaluation framework can facilitate the software developers on selecting a
development methodology that suits their software requirements and reduces the
development effort of building self-adaptive software systems. This study
highlights the major drawbacks of the propped model-driven approaches in the
related works, and emphasise on considering the volatile aspects of
self-adaptive software in the analysis, design and implementation phases of the
development methodologies. In addition, we argue that the development
methodologies should leave the selection of modelling languages and modelling
tools to the software developers.Comment: model-driven architecture, COP, AOP, component composition,
self-adaptive application, context oriented software developmen
Learning in evolutionary environments
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Econometrics: A bird's eye view
As a unified discipline, econometrics is still relatively young and has been transforming and expanding very rapidly over the past few decades. Major advances have taken place in the analysis of cross sectional data by means of semi-parametric and non-parametric techniques. Heterogeneity of economic relations across individuals, firms and industries is increasingly acknowledge and attempts have been made to take them into account either by integrating out their effects or by modeling the sources of heterogeneity when suitable panel data exists. The counterfactual considerations that underlie policy analysis and treatment evaluation have been given a more satisfactory foundation. New time series econometric techniques have been developed and employed extensively in the areas of macroeconometrics and finance. Non-linear econometric techniques are used increasingly in the analysis of cross section and time series observations. Applications of Bayesian techniques to econometric problems have been given new impetus largely thanks to advances in computer power and computational techniques. The use of Bayesian techniques have in turn provided the investigators with a unifying framework where the tasks and forecasting, decision making, model evaluation and learning can be considered as parts of the same interactive and iterative process; thus paving the way for establishing the foundation of the "real time econometrics". This paper attempts to provide an overview of some of these developments
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