Custom digital workflows : a new framework for design analysis integration

Flexible information exchange is critical to successful design-analysis integration, but current top-down, standards-based and model-oriented strategies impose restrictions that contradicts this flexibility. In this article we present a bottom-up, user-controlled and process-oriented approach to linking design and analysis applications that is more responsive to the varied needs of designers and design teams. Drawing on research into scientific workflows, we present a framework for integration that capitalises on advances in cloud computing to connect discrete tools via flexible and distributed process networks. We then discuss how a shared mapping process that is flexible and user friendly supports non-programmers in creating these custom connections. Adopting a services-oriented system architecture, we propose a web-based platform that enables data, semantics and models to be shared on the fly. We then discuss potential challenges and opportunities for its development as a flexible, visual, collaborative, scalable and open system.

Custom digital workflows : a new framework for design analysis integration

Flexible information exchange is critical to successful design integration, but current top-down, standards-based and model-oriented strategies impose restrictions that are contradictory to this flexibility. In this paper we present a bottom-up, user-controlled and process-oriented approach to linking design and analysis applications that is more responsive to the varied needs of designers and design teams. Drawing on research into scientific workflows, we present a framework for integration that capitalises on advances in cloud computing to connect discrete tools via flexible and distributed process networks. Adopting a services-oriented system architecture, we propose a web-based platform that enables data, semantics and models to be shared on the fly. We discuss potential challenges and opportunities for the development thereof as a flexible, visual, collaborative, scalable and open system.

Patient-specific simulations of spinal deformity surgery

Adolescent idiopathic scoliosis (AIS) is a three-dimensional spinal deformity involving the side-to-side curvature of the spine in the coronal plane and axial rotation of the vertebrae in the transverse plane. For patients with a severe or rapidly progressing deformity, corrective instrumented fusion surgery is performed. The wide choice of implants and large variability between patients make it difficult for surgeons to choose optimal treatment strategies. This paper describes the patient specific finite element modelling techniques employed and the results of preliminary analyses predicting the surgical outcomes for a series of AIS patients. This report highlights the importance of not only patient-specific anatomy and material parameters, but also patient-specific data for the clinical and physiological loading conditions experienced by the patient who has corrective scoliosis surgery.

Fostering wellbeing of immigrants and refugees? Evaluating the outcomes of work integration social enterprise

Work integration social enterprises (WISE) seek to create employment and pathways to employment for those highly disadvantaged in the labour market. This chapter examines the effects of WISE on the wellbeing of immigrants and refugees experiencing multiple barriers to economic and social participation. Drawing on an evaluation of a programme that supports seven such enterprises in the Australian state of Victoria, the effects of involvement for individual participants and their communities are examined. The study finds that this social enterprise model affords unique local opportunities for economic and social participation for groups experiencing significant barriers to meaningful employment. These opportunities have a positive impact on individual and community-level wellbeing. However, the financial costs of the model are high relative to other employment programmes, which is consistent with international findings on intermediate labour market programmes. The productivity costs of WISE are also disproportionately high compared to private sector competitors in some industries. This raises considerable dilemmas for social enterprise operators seeking to produce social value and achieve business sustainability while bearing high productivity costs to fulfil their mission. Further, the evaluation illuminates an ongoing need to address the systemic and structural drivers of health and labour market inequalities that characterize socio-economic participation for immigrants and refugees.

Adaptive stepsize based on control theory for stochastic differential equations

The numerical solution of stochastic differential equations (SDEs) has been focused recently on the development of numerical methods with good stability and order properties. These numerical implementations have been made with fixed stepsize, but there are many situations when a fixed stepsize is not appropriate. In the numerical solution of ordinary differential equations, much work has been carried out on developing robust implementation techniques using variable stepsize. It has been necessary, in the deterministic case, to consider the "best" choice for an initial stepsize, as well as developing effective strategies for stepsize control-the same, of course, must be carried out in the stochastic case. In this paper, proportional integral (PI) control is applied to a variable stepsize implementation of an embedded pair of stochastic Runge-Kutta methods used to obtain numerical solutions of nonstiff SDEs. For stiff SDEs, the embedded pair of the balanced Milstein and balanced implicit method is implemented in variable stepsize mode using a predictive controller for the stepsize change. The extension of these stepsize controllers from a digital filter theory point of view via PI with derivative (PID) control will also be implemented. The implementations show the improvement in efficiency that can be attained when using these control theory approaches compared with the regular stepsize change strategy.

A multi-scaled approach for simulating chemical reaction systems

In this paper we give an overview of some very recent work, as well as presenting a new approach, on the stochastic simulation of multi-scaled systems involving chemical reactions. In many biological systems (such as genetic regulation and cellular dynamics) there is a mix between small numbers of key regulatory proteins, and medium and large numbers of molecules. In addition, it is important to be able to follow the trajectories of individual molecules by taking proper account of the randomness inherent in such a system. We describe different types of simulation techniques (including the stochastic simulation algorithm, Poisson Runge-Kutta methods and the balanced Euler method) for treating simulations in the three different reaction regimes: slow, medium and fast. We then review some recent techniques on the treatment of coupled slow and fast reactions for stochastic chemical kinetics and present a new approach which couples the three regimes mentioned above. We then apply this approach to a biologically inspired problem involving the expression and activity of LacZ and LacY proteins in E coli, and conclude with a discussion on the significance of this work. (C) 2004 Elsevier Ltd. All rights reserved.

Procuring OSM : base-line models of off-site manufacture business processes in Australia

A pressing cost issue facing construction is the procurement of off-site pre-manufactured assemblies. In order to encourage Australian adoption of off-site manufacture (OSM), a new approach to underlying processes is required. The advent of object oriented digital models for construction design assumes intelligent use of data. However, the construction production system relies on traditional methods and data sources and is expected to benefit from the application of well-established business process management techniques. The integration of the old and new data sources allows for the development of business process models which, by capturing typical construction processes involving OSM, provides insights into such processes. This integrative approach is the foundation of research into the use of OSM to increase construction productivity in Australia. The purpose of this study is to develop business process models capturing the procurement, resources and information flow of construction projects. For each stage of the construction value chain, a number of sub-processes are identified. Business Process Modelling Notation (BPMN), a mainstream business process modelling standard, is used to create base-line generic construction process models. These models identify OSM decision-making points that could provide cost reductions in procurement workflow and management systems. This paper reports on phase one of an on-going research aiming to develop a proto-type workflow application that can provide semi-automated support to construction processes involving OSM and assist in decision-making in the adoption of OSM thus contributing to a sustainable built environment.

Numerical solutions of stochastic differential equations – implementation and stability issues

Stochastic differential equations (SDEs) arise fi om physical systems where the parameters describing the system can only be estimated or are subject to noise. There has been much work done recently on developing numerical methods for solving SDEs. This paper will focus on stability issues and variable stepsize implementation techniques for numerically solving SDEs effectively.

A variable stepsize implementation for stochastic differential equations

Stochastic differential equations (SDEs) arise from physical systems where the parameters describing the system can only be estimated or are subject to noise. Much work has been done recently on developing higher order Runge-Kutta methods for solving SDEs numerically. Fixed stepsize implementations of numerical methods have limitations when, for example, the SDE being solved is stiff as this forces the stepsize to be very small. This paper presents a completely general variable stepsize implementation of an embedded Runge Kutta pair for solving SDEs numerically; in this implementation, there is no restriction on the value used for the stepsize, and it is demonstrated that the integration remains on the correct Brownian path.

Adams-Type Methods for the Numerical Solution of Stochastic Ordinary Differential Equations

Stochastic differential equations (SDEs) arise fi om physical systems where the parameters describing the system can only be estimated or are subject to noise. There has been much work done recently on developing numerical methods for solving SDEs. This paper will focus on stability issues and variable stepsize implementation techniques for numerically solving SDEs effectively. (C) 2000 Elsevier Science B.V. All rights reserved.

High strong order methods for non-commutative stochastic ordinary differential equation systems and the Magnus formula

In recent years considerable attention has been paid to the numerical solution of stochastic ordinary differential equations (SODEs), as SODEs are often more appropriate than their deterministic counterparts in many modelling situations. However, unlike the deterministic case numerical methods for SODEs are considerably less sophisticated due to the difficulty in representing the (possibly large number of) random variable approximations to the stochastic integrals. Although Burrage and Burrage [High strong order explicit Runge-Kutta methods for stochastic ordinary differential equations, Applied Numerical Mathematics 22 (1996) 81-101] were able to construct strong local order 1.5 stochastic Runge-Kutta methods for certain cases, it is known that all extant stochastic Runge-Kutta methods suffer an order reduction down to strong order 0.5 if there is non-commutativity between the functions associated with the multiple Wiener processes. This order reduction down to that of the Euler-Maruyama method imposes severe difficulties in obtaining meaningful solutions in a reasonable time frame and this paper attempts to circumvent these difficulties by some new techniques. An additional difficulty in solving SODEs arises even in the Linear case since it is not possible to write the solution analytically in terms of matrix exponentials unless there is a commutativity property between the functions associated with the multiple Wiener processes. Thus in this present paper first the work of Magnus [On the exponential solution of differential equations for a linear operator, Communications on Pure and Applied Mathematics 7 (1954) 649-673] (applied to deterministic non-commutative Linear problems) will be applied to non-commutative linear SODEs and methods of strong order 1.5 for arbitrary, linear, non-commutative SODE systems will be constructed - hence giving an accurate approximation to the general linear problem. Secondly, for general nonlinear non-commutative systems with an arbitrary number (d) of Wiener processes it is shown that strong local order I Runge-Kutta methods with d + 1 stages can be constructed by evaluated a set of Lie brackets as well as the standard function evaluations. A method is then constructed which can be efficiently implemented in a parallel environment for this arbitrary number of Wiener processes. Finally some numerical results are presented which illustrate the efficacy of these approaches. (C) 1999 Elsevier Science B.V. All rights reserved.

Exponential asymptotics of free surface flow due to a line source

The steady problem of free surface flow due to a submerged line source is revisited for the case in which the fluid depth is finite and there is a stagnation point on the free surface directly above the source. Both the strength of the source and the fluid speed in the far field are measured by a dimensionless parameter, the Froude number. By applying techniques in exponential asymptotics, it is shown that there is a train of periodic waves on the surface of the fluid with an amplitude which is exponentially small in the limit that the Froude number vanishes. This study clarifies that periodic waves do form for flows due to a source, contrary to a suggestion by Chapman & Vanden-Broeck (2006, J. Fluid Mech., 567, 299--326). The exponentially small nature of the waves means they appear beyond all orders of the original power series expansion; this result explains why attempts at describing these flows using a finite number of terms in an algebraic power series incorrectly predict a flat free surface in the far field.

Optical techniques for real-time binary multiplication

An optical system which performs the multiplication of binary numbers is described and proof-of-principle experiments are performed. The simultaneous generation of all partial products, optical regrouping of bit products, and optical carry look-ahead addition are novel features of the proposed scheme which takes advantage of the parallel operations capability of optical computers. The proposed processor uses liquid crystal light valves (LCLVs). By space-sharing the LCLVs one such system could function as an array of multipliers. Together with the optical carry look-ahead adders described, this would constitute an optical matrix-vector multiplier.

Integration of opinion into customer analysis model

As e-commerce is becoming more and more popular, the number of customer reviews that a product receives grows rapidly. In order to enhance customer satisfaction and their shopping experiences, it has become important to analysis customers reviews to extract opinions on the products that they buy. Thus, Opinion Mining is getting more important than before especially in doing analysis and forecasting about customers’ behavior for businesses purpose. The right decision in producing new products or services based on data about customers’ characteristics means profit for organization/company. This paper proposes a new architecture for Opinion Mining, which uses a multidimensional model to integrate customers’ characteristics and their comments about products (or services). The key step to achieve this objective is to transfer comments (opinions) to a fact table that includes several dimensions, such as, customers, products, time and locations. This research presents a comprehensive way to calculate customers’ orientation for all possible products’ attributes.

A banded preconditioner for the two-sided, nonlinear space-fractional diffusion equation

The method of lines is a standard method for advancing the solution of partial differential equations (PDEs) in time. In one sense, the method applies equally well to space-fractional PDEs as it does to integer-order PDEs. However, there is a significant challenge when solving space-fractional PDEs in this way, owing to the non-local nature of the fractional derivatives. Each equation in the resulting semi-discrete system involves contributions from every spatial node in the domain. This has important consequences for the efficiency of the numerical solver, especially when the system is large. First, the Jacobian matrix of the system is dense, and hence methods that avoid the need to form and factorise this matrix are preferred. Second, since the cost of evaluating the discrete equations is high, it is essential to minimise the number of evaluations required to advance the solution in time. In this paper, we show how an effective preconditioner is essential for improving the efficiency of the method of lines for solving a quite general two-sided, nonlinear space-fractional diffusion equation. A key contribution is to show, how to construct suitable banded approximations to the system Jacobian for preconditioning purposes that permit high orders and large stepsizes to be used in the temporal integration, without requiring dense matrices to be formed. The results of numerical experiments are presented that demonstrate the effectiveness of this approach.