Modeling control objectives for business process compliance

Business process design is primarily driven by process improvement objectives. However, the role of control objectives stemming from regulations and standards is becoming increasingly important for businesses in light of recent events that led to some of the largest scandals in corporate history. As organizations strive to meet compliance agendas, there is an evident need to provide systematic approaches that assist in the understanding of the interplay between (often conflicting) business and control objectives during business process design. In this paper, our objective is twofold. We will firstly present a research agenda in the space of business process compliance, identifying major technical and organizational challenges. We then tackle a part of the overall problem space, which deals with the effective modeling of control objectives and subsequently their propagation onto business process models. Control objective modeling is proposed through a specialized modal logic based on normative systems theory, and the visualization of control objectives on business process models is achieved procedurally. The proposed approach is demonstrated in the context of a purchase-to-pay scenario.

Compliance aware business process design

Historically, business process design has been driven by business objectives, specifically process improvement. However this cannot come at the price of control objectives which stem from various legislative, standard and business partnership sources. Ensuring the compliance to regulations and industrial standards is an increasingly important issue in the design of business processes. In this paper, we advocate that control objectives should be addressed at an early stage, i.e., design time, so as to minimize the problems of runtime compliance checking and consequent violations and penalties. To this aim, we propose supporting mechanisms for business process designers. This paper specifically presents a support method which allows the process designer to quantitatively measure the compliance degree of a given process model against a set of control objectives. This will allow process designers to comparatively assess the compliance degree of their design as well as be better informed on the cost of non-compliance.

Small molecular probes for G-protein-coupled C5a receptors: Conformationally constrained antagonists derived from the C terminus of the human plasma protein C5a

Activation of the human complement system of plasma proteins in response to infection or injury produces a 4-helix bundle glycoprotein (74 amino acids) known as C5a. C5a binds to G-protein-coupled receptors on cell surfaces triggering receptor-ligand internalization, signal transduction, and powerful inflammatory responses. Since excessive levels of C5a are associated with autoimmune and chronic inflammatory disorders, inhibitors of receptor activation may have therapeutic potential. We now report solution structures and receptor-binding and antagonist activities for some of the first small molecule antagonists of C5a derived from its hexapeptide C terminus. The antagonist NMe-Phe-Lys-Pro-D-Cha-Trp-D-Arg-CO2H (1) surprisingly shows an unusually well-defined solution structure as determined by H-1 NMR spectroscopy. This is one of the smallest acyclic peptides found to possess a defined solution conformation, which can be explained by the constraining role of intramolecular hydrogen bonding. NOE and coupling constant data, slow deuterium exchange, and a low dependence on temperature for the chemical shift of the D-Cha-NH strongly indicate an inverse gamma turn stabilized by a D-Cha-NH ... OC-Lys hydrogen bond. Smaller conformational populations are associated with a hydrogen bond between Trp-NH ... OC-Lys, defining a type II beta turn distorted by the inverse gamma turn incorporated within it. An excellent correlation between receptor-affinity and antagonist activity is indicated for a limited set of synthetic peptides. Conversion of the C-terminal carboxylate of 1 to an amide decreases antagonist potency 5-fold, but potency is increased up to 10-fold over 1 if the amide bond is made between the C-terminal carboxylate and a Lys/Orn side chain to form a cyclic analogue. The solution structure of cycle 6 also shows gamma and beta turns; however, the latter occurs in a different position, and there are clear conformational changes in 6 vs 1 that result in enhanced activity. These results indicate that potent C5a antagonists can be developed by targeting site 2 alone of the C5a receptor and define a novel pharmacophore for developing powerful receptor probes or drug candidates.

Indicators used to measure the innovation process: defects and possible remedies

Some diverse indicators used to measure the innovation process are considered, They include those with art aggregate, and often national, focus, and rely on data from scientific publications, patents and R&D expenditures, etc. Others have a firm-level perspective, relying primarily on surveys or case studies. Also included are indicators derived from specialized databases, or consensual agreements reached through foresight exercises. There is an obvious need for greater integration of the various approaches to capture move effectively the richness of available data and better reflect the reality of innovation. The focus for such integration could be in the area of technology strategy, which integrates the diverse scientific, technological, and innovation activities of firms within their operating environments; improved capacity to measure it has implications for policy-makers, managers and researchers.

Simultaneous steady state and dynamic design of process systems using structural indicators

The simultaneous design of the steady-state and dynamic performance of a process has the ability to satisfy much more demanding dynamic performance criteria than the design of dynamics only by the connection of a control system. A method for designing process dynamics based on the use of a linearised systems' eigenvalues has been developed. The eigenvalues are associated with system states using the unit perturbation spectral resolution (UPSR), characterising the dynamics of each state. The design method uses a homotopy approach to determine a final design which satisfies both steady-state and dynamic performance criteria. A highly interacting single stage forced circulation evaporator system, including control loops, was designed by this method with the goal of reducing the time taken for the liquid composition to reach steady-state. Initially the system was successfully redesigned to speed up the eigenvalue associated with the liquid composition state, but this did not result in an improved startup performance. Further analysis showed that the integral action of the composition controller was the source of the limiting eigenvalue. Design changes made to speed up this eigenvalue did result in an improved startup performance. The proposed approach provides a structured way to address the design-control interface, giving significant insight into the dynamic behaviour of the system such that a systematic design or redesign of an existing system can be undertaken with confidence.

Assisting decision-making in Queensland barley production through chance constrained programming

A chance constrained programming model is developed to assist Queensland barley growers make varietal and agronomic decisions in the face of changing product demands and volatile production conditions. Unsuitable or overlooked in many risk programming applications, the chance constrained programming approach nonetheless aptly captures the single-stage decision problem faced by barley growers of whether to plant lower-yielding but potentially higher-priced malting varieties, given a particular expectation of meeting malting grade standards. Different expectations greatly affect the optimal mix of malting and feed barley activities. The analysis highlights the suitability of chance constrained programming to this specific class of farm decision problem.

Finite element modelling of rock alteration and metamorphic process in hydrothermal systems

We use the finite element method to simulate the rock alteration and metamorphic process in hydrothermal systems. In particular, we consider the fluid-rock interaction problems in pore-fluid saturated porous rocks. Since the fluid rock interaction takes place at the contact interface between the pore-fluid and solid minerals, it is governed by the chemical reaction which usually takes place very slowly at this contact interface, from the geochemical point of view. Due to the relative slowness of the rate of the chemical reaction to the velocity of the pore-fluid flow in the hydrothermal system to be considered, there exists a retardation zone, in which the conventional static theory in geochemistry does not hold true. Since this issue is often overlooked by some purely numerical modellers, it is emphasized in this paper. The related results from a typical rock alteration and metamorphic problem in a hydrothermal system have shown not only the detailed rock alteration and metamorphic process, but also the size of the retardation zone in the hydrothermal system. Copyright (C) 2001 John Wiley & Sons, Ltd.

Visualization of learning in multilayer perceptron networks using principal component analysis

This paper is concerned with the use of scientific visualization methods for the analysis of feedforward neural networks (NNs). Inevitably, the kinds of data associated with the design and implementation of neural networks are of very high dimensionality, presenting a major challenge for visualization. A method is described using the well-known statistical technique of principal component analysis (PCA). This is found to be an effective and useful method of visualizing the learning trajectories of many learning algorithms such as back-propagation and can also be used to provide insight into the learning process and the nature of the error surface.