Evaluation of the applicability of investment appraisal techniques for assessing the business value of IS services.

There is a consensus among academics and practitioners that ICT investments should be carefully justified, measured and controlled. This is not different for the development of a service architecture or the development of particular services as such. In practice, the traditional capital investment appraisal techniques (CIAT’s) such as payback period or net present value are by far the most used techniques for assessing the feasibility of ICT investments. Nevertheless, serious doubts about the fitness of these techniques in a service based value net environment arise. Value nets have special characteristics such as high flexibility and agility, re-use of services,… that makes the use of these techniques very difficult and the reliability of the outcome most uncertain. Efforts are made to find more appropriate techniques. In the past, CIAT’s have been adjusted so that these techniques become more reliable in an ICT environment and new justification methods and techniques have been developed. However neither these adjusted techniques nor the new techniques are frequently used. This might be explained by the fact that the outcome of these techniques is difficult to interpret and to use and the fact that some significant problems (like the estimation of hidden costs) remain unsolved. Moreover, most of the new techniques are still in the conceptual phase. In this paper we evaluate these adjusted and new techniques in the light of service oriented architectures. We will argue that non of the techniques offers a good solution for assessing the business value of IS services. Despite the existence of a wealth of literature, the IS community appears to be no nearer to a solution to many problems associated with ICT appraisal. This is potentially problematic when dealing with investments in emerging technology such as IS services or service architectures. Since all techniques presented in the article have their drawbacks, it is safe to say that reliance on a sole technique may lead to sub-optimalisation or even failure. Therefore it makes sense to use a mixture of techniques, eliminating or diminishing the weaknesses of each of the techniques used. We strongly recommend a multi-layer evaluation process, or an evaluation process derived from the balanced scorecard, for the appraisal of investments in services or service architectures.

New Examples of Marginally Trapped Surfaces and Tubes in Warped Spacetimes

In the present paper we provide new examples of marginally trapped surfaces and tubes in FLRW spacetimes by using a basic relation between these objects and CMC surfaces in 3-manifolds. We also provide a new method to construct marginally trapped surfaces in closed FLRW spacetimes, which is based on the classical Hopf map. The utility of this method is illustrated by providing marginally trapped surfaces crossing expanding and collapsing regions of a closed FLRW spacetime. The approach introduced in this paper is also extended to twisted spaces.Comment: 20 page

Natural Intrinsic Geometrical Symmetries

A proposal is made for what could well be the most natural symmetrical Riemannian spaces which are homogeneous but not isotropic, i.e. of what could well be the most natural class of symmetrical spaces beyond the spaces of constant Riemannian curvature, that is, beyond the spaces which are homogeneous and isotropic, or, still, the spaces which satisfy the axiom of free mobility.Comment: Theorem 20 is corrected and References [13, 14] are adde

Existence dependency-based domain modeling for improving stateless process enactment.

In a process-enabled service oriented architecture, a process engine typically stores the state of the process instances during enactment. As an alternative, stateless process enactment entails that process state is derived from the state of business objects, which are organized in a domain model. The business objects are referred to in pre- and post-conditions of activities, which determine when the activity is enabled and completed, respectively. Despite the fact that the latter approach has multiple benefits compared with the former, the repeated state (re)calculations deteriorate performance and the formulation of clear conditions is not self-evident if typical domain modeling techniques (e.g. UML or ER) are adopted. In this paper we show that by adopting a specific domain modeling technique, which is based on the notion of existence dependency between the business objects, the performance and comprehensibility issues can proficiently be dealt with. We illustrate the technique using a real-world case from the insurance domain and analyze the emerging duality between process modeling and domain modeling.

A new approach for discovering business process models from event logs.

Process mining is the automated acquisition of process models from the event logs of information systems. Although process mining has many useful applications, not all inherent difficulties have been sufficiently solved. A first difficulty is that process mining is often limited to a setting of non-supervised learnings since negative information is often not available. Moreover, state transitions in processes are often dependent on the traversed path, which limits the appropriateness of search techniques based on local information in the event log. Another difficulty is that case data and resource properties that can also influence state transitions are time-varying properties, such that they cannot be considered ascross-sectional.This article investigates the use of first-order, ILP classification learners for process mining and describes techniques for dealing with each of the above mentioned difficulties. To make process mining a supervised learning task, we propose to include negative events in the event log. When event logs contain no negative information, a technique is described to add artificial negative examples to a process log. To capture history-dependent behavior the article proposes to take advantage of the multi-relational nature of ILP classification learners. Multi-relational process mining allows to search for patterns among multiple event rows in the event log, effectively basing its search on global information. To deal with time-varying case data and resource properties, a closed-world version of the Event Calculus has to be added as background knowledge, transforming the event log effectively in a temporal database. First experiments on synthetic event logs show that first-order classification learners are capable of predicting the behavior with high accuracy, even under conditions of noise.Credit; Credit scoring; Models; Model; Applications; Performance; Space; Decision; Yield; Real life; Risk; Evaluation; Rules; Neural networks; Networks; Classification; Research; Business; Processes; Event; Information; Information systems; Systems; Learning; Data; Behavior; Patterns; IT; Event calculus; Knowledge; Database; Noise;

Ants constructing rule-based classifiers.

Classifiers; Data; Data mining; Studies;

A stigmergy based approach to data mining.

Data; Data mining;

A new and improved strategy combining a dispersive-solid phase extraction-based multiclass method with ultra high pressure liquid chromatography for analysis of low molecular weight polyphenols in vegetables

This paper reports on the development and optimization of a modified Quick, Easy, Cheap Effective, Rugged and Safe (QuEChERS) based extraction technique coupled with a clean-up dispersive-solid phase extraction (dSPE) as a new, reliable and powerful strategy to enhance the extraction efficiency of free low molecular-weight polyphenols in selected species of dietary vegetables. The process involves two simple steps. First, the homogenized samples are extracted and partitioned using an organic solvent and salt solution. Then, the supernatant is further extracted and cleaned using a dSPE technique. Final clear extracts of vegetables were concentrated under vacuum to near dryness and taken up into initial mobile phase (0.1% formic acid and 20% methanol). The separation and quantification of free low molecular weight polyphenols from the vegetable extracts was achieved by ultrahigh pressure liquid chromatography (UHPLC) equipped with a phodiode array (PDA) detection system and a Trifunctional High Strength Silica capillary analytical column (HSS T3), specially designed for polar compounds. The performance of the method was assessed by studying the selectivity, linear dynamic range, the limit of detection (LOD) and limit of quantification (LOQ), precision, trueness, and matrix effects. The validation parameters of the method showed satisfactory figures of merit. Good linearity (View the MathML sourceRvalues2>0.954; (+)-catechin in carrot samples) was achieved at the studied concentration range. Reproducibility was better than 3%. Consistent recoveries of polyphenols ranging from 78.4 to 99.9% were observed when all target vegetable samples were spiked at two concentration levels, with relative standard deviations (RSDs, n = 5) lower than 2.9%. The LODs and the LOQs ranged from 0.005 μg mL−1 (trans-resveratrol, carrot) to 0.62 μg mL−1 (syringic acid, garlic) and from 0.016 μg mL−1 (trans-resveratrol, carrot) to 0.87 μg mL−1 ((+)-catechin, carrot) depending on the compound. The method was applied for studying the occurrence of free low molecular weight polyphenols in eight selected dietary vegetables (broccoli, tomato, carrot, garlic, onion, red pepper, green pepper and beetroot), providing a valuable and promising tool for food quality evaluation