Managing Process Variants in the Process Life Cycle

When designing process-aware information systems, often variants of the same process have to be specified. Each variant then constitutes an adjustment of a particular process to specific requirements building the process context. Current Business Process Management (BPM) tools do not adequately support the management of process variants. Usually, the variants have to be kept in separate process models. This leads to huge modeling and maintenance efforts. In particular, more fundamental process changes (e.g., changes of legal regulations) often require the adjustment of all process variants derived from the same process; i.e., the variants have to be adapted separately to meet the new requirements. This redundancy in modeling and adapting process variants is both time consuming and error-prone. This paper presents the Provop approach, which provides a more flexible solution for managing process variants in the process life cycle. In particular, process variants can be configured out of a basic process following an operational approach; i.e., a specific variant is derived from the basic process by applying a set of well-defined change operations to it. Provop provides full process life cycle support and allows for flexible process configuration resulting in a maintainable collection of process variants

On Formal Consistency between Value and Coordination Models

In information systems (IS) engineering dierent techniques for modeling inter-organizational collaborations are applied. In particular, value models estimate the profitability for involved stakeholders, whereas coordination models are used to agree upon the inter-organizational processes before implementing them. During the execution of inter-organizational collaboration, in addition, event logs are collected by the individual organizations representing another view of the IS. The combination of the two models and the event log represent the IS and they should therefore be consistent, i.e., not contradict each other. Since these models are provided by dierent user groups during design time and the event log is collected during run-time consistency is not straight forward. Inconsistency occurs when models contain a conflicting description of the same information, i.e., there exists a conflicting overlap between the models. In this paper we introduce an abstraction of value models, coordination models and event logs which allows ensuring and maintaining alignment between models and event log. We demonstrate its use by outlining a proof of an inconsistency resolution result based on this abstraction. Thus, the introduction of abstractions allows to explore formal inter-model relations based on consistency

Issues in Process Variants Mining

In today's dynamic business world economic success of an enterprise increasingly depends on its ability to react to internal and external changes in a quick and flexible way. In response to this need, process-aware information systems (PAIS) emerged, which support the modeling, orchestration and monitoring of business processes and services respectively. Recently, a new generation of flexible PAIS was introduced, which additionally allows for dynamic process and service changes. This, in turn, will lead to a large number of process variants, which are created from the same original process model, but might slightly differ from each other. This paper deals with issues related to the mining of such process variant collections. Our overall goal is to learn from process changes and to merge the resulting model variants into a generic process model in the best possible way. By adopting this generic process model in the PAIS, future cost of process change and need for process adaptations will decrease. Finally, we compare our approach with existing process mining techniques, and show that process variants mining is additionally needed to learn from process changes

A Heuristic Approach for Discovering Reference Models by Mining Process Model Variants

Recently, a new generation of adaptive Process-Aware Information Systems (PAISs) has emerged, which enables structural process changes during runtime while preserving PAIS robustness and consistency. Such flexibility, in turn, leads to a large number of process variants derived from the same model, but differing in structure. Generally, such variants are expensive to configure and maintain. This paper provides a heuristic search algorithm which fosters learning from past process changes by mining process variants. The algorithm discovers a reference model based on which the need for future process configuration and adaptation can be reduced. It additionally provides the flexibility to control the process evolution procedure, i.e., we can control to what degree the discovered reference model differs from the original one. As benefit, we can not only control the effort for updating the reference model, but also gain the flexibility to perform only the most important adaptations of the current reference model. Our mining algorithm is implemented and evaluated by a simulation using more than 7000 process models. Simulation results indicate strong performance and scalability of our algorithm even when facing large-sized process models

What are the Problem Makers: Ranking Activities According to their Relevance for Process Changes

Recently, a new generation of adaptive process management technology has emerged, which enables dynamic changes of composite services and process models respectively. This, in turn, results in a large number of process variants derived from the same process model, but differing in structure due to the applied changes. Since such process variants are expensive to maintain, the process model should be evolved accordingly. In this context, we need to know which activities have been more often involved in process adaptations than others, such that we can focus on them when reconfiguring the process model. This paper provides two approaches for ranking activities according to their involvement in process adaptations. The first one allows to precisely rank the activities, but is expensive to perform since the algorithm is at NP level. We therefore provide as alternative an approximation ranking algorithm which computes in polynomial time. The performance of the approximation algorithm is evaluated and compared through a simulation of 3600 process models. Statistical significance tests indicate that the performance of the approximation ranking algorithm does not depend on the size of process models, i.e., our algorithm can scale up

Discovering Process Reference Models from Process Variants Using Clustering Techniques

In today's dynamic business world, success of an enterprise increasingly depends on its ability to react to changes in a quick and flexible way. In response to this need, process-aware information systems (PAIS) emerged, which support the modeling, orchestration and monitoring of business processes and services respectively. Recently, a new generation of flexible PAIS was introduced, which additionally allows for dynamic process and service changes. This, in turn, has led to large number of process and service variants derived from the same model, but differs in structures due to the applied changes. This paper provides a sophisticated approach which fosters learning from past process changes and allows for determining such process variants. As a result we obtain a generic process model for which the average distances between this model and the process variants becomes minimal. By adopting this generic process model in the PAIS, need for future process configuration and adaptation will decrease. The mining method proposed has been implemented in a powerful proof-of-concept prototype and further validated by a comparison between other process mining algorithms

The labial gene is required to terminate proliferation of identified neuroblasts in postembryonic development of the Drosophila brain

The developing brain of Drosophila has become a useful model for studying the molecular genetic mechanisms that give rise to the complex neuronal arrays that characterize higher brains in other animals including mammals. Brain development in Drosophila begins during embryogenesis and continues during a subsequent postembryonic phase. During embryogenesis, the Hox gene labial is expressed in the developing tritocerebrum, and labial loss-of-function has been shown to be associated with a loss of regional neuronal identity and severe patterning defects in this part of the brain. However nothing is known about the expression and function of labial, or any other Hox gene, during the postembryonic phase of brain development, when the majority of the neurons in the adult brain are generated. Here we report the first analysis of Hox gene action during postembryonic brain development in Drosophila. We show that labial is initially expressed in six larval brain neuroblasts, of which only four give rise to the labial expressing neuroblast lineages present in the late larval brain. Although MARCM-based clonal mutation of labial in these four neuroblast lineages does not result in an obvious phenotype, a striking and unexpected effect of clonal labial loss-of-function does occur during postembryonic brain development, namely the formation of two ectopic neuroblast lineages that are not present in wild-type brains. The same two ectopic neuroblast lineages are also observed following cell death blockage and, significantly, in this case the resulting ectopic lineages are Labial-positive. These findings imply that labial is required in two specific neuroblast lineages of the wildtype brain for the appropriate termination of proliferation through programmed cell death. Our analysis of labial function reveals a novel cell autonomous role of this Hox gene in shaping the lineage architecture of the brain during postembryonic development

An experimental investigation of S-duct flow control using arrays of low-profile vortex generators

An experimental investigation was undertaken to measure the effect of various configurations of low-profile vortex generator arrays on the flow in a diffusing S-duct. Three parameters that characterize the vortex generator array were systematically varied to determine their effect: (1) the vortex generator height; (2) the streamwise location of the vortex generator array; and (3) the vortex generator spacing. Detailed measurements of total pressure at the duct exit, surface static pressure, and surface flow visualization were gathered for each vortex generator configuration. These results are reported here along with total pressure recovery and distortion coefficients determined from the experimental data. Each array of vortex generators tested improved total pressure recovery. The configuration employing the largest vortex generators was the most effective in reducing total pressure recovery. No configuration of vortex generators completely eliminated the flow separation that naturally occurs in the S-duct, however the extent of the separated flow region was reduced

Observation of electron spin resonance of negative ions in liquid helium

Electron spin resonance signals of negative ions in liquid helium were observed. The line width and g-value were measured. Electrons injected into helium by field emission from ferromagnetic tips are shown to be polarized. A new technique for the measurement of electron spin polarization is presented