Service-based analysis of biological pathways

Background: Computer-based pathway discovery is concerned with two important objectives: pathway identification and analysis. Conventional mining and modeling approaches aimed at pathway discovery are often effective at achieving either objective, but not both. Such limitations can be effectively tackled leveraging a Web service-based modeling and mining approach. Results: Inspired by molecular recognitions and drug discovery processes, we developed a Web service mining tool, named PathExplorer, to discover potentially interesting biological pathways linking service models of biological processes. The tool uses an innovative approach to identify useful pathways based on graph-based hints and service-based simulation verifying user's hypotheses. Conclusion: Web service modeling of biological processes allows the easy access and invocation of these processes on the Web. Web service mining techniques described in this paper enable the discovery of biological pathways linking these process service models. Algorithms presented in this paper for automatically highlighting interesting subgraph within an identified pathway network enable the user to formulate hypothesis, which can be tested out using our simulation algorithm that are also described in this paper

Evaluating concepts for short-term control in financial service processes

Financial services are characterised by the integration of customers while the service is being delivered. This integration leads to interruptions and thus delays in the processing of a customer order until for example the customer provides the missing input. Because customer behaviour can only be planned to a certain extent this is a major problem for an efficient control of financial service processes. It would be helpful to know which concept leads to the best solution for a certain situation in controlling the process. A concept contains explicit practical knowledge e.g. using a stand-by-employee or a prioritisation of customer orders with first-infirst-out. As financial services differ from manufacturing processes application knowledge of concepts cannot be transferred one to one. To test concepts regarding their ability to deal efficiently with interruptions by customers short-term simulations should be conducted. Shortterm simulation uses the actual state of a process and is not focussing on steady-state results. The research presented focuses on comparing several concepts for short-term control using case-study data of a typical financial service process. For this process a simulation model is built based on process mining. This approach is used to gather information out of documented timestamps of underlying process-aware information systems. Such timestamps allow a historical analysis to build typical scenarios and to gather the actual state of a financial service process as a starting point for a simulation analysis. The depicted concepts are simulated for different typical scenarios points to determine respectively which concept suits best. The results show which concepts suit best in certain situations for the case study conducted. --short-term control,financial services,business process simulation

An Evidence-Based Decision Support Framework for Clinician Medical Scheduling

In healthcare management, waiting time for consultation is an important measure that has strong associations with patient's satisfaction (i.e., the longer patients wait for consultation, the less satisfied they are). To this end, it is required to optimize medical scheduling for clinicians. A typical approach for deriving the optimized schedules is to perform experiments using discrete event simulation. The existing work has developed how to build a simulation model based on process mining techniques. However, applying this method for outpatient processes straightforwardly, in particular medical scheduling, is challenging: 1) the collected data from electronic health record system requires a series of processes to acquire simulation parameters from the raw data; and 2) even if the derived simulation model fully reflects the reality, there is no systematic approach to deriving effective improvements for simulation analysis, i.e., experimental scenarios. To overcome these challenges, this paper proposes a novel decision support framework for a clinician's schedule using simulation analysis. In the proposed framework, a data-driven simulation model is constructed based on process mining analysis, which includes process discovery, patient arrival rate analysis, and service time analysis. Also, a series of steps to derive the optimal improvement method from the simulation analysis is included in the framework. To demonstrate the usefulness of our approach, we present the case study results with real-world data in a hospital.11Ysciescopu

Freshwater ecosystem services in mining regions : modelling options for policy development support

The ecosystem services (ES) approach offers an integrated perspective of social-ecological systems, suitable for holistic assessments of mining impacts. Yet for ES models to be policy-relevant, methodological consensus in mining contexts is needed. We review articles assessing ES in mining areas focusing on freshwater components and policy support potential. Twenty-six articles were analysed concerning (i) methodological complexity (data types, number of parameters, processes and ecosystem-human integration level) and (ii) potential applicability for policy development (communication of uncertainties, scenario simulation, stakeholder participation and management recommendations). Articles illustrate mining impacts on ES through valuation exercises mostly. However, the lack of ground-and surface-water measurements, as well as insufficient representation of the connectivity among soil, water and humans, leave room for improvements. Inclusion of mining-specific environmental stressors models, increasing resolution of topographies, determination of baseline ES patterns and inclusion of multi-stakeholder perspectives are advantageous for policy support. We argue that achieving more holistic assessments exhorts practitioners to aim for high social-ecological connectivity using mechanistic models where possible and using inductive methods only where necessary. Due to data constraints, cause-effect networks might be the most feasible and best solution. Thus, a policy-oriented framework is proposed, in which data science is directed to environmental modelling for analysis of mining impacts on water ES