Third international workshop on empirical research in business process management (ER-BPM 2012)

Empirical research in business process management(BPM) is coming of age. In 2009, when the inaugural ER-BPM workshop was held, the field of BPM research was characterized by a strong emphasis on solution development, but also by an increasing demand for insights or evaluations of BPM technology based on dedicated empirical research strategies. The ER-BPM workshop series was created to provide an international forum for researchers to discuss and present such research.

Automated risk mitigation in business processes

This paper proposes a concrete approach for the automatic mitigation of risks that are detected during process enactment. Given a process model exposed to risks, e.g. a financial process exposed to the risk of approval fraud, we enact this process and as soon as the likelihood of the associated risk(s) is no longer tolerable, we generate a set of possible mitigation actions to reduce the risks' likelihood, ideally annulling the risks altogether. A mitigation action is a sequence of controlled changes applied to the running process instance, taking into account a snapshot of the process resources and data, and the current status of the system in which the process is executed. These actions are proposed as recommendations to help process administrators mitigate process-related risks as soon as they arise. The approach has been implemented in the YAWL environment and its performance evaluated. The results show that it is possible to mitigate process-related risks within a few minutes.

Fundamentals of business process management

Encompasses the whole BPM lifecycle, including process identification, modelling, analysis, redesign, automation and monitoring Class-tested textbook complemented with additional teaching material on the accompanying website Covers both relevant conceptual background, industrial standards and actionable skills Business Process Management (BPM) is the art and science of how work should be performed in an organization in order to ensure consistent outputs and to take advantage of improvement opportunities, e.g. reducing costs, execution times or error rates. Importantly, BPM is not about improving the way individual activities are performed, but rather about managing entire chains of events, activities and decisions that ultimately produce added value for an organization and its customers. This textbook encompasses the entire BPM lifecycle, from process identification to process monitoring, covering along the way process modelling, analysis, redesign and automation. Concepts, methods and tools from business management, computer science and industrial engineering are blended into one comprehensive and inter-disciplinary approach. The presentation is illustrated using the BPMN industry standard defined by the Object Management Group and widely endorsed by practitioners and vendors worldwide. In addition to explaining the relevant conceptual background, the book provides dozens of examples, more than 100 hands-on exercises – many with solutions – as well as numerous suggestions for further reading. The textbook is the result of many years of combined teaching experience of the authors, both at the undergraduate and graduate levels as well as in the context of professional training. Students and professionals from both business management and computer science will benefit from the step-by-step style of the textbook and its focus on fundamental concepts and proven methods. Lecturers will appreciate the class-tested format and the additional teaching material available on the accompanying website fundamentals-of-bpm.org.

Real-time risk monitoring in business processes : a sensor-based approach

This article proposes an approach for real-time monitoring of risks in executable business process models. The approach considers risks in all phases of the business process management lifecycle, from process design, where risks are defined on top of process models, through to process diagnosis, where risks are detected during process execution. The approach has been realized via a distributed, sensor-based architecture. At design-time, sensors are defined to specify risk conditions which when fulfilled, are a likely indicator of negative process states (faults) to eventuate. Both historical and current process execution data can be used to compose such conditions. At run-time, each sensor independently notifies a sensor manager when a risk is detected. In turn, the sensor manager interacts with the monitoring component of a business process management system to prompt the results to process administrators who may take remedial actions. The proposed architecture has been implemented on top of the YAWL system, and evaluated through performance measurements and usability tests with students. The results show that risk conditions can be computed efficiently and that the approach is perceived as useful by the participants in the tests.

Slice, mine and dice : complexity-aware automated discovery of business process models

Automated process discovery techniques aim at extracting models from information system logs in order to shed light into the business processes supported by these systems. Existing techniques in this space are effective when applied to relatively small or regular logs, but otherwise generate large and spaghetti-like models. In previous work, trace clustering has been applied in an attempt to reduce the size and complexity of automatically discovered process models. The idea is to split the log into clusters and to discover one model per cluster. The result is a collection of process models -- each one representing a variant of the business process -- as opposed to an all-encompassing model. Still, models produced in this way may exhibit unacceptably high complexity. In this setting, this paper presents a two-way divide-and-conquer process discovery technique, wherein the discovered process models are split on the one hand by variants and on the other hand hierarchically by means of subprocess extraction. The proposed technique allows users to set a desired bound for the complexity of the produced models. Experiments on real-life logs show that the technique produces collections of models that are up to 64% smaller than those extracted under the same complexity bounds by applying existing trace clustering techniques.

Efficient querying of large process model repositories

Recent years have seen an increased uptake of business process management technology in industries. This has resulted in organizations trying to manage large collections of business process models. One of the challenges facing these organizations concerns the retrieval of models from large business process model repositories. For example, in some cases new process models may be derived from existing models, thus finding these models and adapting them may be more effective and less error-prone than developing them from scratch. Since process model repositories may be large, query evaluation may be time consuming. Hence, we investigate the use of indexes to speed up this evaluation process. To make our approach more applicable, we consider the semantic similarity between labels. Experiments are conducted to demonstrate that our approach is efficient.

Process monitoring using sensors in YAWL

This article describes the architecture of a monitoring component for the YAWL system. The architecture proposed is based on sensors and it is realized as a YAWL service to have perfect integration with the YAWL systems. The architecture proposed is generic and applicable in different contexts of business process monitoring. Finally, it was tested and evaluated in the context of risk monitoring for business processes.

Characterization of the sulphate mineral amarantite Fe3 2 3+ (SO4)O 7H2O using infrared, Raman spectroscopy and thermogravimetry

The mineral amarantite Fe23+(SO4)O∙7H2O has been studied using a combination of techniques including thermogravimetry, electron probe analyses and vibrational spectroscopy. Thermal analysis shows decomposition steps at 77.63, 192.2, 550 and 641.4°C. The Raman spectrum of amarantite is dominated by an intense band at 1017 cm-1 assigned to the SO42- ν1 symmetric stretching mode. Raman bands at 1039, 1054, 1098, 1131, 1195 and 1233 cm-1 are attributed to the SO42- ν3 antisymmetric stretching modes. Very intense Raman band is observed at 409 cm-1 with shoulder bands at 399, 451 and 491 cm-1 are assigned to the v2 bending modes. A series of low intensity Raman bands are found at 543, 602, 622 and 650 cm-1 are assigned to the v4 bending modes. A very sharp Raman band at 3529 cm-1 is assigned to the stretching vibration of OH units. A series of Raman bands observed at 3025, 3089, 3227, 3340, 3401 and 3480 cm-1 are assigned to water bands. Vibrational spectroscopy enables aspects of the molecular structure of the mineral amarantite to be ascertained.

Vibrational spectroscopy of the mineral meyerhofferite CaB3O3(OH)5·H2O – An assessment of the molecular structure

Meyerhofferite is a calcium hydrated borate mineral with ideal formula: CaB3O3(OH)5�H2O and occurs as white complex acicular to crude crystals with length up to �4 cm, in fibrous divergent, radiating aggregates or reticulated and is often found in sedimentary or lake-bed borate deposits. The Raman spectrum of meyerhofferite is dominated by intense sharp band at 880 cm�1 assigned to the symmetric stretching mode of trigonal boron. Broad Raman bands at 1046, 1110, 1135 and 1201 cm�1 are attributed to BOH in-plane bending modes. Raman bands in the 900–1000 cm�1 spectral region are assigned to the antisymmetric stretching of tetrahedral boron. Distinct OH stretching Raman bands are observed at 3400, 3483 and 3608 cm�1. The mineral meyerhofferite has a distinct Raman spectrum which is different from the spectrum of other borate minerals, making Raman spectroscopy a very useful tool for the detection of meyerhofferite in sedimentary and lake bed deposits.

Vibrational spectroscopy of the phosphate mineral kovdorskite – Mg2PO4(OH)⋅3H2O

The mineral kovdorskite Mg2PO4(OH)�3H2O was studied by electron microscopy, thermal analysis and vibrational spectroscopy. A comparison of the vibrational spectroscopy of kovdorskite is made with other magnesium bearing phosphate minerals and compounds. Electron probe analysis proves the mineral is very pure. The Raman spectrum is characterized by a band at 965 cm�1 attributed to the PO3� 4 m1 symmetric stretching mode. Raman bands at 1057 and 1089 cm�1 are attributed to the PO3�4 m3 antisymmetric stretching modes. Raman bands at 412, 454 and 485 cm�1 are assigned to the PO3�4 m2 bending modes. Raman bands at 536, 546 and 574 cm�1 are assigned to the PO3�4 m4 bending modes. The Raman spectrum in the OH stretching region is dominated by a very sharp intense band at 3681 cm�1 assigned to the stretching vibration of OH units. Infrared bands observed at 2762, 2977, 3204, 3275 and 3394 cm�1 are attributed to water stretching bands. Vibrational spectroscopy shows that no carbonate bands are observed in the spectra; thus confirming the formula of the mineral as Mg2PO4(OH)�3H2O.

Vibrational spectroscopic characterization of the phosphate mineral series eosphorite–childrenite–(Mn,Fe)Al(PO4)(OH)2·(H2O)

The phosphate mineral series eosphorite–childrenite–(Mn,Fe)Al(PO4)(OH)2·(H2O) has been studied using a combination of electron probe analysis and vibrational spectroscopy. Eosphorite is the manganese rich mineral with lower iron content in comparison with the childrenite which has higher iron and lower manganese content. The determined formulae of the two studied minerals are: (Mn0.72,Fe0.13,Ca0.01)(Al)1.04(PO4, OHPO3)1.07(OH1.89,F0.02)·0.94(H2O) for SAA-090 and (Fe0.49,Mn0.35,Mg0.06,Ca0.04)(Al)1.03(PO4, OHPO3)1.05(OH)1.90·0.95(H2O) for SAA-072. Raman spectroscopy enabled the observation of bands at 970 cm−1 and 1011 cm−1 assigned to monohydrogen phosphate, phosphate and dihydrogen phosphate units. Differences are observed in the area of the peaks between the two eosphorite minerals. Raman bands at 562 cm−1, 595 cm−1, and 608 cm−1 are assigned to the �4 bending modes of the PO4, HPO4 and H2PO4 units; Raman bands at 405 cm−1, 427 cm−1 and 466 cm−1 are attributed to the �2 modes of these units. Raman bands of the hydroxyl and water stretching modes are observed. Vibrational spectroscopy enabled details of the molecular structure of the eosphorite mineral series to be determined.

Pregnancy loss and psychiatric disorders in young women : an Australian birth cohort study

Background Recent evidence has linked induced abortion with later adverse psychiatric outcomes in young women. Aims To examine whether abortion or miscarriage are associated with subsequent psychiatric and substance use disorders. Method A sample (n=1223) of women from a cohort born between 1981 and 1984 in Australia were assessed at 21 years for psychiatric and substance use disorders and lifetime pregnancy histories. Results Young women reporting a pregnancy loss had nearly three times the odds of experiencing a lifetime illicit drug disorder (excluding cannabis): abortion odds ratio (OR)=3.6 (95% CI 2.0–6.7) and miscarriage OR=2.6 (95% CI 1.2–5.4). Abortion was associated with alcohol use disorder (OR=2.1, 95% CI 1.3–3.5) and 12-month depression (OR=1.9, 95% CI 1.1–3.1). Conclusions These findings add to the growing body of evidence suggesting that pregnancy loss per se, whether abortion or miscarriage, increases the risk of a range of substance use disorders and affective disorders in young women.

The ability of YSR DSM-oriented depression scales to predict DSM-IV depression in young adults : a longitudinal study

Background The Achenbach child behaviour checklist (CBCL/YSR) is a widely used screening tool for affective problems. Several studies report good association between the checklists and psychiatric diagnoses; although with varying degrees of agreement. Most are cross-sectional studies involving adolescents referred to mental health services. This paper aims to evaluate the performance of the youth self report (YSR) empirical and DSM-oriented internalising scales in predicting later depressive disorders in young adults. Methods Sample was 2431 young adults from an Australian birth cohort study. The strength of association between the empirical and DSM-oriented scales assessed at 14 and 21 years and structured-interview derived depression in young adulthood (18 to 22 years) were tested using odds ratios, ROC analyses and related diagnostic efficiency tests (sensitivity, specificity, positive and negative predictive values). Results Adolescents with internalising symptoms were twice (OR 2.3, 95%CI 1.7 to 3.1) as likely to be diagnosed with DSM-IV depression by age 21. Use of DSM-oriented depressive scales did not improve the concordance between the internalising behaviour and DSM-IV diagnosed depression at age 14 (ORs ranged from 1.9 to 2.5). Limitations Some loss to follow-up over the 7-year gap between the two waves of follow-up. Conclusion DSM-oriented scales perform no better than the standard internalising or anxious/depressed scales in identifying young adults with later DSM-IV depressive disorder.

Predicting depressive and anxiety disorders with the YASR internalising scales (empirical and DSM-oriented)

Background The Achenbach problem behaviour scales (CBCL/YSR) are widely used. The DSM-oriented anxiety and depression scales have been created to improve concordance between Achenbach’s internalising scales and DSM-IV depression and anxiety. To date no study has examined the concurrent utility of the young adult (YASR) internalising scales, either the empirical or newly developed DSM-oriented depressive or anxiety scales. Methods A sample of 2,551 young adults, aged 18–23 years, from an Australian cohort study. The association between the empirical and DSM-oriented anxiety and depression scales were individually assessed against DSMIV depression and anxiety diagnoses derived from structured interview. Odds ratios, ROC analyses and diagnostic efficiency tests (sensitivity, specificity, positive and negative predictive values) were used to report findings. Results YASR empirical internalising scale predicted DSM-IV mood disorders (depression OR = 6.9, 95% CI 5.0–9.5; anxiety OR = 5.1, 95% CI 3.8–6.7) in the previous 12 months. DSM-oriented depressive or anxiety scales did not appear to improve the concordance with DSM-IV diagnosed depression or anxiety. The internalising scales were much more effective at identifying those with comorbid depression and anxiety, with Ors between 10.1 and 21.7 depending on the internalising scale used. Conclusion DSM-oriented scales perform no better than the standard internalising in identifying young adults with DSM-IV mood or anxiety disorder.

Validating a screening tool for mental health and substance use risk in an Indigenous prison population

Introduction and Aims: The Indigenous Risk Impact Screen (IRIS) is a validated culturally appropriate and widely used tool in the community for assessing substance use and mental disorder. This research aimed to assess the utility of this tool in an Indigenous prison population. Design and Methods: The study used data collected from a cross-sectional study of mental health among indigenous inmates in Queensland custodial centres (n=395, 84% male). Participants were administered a modified version of the IRIS, and ICD-10 diagnoses of substance use, depressive and anxiety disorders obtained using the Composite International Diagnostic Interview (CIDI). The concurrent validity of the modified IRIS was assessed against those of the CIDI. Results: 312 people screened as high risk for a substance use disorder and 179 were high risk for mental problems. 73% of males and 88% of females were diagnosed with a mental disorder. The IRIS was an effective screener for substance use disorders, with high sensitivity (Se) of 94% and low specificity (Sp) of 33%. The screener was less effective in identifying depression (Se 82%, Sp 59%) and anxiety (Se 68%, Sp 60%). Discussion: The IRIS is the first culturally appropriate screening instrument to be validated for the risk of drug and alcohol and mental disorder among Indigenous adults in custody. Conclusions: This study demonstrated that the IRIS is a valid tool for screening of alcohol and drug use risk among an incarcerated Indigenous population. The IRIS could offer an opportunity to improve the identification, treatment and health outcomes for incarcerated Indigenous adults.