IDENTIFICATION, ABSTRACTION AND CLASSIFICATION OF INCONSISTENCY STRUCTURES IN DECLARATIVE PROCESS MODELS

Handling inconsistencies in declarative process models (DPMs) has been of increased interest in previous years as even a single contradiction within a constraint set makes the entire DPM unsatisfiable. To support inconsistency detection and resolution, we provide a collection of generic inconsistency structures in this work. To this aim, we (1) iteratively identify inconsistency structures, (2) generalize them by analyzing their extendibility, (3) classify them based on their characteristics and (4) provide a visual representation of each generic structure. The resulting collection of structures provides the basis for future inconsistency detection and visualization approaches

Investigating Inconsistency Understanding to Support Interactive Inconsistency Resolution in Declarative Process Models

Handling inconsistencies in business rules is an important part of corporate compliance management. This includes the resolution of inconsistencies, which currently is a fully automated process that might not always be plausible in a real-world scenario. To include human experts and develop interactive resolution approaches, an understanding of inconsistencies is crucial. Thus, we focus on investigating inconsistency understanding in declarative process models by testing the applicability of insights from declarative process model understanding to different inconsistency characteristics. In the future, this will provide the basis for a series of cognitive experiments evaluating the effects of inconsistency characteristics and representation on inconsistency understanding in declarative process models

Analysis of Task Management in Virtual Academic Teams

Social Collaboration Analytics (SCA) aims at measuring collaboration in Enterprise Collaboration Systems (ECS). In this paper, we apply SCA to investigate the use of Task Management (TM) features in virtual academic teams on a collaboration platform. This paper contributes to theory by developing the TM Catalog describing the elements and characteristics of TM. Our literature review identified only three studies analyzing the use of TM features in ECS. These studies base their analyses on transactional data (event logs). We propose to analyze both the structure and characteristics of tasks, as well as how tasks are used. In our paper, we show how SCA can be applied to gain insights on the use of TM features. Based on data from an academic collaboration platform, we demonstrate the characteristics of tasks and how different types of virtual academic teams make use of TM features

Effects of Visualization Techniques on Understanding Inconsistencies in Automated Decision-Making

The automation of business processes and decision-making have received major interest from practice and academia. As automation allows to execute more processes (cases), monitoring automated decision-making is currently evolving into a big data analytics problem for companies. Thus, not only monitoring insights themselves, but also an effective use of such insights become important. In this context, the speed and ability to interpret data is closely related to the visualization of metrics and data. While various approaches for quantitative insights on automated decision-making have been proposed, there is currently no evidence as to how the specific visualization of such metrics helps companies to create more value from their data. In this report, we therefore present the results of an empirical experiment analyzing the cognitive effects of different visualization techniques for quantitative insights on understanding inconsistencies in automated decision-making data

Towards Intelligent Chatbots for Customer Care - Practice-Based Requirements for a Research Agenda

Chatbots bare a great potential to save efforts and costs in customer care through service automation. Current results are however still at an early stage in functionality and not widely attainable. Here, developing a new form of intelligent chatbots is a current challenge still under review. While there have been numerous proposals for future work, virtually all agenda-setting contributions are solely based on scientific literature. This is unsatisfactory from both an academic and practical perspective, as the industrial view on the future of chatbots seems to be neglected. Therefore, this work explores how professional experts see the future of intelligent chatbots for customer care and suggests how practice can guide research based on an expert panel with 17 industrial partners. Our work identifies research opportunities based on the demands and views of key practitioners by pin-pointing expected trends. Furthermore, based on the expert opinions, we derive guidelines for organizations which state key factors that should be considered in the development or adoption of chatbots in customer care

Effects of Quantitative Measures on Understanding Inconsistencies in Business Rules

Business Rules have matured to an important aspect in the development of organizations, encoding company knowledge as declarative constraints, aimed to ensure compliant business. The management of business rules is widely acknowledged as a challenging task. A problem here is a potential inconsistency ofbusiness rules, as business rules are often created collaboratively. To support companies in managing inconsistency, many works have suggested that a quantification of inconsistencies could provide valuable insights. However, the actual effects of quantitative insights in business rules management have not yet been evaluated. In this work, we present the results of an empirical experiment using eye-tracking and other performance measures to analyze the effects of quantitative measures on understanding inconsistencies in business rules. Our results indicate that quantitative measures are associated with better understanding accuracy, understanding efficiency and less mental effort in business rules management

Determining the Pore Size Distribution in Synthetic and Building Materials Using 1D NMR

NMR is gaining increasing interest in civil engineering for applications regarding microstructure characterization as e.g., to determine pore sizes or to monitor moisture transport in porous materials. This study reveals the capability of NMR as a tool for pore size characterization. Therefore, we measured floor screed and synthetic materials at partial and full saturation. For most examined materials, the pore size distribution was successfully determined using either a reference or a calibration method. Since diffusion effects were observed for some samples in single-sided NMR measurements, further tests employing an NMR core analyzer were carried out in a homogeneous magnetic field. The finally obtained surface relaxivity of floor screed (50 μm/s) resulted to be much higher than suggested by literature

The impact of social status inconsistency on cardiovascular risk factors, myocardial infarction and stroke in the EPIC-Heidelberg cohort

BACKGROUND: Social inequalities in cardiovascular diseases are well documented. Yet, the relation of social status inconsistency (having different ranks in two or more status indicators like education, occupational position or income) and medical conditions of heart or vessels is not clear. Status inconsistency (SI) is assumed to be stressful, and the association of psychosocial distress and health is well known. Therefore, we aimed to analyze the relationship between cardiovascular diseases (CVD) and status inconsistency. Another target was to assess the influence of behaviour related risk factors on this association. METHODS: 8960 men and 6070 women, aged 45-65 years, from the EPIC-Heidelberg cohort (European Prospective Investigation into Cancer and Nutrition) were included. Socio-economic status was assessed by education/vocational training and occupational position at recruitment. During a median follow-up of 8.7 years, information on CVD was collected. RESULTS: Compared to status consistent subjects, men who were in a higher occupational position than could be expected given their educational attainment had a nearly two-fold increased incidence of CVD (Odds Ratio (OR) = 1.8, 95% Confidence Interval (CI) = 1.5; 2.4, adjusted for age). Smoking behaviour and BMI differed significantly between those who had adequate occupational positions and those who did not. Yet, these lifestyle factors, as opposed to age, did not contribute to the observed differences in CVD. No association of cardiovascular diseases and status inconsistency was found for women or in cases where education exceeded occupational position. CONCLUSIONS: Status inconsistent men (occupational position > education) had a higher risk of cardiovascular diseases than status consistent men. However, harmful behaviour did not explain this relationship

The impact of education on risk factors and the occurrence of multimorbidity in the EPIC-Heidelberg cohort

<p>Abstract</p> <p>Background</p> <p>In aging populations, the prevalence of multimorbidity is high, and the role of socioeconomic status and its correlates is not well described. Thus, we investigated the association between educational attainment and multimorbidity in a prospective cohort study, taking also into account intermediate factors that could explain such associations.</p> <p>Methods</p> <p>We included 13,781 participants of the Heidelberg cohort of the European Prospective Investigation into Cancer and Nutrition (EPIC), who were 50–75 years at the end of follow-up. Information on diet and lifestyle was collected at recruitment (1994–1998). During a median follow-up of 8.7 years, information on chronic conditions and death were collected.</p> <p>Results</p> <p>Overall, the prevalence of multimorbidity (>= 2 concurrent chronic diseases) was 67.3%. Compared to the highest educational category, the lowest was statistically significantly associated with increased odds of multimorbidity in men (OR = 1.43; 95% CI 1.28–1.61) and women (OR = 1.33; 95% CI 1.18–1.57). After adjustment, the positive associations were attenuated (men: OR = 1.28; 95% CI 1.12–1.46; women: OR = 1.16; 95% CI 0.99–1.36). Increasing BMI was more strongly than smoking status an intermediate factor in the association between education and multimorbidity.</p> <p>Conclusion</p> <p>In this German population, the prevalence of multimorbidity is high and is significantly associated with educational level. Increasing BMI is the most important predictor of this association. However, even the fully adjusted model, i.e. considering also other known risk factors for chronic diseases, could not entirely explain socio-economic inequalities in multimorbidity. Educational level should be considered in the development and implementation of prevention strategies of multimorbidity.</p

Left ventricular hypertrabeculation/noncompaction with epilepsy, other heart defects, minor facial anomalies and new copy number variants

BACKGROUND: Left ventricular hypertrabeculation/noncompaction (LVHT) is a cardiac abnormality of unknown etiology which has been described in children as well as in adults with and without chromosomal aberrations. LVHT has been reported in association with various cardiac and extracardiac abnormalities like epilepsy and facial dysmorphism. CASE PRESENTATION: A unique combination of LVHT, atrial septal defect, pulmonary valve stenosis, aortic stenosis, epilepsy and minor facial anomalies is presented in a 5.5 years old girl. Microarray-based genomic hybridization (array-CGH) detected six previously not described copy number variants (CNVs) inherited from a clinically unaffected father and minimally affected mother, thus, most likely, not clinically significant but rare benign variants. CONCLUSIONS: Despite this complex phenotype de novo microdeletions or microduplications were not detected by array CGH. Further investigations, such as whole exome sequencing, could reveal point mutations and small indels as the possible cause