The Connection between Process Complexity of Event Sequences and Models discovered by Process Mining

Process mining is a research area focusing on the design of algorithms that can automatically provide insights into business processes by analysing historic process execution data, known as event logs. Among the most popular algorithms are those for automated process discovery, whose ultimate goal is to generate the best process model that summarizes the behaviour recorded in the input event log. Over the past decade, several process discovery algorithms have been proposed but, until now, this research was driven by the implicit assumption that a better algorithm would discover better process models, no matter the characteristics of the input event log. In this paper, we take a step back and question that assumption. Specifically, we investigate what are the relations between measures capturing characteristics of the input event log and the quality of the discovered process models. To this end, we review the state-of-the-art process complexity measures, propose a new process complexity measure based on graph entropy, and analyze this set of complexity measures on an extensive collection of event logs and corresponding automatically discovered process models. Our analysis shows that many process complexity measures correlate with the quality of the discovered process models, demonstrating the potential of using complexity measures as predictors for the quality of process models discovered with state-of-the-art process discovery algorithms. This finding is important for process mining research, as it highlights that not only algorithms, but also connections between input data and output quality should be studied

The Interplay between Cognition and Worry

An increasing amount of research findings is showing that higher engagement in cognitive tasks alleviates the interference of anxiety and worry on task performance as compared to lower task engagement. Yet, it is still not clear which cognitive functions are mostly contributing to this relieving effect. To add to the current knowledge, the present experimental work investigated the relations between task performance, patterns in pupil dilation and increased difficulty in tasks requiring, among others, cognitive maintenance and updating functions in induced ‘worry’ and ‘no worry’ conditions. In addition, the present experiment explored if visual complexity level of stimuli is modulating these relations. Data analyses of the response speed, proportion of correct answers and pupillary baseline measures revealed statistically significant three-way interactions between the condition (‘worry’, ‘no worry’), visual complexity (low, high), and task (n-back, reference-back). The results showed lower performance measures in the ‘worry’ condition than in the ‘no worry’ condition in an easier n-back task, but this disadvantage was eliminated with increased task difficulty. Results of the reference-back task revealed that increased period of mental object maintenance may be sufficient to shield from disadvantages in the performance efficiency in the ‘worry’ condition. The results also showed that increased visual complexity of stimuli interfered with the task performance more in the ‘worry’ condition than in the ‘no worry’ condition. Pupil dilation data showed higher baseline pupil sizes in the ‘no worry’ condition linked with, among others, higher working memory capacity, as compared to smaller pupil sizes in the ‘worry’ condition

QoS-aware Metamorphic Testing: An Elevation Case Study

Elevators are among the oldest and most widespread transportation systems, yet their complexity increases rapidly to satisfy customization demands and to meet quality of service requirements. Verification and validation tasks in this context are costly, since they rely on the manual intervention of domain experts at some points of the process. This is mainly due to the difficulty to assess whether the elevators behave as expected in the different test scenarios, the so-called test oracle problem. Metamorphic testing is a thriving testing technique that alleviates the oracle problem by reasoning on the relations among multiple executions of the system under test, the so-called metamorphic relations. In this practical experience paper, we report on the application of metamorphic testing to verify an industrial elevator dispatcher. Together with domain experts from the elevation sector, we defined multiple metamorphic relations that consider domain-specific quality of service measures. Evaluation results with seeded faults show that the approach is effective at detecting faults automatically

Entropy Measures in Machine Fault Diagnosis: Insights and Applications

Entropy, as a complexity measure, has been widely applied for time series analysis. One preeminent example is the design of machine condition monitoring and industrial fault diagnostic systems. The occurrence of failures in a machine will typically lead to non-linear characteristics in the measurements, caused by instantaneous variations, which can increase the complexity in the system response. Entropy measures are suitable to quantify such dynamic changes in the underlying process, distinguishing between different system conditions. However, notions of entropy are defined differently in various contexts (e.g., information theory and dynamical systems theory), which may confound researchers in the applied sciences. In this paper, we have systematically reviewed the theoretical development of some fundamental entropy measures and clarified the relations among them. Then, typical entropy-based applications of machine fault diagnostic systems are summarized. Further, insights into possible applications of the entropy measures are explained, as to where and how these measures can be useful towards future data-driven fault diagnosis methodologies. Finally, potential research trends in this area are discussed, with the intent of improving online entropy estimation and expanding its applicability to a wider range of intelligent fault diagnostic systems

Transversality in Diversity: Experiencing Networks of Confusion and Convergence in the World Social Forum

Drawing on the World Social Forum as an exemplary case study, this article shows how an emerging mode of cosmopolitanist vision (‘transversalism’) can be explained in terms of activists’ experiences of both complexity and contradiction in their networks. The paper questions the idea that the transnationalization of networks of solidarity and interconnection can uncomplicatedly encourage the growth of cosmopolitanism among global justice activists. Activists’ experiences of dissonances between their ideals, the complexity of power relations and the structural uncertainties in their global justice networks can provide them with a base for self-reflexive ideation and deliberation, and thereby encourage agendas for accommodating differences. Underpinning the accommodating measures which arise for dealing with such a cognitive-practical dissonance is a new mode of cosmopolitanism, coined here as ‘transversalism’. The article proposes a new conceptual framework and an analytical model to investigate the complexity of this process more inclusively and systematically

Increase in Cognitive Complexity: a Comparison of Human Relations Training and Group Psychotherapy.

The purpose of this investigation was to measure whether, after group treatment, open ward hospitalized psychiatric patients would demonstrate an increase in ability to describe other people by means of interpersonal constructs. Measuring the ability to describe other people, or more precisely cognitive complexity, has never been undertaken with a hospitalized psychiatric patient population nor has the effect of group treatment on cognitive complexity been examined. Responses investigated included cognitive complexity before and after four weeks of treatment, variability in description of others depending on sex of the other person and whether he or she was liked or disliked, and improvement after four weeks of treatment and on a two-month follow-up. Cognitive complexity was considered in its possible relationship to symptomatology, intelligence, diagnosis, patients\u27 conceptualization of control of their destiny, improvement after treatment, and certain factors involving group process. Two groups of psychiatric patients on open wards at a VA hospital were compared. One group received Human Relations Training Laboratory exercises and had autonomous group sessions for four weeks. The other group received more traditional Group Psychotherapy and had a therapist present for alternate sessions for four weeks. Subjects were comparable in age, education and intelligence. The cognitive complexity measure was a free response paper and pencil instrument on which subjects were asked to identify and describe two liked males, two liked females, two disliked males and two disliked females. Experimental findings may be summarized as follows: 1. Neither group increased in cognitive complexity after treatment. Human Relations Training Laboratory patients decreased significantly more than Group Psychotherapy patients. 2. Psychiatric patients described liked females with greatest facility, implying that they are most adept in. such interactions. They described liked and disliked males with equal facility and had greatest difficulty describing disliked females. 3. When sex is or is not considered, patients produced a greater variety of constructs to describe people who are liked as opposed to people who are disliked. 4. No significant relationship was found between degree of cognitive complexity and degree of symptomatology. 5. Patients manifested equal degree of symptomatic improvement after both types of treatment as rated by the staff and on self-ratings. 6. A significant correlation between intelligence and cognitive complexity was obtained within the intelligence range represented in a patient population. 7. The Rotter I-E score, which measures a person\u27s sense of control of his overall environment, was not correlated with cognitive complexity, which hypothetically measures a person\u27s sense of control of interpersonal relations. 8. Differences in cognitive complexity were not found among the diagnostic categories of depressive reaction, anxiety reaction and personality disorder. 9. Less than half of the 29 Human Relations Training Laboratory patients answering the follow-up were working. More than half of the 27 Group Psychotherapy patients responding were working. However, more Group Psychotherapy patients had jobs waiting when they entered treatment, and several had just left the hospital. 10. Cognitive complexity was not correlated to prominence or hyperdependency within the group, but it was related to a tendency to engage in conflict. Cognitive complexity was correlated to participation in group discussion. These conclusions applied only

Dynamical Patterns of Cattle Trade Movements

Despite their importance for the spread of zoonotic diseases, our understanding of the dynamical aspects characterizing the movements of farmed animal populations remains limited as these systems are traditionally studied as static objects and through simplified approximations. By leveraging on the network science approach, here we are able for the first time to fully analyze the longitudinal dataset of Italian cattle movements that reports the mobility of individual animals among farms on a daily basis. The complexity and inter-relations between topology, function and dynamical nature of the system are characterized at different spatial and time resolutions, in order to uncover patterns and vulnerabilities fundamental for the definition of targeted prevention and control measures for zoonotic diseases. Results show how the stationarity of statistical distributions coexists with a strong and non-trivial evolutionary dynamics at the node and link levels, on all timescales. Traditional static views of the displacement network hide important patterns of structural changes affecting nodes' centrality and farms' spreading potential, thus limiting the efficiency of interventions based on partial longitudinal information. By fully taking into account the longitudinal dimension, we propose a novel definition of dynamical motifs that is able to uncover the presence of a temporal arrow describing the evolution of the system and the causality patterns of its displacements, shedding light on mechanisms that may play a crucial role in the definition of preventive actions