Investigating the trade-off between the effectiveness and efficiency of process modeling

Despite recent efforts to improve the quality of process models, we still observe a significant dissimilarity in quality between models. This paper focuses on the syntactic condition of process models, and how it is achieved. To this end, a dataset of 121 modeling sessions was investigated. By going through each of these sessions step by step, a separate ‘revision’ phase was identified for 81 of them. Next, by cutting the modeling process off at the start of the revision phase, a partial process model was exported for these modeling sessions. Finally, each partial model was compared with its corresponding final model, in terms of time, effort, and the number of syntactic errors made or solved, in search for a possible trade-off between the effectiveness and efficiency of process modeling. Based on the findings, we give a provisional explanation for the difference in syntactic quality of process models

Doctor of Philosophy

dissertationMemory access irregularities are a major bottleneck for bandwidth limited problems on Graphics Processing Unit (GPU) architectures. GPU memory systems are designed to allow consecutive memory accesses to be coalesced into a single memory access. Noncontiguous accesses within a parallel group of threads working in lock step may cause serialized memory transfers. Irregular algorithms may have data-dependent control flow and memory access, which requires runtime information to be evaluated. Compile time methods for evaluating parallelism, such as static dependence graphs, are not capable of evaluating irregular algorithms. The goals of this dissertation are to study irregularities within the context of unstructured mesh and sparse matrix problems, analyze the impact of vectorization widths on irregularities, and present data-centric methods that improve control flow and memory access irregularity within those contexts. Reordering associative operations has often been exploited for performance gains in parallel algorithms. This dissertation presents a method for associative reordering of stencil computations over unstructured meshes that increases data reuse through caching. This novel parallelization scheme offers considerable speedups over standard methods. Vectorization widths can have significant impact on performance in vectorized computations. Although the hardware vector width is generally fixed, the logical vector width used within a computation can range from one up to the width of the computation. Significant performance differences can occur due to thread scheduling and resource limitations. This dissertation analyzes the impact of vectorization widths on dense numerical computations such as 3D dG postprocessing. It is difficult to efficiently perform dynamic updates on traditional sparse matrix formats. Explicitly controlling memory segmentation allows for in-place dynamic updates in sparse matrices. Dynamically updating the matrix without rebuilding or sorting greatly improves processing time and overall throughput. This dissertation presents a new sparse matrix format, dynamic compressed sparse row (DCSR), which allows for dynamic streaming updates to a sparse matrix. A new method for parallel sparse matrix-matrix multiplication (SpMM) that uses dynamic updates is also presented

Toward a Taxonomy of Modeling Difficulties: A Multi-Modal Study on Individual Modeling Processes

Conceptual modeling is an essential activity during information systems development and, accordingly, a learning task faced by students of Information Systems. Presently, surprisingly little is known about how learning processes of conceptual modeling proceed, and about modeling difficulties learners experience. In this study, we integrate complementary modes of observation of learners\u27 modeling processes to identify modeling difficulties these learners face while performing a data modeling task using a modeling tool. We use the concept of cognitive breakdowns to analyze verbal protocols, recordings of learner-tool interactions and video recordings of learners\u27 modeling processes and survey learners about modeling difficulties. Our study identifies five types of modeling difficulties relating to different aspects of constructing conceptual data models, i.e., entity types, relationship types, attributes, and cardinalities. The identified types of modeling difficulties motivate a taxonomic theory of modeling difficulties intended to inform design science research on tool support for learners of conceptual modeling

How Healthcare Professionals Comprehend Process Models - An Empirical Eye Tracking Analysis

Digitization is advancing rapidly in many prevalently analogue domains such as healthcare. For the latter domain, the synergies with modern information technologies (IT)have become an integral part regarding communication and collaboration. For this reason, a comprehensible language is of importance in order to allow for a frictionless exchange of information between domain experts. The Business Process Model and Notation (BPMN) 2.0 represents a promising notation that may be applied as lingua franca. Although BPMN 2.0 is widespread and applied by experts in business and industry, little experience exists on how BPMN 2.0 is adopted in healthcare. In order to assess how BPMN 2.0 is deployed in healthcare, we conducted a preliminary eye tracking study, in which n = 16 professionals from healthcare comprehended a particular BPMN 2.0 process model. The results indicate that BPMN 2.0 might be a candidate for a lingua franca to foster the comprehensible exchange of information as well as collaboration between healthcare and I

Who is behind the Model? Classifying Modelers based on Pragmatic Model Features

\u3cp\u3eProcess modeling tools typically aid end users in generic, non-personalized ways. However, it is well conceivable that different types of end users may profit from different types of modeling support. In this paper, we propose an approach based on machine learning that is able to classify modelers regarding their expertise while they are creating a process model. To do so, it takes into account pragmatic features of the model under development. The proposed approach is fully automatic, unobtrusive, tool independent, and based on objective measures. An evaluation based on two data sets resulted in a prediction performance of around 90%. Our results further show that all features can be efficiently calculated, which makes the approach applicable to online settings like adaptive modeling environments. In this way, this work contributes to improving the performance of process modelers.\u3c/p\u3

Assessing an Age-Graded Theory of Informal Social Control: Are There Conditional Effects of Life Events in the Desistance Process?

In 1993, Sampson and Laub presented their age-graded theory of informal social control in Crime in the Making: Pathways and Turning Points Through Life. In essence, Sampson and Laub state that, among offenders, strong social bonds stemming from a variety of life events predict desistance from criminal offending in adulthood. In the past decade, there has been a growing amount of research supporting this general finding. However, little research has examined the potential conditional effects of life events on desistance. Using Sheldon and Eleanor Gluecks' Unraveling Juvenile Delinquency data, their follow-up data to age 32, and the long-term follow-up data collected by John Laub and Robert Sampson, this research focuses on the potential conditional effects of marital attachment, stable employment, honorable military service, and long-term juvenile incarceration on criminal offending over the life course. Specifically, the present study tests Sampson and Laub's notion that strong social bonds predict desistance by asking two fundamental questions that bear on both theory and policy surrounding desistance from crime. First, does a high level of social integration as evidenced by the accumulation of social bonds stemming from life events within the same individual influence a person's level of offending and/or rate of desistance? Second, does the individual risk factor of low self-control or the related protective factor of adolescent competence interact with life events such that they differentially influence adult offending patterns? Using the longitudinal methodologies of semiparametric mixed Poisson modeling and hierarchical linear modeling, the analyses find additional support for Sampson and Laub's theory. First, a person's level of social integration significantly affects his future offending patterns even after controlling for criminal propensity and prior adult crime. Second, no significant interaction effects emerge between life events and individual characteristics on future offending patterns. The conclusion then is that a high level of social bonding within the same individual influences offending, regardless of a person's level of self-control or adolescent competence. The implications of this research for life-course theories of crime, future research, and policies regarding desistance are discussed