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An approach for analyzing business process execution complexity based on textual data and event log
(2023)
With the advent of digital transformation, organizations increasingly rely on various information systems to support their business processes (BPs). Recorded data, including textual data and event log, expand exponentially, complicating decision-making and posing new challenges for BP complexity analysis in Business Process Management (BPM). Herein, Process Mining (PM) serves to derive insights based on historic BP execution data, called event log. However, in PM, textual data is often neglected or limited to BP descriptions. Therefore, in this study, we propose a novel approach for analyzing BP execution complexity by combining textual data serving as an input at the BP start and event log. The approach is aimed at studying the connection between complexities obtained from these two data types. For textual data-based complexity, the approach employs a set of linguistic features. In our previous work, we have explored the design of linguistic features favorable for BP execution complexity prediction. Accordingly, we adapt and incorporate them into the proposed approach. Using these features, various machine learning techniques are applied to predict textual data-based complexity. Moreover, in this prediction, we show the adequacy of our linguistic features, which outperformed the linguistic features of a widely-used text analysis technique. To calculate event log-based complexity, the event log and relevant complexity metrics are used. Afterward, a correlation analysis of two complexities and an analysis of the significant differences in correlations are performed. The results serve to derive recommendations and insights for BP improvement. We apply the approach in the IT ticket handling process of the IT department of an academic institution. Our findings show that the suggested approach enables a comprehensive identification of BP redesign and improvement opportunities.
Large three-dimensional metallic parts can be printed layer-by-layer using gas metal arc directed energy deposition (GMA-DED) process at a high deposition rate and with little or no material wastage. Fast responsive real-time monitoring of GMA-DED process signatures and their transient variations is required for printing of dimensionally accurate and structurally sound parts. A systematic experimental investigation is presented here on multi-layer GMA-DED with two different scanning strategies using a high strength low alloy (HSLA) filler wire. The dynamic metal transfer, melt pool temperature field and its longitudinal cross-section, and arc voltage and current are monitored synchronously. The transient arc heat input and the melt pool solidification cooling rate are estimated from the monitored signals. The layer-wise variations of the melt pool dimension, surface temperature profile, thermal cycles, and solidification cooling rate are examined for different scanning strategies. It is comprehended that the part defects can be minimized, and the mass production of zero-defect parts can be achieved in GMA-DED process with synchronized monitoring and assessment of the real-time process signatures.
When a droplet is brought in contact with an undercooled surface, it wets the substrate and solidifies at the same time. The interplay between the phase transition effects and the contact-line motion, leading to its arrest, remains poorly understood. Here we reveal the early solidification patterns and dynamics of spreading hexadecane droplets. Total internal reflection imaging is employed to temporally and spatially resolve the early solidification behavior. With this, we determine the conditions leading to the contact-line arrest. We quantify the overall nucleation behavior, i.e., the nucleation rate and the crystal growth speed and show its sensitivity to the applied undercooling of the substrate. We also show that for strong enough undercooling it is the rapid growth of the crystals which determines the eventual arrest of the spreading contact line. By combining the Johnson-Mehl-Avrami-Kolmogorov nucleation theory and scaling relations for the spreading, we calculate the temporal evolution of the solid area fraction, which is in good agreement with our observations.
A central idea of ubiquitous music is that music does not arise from the ideas of an isolated genius, but rather from the interaction of several participants [Keller et al. 2014]. But this requires a certain amount of restraint on the part of the designers of the respective setting and at the same time seems to require a full disclosure of the underlying theoretical and aesthetic concepts to the participants, if the participants are really to be taken seriously and given the means to actually be able to become creative themselves in an understandable way within the given context. In this paper, the consequences of such a demand are first discussed theoretically. Finally, for the concept developed by the author, ”Every human being can compose on the basis of natural numbers”, an attempt is made in this specific case to determine in what form such a concept could be passed on in order to meet the above criteria.
Der Erwartungswert einer Zufallsgröße kann generell am Graphen ihrer Verteilungsfunktion durch eine naheliegende Gleichheit zweier Flächeninhalte festgelegt werden. Äquivalent dazu lässt er sich mit zwei uneigentlichen Riemann-Integralen darstellen. Davon ausgehend werden die Tschebyschow-Ungleichung und ihre Modifikation mit strikten Ungleichheitszeichen hergeleitet.