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Institute
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.
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.
Context awareness is critical for the successful execution of processes. In the abundance of business process management (BPM) research, frameworks exclusively devoted to extracting context from textual process data are scarce. With the deluge of textual data and its increasing value for organizations, it becomes essential to employ relevant text analytics techniques to increase the awareness of process workers, which is important for process execution. The present paper addresses this demand by developing a framework for context awareness based on process executions-related textual data using a well-established layered BPM context model. This framework combines and maps various text analytics techniques to the layers of the context model, aiming to increase the context awareness of process workers and facilitate informed decision-making. The framework is applied in an IT ticket processing case study. The findings show that contextual information obtained using our framework enriches the awareness of process workers regarding the process instance urgency, complexity, and upcoming tasks and assists in making decisions in terms of these aspects.
Compliance-Management
(2023)
Dieses Buch bietet eine komprimierte und praxisorientierte Einführung in die Grundlagen und Anforderungen eines Compliance-Managements, um den Leser schnell mit aktuellen und zentralen Regelungen vertraut zu machen. Dabei wird auf gesetzliche und regulatorische Bestimmungen ebenso eingegangen wie auf betriebswirtschaftliche Notwendigkeiten, um Mitarbeitende und Unternehmen vor den schwerwiegenden Folgen von Compliance-Verstößen zu schützen.
Limitierende Faktoren
(2023)
Wie bei allen Risiken gibt es auch bei Compliance-Risiken kein Null-Risiko. Man wird in der Praxis noch nicht einmal in die unmittelbare Nähe einer Null kommen. Ein Null-Compliance-Risiko ist auch deshalb nicht erreichbar, weil sich ständig neue Risikofelder auftun. So beispielsweise durch Änderung von Geschäftsmodellen oder Vertriebswegen oder durch neue rechtliche Rahmenbedingen.
Unsere Welt verändert sich in unterschiedlichen Tempi und Verwerfungstiefen. Dies ist das einzig Verlässliche für Wirtschaft und Gesellschaft.
Zum einen zählt die kreative Zerstörung zum ‚Markenkern‘ marktwirtschaftlicher Systeme. Die Wirtschaftsakteure stehen dadurch an ihrem jeweiligen Standort unter einer Art (produktivem) Dauerstress. Es gibt Gewinner und Verlierer, weil Wettbewerber unterschiedlich erfolgreich kostensenkende Rationalisierungen, technischen Fortschritt und die Erschließung neuer (globaler) Märkte realisieren. Der damit einhergehende Strukturwandel gilt als wirtschaftssystemischer Normalzustand.
Zum anderen gibt es Krisen. Und auch ‚unter Schock‘ (re-)agieren Akteure ungleich, wie die Corona-Pandemie oder abrupte Veränderungen durch die Finanzkrise zeigen. Einige Akteure und Standorte bleiben mit ihrem jeweiligen Profil und Potenzial (weiterhin) produktiv widerstandsfähig. Für andere verschärfen sich der wirtschaftliche Niedergang und dessen Folgen für die Arbeitsmärkte und Lebensqualität der Betroffenen.
Regionale Wirtschaftsförderung unterstützt, dass sich die Wirtschaftsstrukturen an einem Standort überlebensfähig ausrichten. Doch kann sie auch beim Umgang mit Krisen einen Mehrwert erzielen und zählt dies überhaupt zu ihrem Regelauftrag? Und welche Rolle spielt die Digitalisierung? Der Beitrag stellt den sachlogischen Zusammenhang zwischen diesen Teilfragen her und ordnet neuere Ansätze ein. Zudem werden Ansatzstellen aufgezeigt, um die regionale Wirtschaftsförderung praxisorientiert weiterzuentwickeln. ‚Electronic Government‘ (E-Government) beschreibt dabei den Einsatz von Informationstechnik, Telekommunikation und Medien (ITKM) im öffentlichen Sektor, während ‚Electronic Governance‘ (E-Governance) hybride oder private Akteure miteinbezieht.
Der Beitrag ist wie folgt strukturiert: Zunächst werden Schlüsselbegriffe wie Strukturpolitik und Resilienz geklärt und mit den Kontextfaktoren verknüpft, welche die Steuerungslogik von Wirtschaftsförderung bestimmen. Danach wird diskutiert, inwiefern die Wirtschaftsförderung E-Government und E-Governance nutzen kann, um Resilienz zu stärken und möglichst transformativ wirken zu können.
Digital transformation initiatives in small and medium-sized enterprises (SME) are often hampered by individual practitioners' perceptions of information and communication technology (ICT). This research employs an educational escape room (ER) game for an intervention towards informed decision-making on ICT adoption in SMEs. ER design and implementation are elaborated and consequently tested with SME practitioners, all embedded in an action-design study based on a qualitative research methodology. The result highlights a trade-off between creating immersive game experiences and achieving learning objectives. Still, the outcome implies an impact on players' perception of ICT integrated in the ER. The findings contribute to the emerging field of serious games for learning and shed light on the potential of game-based interventions for SMEs.
Ubiquitous Music is an interdisciplinary research area that combines methodologies from music, computer science, education, creativity studies, human sciences and engineering.
The Ubiumus 2023 symposium, held at Ulster University and North West Regional College in Derry~Londonderry, Northern Ireland, included contributions on the following topics:
Rapid Prototyping and Live Environments
Ecological Approaches to Ubiquitous Music
Ubiquitous Music Creative Practices, Tools and Influences
The symposium also included a number of artistic contributions and workshops, which are also discussed in the proceedings volume. A number of events (including all paper presentations, an invited lecture, a panel discussion, and a keynote and associated performance) were also documented via video, with a link available in this Proceedings volume.
This paper presents a study on the feasibility of using large language models (LLM) for coding with low-resource and domain-specific programming languages that typically lack the amount of data required for effective LLM processing techniques. This study focuses on the econometric scripting language named hansl of the open-source software gretl and employs a proprietary LLM based on GPT-3.5. Our findings suggest that LLMs can be a useful tool for writing, understanding, improving, and documenting gretl code, which includes generating descriptive docstrings for functions and providing precise explanations for abstract and poorly documented econometric code. While the LLM showcased promoting docstring-to-code translation capability, we also identify some limitations, such as its inability to improve certain sections of code and to write accurate unit tests. This study is a step towards leveraging the power of LLMs to facilitate software development in low-resource programming languages and ultimately to lower barriers to entry for their adoption.