TY - JOUR A1 - Sandmann, Michael A1 - Münzberg, Marvin A1 - Bressel, Lena A1 - Reich, Oliver A1 - Hass, Roland T1 - Inline monitoring of high cell density cultivation of Scenedesmus rubescens in a mesh ultra-thin layer photobioreactor by photon density wave spectroscopy JF - BMC Research Notes / Biomed Central N2 - Objective Due to multiple light scattering that occurs inside and between cells, quantitative optical spectroscopy in turbid biological suspensions is still a major challenge. This includes also optical inline determination of biomass in bioprocessing. Photon Density Wave (PDW) spectroscopy, a technique based on multiple light scattering, enables the independent and absolute determination of optical key parameters of concentrated cell suspensions, which allow to determine biomass during cultivation. Results A unique reactor type, called "mesh ultra-thin layer photobioreactor" was used to create a highly concentrated algal suspension. PDW spectroscopy measurements were carried out continuously in the reactor without any need of sampling or sample preparation, over 3 weeks, and with 10-min time resolution. Conventional dry matter content and coulter counter measurements have been employed as established offline reference analysis. The PBR allowed peak cell dry weight (CDW) of 33.4 g L-1. It is shown that the reduced scattering coefficient determined by PDW spectroscopy is strongly correlated with the biomass concentration in suspension and is thus suitable for process understanding. The reactor in combination with the fiber-optical measurement approach will lead to a better process management. KW - Photon density wave spectroscopy KW - Multiple light scattering KW - Process KW - analytical technology KW - Fiber-optical spectroscopy KW - Mesh ultra-thin layer KW - photobioreactor Y1 - 2022 U6 - https://doi.org/10.1186/s13104-022-05943-2 SN - 1756-0500 VL - 15 IS - 1 PB - Biomed Central (London) CY - London ER - TY - JOUR A1 - Ewelt-Knauer, Corinna A1 - Schwering, Anja A1 - Winkelmann, Sandra T1 - Probabilistic audits and misreporting BT - the influence of audit process design on employee behavior JF - European accounting review N2 - We investigate how the design of audit processes influences employees’ reporting decisions. We focus specifically on detective employee audits for which several employees are randomly selected after a defined period to audit their ex-post behavior. We investigate two design features of the audit process, namely, employee anonymity and process transparency, and analyze their impact on misreporting. Overall, we find that both components influence the extent of individuals’ misreporting. A nonanonymous audit decreases performance misreporting more than an audit in which the employee remains anonymous. Furthermore, the high incidence of performance misreporting in the case of anonymous audits can be decreased when the process transparency is low. Thus, our study informs accountants about how the two design features of employee anonymity and transparency of the audit process can be used to constrain performance misreporting to increase the efficiency of audits KW - Performance misreporting KW - Employee audits KW - Employee anonymity KW - Process KW - transparency Y1 - 2021 U6 - https://doi.org/10.1080/09638180.2021.1899014 SN - 1468-4497 SN - 0963-8180 VL - 30 IS - 5 SP - 989 EP - 1012 PB - Routledge CY - London ER - TY - THES A1 - Grum, Marcus T1 - Construction of a concept of neuronal modeling N2 - The business problem of having inefficient processes, imprecise process analyses, and simulations as well as non-transparent artificial neuronal network models can be overcome by an easy-to-use modeling concept. With the aim of developing a flexible and efficient approach to modeling, simulating, and optimizing processes, this paper proposes a flexible Concept of Neuronal Modeling (CoNM). The modeling concept, which is described by the modeling language designed and its mathematical formulation and is connected to a technical substantiation, is based on a collection of novel sub-artifacts. As these have been implemented as a computational model, the set of CoNM tools carries out novel kinds of Neuronal Process Modeling (NPM), Neuronal Process Simulations (NPS), and Neuronal Process Optimizations (NPO). The efficacy of the designed artifacts was demonstrated rigorously by means of six experiments and a simulator of real industrial production processes. N2 - Die vorliegende Arbeit addressiert das Geschäftsproblem von ineffizienten Prozessen, unpräzisen Prozessanalysen und -simulationen sowie untransparenten künstlichen neuronalen Netzwerken, indem ein Modellierungskonzept zum Neuronalen Modellieren konstruiert wird. Dieses neuartige Konzept des Neuronalen Modellierens (CoNM) fungiert als flexibler und effizienter Ansatz zum Modellieren, Simulieren und Optimieren von Prozessen mit Hilfe von neuronalen Netzwerken und wird mittels einer Modellierungssprache, dessen mathematischen Formalisierung und technischen Substanziierung sowie einer Sammlung von neuartigen Subartefakten beschrieben. In der Verwendung derer Implementierung als CoNM-Werkzeuge können somit neue Arten einer Neuronalen-Prozess-Modellierung (NPM), Neuronalen-Prozess-Simulation (NPS) sowie Neuronalen-Prozess-Optimierung (NPO) realisiert werden. Die Wirksamkeit der erstellten Artefakte wurde anhand von sechs Experimenten demonstriert sowie in einem Simulator in realen Produktionsprozessen gezeigt. T2 - Konzept des Neuronalen Modellierens KW - Deep Learning KW - Artificial Neuronal Network KW - Explainability KW - Interpretability KW - Business Process KW - Simulation KW - Optimization KW - Knowledge Management KW - Process Management KW - Modeling KW - Process KW - Knowledge KW - Learning KW - Enterprise Architecture KW - Industry 4.0 KW - Künstliche Neuronale Netzwerke KW - Erklärbarkeit KW - Interpretierbarkeit KW - Geschäftsprozess KW - Simulation KW - Optimierung KW - Wissensmanagement KW - Prozessmanagement KW - Modellierung KW - Prozess KW - Wissen KW - Lernen KW - Enterprise Architecture KW - Industrie 4.0 Y1 - 2021 ER -