TY - BOOK A1 - Borgeest, Kai T1 - Messtechnik und Prüfstände für Verbrennungsmotoren N2 - Dieses Buch vermittelt sowohl Studenten, als auch Planern und Betreibern in Industrie und Wissenschaft das nötige umfangreiche Wissen, um Messungen an Motorenprüfständen durchführen zu können. Messtechnik und Prüfstände für Verbrennungsmotoren helfen, Kraftstoff einzusparen, Treibhausgase und Schadstoffe zu reduzieren, mit kleineren Motoren mehr Leistung abzugeben sowie Komponenten und Betriebsstoffe zu optimieren. Mit den Motoren und der Abgasgesetzgebung entwickelt sich auch die für die Entwicklung erforderliche mechanische, thermodynamische und Abgasmesstechnik weiter. KW - Kraftfahrzeugtechnik KW - Verbrennungsmotor KW - Messtechnik KW - Regelungstechnik KW - Verbrennungsmotor KW - Abgas KW - Messtechnik KW - Motorenprüfstand KW - Thermodynamik KW - Prüfstand Y1 - 2024 UR - https://link.springer.com/book/10.1007/978-3-658-43284-3 SN - 978-3-658-43283-6 U6 - https://doi.org/10.1007/978-3-658-43284-3 VL - 2024 PB - Springer Vieweg CY - Wiesbaden ET - 3., überarbeitete und erweiterte Auflage ER - TY - CHAP A1 - Smeets, Mario A1 - Rötzel, Peter T1 - The Moderating Role of Relative Performance Information in Reducing Algorithm Aversion In The Adoption Of AI-Based Decision Support Systems in Insolvency Prediction Tasks T2 - 4th ENEAR Conference at Erasmus University Rotterdam N2 - The integration of Artificial Intelligence (AI) into decision-making processes emerges as a pivotal strategy for enhancing organizational performance. The paper delves into the criticality of trust in AI-based Decision Support Systems (DSSs), similar to the trust required for other (Accounting) information systems to integrate them efficiently. We explore the disruptive phenomenon known as "algorithm aversion" - a significant barrier to the trust and acceptance of AI. Although AI recommendations outperform human recommendations in different decision-making fields, there exists a tendency among individuals to underweight AI-based DSSs recommendations relative to those from human decision-makers. This underutilization is attributed to the lack of trust in AI. We conducted a laboratory experiment designed to investigate the role of AI recommendations in a workplace-related task in the field of financial accounting. The study is twofold: firstly, it examines how AI trust mediates and algorithm aversion adversely impacts decision-making performance, while also considering the moderating role of technical competence. Secondly, it investigates the potential of gamification by using means of Relative Performance Information (RPI) as a strategy to mitigate the effects of algorithm aversion. Through this experiment, we provide empirical evidence on methods to enhance decision-making performance in the context of AI recommendations. Additionally, we identify and propose counterstrategies to combat algorithm aversion, thereby facilitating the broader adoption and integration of AI-based DSSs in accounting and auditing settings. This study contributes to the accounting and auditing research community by offering insights into how AI can be more effectively incorporated into decision-making processes, addressing both psychological and technical barriers to its acceptance. KW - artificial intelligence KW - algorithm aversion KW - relative performance information KW - Künstliche Intelligenz KW - Entscheidungsprozess KW - Rechnungslegung KW - Wirtschaftsprüfung Y1 - 2024 VL - 4 IS - 1 SP - 1 EP - 18 ER - TY - JOUR A1 - Sallum, Loriz Francisco A1 - Alves, Caroline A1 - Thielemann, Christiane A1 - Rodrigues, Francisco A. T1 - Revealing patterns in major depressive disorder with machine learning and networks JF - medrxiv N2 - Major depressive disorder (MDD) is a multifaceted condition that affects millions of people worldwide and is a leading cause of disability. There is an urgent need for an automated and objective method to detect MDD due to the limitations of traditional diagnostic approaches. In this paper, we propose a methodology based on machine and deep learning to classify patients with MDD and identify altered functional connectivity patterns from EEG data. We compare several connectivity metrics and machine learning algorithms. Complex network measures are used to identify structural brain abnormalities in MDD. Using Spearman correlation for network construction and the SVM classifier, we verify that it is possible to identify MDD patients with high accuracy, exceeding literature results. The SHAP (SHAPley Additive Explanations) summary plot highlights the importance of C4-F8 connections and also reveals dysfunction in certain brain areas and hyperconnectivity in others. Despite the lower performance of the complex network measures for the classification problem, assortativity was found to be a promising biomarker. Our findings suggest that understanding and diagnosing MDD may be aided by the use of machine learning methods and complex networks. KW - Depression KW - Elektroencephalographie KW - Maschinelles Lernen Y1 - 2024 U6 - https://doi.org/doi.org/10.1101/2024.06.07.24308619 VL - 2024 IS - 1 SP - 1 EP - 17 ER - TY - JOUR A1 - Szewczyk, Nathaniel J. A1 - Monici, Monica A1 - Thielemann, Christiane T1 - How to obtain an integrated picture of the molecular networks involved in adaptation to microgravity in different biological systems? JF - npj Microgravity N2 - Periodically, the European Space Agency (ESA) updates scientific roadmaps in consultation with the scientific community. The ESA SciSpacE Science Community White Paper (SSCWP) 9, “Biology in Space and Analogue Environments”, focusses in 5 main topic areas, aiming to address key community-identified knowledge gaps in Space Biology. Here we present one of the identified topic areas, which is also an unanswered question of life science research in Space: “How to Obtain an Integrated Picture of the Molecular Networks Involved in Adaptation to Microgravity in Different Biological Systems?” The manuscript reports the main gaps of knowledge which have been identified by the community in the above topic area as well as the approach the community indicates to address the gaps not yet bridged. Moreover, the relevance that these research activities might have for the space exploration programs and also for application in industrial and technological fields on Earth is briefly discussed. KW - Weltraumforschung KW - Biowissenschaften Y1 - 2024 U6 - https://doi.org/DOI: 10.1038/s41526-024-00395-3 VL - 2024 IS - 10 SP - 1 EP - 5 ER - TY - BOOK A1 - Lauer, Thomas T1 - Change Management: Grundlagen und Erfolgsfaktoren KW - Change Management KW - Erfolgsfaktor KW - Agilität Management Y1 - 2019 SN - 978-3-662-59101-7 U6 - https://doi.org/10.1007/978-3-662-59102-4 PB - Springer Gabler CY - Berlin ET - 3., vollständig überarbeitete und erweiterte Auflage ER - TY - RPRT A1 - Jost, Thomas A1 - Mink, Reimund T1 - Central bank losses and commercial bank profits - unexpected and unfair? T2 - IMFS Working Paper Series No. 199 N2 - The Eurosystem and the Deutsche Bundesbank will incur substantial losses in 2023 that are likely to persist for several years. Due to the massive purchases of securities in the last 10 years, especially of government bonds, the banks' excess reserves have risen sharply. The resulting high interest payments to the banks since the turnaround in monetary poli-cy, with little income for the large-scale securities holdings, led to massive criticism. The banks were said to be making "unfair" profits as a result, while the fiscal authorities had to forego the previously customary transfers of central bank profits. Populist demands to limit bank profits by, for example, drastically increasing the minimum reserve ratios in the Eurosystem to reduce excess reserves are creating new severe problems and are neither justified nor helpful. Ultimately, the EU member states have benefited for a very long time from historically low interest rates because of the Eurosystem's extraordinary loose monetary policy and must now bear the flip side consequences of the massive expansion of central bank balance sheets during the necessary period of monetary policy normalisa-tion. KW - Notenbank KW - Geldpolitik KW - Geschäftsbank KW - Deutsche Bundesbank KW - Central bank losses, monetary policy, ecb, minimum reserve Y1 - 2024 UR - https://www.econbiz.de/Record/central-bank-losses-and-commercial-bank-profits-unexpected-and-unfair-jost-thomas/10014476309 ER - TY - GEN A1 - Jost, Thomas A1 - Mink, Reimund T1 - How to deal with the negative effects of inflated central bank balance sheets? N2 - Due to the massive purchases of securities in the last 15 years central banks incur substantial losses likely to persist for several years. On the other hand, the banking sector gains large profits from interest payments on their excess reserves holdings. Central banks and fiscal authorities must now bear the flip side consequences of their bond purchase programs. Populist demands to limit bank profits by drastically increasing minimum reserve ratios in the Eurosystem are creating new severe problems. Instead, a consistent and faster normalisation of central bank balance sheets would be desirable. Central banks should also no longer be central players in government bond markets to restore the lost boundaries between fiscal and monetary policy. KW - Europäische Zentralbank KW - Geldpolitik KW - Notenbank KW - ecb, minimum reserve, monetary policy Y1 - 2024 UR - https://www.suerf.org/wp-content/uploads/2024/04/SUERF-Policy-Brief-860_Jost-Mink.pdf SP - 1 EP - 4 ER - TY - BOOK A1 - Hofmann, Georg Rainer A1 - Scheidler, Percy T1 - Chief Qualification Officer (CQO) und Weiterbildungsmentoren N2 - Alte Weisheiten wie „Schuster bleib bei deinem Leisten!“ oder auch „Was das Hänschen nicht lernt, das lernt der Hans nimmermehr“ haben in der heutigen, sich wandelnden Arbeitswelt ihren Sinn verloren. Das bedeutet, dass sich die komplette Belegschaft lebenslang weiterbilden muss, idealerweise mit Unterstützung des Arbeitgebers. In der Veröffentlichung "Chief Qualification Officers (CQOs) und Weiterbildungsmentoren - Thesen und Argumente" wird unter anderem das paradoxe Verhältnis von Arbeitslosigkeit und Fachkräftemangel erläutert, das Marktversagen im Weiterbildungsmarkt beschrieben und die Forderung nach einem Weiterbildungsbeauftragten (CQO) begründet. KW - Weiterbildungsmentoren KW - Weiterbildung KW - Erwachsenenbildung KW - Lebenslanges Lernen Y1 - 2024 UR - https://www.mainproject.eu/shop SN - 978-3-9826305-0-2 ER - TY - CHAP A1 - Smeets, Mario A1 - Rötzel, Peter T1 - The Moderating Role of Non-Monetary Gamification in Reducing Algorithm Aversion in the Adoption of AI-based Decision Support Systems T2 - ECIS - European Conference on Information Systems N2 - Integrating artificial intelligence (AI) into decision-making processes is key to improving organizational performance. However, trust in AI-based decision support systems (DSSs), similar to other information systems, is important for successful integration. A disruptive phenomenon, “algorithm aversion”, can impede AI trust and, thus, acceptance. Although AI recommendations outperform human recommendations in different decision-making fields, individuals underweight recommendations from AI-based DSSs compared to human decision-makers due to a lack of AI trust. We conducted a lab experiment to investigate the role of AI recommendations in workplace-related tasks, first focusing on the mediating effect of AI trust and the negative impact of algorithm aversion on decision-making performance and the moderating effect of technical competence. Second, we analyzed the ability of gamification to reduce this phenomenon. We provide evidence regarding how to enhance decision-making performance when AI recommendations are deployed and identify countermeasures against algorithm aversion to facilitate the adoption of AI-based DSSs. KW - Decision Support Systems KW - Algorithm Aversion KW - Gamification KW - Künstliche Intelligenz KW - Gamification Y1 - 2024 VL - 2024 IS - 1 ER - TY - CHAP A1 - Sauer, Jonas A1 - Hoppe, Florian A1 - Bruhm, Hartmut T1 - Modellierung des Antriebsstrangs einer Textilmaschine zum Zweck der modellbasierten Steuerung T2 - Tagungsband AALE 2024, 20. Konferenz N2 - Zur Produktion von gewirkten Textilien werden mehrere Nadeln auf eine Legebarre gesetzt, die durch Servoantriebe positioniert werden. Aufgrund der erzwungenen Bewegung kann der Antriebsstrang bei hohen Drehzahlen zur Schwingung angeregt werden. Die richtige Wahl der Steuerkurven ist daher eine sehr wichtige und anspruchsvolle Aufgabe, die durch ein Antriebsstrangmodell unterstützt werden soll. Dafür wird am Beispiel eines Teststands ein Modell des Antriebsstranges in MATLAB/Simulink® entwickelt. Für das Antriebsstrangmodell müssen eine geeignete Modellordnung und Modellparameter gewählt werden. Die unbekannten Modellparameter werden durch eine Parameteridentifikation ermittelt. Mit einer Validierung wird ein geeignetes Anregungsspektrum für die Bestimmung der Modellordnung und die Parameteridentifikation ermittelt. KW - Textilmaschine KW - Triebstrang KW - MATLAB KW - SIMULINK KW - Modellierung KW - Grey-Box-Modell KW - Parameteridentifikation KW - MATLAB/ Simulink® KW - Inverses Modell KW - Input Shaping Y1 - 2024 U6 - https://doi.org/https://doi.org/10.33968/2024.33 VL - 2024 ER -