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Dämmstoffe aus nachwachsenden Rohstoffen in der Bauteilprognose mittels der Finiten-Elemente-Methode
(2020)
Bauakustik meets BIM
(2020)
Die Berechnung des bewerteten Norm-Trittschallpegels im Bau L'n,w erfolgt aktuell in der DIN 4109-2:2018 sowohl für den Massivbau als auch für den Holz-, Leicht- und Trockenbau unter Berücksichtigung relativ pauschaler Korrekturen für die flankierende Schallübertragung. Darüber hinaus unterliegen die derzeitigen Verfahren einigen weiteren gravierenden Beschränkungen des Anwendungsbereiches, die eine Überarbeitung der Verfahren wünschenswert erscheinen lassen. Basierend auf dem neuen vereinfachten Verfahren der DIN EN ISO 12354-2:2017 werden deshalb Berechnungsverfahren auf der Basis von Einzahlangaben vorgestellt, mit denen die direkte und die flankierende Trittschallübertragung, wie beim Luftschall, getrennt berechnet und anschließend aufsummiert werden. Hierdurch ergeben sich deutlich bessere Möglichkeiten, die tatsächliche Bausituation im Rechenmodell abzubilden und somit eine bessere Übereinstimmung zwischen dem prognostizierten und einem gemessenen Wert zu erhalten. Im Massivbau kann beispielsweise eine Vorsatzkonstruktion im Empfangsraum vor dem trennenden oder dem flankierenden Bauteil entsprechend ihrer schalltechnischen Wirkung berücksichtigt werden. Weiterhin können auch horizontale oder diagonale Übertragungssituationen oder die Trittschallübertragung von Treppen abhängig von der jeweiligen baulichen Situation berechnet werden. Die neuen Berechnungsverfahren ermöglichen damit eine wirtschaftlichere Dimensionierung der Bauteile.
Neue Erkenntnisse zur Wichtigkeit ausreichender Tageslichtversorgung im Innenraum haben planungsrelevante Änderungen normativer Vorgaben nach sich gezogen. Renate Hammer und Mathias Wambsganß veranschaulichen die neuen Anforderungen und erläutern die Möglichkeiten zur planerischen Umsetzung. Die Autoren klären, wann Tageslichtversorgung und Besonnung als ausreichend gelten, welche Qualitäten die Sichtverbindung nach außen erfüllen muss und wie Blendung durch Tageslicht zu begrenzen ist. Angaben zur melanopischen Wirkungsweise von Tageslicht bieten einen Einstieg in den planerischen Umgang mit nicht-visuellen Kriterien. Ein weiteres Kapitel zeigt die Schnittstellen mit anderen Aspekten der Bauplanung.
Holzbasierte Bioökonomie
(2020)
Die holzbasierte Bioökonomie beschreibt die innovative Nutzung des Rohstoffs Holz in allen Bereichen der Bioökonomie. Insbesondere versteht sie sich als strategisch altbekannter, aber vor allem als erweiterter, neuartiger Innovationsraum einer Kreislaufwirtschaft mit der gesamten Wertschöpfungskette Holz. Diese erfolgt idealerweise in Form einer sogenannten Nutzungskaskade: vom Forst über die forstlichen Dienstleister, die Sägeindustrie, den Holzbau, die Zellstoff-/Papierindustrie, die Holzwerkstoffindustrie und in zunehmendem Maße bis hin zur chemischen Industrie sowie hinein in moderne Verbrauchs- und Investitionsgüter. Die Nutzungskaskade betrifft damit den gesamten Wirtschaftskreislauf im Kern. Anders als im bisherigen, skalenökonomisch determinierten Wirtschaftsraum muss die Bioökonomie die begrenzte Verfügbarkeit von Ressourcen in Betracht ziehen und zielführende Nachhaltigkeitskriterien beachten. Nutzungskonkurrenzen sollen demzufolge durch intelligente, wertige Verwendung der jeweiligen Holz-, Restholz- und Abfallsortimente weitgehend vermieden werden, wodurch ein tatsächlich sinnvoller Gesamtnutzen für die Gesellschaft möglich erscheint. Um die Bioökonomie umzusetzen und wirtschaftlich zu etablieren, gibt es eine Reihe europäischer, nationaler und regionaler Politikprogramme, Initiativen und Strukturen, die die Forschung und Entwicklung, die Förderung industrieller Umsetzungen und die Etablierung neuer Geschäftsmodelle zum Ziel haben. Deutsche Hochschulen und Universitäten stellen sich auf die entsprechende Erweiterung bzw. Anpassung von Studiengängen ein.
Holz statt Braunkohle
(2020)
Stichwort Sexfluencing.
(2020)
Road network performance (RNP) is a key element for urban sustainability as it has a significant impact on economy, environment, and society. Poor RNP can lead to traffic congestion, which can lead to higher transportation costs, more pollution and health issues regarding the urban population. To evaluate the effects of the RNP, the involved stakeholders need a real-world data base to work with. This paper develops a data collection approach to enable location-based RNP analysis using publicly available traffic information. Therefore, we use reachable range requests implemented by navigation service providers to retrieve travel times, travel speeds, and traffic conditions. To demonstrate the practicability of the proposed methodology, a comparison of four German cities is made, considering the network characteristics with respect to detours, infrastructure, and traffic congestion. The results are combined with cost rates to compare the economical dimension of sustainability of the chosen cities. Our results show that digitization eases the assessment of traffic data and that a combination of several indicators must be considered depending on the relevant sustainability dimension decisions are made from.
Environmental regulations force automotive companies to modify the powertrain technology portfolio offered to the customer to comply with greenhouse gas (GHG) emission targets. Automotive companies, in turn, are faced with the decision of finding the right powertrain technology portfolio because the selection of a particular technology portfolio affects different company targets at the same time. What makes this decision even more interesting is the fact that future market shares of the different technologies are uncertain. With its numerous objectives, this challenge requires multi-criteria decision-making techniques to identify the optimal powertrain technology portfolio. The objective of this research is to present a new decision support approach for assembling optimal powertrain technology portfolios while making decision-makers aware of the trade-offs between the achievable market share, the market share risk, and the GHG emissions generated by the selected vehicle fleet. The proposed approach combines `a posteriori' decision-making, multi-objective optimization, and the Markowitz portfolio theory. In an application case, the outlooks of selected market studies are fed into the proposed decision support system. The result is a visualization and analysis of the current real-world decision-making problem faced by many automotive companies. Interesting findings of this research include that for the assumed GHG restrictions in place in 2030, there exists no optimal powertrain technology portfolio that is not composed of at least 20% of electric vehicles.
VBA mit Excel
(2020)
Dieses Buch bietet eine anwendungsorientierte Einführung in die Programmierung mit Visual Basic for Applications (VBA) in Microsoft Excel. Es ermöglicht auch Einsteigern die selbstständige Lösung kleiner bis mittelgroßer Programmieraufgaben aus dem betriebswirtschaftlichen Alltag. Der Schwierigkeitsgrad der Inhalte ist überwiegend einfach gehalten, sodass Nutzer, die bereits grundlegende Tätigkeiten in MS Excel beherrschen, sich nach ihren jeweiligen Anforderungen entsprechend fortbilden können. Zahlreiche Praxisbeispiele und Übungen, die auf einem Windows-Betriebssystem entwickelt und getestet wurden, unterstützen das Lernen Schritt für Schritt und zeigen, wie hilfreich VBA durch Automatisierung und Individualisierung in jedem Büro sein kann.
Dieses Buch bietet Studierenden mehr als 70 Übungsaufgaben und drei Fallstudien inklusive ausführlicher Lösungen zu ausgewählten Themen der Produktionswirtschaft und Industrie 4.0. Jedes Kapitel enthält eine kurze Einleitung sowie zu erreichende Lernziele. Querverweise auf das Lehrbuch „Produktionswirtschaft“ von Kellner/Lienland/Lukesch erleichtern das Selbststudium und ermöglichen eine optimale Prüfungsvorbereitung. In der 2. Auflage wurden umfangreiche Überarbeitungen hinsichtlich Sprache und Aufbau von Aufgaben, Lösungswegen und Abbildungen vorgenommen sowie zahlreiche neue Aufgaben ergänzt.
Teams are beginning to rely on smart communication technology that is enhanced by Artificial Intelligence (AI). Yet, we lack understanding of how these smart communication technologies (SCT) influence team collaboration, especially in global virtual teams (GVT). This study empirically investigates how cultural values and practices influence the acceptance of SCT and how the use of this technology impacts communication effectiveness in GVT. We surveyed 643 members of 109 GVT before and after using the SCT. Results showed that team members from individualistic, future oriented cultures generally had more positive expectations towards the performance and enjoyment of using the technology. Uncertainty avoidance increased effort expectancy. After using SCT for communicating in the GVT, most differences disappeared. Regarding communication effectiveness, SCT had a positive influence, which was stronger for performance and future oriented cultures.
Virtual teams that use integrated communication platforms are ubiquitous in cross-border collaboration. This study explores the use of communication media and team outcomes—both social outcomes and task accomplishment—in multilingual virtual teams. Based on surveys from 96 virtual teams (with 578 team members), the research shows that the more time spent in rich communication channels, such as online conferences, increased inclusion and satisfaction, whereas the more time spent with written communication that is lower in richness increased the level of task accomplishment. Team members with lower language proficiency felt less included in all collaboration channels, whereas team members with higher language proficiency felt less satisfied with lean collaboration. In addition, limited language proficiency speakers were significantly less likely to view rich tools as helpful for their teams to reach a mutual decision. Our data support media richness theory in its original context for native and highly proficient English speakers. Our study extends the scope of the theory by applying it to the new context of team members with limited language proficiency. Management should implement a collaboration infrastructure consisting of communication platforms that integrate a variety of media to account for different tasks and different communication needs.
Each year, the Virtual Business Professional (VBP) program brings together professors and students from across the globe to engage in client projects. The VBP program of 2020 occurred from the beginning of March through the middle of April. In this article, we share how the COVID-19 pandemic affected VBP participants and their teams. We present post-project survey results (completed by 440 of 530 participants for an 83 percent response rate), professor comments, and student comments to demonstrate how VBP participants overcame many of the pandemic disruptions to work effectively in virtual teams, develop compassion and empathy for one another, and foster more global mindsets.
This study examines the impact of perceived foreign language proficiency on hybrid culture building in multicultural teams. Hybrid culture includes a mutually shared set of norms, communication patterns, problem-solving approaches, and synergistic task coordination that result from the diverse cultural backgrounds of the team members. Language is the main vehicle for communication and plays a major role in social interaction and therefore hybrid culture building. We argue that the level of perceived language proficiency of multicultural team members influences hybrid culture building; consequently, adequate language skills lead not only to an efficient task solution but are also an important factor in creating interpersonal relationships and building a shared culture. Our empirical analysis supports the positive influence of language proficiency in hybrid teams; however, foreign language proficiency is more influential on cognitively oriented areas of multicultural teamwork than on affective ones.
A novel approach to optically distinguish plastics based on fluorescence lifetime measurements
(2020)
In medical and biological research, fluorescence lifetime measurements and fluorescence lifetime imaging is already a part of the standardized analysis procedures. As first investigations have shown, polymers can be identified using fluorescence lifetime imaging and an evaluation algorithm. Thus, this contribution pursues a novel approach for the direct differentiation of four polymers with fluorescence lifetime imaging. Therefore, the evaluation algorithm is extended to compare several fluorescence lifetime images to prove that a distinction is possible.
Im Rahmen der Digitalisierung der industriellen Produktion mit Industrie 4.0 und des autonomen Fahrens erlangen möglichst detaillierte digitale Abbilder von Maschinen und Fahrzeugen für den vollständigen Zeitraum ihres Einsatzes eine zentrale Bedeutung. Sowohl durch geplante Veränderungen des Arbeitspunkts aber auch durch Abnutzung und Verschleiß kommt es zu Abweichungen des Systemverhaltens. In diesem Posterbeitrag werden die Entwicklung und die Anwendung eines Identifikations-Algorithmus für die automatisierte Modellierung eines dynamischen Systems basierend auf einem gemessenen Ein- und Ausgangssignal beschrieben. Der in MATLAB und Simulink programmierte Algorithmus läuft parallel zum realen System auf einer embedded Hardware ab, so dass eine Identifikation online und selbstständig ausgeführt wird. Die prozess- oder verschleißbedingten Veränderungen des Systemverhaltens werden damit unmittelbar bei der Modellierung während des Betriebs berücksichtigt. Im Anschluss an die Identifikation sind die Selbst-Optimierung, die Vorsteuerung und die Selbst-Konfiguration des Systems, z.B. die Anpassung von Reglern, basierend auf dem aktuellen Modell durchführbar.
Artificial Intelligence (AI) and Machine Learning (ML) promise to significantly enhance the capabilities of decision support systems in medicine. Yet, if these systems fail to providean understandable rationale of the decision making process the adoption of this powerful technology will be difficult. Hence, there is growing interest in Explainable Artificial Intelligence (XAI). Explanations that speak the language of the user are a cornerstone for Fair AI. In this position paper, we reflect on research about XAI and designing decision support in medicine. From there, we lay out an approach to use co-design methodology to explore how users perceive and interact with explanations of decision support systems.
Oncologic patients are regarded as the population most at risk of developing a severe course of COVID-19 due to the fact that malignant diseases and chemotherapy often weaken the immune system. In the face of the ongoing SARS-CoV-2 pandemic, how particular patients deal with this infection remains an important question. In the period between the 15 and 26 April 2020, a total of 1227 patients were tested in one of seven oncologic outpatient clinics for SARS-CoV-2, regardless of symptoms, employing RT-qPCR. Of 1227 patients, 78 (6.4%) were tested positive of SARS-CoV-2. Only one of the patients who tested positive developed a severe form of COVID-19 with pneumonia (CURB-65 score of 2), and two patients showed mild symptoms. Fourteen of 75 asymptomatic but positively tested patients received chemotherapy or chemo-immunotherapy according to their regular therapy algorithm (±4 weeks of SARS-CoV-2 test), and 48 of 78 (61.5%) positive-tested patients received glucocorticoids as co-medication. None of the asymptomatic infected patients showed unexpected complications due to the SARS-CoV-2 infection during the cancer treatment. These data clearly contrast the view that patients with an oncologic disease are particularly vulnerable to SARS-CoV-2 and suggest that compromising therapies could be continued or started despite the ongoing pandemic. Moreover the relatively low appearance of symptoms due to COVID-19 among patients on chemotherapy and other immunosuppressive co-medication like glucocorticoids indicate that suppressing the response capacity of the immune system reduces disease severity.
In this position paper, we lay out an approach to use participatory and co-design methodology to explore how users perceive and interact with explanations of artificially intelligent decision support systems. We describe how we intend to construct bottom-up participatory design spaces to systematically inform the design of interactive explanations in Human-AI interaction.
Artificial Intelligence (AI) is continuously moving into our surroundings. In its various forms, it has the potential to disrupt most aspects of human life. Yet, the discourse around AI has long been by experts and for experts. In this paper, we argue for a participatory approach towards designing human-AI interactions. We outline how we used design methodology to organise an interdisciplinary workshop with a diverse group of students – a workbook sprint with 45 participants from four different programs and 13 countries – to develop speculative design futures in five focus areas. We then provide insights into our findings and share our lessons learned regarding our workshop topic – AI and Space – our process, and our research. We learned that involving non-experts in complex technical discourses – such as AI – through the structural rigour of design methodology is a viable approach. We then conclude by laying out how others might use our findings and initiate their own workbook sprint to explore complex technologies in a human-centred way.
Design of a Low Multi-Loop Inductance Three Level Neutral Point Clamped Converter with GaN HEMTs
(2020)
This work shows a numerical and experimental analysis of a Neutral-Point-Clamp (NPC) three level inverter featuring an ultra low inductance printed circuit board (PCB) design in consideration of the mutual inductive and capacitive couplings. The commutation loops in this design are found to be strongly dependent on the vertical thickness of the used prepregs and the core. For vertical thicknesses ≤ 100 μm capacitive coupling must be taken into account in the switching cell design. Experimental measurements of a test set-up with a total PCB thickness of 400 μm results in commutation loop inductances from 1.4 nH up to 3.1 nH. In this set-up, switching tests without external gate resistor showed only a maximum voltage overshoot of 7% at 800 V. Based on a numerical analysis of the NPC cell we propose a further switching performance improvement with significant smaller parasitic inductance due to the application of novel printed circuit technologies such as the integration of bare dies into the printed circuit board or polyimide as an interlayer dielectric material.
Objective: Functioning is an important outcome for rheumatoid arthritis (RA) management. Heterogeneity of respective patient-reported outcome measures (PROMs) challenges direct comparisons between their results. This study aimed to standardize reporting of such PROMs measuring functioning in RA to facilitate comparability.
Methods: Common Item Non-Equivalent Groups Design (NEAT) with the Health Assessment Questionnaire (HAQ) as a common scale across data sets from various countries (incl. UK, Turkey and Germany) to establish a common metric. Other PROMs included are the Physical Function items of the Multidimensional Health Assessment Questionnaire (MDHAQ), Disabilities of Arm, Shoulder and Hand (DASH), Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), World Health Organization Disability Assessment Schedule Version 2.0 (WHODAS 2.0), and four short forms (20, 10, 6, and 4 physical function items) from the Patient-Reported Outcomes Measurement Information System (PROMIS). As the HAQ includes mobility, self-care and domestic life items, this study focuses on these three domains. PROMs were described using Standard Error of Measurement (SEM) and Smallest Detectable Difference (SDD). Rasch Measurement model was used to create the common metric.
Results: Range of SEM is 0.2 (MDHAQ) to 7.4 (SF36-PF). SDD revealed a range from 9.7 % (WOMAC-RAT) to 33.5 % (WHODAS-PF). PROMs co-calibration revealed fit to the Rasch measurement model. A transformation table was developed to allow exchange between PROMs scores.
Discussion: Scores between the Daily Activity PROMs commonly used in RA can now be compared. Factors such as SEM and SDD help determine choice of PROM in clinical practice and research.
Providing a subset of previously studied information as a retrieval cue can impair memory for the remaining information. Previous work with adults has shown that such part-list cuing impairment (PLCI) can be transient or lasting, depending on study condition. Here, we investigated the persistence of PLCI in children. Three age groups (7- and 8-year-olds, 9- and 10-year-olds, and 12- to 14-year-olds) learned a list of items, either through a single study trial (1-study condition) or through two study-test cycles (2-study-test condition). Subsequently, two recall tests were administered, with part-list cues being provided in the first (critical) test but not in the second (final) test. Of primary interest was whether the detrimental effect of part-list cuing induced in the critical test would persist to the uncued final test. In 12- to 14-year-olds, we found an adult-like pattern of results, with lasting impairment in the 1-study condition but transient impairment in the 2-study-test condition. In contrast, in the two younger age groups, we found PLCI to be lasting in both study conditions, suggesting age differences in the persistence of PLCI. The results are discussed in light of a recently proposed two-mechanism account of PLCI that attributes lasting impairment to retrieval inhibition and transient impairment to strategy disruption. Following this account, the results suggest that whereas 12- to 14-year-olds’ PLCI was caused by (lasting) retrieval inhibition in the 1-study condition and by (transient) strategy disruption in the 2-study-test condition, 7- and 8-year-olds’ and 9- and 10-year-olds’ PLCI was caused by (lasting) retrieval inhibition in both study conditions.