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Tensegrity structures are structures in which elements stabilize each other by bearing compressive or tensile loads. They have a high potential for lightweight design. As structures with tensile loads, wires can be used that are connected to other structures using a laser bonding process. Investigations of bonding a mild steel wire with a diameter of 1 mm onto a flat substrate have been conducted using a coaxial deposition welding head. The influence of the parameters focus position, laser power, wire feed rate and bonding processing time has been investigated regarding the bonding quality. A process window for a stable process and a sufficient bond of wire and substrate was determined. The laser intensity and stickout length have a significant influence on the bonding. High intensities and stickout lengths lead to wire burn back and no bond with the substrate while wire backup occurred at low intensities and stickout lengths.
Der Projektbericht dokumentiert die Durchführung und die Ergebnisse des Studierendenprojekts „Guided Walk Reloaded: Recherchekompetenz spielerisch vermitteln“, das im Sommersemester 2024 im Studiengang „Informationsmanagement - berufsbegleitend“ an der Hochschule Hannover in Zusammenarbeit mit der ZBW – Leibniz-Informationszentrum Wirtschaft realisiert wurde.
The development of methods for the meta‐analysis of diagnostic test accuracy (DTA) studies is still an active area of research. While methods for the standard case where each study reports a single pair of sensitivity and specificity are nearly routinely applied nowadays, methods to meta‐analyze receiver operating characteristic (ROC) curves are not widely used. This situation is more complex, as each primary DTA study may report on several pairs of sensitivity and specificity, each corresponding to a different threshold. In a case study published earlier, we applied a number of methods for meta‐analyzing DTA studies with multiple thresholds to a real‐world data example (Zapf et al., Biometrical Journal. 2021; 63(4): 699–711). To date, no simulation study exists that systematically compares different approaches with respect to their performance in various scenarios when the truth is known. In this article, we aim to fill this gap and present the results of a simulation study that compares three frequentist approaches for the meta‐analysis of ROC curves. We performed a systematic simulation study, motivated by an example from medical research. In the simulations, all three approaches worked partially well. The approach by Hoyer and colleagues was slightly superior in most scenarios and is recommended in practice.
Autonomes Fahren rückt immer mehr in den Fokus der Gesellschaft. Im Gesetz zum autonomen Fahren sieht die deutsche Bundesregierung einen Meilenstein, der die Realisierung des autonomen Fahrens ermöglicht. Dennoch sind keine serienreifen, autonomen Fahrfunktionen auf deutschen Straßen zugelassen. Wie weit sind wir noch vom Traum vom autonomen Fahren entfernt? In diesem Beitrag wird untersucht, welche offenen Fragen es aus juristischer und technischer Sicht gibt und in welchen Punkten beide Disziplinen aufeinander warten. Der aktuelle Stand wird in den Bereichen Typgenehmigung/Zulassung, Fahrerlaubnis (Führerschein) und Haftung systematisch untersucht. Mit Hilfe eines Gedankenexperiments, bei dem der menschliche Fahrer durch einen Roboterfahrer ersetzt wird, wird eine einheitliche Basis geschaffen, um automatisierte Fahrfunktionen und Fahrerassistenzsysteme zu vergleichen. Dieser Beitrag deckt offene Fragen auf, die für die Realisierung des vollständig autonomen Fahrens noch beantwortet werden müssen. Eine praktische Umsetzung erfordert eine enge interdisziplinäre Zusammenarbeit, insbesondere von Expert*innen aus den Bereichen Regulierung, Technik und Sozialwissenschaften.
Introduction: The integration of Patient-Reported Experience Measures (PREM) alongside traditional clinical outcomes is crucial for improving quality of care. Although PREMs are frequently measured in inpatient treatment settings, they are rarely employed in digitally supported care processes or longitudinal assessment of care pathways.
Methods: To gain an overview of PREMs used to cover patients’ experiences with digitally supported care processes in heart failure (HF), a scoping review was conducted in Medline.
Results: Out of 538 publications, 29 were identified that focus on PREMs in digitally supported care processes across 9 unspecific and 14 disease-specific groups, with 5 manuscripts focusing on HF. PREMs were mostly assessed using self-developed, study-specific questionnaires lacking standardization and validity. In total, 9 PREM dimensions and 25 sub-dimensions were identified. This included care delivery, privacy, physician-patient relationship, involvement, administration, information, knowledge, technology, and experiences in general.
Conclusion: The findings suggest that the relevance of different dimensions assessed depends largely on the type of care rather than the underlying chronic disease.
Postpartum excretion of internal teat sealant after selective dry cow treatment of dairy cows
(2024)
To comply with antibiotic restriction policies in the European Union, internal teat sealants (TS) are increasingly used at dry off (DO) in selective dry cow treatment protocols to maintain udder health. Postcalving TS residue attachment to milking equipment and associated cleaning difficulties is a reason some farmers stay away from blanket TS use. Our objective was therefore to improve insight into TS excretion visibility and to compare quantity, pattern, and presence versus absence of TS excretion postcalving between the typical 2 cow categories at DO: high (H)- and low (L)-SCC cows, treated with antibiotic (AB) plus TS (H-ABTS) or TS only (L-TS), respectively. In herds in the Netherlands (n = 3), and Germany (n = 4), cows were enrolled at DO, and categorized as H-ABTS (n = 93), or L-TS (n = 99). Postcalving, quarter-level TS visibility, quantities, patterns, and percentage of TS infused and excreted postcalving were recorded from 50 mL of premilk of every quarter at each of the first 15 or 16 milkings. Udder quarter health status was determined by bacteriological culture and SCC of quarter milk samples taken at DO and at d 3 postcalving and by clinical mastitis incidence from DO until 30 DIM. Univariable and multivariable models were created to explore associations of TS excretion presence versus absence at the first 3 milkings. Irrespective of SCC category, both laboratory personnel and farmers saw TS residues at the first milking in an equal 72% of quarters. Compared with laboratory as the gold standard, farmer sensitivity to spotting TS in premilk was 74.5% at the first milking and decreased to a maximum of 8.3% at the last 3 milkings. At the first milking, TS excretion quantities showed a bimodal distribution pattern and the mean percentage of TS infused (3.83 g) that was excreted in premilk at the first milking, was higher in the L-TS cows (45.5%) compared with the H-ABTS cows (32%). At the second and third milking, mean-adjusted TS percentage excreted was higher in the H-ABTS cows (8.5% and 1.8%, respectively) compared with the L-TS cows (4.6% and 0.4%, respectively). The multivariable model of the first 3 milkings showed parity at both the first and second milking, and the study group at both the second and third milking was significantly associated with TS presence. The univariable model showed no association between TS presence at the first milking and udder health. In conclusion, in premilk of the first milking, TS residue excretion was bimodal, higher in L-TS cows, more likely to be present in multiparous cows, and not associated with udder health. At the second and third milking, excretion was higher in H-ABTS cows and TS presence was only more likely in multiparous cows at the second milking.
We study the statistical properties of the Bitcoin return series and provide a thorough forecasting exercise. Also, we calibrate state-of-the-art machine learning techniques and compare the results with econometric time series models. The empirical assessment provides evidence that the application of machine learning techniques outperforms econometric benchmarks in terms of forecasting precision for both in- and out-of-sample forecasts. We find that both deep learning architectures as well as complex layers, such as LSTM, do not increase the precision of daily forecasts. Specifically, a simple recurrent neural network describes a sensible choice for forecasting daily return series.
Wie lässt sich die Logistik in Städten zukunftssicher und klimaschonend gestalten? Dazu bedarf es innovativer Konzepte für leise, emissionsfreie sowie sichere und zuverlässige Transportlösungen. Im Forschungsprojekt USEfUL haben sich Akteure aus Kommunen, Wissenschaft und Wirtschaft der Regionen Hannover und Braunschweig zusammengeschlossen. Das Projektteam entwickelt eine App, die verschiedene Logistikkonzepte und ihre Auswirkungen vergleicht. Sie kann Politik, Kommunen und Unternehmen bei der Entscheidung unterstützen.
Kunststoffe sind wertvolle Werkstoffe für unterschiedlichste Anwendungen. Doch die durch sie verursachten Umweltverschmutzungen sind weltweit ein großes Problem. Ein Trend für mehr Nachhaltigkeit ist Mehrweg- statt Einwegnutzung. Eine Kooperation aus Hannover arbeitet am Einsatz von Biokunststoffen in Pfandsystemen für To-go-Lebensmittel.
Schmalspurfahrzeuge als kompaktes Mittel zur Beförderung von Personen oder Gütern auf der Straße neigen insbesondere bei schneller Kurvenfahrt zum Umkippen. Sowohl Tüftler und Kleinserienhersteller als auch einige Großkonzerne der Automobilindustrie haben in den letzten Jahrzehnten immer wieder versucht, ein Fahrzeug mit geringer Verkehrsfläche zu konstruieren, welches dennoch die erforderliche Kurvenstabilität aufweist. Durch den Einsatz der Neigetechnik bei Straßenfahrzeugen entstand die Fahrzeugklasse der Kurvenleger.
Im Rahmen dieses Berichtes werden die Grundlagen der Neigetechnik in Kurvenlegern erläutert und die verschiedenen Ansätze und Technologien zur Umsetzung bei unterschiedlichen Beispielfahrzeugen beleuchtet.