Publikationsserver der Ostbayerischen Technischen Hochschule Regensburg
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The impact of eyenalyzer
Empirical research poses numerous challenges for beginners. This is especially true for data analysis – a task that usually requires knowledge from two distinct areas: statistics and programming. To support prospective researchers with that task, we developed a web-based tool called eyenalyzer. It supports common activities in the data analysis phase of empirical studies in a way that is suitable for novices in both, statistics and programming. The present article describes a controlled experiment investigating
the impact of this tool with a total of 20 participants. All of them are given a set of common data analysis tasks. Half of the participants complete the tasks using eyenalyzer, the other half can use anything except for eyenalyzer. For each task and participant, we record the time in minutes, the task score, and the perceived difficulty. The results confirm that our tool is a valuable support for novice researchers: With eyenalyzer, the participants are significantly faster, achieve higher scores, and perceive the tasks
to be less difficult
On the Piezomagnetism of Magnetoactive Elastomeric Cylinders in Uniform Magnetic Fields: Height Modulation in the Vicinity of an Operating Point by Time-Harmonic Fields
Soft magnetoactive elastomers (MAEs) are currently considered to be promising materials for actuators in soft robotics. Magnetically controlled actuators often operate in the vicinity of a bias point. Their dynamic properties can be characterized by the piezomagnetic strain coefficient, which is a ratio of the time-harmonic strain amplitude to the corresponding magnetic field strength. Herein, the dynamic strain response of a family of MAE cylinders to the time-harmonic (frequency of 0.1-2.5 Hz) magnetic fields of varying amplitude (12.5 kA/m-62.5 kA/m), superimposed on different bias magnetic fields (25-127 kA/m), is systematically investigated for the first time. Strain measurements are based on optical imaging with sub-pixel resolution. It is found that the dynamic strain response of MAEs is considerably different from that in conventional magnetostrictive polymer composites (MPCs), and it cannot be described by the effective piezomagnetic constant from the quasi-static measurements. The obtained maximum values of the piezomagnetic strain coefficient (∼102 nm/A) are one to two orders of magnitude higher than in conventional MPCs, but there is a significant phase lag (35-60°) in the magnetostrictive response with respect to an alternating magnetic field. The experimental dependencies of the characteristics of the alternating strain on the amplitude of the alternating field, bias field, oscillation frequency, and aspect ratio of cylinders are given for several representative examples. It is hypothesized that the main cause of observed peculiarities is the non-linear viscoelasticity of these composite materials
KI in der Projektmanagement-Lehre
Der Artikel beschäftigt sich mit dem Einbezug von Künstlicher Intelligenz (KI) in die Projektmanagement-Lehre an Hochschulen. Um zeitgemäße Projektmanagement-Lehre anbieten zu können, ist es förderlich, KI in die Lehre einzubeziehen, und so Studierende bei der Entwicklung von Future Skills zu unterstützen. Die Integration von KI in die Lehre wird anhand von vier Handlungsfeldern aufgezeigt. Im Sinne eines Call-to-Action wird ermutigt, KI-bezogene Lernziele explizit zu definieren und diese mit den Prüfungsleistungen und den Lehr-/Lernaktivitäten entsprechend des vorgestellten didaktischen Ansatzes des Constructive Alignment aufeinander abzustimmen. Es werden drei Good-Practice-Beispiele vorgestellt, die als Anregung dienen sollen. Der Beitrag plädiert für Experimente im Zusammenhang mit dem Einsatz von KI in der Lehre. Durch experimentelles Lernen können Studierende Kompetenzen im Umgang mit KI aufbauen und sich so auf eine künftige Arbeitswelt vorbereiten, die von Projektarbeit und KI-Unterstützung geprägt sein wird
Aufzugschächte in Holzbauweise – Konstruktionsprinzipien und Prognosemöglichkeiten für den Schallschutz
Creating Moving Regions from Satellite Scan Data
Moving objects databases are specialized on storing and processing objects with spatial attributes that change over time. An important class of objects are moving regions that can change shape and position over time. Currently, the prevailing method for constructing moving regions is to interpolate them from snapshots. In this paper, an alternative method is proposed, that is better suitable for certain kinds of data as, for example, satellite scans of the earth surface. For instance, the NASA provides datasets with active fire data in near real-time from the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor, attached to satellites as the Suomi NPP and NOAA-20. These satellites orbit earth about 14 times a day and provide full global coverage twice a day. Using these satellites, datasets are compiled that provide locations of active fires on earth as lists of positions and timestamps. This paper describes an alternative, better suitable method for creating moving regions from these lists, which can then be imported into and processed by moving objects databases
Measured and predicted sound transmission through a laboratory concrete floor
The direct sound transmission through a simple, massive, homogeneous building element with and without lining is investigated experimentally and compared with analytical and empirical models from the literature. A 150 mm thick concrete floor and a 100 mm thick floating floor were measured in the floor transmission facility of the National Research Council Canada, i.e. without flanking sound transmission. In addition to the sound reduction index and the normalized impact sound pressure level, loss factors, radiation efficiencies, and mean squared velocities were recorded in the laboratory. The measured data is compared to established models of sound transmission. A focus is placed on the calculation model of ISO 12354-1 (Appendix B), which uses calculated radiation efficiencies and loss factors to predict the sound reduction index of heavy, homogeneous building elements. Some difficulties with the calculation model and the examples in the standard are discussed. In principle, the results in this study show that the calculation model of ISO 12354-1 gives good estimates when the correct input parameters are used. However, deviations between the calculated and the measured loss factors and radiation efficiencies have large effects on the accuracy of the estimates, particularly in the region around the coincidence frequency
KI-gestützte Untersuchung in der nicht-operativen Versorgung symptomgebender Erkrankungen des Kniegelenks – ein multiprofessionelles Konzept (KINEESIO)
Beschwerdebilder am Kniegelenk aufgrund muskuloskelettaler degenerativer oder verletzungsbedingter Erkrankungen sind häufig, nehmen im Alter zu und sind mit der steigenden Inanspruchnahme ärztlicher und therapeutischer Behandlungsmaßnahmen verbunden. Einer erfolgreichen Therapie gehen oft notwendige zeit- und ressourcenaufwendige Untersuchungen zur Erkennung und Differenzierung der patient*innenspezifischen Problematik voraus. Im Zusammenhang mit der nicht-operativen Versorgung des Kniegelenks hat ein sektorübergreifendes multiprofessionelles Forschungsteam ein Konzept entwickelt, um künstliche neuronale Netze so zu trainieren, dass sie bei der ärztlichen und physiotherapeutischen Untersuchung unterstützend Einsatz finden können. Denn gerade in der Erfassung und Auswertung umfassender Datenmengen liegen große Potenziale in der Künstlichen Intelligenz (KI) im Gesundheitswesen. Das Projekt KINEESIO trainiert und testet KI-gestützte Screening- Tools zur Untersuchung von Patient*innen mit Kniegelenkerkrankungen. Diese unterstützen die Abläufe zwischen Leistungserbringern und Patient*innen, tragen zu einer verbesserten Differenzierung individueller Beschwerdebilder bei und dienen Entscheidungsprozessen für eine adäquate Versorgung. Dadurch sollen Ressourcen im Gesundheitswesen geschont und eine qualitativ hochwertige Therapie ausreichend ermöglicht werden.Complaints regarding knee joints resulting from musculoskeletal degenerative or injury-related conditions are common, increase with age, and are associated with rising demand for treatments by physicians and therapists. The success of a therapeutic intervention is frequently contingent upon necessary time- and resource-intensive examinations to identify and differentiate the patient’s specific issues. In connection with non-surgical knee joint treatment, a crosssectoral, multidisciplinary research team has developed a concept for training artificial neural networks to assist in medical and physiotherapeutic examinations. After all, there is great potential for artificial intelligence (AI) in healthcare, particularly in collecting and analyzing large amounts of data. The KINEESIO project is training and testing screening tools supported by artificial intelligence for the assessment of patients with knee joint disorders. These tools support the workflows between healthcare providers and patients, improve the differentiation of individual symptoms and serve the decisionmaking process towards appropriate care. This should conserve healthcare resources and enable sufficient high-quality treatment
Systematic development of a patient-reported ONCOlogical-ROUTinE-Screening (ONCO-ROUTES) procedure at the University Cancer Center Regensburg
Purpose
The evaluation of treatment success and progression in oncology patient-reported outcomes (PROs) is playing an increasingly important role. Meanwhile, PROs are a component of the certification requirements of the German Cancer Society for oncology centers. PROs are used to provide supportive therapy. There is currently no instrument that fully covers the requirements. At the University Hospital Regensburg (UKR), a digital ONCOlogical-ROUTinE-Screening (ONCO-ROUTES) procedure was developed in order to assess the need for supportive therapy in a standardized way and to provide patients with supportive interventions tailored to their needs.
Methods
On the basis of current requirements and guidelines, the development of ONCO-ROUTES was supported by experts in focus groups and interviews, and digitalization was carried out in connection with the IT infrastructure.
Results
A Needs-based, Quality-of-life (QoL) and Symptoms Screening (NQS2) tool already established in the routine at the UKR was further developed into ONCO-ROUTES, which is made up of the domains therapy phase, nutrition, tobacco use, alcohol use, quality of life, general condition/functional status, physical activity, psychooncology, social services, and further support needs. By linking the digitized questionnaire to the hospital information system, the results are available for immediate use in routine operations and thus for the referral of patients for further supportive therapy.
Conclusion
The digital PRO application ONCO-ROUTES is designed to involve patients in monitoring additional supportive needs and thus, improves supportive interdisciplinary treatment
Konzeptionierung und Implementierung einer standardisierten RPA-Schnittstelle für eine Analytics-On-Demand-Self-Service-Lösung zur Bereitstellung von einkaufsbezogenen Daten in der Krones AG
Hohe Bearbeitungs- und Antwortzeiten von Tickets, die diverse Aufgaben aus dem Bereich Analytics inkludieren, führten Corporate Procurement (CP) Processes and Systems zur Konzeptionierung und Implementierung einer standardisierten RPA-Schnittstelle, um einen Analytics-On-Demand-Self-Service zur Bereitstellung von einkaufsbezogenen Daten zu realisieren. Dafür wurde zunächst ein Anforderungskatalog erarbeitet, der als Basis für die Konzeptionierung und Implementierung aller zur Prüfung der Funktionsfähigkeit der RPA-Schnittstelle erforderlichen Komponenten diente. Als Proof-of-Concept fungieren die Analytics-Use-Cases der Orderbuchabfrage und Abfrage von Einkaufsinfosätzen mit Konditionen. Die durchgeführte Evaluation bescheinigt aus technischer und prozessualer Sicht den Erfolg des Projekts, wobei im Vordergrund die zukünftig nach Einführung des Analytics-On-Demand-Self Service gewonnen zeitlichen Kapazitäten und verringerten Wartezeiten bei den Mitarbeitenden des Einkaufs der Krones AG stehen