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Optimierung visueller Benutzeroberflächen zur Stressreduzierung
No full textDurch die Menschzentrierung in der Industrie 5.0 sollten bestehende Ansätze hinterfragt und geprüft werden. Gerade der, durch die Digitalisierung hervorgerufene, Technostress sollte neben dem Fachkräftemangel einen zunehmenden Betrachtungsfaktor im Produktionsumfeld erhalten. Da trotz bisheriger Maßnahmen eine stetige Zunahme von Stress zu verzeichnen ist. Auffällig sind dabei die Arbeitsunfähigkeits-Fehltage, welche im letzten Jahr um weitere 6 % bzw. um 18,2 Fehltage gestiegen sind. Womit durchschnittlich jede Erwerbsperson 3,17 Tage unter der Diagnose „psychische Störung“ krankgeschrieben wurde. Um diesen Trend entgegenzuwirken, betrachtet der Beitrag die Möglichkeiten der Software-Ergonomie, womit die Gestaltung von HMIs (Mensch-Maschinen-Interfaces) den Menschen gezielter berücksichtigt um etwaige Belastungen zu reduzieren. Im Rahmen der komplementären Industrie 4.0 und der einhergehenden Informationsflut, bestimmen immer komplexer werdende Schnittstellen und Bedienoberflächen einen Großteil des Arbeitsalltags. Diese ermöglichen den Anwenderinnen und Anwendern neben einem schnellen Überblick über Maschinendaten, Prozessabläufe und Handlungsempfehlungen die Möglichkeit zur einfachen Bedienung der technischen Anlagen. Der hier vorgestellte Ansatz betrachtet am Beispiel einer Bestandsanlage, wo sich Potenziale in der Stressreduzierung im Bereich der visuellen Benutzerschnittstellen befinden und welche Auswirkungen eine Veränderung der Leitführung ermöglicht. Hierfür wurde eine mehrphasige Studie durchgeführt dessen Ergebnisse im Bereich des Eye-Trackings sowie anhand von Vitalwerten im vorliegenden Beitrag diskutiert werden
Photoacoustic tomography using a Fabry-Perot sensor with homogeneous optical thickness and wide-field camera-based detection
No full textFabry-Perot (FP) sensors are typically read out using a raster scan to acquire tomographic Photoacoustic (PA) images. To speed up the recording time, wide-field illumination of the sensor in combination with a camera as detector can be used. In this study, an sCMOS camera and wavelengths around 517 nm are used to interrogate a FP sensor with a homogeneous optical thickness over a 4 cm2 aperture. The recorded time series show PA signals are acquired over the entire area of the interrogation beam. The performance of the system, such as the noise equivalent pressure, is evaluated
Fluorescence optical imaging feature selection with machine learning for differential diagnosis of selected rheumatic diseases
No full textBackground and objective: Accurate and fast diagnosis of rheumatic diseases affecting the hands is essential for further treatment decisions. Fluorescence optical imaging (FOI) visualizes inflammation-induced impaired microcirculation by increasing signal intensity, resulting in different image features. This analysis aimed to find specific image features in FOI that might be important for accurately diagnosing different rheumatic diseases.
Patients and methods: FOI images of the hands of patients with different types of rheumatic diseases, such as rheumatoid arthritis (RA), osteoarthritis (OA), and connective tissue diseases (CTD), were assessed in a reading of 20 different image features in three phases of the contrast agent dynamics, yielding 60 different features for each patient. The readings were analyzed for mutual differential diagnosis of the three diseases (One-vs-One) and each disease in all data (One-vs-Rest). In the first step, statistical tools and machine-learning-based methods were applied to reveal the importance rankings of the features, that is, to find features that contribute most to the model-based classification. In the second step machine learning with a stepwise increasing number of features was applied, sequentially adding at each step the most crucial remaining feature to extract a minimized subset that yields the highest diagnostic accuracy.
Results: In total, n = 605 FOI of both hands were analyzed (n = 235 with RA, n = 229 with OA, and n = 141 with CTD). All classification problems showed maximum accuracy with a reduced set of image features. For RA-vs.-OA, five features were needed for high accuracy. For RA-vs.-CTD ten, OA-vs.-CTD sixteen, RA-vs.-Rest five, OA-vs.-Rest eleven, and CTD-vs-Rest fifteen, features were needed, respectively. For all problems, the final importance ranking of the features with respect to the contrast agent dynamics was determined.
Conclusions: With the presented investigations, the set of features in FOI examinations relevant to the differential diagnosis of the selected rheumatic diseases could be remarkably reduced, providing helpful information for the physician
Angewandte Forschung in der Wirtschaftsinformatik 2023 : Tagungsband zur 36. AKWI-Jahrestagung vom 11.09.2023 bis 13.09.2023 ausgerichtet von der Technischen Hochschule Wildau
No full textTagungsband zur 36. Jahrestagung des "Arbeitskreises Wirtschaftsinformatik an Hochschulen für Angewandte Wissenschaften im deutschsprachigen Raum" (AKWI) der Gesellschaft für Informatik e. V
Framing curriculum making: bureaucracy and couplings in school administration
No full textThis article aims to undertake a comparative investigation of school administration to understand further the frames of curriculum making. School administration is an under-illuminated aspect of curriculum research. The paper commences from the notion that, in mass education, a school system is operationalized by many schools, which are coupled to each other and to political decisions. Here is the curriculum vital. Building on the classic work of Stefan Hopmann, a curriculum is part of the administrational structure of the school system. The Article suggests several categories that can describe the nature and function of school administration in various contexts. There are external matters of schooling, such as school buildings, school food, etc. and internal matters of schooling, such as curriculum, pedagogy, and evaluation. Individual schools and school administration are coupled via licences, and programmatic, professional, and procedural supervision. The article employs these categories with a comparison of a decentralized Sweden and a centralized Germany. The comparison investigated 290 Swedish municipality school administrations and 45 state education authorities in 4 German federal states. In this comparison many interesting similarities between both contexts can be hightligthed
Lateral Selective SiGe Growth for Local Dislocation-Free SiGe-on-Insulator Virtual Substrate Fabrication
No full textDislocation free local SiGe-on-insulator (SGOI) virtual substrate is fabricated using lateral selective SiGe growth by reduced pressure chemical vapor deposition. The lateral selective SiGe growth is performed around a ∼1.25 μm square Si (001) pillar in a cavity formed by HCl vapor phase etching of Si at 850 °C from side of SiO2/Si mesa structure on buried oxide. Smooth root mean square roughness of SiGe surface of 0.14 nm, which is determined by interface roughness between the sacrificially etched Si and the SiO2 cap, is obtained. Uniform Ge content of ∼40% in the laterally grown SiGe is observed. In the Si pillar, tensile strain of ∼0.65% is found which could be due to thermal expansion difference between SiO2 and Si. In the SiGe, tensile strain of ∼1.4% along 〈010〉 direction, which is higher compared to that along 〈110〉 direction, is observed. The tensile strain is induced from both [110] and [−110] directions. Threading dislocations in the SiGe are located only ∼400 nm from Si pillar and stacking faults are running towards 〈110〉 directions, resulting in the formation of a wide dislocation-free area in SiGe along 〈010〉 due to horizontal aspect ratio trapping
Evaluation of ultrasound sensors for transcranial photoacoustic sensing and imaging
No full textPhotoacoustic imaging through skull bone causes strong attenuation and distortion of the acoustic wavefront, which diminishes image contrast and resolution. As a result, transcranial photoacoustic measurements in humans have been challenging to demonstrate. In this study, we investigated the acoustic transmission through the human skull to design an ultrasound sensor suitable for transcranial PA imaging and sensing. We measured the frequency dependent losses of human cranial bones ex vivo, compared the performance of a range of piezoelectric and optical ultrasound sensors, and imaged skull phantoms using a PA tomograph based on a planar Fabry–Perot sensor. All transcranial photoacoustic measurements show the typical effects of frequency and thickness dependent attenuation and aberration associated with acoustic propagation through bone. The performance of plano-concave optical resonator ultrasound sensors was found to be highly suitable for transcranial photoacoustic measurements
Vergleichende Analyse von Unternehmenswerten in Online Stellenanzeigen mittels NLP / LIWC
No full textDie Analyse von Unternehmenswerten wird schon seit Jahrzenten durchgeführt. Es gibt verschiedene Modelle, wie zum Beispiel den Ansatz von Hofstede oder das „Universal Value Structure Modell“ von Schwartz, welche die Unternehmenswerte darstellen. Aktuelle Studien empfehlen Unternehmenswerte unter der Nutzung von Natural Language Processing und definierten Wortlisten bei größeren Textdaten zu untersuchen. Ziel der vorliegenden Analyse war zu identifizieren, ob die deutschen Übersetzungen der bisher englischsprachigen Ansätze im Kontext von Online-Stellenanzeigen funktional anwendbar sind. Daher wurden ca. 151.000 online-Stellenanzeigen von ca. 29.000 Unternehmen mittels drei Wortlisten analysiert. Der Umfang der verwendeten Listen lag zwischen 126 und 944 deutschen Wörtern. Die Ergebnisse zeigen, dass a) alle angewendeten Wortlisten grundsätzlich funktional sind, b) dass einer der Listen jedoch herausragende Ergebnisse aufweist, welcher jedoch c) um fehlende Begriffe der beiden anderen Ansätze erweitert werden kann. Somit können Unternehmen ein eigenes Werteprofil Ihrer externen Online-Kommunikation ermitteln und dieses mit den internen Wertvorstellungen bzw. dem intern erhobenen realen Werteprofil abgleichen
Identification of Personality Based on the Sphenoid Sinus Structure Using Machine Learning
No full textThe aim of our study is to develop a new, simple, and effective method for identification of personality based on the characteristics of the sphenoid sinus structure, using machine learning for subsequent implementation into routine medical practice in Ukraine. The study involved 200 multislice computed tomography (MSCT) scans of individuals of various genders and ages. During the study, we obtained results with an accuracy exceeding 70%
Additive Manufacturing of Electrodes: Innovative Applications and Opportunities
No full textAdditive manufacturing, also known as 3D printing, has gained tremendous importance in recent years. One of the areas where additive manufacturing is particularly useful is in the fabrication of electrodes. Electrodes are an important component of a wide range of applications, including electrochemistry, biomedical engineering, energy storage, analytics, electronics as well as life sciences. Traditionally, electrodes have been manufactured through costly processes such as etching, electroplating or cutting and milling. Additive manufacturing offers a new way to fabricate electrodes by depositing materials layer by layer (Yap et al., 2015). This opens up new possibilities for designing electrodes with complex geometries and structures that would not be possible using conventional methods. As a result, 3D printed electrodes are gaining interest in fields such as electromobility, water disinfection, manufacturing, and life sciences, which will be presented in this paper