Publikationsserver der Ostbayerischen Technischen Hochschule Regensburg
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Preliminary considerations on the form-finding of a tensegrity joint to be used in dynamic orthoses
No full textNeutrophil extracellular traps -a potential trigger for the development of thrombocytopenia during extracorporeal membrane oxygenation
No full textNeutrophil extracellular traps (NETs) have recently emerged as a potential link between inflammation, immunity, and thrombosis, as well as other coagulation disorders which present a major challenge in the context of extracorporeal membrane oxygenation (ECMO). By examining blood from ECMO patients for NETs and their precursors and correlating them with clinical and laboratory biomarkers of coagulation and inflammation, this study aims to evaluate the association between the presence of NETs in the bloodstream of ECMO patients and the development of potentially severe coagulation disorders during ECMO therapy.
Therefore, blood samples were collected from healthy volunteers (n=13) and patients receiving veno-venous (VV) ECMO therapy (n=10). To identify NETs and their precursors, DNA and myeloperoxidase as well as granulocyte marker CD66b were visualized simultaneously by immunofluorescence staining in serial blood smears. Differentiation of DNA-containing objects and identification of NETs and their precursors was performed semiautomatically by a specific algorithm using the shape and size of DNA staining and the intensity of MPO and CD66b signal.
Neutrophil extracellular traps and their precursors could be detected in blood smears from patients requiring VV ECMO. Compared to volunteers, ECMO patients presented significantly higher rates of NETs and NET precursors as well as an increased proportion of neutrophil granulocytes in all detected nucleated cells. A high NET rate prior to the initiation of ECMO therapy was associated with both increased iL-6 and TNF-α levels as an expression of a high cytokine burden. These patients with increased NET release also presented an earlier and significantly more pronounced decrease in platelet counts and ATIII activity following initiation of therapy compared with patients with less elevated NETs. These findings provide further indications for the development of immune-mediated acquired thrombocytopenia in ECMO patients
Usability and User Experience of a Chatbot for Student Support
No full textThis paper describes the usability evaluation of the parts of the CHATU chatbot. The evaluation was conducted with 21 participants. A focus of this paper is the description of the carefully designed evaluation procedure, which aims to avoid textual priming of the participants. The general evaluation procedure can be applied to other speech- or text-based conversational systems, and additional material is provided. The evaluation results show that the usability and user experience of CHATU are positively rated. However, the naturalness and novelty of the interaction are not optimal, and the potential influence of users’ experience with LLMs on the evaluation is discussed
An Investigation of Acoustic Features of the Lower Vocal Tract for Speaker Recognition
No full textSpeaker recognition systems often use mel-scaled cepstral coefficients (MFCCs) as main features. In contrast to MFCCs, Godoy et al. (2015) proposed a different type of short-term spectral analysis that provides features related to the lower vocal tract (LVT). They are calculated as the ratio of the acoustic shorttime spectra during the closed and open phases of the glottal oscillation cycles based on a pitch-synchronous analysis. These features were suggested to be particularly speaker-specific and might therefore be suitable to substitute or complement MFCCs in speaker recognition systems. The present study investigated the benefit of these features in an i-vector-based speaker recognition system. Using the LVT features alone, the system achieved a speaker recognition rate of 92.3% with 63 enrolled speakers. When the LVT features were fused with conventional MFCC features, the recognition rate was about equal to the recognition rate using MFCC features alone (> 98%)
Empirical Evaluation of ASR and NLU in a Multimodal Dialogue System for Survey Answering
No full textPROM surveys, used to measure the effect of rehabilitation treatments, are typically filled out on paper, and often suffer from low response rates. Replacing it with a multimodal survey system, supporting touch and speech interaction, could lead to lower hurdles and therefore more data quantity. To do this, it requires task-specific training samples for the Automatic Speech Recognition (ASR) and Natural Language Understanding (NLU) to classify spoken answers into one of the standardized PROM answer options.
Due to the lack of training data for medical PROM surveys, we created augmented text samples with each answer option description, combined with different templates. To improve training capabilities, introduce a proper test set, and evaluate the ASR, we also collected 1,797 real voice samples within an empirical study. Further, we incorporate the contextual knowledge of the current question into our NLU architecture by implementing one classifier for every question scale.
Our results reveal that training with empirical data leads to better results than augmented data from templates and original answer option descriptions. Because of participant mislabeling of 33% due to the ambiguity of the task, we receive overall low NLU performances with up to 51.1% accuracy, and rank-1-accuracy up to 79.3%. We also find that our implementation of many scale-specific NLU classifiers significantly outperforms one NLU classifier for all labels, that incorporates the same contextual knowledge after the prediction, by 8 percent points
The influence of signal segmentation methods on rhythm-bassed speaker recognition
No full textThis study investigates the effects of speech segmentation methods on speaker recognition models, particularly with regard to the use of rhythmic feature sets. Using three automatic methods and one manual method on the German database of Kiel corpus, segmentation was performed based on the identification of vowel onsets. Subsequently rhythmic variability indices derived from these intervals were calculated and used for principal component analysis and support vector machine model in order to investigate the variation among speakers. The results underline the influence of signal segmentation methods on speaker recognition models
Integrated silicon electron source for high vacuum microelectromechanical system devices
No full textThe article presents the process of developing a silicon electron source designed for high-vacuum microelectromechanical system (HV MEMS) devices, i.e., MEMS electron microscope and MEMS x-ray source. Technological constraints and issues of such an electron source are explained. The transition from emitters made of carbon nanotubes to emitters made of pure silicon is described. Overall, the final electron source consists of a silicon tip emitter and a silicon gate electrode integrated on the same glass substrate. The source generates an electron beam without any carbon nanotube coverage. It generates a high and stable electron current and works after the final bonding process of an HV MEMS device
Smoke Classification in Laparoscopic Cholecystectomy Videos Incorporating Spatio-temporal Information
No full textHeavy smoke development represents an important challenge for operating physicians during laparoscopic procedures and can potentially affect the success of an intervention due to reduced visibility and orientation. Reliable and accurate recognition of smoke is therefore a prerequisite for the use of downstream systems such as automated smoke evacuation systems. Current approaches distinguish between non-smoked and smoked frames but often ignore the temporal context inherent in endoscopic video data. In this work, we therefore present a method that utilizes the pixel-wise displacement from randomly sampled images to the preceding frames determined using the optical flow algorithm by providing the transformed magnitude of the displacement as an additional input to the network. Further, we incorporate the temporal context at evaluation time by applying an exponential moving average on the estimated class probabilities of the model output to obtain more stable and robust results over time. We evaluate our method on two convolutional-based and one state-of-the-art transformer architecture and show improvements in the classification results over a baseline approach, regardless of the network used
Sprachassistenten: Anwendungen, Implikationen, Entwicklungen
No full textDer zweite ITG-Workshop „Sprachassistenten – Anwendungen, Implikationen, Entwicklungen“ fand am 5. März 2024 in Regensburg statt. Er bot eine organisatorische und inhaltliche Fortführung des ersten Workshops vor vier Jahren in Magdeburg 2020. Auch in diesem Jahr war er wieder der Konferenz Elektronische Sprachsignalverarbeitung angegliedert. Auf dem Workshop wurden vielfältige und interdisziplinäre Beiträge in eingeladenen Vorträgen und als eingereichte Poster präsentiert. Durch die gute Mischung von Beitragenden sowohl aus der Hochschullandschaft als auch aus der Industrie wurden die verschiedensten Aspekte anwendungsnah diskutiert
Friction modeling from a practical point of view
No full textAbstractRegularized static friction models have been used successfully for many years. However, they are unable to maintain static friction in detail. For this reason, dynamic friction models have been developed and published in the literature. However, commercial multibody simulation packages such as Adams, RecurDyn, and Simpack have developed their own specific stick-slip models instead of adopting one of the public domain approaches. This article introduces the fundamentals of these commercial models and their behavior from a practical point of view. The stick-slip models were applied to a simple test model and a more sophisticated model of a festoon cable system using their standard parameters