OPUS THD (Technischen Hochschule Deggendorf)
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126 research outputs found
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TSN Network Scheduling—Challenges and Approaches
No full textTime-Sensitive Networking (TSN) is a set of Ethernet standards aimed to improve determinism in packet delivery for converged networks. The main goal is to provide mechanisms that enable low and predictable transmission latency and high availability for demanding applications such as real-time audio/video streaming, automotive, and industrial control. To provide the required guarantees, TSN integrates different traffic shaping mechanisms including 802.1Qbv, 802.1Qch, and 802.1Qcr, allowing for the coexistence of different traffic classes with different priorities on the same network. Achieving the required quality of service (QoS) level needs proper selection and configuration of shaping mechanisms, which is difficult due to the diversity in the requirements of the coexisting streams under the presence of potential end-system-induced jitter. This paper discusses the suitability of the TSN traffic shaping mechanisms for the different traffic types, analyzes the TSN network configuration problem, i.e., finds the optimal path and shaper configurations for all TSN elements in the network to provide the required QoS, discusses the goals, constraints, and challenges of time-aware scheduling, and elaborates on the evaluation criteria of both the network-wide schedules and the scheduling algorithms that derive the configurations to present a common ground for comparison between the different approaches. Finally, we analyze the evolution of the scheduling task, identify shortcomings, and suggest future research directions
Detection of Plastic Granules and Their Mixtures
No full textChemically pure plastic granulate is used as the starting material in the production of plastic parts. Extrusion machines rely on purity, otherwise resources are lost, and waste is produced. To avoid losses, the machines need to analyze the raw material. Spectroscopy in the visible and near-infrared range and machine learning can be used as analyzers. We present an approach using two spectrometers with a spectral range of 400–1700 nm and a fusion model comprising classification, regression, and validation to detect 25 materials and proportions of their binary mixtures. one dimensional convolutional neural network is used for classification and partial least squares regression for the estimation of proportions. The classification is validated by reconstructing the sample spectrum using the component spectra in linear least squares fitting. To save time and effort, the fusion model is trained on semi-empirical spectral data. The component spectra are acquired empirically and the binary mixture spectra are computed as linear combinations. The fusion model achieves very a high accuracy on visible and near-infrared spectral data. Even in a smaller spectral range from 400–1100 nm, the accuracy is high. The visible and near-infrared spectroscopy and the presented fusion model can be used as a concept for building an analyzer. Inexpensive silicon sensor-based spectrometers can be used
Responsibility Under Uncertainty: Which Climate Decisions Matter Most?
No full textWe propose a new method for estimating how much decisions under monadic uncertainty matter. The method is generic and suitable for measuring responsibility in finite horizon sequential decision processes. It fulfills “fairness” requirements and three natural conditions for responsibility measures: agency, avoidance and causal relevance. We apply the method to study how much decisions matter in a stylized greenhouse gas emissions process in which a decision maker repeatedly faces two options: start a “green” transition to a decarbonized society or further delay such a transition. We account for the fact that climate decisions are rarely implemented with certainty and that their consequences on the climate and on the global economy are uncertain. We discover that a “moral” approach towards decision making — doing the right thing even though the probability of success becomes increasingly small — is rational over a wide range of uncertainties
Minimally Invasive versus Conventional Approaches in Total Hip Arthroplasty: A Systematic Review and Meta-Analysis of 47 Randomized Controlled Trials
No full textBackground:
Recent meta-analyses have shown indifferent results between minimally invasive (MI) and conventional approach (CA) total hip arthroplasty (THA), not including the superior MI approach SuperPATH. The aim was to compare the surgical, functional and radiological outcomes and postoperative complications of MI THA, including SuperPATH, with CA THA in patients with hip disease or femoral neck fracture.
Methods:
PubMed, CNKI, The Cochrane Library, clinical trials, CINAHL and Embase were searched for randomized controlled trials (RCTs) comparing MI THA and CA THA up to 31 July 2023. Mean differences (MDs) with 95% confidence intervals (CIs) were calculated for continuous outcomes and odds ratios (ORs) with 95% CIs were calculated for dichotomous outcomes using a common effect/random effects model. The random effects model was used to present the results. Heterogeneity was assessed using the Cochrane Q test and the Higgins I2 test.
Results:
A total of 47 RCTs with 4086 THAs in 4063 patients were included in our meta-analysis. MI THA showed better results than CA THA in 8 of 18 outcome parameters studied. MI THA showed a higher Harris Hip Score (HHS) than CA THA at 0–1.5, 3, 6 and ≥12 months postoperatively (p < 0.01; p = 0.02; p = 0.01; p = 0.01). MI THA showed an indifferent overall postoperative complication risk compared to CA THA (p = 0.61). Acetabular positioning angles were within the safe zone in all approaches.
Conclusions:
The results of the meta-analysis suggest that MI THA has several advantages over CA THA in terms of short-term surgical and functional outcomes, with equal postoperative complication rates. We cannot recommend a change in surgical approach based on our results, as the differences between the investigated approaches did not reach minimal clinically important differences. Level of evidence I: a systematic review of all relevant randomized controlled trials
Spectral Clustering of CRISM Datasets in Jezero Crater Using UMAP and k-Means
No full textIn this paper, we expand upon our previous research on unsupervised learning algorithms to map the spectral parameters of the Martian surface. Previously, we focused on the VIS-NIR range of hyperspectral data from the CRISM imaging spectrometer instrument onboard NASA’s Mars Reconnaissance Orbiter to relate to other correspondent imager data sources. In this study, we generate spectral cluster maps on a selected CRISM datacube in a NIR range of 1050–2550 nm. This range is suitable for identifying most dominate mineralogy formed in ancient wet environment such as phyllosilicates, pyroxene and smectites. In the machine learning community, the UMAP method for dimensionality reduction has recently gained attention because of its computing efficiency and speed. We apply this algorithm in combination with k-Means to data from Jezero Crater. Such studies of Jezero Crater are of priority to support the planning of the current NASA’s Perseversance rover mission. We compare our results with other methodologies based on a suitable metric and can identify an optimal cluster size of six for the selected datacube. Our proposed approach outperforms comparable methods in efficiency and speed. To show the geological relevance of the different clusters, the so-called “summary products” derived from the hyperspectral data are used to correlate each cluster with its mineralogical properties. We show that clustered regions relate to different mineralogical compositions (e.g., carbonates and pyroxene). Finally the generated spectral cluster map shows a qualitatively strong resemblance with a given manually compositional expert map. As a conclusion, the presented method can be implemented for automated region-based analysis to extend our understanding of Martian geological history
Coronary microvascular dysfunction is a hallmark of all subtypes of MINOCA
No full textIntroduction
Myocardial infarction without obstructive coronary artery disease (MINOCA) is a heterogeneous clinical condition presenting with myocardial necrosis not due to an obstruction of a major coronary artery. Recently, a relevant role of coronary microvascular dysfunction (CMD) in the pathogenesis of MINOCA has been suggested; however, data on this are scarce. Particularly, it is unclear if CMD is equally present in all subtypes of MINOCA or differentially identifies one or more of these conditions. Therefore, the aim of this study was to assess CMD in all three coronary vessels of MINOCA patients, relating it with the clinical subtype.
Methods
We retrospectively assessed coronary microvascular function in all three coronary territories by means of angiography-based index of microvascular resistance (aIMR) in 92 patients (64 with working diagnosis of MINOCA, 28 control patients). To further assess the association of CMD with MINOCA subtypes, MINOCA patients were subdivided according to clinical data in coronary cause (n = 13), takotsubo (n = 13), infiltrative or inflammatory cardiomyopathy (n = 9) or unclear (n = 29).
Results
Patients with working diagnosis of MINOCA showed a significantly elevated average aIMR compared to control patients (30.5 ± 7.6 vs. 22.1 ± 5.9, p < 0.001) as a marker of a relevant CMD; these data were consistent in all vessels. Among MINOCA subtypes, no significant difference in average aIMR could be detected between patients with coronary cause (33.2 ± 6.6), takotsubo cardiomyopathy (29.2 ± 6.9), infiltrative or inflammatory cardiomyopathy (28.1 ± 6.8) or unclear cause (30.6 ± 8.5; p = 0.412). Interestingly, aIMR was significantly elevated in the coronary vessel supplying the diseased myocardium compared with other vessels (31.9 ± 11.4 vs. 27.8 ± 8.2, p = 0.049).
Conclusion
Coronary microvascular dysfunction is a hallmark of all MINOCA subtypes. This study adds to the pathophysiological understanding of MINOCA and sheds light into the role of CMD in MINOCA
Atomization of Borosilicate Glass Melts for the Fabrication of Hollow Glass Microspheres
No full textDirect atomization of a free-flowing glass melt was carried out using a high-speed flame with the aim of producing tiny, self-expanding glass melt droplets to form hollow glass microspheres. Atomization experiments were carried out using a specially adapted free-fall atomizer in combination with a high-power gas burner to achieve sufficient temperatures to atomize the melt droplets and to directly expand them into hollow glass spheres. In addition, numerical simulations were carried out to investigate non-measurable parameters such as hot gas velocities and temperatures in the flame region by the finite volume-based software Star CCM+® (v. 2022.1.1), using the Reynolds-Averaged Navier–Stokes (RANS) turbulence and the segregated flow model. To calculate the combustion process, the laminar flamelet method was used. The experiments and simulations indicated that a maximum gas velocity of about 170 m/s was achieved at the point of atomization in the flame. The particle size distribution of the atomized glass droplets, either solid or hollow, ranged from 2 µm to 4 mm. Mean particle sizes in the range of 370 µm to 650 µm were highly dependent on process parameters such as gas velocity. They were in good agreement with theoretically calculated median diameters. The formation of hollow glass microspheres with the proposed concept could be demonstrated. However, only a small fraction of hollow glass spheres was found to be formed. These hollow spheres had diameters up to 50 µm and, as expected, a thin wall thickness
OpenVNT: An Open Platform for VIS-NIR Technology
No full textSpectrometers measure diffuse reflectance and create a “molecular fingerprint” of the material under investigation. Ruggedized, small scale devices for “in-field” use cases exist. Such devices might for example be used by companies in the food supply chain for inward inspection of goods. However, their application for the industrial Internet of Things workflows or scientific research is limited due to their proprietary nature. We propose an open platform for visible and near-infrared technology (OpenVNT), an open platform for capturing, transmitting, and analysing spectral measurements. It is built for use in the field, as it is battery-powered and transmits data wireless. To achieve high accuracy, the OpenVNT instrument contains two spectrometers covering a wavelength range of 400–1700 nm. We conducted a study on white grapes to compare the performance of the OpenVNT instrument against the Felix Instruments F750, an established commercial instrument. Using a refractometer as ground truth, we built and validated models to estimate the Brix value. As a quality measure, we used coefficient of determination of the cross-validation (R2CV) between the instrument estimation and ground truth. With 0.94 for the OpenVNT and 0.97 for the F750, a comparable R2CV was achieved for both instruments. OpenVNT matches the performance of commercially available instruments at one tenth of the price. We provide an open bill of materials, building instructions, firmware, and analysis software to enable research and industrial IOT solutions without the limitations of walled garden platforms
Anonymization Procedures for Tabular Data: An Explanatory Technical and Legal Synthesis
No full textIn the European Union, Data Controllers and Data Processors, who work with personal data, have to comply with the General Data Protection Regulation and other applicable laws. This affects the storing and processing of personal data. But some data processing in data mining or statistical analyses does not require any personal reference to the data. Thus, personal context can be removed. For these use cases, to comply with applicable laws, any existing personal information has to be removed by applying the so-called anonymization. However, anonymization should maintain data utility. Therefore, the concept of anonymization is a double-edged sword with an intrinsic trade-off: privacy enforcement vs. utility preservation. The former might not be entirely guaranteed when anonymized data are published as Open Data. In theory and practice, there exist diverse approaches to conduct and score anonymization. This explanatory synthesis discusses the technical perspectives on the anonymization of tabular data with a special emphasis on the European Union’s legal base. The studied methods for conducting anonymization, and scoring the anonymization procedure and the resulting anonymity are explained in unifying terminology. The examined methods and scores cover both categorical and numerical data. The examined scores involve data utility, information preservation, and privacy models. In practice-relevant examples, methods and scores are experimentally tested on records from the UCI Machine Learning Repository’s “Census Income (Adult)” dataset
Low incidence of acute kidney injury in VLBW infants with restrictive use of mechanical ventilation
No full textBackground
We assessed the incidence of and risk factors for acute kidney injury (AKI) in very low birthweight infants (VLBW) in a center with a specific neonatal management protocol focusing on avoidance of early mechanical ventilation (MV).
Methods
This retrospective single center analysis includes 128 infants born in 2020 with a gestational age ≥ 22 weeks who were screened for AKI using the nKDIGO criteria.
Results
AKI was identified in 25/128 patients (19.5%) with eight of them (6.3%) presenting with severe AKI. Low gestational age, birthweight and 10-minute Apgar score as well as high CRIB-1 score were all associated with incidence of AKI. Forty-five percent of the infants with MV developed AKI vs. 8.9% of those without MV (p < 0.001). Early onset of MV and administration of more than 3 dosages of NSAIDs for patent duct were identified as independent risk factors for AKI in a logistic regression analysis.
Conclusions
We report a substantially lower frequency of AKI in VLBW infants as compared to previous studies, along with a very low rate of MV. A neonatal protocol focusing on avoidance of MV within the first days of life may be a key factor to decrease the risk of AKI in immature infants