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Camera-based object detection is widely used in safety-critical applications such as advanced driver assistance systems (ADAS) and autonomous vehicle research. Road infrastructure has been designed for human vision, so computer vision, with RGB cameras, is a vital source of semantic information from the environment. Sensors, such as LIDAR and RADAR, are also often utilized for these applications; however, cameras provide a higher spatial resolution and color information. The spatial frequency response (SFR), or sharpness of a camera, utilized in object detection systems must be sufficient to allow a detection algorithm to localize objects in the environment over its lifetime reliably. This study explores the relationship between object detection performance and SFR. Six state-of-the-art object detection models are evaluated with varying levels of lens defocus. A novel raw image dataset is created and utilized, containing pedestrians and cars over a range of distances up to 100-m from the sensor. Object detection performance for each defocused dataset is analyzed over a range of distances to determine the minimum SFR necessary in each case. Results show that the relationship between object detection performance and lens blur is much more complex than previous studies have found due to lens field curvature, chromatic aberration, and astigmatisms. We have found that smaller objects are disproportionately impacted by lens blur, and different object detection models have differing levels of robustness to lens blur
The importance of high data quality is increasing with the growing impact and distribution of ML systems and big data. Also, the planned AI Act from the European commission defines challenging legal requirements for data quality especially for the market introduction of safety relevant ML systems. In this paper, we introduce a novel approach that supports the data quality assurance process of multiple data quality aspects. This approach enables the verification of quantitative data quality requirements. The concept and benefits are introduced and explained on small example data sets. How the method is applied is demonstrated on the well-known MNIST data set based an handwritten digits.
A numerical study is carried out meticulously to scrutinize the impact of different shapes of chimneys like circular (outer dia, dc), convergent (outer dia, 0.5dc), divergent (outer dia, 1.5dc), sudden contraction (outer dia, 0.5dc), and sudden expansion (outer dia, 1.5dc) on the performance of an SCPP. Furthermore, the parametric impact with different chimney divergence angles (CDA, ϕ), and ground absorber slope angle (GSA, γ) on the SCPP performance is also scrutinized. Optimum divergence angle (ϕ=+0.75◦) enhances the power generation up to ~ 47% (76 kW) with a horizontal ground absorber surface. An increase or decrease in CDA lessens the power generation. With a sloped ground absorber angle γ=0.6◦, the gain in power generation is 60% (82 kW). The study of combination of ground sloped absorber (γ=0.6◦) and divergent chimney (ϕ=+0.75◦) shows enhancement of the power generation upto 80% (92 kW) more than the classical Manzaranes plant.
Refractive power measurements serve as the primary quality standard in the automotive glazing industry. In the light of autonomous driving new optical metrics are becoming more and more popular for specifying optical quality requirements for the windshield. Nevertheless, the link between those quantities and the refractive power needs to be established in order to ensure a holistic requirement profile for the windshield. As a consequence, traceable high-resolution refractive power measurements are still required for the glass quality assessment. Standard measurement systems using Moiré patterns for refractive power monitoring in the automotive industry are highly resolution limited, wherefore they are insufficient for evaluating the camera window area. Consequently, there is a need for more sophisticated refractive power measurement systems that provide a higher spatial resolution. In addition, a calibration procedure has to be developed in order to guarantee for comparability of the measurement results. For increasing the resolution, a measurement setup based on an auto-correlation algorithm is tested in this paper. Furthermore, a calibration procedure is established by using a single reference lens with a nominal refractive power of 100 km-1. For the calibration of the entire measurement range of the system, the lens is tilted by an inclination angle orthogonal to the optical axis. The effective refractive power is then given by the Kerkhof model. By adopting the measurement and calibration procedure presented in this paper, glass suppliers in the automotive industry will be able to detect relevant manufacturing defects within the camera window area more accurately paving the way for a holistic quality assurance of the windshield for future advanced driver-assistance system (ADAS) functionalities. Concurrently, the traceability of the measurement results is ensured by establishing a calibration chain based on a single reference lens, which is traced back to international standards.
Abstract The modulation-transfer function (MTF) is a fundamental optical metric to measure the optical quality of an imaging system. In the automotive industry it is used to qualify camera systems for ADAS/AD. Each modern ADAS/AD system includes evaluation algorithms for environment perception and decision making that are based on AI/ML methods and neural networks. The performance of these AI algorithms is measured by established metrics like Average Precision (AP) or precision-recall-curves. In this article we research the robustness of the link between the optical quality metric and the AI performance metric. A series of numerical experiments were performed with object detection and instance segmentation algorithms (cars, pedestrians) evaluated on image databases with varying optical quality. We demonstrate with these that for strong optical aberrations a distinct performance loss is apparent, but that for subtle optical quality differences – as might arise during production tolerances – this link does not exhibit a satisfactory correlation. This calls into question how reliable the current industry practice is where a produced camera is tested end-of-line (EOL) with the MTF, and fixed MTF thresholds are used to qualify the performance of the camera-under-test.
Schule als sicherer Ort
(2017)
Management des Innovationsportfolios: Portfolio-Matrizen zumManagement von Innovationsprojekten
(2021)
In the present contribution, the utilization of steel-mill gases for an industrial methanol synthesis process is described. The focus of this work is on the influence of syngas compositions derived from steel-mill gases on an industrial Cu/ZnO/Al2O3 catalyst. Elevated CO2 and H2O concentrations seem to have an irreversible impact on the activity of the catalyst. In order to obtain realistic gas composition for the catalyst tests, a process simulation of the methanol synthesis was conducted. The calculated gas compositions at the reactor inlet were applied in a practical test in order to evaluate the catalyst stability under steel mill gas conditions. No noticeable deactivation was observed.
The optimization of full-scale biogas plant operation is of great importance to make biomass a competitive source of renewable energy. The implementation of innovative control and optimization algorithms, such as Nonlinear Model Predictive Control, requires an online estimation of operating states of biogas plants. This state estimation allows for optimal control and operating decisions according to the actual state of a plant. In this paper such a state estimator is developed using a calibrated simulation model of a full-scale biogas plant, which is based on the Anaerobic Digestion Model No.1. The use of advanced pattern recognition methods shows that model states can be predicted from basic online measurements such as biogas production, CH4 and CO2 content in the biogas, pH value and substrate feed volume of known substrates. The machine learning methods used are trained and evaluated using synthetic data created with the biogas plant model simulating over a wide range of possible plant operating regions. Results show that the operating state vector of the modelled anaerobic digestion process can be predicted with an overall accuracy of about 90%. This facilitates the application of state-based optimization and control algorithms on full-scale biogas plants and therefore fosters the production of eco-friendly energy from biomass.
Airborne volcanic ash particles are a known hazard to aviation. Currently, there are no means available to detect ash in flight as the particles are too fine (radii < 30 μm) for on-board radar detection and, even in good visibility, ash clouds are difficult or impossible to detect by eye. The economic cost and societal impact of the April/May 2010 Icelandic eruption of Eyjafjallajökull generated renewed interest in finding ways to identify airborne volcanic ash in order to keep airspace open and avoid aircraft groundings. We have designed and built a bi-spectral, fast-sampling, uncooled infrared camera device (AVOID) to examine its ability to detect volcanic ash from commercial jet aircraft at distances of more than 50 km ahead. Here we report results of an experiment conducted over the Atlantic Ocean, off the coast of France, confirming the ability of the device to detect and quantify volcanic ash in an artificial ash cloud created by dispersal of volcanic ash from a second aircraft. A third aircraft was used to measure the ash in situ using optical particle counters. The cloud was composed of very fine ash (mean radii ~10 μm) collected from Iceland immediately after the Eyjafjallajökull eruption and had a vertical thickness of ~200 m, a width of ~2 km and length of between 2 and 12 km. Concentrations of ~200 μg m(-3) were identified by AVOID at distances from ~20 km to ~70 km. For the first time, airborne remote detection of volcanic ash has been successfully demonstrated from a long-range flight test aircraft.
Rituals, such as gazing at faces, are common in body dysmorphic disorder (BDD) and appear in cognitive-behavioral models as a maintaining factor. Rituals are also common in obsessive-compulsive disorder (OCD). In contrast to OCD, the proposed associations between rituals and intrusive thoughts/appearance preoccupation have not been empirically investigated for BDD. We examined if the assumed effect of gazing rituals on attractiveness ratings exists and if it is associated with dissociation. In an experiment, we asked N = 65 non-clinical females to focus on the nose of a photographed face at pre- and post-test. In between, participants gazed at the nose of either the same (relevant gazing) or another face (irrelevant gazing). We found increasing dissociation after gazing in both conditions and a differentially stronger decrease of attractiveness ratings in the relevant gazing condition. Our findings support the hypothesized effect of gazing rituals on attractiveness evaluation in cognitive-behavioral models for BDD.
Dandyismus und Popkultur
(2013)
Am Musikvideo „Kiss“ von Prince and the Revolution (1986) werden exemplarisch verschiedene Verfahren beleuchtet, wie Gender durch „Stimme“ im konkreten und abstrakten Sinn auf ambivalente Weise inszeniert wird. Michael Bachtins Metapher der fremden Stimme für das intertexuelle Verweisgeflecht von Sprache im Allgemeinen und Literatur im Besonderen wird hier sowohl im übertragenen als auch im wörtlichen Sinne verwendet und auf audiovisuelle Musikformate übertragen. Das Spiel mit Gender entsteht durch eine komplexe Verwebung von intertextuellen und intermedialen Verweisen auf andere Liedtexte, Filme, Gesangstraditionen, Subkulturen etc. Dabei wird vestimentäres Cross-Dressing mit gesanglichem Cross-Dressing kombiniert.
Kaufhaus-Punk auf youtube. Mediale Kontrolle zwischen Musiker und Fans am Beispiel von Jan Delay
(2012)
We present a system that exploits mobile rotational tracking and photospherical imagery to allow users to share their environment with remotely connected peers “on the go.” We surveyed related interfaces and developed a unique groupware application that shares a mixed reality space with spatially-oriented live video feeds. Users can collaborate through realtime audio, video, and drawings in a virtual space. The developed system was tested in a preliminary user study, which confirmed an increase in spatial and situational awareness among viewers as well as reduction in cognitive workload. Believing that our system provides a novel style of collaboration in mixed reality environments, we discuss future applications and extensions of our prototype.
Geschäftsmodelle für das Internet der Dinge: Welche Geschäftsmodellinnovation passt zum Unternehmen?
(2020)
Der Beitrag stellt am Beispiel von studentischen Projekt- und Praxisarbeiten aus den bibliothekswissenschaftlichen Studiengängen der TH Köln Möglichkeiten der Erstellung von E-Learning-Angeboten vor, die sich in kurzer Zeit und ohne finanzielles Budget realisieren lassen. Der Fokus liegt dabei auf unkonventionellen Darstellungsformen wie bspw. Comic-artigen Animationsfilmen oder der Präsentation bibliothekarischer Inhalte nach dem Modell von „Sommers Weltliteratur“. Der Beitrag möchte Bibliotheken dazu anregen, im Kontext des E-Learning mit neuen Formaten zu experimentieren, die dazu beitragen können, die Attraktivität der bibliothekarischen Angebote zu erhöhen und die sich gleichzeitig mit geringem zeitlichem und finanziellem Aufwand realisieren lassen.
This paper deals with the design of a micro-scale ORC plant for teaching and research including the development of an automated control concept. The aim is to provide a safe and environmentally acceptable micro-scale heat engine, which can be developed, implemented and used in university labs for the education of students as well as for small research projects. The test rig allows the support of several learning outcomes on a multi-disciplinary level particularly for the implementation and simulation of small power systems. Special attention was given to the organic working fluid characteristics and its selection process. In addition to the above-mentioned performance goals, favourable safety properties and low global warming potential were decisive in the selection of the novel organic fluid called 3M™ Novec™ 649. The performance and the fluid behaviour of Novec 649 in a micro-scale power cycle are of major interest and the research goal for the test rig presented in this paper. Due to the expected power output of 1 kW, a scroll expander was chosen as the generator drive for the micro plant. In order to design the major parts of the ORC, the thermodynamic simulation software EBSILON®Professional was used. The supply temperature was set to 140 °C. As a result of the simulation, feasible expander inlet pressures spread from 5.5 bar to 8.5 bar. This leads to thermal efficiencies of the ORC in the order of 5 %. Adding a recuperator to the cycle system decreases the operating pressure range but in the end, the thermal efficiency can be increased by 1.5 %-points up to 6.2 %. Finally, an automated control concept is introduced, where the pump is controlled via the fill level measurement system.