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Adapting augmented reality systems to the users’ needs using gamification and error solving methods
(2021)
Animations of virtual items in AR support systems are typically predefined and lack interactions with dynamic physical environments. AR applications rarely consider users’ preferences and do not provide customized spontaneous support under unknown situations. This research focuses on developing adaptive, error-tolerant AR systems based on directed acyclic graphs and error resolving strategies. Using this approach, users will have more freedom of choice during AR supported work, which leads to more efficient workflows. Error correction methods based on CAD models and predefined process data create individual support possibilities. The framework is implemented in the Industry 4.0 model factory at FH Aachen.
To prevent the reduction of muscle mass and loss of strength coming along with the human aging process, regular training with e.g. a leg press is suitable. However, the risk of training-induced injuries requires the continuous monitoring and controlling of the forces applied to the musculoskeletal system as well as the velocity along the motion trajectory and the range of motion. In this paper, an adaptive norm-optimal iterative learning control algorithm to minimize the knee joint loadings during the leg extension training with an industrial robot is proposed. The response of the algorithm is tested in simulation for patients with varus, normal and valgus alignment of the knee and compared to the results of a higher-order iterative learning control algorithm, a robust iterative learning control and a recently proposed conventional norm-optimal iterative learning control algorithm. Although significant improvements in performance are made compared to the conventional norm-optimal iterative learning control algorithm with a small learning factor, for the developed approach as well as the robust iterative learning control algorithm small steady state errors occur.
Adaptive logistics : information management for planning and control of small series assembly
(2007)
The esophageal Doppler monitor (EDM) is a minimally-invasive hemodynamic device which evaluates both cardiac output (CO), and fluid status, by estimating stroke volume (SV) and calculating heart rate (HR). The measurement of these parameters is based upon a continuous and accurate approximation of distal thoracic aortic blood flow. Furthermore, the peak velocity (PV) and mean acceleration (MA), of aortic blood flow at this anatomic location, are also determined by the EDM. The purpose of this preliminary report is to examine additional clinical hemodynamic calculations of: compliance (C), kinetic energy (KE), force (F), and afterload (TSVRi). These data were derived using both velocity-based measurements, provided by the EDM, as well as other contemporaneous physiologic parameters. Data were obtained from anesthetized patients undergoing surgery or who were in a critical care unit. A graphical inspection of these measurements is presented and discussed with respect to each patient’s clinical situation. When normalized to each of their initial values, F and KE both consistently demonstrated more discriminative power than either PV or MA. The EDM offers additional applications for hemodynamic monitoring. Further research regarding the accuracy, utility, and limitations of these parameters is therefore indicated.
The cooling process in induction based crucible melting furnaces for Industrial applications is one of the important and challenging factors in production and safety engineering. Accordingly, proper implementation of the cooling system of the furnace using optimum cooling guides and fail-safe features are critical in order to improve the safety of the process. Regarding this, manufacturing of porous material with high electrical isolation for the drainage segments of the cooling channels is examined in this study. Consequently, various geometries with different porosities using glass and ceramic powder are fabricated using Selective Laser Sintering (SLS) process. The manufactured parts are examined in a prototype furnace testing and the feasibility of the SLS manufacturing of parts for this application is discussed.
Neuromuscular strength training of the leg extensor muscles plays an important role in the rehabilitation and prevention of age and wealth related diseases. In this paper, we focus on the design and implementation of a Cartesian admittance control scheme for isotonic training, i.e. leg extension and flexion against a predefined weight. For preliminary testing and validation of the designed algorithm an experimental research and development platform consisting of an
industrial robot and a force plate mounted at its end-effector has been used. Linear, diagonal and arbitrary two-dimensional motion trajectories with different weights for the leg extension and flexion part are applied. The proposed algorithm is easily adaptable to trajectories consisting of arbitrary six-dimensional poses and allows the implementation of individualized trajectories.
Integrated voice assistants (IVA) receive more and more attention and are widespread for entertainment use cases, such as radio hearing or web searches. At the same time, the health care segment suffers in process inefficiency and missing staff, whereas the usage of IVA has the potential to improve caring processes and patient satisfaction. By applying a design science approach and based on a qualitative study, we identify IVA requirements, barriers and design guidelines for the health care sector. The results reveal three important IVA functions: the ability to set appointments with care service staff, the documentation of health history and the communication with service staff. Integration, system stability and volume control are the most important nonfunctional requirements. Based on the interview results and project experiences, six design and implementation guidelines are derived.
Bacterial lipopolysaccharides (endotoxins) show strong biological effects at very low concentrations in human beings and many animals when entering the blood stream. These include affecting structure and function of organs and cells, changing metabolic functions, raising body temperature, triggering the coagulation cascade, modifying hemodynamics and causing septic shock. Because of this toxicity, the removal of even minute amounts is essential for safe parenteral administration of drugs and also for septic shock patients' care. The absence of a general method for endotoxin removal from liquid interfaces urgently requires finding new methods and materials to overcome this gap. Nanostructured carbonized plant parts is a promising material that showed good adsorption properties due to its vast pore network and high surface area. The aim of this study was comparative measurement of endotoxin- and blood proteins-related adsorption rate and adsorption capacity for different carboneous materials produced at different temperatures and under different surface modifications. As a main surface modificator, positively cbarged polymer, polyethileneimine (PEl) was used. Activated carbon materials showed good adsorption properties for LPS and some proteins used in the experiments. During the batch experiments, several techniques (dust removal, autoclaving) were used and optimized for improving the material's adsorption behavior. Also, with the results obtained it was possible to differentiate the materials according to their adsorption capacity and kinetic characteristics. Modification of the surface apparently has not affected hemoglobin binding to the adsorbent's surface. Obtained adsorption isotherms can be used as a powerful tool for designing of future column-based setups for blood purification from LPS, which is especially important for septic shock treatment.
The scope of this study is the measurement of endotoxin adsorption rate for carbonized rice husk. It showed good adsorption properties for LPS. During the batch experiments, several techniques were used and optimized for improving the material’s adsorption behavior. Also, with the results obtained it was possible to differentiate the materials according to their adsorption capacity and kinetic characteristics.
Due to their anion exchange characteristics, layered double hydroxides (LDHs) are suitable for the detoxification of aqueous, fatty acid containing fermentation substrates. The aim of this study is to examine the adsorption mechanism, using crude glycerol from plant oil esterification as a model system. Changes in the intercalation structure in relation to the amount of fatty acids adsorbed are monitored by X-ray diffraction and infra-red spectroscopy. Additionally, calcination of LDH is investigated in order to increase the binding capacity for fatty acids. Our data propose that, at ambient temperature, fatty acids can be bound to the hydrotalcite by adsorption or in addition by intercalation, depending on fatty acid concentration. The adsorption of fatty acids from crude glycerol shows a BET-like behavior. Above a fatty acid concentration of 3.5 g L−1, intercalation of fatty acids can be shown by the appearance of an increased interlayer spacing. This observation suggests a two phase adsorption process. Calcination of LDHs allows increasing the binding capacity for fatty acids by more than six times, mainly by reduction of structural CO32−.
To fulfil the CO2 emission reduction targets of the European Union (EU), heavy-duty (HD) trucks need to operate 15% more efficiently by 2025 and 30% by 2030. Their electrification is necessary as conventional HD trucks are already optimized for the long-haul application. The resulting hybrid electric vehicle (HEV) truck gains most of the fuel saving potential by the recuperation of potential energy and its consecutive utilization. The key to utilizing the full potential of HEV-HD trucks is to maximize the amount of recuperated energy and ensure its intelligent usage while keeping the operating point of the internal combustion engine as efficient as possible. To achieve this goal, an intelligent energy management strategy (EMS) based on ECMS is developed for a parallel HEV-HD truck which uses predictive discharge of the battery and adaptive operating strategy regarding the height profile and the vehicle mass. The presented EMS can reproduce the global optimal operating strategy over long phases and lead to a fuel saving potential of up to 2% compared with a heuristic strategy. Furthermore, the fuel saving potential is correlated with the investigated boundary conditions to deepen the understanding of the impact of intelligent EMS for HEV-HD trucks.
Traditional vulcanization mold manufacturing is complex, costly, and under pressure due to shorter product lifecycles and diverse variations. Additive manufacturing using Fused Filament Fabrication and high-performance polymers like PEEK offer a promising future in this industry. This study assesses the compressive strength of various infill structures (honeycomb, grid, triangle, cubic, and gyroid) when considering two distinct build directions (Z, XY) to enhance PEEK’s economic and resource efficiency in rapid tooling. A comparison with PETG samples shows the behavior of the infill strategies. Additionally, a proof of concept illustrates the application of a PEEK mold in vulcanization. A peak compressive strength of 135.6 MPa was attained in specimens that were 100% solid and subjected to thermal post-treatment. This corresponds to a 20% strength improvement in the Z direction. In terms of time and mechanical properties, the anisotropic grid and isotropic cubic infill have emerged for use in rapid tooling. Furthermore, the study highlights that reducing the layer thickness from 0.15 mm to 0.1 mm can result in a 15% strength increase. The study unveils the successful utilization of a room-temperature FFF-printed PEEK mold in vulcanization injection molding. The parameters and infill strategies identified in this research enable the resource-efficient FFF printing of PEEK without compromising its strength properties. Using PEEK in rapid tooling allows a cost reduction of up to 70% in tool production.
Advanced on-wafer multiport calibration methods for mono- and mixed-mode device characterization
(2004)
Sleep spindles are neurophysiological phenomena that appear to be linked to memory formation and other functions of the central nervous system, and that can be observed in electroencephalographic recordings (EEG) during sleep. Manually identified spindle annotations in EEG recordings suffer from substantial intra- and inter-rater variability, even if raters have been highly trained, which reduces the reliability of spindle measures as a research and diagnostic tool. The Massive Online Data Annotation (MODA) project has recently addressed this problem by forming a consensus from multiple such rating experts, thus providing a corpus of spindle annotations of enhanced quality. Based on this dataset, we present a U-Net-type deep neural network model to automatically detect sleep spindles. Our model’s performance exceeds that of the state-of-the-art detector and of most experts in the MODA dataset. We observed improved detection accuracy in subjects of all ages, including older individuals whose spindles are particularly challenging to detect reliably. Our results underline the potential of automated methods to do repetitive cumbersome tasks with super-human performance.
In order to realistically predict and optimize the actual performance of a concentrating solar power (CSP) plant sophisticated simulation models and methods are required. This paper presents a detailed dynamic simulation model for a Molten Salt Solar Tower (MST) system, which is capable of simulating transient operation including detailed startup and shutdown procedures including drainage and refill. For appropriate representation of the transient behavior of the receiver as well as replication of local bulk and surface temperatures a discretized receiver model based on a novel homogeneous two-phase (2P) flow modelling approach is implemented in Modelica Dymola®. This allows for reasonable representation of the very different hydraulic and thermal properties of molten salt versus air as well as the transition between both. This dynamic 2P receiver model is embedded in a comprehensive one-dimensional model of a commercial scale MST system and coupled with a transient receiver flux density distribution from raytracing based heliostat field simulation. This enables for detailed process prediction with reasonable computational effort, while providing data such as local salt film and wall temperatures, realistic control behavior as well as net performance of the overall system. Besides a model description, this paper presents some results of a validation as well as the simulation of a complete startup procedure. Finally, a study on numerical simulation performance and grid dependencies is presented and discussed.
Advanced window systems and building energy performance / S. Reilly ; J. Göttsche ; V. Wittwer
(1991)
Bacterial cellulose (BC) is a biopolymer produced by different microorganisms, but in biotechnological practice, Komagataeibacter xylinus is used. The micro- and nanofibrillar structure of BC, which forms many different-sized pores, creates prerequisites for the introduction of other polymers into it, including those synthesized by other microorganisms. The study aims to develop a cocultivation system of BC and prebiotic producers to obtain BC-based composite material with prebiotic activity. In this study, pullulan (PUL) was found to stimulate the growth of the probiotic strain Lactobacillus rhamnosus GG better than the other microbial polysaccharides gellan and xanthan. BC/PUL biocomposite with prebiotic properties was obtained by cocultivation of Komagataeibacter xylinus and Aureobasidium pullulans, BC and PUL producers respectively, on molasses medium. The inclusion of PUL in BC is proved gravimetrically by scanning electron microscopy and by Fourier transformed infrared spectroscopy. Cocultivation demonstrated a composite effect on the aggregation and binding of BC fibers, which led to a significant improvement in mechanical properties. The developed approach for “grafting” of prebiotic activity on BC allows preparation of environmentally friendly composites of better quality.
The ANM’09 multi-disciplinary scientific program includes topics in the fields of "Nanotechnology and Microelectronics" ranging from "Bio/Micro/Nano Materials and Interfacing" aspects, "Chemical and Bio-Sensors", "Magnetic and Superconducting Devices", "MEMS and Microfluidics" over "Theoretical Aspects, Methods and Modelling" up to the important bridging "Academics meet Industry".