15 Fakultätsübergreifend / Sonstige Einrichtung

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    Die Ermittlung von Steuerprofilen zur Insulinabgabe mit programmierbaren Insulininfusionssystemen
    (1981) Schulz, Gerhard; Beyer, Jürgen; Nagel, Joachim H.; Strack, Thomas; Krause, Ulrich; Hassinger, Wieland; Cordes, Uwe
    Der Insulinverbrauch und die Form der Insulinabgabeprofile bei intravenöser Insulintherapie mit nicht rückgekoppelten Infusionsgeräten wurde bisher nur rein empirisch ermittelt. Dabei war die Form der Insulinabgabeprofile nicht zuletzt auch von den technischen Möglichkeiten des Dosiergerätes abhängig. Unser Ziel war es, Grundsätze für die Blutzuckerführung mit Open-Loop-Systemen zu entwickeln. Die Insulinprofile sollten dem Blutzuckeranstieg und Abfall nach den Mahlzeiten möglichst gut angepaßt sein und individuell programmiert werden können, so daß der Patient zu den Mahlzeiten das entsprechende Programm abrufen kann.
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    Issues in designing object management systems
    (1990) Clow, Geoff; Plödereder, Erhard
    This paper summarizes the discussions of the Object Management System (OMS) session at the Chinon Workshop. The session identified numerous capabilities which might be required in an OMS. The facilities which were agreed upon as essential to an OMS are presented in Section 1, OMS Core Facilities. A number of issues in the realization of these and other capabilities, influenced in part by specific application scenarios, are discussed in Section 2, OMS Requirements Issues. Promising applications requiring further investigation can be found in Section 3, Perceptions for the Future. Some global observations on the past and future conduct of the OMS field are summarized in Section 4, Concluding Observations.
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    Quantification of aortic stenosis based on the morphology of Doppler ultrasound signals using image processing techniques
    (1994) Zahn, Thomas P.; Nagel, Joachim H.; Agatston, Arthur S.
    A method was developed to evaluate the morphologic structure of continuous wave Doppler ultrasound signals in order to quantify aortic valve stenosis in the human heart. The systolic peaks of the Doppler signal were assigned digital images and the stability of shape information was tested for patients with low stroke volume and aortal fibrillation. The results indicate that the shape of the signal peaks remains stable despite variations in amplitude and duration. The shape information was then used to quantify the severity of aortic stenosis by optimally matching Doppler peak images to selected templates representing typical diagnostic patterns. The developed software is capable of automatic extraction of shape information from Doppler ultrasound signals in order to support the clinical decision about valve functioning and replacement.
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    Digital signal processing of the fetal heart sound
    (1982) Kartmann, Peter; Schlotter, Claus M.; Zhou, Li Gao; Nagel, Joachim H.; Schaldach, Max
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    Diagnosis and modelling of Alzheimer's disease through neural network analyses of PET studies
    (1990) Kippenhan, Jonathan Shane; Nagel, Joachim H.
    The back-propagation neural network algorithm was applied to the analysis of regional patterns in cerebral function, as demonstrated in positron emission tomography (PET). A trained network was able to successfully distinguish PET scans of normal subjects from PET scans of Alzheimer's Disease patients. It is concluded that the combination of PET and neural networks is a useful diagnostic tool for Alzheimer's Disease. A new paradigm for back-propagation learning is discussed which emphasizes its similarity to template matching. It is demonstrated that, under certain circumstances, the back-propagation network can be used as an estimation tool, as well as a classification tool, i.e., a trained neural network can indicate the criteria by which its classifications are performed.
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    Comparison of Taguchi Method and Robust Design Optimization (RDO) : by application of a functional adaptive simulation model for the robust product-optimization of an adjuster unit
    (2015) Kemmler, Stefan; Fuchs, Alexander; Leopold, Tobias; Bertsche, Bernd
    Current research and development have been trending towards approaches based on simulation and virtual testing. Industrial development processes for complex products employ optimization methods to ensure results are close to reality, simultaneously minimizing required resources. The results of virtual testing are optimized in accordance with requirements using optimization techniques. Robust Design Optimization (RDO) is one established approach to optimization. RDO is based on the identification of an optimal parameter set which includes a small variance of the target value as a constraint. Under most circumstances, this approach does not involve separate optimization of the target value and target variance. However, the basic strategy of the optimization approach developed by Taguchi is to first optimize the parameter sets for the target value and then optimize and minimize the target variance. According to an application example , the benefit of Taguchi's approach (TM) is that it facilitates the identification of an optimal parameter set of nominal values for technical feasibility and possible manufacturing. If an optimal parameter set is determined, the variance can be minimized under consideration of process parameters. This paper examines and discusses the differences between and shared characteristics of the robust optimization methods TM and RDO, and discusses their shortcomings. In order to provide a better illustration, this paper explains and applies both methods using an adjuster unit of a commercial vehicle braking system. A simulation model is developed including an appropriate work ow by applying optiSLang-modules.
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    Validation and analysis of linear distillation models for controller design
    (1993) Amrhein, Michael; Allgöwer, Frank; Marquardt, Wolfgang
    It is a nontrivial task to decide whether a model describes the main dynamic characteristics of a process and to determine which model is to be preferred for controller design. Techniques for examining lineal models for controller design are described in Section 2. One focus of this paper is on tools for analysing multivariable processes in the frequency domain, for example, condition number and dynamic relative gain array (RGA) analysis. The latter tool is extended by the phase information of the RGA. A novel evaluation tool involving the singular directions over frequency of the respective processes is introduced. In Section 3, a new linear low-order model is compared to five models from the literature using the analysis tools introduced in Section 2. The new model directly exploits wave propagation phenomena, and, therefore, will be called the wave model. Finally, Section 4 shows briefly result of the H∞-coutrolled column where the controller is designed on the basis of the wave model. Simulations with a detailed nonlinear distillation model show that very good control action can be achieved with this model. Moreover, the linear model allows to predict the nonlinear closed loop behavior quite accurately.
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    Fast multimodality image matching
    (1988) Apicella, Anthony; Nagel, Joachim H.; Duara, Ranjan
    The diagnostic potential of medical images obtained at different times or from complimentary imaging modalities may be augmented by objective, accurate matching of the different data sets. Correlation analysis offers a powerful technique for the computation of translation, rotation, and scaling differences between image data sets, especially in the case of complimentary images containing similar but not exact information. So far, this technique suffers from the drawback of high computational expense. We have reformulated this approach, yielding a fast, computationally much less expensive algorithm. Reduction of computation time is about seventy five percent.
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    Design and evaluation of a lidar-based feedforward controller for the INNWIND.EU 10 MW wind turbine
    (2015) Fürst, Holger; Schlipf, David; Iribas Latour, Mikel; Cheng, Po Wen
    For the development of the next generation of multi megawatt wind turbines, advanced control concepts are one of the major tasks. Reduction of fatigue and extreme loading could help to improve the overall design process and make plants more cost effective. This work deals with the application of the promising methodology of feedforward control using nacelle-based lidar sensor measurements on a 10 MW wind turbine concept. After lidar data processing has been described, the feedforward controller is designed such that disturbances from the changing wind speed to the generator speed are compensated by adding an update to the collective pitch rate signal of the normal feedback controller. The evaluation of the feedforward controller is done in two steps: Firstly, simulations using perfect lidar data measurements are applied to check the robustness of the controller against model uncertainties. After that, simulations with realistic lidar measurements are investigated. To improve control performance, the scanning configuration of the used lidar system is optimized. Over all it can be shown that lidar-assisted control leads to significant load reductions, especially in the full load region of the 10 MW turbine.
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    Decomposition of heart rate variability by adaptive filtering for estimation of cardiac vagal tone
    (1991) Han, Kedu; Nagel, Joachim H.; Hurwitz, Barry E.; Schneiderman, Neil
    Heart rate fluctuations resulting from respiration and other influences upon the cardiovascular system are encoded into the patterns of heart rate variability (HRV). The fluctuations due to respiration are called respiratory sinus arrhythmia (RSA). Since RSA is primarily mediated through the autonomic nervous system (ANS), it is of interest to separate RSA from other influences to assess the underlying ANS function. On the other hand, the RSA may obscure heart rate responses to external manipulations in psychophysiological tests. A method of partitioning the HRV signal which can provide quantitative estimate of RSA as well as true heart rate responses without respiratory disturbances for psychophysiological studies is developed. The analysis of HRV signal is performed using an adaptive filtering system. With the simultaneously recorded respiration signal as a reference input, the HRV signal can be separated into two components, RSA and fluctuation due to other influences. After the separation, the variance of RSA, an estimate of cardiac vagal tone (ECVT), is readily obtained. The performance of the system was evaluated using artificial test signals as well as real HR V data. As a time domain approach, the method is simple, fast and robust.