Christian Gruhl

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Computed tomography was used to analyze the patellofemoral relationship during the first 60° of knee flexion in patients with chronic patellofemoral pain syndrome (49 knees) and a healthy control group (15 knees). The patellofemoral joints were imaged axially through the center of the patella articular cartilage with the knee flexed 0°, 0° with maximal(More)
We describe a 14-year-old female gymnast whose complaint was that of chronic low back pain. Radiographs and computed tomograms showed both lumbar manifestations of Scheuermann's disease and an osseous destruction of the S1 vertebral body. We suggest that this is a sacral component of Scheuermann's disease.
After data selection, pre-processing, transformation, and feature extraction, knowledge extraction is not the final step in a data mining process. It is then necessary to understand this knowledge in order to apply it efficiently and effectively. Up to now, there is a lack of appropriate techniques that support this significant step. This is partly due to(More)
Self-adaptive and self-organising (SASO) systems are one promising approach to counter the raising interconnectedness and complexity in technical systems [1]. In particular, decisions about parametrisation, behaviour, and even structure are moved into the responsibility of the systems themselves: from design-time to runtime. This means that hardly all(More)
Hidden Markov Models (HMM) have been used for several years in many time series analysis or pattern recognitions tasks. HMM are often trained by means of the Baum-Welch algorithm which can be seen as a special variant of an expectation maximization (EM) algorithm. Second-order training techniques such as Variational Bayesian Inference (VI) for probabilistic(More)
In this article, we propose CANDIES (Combined Approach for Novelty Detection in Intelligent Embedded Systems), a new approach to novelty detection in technical systems. We assume that in a technical system several processes interact. If we observe these processes with sensors, we are able to model the observations (samples) with a probabilistic model,(More)
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