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The unsolved problem in three-dimensional surgical planning for patients with facial deformity, dysgnathia, or asymmetry is the lack of a normative database of "norm skulls" that can be used as treatment objectives. A study was conducted on 90 Eurasian persons (46 male and 44 female adults) for whom cone beam-computed tomography images were available. Inclusion criteria were adult patients with a skeletal Class I pattern, proper interincisal relationship with normal occlusion, the absence of an open bite both in the anterior and posterior region, and a normal and balanced facial appearance; patients with dysgnathia and malformations were excluded. A total of 18 landmarks were digitized and 3D cephalometric measurements were performed and analyzed by means of proportions calculated from the landmarks. Male and female skulls were analyzed, as well as subdivisions revealed by cluster analysis. The data showed that four subtypes of skulls were distinguishable with statistical significance (p < 0.05). A male and a female type subdivided in a brachiocephalic and dolichocephalic phenotype could be identified. For each type, a mean shape was calculated by a Procrustes transformation, which, in turn, was used to create four template skulls from a male and a female skull. This was accomplished by fitting the polygon models of the two skulls to each of the two subtypes based on the landmarks marked on them using a thin plate spline transformation. The normative data of the subtypes can individually serve as a guide for orthodontic surgery in the Eurasian population, which is especially helpful in 3D planning and the execution of craniofacial operations. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a parsimonious fundamental model for the German day-ahead market. The methodology approximates the supply stack by a piecewise linear function and considers fundamental information, e.g. power plant availabilities, must-run production and cross-border exchange. We reduce complexity by considering technology classes, uncoupled time periods and only one market area. The model accurately reproduces the hourly historical prices and electricity production volumes for most thermal production units in Germany. In a case study, we investigate the effects of the German nuclear phase-out decision. We find an additional price decrease and reduced electricity imports in the counterfactual scenario. • A parsimonious fundamental model with reduced complexity is introduced. • The Model is validated for the German day-ahead market for the years 2011-2015. • The model accurately reproduces German day-ahead spot prices and production volumes. • Case study: German nuclear phase-out decision led to higher prices. • Fossil fired production and additional imports have substituted nuclear production. [ABSTRACT FROM AUTHOR]

A concept for an optomechanical derotator is presented. The derotator allows optical measurements of rotating objects during operation. To guarantee a stationary optical image, the optical axis of the derotator needs to be coaxially aligned to the rotational axis of the measured object. The correlation between the movement of the optical image and a miscalibration is explained by a mathematical model. The movement of the optical image is tracked with a high-speed camera. Approximating the tracked path as a Limacon of Pascal, a parameter corresponding to the magnitude of the miscalibration is identified. This parameter is minimized by modifying the position and the orientation of the derotator with a hexapod. The limitations of this procedure are analyzed and further approaches are discussed. [ABSTRACT FROM AUTHOR]

Abstract: Objective: Mediastinal staging is of paramount importance prior to surgery for non-small-cell lung cancer (NSCLC) to identify patients with N2-disease. Mediastinoscopy remains the gold standard, and sampling from at least three lymph node stations is generally recommended. It is unknown whether biopsy volume has any influence on the result of conventional cervical mediastinoscopy. In this study, we investigated the influence of biopsy volume and the number of lymph node stations biopsied during mediastinoscopy on the probability of demonstrating N2-disease in patients with NSCLC. Methods: We identified 678 consecutive patients who underwent mediastinoscopy for staging of NSCLC during an 8-year period (1999–2007), but 111 patients were later excluded from analysis because of misclassification or of missing data. All patient charts and pathology reports of the remaining 567 patients were reviewed retrospectively. Demographics and the number of lymph node stations biopsied were recorded, and the volume of biopsies from each lymph node station was calculated. Results: Multivariate logistic regression analysis demonstrated that larger biopsy volume was significantly associated with increased probability of demonstrating N2-disease (p < 0.001). However, sampling from several lymph node stations was significantly associated with a decreased probability of demonstrating N2-disease (p = 0.015) and volume was significantly larger per station when fewer stations were sampled (p < 0.001). Conclusions: Biopsy volume from lymph nodes during mediastinoscopy was significantly associated with the probability of demonstrating N2-disease; however, contrary to common belief, sampling from several lymph node stations was not associated with an increased probability of detecting N2-disease. Although purely speculative, these findings may be explained by a perioperative clinical decision by the surgeon: large volumes are secured from macroscopically large and suspicious lymph nodes if detected. Consequently, further dissection and possible complications were avoided. [Copyright &y& Elsevier]

Investigations of machine components are important for a faultless functioning of the machine. Ideally, the components are investigated during operation. Thus, a realistic performance of the machine can be analyzed. However, measurements of fast rotating machine components can be quite challenging especially under bad illumination conditions leading to the necessity of high exposure times. In case high‐speed cameras reach their limits due to motion blur resulting of high exposure times or high velocities, an optomechanical image derotator can still lead to sufficient results. This is due to its operating principle consisting of a rotating reflector assembly inspired by a Abbe‐Koenig‐prism which optically eliminates the rotational movement. To generate a stationary image, the optomechanical image derotator containing the reflector assembly has to rotate exactly half as fast as the rotating object. Therefore, the angular velocity of the object has to be determined. A common way for this is the use of rotary encoders although not every machine can be equipped with such sensors. A flexible solution for this is to identify the angular position and thereby the velocity with a high speed camera capturing images of the rotating object. Using image processing algorithms the marker can be detected and thus the velocity can be calculated from the image data. However, due to high rotational velocities and long exposure times motion blur of the marker can occur. Generally, motion blur can be treated as an artifact since it impedes the image analysis. However, motion blur can be used to determine the velocity of the rotating objects in knowing the shutter speed as well as the length of the streaking of a blurred object. This work presents an approach which determines the rotational velocity from image blur for different velocities. The resulting information will be used as the input source for a velocity control of the derotator. Furthermore it will be discussed whether the velocity information is precise enough to control the derotator leading to a resting image of the rotating object. [ABSTRACT FROM AUTHOR]

Precise alignment of optical components is crucial for the assembly of optical system. Misaligned components (due to positioning tolerances) lead to a distorted wavefront that deviates from a desired wavefront given by an initial nominal design. Inferring the current poses of optical components solely from detector measurements is a difficult but necessary task in order to calculate corrections for feedback control without using external measurement devices. In this paper, we aim at deducing lens poses of a two‐lens system solely from wavefront measurements. The wavefront can be decomposed into a finite sequence of polynomials which are weighted by coefficients. Since pose deviations directly lead to deviations in the wavefront (and therefore in the wavefront coefficients), a sensitivity matrix can be established. The choice of lens poses and wavefront coefficients determines the sensitivity matrix which is often ill‐conditioned and may potentially suffer from rank loss. We conduct a sensitivity analysis and show how the sensitivity matrix can be utilized to generate a linear estimate of the optical component poses. This estimate can then be used to close the feedback loop. Validation is conducted by simulating an optical system consisting of a laser, two bi‐convex lenses, and a wavefront sensor. [ABSTRACT FROM AUTHOR]

This paper presents an active wide-baseline triple-camera measurement system designed especially for 3D modeling in general outdoor environments, as well as a novel parallel surface refinement algorithm within the multi-view stereo (MVS) framework. Firstly, the pre-processing module converts the synchronized raw triple images from one single-shot acquisition of our setup to aligned RGB-Depth frames, which are then used for camera pose estimation using iterative closest point (ICP) and RANSAC perspective-n-point (PnP) approaches. Afterwards, an efficient dense reconstruction method, mostly implemented on the GPU in a grid manner, takes the raw depth data as input and optimizes the per-pixel depth values based on the multi-view photographic evidence, surface curvature and depth priors. Through a basic fusion scheme, an accurate and complete 3D model can be obtained from these enhanced depth maps. For a comprehensive test, the proposed MVS implementation is evaluated on benchmark and synthetic datasets, and a real-world reconstruction experiment is also conducted using our measurement system in an outdoor scenario. The results demonstrate that (1) our MVS method achieves very competitive performance in terms of modeling accuracy, surface completeness and noise reduction, given an input coarse geometry; and (2) despite some limitations, our triple-camera setup in combination with the proposed reconstruction routine, can be applied to some practical 3D modeling tasks operated in outdoor environments where conventional stereo or depth senors would normally suffer. [ABSTRACT FROM AUTHOR]

Abstract: Due to their almost unlimited resolution and fast dynamics, piezoelectric actuators are a common choice for mechatronic systems targeting positioning tasks with high demands on precision. However, these piezoelectric actuators inherently suffer from nonlinear characteristics (mainly hysteresis and creep effects) which need to be addressed by appropriate control strategies. The operator‐based modified Prandtl‐Ishlinksii (mPI) approach does not only model hysteresis effects with asymmetries and creep effects but also provides an analytical solution for its inverse model. Online feedforward compensation of the aforementioned nonlinear effects can be realized by using the inverse model and additional weight adaptation. In this paper, online compensation via the mPI model is applied to a commercial micro‐positioning unit driven by piezoelectric actuators with more than one degree of freedom (DOF). For validation of the proposed approach, two coupled trajectories in the X‐Y plane are utilized. Subsequent tracking error analysis validates the efficacy of the stated approach. (© 2017 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim) [ABSTRACT FROM AUTHOR]

Abstract: In this paper an image‐based control for an optomechanical image derotator is implemented. A derotator is an optical system to support measurements on rotating components by tracking their rotational movement. As a consequence, the position and rotational velocity of the measurement object has to be known continuously. In general this would be accomplished by measuring these variables using a rotary encoder. However, not all measuring objects are equipped for this task. As a solution universally applicable to a wide range of measuring objects, an image‐based approach is developed in the scope of this work. The object is captured with a high‐speed camera to determine its position and velocity by image processing algorithms. To proof the applicability of this concept, a controller using the data acquired with the camera and a controller using data of the rotary encoder are compared. (© 2017 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim) [ABSTRACT FROM AUTHOR]

• A binocular stereo vision sensor is employed to guide the rotation axis alignment for an optomechanical derotator. • An auxiliary laser is introduced to make sure the rotation axis of the object can be measured far from the object. • Axes of both the object and the derotator are estimated in the same coordinate system, which can be used to calculate the misalignment in 4 degrees of freedom (DoF). • Axes are aligned through manual adjustment with the guidance of the real-time updated misalignment information. An image derotator is a device that can compensate the image blur caused by the rotation of an object. However, a key problem when using a derotator is to ensure the coincident alignment between the rotation axes of the derotator and measured object. An approach of machine-vision-guided rotation axis alignment is proposed in this paper. Circular markers and a laser dot are deployed to indicate the rotation axes of the derotator and object, respectively. A binocular stereo sensor is established to estimate the poses of both axes. With the misalignment information between the two axes updated in real-time, axis alignment can be achieved through manual adjustment. The validity and precision of the proposed approach are demonstrated through experiments. [ABSTRACT FROM AUTHOR]

In this paper an optomechatronical image derotator is used for vibration measurements on rotating objects. First of all, the concept of the derotator is explained and it is shown that the phase position and the rotational velocity of the derotator and the measurement object have to be aligned. Therefore, a highly dynamic tracking-control is needed. Considering the nonlinear friction of the synchronous motor, a model of the system which considers this non-linearity is evolved. This is accomplished by using neural networks for the approximation of the friction term. In this case General Regression Neural Networks (GRNN) are used for the learning algorithm. Moreover, the system's parameters, eg. the friction term and the inertia, are identified based on the nonlinear model. Then a feedback control is designed by using the controllable canonical form through feedback linearization. Finally, the results of vibration measurements on a rotating blisk using the nonlinear control concept for the derotator are shown. (© 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim) [ABSTRACT FROM AUTHOR]