Long-time principal geodesic analysis in director-based dynamics of hybrid mechanical systems

In this article, we investigate an extended version of principal geodesic analysis for the unit sphere S2 and the special orthogonal group SO(3). In contrast to prior work, we address the construction of long-time smooth lifts of possibly non-localized data across branches of the respective logarithm maps. To this end, we pay special attention to certain critical numerical aspects such as singularities and their consequences on the numerical accuracy. Moreover, we apply principal geodesic analysis to investigate the behavior of several mechanical systems that are very rich in dynamics. The examples chosen are computationally modeled by employing a director-based formulation for rigid and flexible mechanical systems. Such a formulation allows to investigate our algorithms in a direct manner while avoiding the introduction of additional sources of error that are unrelated to principal geodesic analysis. Finally, we test our numerical machinery with the examples and, at the same time, we gain deeper insight into their dynamical behavior

SABMIS: sparse approximation based blind multi-image steganography scheme

We hide grayscale secret images into a grayscale cover image, which is considered to be a challenging steganography problem. Our goal is to develop a steganography scheme with enhanced embedding capacity while preserving the visual quality of the stegoimage as well as the extracted secret image, and ensuring that the stego-image is resistant to steganographic attacks. The novel embedding rule of our scheme helps to hide secret image sparse coefficients into the oversampled cover image sparse coefficients in a staggered manner. The stego-image is constructed by using the Alternating Direction Method of Multipliers (ADMM) to solve the Least Absolute Shrinkage and Selection Operator (LASSO) formulation of the underlying minimization problem. Finally, the secret images are extracted from the constructed stego-image using the reverse of our embedding rule. Using these components together, to achieve the above mentioned competing goals, forms our most novel contribution. We term our scheme SABMIS (Sparse Approximation Blind Multi-Image Steganography). We perform extensive experiments on several standard images. By choosing the size of the length and the width of the secret images to be half of the length and the width of cover image, respectively, we obtain embedding capacities of 2 bpp (bits per pixel), 4 bpp, 6 bpp, and 8 bpp while embedding one, two, three, and four secret images, respectively. Our focus is on hiding multiple secret images. For the case of hiding two and three secret images, our embedding capacities are higher than all the embedding capacities obtained in the literature until now (3 times and 6 times than the existing best, respectively). For the case of hiding four secret images, although our capacity is slightly lower than one work (about 2/3rd), we do better on the other two goals (quality of stego-image & extracted secret image as well as resistance to steganographic attacks). For our experiments, there is very little deterioration in the quality of the stego-images as compared to their corresponding cover images. Like all other competing works, this is supported visually as well as over 30 dB of Peak Signal-to-Noise Ratio (PSNR) values. The good quality of the stego-images is further validated by multiple numerical measures. None of the existing works perform this exhaustive validation. When using SABMIS, the quality of the extracted secret images is almost same as that of the corresponding original secret images. This aspect is also not demonstrated in all competing literature. SABMIS further improves the security of the inherently steganographic attack resistant transform based schemes. Thus, it is one of the most secure schemes among the existing ones. Additionally, we demonstrate that SABMIS executes in few minutes, and show its application on the real-life problems of securely transmitting medical images over the internet

Computational optimization of gas compressor stations: MINLP models versus continuous reformulations

When considering cost-optimal operation of gas transport networks, compressor stations play the most important role. Proper modeling of these stations leads to nonconvex mixed-integer nonlinear optimization problems. In this article, we give an isothermal and stationary description of compressor stations, state MINLP and GDP models for operating a single station, and discuss several continuous reformulations of the problem. The applicability and relevance of different model formulations, especially of those without discrete variables, is demonstrated by a computational study on both academic examples and real-world instances. In addition, we provide preliminary computational results for an entire network.German Federal Ministry of Economics and Technolog

Algorithmisches Programmieren (Numerische Algorithmen mit C++)

Dieser Kurs führt in die Programmiersprache C++ ein. Es werden die Grundlagen von C++, Kontrollstrukturen, Zahldarstellungen und Datentypen, Funktionen, Zeiger, objekt-orientierte Programmierung, Operatoren und deren Überladung, bishin zu Grundlagen der Vererbung und Klassentemplates, behandelt. Dieses Skriptum ist durch langjährige Erfahrungen der Autoren im Rahmen der gleichnamigen Vorlesung an der Leibniz Universität Hannover entstanden

Exploiting Chordality in Optimization Algorithms for Model Predictive Control

In this chapter we show that chordal structure can be used to devise efficient optimization methods for many common model predictive control problems. The chordal structure is used both for computing search directions efficiently as well as for distributing all the other computations in an interior-point method for solving the problem. The chordal structure can stem both from the sequential nature of the problem as well as from distributed formulations of the problem related to scenario trees or other formulations. The framework enables efficient parallel computations.Comment: arXiv admin note: text overlap with arXiv:1502.0638

Resting-state functional connectivity and reading subskills in children

Individual differences in reading ability have been linked to characteristics of functional connectivity in the brain in both children and adults. However, many previous studies have used single or composite measures of reading, leading to difficulty characterizing the role of functional connectivity in discrete subskills of reading. The present study addresses this issue using resting-state fMRI to examine how resting-state functional connectivity (RSFC) related to individual differences in children\u27s reading subskills, including decoding, sight word reading, reading comprehension, and rapid automatized naming (RAN). Findings showed both positive and negative RSFC-behaviour relationships that diverged across different reading subskills. Positive relationships included increasing RSFC among left dorsal and anterior regions with increasing decoding proficiency, and increasing RSFC between the left thalamus and right fusiform gyrus with increasing sight word reading, RAN, and reading comprehension abilities. In contrast, negative relationships suggested greater functional segregation of attentional and reading networks with improved performance on RAN, decoding, and reading comprehension tasks. Importantly, the results suggest that although reading subskills rely to some extent on shared functional networks, there are also distinct functional connections supporting different components of reading ability in children

Recurrence quantification analysis as a tool for the characterization of molecular dynamics simulations

A molecular dynamics simulation of a Lennard-Jones fluid, and a trajectory of the B1 immunoglobulin G-binding domain of streptococcal protein G (B1-IgG) simulated in water are analyzed by recurrence quantification, which is noteworthy for its independence from stationarity constraints, as well as its ability to detect transients, and both linear and nonlinear state changes. The results demonstrate the sensitivity of the technique for the discrimination of phase sensitive dynamics. Physical interpretation of the recurrence measures is also discussed.Comment: 7 pages, 8 figures, revtex; revised for review for Phys. Rev. E (clarifications and expansion of discussion)-- addition of the 8 postscript figures previously omitted, but unchanged from version

MR imaging of clear cell sarcoma (malignant melanoma of the soft parts): A multicenter correlative MRI-pathology study of 21 cases and literature review

Objective. To evaluate MR imaging and pathology findings in order to define the characteristic features of clear cell sarcoma of the soft tissues (malignant melanoma of the soft parts). Design and patients. MR examinations of 21 patients with histologically proven clear cell sarcoma of the musculoskeletal system were retrospectively reviewed and assessed for shape, homogeneity, delineation, signal intensities on T1- and T2-weighted images, contrast enhancement, relationship with adjacent fascia or tendon, secondary bone involvement, and intratumoral necrosis. In 19 cases the pathology findings were available for review and for a comparative MR-pathology study. Results. On T1-weighted images, lesions were isointense (n=3), hypointense (n=7) or slightly hyperintense to muscle (n=11). Immunohistochemical examination was performed in 17 patients. All 17 specimens showed positivity for HMB-45 antibody. In nine of 11 lesions with slightly increased signal intensity on T1-weighted images, a correlative MR imaging-pathology study was possible. All nine were positive to HMB-45 antibody. Conclusions. Clear cell sarcoma of the musculoskeletal system often has a benign-looking appearance on MR images. In up to 52% of patients, this lesion with melanocytic differentiation has slightly increased signal intensity on T1-weighted images compared with muscle. As the presence of this relative higher signal intensity on T1-weighted images is rather specific for tumors displaying melanocytic differentiation, radiologists should familiarize themselves with this rare entity and include it in their differential diagnosis when confronted with a well- defined, homogeneous, strongly enhancing mass with slightly higher signal intensity compared with muscle on native T1-weighted images