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  • 2015-2019  (670)
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  • 201
    Publication Date: 2022-07-19
    Description: In 2004, a team of researchers realized a semi-immersive interactive gallery installation, visualizing an 1834 Mediterranean garden, introduced as “italienisches Kunststück” (Italian legerdemain) by Peter Joseph Lenné. The park was originally realized on the grounds of Schloss Sanssouci in Potsdam, Germany. The installation centered on highly detailed renderings of hundreds of plants projected upon a panoramic display. Interactivity was expressed with a tangible interface which (while presently dated) we believe remains without near-precedent then or since. We present the installation (experienced by roughly 20,000 visitors), focusing on the interaction aspects. We introduce new book and table/door-format mockups. Drawing upon a heuristic of the scientist-philosopher Freeman Dyson, we consider grounded future prospect variations in the contexts of 2018, 2032, and 2202. We see this exercise as prospectively generalizing to a variety of similar and widely diverse application domains.
    Language: English
    Type: conferenceobject , doc-type:conferenceObject
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  • 202
    Publication Date: 2022-07-19
    Description: Haie und Rochen sind die einzigen Wirbeltiere, die sich durch ein Knorpelskelett auszeichnen, das mit winzigen mineralisierten Elementen bedeckt ist, die sogenannten Tesserae. Obwohl dieser mineralisierte Knorpel seit hunderten von Millionen Jahren ein charakteristisches Merkmal dieser Tiere ist, ist der funktionelle Vorteil dieses Gewebestruktur bisher unklar geblieben. In dieser Masterarbeit wird diese Struktur mithilfe der Finite-Elemente-Methode(FEM) untersucht, wobei biologische Informationen zu den Muskeln und der geometrischen Gegebenheiten aus einem hochaufgelösten, kontrastgefärbten μCT-Scan einer Stechrochenhyomandibula verwendet werden. Für die Analyse werden Computer-Aided-Design(CAD)-Modelle und FE-Modelle konstruiert sowie vorhandene Methoden erweitert, um bei den Berechnungen die Charakteristika des biologischen Objektes bestmöglich zu berücksichtigen. Die Modelle bauen auf einer Segmentierung der Hyomandibula auf, wobei die mehreren tausend Tesserae in diesem Datensatz bereits voneinander isoliert sind. Für die Modellierung der Hyomandibula wird als erstes ein CAD-Modell konstruiert. Bei dieser Konstruktion wird eine Tesserae-Mittelfläche erstellt und im Anschluss nach innen und außen verschoben. Der nächste Schritt basiert auf dem Einbau von Zwischenwänden, die die Tesserae voneinander separieren. Auf Grundlage dieses Modells wird ein Tetraedergitter generiert, das die Basis für den zweiten Teil dieser Arbeit darstellt - die Berechnungen mit der FEM. Die wesentliche Aufgabe des zweiten Teils beinhaltet die Konstruktion eines FE-Modells, das in die lineare FEM einzuordnen ist. In dieses fließen die Randbedingungen und die Materialeigenschaften des Skelettelements ein. Mithilfe der FEM lassen sich die durch Krafteinwirkung auftretenden Verschiebungen und Spannungen der Hyomandibula ermitteln. Die Ergebnisse geben Rückschlüsse über das Verhalten des Materials, die Besonderheiten der Geometrie und damit über die Stabilität des Objektes. Der dritte Teil der Abschlussarbeit beschäftigt sich mit zusätzlichen Anpassungen und Änderungen der Modelle (CAD-Modell und FE-Modell), um diese Resultate mit dem Modell zu vergleichen, das der Biologie am nächsten kommt. Diese Anpassungen beinhalten das Variieren der Dicke der mineralisierten Schicht, die Konstellation des Materials und den Abstand zwischen den Tesserae. Die Ergebnisse zeigen, dass sowohl die Tesserae-Struktur als auch die zwischen den Tesserae liegenden Kollagenfasern vermutlich keinen Einfluss auf die Mechanik und dementsprechend die Stabilität haben. Jedoch lassen die unterschiedlichen Resultate im Fall verschieden gewählter Tesserae-Dicken annehmen, dass diese sehr wohl einen Einfluss besitzen.
    Description: Sharks and rays are the only vertebrates characterized by a peculiar cartilage skeleton covered with minute mineralized tiles called tesserae. Although this tessellated cartilage has been a defining feature of this lineage for hundreds of millions of years, the functional advantage of this tissue design has remained obscure. In this Master’s thesis, the finite element method (FEM) is used to investigate the role of tiling in the skeleton, using biological information on the muscles and shape from a high-resolution, contrast-stained μCT-scan of a stingray hyomandibula. For this purpose, computer aided design (CAD) models and FE models are constructed and existing methods will be extended to take the best possible account of the characteristics of the biological object. The analysis builds from a segmentation of the hyomandibula, with the dataset’s several thousand tesserae pre-isolated from one another. For the modeling of the hyomandibula a CAD model is constructed. In this construction, a medial surface is created using the tesserae which is subsequently moved to the inside and outside. The next step is to integrate partition walls separating the tesserae elements. Based on this model, a tetrahedral grid is then generated, which is the content of the second part of this thesis, the calculation with the FEM. A finite element model is constructed including boundary conditions and material properties of the skeletal element to compute the results using the linear FEM theory. The FEM is used to determine the displacements and stresses resulting from biological forces acting on the hyomandibula. The results allow conclusions of the material behavior, geometric characteristics (tesselation) and therefore the object stability. Important contributions of this thesis are additional adjustments and changes to the models (CAD model and FE model) to make it more appropriate to study the biological data at hand. The tesserae thickness, the length of the collagenious fibres and the constellation of the material are the parameters, which are changed. In contrast to the tesserae thicknesses, the results suggest that both the arrangement of the tesserae and its interposed collagen fibers have no substantial influence on the mechanics.
    Language: German
    Type: masterthesis , doc-type:masterThesis
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  • 203
    Publication Date: 2022-07-19
    Description: In this thesis we investigate the task of automatically detecting phases in surgical workflow in endoscopic video data. For this, we employ deep learning approaches that solely rely on frame-wise visual information, instead of using additional signals or handcrafted features. While previous work has mainly focused on tool presence and temporal information for this task, we reason that additional global information about the context of a frame might benefit the phase detection task. We propose novel deep learning architectures: a convolutional neural network (CNN) based model for the tool detection task only, called Clf-Net, as well as a model which performs joint (context) feature learning and tool classification to incorporate information about the context, which we name Context-Clf-Net. For the phase detection task lower-dimensional feature vectors are extracted, which are used as input to recurrent neural networks in order to enforce temporal constraints. We compare the performance of an online model, which only considers previous frames up to the current time step, to that of an offline model that has access to past and future information. Experimental results indicate that the tool detection task benefits strongly from the introduction of context information, as we outperform both Clf-Net results and stateof-the-art methods. Regarding the phase detection task our results do not surpass state-of-the-art methods. Furthermore, no improvement of using features learned by the Context-Clf-Net is observed in the phase detection task for both online and offline versions
    Language: English
    Type: masterthesis , doc-type:masterThesis
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  • 204
    Publication Date: 2022-07-19
    Description: Die Auswertungen der großen Datenmengen moderner bildgebender Verfahren der ZfP können manuell kaum noch bewältigt werden. Hochauflösende 3D-CT-Aufnahmen bestehen oft aus über 1000 Schichtbildern mit einer Datenmenge von mehreren Gigabytes. Aktuelle Computer können diese zwar problemlos visualisieren und erlauben somit eine visuelle Inspektion, aber die möglichst vollständige Erkennung bestimmter Merkmale in den Daten und deren qualitative wie quantitative Auswertung ist durch Experten manuell nicht mehr zu bewältigen. Das gilt insbesondere im Kontext der Schadensaufklärung für die quantitative Analyse verschiedenartig induzierter Risse in Betonen (z.B. durch mechanische Belastungen sowie Frost, Sulfat und Alkali-Kieselsäure-Reaktion). Eine dazu notwendige Segmentierung und Merkmalserkennung kann nur automatisch durchgeführt werden. Dabei ergibt sich (auch fast automatisch) die Frage nach der Verlässlichkeit der verwendeten Algorithmen. Inwieweit kann man davon ausgehen, dass alle gesuchten Merkmale auch tatsächlich gefunden worden sind? Sind die gefundenen Merkmale quantitativ auswertbar und wie wirken sich Parameteränderungen auf die Ergebnisse aus? Sollten immer dieselben, einmal mit gutem Ergebnis angewandten, Parameter auch bei anderen Proben zur besseren Vergleichbarkeit genutzt werden? Anhand eines Risserkennungsalgorithmus basierend auf Formerkennung und Bildverarbeitung wird die Problematik diskutiert. Als Grundlage zur Bewertung des Ansatzes dienen 3D-CT-Aufnahmen von geschädigten Betonprobekörpern und Datensätze, in denen sich aufgrund ihres homogenen Aufbaus mit einfachen Mitteln Risse sicher und eindeutig erkennen lassen. Zur Auswertung der erkannten Risse gehört auch deren Einbettung in das umliegende Material. Das erfordert neben einer automatischen Risserkennung auch eine Segmentierung des gesamten Probekörpers in Zementsteinmatrix, Gesteinskörnung und Porenraum. Da eine solche Segmentierung aufgrund der Datenmenge nur schwer manuell erfolgen kann, werden erste Ergebnisse aus einer Segmentierung mit Hilfe selbstlernender Convolutional Neural Networks gezeigt.
    Language: German
    Type: conferenceobject , doc-type:conferenceObject
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  • 205
    Publication Date: 2022-07-19
    Description: Mitotic and meiotic spindles are microtubule-based structures to faithfully segregate chromosomes. Electron tomography is currently the method of choice to analyze the three-dimensional (3D) architecture of both types of spindles. Over the years, we have developed methods and software for automatic segmentation and stitching of microtubules in serial sections for large-scale reconstructions. 3D reconstruction of microtubules, however, is only the first step toward biological insight. The second step is the analysis of the structural data to derive measurable spindle properties. Here, we present a comprehensive set of techniques to quantify spindle parameters. These techniques provide quantitative analyses of specific microtubule classes and are applicable to a variety of tomographic reconstructions of spindles from different organisms.
    Language: English
    Type: bookpart , doc-type:bookPart
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  • 206
    Publication Date: 2022-07-19
    Description: The void space of granular materials is generally divided into larger local volumes denoted as pores and throats connecting pores. The smallest section in a throat is usually denoted as constriction. A correct description of pores and constrictions may help to understand the processes related to the transport of fluid or fine particles through granular materials, or to build models of imbibition for unsaturated granular media. In the case of numerical granular materials involving packings of spheres, different methods can be used to compute the pore space properties. However, these methods generally induce an over-segmentation of the pore network and a merging step is usually applied to mitigate such undesirable artifacts even if a precise delineation of a pore is somewhat subjective. This study provides a comparison between different merging criteria for pores in packing of spheres and a discussion about their implication on both the pore size distribution and the constriction size distribution of the material. A correspondence between these merging techniques is eventually proposed as a guide for the user.
    Language: English
    Type: reportzib , doc-type:preprint
    Format: application/pdf
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  • 207
    Publication Date: 2022-07-19
    Description: In oocytes of many organisms, meiotic spindles form in the absence of centrosomes [1–5]. Such female meiotic spindles have a pointed appearance in metaphase with microtubules focused at acentrosomal spindle poles. At anaphase, the microtubules of acentrosomal spindles then transition to an inter- chromosomal array, while the spindle poles disappear. This transition is currently not understood. Previous studies have focused on this inter- chromosomal microtubule array and proposed a pushing model to drive chromosome segregation [6, 7]. This model includes an end-on orientation of microtubules with chromosomes. Alternatively, chromosomes were thought to associate along bundles of microtubules [8, 9]. Starting with metaphase, this second model proposed a pure lateral chromosome-to-microtubule association up to the final meiotic stages of anaphase. Here we applied large-scale electron tomography [10] of staged C. elegans oocytes in meiosis to analyze the orientation of microtubules in respect to chromosomes. We show that microtubules at metaphase I are primarily oriented laterally to the chromosomes and that microtubules switch to an end-on orientation during progression through anaphase. We further show that this switch in microtubule orientation involves a kinesin-13 microtubule depolymerase, KLP-7, which removes laterally associated microtubules around chromosomes. From this we conclude that both lateral and end-on modes of microtubule-to-chromosome orientations are successively used in C. elegans oocytes to segregate meiotic chromosomes.
    Language: English
    Type: article , doc-type:article
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  • 208
    Publication Date: 2022-07-19
    Description: In oocytes of many organisms, meiotic spindles form in the absence of centrosomes [1–5]. Such female meiotic spindles have a pointed appearance in metaphase with microtubules focused at acentrosomal spindle poles. At anaphase, the microtubules of acentrosomal spindles then transition to an inter- chromosomal array, while the spindle poles disappear. This transition is currently not understood. Previous studies have focused on this inter- chromosomal microtubule array and proposed a pushing model to drive chromosome segregation [6, 7]. This model includes an end-on orientation of microtubules with chromosomes. Alternatively, chromosomes were thought to associate along bundles of microtubules [8, 9]. Starting with metaphase, this second model proposed a pure lateral chromosome-to-microtubule association up to the final meiotic stages of anaphase. Here we applied large-scale electron tomography [10] of staged C. elegans oocytes in meiosis to analyze the orientation of microtubules in respect to chromosomes. We show that microtubules at metaphase I are primarily oriented laterally to the chromosomes and that microtubules switch to an end-on orientation during progression through anaphase. We further show that this switch in microtubule orientation involves a kinesin-13 microtubule depolymerase, KLP-7, which removes laterally associated microtubules around chromosomes. From this we conclude that both lateral and end-on modes of microtubule-to-chromosome orientations are successively used in C. elegans oocytes to segregate meiotic chromosomes.
    Language: English
    Type: reportzib , doc-type:preprint
    Format: application/pdf
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  • 209
    Publication Date: 2022-07-19
    Description: A great amount of material properties is strongly influenced by dislocations, the carriers of plastic deformation. It is therefore paramount to have appropriate tools to quantify dislocation substructures with regard to their features, e.g., dislocation density, Burgers vectors or line direction. While the transmission electron microscope (TEM) has been the most widely-used equipment implemented to investigate dislocations, it usually is limited to the two-dimensional (2D) observation of three-dimensional (3D) structures. We reconstruct, visualize and quantify 3D dislocation substructure models from only two TEM images (stereo-pairs) and assess the results. The reconstruction is based on the manual interactive tracing of filiform objects on both images of the stereo-pair. The reconstruction and quantification method are demonstrated on dark field (DF) scanning (S)TEM micrographs of dislocation substructures imaged under diffraction contrast conditions. For this purpose, thick regions (〉 300 nm) of TEM foils are analyzed, which are extracted from a Ni-base superalloy single crystal after high temperature creep deformation. It is shown how the method allows 3D quantification from stereo-pairs in a wide range of tilt conditions, achieving line length and orientation uncertainties of 3 % and 7°, respectively. Parameters that affect the quality of such reconstructions are discussed.
    Language: English
    Type: reportzib , doc-type:preprint
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  • 210
    Publication Date: 2022-07-19
    Description: A great amount of material properties is strongly influenced by dislocations, the carriers of plastic deformation. It is therefore paramount to have appropriate tools to quantify dislocation substructures with regard to their features, e.g., dislocation density, Burgers vectors or line direction. While the transmission electron microscope (TEM) has been the most widely-used equipment implemented to investigate dislocations, it usually is limited to the two-dimensional (2D) observation of three-dimensional (3D) structures. We reconstruct, visualize and quantify 3D dislocation substructure models from only two TEM images (stereo pairs) and assess the results. The reconstruction is based on the manual interactive tracing of filiform objects on both images of the stereo pair. The reconstruction and quantification method are demonstrated on dark field (DF) scanning (S)TEM micrographs of dislocation substructures imaged under diffraction contrast conditions. For this purpose, thick regions (〉300 nm) of TEM foils are analyzed, which are extracted from a Ni-base superalloy single crystal after high temperature creep deformation. It is shown how the method allows 3D quantification from stereo pairs in a wide range of tilt conditions, achieving line length and orientation uncertainties of 3% and 7°, respectively. Parameters that affect the quality of such reconstructions are discussed.
    Language: English
    Type: article , doc-type:article
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  • 211
    Publication Date: 2022-07-19
    Language: English
    Type: masterthesis , doc-type:masterThesis
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  • 212
    Publication Date: 2022-07-19
    Description: We show how biologically coherent mesh models of animals can be created from μCT data to generate artificial yet naturally looking intermediate objects. The whole pipeline of processing algorithms is presented, starting from generating topologically equivalent surface meshes, followed by solving the correspondence problem, and, finally, creating a surface morphing. In this pipeline, we address all the challenges that are due to dealing with complex biological, non-isometric objects. For biological objects it is often particularly important to obtain deformations that look as realistic as possible. In addition, spatially non-uniform shape morphings that only change one part of the surface and keep the rest as stable as possible are of interest for evolutionary studies, since functional modules often change independently from one another. We use Poisson interpolation for this purpose and show that it is well suited to generate both global and local shape deformations.
    Language: English
    Type: conferenceobject , doc-type:conferenceObject
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  • 213
    Publication Date: 2022-07-19
    Language: English
    Type: reportzib , doc-type:preprint
    Format: application/pdf
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  • 214
    Publication Date: 2022-07-19
    Description: We show how biologically coherent mesh models of animals can be created from μCT data to generate artificial yet naturally looking intermediate objects. The whole pipeline of processing algorithms is presented, starting from generating topologically equivalent surface meshes, followed by solving the correspondence problem, and, finally, creating a surface morphing. In this pipeline, we address all the challenges that are due to dealing with complex biological, non-isometric objects. For biological objects it is often particularly important to obtain deformations that look as realistic as possible. In addition, spatially non-uniform shape morphings that only change one part of the surface and keep the rest as stable as possible are of interest for evolutionary studies, since functional modules often change independently from one another. We use Poisson interpolation for this purpose and show that it is well suited to generate both global and local shape deformations.
    Language: English
    Type: reportzib , doc-type:preprint
    Format: application/pdf
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  • 215
    Publication Date: 2022-07-19
    Description: Acetabular bone defects are still challenging to quantify. Numerous classification schemes have been proposed to categorize the diverse kinds of defects. However, these classification schemes are mainly descriptive and hence it remains difficult to apply them in pre-clinical testing, implant development and pre-operative planning. By reconstructing the native situation of a defect pelvis using a Statistical Shape Model (SSM), a more quantitative analysis of the bone defects could be performed. The aim of this study is to develop such a SSM and to validate its accuracy using relevant clinical scenarios and parameters.
    Language: English
    Type: article , doc-type:article
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  • 216
    Publication Date: 2022-07-19
    Description: The transition mechanism of jump processes between two different subsets in state space reveals important dynamical information of the processes and therefore has attracted considerable attention in the past years. In this paper, we study the first passage path ensemble of both discrete-time and continuous-time jump processes on a finite state space. The main approach is to divide each first passage path into nonreactive and reactive segments and to study them separately. The analysis can be applied to jump processes which are non-ergodic, as well as continuous-time jump processes where the waiting time distributions are non-exponential. In the particular case that the jump processes are both Markovian and ergodic, our analysis elucidates the relations between the study of the first passage paths and the study of the transition paths in transition path theory. We provide algorithms to numerically compute statistics of the first passage path ensemble. The computational complexity of these algorithms scales with the complexity of solving a linear system, for which efficient methods are available. Several examples demonstrate the wide applicability of the derived results across research areas.
    Language: English
    Type: article , doc-type:article
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  • 217
    Publication Date: 2022-07-19
    Description: Changes in knee shape and geometry resulting from total knee arthroplasty can affect patients in numerous important ways: pain, function, stability, range of motion, and kinematics. Quantitative data concerning these changes have not been previously available, to our knowledge, yet are essential to understand individual experiences of total knee arthroplasty and thereby improve outcomes for all patients. The limiting factor has been the challenge of accurately measuring these changes. Our study objective was to develop a conceptual framework and analysis method to investigate changes in knee shape and geometry, and prospectively apply it to a sample total knee arthroplasty population. Using clinically available computed tomography and radiography imaging systems, the three-dimensional knee shape and geometry of nine patients (eight varus and one valgus) were compared before and after total knee arthroplasty. All patients had largely good outcomes after their total knee arthroplasty. Knee shape changed both visually and numerically. On average, the distal condyles were slightly higher medially and lower laterally (range: +4.5 mm to −4.4 mm), the posterior condyles extended farther out medially but not laterally (range: +1.8 to −6.4 mm), patellofemoral distance increased throughout flexion by 1.8–3.5 mm, and patellar thickness alone increased by 2.9 mm (range: 0.7–5.2 mm). External femoral rotation differed preop and postop. Joint line distance, taking cartilage into account, changed by +0.7 to −1.5 mm on average throughout flexion. Important differences in shape and geometry were seen between pre-total knee arthroplasty and post-total knee arthroplasty knees. While this is qualitatively known, this is the first study to report it quantitatively, an important precursor to identifying the reasons for the poor outcome of some patients. Using the developed protocol and visualization techniques to compare patients with good versus poor clinical outcomes could lead to changes in implant design, implant selection, component positioning, and surgical technique. Recommendations based on this sample population are provided. Intraoperative and postoperative feedback could ultimately improve patient satisfaction.
    Language: English
    Type: article , doc-type:article
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  • 218
    Publication Date: 2022-07-19
    Description: Comets display with decreasing solar distance an increased emission of gas and dust particles, leading to the formation of the coma and tail. Spacecraft missions provide insight in the temporal and spatial variations of the dust and gas sources located on the cometary nucleus. For the case of comet 67P/Churyumov-Gerasimenko (67P/C-G), the long-term obser- vations from the Rosetta mission point to a homogeneous dust emission across the entire illuminated surface. Despite the homogeneous initial dis- tribution, a collimation in jet-like structures becomes visible. We propose that this observation is linked directly to the complex shape of the nucleus and projects concave topographical features into the dust coma. To test this hypothesis, we put forward a gas-dust description of 67P/C-G, where gravitational and gas forces are accurately determined from the surface mesh and the rotation of the nucleus is fully incorporated. The emerging jet-like structures persist for a wide range of gas-dust interactions and show a dust velocity dependent bending.
    Language: English
    Type: article , doc-type:article
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  • 219
    Publication Date: 2022-07-19
    Description: Here, we report on different types of shell pathologies of the enigmatic deep-sea (mesopelagic) cephalopod Spirula spirula. For the first time, we apply non-invasive imaging methods to: document trauma-induced changes in shell shapes, reconstruct the different causes and effects of these pathologies, unravel the etiology, and attempt to quantify the efficiency of the buoyancy apparatus. We have analysed 2D and 3D shell parameters from eleven shells collected as beach findings from the Canary Islands (Gran Canaria and Fuerteventura), West-Australia, and the Maldives. All shells were scanned with a nanotom-m computer tomograph. Seven shells were likely injured by predator attacks: fishes, cephalopods or crustaceans, one specimen was infested by an endoparasite (potentially Digenea) and one shell shows signs of inflammation and one shell shows large fluctuations of chamber volumes without any signs of pathology. These fluctuations are potential indicators of a stressed environment. Pathological shells represent the most deviant morphologies of a single species and can therefore be regarded as morphological end-members. The changes in the shell volume / chamber volume ratio were assessed in order to evaluate the functional tolerance of the buoyancy apparatus showing that these had little effect.
    Language: English
    Type: article , doc-type:article
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  • 220
    Publication Date: 2023-01-06
    Language: English
    Type: article , doc-type:article
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  • 221
    Publication Date: 2022-12-12
    Description: The Vienna Ab initio Simulation Package (VASP) is a widely used electronic structure code that originally exploits process-level parallelism through the Message Passing Interface (MPI) for work distribution within and across nodes. Architectural changes of modern parallel processors urge programmers to address thread- and data-level parallelism as well to benefit most from the available compute resources within a node. We describe for VASP how to approach for an MPI + OpenMP parallelization including data-level parallelism through OpenMP SIMD constructs together with a generic high-level vector coding scheme. We can demonstrate an improved scalability of VASP and more than 20% gain over the MPI-only version, as well as a 2x increased performance of collective operations using the multiple-endpoint MPI feature. The high-level vector coding scheme applied to VASP's general gradient approximation routine gives up 9x performance gain on AVX512 platforms with the Intel compiler.
    Language: English
    Type: article , doc-type:article
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  • 222
    Publication Date: 2023-02-06
    Description: Packing rings into a minimum number of rectangles is an optimization problem which appears naturally in the logistics operations of the tube industry. It encompasses two major difficulties, namely the positioning of rings in rectangles and the recursive packing of rings into other rings. This problem is known as the Recursive Circle Packing Problem (RCPP). We present the first dedicated method for solving RCPP that provides strong dual bounds based on an exact Dantzig–Wolfe reformulation of a nonconvex mixed-integer nonlinear programming formulation. The key idea of this reformulation is to break symmetry on each recursion level by enumerating one-level packings, i.e., packings of circles into other circles, and by dynamically generating packings of circles into rectangles. We use column generation techniques to design a “price-and-verify” algorithm that solves this reformulation to global optimality. Extensive computational experiments on a large test set show that our method not only computes tight dual bounds, but often produces primal solutions better than those computed by heuristics from the literature.
    Language: English
    Type: article , doc-type:article
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  • 223
    Publication Date: 2023-03-20
    Description: Forecasting natural gas demand and supply is essential for an efficient operation of the German gas distribution system and a basis for the operational decisions of the transmission system operators. The German gas market is moving towards more short-term planning, in particular, day-ahead contracts. This increases the difficulty that the operators in the dispatching centre are facing, as well as the necessity of accurate forecasts. This paper presents a novel predictive model that provides day-ahead forecasts of the high resolution gas flow by developing a Functional AutoRegressive model with eXogenous variables (FARX). The predictive model allows the dynamic patterns of hourly gas flows to be described in a wide range of historical profiles, while also taking the relevant determinants data into account. By taking into account a richer set of information, FARX provides stronger performance in real data analysis, with both accuracy and high computational efficiency. Compared to several alternative models in out-of-sample forecasts, the proposed model can improve forecast accuracy by at least 12% and up to 5-fold for one node, 3% to 2-fold and 2-fold to 4-fold for the other two nodes. The results show that lagged 1-day gas flow and nominations are important predictors, and with their presence in the forecast model, temperature becomes insignificant for short-term predictions.
    Language: English
    Type: article , doc-type:article
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  • 224
    Publication Date: 2023-03-31
    Description: We present a concept that provides an efficient description of differential-algebraic equations (DAEs) describing flow networks which provides the DAE function f and their Jacobians in an automatized way such that the sparsity pattern of the Jacobians is determined before their evaluation and previously determined values of f can be exploited. The user only has to provide the network topology and local function descriptions for each network element. The approach uses automatic differentiation (AD) and is adapted to switching element functions via the abs-normal-form (ANF).
    Language: English
    Type: conferenceobject , doc-type:conferenceObject
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  • 225
    Publication Date: 2023-03-31
    Description: Recent research has shown that piecewise smooth (PS) functions can be approximated by piecewise linear functions with second order error in the distance to a given reference point. A semismooth Newton type algorithm based on successive application of these piecewise linearizations was subsequently developed for the solution of PS equation systems. For local bijectivity of the linearization at a root, a radius of quadratic convergence was explicitly calculated in terms of local Lipschitz constants of the underlying PS function. In the present work we relax the criterium of local bijectivity of the linearization to local openness. For this purpose a weak implicit function theorem is proved via local mapping degree theory. It is shown that there exist PS functions f:IR^2 --〉 IR^2 satisfying the weaker criterium where every neighborhood of the root of f contains a point x such that all elements of the Clarke Jacobian at x are singular. In such neighborhoods the steps of classical semismooth Newton are not defined, which establishes the new method as an independent algorithm. To further clarify the relation between a PS function and its piecewise linearization, several statements about structure correspondences between the two are proved. Moreover, the influence of the specific representation of the local piecewise linear models on the robustness of our method is studied. An example application from cardiovascular mathematics is given.
    Language: English
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  • 226
    Publication Date: 2023-03-31
    Description: In this article we analyze a generalized trapezoidal rule for initial value problems with piecewise smooth right hand side F:IR^n -〉 IR^n. When applied to such a problem, the classical trapezoidal rule suffers from a loss of accuracy if the solution trajectory intersects a non-differentiability of F. In such a situation the investigated generalized trapezoidal rule achieves a higher convergence order than the classical method. While the asymptotic behavior of the generalized method was investigated in a previous work, in the present article we develop the algorithmic structure for efficient implementation strategies and estimate the actual computational cost of the latter. Moreover, energy preservation of the generalized trapezoidal rule is proved for Hamiltonian systems with piecewise linear right hand side.
    Language: English
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  • 227
    Publication Date: 2023-03-31
    Description: We present an extension of Taylor’s theorem towards nonsmooth evalua- tion procedures incorporating absolute value operaions. Evaluations procedures are computer programs of mathematical functions in closed form expression and al- low a different treatment of smooth operations and calls to the absolute value value function. The well known classical Theorem of Taylor defines polynomial approx- imation of sufficiently smooth functions and is widely used for the derivation and analysis of numerical integrators for systems of ordinary differential or differential algebraic equations, for the construction of solvers for the continuous nonlinear op- timization of finite dimensional objective functions and for root solving of nonlinear systems of equations. The herein provided proof is construtive and allow efficiently designed algorithms for the execution and computation of generalized piecewise polynomial expansions. As a demonstration we will derive a k-step method on the basis of polynomial interpolation and the proposed generalized expansions.
    Language: English
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  • 228
    Publication Date: 2023-04-17
    Description: Ahierarchical mixed-integer linear programmingmethod has been proposed to solve optimal design problems of energy supply systems efficiently. In this paper, a method of reducing model by clustering periods is proposed to search design solution candidates efficiently in the relaxed optimal design problem at the upper level. This method is realized only by clustering periods and averaging energy demands for clustered periods, while it guarantees to derive the optimal solution. Through acase study on the optimaldesign of a cogeneration system, ti is clarified how the model reduction si effective ot enhance the computation efficiency.
    Language: Japanese
    Type: article , doc-type:article
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  • 229
    Publication Date: 2023-04-17
    Description: A hierarchical mixed-integer linear programming method to solve optimal design problems of energy supply systems efficiently has been proposed. The original problem is solved by dividing it into a relaxed optimal design problem at the upper level and optimal operation problems which are independent of each other at the lower level. In this paper, a method of reducing model by time aggregation is proposed to search design solution candidates efficiently in the relaxed optimal design problem at the upper level. This method is realized only by clustering periods and averaging energy demands for clustered periods, while it guarantees to derive the optimal solution. On one hand, the method may decrease the number of design variables and costraints at the upper level, and thus the computation time at the upper level. On the other hand, it may increase the numbers of generated design solution candidates and solved optimal operation problems, and thus the computation time at both the levels. Though a case study on the optimal design of a cogeneration system, it is clarified how the model reduction is effective to enhance the computation efficiency.
    Language: Japanese
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  • 230
    Publication Date: 2023-04-28
    Description: This chapter explains the different ways in which Markov State Models (MSMs) can be helpful in structure-based drug design. MSMs are constructed from the time series of molecular dynamics (MD), which can be generated by classical MD simulations. Several features of the MSMs can be utilized for rational drug design. The discretization of a validated MSM is particularly suited to extract meaningful representatives from the conformational ensemble, because the discretization yields a small number of microstates and mirrors the features of the free energy landscape. Long-lived conformations consist of a set of microstates which show high transition rates within the set and low transition rates to microstates outside of the set. The Bayesian agglomerative clustering engine (BACE) algorithm uses the observed transition counts to extract long-lived conformations from an MSM. By iteratively merging microstates according to the Bayes factor and recalculating the Bayes-factor matrix, the algorithm yields an aggregation of the microstates into long-lived conformations.
    Language: English
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  • 231
    Publication Date: 2023-04-28
    Description: In recent years, for the analysis of molecular processes, the estimation of time-scales and transition rates has become fundamental. Estimating the transition rates between molecular conformations is—from a mathematical point of view—an invariant subspace projection problem. We present a method to project the infinitesimal generator acting on function space to a low-dimensional rate matrix. This projection can be performed in two steps. First, we discretize the conformational space in a Voronoi tessellation, then the transition rates between adjacent cells is approximated by the geometric average of the Boltzmann weights of the Voronoi cells. This method demonstrates that there is a direct relation between the potential energy surface of molecular structures and the transition rates of conformational changes. We will show also that this approximation is correct and converges to the generator of the Smoluchowski equation in the limit of infinitely small Voronoi cells. We present results for a two dimensional diffusion process and alanine dipeptide as a high-dimensional system.
    Language: English
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  • 232
    Publication Date: 2023-04-28
    Description: We have combined infrared (IR) experiments with molecular dynamics (MD) simulations in solution at finite temperature to analyse the vibrational signature of the small floppy peptide Alanine-Leucine. IR spectra computed from first-principles MD simulations exhibit no distinct differences between conformational clusters of -helix or -sheet-like folds with different orientations of the bulky leucine side chain. All computed spectra show two prominent bands, in good agreement with the experiment, that are assigned to the stretch vibrations of the carbonyl and carboxyl group, respectively. Variations in band widths and exact maxima are likely due to small fluctuations in the backbone torsion angles.
    Language: English
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  • 233
    Publication Date: 2023-04-28
    Description: Metadynamics is a computational method to explore the phase space of a molecular system. Gaussian functions are added along relevant coordinates on the fly during a molecular-dynamics simulation to force the system to escape from minima in the potential energy function. The dynamics in the resulting trajectory are however unphysical and cannot be used directly to estimate dynamical properties of the system. Girsanov reweighting is a recent method used to construct the Markov State Model (MSM) of a system subjected to an external perturbation. With the combination of these two techniques—metadynamics/Girsanov-reweighting—the unphysical dynamics in a metadynamics simulation can be reweighted to obtain the MSM of the unbiased system. We demonstrate the method on a one-dimensional diffusion process, alanine dipeptide, and the hexapeptide Val-Gly-Val-Ala-Pro-Gly (VGVAPG). The results are in excellent agreement with the MSMs obtained from direct unbiased simulations of these systems. We also apply metadynamics/Girsanov-reweighting to a β-hairpin peptide, whose dynamics is too slow to efficiently explore its phase space by direct simulation
    Language: English
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  • 234
    Publication Date: 2023-07-17
    Description: Aim of this thesis was to evaluate the performance of three popular machine learning methods – decision trees, support vector machines, and neural networks – on a supervised image classification task from the domain of cell biology. Specifically, the task was to classify microtubule ends in electron tomography images as open or closed. Microtubules are filamentous macromolecules of the cytoskeleton. Distribution of their end types is of interest to cell biologists as it allows to analyze microtubule nucleation sites. Currently classification is done manually by domain experts, which is a difficult task due to the low signal-to-noise ratio and the abundance of microtubules in a single cell. Automating this tedious and error prone task would be beneficial to both efficiency and consistency. Images of microtubule ends were obtained from electron tomography reconstructions of mitotic spindles. As ground truth data for training and testing four independent expert classifications for the same samples from different tomograms were used. Image information around microtubule ends was extracted in various formats for further processing. For all classifiers we considered how the performance varies when different preprocessing techniques (per-feature and per-image standardization) are applied. or decision trees and support vector machines we also evaluated the effect of training on a) imbalanced versus under- and over-sampled data and b) image-based vs feature-based input for specifically designed features. The results show that for decision trees and support vector machines classification on features outperforms classification on images. Both methods give most equalized per-class accuracies when the training data was undersampled and when preprocessed with per-image standardization prior to features extraction. Neural networks gave the best results when no preprocessing was applied. The final decision tree, support vector machine, and neural network obtained accuracies on the test set for (open,closed ) samples of (62%, 72%), (66%, 70%), and (61%, 78%) respectively, when considering all samples where at least one expert assigned a label. Restricting the test set to samples with at least three agreeing expert labels raised these to (78%, 84%), (74%, 92%), and (82%, 88%). It can be observed that many samples misclassified by the algorithms were also difficult to classify for the experts.
    Language: English
    Type: masterthesis , doc-type:masterThesis
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  • 235
    Publication Date: 2023-07-14
    Description: Optimization models often feature disjunctions of polytopes as submodels. Such a disjunctive set is initially (at best) relaxed to its convex hull, which is then refined by branching. To measure the error of the convex relaxation, the (relative) difference between the volume of the convex hull and the volume of the disjunctive set may be used. This requires a method to compute the volume of the disjunctive set. Naively, this can be done via inclusion/exclusion and leveraging the existing code for the volume of polytopes. However, this is often inefficient. We propose a revised variant of an old algorithm by Bieri and Nef (1983) for this purpose. The algorithm uses a sweep-plane to incrementally calculate the volume of the disjunctive set as a function of the offset parameter of the sweep-plane.
    Language: English
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  • 236
    Publication Date: 2023-07-14
    Description: Das Thema dieser Arbeit ist ein Volumen-Algorithmus für die Vereinigung von Polytopen. Der Algorithmus basiert auf der Arbeit von Bieri und Nef. Er berechnet das Volumen der Vereinigung von Polytopen mit einem Sweep-Verfahren. Dabei wird eine Hyperebene im Raum verschoben und das Volumen auf der einen Seite der Hyperebene berechnet. Umso weiter die Hyperebene verschobe wird, desto größer ist auch der Halbraum. Unser Algorithmus berechnet das Volumen einer Vereinigung von Polytopen geschnitten mit dem Halbraum der Sweep-Ebene als eine Funktion abhängig von der Veschiebung. Ab einem gewissen Punkt liegt der Körper dabei komplett im Halbraum der Sweep-Ebene und das Volumen bleibt konstant. Unser Algorithmus unterscheidet sich in zwei Punkten von dem Algorithmus von Bieri und Nef. Erstens funktioniert er nur auf der Vereinigung von Polytopen, wohingegen der Algorithmus von Bieri und Nef für Nef-Polyeder funktioniert. Diese sind eine Verallgemeinerung von Polyedern, die auch die Klasse der Vereinigung von Polytopen umfasst. Für uns ist das allerdings kein Nachteil, da unsere Datensätze zu Vereinigungen von Polytopen führen. Zweitens ist unser Algorithmus in zwei Teile aufgeteilt. Im ersten Teil wird eine Datenstruktur entwickelt, aus der im zweiten Teil zusammen mit einer Richtung die Sweep-Ebenen-Volumenfunktion berechnet wird. Der Großteil der Komplexität liegt im ersten Teil des Algorithmus. Das hat den Vorteil, dass wir die Volumenfunktionen für viele verschiedene Richtungen berechnen können. So können Einblicke in die Struktur des Körpers gewonnen werden. Der Algorithmus beruht auf zwei verschiedenen Zerlegungsansätzen. Zuerst können wir mit Hilfe von Anordnungen von Hyperebenen eine Vereinigung von Polytopen in ihre Zellen zerlegen. Dabei berufen wir uns auf die Arbeit von Gerstner und Holtz, in der das Konzept der Positionsvektoren eingeführt wird. Diese nutzen wir um die Ecken und ihre benachbarten Zellen zu bestimmen. So erhalten wir eine Zerlegung unserer Vereinigung in Zellen, deren paarweise Schnitte kein Volumen haben. Das zweite Zerlegungskonzept ist die konische Zerlegung, wie sie von Lawrence eingeführt wurde. Mit Hilfe dieser können wir die Indikatorfunktion eines Polytops als die Summe der Indikatorfunktionen seiner Vorwärtskegel schreiben. Die Sweep-Ebenen Volumenfunktionen können dann leicht mit Hilfe einer altbekannten Formel für das Volumen von Simplices berechnet werden.
    Language: English
    Type: masterthesis , doc-type:masterThesis
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  • 237
    Publication Date: 2023-07-17
    Language: English
    Type: article , doc-type:article
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  • 238
    Publication Date: 2023-07-17
    Description: One of the most widely recognized features of biological systems is their modularity. The modules that constitute biological systems are said to be redeployed and combined across several conditions, thus acting as building blocks. In this work, we analyse to what extent are these building blocks reusable as compared with those found in randomized versions of a system. We develop a notion of decompositions of systems into phenotypic building blocks, which allows them to overlap while maximizing the number of times a building block is reused across several conditions. Different biological systems present building blocks whose reusability ranges from single use (e.g. condition specific) to constitutive, although their average reusability is not always higher than random equivalents of the system. These decompositions reveal a distinct distribution of building block sizes in real biological systems. This distribution stems, in part, from the peculiar usage pattern of the elements of biological systems, and constitutes a new angle to study the evolution of modularity.
    Language: English
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  • 239
    Publication Date: 2023-07-17
    Description: Air temperature (Tair or T2m) is an important climatological variable for forest biosphere processes and climate change research. Due to the low density and the uneven distribution of weather stations, traditional ground-based observations cannot accurately capture the spatial distribution of Tair. In this study, Tair in Berlin is estimated during the day and night time over six land cover/land use (LC/LU) types by satellite remote sensing data over a large domain and a relatively long period (7 years). Aqua and Terra MODIS (Moderate Resolution Imaging Spectroradiometer) data and meteorological data for the period from 2007 to 2013 were collected to estimate Tair. Twelve environmental variables (land surface temperature (LST), normalized difference vegetation index (NDVI), Julian day, latitude, longitude, Emissivity31, Emissivity32, altitude, albedo, wind speed, wind direction and air pressure) were selected as predictors. Moreover, a comparison between LST from MODIS Terra and Aqua with daytime and night time air temperatures (Tday, Tnight) was done respectively and in addition, the spatial variability of LST and Tair relationship by applying a varying window size on the MODIS LST grid was examined. An analysis of the relationship between the observed Tair and the spatially averaged remotely sensed LST, indicated that 3 × 3 and 1 × 1 pixel size was the optimal window size for the statistical model estimating Tair from MODIS data during the day and night time, respectively. Three supervised learning methods (Adaptive Neuro Fuzzy Inference system (ANFIS), Artificial Neural Network (ANN) and Support vector machine (SVR)) were used to estimate Tair during the day and night time, and their performances were validated by cross-validation for each LC/LU. Moreover, tuning the hyper parameters of some models like SVR and ANN were investigated. For tuning the hyper parameters of SVR, Simulated Annealing (SA) was applied (SA-SVR model) and a multiple-layer feed-forward (MLF) neural networks with three layers and different nodes in hidden layers are used with Levenber-Marquardt back-propagation (LM-BP), in order to achieve higher accuracy in the estimation of Tair. Results indicated that the ANN model achieved better accuracy (RMSE= 2.16°C, MAE = 1.69°C, R2 = 0.95) than SA_SVR model (RMSE= 2.50°C, MAE = 1.92°C, R2 = 0.91) and ANFIS model (RMSE= 2.88°C, MAE= 2.2°C, R2 = 0.89) over six LC/LU during the day and night time. The Q-Q diagram of SA-SVR, ANFIS and NN show that all three models slightly tended to underestimate and overestimate the extreme and low temperatures for all LC/LU classes during the day and night time. The weak performance in the extreme and low temperatures are a consequence of the small number of data in these temperatures. These satisfactory results indicate that this approach is proper for estimating air temperature and spatial window size is an important factor that should be considered in the estimation of air temperature.
    Language: English
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  • 240
    Publication Date: 2023-07-17
    Description: Studies have shown that the predictive value of “clinical diagnoses” of influenza and other respiratory viral infections is low, especially in children. In routine care, pediatricians often resort to clinical diagnoses, even in the absence of robust evidence‐based criteria. We used a dual approach to identify clinical characteristics that may help to differentiate infections with common pathogens including influenza, respiratory syncytial virus, adenovirus, metapneumovirus, rhinovirus, bocavirus‐1, coronaviruses, or parainfluenza virus: (a) systematic review and meta‐analysis of 47 clinical studies published in Medline (June 1996 to March 2017, PROSPERO registration number: CRD42017059557) comprising 49 858 individuals and (b) data‐driven analysis of an inception cohort of 6073 children with ILI (aged 0‐18 years, 56% male, December 2009 to March 2015) examined at the point of care in addition to blinded PCR testing. We determined pooled odds ratios for the literature analysis and compared these to odds ratios based on the clinical cohort dataset. This combined analysis suggested significant associations between influenza and fever or headache, as well as between respiratory syncytial virus infection and cough, dyspnea, and wheezing. Similarly, literature and cohort data agreed on significant associations between HMPV infection and cough, as well as adenovirus infection and fever. Importantly, none of the abovementioned features were unique to any particular pathogen but were also observed in association with other respiratory viruses. In summary, our “real‐world” dataset confirmed published literature trends, but no individual feature allows any particular type of viral infection to be ruled in or ruled out. For the time being, laboratory confirmation remains essential. More research is needed to develop scientifically validated decision models to inform best practice guidelines and targeted diagnostic algorithms.
    Language: English
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  • 241
    Publication Date: 2023-07-17
    Language: English
    Type: masterthesis , doc-type:masterThesis
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  • 242
  • 243
    Publication Date: 2023-07-17
    Language: English
    Type: article , doc-type:article
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  • 244
  • 245
  • 246
    Publication Date: 2023-11-03
    Language: English
    Type: article , doc-type:article
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  • 247
    Publication Date: 2023-11-03
    Description: Due to very short T2 relaxation times, imaging of tendons is typically performed using ultra-short echo-time (UTE) acquisition techniques. In this work, we combined an echo-train shifted multi-echo 3D UTE imaging sequence with a 3D curved surface reconstruction to virtually extract the patellar tendon from an acquired 3D UTE dataset. Based on the analysis of the acquired multi-echo data, a T2* relaxation time parameter map was calculated and interpolated to the curved surface of the patellar tendon.
    Language: English
    Type: conferenceobject , doc-type:conferenceObject
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  • 248
    Publication Date: 2023-11-03
    Description: Markov state models (MSMs) have received an unabated increase in popularity in recent years, as they are very well suited for the identification and analysis of metastable states and related kinetics. However, the state-of-the-art Markov state modeling methods and tools enforce the fulfillment of a detailed balance condition, restricting their applicability to equilibrium MSMs. To date, they are unsuitable to deal with general dominant data structures including cyclic processes, which are essentially associated with nonequilibrium systems. To overcome this limitation, we developed a generalization of the common robust Perron Cluster Cluster Analysis (PCCA+) method, termed generalized PCCA (G-PCCA). This method handles equilibrium and nonequilibrium simulation data, utilizing Schur vectors instead of eigenvectors. G-PCCA is not limited to the detection of metastable states but enables the identification of dominant structures in a general sense, unraveling cyclic processes. This is exemplified by application of G-PCCA on nonequilibrium molecular dynamics data of the Amyloid β (1−40) peptide, periodically driven by an oscillating electric field.
    Language: English
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  • 249
    Publication Date: 2023-11-03
    Language: English
    Type: masterthesis , doc-type:masterThesis
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  • 250
    Publication Date: 2023-11-03
    Description: Spectral clustering methods are based on solving eigenvalue problems for the identification of clusters, e.g., the identification of metastable subsets of a Markov chain. Usually, real-valued eigenvectors are mandatory for this type of algorithms. The Perron Cluster Analysis (PCCA+) is a well-known spectral clustering method of Markov chains. It is applicable for reversible Markov chains, because reversibility implies a real-valued spectrum. We also extend this spectral clustering method to non-reversible Markov chains and give some illustrative examples. The main idea is to replace the eigenvalue problem by a real-valued Schur decomposition. By this extension non-reversible Markov chains can be analyzed. Furthermore, the chains do not need to have a positive stationary distribution. In addition to metastabilities, dominant cycles and sinks can also be identified. This novel method is called GenPCCA (i.e., generalized PCCA), since it includes the case of non-reversible processes. We also apply the method to real-world eye-tracking data.
    Language: English
    Type: article , doc-type:article
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  • 251
    Publication Date: 2023-11-03
    Description: Spectral clustering methods are based on solving eigenvalue problems for the identification of clusters, e.g. the identification of metastable subsets of a Markov chain. Usually, real-valued eigenvectors are mandatory for this type of algorithms. The Perron Cluster Analysis (PCCA+) is a well-known spectral clustering method of Markov chains. It is applicable for reversible Markov chains, because reversibility implies a real-valued spectrum. We also extend this spectral clustering method to non-reversible Markov chains and give some illustrative examples. The main idea is to replace the eigenvalue problem by a real-valued Schur decomposition. By this extension non-reversible Markov chains can be analyzed. Furthermore, the chains do not need to have a positive stationary distribution. In addition to metastabilities, dominant cycles and sinks can also be identified. This novel method is called GenPCCA (i.e. Generalized PCCA), since it includes the case of non reversible processes. We also apply the method to real world eye tracking data.
    Language: English
    Type: reportzib , doc-type:preprint
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  • 252
    Publication Date: 2023-11-03
    Description: In this article we propose an adaptive importance sampling scheme for dynamical quantities of high dimensional complex systems which are metastable. The main idea of this article is to combine a method coming from Molecular Dynamics Simulation, Metadynamics, with a theorem from stochastic analysis, Girsanov's theorem. The proposed algorithm has two advantages compared to a standard estimator of dynamic quantities: firstly, it is possible to produce estimators with a lower variance and, secondly, we can speed up the sampling. One of the main problems for building importance sampling schemes for metastable systems is to find the metastable region in order to manipulate the potential accordingly. Our method circumvents this problem by using an assimilated version of the Metadynamics algorithm and thus creates a non-equilibrium dynamics which is used to sample the equilibrium quantities.
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  • 253
    Publication Date: 2023-11-03
    Description: Mathematical models for optimal decisions often require both nonlinear and discrete components. These mixed-integer nonlinear programs (MINLP) may be used to optimize the energy use of large industrial plants, integrate renewable sources into energy networks, design biological and biomedical systems, and address numerous other applications of societal importance. The first MINLP algorithms and software were designed by application engineers. While these efforts initially proved useful, scientists, engineers, and practitioners have realized that a transformational shift in technology will be required for MINLP to achieve its full potential. MINLP has transitioned to a forefront position in computer science, with researchers actively developing MINLP theory, algorithms, and implementations. Even with their concerted effort, algorithms and available software are often unable to solve practically-sized instances of these important models. Current obstacles include characterizing the computability boundary, effectively exploiting known optimization technologies for specialized classes of MINLP, and effectively using logical formulas holistically throughout algorithms.
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  • 254
    Publication Date: 2023-11-06
    Description: Natural gas is the cleanest fossil fuel since it emits the lowest amount of other remains after being burned. Over the years, natural gas usage has increased significantly. Accurate forecasting is crucial for maintaining gas supplies, transportation and network stability. This paper presents two methodologies to identify the optimal configuration o parameters of a Neural Network (NN) to forecast the next 24 h of gas flow for each node of a large gas network. In particular the first one applies a Design Of Experiments (DOE) to obtain a quick initial solution. An orthogonal design, consisting of 18 experiments selected among a total of 4.374 combinations of seven parameters (training algorithm, transfer function, regularization, learning rate, lags, and epochs), is used. The best result is selected as initial solution of an extended experiment for which the Simulated Annealing is run to find the optimal design among 89.100 possible combinations of parameters. The second technique is based on the application of Genetic Algorithm for the selection of the optimal parameters of a recurrent neural network for time series forecast. GA was applied with binary representation of potential solutions, where subsets of bits in the bit string represent different values for several parameters of the recurrent neural network. We tested these methods on three municipal nodes, using one year and half of hourly gas flow to train the network and 60 days for testing. Our results clearly show that the presented methodologies bring promising results in terms of optimal configuration of parameters and forecast error.
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  • 255
    Publication Date: 2023-11-06
    Description: Markov jump processes are widely used to model natural and engineered processes. In the context of biological or chemical applications one typically refers to the chemical master equation (CME), which models the evolution of the probability mass of any copy-number combination of the interacting particles. When many interacting particles (“species”) are considered, the complexity of the CME quickly increases, making direct numerical simulations impossible. This is even more problematic when one aims at controlling the Markov jump processes defined by the CME. In this work, we study both open loop and feedback optimal control problems of the Markov jump processes in the case that the controls can only be switched at fixed control stages. Based on Kurtz’s limit theorems, we prove the convergence of the respective control value functions of the underlying Markov decision problem as the copy numbers of the species go to infinity. In the case of the optimal control problem on a finite time-horizon, we propose a hybrid control policy algorithm to overcome the difficulties due to the curse of dimensionality when the copy number of the involved species is large. Two numerical examples demonstrate the suitability of both the analysis and the proposed algorithms.
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  • 256
    Publication Date: 2024-01-12
    Description: In this paper, we present a new, optimization-based method to exhibit cyclic behavior in non-reversible stochastic processes. While our method is general, it is strongly motivated by discrete simulations of ordinary differential equations representing non-reversible biological processes, in particular molecular simulations. Here, the discrete time steps of the simulation are often very small compared to the time scale of interest, i.e., of the whole process. In this setting, the detection of a global cyclic behavior of the process becomes difficult because transitions between individual states may appear almost reversible on the small time scale of the simulation. We address this difficulty using a mixed-integer programming model that allows us to compute a cycle of clusters with maximum net flow, i.e., large forward and small backward probability. For a synthetic genetic regulatory network consisting of a ring-oscillator with three genes, we show that this approach can detect the most productive overall cycle, outperforming classical spectral analysis methods. Our method applies to general non-equilibrium steady state systems such as catalytic reactions, for which the objective value computes the effectiveness of the catalyst.
    Language: English
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  • 257
    Publication Date: 2024-01-12
    Description: 3D Morphable Models (MM) are a popular tool for analysis and synthesis of facial expressions. They represent plausible variations in facial shape and appearance within a low-dimensional parameter space. Fitted to a face scan, the model's parameters compactly encode its expression patterns. This expression code can be used, for instance, as a feature in automatic facial expression recognition. For accurate classification, an MM that can adequately represent the various characteristic facets and variants of each expression is necessary. Currently available MMs are limited in the diversity of expression patterns. We present a novel high-quality Facial Expression Morphable Model built from a large-scale face database as a tool for expression analysis and synthesis. Establishment of accurate dense correspondence, up to finest skin features, enables a detailed statistical analysis of facial expressions. Various characteristic shape patterns are identified for each expression. The results of our analysis give rise to a new facial expression code. We demonstrate the advantages of such a code for the automatic recognition of expressions, and compare the accuracy of our classifier to state-of-the-art.
    Language: English
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  • 258
    Publication Date: 2024-01-12
    Description: Mixed integer nonlinear programs (MINLPs) are arguably among the hardest optimization problems, with a wide range of applications. MINLP solvers that are based on linear relaxations and spatial branching work similar as mixed integer programming (MIP) solvers in the sense that they are based on a branch-and-cut algorithm, enhanced by various heuristics, domain propagation, and presolving techniques. However, the analysis of infeasible subproblems, which is an important component of most major MIP solvers, has been hardly studied in the context of MINLPs. There are two main approaches for infeasibility analysis in MIP solvers: conflict graph analysis, which originates from artificial intelligence and constraint programming, and dual ray analysis. The main contribution of this short paper is twofold. Firstly, we present the first computational study regarding the impact of dual ray analysis on convex and nonconvex MINLPs. In that context, we introduce a modified generation of infeasibility proofs that incorporates linearization cuts that are only locally valid. Secondly, we describe an extension of conflict analysis that works directly with the nonlinear relaxation of convex MINLPs instead of considering a linear relaxation. This is work-in-progress, and this short paper is meant to present first theoretical considerations without a computational study for that part.
    Language: English
    Type: reportzib , doc-type:preprint
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  • 259
    Publication Date: 2024-01-12
    Description: State-of-the-art solvers for mixed integer programs (MIP) govern a variety of algorithmic components. Ideally, the solver adaptively learns to concentrate its computational budget on those components that perform well on a particular problem, especially if they are time consuming. We focus on three such algorithms, namely the classes of large neighborhood search and diving heuristics as well as Simplex pricing strategies. For each class we propose a selection strategy that is updated based on the observed runtime behavior, aiming to ultimately select only the best algorithms for a given instance. We review several common strategies for such a selection scenario under uncertainty, also known as Multi Armed Bandit Problem. In order to apply those bandit strategies, we carefully design reward functions to rank and compare each individual heuristic or pricing algorithm within its respective class. Finally, we discuss the computational benefits of using the proposed adaptive selection within the \scip Optimization Suite on publicly available MIP instances.
    Language: English
    Type: reportzib , doc-type:preprint
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  • 260
    Publication Date: 2024-01-12
    Description: Conflict learning algorithms are an important component of modern MIP and CP solvers. But strong conflict information is typically gained by depth-first search. While this is the natural mode for CP solving, it is not for MIP solving. Rapid Learning is a hybrid CP/MIP approach where CP search is applied at the root to learn information to support the remaining MIP solve. This has been demonstrated to be beneficial for binary programs. In this paper, we extend the idea of Rapid Learning to integer programs, where not all variables are restricted to the domain {0, 1}, and rather than just running a rapid CP search at the root, we will apply it repeatedly at local search nodes within the MIP search tree. To do so efficiently, we present six heuristic criteria to predict the chance for local Rapid Learning to be successful. Our computational experiments indicate that our extended Rapid Learning algorithm significantly speeds up MIP search and is particularly beneficial on highly dual degenerate problems.
    Language: English
    Type: reportzib , doc-type:preprint
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  • 261
    Publication Date: 2024-01-12
    Description: The SCIP Optimization Suite provides a collection of software packages for mathematical optimization centered around the constraint integer programming framework SCIP. This paper discusses enhancements and extensions contained in version 6.0 of the SCIP Optimization Suite. Besides performance improvements of the MIP and MINLP core achieved by new primal heuristics and a new selection criterion for cutting planes, one focus of this release are decomposition algorithms. Both SCIP and the automatic decomposition solver GCG now include advanced functionality for performing Benders’ decomposition in a generic framework. GCG’s detection loop for structured matrices and the coordination of pricing routines for Dantzig-Wolfe decomposition has been significantly revised for greater flexibility. Two SCIP extensions have been added to solve the recursive circle packing problem by a problem-specific column generation scheme and to demonstrate the use of the new Benders’ framework for stochastic capacitated facility location. Last, not least, the report presents updates and additions to the other components and extensions of the SCIP Optimization Suite: the LP solver SoPlex, the modeling language Zimpl, the parallelization framework UG, the Steiner tree solver SCIP-Jack, and the mixed-integer semidefinite programming solver SCIP-SDP.
    Language: English
    Type: reportzib , doc-type:preprint
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  • 262
    Publication Date: 2024-01-12
    Description: We consider the problem of pattern detection in large scale railway timetables. This problem arises in rolling stock optimization planning in order to identify invariant sections of the timetable for which a cyclic rotation plan is adequate. We propose a dual reduction technique which leads to an decomposition and enumeration method. Computational results for real world instances demonstrate that the method is able to produce optimal solutions as fast as standard MIP solvers.
    Language: English
    Type: conferenceobject , doc-type:conferenceObject
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  • 263
    Publication Date: 2024-01-12
    Description: State-of-the-art solvers for mixed integer programs (MIP) govern a variety of algorithmic components. Ideally, the solver adaptively learns to concentrate its computational budget on those components that perform well on a particular problem, especially if they are time consuming. We focus on three such algorithms, namely the classes of large neighborhood search and diving heuristics as well as Simplex pricing strategies. For each class we propose a selection strategy that is updated based on the observed runtime behavior, aiming to ultimately select only the best algorithms for a given instance. We review several common strategies for such a selection scenario under uncertainty, also known as Multi Armed Bandit Problem. In order to apply those bandit strategies, we carefully design reward functions to rank and compare each individual heuristic or pricing algorithm within its respective class. Finally, we discuss the computational benefits of using the proposed adaptive selection within the SCIP Optimization Suite on publicly available MIP instances.
    Language: English
    Type: conferenceobject , doc-type:conferenceObject
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  • 264
    Publication Date: 2024-01-12
    Language: English
    Type: conferenceobject , doc-type:conferenceObject
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  • 265
    Publication Date: 2024-02-12
    Description: We consider the stochastic extensible bin packing problem (SEBP) in which n items of stochastic size are packed into m bins of unit capacity. In contrast to the classical bin packing problem, the number of bins is fixed and they can be extended at extra cost. This problem plays an important role in stochastic environments such as in surgery scheduling: Patients must be assigned to operating rooms beforehand, such that the regular capacity is fully utilized while the amount of overtime is as small as possible. This paper focuses on essential ratios between different classes of policies: First, we consider the price of non-splittability, in which we compare the optimal non-anticipatory policy against the optimal fractional assignment policy. We show that this ratio has a tight upper bound of 2. Moreover, we develop an analysis of a fixed assignment variant of the LEPT rule yielding a tight approximation ratio of (1+e−1)≈1.368 under a reasonable assumption on the distributions of job durations. Furthermore, we prove that the price of fixed assignments, related to the benefit of adaptivity, which describes the loss when restricting to fixed assignment policies, is within the same factor. This shows that in some sense, LEPT is the best fixed assignment policy we can hope for.
    Language: English
    Type: conferenceobject , doc-type:conferenceObject
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  • 266
    Publication Date: 2024-02-12
    Description: We consider the Cumulative Scheduling Problem (CuSP) in which a set of $n$ jobs must be scheduled according to release dates, due dates and cumulative resource constraints. In constraint programming, the CuSP is modeled as the cumulative constraint. Among the most common propagation algorithms for the CuSP there is energetic reasoning (Baptiste et al., 1999) with a complexity of O(n^3) and edge-finding (Vilim, 2009) with O(kn log n) where k 〈= n is the number of different resource demands. We consider the complete versions of the propagators that perform all deductions in one call of the algorithm. In this paper, we introduce the energetic edge-finding rule that is a generalization of both energetic reasoning and edge-finding. Our main result is a complete energetic edge-finding algorithm with a complexity of O(n^2 log n) which improves upon the complexity of energetic reasoning. Moreover, we show that a relaxation of energetic edge-finding with a complexity of O(n^2) subsumes edge-finding while performing stronger propagations from energetic reasoning. A further result shows that energetic edge-finding reaches its fixpoint in strongly polynomial time. Our main insight is that energetic schedules can be interpreted as a single machine scheduling problem from which we deduce a monotonicity property that is exploited in the algorithms. Hence, our algorithms improve upon the strength and the complexity of energetic reasoning and edge-finding whose complexity status seemed widely untouchable for the last decades.
    Language: English
    Type: conferenceobject , doc-type:conferenceObject
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  • 267
    Publication Date: 2024-02-12
    Description: Cycle inequalities play an important role in the polyhedral study of the periodic timetabling problem. We give the first pseudo-polynomial time separation algo- rithm for cycle inequalities, and we give a rigorous proof for the pseudo-polynomial time separability of the change-cycle inequalities. Moreover, we provide several NP-completeness results, indicating that pseudo-polynomial time is best possible. The efficiency of these cutting planes is demonstrated on real-world instances of the periodic timetabling problem.
    Language: English
    Type: reportzib , doc-type:preprint
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  • 268
    Publication Date: 2024-04-05
    Description: User-defined and system-level checkpointing have contrary properties. While user-defined checkpoints are smaller and simpler to recover, system-level checkpointing better knows the global system's state and parameters like the expected mean time to failure (MTTF) per node. Both approaches lead to non-optimal checkpoint time, intervals, sizes, or I/O bandwidth when concurrent checkpoints conflict and compete for it. We combine user-defined and system-level checkpointing to exploit the benefits and avoid the drawbacks of each other. Thus, applications frequently offer to create checkpoints. The system accepts such offers according to the current status and implied costs to recalculate from the last checkpoint or denies them, i.e., immediately lets continue the application without checkpoint creation. To support this approach, we develop economic models for multi-application checkpointing on shared I/O resources that are dedicated for checkpointing (e.g. burst-buffers) by defining an appropriate goal function and solving a global optimization problem. Using our models, the checkpoints of applications on a supercomputer are scheduled to effectively use the available I/O bandwidth and minimize the failure overhead (checkpoint creations plus recalculations). Our simulations show an overall reduction in failure overhead of all nodes of up to 30% for a typical supercomputer workload (HLRN). We can also derive the most cost effective burst-buffer bandwidth for a given node's MTTF and application workload.
    Language: English
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  • 269
    Publication Date: 2024-04-05
    Language: English
    Type: poster , doc-type:Other
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  • 270
    Publication Date: 2024-05-16
    Description: Background: Hashtags are widely used for communication in online media. As a condensed version of information, they characterize topics and discussions. For their analysis, we apply methods from network science and propose novel tools for tracing their dynamics in time-dependent data. The observations are characterized by bursty behaviors in the increases and decreases of hashtag usage. These features can be reproduced with a novel model of dynamic rankings. Hashtag communities in time: We build temporal and weighted co-occurrence networks from hashtags. On static snapshots, we infer the community structure using customized methods. On temporal networks, we solve the bipartite matching problem of detected communities at subsequent timesteps by taking into account higher-order memory. This results in a matching protocol that is robust toward temporal fluctuations and instabilities of the static community detection. The proposed methodology is broadly applicable and its outcomes reveal the temporal behavior of online topics. Modeling topic-dynamics: We consider the size of the communities in time as a proxy for online popularity dynamics. We find that the distributions of gains and losses, as well as the interevent times are fat-tailed indicating occasional, but large and sudden changes in the usage of hashtags. Inspired by typical website designs, we propose a stochastic model that incorporates a ranking with respect to a time-dependent prestige score. This causes occasional cascades of rank shift events and reproduces the observations with good agreement. This offers an explanation for the observed dynamics, based on characteristic elements of online media.
    Language: English
    Type: article , doc-type:article
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  • 271
    Book
    Book
    Boca Raton ; London ; New York :CRC Press, Taylor & Francis Group,
    Title: Programming for Hybrid Multi/Manycore MPP Systems /
    Author: Levesque, John
    Contributer: Vose, Aaron
    Publisher: Boca Raton ; London ; New York :CRC Press, Taylor & Francis Group,
    Year of publication: 2018
    Pages: xxxv, 305 Seiten : , Diagramme
    Series Statement: Chapman & Hall/CRC computational science series
    ISBN: 978-1-4398-7371-7
    Type of Medium: Book
    Language: English
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  • 272
    Title: Einführung in Python 3 : für Ein- und Umsteiger
    Author: Klein, Bernd
    Edition: 3., überarb. Aufl.
    Year of publication: 2018
    Pages: XVI, 537 Seiten : , Illustrationen ; , 25 cm
    ISBN: 978-3-446-45208-4 , 3-446-45208-7
    Type of Medium: Book
    Language: German
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  • 273
    Title: High-dimensional probability : an introduction with applications in data science
    Author: Vershynin, Roman
    Year of publication: 2018
    Pages: 296 S. : , Diagramme
    ISBN: 978-1-108-41519-4
    Type of Medium: Book
    Language: English
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  • 274
    Title: Unterschwellenvergabeordnung (UVgO) : und Allgemeine Vertragsbedingungen für die Ausführung von Leistungen (VOL Teil B)
    Author: Schaller, Hans
    Publisher: München :C.H. Beck,
    Year of publication: 2018
    Pages: X, 348 Seiten
    ISBN: 978-3-406-71322-4
    Type of Medium: Book
    Language: German
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  • 275
    Title: Leitfaden zur Bildverarbeitung in der zerstörungsfreien Prüfung /; 18
    Author: Sackewitz, Michael
    Contributer: Fraunhofer-Allianz Vision [Herausgeber]
    Publisher: Fürth :Fraunhofer Verlag,
    Year of publication: 2018
    Pages: 126 Seiten
    Series Statement: Vision Leitfaden 18
    ISBN: 978-3-8396-1380-1
    Type of Medium: Book
    Language: German
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  • 276
    Title: TV-L Jahrbuch Länder 2018 : kommentierte Textsammlung : TV-L mit Überleitungstarifvertrag, ergänzende Tarifverträge, Entgeltordnungen
    Author: Effertz, Jörg
    Edition: Ausgabe 2018, Stand vom 1. November 2017
    Year of publication: 2018
    Pages: 1564 Seiten
    Series Statement: Wissen für die Praxis
    ISBN: 978-3-8029-7928-6 , 3-8029-7928-1
    Type of Medium: Book
    Language: German
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  • 277
    Title: Exploiting structure in non-convex quadratic optimization and gas network planning under uncertainty /
    Author: Schweiger, Jonas
    Publisher: Berlin :Logos Verlag,
    Year of publication: 2018
    Pages: xiii, 186 S.
    Dissertation note: zugl. Diss. an Fakultät II - Mathematik und Naturwissenschaften der Technischen Universität Berlin
    ISBN: 978-3-8325-4667-0
    Type of Medium: Book
    Language: English
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  • 278
    Title: Machine Learning : kurz & gut
    Author: Nguyen, Chi Nhan
    Contributer: Zeigermann, Oliver
    Edition: 1. Auflage
    Year of publication: 2018
    Pages: 183 Seiten : , Illustrationen, Diagramme ; , 17.8 cm x 10.8 cm
    Series Statement: O'Reillys Taschenbibliothek
    ISBN: 978-3-96009-052-6
    Type of Medium: Book
    Language: German
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  • 279
    Title: Bitcoin und Blockchain - Grundlagen und Programmierung : die Blockchain verstehen, Anwendungen entwickeln
    Author: Antonopoulos, Andreas M.
    Contributer: Klicman, Peter
    Edition: 2. Auflage
    Year of publication: 2018
    Pages: XXXI, 377 Seiten : , Illustrationen, Diagramme ; , 24 cm x 16.5 cm
    ISBN: 978-3-96009-071-7
    Type of Medium: Book
    Language: German
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  • 280
    Book
    Book
    San Rafeal :Morgen & Claypool,
    Title: Demystifying Owl for the Enterprise
    Author: Unschold, Micheal
    Contributer: Ding, Ying , Groth, Paul
    Publisher: San Rafeal :Morgen & Claypool,
    Year of publication: 2018
    Pages: 264 S.
    ISBN: 978-1-68173-127-8
    Type of Medium: Book
    Language: German
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  • 281
    Title: Ubuntu Server 18.04 LTS : Das umfassende Handbuch
    Author: Soest, Daniel van
    Edition: 3. aktualisierte und erweiterte Auflage
    Year of publication: 2018
    Pages: 1066 S. ; , 24 cm x 16.8 cm
    ISBN: 978-3-8362-6288-0
    Type of Medium: Book
    Language: German
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  • 282
    Title: Docker : das Praxisbuch für Entwickler und DevOps-Teams
    Author: Öggl, Bernd
    Contributer: Kofler, Michael
    Edition: 1. Aufl.
    Year of publication: 2018
    Pages: 431 S. : , Illustrationen, Diagramme ; , 24 cm x 16.8 cm
    ISBN: 978-3-8362-6176-0
    Type of Medium: Book
    Language: German
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  • 283
    Title: Eclipse : kennenlernen ; verstehen ; Effizient nutzen
    Author: Künneth, Thomas
    Year of publication: 2018
    Pages: 318 Seiten
    ISBN: ISBN 978-3-446-45466-8 , ISBN 3-446-45466-7
    Type of Medium: Book
    Language: German
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  • 284
    Book
    Book
    Singapur :World Scientific Publishing Co Pte Ltd,
    Title: Nonlinear Algebra in an ACORN : with Applications To Deep Learning
    Author: Lee, Martin
    Publisher: Singapur :World Scientific Publishing Co Pte Ltd,
    Year of publication: 2018
    Pages: 92 S.
    ISBN: 978-981-327-151-7
    Type of Medium: Book
    Language: English
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  • 285
    Title: Artist, authorship & legacy : a reader
    Contributer: McClean, Daniel
    Year of publication: 2018
    Pages: 398 Seiten
    ISBN: 978-1-909932-45-6
    Type of Medium: Book
    Language: English
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  • 286
    Title: Clean architecture : a craftsman's guide to software structure and design
    Author: Martin, Robert C.
    Year of publication: 2018
    Pages: xxv, 404 Seiten : , Illustrationen
    Series Statement: Robert C. Martin series
    ISBN: 978-0-13-449416-6
    Type of Medium: Book
    Language: English
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  • 287
    Book
    Book
    Cambridge :Cambridge Univ. Pr.,
    Title: Spectral theory and differential operators; 42
    Author: Davies, Edward B.
    Edition: 2. Ed.
    Publisher: Cambridge :Cambridge Univ. Pr.,
    Year of publication: 2018
    Series Statement: Cambridge studies in advanced mathematics 42
    Type of Medium: Book
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  • 288
    Title: Practical mathematical optimization : an introduction to basic optimization theory and classical and new Gradient-Based Algorithms; 97
    Author: Snyman, Jan A.
    Edition: 2. Ed.
    Publisher: Berlin [u.a.] :Springer,
    Year of publication: 2018
    Pages: 372 S. : , Ill., graph. Darst.
    Series Statement: Applied optimization 97
    ISBN: 978-3-319-77586-9 , 978-319-77585-2
    Type of Medium: Book
    Language: English
    Parallel Title: Auch als Internetausg.
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  • 289
    Book
    Book
    Cambridge :MIT Press,
    Title: Reinforcement learning : an introduction
    Author: Sutton, Richard S.
    Contributer: Barto, Andrew
    Edition: Second edition
    Publisher: Cambridge :MIT Press,
    Year of publication: 2018
    Pages: 526 Seiten
    ISBN: 978-0-262-03924-6
    Type of Medium: Book
    Language: English
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  • 290
    Title: Organization, representation and description through the digital age : information in libraries, archives and museums
    Author: Angel, Christine
    Contributer: Fuchs, Caroline
    Publisher: Berlin ; Boston :De Gruyter Sauer,
    Year of publication: 2018
    Pages: 303 Seiten
    ISBN: 3-11-033715-0
    Type of Medium: Book
    Language: English
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  • 291
    Book
    Book
    Princeton ; Oxford :Princeton University Press,
    Title: ¬The¬ tyranny of metrics /
    Author: Muller, Jerry Z.
    Publisher: Princeton ; Oxford :Princeton University Press,
    Year of publication: 2018
    Pages: xxiii, 220 Seiten
    ISBN: 978-0-691-17495-2
    Type of Medium: Book
    Language: English
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  • 292
    Title: DSGVO - Verzeichnis der wichtigen Verarbeitungstätigkeiten /
    Author: Frahm, Jörg
    Contributer: Koch, Holger , Seiffert, Evelyn
    Year of publication: 2018
    Pages: 1 CD-ROM ; , 12 cm, Behältnis 19 x 14 x 2 cm +
    Series Statement: Business solutions
    ISBN: 978-3-86198-583-9 , 3-86198-583-7
    Type of Medium: Electronic Resource
    Language: German
    Note: Windows (XP ab SP3, Vista, W7, W8, W10)
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  • 293
    Title: Deep Learning mit Python und Keras : das Praxis-Handbuch vom Entwickler der Keras-Bibliothek
    Author: Chollet, François
    Contributer: Lorenzen, Knut
    Edition: 1. Auflage
    Year of publication: 2018
    Pages: 443 S. : , Illustrationen, Diagramme
    ISBN: 978-3-95845-838-3 , 3-95845-838-6
    Type of Medium: Book
    Language: German
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  • 294
    Title: Praxiseinstieg Machine Learning mit Scikit-Learn und TensorFlow : Konzepte, Tools und Techniken für intelligente Systeme
    Author: Géron, Aurélien
    Contributer: Rother, Kristian
    Edition: 1. Auflage
    Year of publication: 2018
    Pages: XXII, 552 Seiten : , Illustrationen, Diagramme
    ISBN: 978-3-96009-061-8
    Type of Medium: Book
    Language: German
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  • 295
    Title: Python 3 : lernen und professionell anwenden : das umfassende Praxisbuch
    Author: Weigend, Michael
    Edition: 7., erw. Aufl.
    Year of publication: 2018
    Pages: 986 Seiten : , Illustrationen, Diagramme ; , 25 cm, 1787 g
    ISBN: 978-3-95845-791-1
    Type of Medium: Book
    Language: German
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  • 296
    Title: Windows PowerShell und PowerShell Core - der schnelle Einstieg : skriptbasierte Systemadministration für Windows, Linux und macOS
    Author: Schwichtenberg, Holger
    Year of publication: 2018
    Pages: XXII, 485 S. : , Ill. ; , 24 cm
    ISBN: ISBN 978-3-446-45214-5
    Type of Medium: Book
    Language: German
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  • 297
    Title: Python 3 : einsteigen und durchstarten
    Author: Kalista, Heiko
    Year of publication: 2018
    Pages: XVI, 498 Seiten
    ISBN: 978-3-446-45469-9
    Type of Medium: Book
    Language: German
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  • 298
    Title: You've been hacked! : alles über Exploits gegen Webanwendungen.
    Author: Eilers, Carsten
    Edition: 1. Aufl.
    Year of publication: 2018
    Pages: 578 Seiten ; , 24 cm x 19 cm
    Type of Medium: Book
    Language: German
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  • 299
    Title: Progressive Web Apps : Das Praxisbuch. Entwicklung plattformübergreifender Apps für Browser, Windows, macOS, iOS, Android mit Angular und Workbox
    Author: Liebel, Christian
    Edition: 1. Aufl.
    Year of publication: 2018
    Pages: 450 Seiten
    ISBN: 978-3-8362-6494-5
    Type of Medium: Book
    Language: German
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  • 300
    Title: Modern Fortran explained /
    Author: Metcalf, Michael
    Contributer: Reid, John Ker , Cohen, Malcolm
    Edition: [5th Revised edition]
    Year of publication: 2018
    Pages: 544 Seiten
    Type of Medium: Book
    Language: English
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