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Sharing economies enabled by technical platforms have been studied regarding their economic, legal, and social effects, as well as with regard to their possible influences on CSCW topics such as work, collaboration, and trust. While a lot current research is focusing on the sharing economy and related communities, there is little work addressing the phenomenon from a socio-technical point of view. Our workshop is meant to address this gap. Building on research themes and discussion from last year’s ECSCW, we seek to engage deeper with topics such as novel socio-technical approaches for enabling sharing communities, discussing issues around digital consumer and worker protection, as well as emerging challenges and opportunities of existing platforms and approaches.
Sie sind im Bereich Qualitätsmanagement tätig und haben die Aufgabe bekommen, ein Problem systematisch zu untersuchen und methodisch zu lösen? Sie haben zu viele Aufgaben und wissen nicht, wie Sie diese priorisieren sollen? Oder haben Sie zu begrenzte Ressourcen, um alle Reklamationen gleichzeitig bearbeiten zu können? Oder wissen nicht, wie Sie einen bestimmten Prozess in seinen Grenzen zielführend verbessern können?
Auch die mittlerweile siebte Ausgabe des wissenschaftlichen Workshops “Usable Security und Privacy” auf der Mensch und Computer 2021 wird aktuelle Forschungs- und Praxisbeiträge präsentiert und anschließend mit allen Teilnehmer:innen diskutiert. Zwei Beiträge befassen sich dieses Jahr mit dem Thema Privatsphäre, zwei mit dem Thema Sicherheit. Mit dem Workshop wird ein etabliertes Forum fortgeführt und weiterentwickelt, in dem sich Expert:innen aus unterschiedlichen Domänen, z. B. dem Usability- und Security- Engineering, transdisziplinär austauschen können.
New cars are increasingly "connected" by default. Since not having a car is not an option for many people, understanding the privacy implications of driving connected cars and using their data-based services is an even more pressing issue than for expendable consumer products. While risk-based approaches to privacy are well established in law, they have only begun to gain traction in HCI. These approaches are understood not only to increase acceptance but also to help consumers make choices that meet their needs. To the best of our knowledge, perceived risks in the context of connected cars have not been studied before. To address this gap, our study reports on the analysis of a survey with 18 open-ended questions distributed to 1,000 households in a medium-sized German city. Our findings provide qualitative insights into existing attitudes and use cases of connected car features and, most importantly, a list of perceived risks themselves. Taking the perspective of consumers, we argue that these can help inform consumers about data use in connected cars in a user-friendly way. Finally, we show how these risks fit into and extend existing risk taxonomies from other contexts with a stronger social perspective on risks of data use.
The dataset contains the following data from successful and failed executions of the Toyota HSR robot placing a book on a shelf.
RGB images from the robot's head camera
Depth images from the robot's head camera
Rendered images of the robot's 3D model from the point of view of the robot's head camera
Force-torque readings from a wrist-mounted force-torque sensor
Joint efforts, velocities and positions
extrinsic and intrinsic camera calibration parameters
frame-level anomaly annotations
The anomalies that occur during execution include:
the manipulated book falling down
books on the shelf being disturbed significantly
camera occlusions
robot being disturbed by an external collision
The dataset is split into a train, validation and test set with the following number of trials:
Train: 48 successful trials
Validation: 6 successful trials
Test: 60 anomalous trials and 7 successful trials
Designs for decorative surfaces, such as flooring, must cover several square meters to avoid visible repeats. While the use of desktop systems is feasible to support the designer, it is challenging for a non-domain expert to get the right impression of the appearances of surfaces due to limited display sizes and a potentially unnatural interaction with digital designs. At the same time, large-format editing of structure and gloss is becoming increasingly important. Advances in the printing industry allow for more faithful reproduction of such surface details. Unfortunately, existing systems for visualizing surface designs cannot adequately account for gloss, especially for non-domain experts. Here, the complex interaction of light sources and the camera position must be controlled using software controls. As a result, only small parts of the data set can be properly inspected at a time. Also, real-world lighting is not considered here. This work presents a system for the processing and realistic visualization of large decorative surface designs. To this end, we present a tabletop solution that is coupled to a live 360° video feed and a spatial tracking system. This allows for reproducing natural view-dependent effects like real-world reflections, live image-based lighting, and the interaction with the design using virtual light sources employing natural interaction techniques that allow for a more accurate inspection even for non-domain experts.
Ablaufdiagramm
(2021)
In diesem Video werden Aufbau, Funktion und Nutzen eines Ablaufdiagrammes als Grundwerkzeug des Qualitätsmanagements gezeigt. Diese bilden die Grundlage für die Visualisierung der definierten und einzuhaltenden Reihenfolge eines Ablaufes für Algorithmen, Programme, Prozesse, Verfahren oder Projekte.
Solving transport network problems can be complicated by non-linear effects. In the particular case of gas transport networks, the most complex non-linear elements are compressors and their drives. They are described by a system of equations, composed of a piecewise linear ‘free’ model for the control logic and a non-linear ‘advanced’ model for calibrated characteristics of the compressor. For all element equations, certain stability criteria must be fulfilled, providing the absence of folds in associated system mapping. In this paper, we consider a transformation (warping) of a system from the space of calibration parameters to the space of transport variables, satisfying these criteria. The algorithm drastically improves stability of the network solver. Numerous tests on realistic networks show that nearly 100% convergence rate of the solver is achieved with this approach.
Voice assistants (VA) collect data about users’ daily life including interactions with other connected devices, musical preferences, and unintended interactions. While users appreciate the convenience of VAs, their understanding and expectations of data collection by vendors are often vague and incomplete. By making the collected data explorable for consumers, our research-through-design approach seeks to unveil design resources for fostering data literacy and help users in making better informed decisions regarding their use of VAs. In this paper, we present the design of an interactive prototype that visualizes the conversations with VAs on a timeline and provides end users with basic means to engage with data, for instance allowing for filtering and categorization. Based on an evaluation with eleven households, our paper provides insights on how users reflect upon their data trails and presents design guidelines for supporting data literacy of consumers in the context of VAs.
Alleine Bowling spielen?
(2021)
Womöglich ist das social distancing dieser Tage gar kein soziales sondern einfach nur ein körperliches, ein body distancing. Sozial können wir heute auch sein, ohne uns physisch zu begegnen. Wir können sogar "gemeinsam einsam" musizieren oder im Chor singen. Trotzdem geht etwas verloren - und am Ende wissen wir Zusammenkünfte in Vereinen welcher Art auch immer vielleicht wieder besonders zu schätzen.
Die Analytik ist zwar ein grundlegendes Thema innerhalb der Chemie, hat es aber ganz schön in sich. Aber keine Sorge, Ulf Ritgen erklärt Ihnen in diesem Buch was Sie zur Analytischen Chemie Wissen sollten. Wie erhält man eigentlich analytische Infos? Welche Standards gibt es? Und wie sollte man überhaupt mit den Stoffgemischen umgehen? All diese Grundlagen werden ausführlich erläutert. Aber auch die Anwendungsgebiete und Methoden kommen keinesfalls zu kurz. Egal ob Gravimetrie, Titration, Fällung oder Konduktometrie, endlich wird alles verständlich erklärt. Jetzt können Prüfung und Praktikum kommen! (Verlagsangaben)
Ice accumulation in the blades of wind turbines can cause them to describe anomalous rotations or no rotations at all, thus affecting the generation of electricity and power output. In this work, we investigate the problem of ice accumulation in wind turbines by framing it as anomaly detection of multi-variate time series. Our approach focuses on two main parts: first, learning low-dimensional representations of time series using a Variational Recurrent Autoencoder (VRAE), and second, using unsupervised clustering algorithms to classify the learned representations as normal (no ice accumulated) or abnormal (ice accumulated). We have evaluated our approach on a custom wind turbine time series dataset, for the two-classes problem (one normal versus one abnormal class), we obtained a classification accuracy of up to 96$\%$ on test data. For the multiple-class problem (one normal versus multiple abnormal classes), we present a qualitative analysis of the low-dimensional learned latent space, providing insights into the capacities of our approach to tackle such problem. The code to reproduce this work can be found here https://github.com/agrija9/Wind-Turbines-VRAE-Paper.
Die Bibliothek der Hochschule Bonn-Rhein-Sieg betreut seit mehr als zehn Jahren mit einer eigenen Abteilung die zentrale E-Learning-Infrastruktur der Hochschule. Aus der ursprünglichen Aufgabe, das Lern-Management-System ILIAS für die gesamte Hochschule einzuführen, entwickelte sich schnell ein umfangreiches E-Learning-Service-Angebot, das weit über das Betreiben einer Lernplattform hinausgeht.
Die nationale Politik- und Forschungsstrategie Bioökonomie sieht eine Transformation der Wirtschaft vor, bei der die Verwendung fossiler Rohstoffe zunehmend durch den Einsatz nachwachsender Rohstoffe ersetzt wird. Der Einsatz biobasierter Kunststoffe soll dabei gefördert werden. Erste Analysen der Berichterstattung zu Biokunststoffen im Rahmen einer Pilotstudie ergaben, dass der Grundgedanke biologisch abbaubarer Kunststoffe breite Zustimmung im öffentlichen Diskurs erfährt. Abseits der soziopolitischen Diskursebene entwickelt sich jedoch eine medial geführte Diskussion um erhebliche Probleme mit den Stoffen in der Abfallwirtschaft. Die Gefahr besteht nun, dass diese Haltung verbreitet durch die Massenmedien auf die öffentliche Meinung abfärbt. Mangelnde öffentliche Akzeptanz könnte den Erfolg von innovativen Biokunststoff-Produkten gefährden.
This book shows in a comprehensive presentation how Bond Graph methodology can support model-based control, model-based fault diagnosis, fault accommodation, and failure prognosis by reviewing the state-of-the-art, presenting a hybrid integrated approach to Bond Graph model-based fault diagnosis and failure prognosis, and by providing a review of software that can be used for these tasks.
Brainstorming
(2021)
Critical consumerism is complex as ethical values are difficult to negotiate, appropriate products are hard to find, and product information is overwhelming. Although recommender systems offer solutions to reduce such complexity, current designs are not appropriate for niche practices and use non-personalized intransparent ethics. To support critical consumption, we conducted a design case study on a personalized food recommender system. Therefore, we first conducted an empirical pre-study with 24 consumers to understand value negotiations and current practices, co-designed the recommender system, and finally evaluated it in a real-world trial with ten consumers. Our findings show how recommender systems can support the negotiation of ethical values within the context of consumption practices, reduce the complexity of finding products and stores, and strengthen consumers. In addition to providing implications for the design to support critical consumption practices, we critically reflect on the scope of such recommender systems and its appropriation.
BWL für Dummies
(2021)
Characterization of Urban Radio Channels and Base Station Antenna Correlation in the 3.75 GHz Band
(2021)
Components and Architecture for the Implementation of Technology-Driven Employee Data Protection
(2021)
Off-lattice Boltzmann methods increase the flexibility and applicability of lattice Boltzmann methods by decoupling the discretizations of time, space, and particle velocities. However, the velocity sets that are mostly used in off-lattice Boltzmann simulations were originally tailored to on-lattice Boltzmann methods. In this contribution, we show how the accuracy and efficiency of weakly and fully compressible semi-Lagrangian off-lattice Boltzmann simulations is increased by velocity sets derived from cubature rules, i.e. multivariate quadratures, which have not been produced by the Gauss-product rule. In particular, simulations of 2D shock-vortex interactions indicate that the cubature-derived degree-nine D2Q19 velocity set is capable to replace the Gauss-product rule-derived D2Q25. Likewise, the degree-five velocity sets D3Q13 and D3Q21, as well as a degree-seven D3V27 velocity set were successfully tested for 3D Taylor-Green vortex flows to challenge and surpass the quality of the customary D3Q27 velocity set. In compressible 3D Taylor-Green vortex flows with Mach numbers Ma={0.5;1.0;1.5;2.0} on-lattice simulations with velocity sets D3Q103 and D3V107 showed only limited stability, while the off-lattice degree-nine D3Q45 velocity set accurately reproduced the kinetic energy provided by literature.
In tree-based adaptive mesh refinement (AMR) we store refinement trees in the cells of an unstructured coarse mesh. This lets us combine the speed and simpler management of structured refinement trees with the more flexible mesh generation of the unstructured coarse mesh. But this creates a conflict between performance and geometrical accuracy. If we favor speed we reduce the cells in our coarse mesh and hence reduce the accuracy of our geometrical representation. If we want more accurate results we generate a finer coarse mesh and lose performance by managing more cells in our unstructured coarse mesh. To mitigate this conflict we present the prototype of an geometry description which we implement in an already existing library. With this description we build geometry adapted hexahedral refinement trees, which also support high-order curved boundary cells. We also present examples on how to use this description. Moreover, we test the speedup of this new algorithm compared with coarse meshes with different geometrical errors.
The Covid-19 pandemic has challenged educators across the world to move their teaching and mentoring from in-person to remote. During nonpandemic semesters at their institutes (e.g. universities), educators can directly provide students the software environment needed to support their learning - either in specialized computer laboratories (e.g. computational chemistry labs) or shared computer spaces. These labs are often supported by staff that maintains the operating systems (OS) and software. But how does one provide a specialized software environment for remote teaching? One solution is to provide students a customized operating system (e.g., Linux) that includes open-source software for supporting your teaching goals. However, such a solution should not require students to install the OS alongside their existing one (i.e. dual/multi-booting) or be used as a complete replacement. Such approaches are risky because of a) the students' possible lack of software expertise, b) the possible disruption of an existing software workflow that is needed in other classes or by other family members, and c) the importance of maintaining a working computer when isolated (e.g. societal restrictions). To illustrate possible solutions, we discuss our approach that used a customized Linux OS and a Docker container in a course that teaches computational chemistry and Python3.
Das Windenergie-auf-See-Gesetz und das Verfassungsrecht: Eine Vervollständigung in drei Etappen
(2021)
Data Science
(2021)
Data Science ist in vielen Organisationen angekommen und oft alltägliche Praxis. Dennoch stehen viele Verantwortliche vor der Herausforderung, sich erstmalig mit konkreten Fragestellungen zu beschäftigen oder laufende Projekte weiterzuentwickeln. Die Spannbreite der Methoden, Werkzeuge und Anwendungsmöglichkeiten ist sehr groß und entwickelt sich kontinuierlich weiter. Die Vielzahl an Publikationen zu Data Science ist spezialisiert und behandelt fokussiert Einzelaspekte.
Das vorliegende Werk gibt den Leserinnen und Lesern eine umfassende Orientierung zum Status Quo aus der wissenschaftlichen Perspektive und zahlreiche vertiefende Darstellungen praxisrelevanter Aspekte. Die Inhalte bauen auf den wissenschaftlichen CAS-Zertifikatskursen zu Big Data und Data Science der Hochschule Niederrhein in Kooperation mit der Hochschule Bonn-Rhein-Sieg und der FH Dortmund auf. Sie berücksichtigen wissenschaftliche Grundlagen und Vertiefungen, aber auch konkrete Erfahrungen aus Data Science Projekten. Das Buch greift praxisrelevante Fragen auf wissenschaftlichem Niveau aus Sicht der Rollen eines „Data Strategist“, „Data Architect“ und „Data Analyst“ auf und bindet erprobte Praxiserfahrungen u. a. von Seminarteilnehmern mit ein. Das Buch gibt für Interessierte einen Einblick in die aktuell relevante Vielfalt der Aspekte zu Data Science bzw. Big Data und liefert Hinweise für die praxisnahe Umsetzung. (Verlagsangaben)
Datensammelblatt
(2021)
Due to ongoing digitalization, more and more cloud services are finding their way into companies. In this context, data integration from the various software solutions, which are provided both on-premise (local use or licensing for local use of software) and as a service, is of great importance. In this regard, Integration Platform as a Service (IPaaS) models aim to support companies as well as software providers in the context of data integration by providing connectors to enable data flow between different applications and systems and other integration services. Since previous research has mostly focused on technical or legal aspects of IPaaS, this article focuses on deriving integration practices and design-related barriers and drivers regarding the adoption of IPaaS. Therefore, we conducted 10 interviews with experts from different software as a services vendors. Our results show that the main factors regarding the adoption of IPaaS are the standardization of data models, the usability and variety of connectors provided, and the issues regarding data privacy, security, and transparency.
Die digitale Universität
(2021)
Die digitale Universität muss als eine Form des Erscheinens ihrer Mitglieder in spezifischen Räumen und Handlungen verstanden werden. Die Verhandlung ihrer Bedingungen ist von brennender Aktualität: Das Feuer, das die Idee der digitalen Universität entfacht, hat das Potential, die apriorische Ebene von Universität zu verabschieden und ihre neue Setzung zu veranlassen.
Die Transformationen der Wissenschaft, ihrer Systeme und Ordnungen fokussiert sich meist auf eine Politik des Digitalen beziehungsweise eine Politik der Digitalität. Durch die jüngsten Ereignisse, die auch die Universität in eine Krisen- und Ausnahmesituation bringen, gewinnt dieser Aspekt eine besondere Brisanz. Die unumgängliche Entwicklung neuer Lehr- und Forschungsformate führt zu einem grundlegenden Strukturwandel der Universität. Diese Frage von philosophischer oder universitätstheoretischer Brisanz, muss ein ernsthaftes Nachdenken über die Idee der digitalen Universität anstoßen. Digitalität und Universität können nicht länger als voneinander getrennte und unveränderliche Begriffe und Phänomene aufgefasst werden, denn sie sind in ihrer Kombination intrinsisch miteinander verbunden. (Verlagsangaben)
Die Kunst, Kunst zu zeigen
(2021)
Die Öffnung der Personenhandelsgesellschaft für Freiberufler in berufsrechtlicher Perspektive
(2021)
Digitale Medienkompetenz
(2021)
In this thesis it is posed that the central object of preference discovery is a co-creative process in which the Other can be represented by a machine. It explores efficient methods to enhance introverted intuition using extraverted intuition's communication lines. Possible implementations of such processes are presented using novel algorithms that perform divergent search to feed the users' intuition with many examples of high quality solutions, allowing them to take influence interactively. The machine feeds and reflects upon human intuition, combining both what is possible and preferred. The machine model and the divergent optimization algorithms are the motor behind this co-creative process, in which machine and users co-create and interactively choose branches of an ad hoc hierarchical decomposition of the solution space.
The proposed co-creative process consists of several elements: a formal model for interactive co-creative processes, evolutionary divergent search, diversity and similarity, data-driven methods to discover diversity, limitations of artificial creative agents, matters of efficiency in behavioral and morphological modeling, visualization, a connection to prototype theory, and methods to allow users to influence artificial creative agents. This thesis helps putting the human back into the design loop in generative AI and optimization.
DNA Sequencing
(2021)
Here we provide the electrophysiology data for the manuscript "Two functional epithelial sodium channel isoforms are present in rodents despite pronounced evolutionary pseudogenization and exon fusion", published in Molecular Biology and Evolution (2021): msab271 (doi: 10.1093/molbev/msab271). Data are reported as current values in Excel format, sorted according to the appearance in Figures and supplemented by explanatory text on the procedures/data presentation.
Im letzten Vortrag vor seinem plötzlichen Tod im Jahr 2018 gelang es Eric McLuhan, Sohn Marshall McLuhans, auf eindrückliche Weise sowohl die Positionen als auch Perspektiven einer bereits mehrere Jahrzehnte umfassenden interdisziplinären und internationalen Media Ecology miteinander zu verknüpfen. Dieses Forschungsfeld thematisiert Medien nicht primär in einer eher traditionellen beziehungsweise konservativen Funktion als Vermittler von Informationen, sondern fokussiert bewusst die materielle und technologische Anwesenheit und Form von Medien innerhalb einer Kultur und betrachtet deren Einfluss auf Psyche und Verhalten von Individuen innerhalb mediatisierter Gesellschaften.
Der Band möchte einen Raum schaffen für die Fortschreibung des McLuhan’schen Denkens im Kontext einer (post-)modernen Media Ecology. Inhaltlich flankiert wird Eric McLuhans hier erstmals im deutschsprachigen Diskurs publizierter Vortrag durch Beiträge von Oliver Ruf und Tobias Held sowie durch ein von Lars C. Grabbe geführtes Interview mit Eric McLuhans Sohn Andrew McLuhan. (Verlagsangaben)
It has been well proved that deep networks are efficient at extracting features from a given (source) labeled dataset. However, it is not always the case that they can generalize well to other (target) datasets which very often have a different underlying distribution. In this report, we evaluate four different domain adaptation techniques for image classification tasks: DeepCORAL, DeepDomainConfusion, CDAN and CDAN+E. These techniques are unsupervised given that the target dataset dopes not carry any labels during training phase. We evaluate model performance on the office-31 dataset. A link to the github repository of this report can be found here: https://github.com/agrija9/Deep-Unsupervised-Domain-Adaptation.
We consider multi-solution optimization and generative models for the generation of diverse artifacts and the discovery of novel solutions. In cases where the domain's factors of variation are unknown or too complex to encode manually, generative models can provide a learned latent space to approximate these factors. When used as a search space, however, the range and diversity of possible outputs are limited to the expressivity and generative capabilities of the learned model. We compare the output diversity of a quality diversity evolutionary search performed in two different search spaces: 1) a predefined parameterized space and 2) the latent space of a variational autoencoder model. We find that the search on an explicit parametric encoding creates more diverse artifact sets than searching the latent space. A learned model is better at interpolating between known data points than at extrapolating or expanding towards unseen examples. We recommend using a generative model's latent space primarily to measure similarity between artifacts rather than for search and generation. Whenever a parametric encoding is obtainable, it should be preferred over a learned representation as it produces a higher diversity of solutions.
Despite their age, ray-based rendering methods are still a very active field of research with many challenges when it comes to interactive visualization. In this thesis, we present our work on Guided High-Quality Rendering, Foveated Ray Tracing for Head Mounted Displays and Hash-based Hierarchical Caching and Layered Filtering. Our system for Guided High-Quality Rendering allows for guiding the sampling rate of ray-based rendering methods by a user-specified Region of Interest (RoI). We propose two interaction methods for setting such an RoI when using a large display system and a desktop display, respectively. This makes it possible to compute images with a heterogeneous sample distribution across the image plane. Using such a non-uniform sample distribution, the rendering performance inside the RoI can be significantly improved in order to judge specific image features. However, a modified scheduling method is required to achieve sufficient performance. To solve this issue, we developed a scheduling method based on sparse matrix compression, which has shown significant improvements in our benchmarks. By filtering the sparsely sampled image appropriately, large brightness variations in areas outside the RoI are avoided and the overall image brightness is similar to the ground truth early in the rendering process. When using ray-based methods in a VR environment on head-mounted display de vices, it is crucial to provide sufficient frame rates in order to reduce motion sickness. This is a challenging task when moving through highly complex environments and the full image has to be rendered for each frame. With our foveated rendering sys tem, we provide a perception-based method for adjusting the sample density to the user’s gaze, measured with an eye tracker integrated into the HMD. In order to avoid disturbances through visual artifacts from low sampling rates, we introduce a reprojection-based rendering pipeline that allows for fast rendering and temporal accumulation of the sparsely placed samples. In our user study, we analyse the im pact our system has on visual quality. We then take a closer look at the recorded eye tracking data in order to determine tracking accuracy and connections between different fixation modes and perceived quality, leading to surprising insights. For previewing global illumination of a scene interactively by allowing for free scene exploration, we present a hash-based caching system. Building upon the concept of linkless octrees, which allow for constant-time queries of spatial data, our frame work is suited for rendering such previews of static scenes. Non-diffuse surfaces are supported by our hybrid reconstruction approach that allows for the visualization of view-dependent effects. In addition to our caching and reconstruction technique, we introduce a novel layered filtering framework, acting as a hybrid method between path space and image space filtering, that allows for the high-quality denoising of non-diffuse materials. Also, being designed as a framework instead of a concrete filtering method, it is possible to adapt most available denoising methods to our layered approach instead of relying only on the filtering of primary hitpoints.
Orešković and Porsdam Mann draw a distinction between ‘fast’ and ‘slow’ science. Whereas the latter involves rigorous and laborious adherence to the scientific method, the former represents the reality that much scientific work faces time pressures which at times force shortcuts. The distinction can be seen to operate in contemporary research into the coronavirus pandemic: whereas the development of vaccines and treatments usually requires years of meticulous laboratory work and several more years of clinical testing, the many millions suffering from the disease need a treatment now. However, by taking too many safeguards off the treatment discovery and testing pipelines, or by refusing to act in accordance with scientific advice, governments risk sacrificing the public’s trust not only in the government’s scientific bona fides but in the scientific process itself. This is a heavy price to pay, argue Orešković and Porsdam Mann, and point to evidence indicating that the success of Germany and Japan in combating COVID-19 can be traced to public trust in science and government, as well as scientifically-informed and respectful national leadership.
Diese etablierte Formelsammlung enthält und erklärt statistische Formeln, wie sie in den Wirtschaftswissenschaften und in der wirtschaftswissenschaftlichen Praxis fundamental notwendig sind. Das Verständnis der Formeln und deren praktische Anwendung werden durch nützliche Hilfen und verständliche Beispiele sinnvoll unterstützt, so dass der Kontext wirtschaftsstatistischer Formeln klar und allgemein verständlich erklärt dargestellt wird. Diese Formelsammlung ist ein unverzichtbares Tool für Studierende der Wirtschaftswissenschaften, aber auch ein nützliches Nachschlagewerk für Verantwortliche aus Wirtschaft, Politik und Lehre. In der 4. Auflage wurden die Inhalte überarbeitet und ergänzt. (Verlagsangaben)
Application of underwater robots are on the rise, most of them are dependent on sonar for underwater vision, but the lack of strong perception capabilities limits them in this task. An important issue in sonar perception is matching image patches, which can enable other techniques like localization, change detection, and mapping. There is a rich literature for this problem in color images, but for acoustic images, it is lacking, due to the physics that produce these images. In this paper we improve on our previous results for this problem (Valdenegro-Toro et al, 2017), instead of modeling features manually, a Convolutional Neural Network (CNN) learns a similarity function and predicts if two input sonar images are similar or not. With the objective of improving the sonar image matching problem further, three state of the art CNN architectures are evaluated on the Marine Debris dataset, namely DenseNet, and VGG, with a siamese or two-channel architecture, and contrastive loss. To ensure a fair evaluation of each network, thorough hyper-parameter optimization is executed. We find that the best performing models are DenseNet Two-Channel network with 0.955 AUC, VGG-Siamese with contrastive loss at 0.949 AUC and DenseNet Siamese with 0.921 AUC. By ensembling the top performing DenseNet two-channel and DenseNet-Siamese models overall highest prediction accuracy obtained is 0.978 AUC, showing a large improvement over the 0.91 AUC in the state of the art.
This exciting and innovative Handbook provides readers with a comprehensive and globally relevant overview of the instruments, actors and design features of social protection systems, as well as their application and impacts in practice. It is the first book that centres around system building globally, a theme that has gained political importance yet has received relatively little attention in academia.
Histogramm
(2021)
HR Management & Leadership
(2021)