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A basic task in the design of an industrial robot application
is the relative placement of robot and workpiece. Process points are defined in Cartesian coordinates relative to the workpiece coordinate system, and the workpiece has to be located such that the robot can reach all points. Finding such a location is still an iterative procedure based on the developers' intuition. One difficulty is the choice of one of the several solutions of the backward transform of a typical 6R robot.
We present a novel algorithm that simultaneously optimizes the workpiece location and the robot configuration at all process points using higher order optimization algorithms. A key ingredient is the extension of the robot with a virtual prismatic axis. The practical feasibility of the approach is shown with an example using a commercial industrial robot.
We present the Regensburg Breast Shape Model (RBSM) – a 3D statistical shape model of the female breast built from 110 breast scans, and the first ever publicly available. Together with the model, a fully automated, pairwise surface registration pipeline used to establish correspondence among 3D breast scans is introduced. Our method is computationally efficient and requires only four landmarks to guide the registration process. In order to weaken the strong coupling between breast and thorax, we propose to minimize the variance outside the breast region as much as possible. To achieve this goal, a novel concept called breast probability masks (BPMs) is introduced. A BPM assigns probabilities to each point of a 3D breast scan, telling how likely it is that a particular point belongs to the breast area. During registration, we use BPMs to align the template to the target as accurately as possible inside the breast region and only roughly outside. This simple yet effective strategy significantly reduces the unwanted variance outside the breast region, leading to better statistical shape models in which breast shapes are quite well decoupled from the thorax. The RBSM is thus able to produce a variety of different breast shapes as independently as possible from the shape of the thorax. Our systematic experimental evaluation reveals a generalization ability of 0.17 mm and a specificity of 2.8 mm for the RBSM. Ultimately, our model is seen as a first step towards combining physically motivated deformable models of the breast and statistical approaches in order to enable more realistic surgical outcome simulation.
Psychiatry" by Ligthart et al. (2021) Ligthart et al. (2021) introduce the idea that "Extended Reality (XR) systems, such as Virtual Reality (VR) and Augmented Reality (AR)," could be used for forensic psychiatry, and then go into detail about considerations that advocate for and against the use of XR systems in forensic psychiatry. Yet, in doing so, they implicitly make presuppositions about the functionality and performance of such systems, which first already seem to be questionable from a technical point of view, understood in a broad sense, but moreover, subsequently have far-reaching significance for a normative assessment of the use of such systems. The following remarks will therefore first describe what Ligthart et al. do not explicitly say about the required technology but must presuppose, and then outline the normative consequences of this omission. In the following, the focus will be placed on virtual reality since the use cases initially mentioned by Ligthart et al. suggest that the authors have also such systems in mind. Presumably, however, the remarks made here can also be applied to Augmented and Extended Reality systems.
While surface kinetics measurements for single atom diffusion have proliferated, little work exists attempting to measure surface dynamics under equilibrium conditions. We will present our recent work on developing Temporal LEED Spectroscopy (TLS) as a dynamic probe of surfaces capable of kinetics measurements at both high temperatures and surface coverages. By tuning the diffraction to specific structural entities such as steps, islands, etc., and monitoring the diffracted signal as a function of time, dynamics information about these structures can be obtained. As an example we will present TLS results for the dynamics of step fluctuations on Si(001) [1]. We have measured activation energies and identified step-edge diffusion as the rate limiting process for 950K < T < 1130K. Although this result is in apparent disagreement with earlier work, a careful analysis, considering crossover temperatures between different microscopic processes, can reconcile the differences. 1. M. Kammler, et al., Phys. Rev. B (in press).
Which influence had the sudden appearance of sound recording, film, and typewriters at the end of the 19th century on the human perception of and our thinking about what we consider “reality”? How did our society change with these technological innovations? After millennia of speech and the culture of writing, a fundamental disruption occurred when Thomas Alva Edison introduced his “phonograph” in 1877. In his book “Grammophon, Film, Typewriter” (Brinkmann & Bose, Berlin 1986), Friedrich Kittler (1943-2011) discusses this question from his perspective as literary scholar and media theorist, reviewing contemporary authors to let them bear witness to their experiences and impressions of the then-new media. This essay intends to be a short extract of Kittler’s book, meandering between additional sources of historians, writers, commentators, yet always coming back to Kittler’s fascinating panopticon.
Mankind has always been confronted with limited knowledge about Nature and many people devoted their lives and intellects to the very question: How to gain knowledge, confirm ideas and theories, and understand the world we live in? Religion was one fundamental base for explanations and existential questions. Philosophy and Science were the other. Nowadays, science and technology dominate our daily lives, religion and metaphysics have lost their former dominance, while our thoughts and factual knowledge are increasingly governed by the digitised versions of conversation and discussion, filtered and guided by the algorithms of social networks. Today, "artificial intelligence" is a phenomenon in information technology which takes over everyday routines. A new ideal, a new promise, and at the same time used as a stratagem by political and economic systems to guide and manipulate our thinking, values, and behaviour. But nothing is so new that one could not find its precursors in earlier times. Science and mathematics has kindled many brilliant ideas. Can we describe the world by numbers, find truth and explanation in mathematical structures? This essay is devoted to early ideas by the medieval philosopher Ramón Llull, the great rationalist G.W. Leibniz, and early approaches to combinations, number theory. and information processing. Llull's thinking machine and subsequent endeavours to find methods of mechanical reasoning and inference paved the way to modern-day concepts of artificial intelligence.
The present paper takes a novel approach to production of fibre-reinforced thermoplastic tubes. The method begins with the raw materials, reinforcing fibre and thermoplastic granulate which are processed to tapes through a newly developed direct impregnation process. It is followed by consolidation of fibre-reinforced thermoplastic tubes using infrared (IR) emitters in the filament winding process. This process employs various angles and utilizes a rotatable consolidation axis. The winding process operates at a constant speed, addressing the challenge of bending the fibre-reinforced tapes in the angle reversal areas near the tube ends. Experiments have confirmed that the process can run at speeds reaching approximately 470 mm/min. The design of the impregnation line takes into account the properties of the thermoplastic and the roving, allowing for a speed of up to 1 m/s.
Many fundamental processes in nature, such as chemical reactions and phase transitions involve rearrangement of the constituent atoms. Such changes cannot be directly measured with visible light and occur transiently on time-scales comparable with the natural oscillation periods of atoms (femtoseconds to picoseconds). We present experiments on Ge-111 films irradiated with 100-fs 800-nm light pulses and probed by a time-delayed sub-ps x-ray pulse at 8 keV. After excitation of a dense electron-hole plasma within the 160-nm film, the ultrafast pathway of lattice disordering is measured as a function laser fluence. For close-to-threshold irradiation, inhomogeneous thermal melting, occurring via surface nucleation of the liquid phase and growth into the bulk determines the dynamics of the solid-to-liquid phase transition. For excitation at about twice the melting threshold, a nonthermal pathway, starting from a highly excited cold solid and relaxing into a hot liquid causes ultrafast melting. At long time delays, nearly perfect recrystallization of a (111) crystal is observed.
Finding the optimal join order (JO) is one of the most important problems in query optimisation, and has been extensively considered in research and practise. As it involves huge search spaces, approximation approaches and heuristics are commonly used, which explore a reduced solution space at the cost of solution quality. To explore even large JO search spaces, we may consider special-purpose software, such as mixed-integer linear programming (MILP) solvers, which have successfully solved JO problems. However, even mature solvers cannot overcome the limitations of conventional hardware prompted by the end of Moore’s law. We consider quantum-inspired digital annealing hardware, which takes inspiration from quantum processing units (QPUs). Unlike QPUs, which likely remain limited in size and reliability in the near and mid-term future, the digital annealer (DA) can solve large instances of mathematically encoded optimisation problems today. We derive a novel, native encoding for the JO problem tailored to this class of machines that substantially improves over known MILP and quantum-based encodings, and reduces encoding size over the state-of-the-art. By augmenting the computation with a novel readout method, we derive valid join orders for each solution obtained by the (probabilistically operating) DA. Most importantly and despite an extremely large solution space, our approach scales to practically relevant dimensions of around 50 relations and improves result quality over conventionally employed approaches, adding a novel alternative to solving the long-standing JO problem.
As global demand for green hydrogen rises, potential hydrogen exporters move into the spotlight. However, the large-scale installation of on-grid hydrogen electrolysis for export can have profound impacts on domestic energy prices and energy-related emissions. Our investigation explores the interplay of hydrogen exports, domestic energy transition and temporal hydrogen regulation, employing a sector-coupled energy model in Morocco. We find substantial co-benets of domestic climate change mitigation and hydrogen exports, whereby exports can reduce domestic electricity prices while mitigation reduces hydrogen export prices. However, increasing hydrogen exports quickly in a system that is still dominated by fossil fuels can substantially raise domestic electricity prices, if green hydrogen production is not regulated. Surprisingly, temporal matching of hydrogen production lowers domestic electricity cost by up to 31% while the effect on exporters is minimal. This policy instrument can steer the welfare (re-)distribution between hydrogen exporting firms, hydrogen importers, and domestic electricity consumers and hereby increases acceptance among actors.