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The Scarab Project
(2015)
Urban Search and Rescue (USAR) is an active research
field in the robotics community. Despite recent advances
for many open research questions, these kind of systems are
not widely used in real rescue missions. One reason is that such
systems are complex and not (yet) very reliable; another is that
one has to be an robotic expert to run such a system. Moreover,
available rescue robots are very expensive and the benefits of
using them are still limited.
In this paper, we present the Scarab robot, an alternative
design for a USAR robot. The robot is light weight, humanpackable
and its primary purpose is that of extending the
rescuer’s capability to sense the disaster site. The idea is that a
responder throws the robot to a certain spot. The robot survives
the impact with the ground and relays sensor data such as
camera images or thermal images to the responder’s hand-held
control unit from which the robot can be remotely controlled.
We present a new approach to the problem of optimal control of solar sails for low-thrust trajectory optimization. The objective was to find the required control torque magnitudes in order to steer a solar sail in interplanetary space. A new steering strategy, controlling the solar sail with generic torques applied about the spacecraft body axes, is integrated into the existing low-thrust trajectory optimization software InTrance. This software combines artificial neural networks and evolutionary algorithms to find steering strategies close to the global optimum without an initial guess. Furthermore, we implement a three rotational degree-of-freedom rigid-body attitude dynamics model to represent the solar sail in space. Two interplanetary transfers to Mars and Neptune are chosen to represent typical future solar sail mission scenarios. The results found with the new steering strategy are compared to the existing reference trajectories without attitude dynamics. The resulting control torques required to accomplish the missions are investigated, as they pose the primary requirements to a real on-board attitude control system.
Solar sails provide ignificant advantages over other low-thrust propulsion systems because they produce thrust by the momentum exchange from solar radiation pressure (SRP) and thus do not consume any propellant.The force exerted on a very thin sail foil basically depends on the light incidence angle. Several analytical SRP force models that describe the SRP force acting on the sail have been established since the 1970s. All the widely used models use constant optical force coefficients of the reflecting sail material. In 2006,MENGALI et al. proposed a refined SRP force model that takes into account the dependancy of the force coefficients on the light incident angle,the sail’s distance from the sun (and thus the sail emperature) and the surface roughness of the sail material [1]. In this paper, the refined SRP force model is compared to the previous ones in order to identify the potential impact of the new model on the predicted capabilities of solar sails in performing low-cost interplanetary space missions. All force models have been implemented within InTrance, a global low-thrust trajectory optimization software utilizing evolutionary neurocontrol [2]. Two interplanetary rendezvous missions, to Mercury and the near-Earth asteroid 1996FG3, are investigated. Two solar sail performances in terms of characteristic acceleration are examined for both scenarios, 0.2 mm/s2 and 0.5 mm/s2, termed “low” and “medium” sail performance. In case of the refined SRP model, three different values of surface roughness are chosen, h = 0 nm, 10 nm and 25 nm. The results show that the refined SRP force model yields shorter transfer times than the standard model.
Disruption experiments targeted at the Bacillus licheniformis degSU operon and GFP-reporter analysis provided evidence for promoter activity immediately upstream of degU. pMutin mediated concomitant introduction of the degU32 allele – known to cause hypersecretion in Bacillus subtilis – resulted in a marked increase in protease activity. Application of 5-fluorouracil based counterselection through establishment of a phosphoribosyltransferase deficient Δupp strain eventually facilitated the marker-free introduction of degU32 leading to further protease enhancement achieving levels as for hypersecreting wild strains in which degU was overexpressed. Surprisingly, deletion of rapG – known to interfere with DegU DNA-binding in B. subtilis – did not enhance protease production neither in the wild type nor in the degU32 strain. The combination of degU32 and Δupp counterselection in the type strain is not only equally effective as in hypersecreting wild strains with respect to protease production but furthermore facilitates genetic strain improvement aiming at biological containment and effectiveness of biotechnological processes.
The growing body of political texts opens up new opportunities for rich insights into political dynamics and ideologies but also increases the workload for manual analysis. Automated speaker attribution, which detects who said what to whom in a speech event and is closely related to semantic role labeling, is an important processing step for computational text analysis. We study the potential of the large language model family Llama 2 to automate speaker attribution in German parliamentary debates from 2017-2021. We fine-tune Llama 2 with QLoRA, an efficient training strategy, and observe our approach to achieve competitive performance in the GermEval 2023 Shared Task On Speaker Attribution in German News Articles and Parliamentary Debates. Our results shed light on the capabilities of large language models in automating speaker attribution, revealing a promising avenue for computational analysis of political discourse and the development of semantic role labeling systems.
The growing body of political texts opens up new opportunities for rich insights into political dynamics and ideologies but also increases the workload for manual analysis. Automated speaker attribution, which detects who said what to whom in a speech event and is closely related to semantic role labeling, is an important processing step for computational text analysis. We study the potential of the large language model family Llama 2 to automate speaker attribution in German parliamentary debates from 2017-2021. We fine-tune Llama 2 with QLoRA, an efficient training strategy, and observe our approach to achieve competitive performance in the GermEval 2023 Shared Task On Speaker Attribution in German News Articles and Parliamentary Debates. Our results shed light on the capabilities of large language models in automating speaker attribution, revealing a promising avenue for computational analysis of political discourse and the development of semantic role labeling systems.
Lightning safety guidelines
(2010)
A High-Throughput Functional Complementation Assay for Classification of BRCA1 Missense Variants
(2013)
[{ReN(PMe2Ph)3}{ReO3N}]2 – Structural Evidence for the Nitridotrioxorhenate(VII) Anion, [ReO3N]2−
(2005)
This thesis introduces the Integrated Emitter Turn-Off (IETO) Thyristor as a new high-power device. Known state-of-the-art research activities like the Dual GCT, the ETO thyristor and the ICT were presented and critically reviewed. A comparison with commercialized solutions identifies the pros and cons of each type of device family. Based on this analysis, the IETO structure is proposed, covering most benefits of each device class. In particular the combination of a MOS-assisted turn-off with a thyristor-based device allows a voltage-controlled MOS switching and the low on-state voltage of the thyristors. The following synthesis of an IETO device stands on a three-dimensional field of optimization spanned by electric, mechanical and thermal aspects. From an electric point of view, the lowest possible parasitic inductance and resistance within the commutation path are optimization criteria. The mechanical construction has to withstand the required contact pressure of multiple kilo Newtons. Finally, thermal borders limit the maximum average current of the device. FEM simulations covering these three aspects are performed for several design proposals. An IETO prototype is constructed and measurements on various test benches attest thermal, mechanical and electric performance. A local decoupling of the external driver stage and the presspack housing is presented by a cable connection. This separation enables a thermal and mechanical independence, which is advantageous in terms of vibrations and thermal cycles including increased reliability. The electric pulse performance of the prototype device is a factor of 3.1 above today''s solutions. In single-pulse measurements, a current up to 1600 A was successfully turned off at 115°C with an active silicon area of 823 mm². One reason for this increased turn-off capability is the extremely low-inductive construction. Additional functionality of the IETO thyristor like over-current self-protection and defined short-circuit failure state are successfully verified.
Motivation-based Learning: Teaching Fundamentals of Electrical Engineering with an LED Spinning Top
(2018)
The continuously growing amount of renewable sources starts compromising the stability of electrical grids. Contradictory to fossil fuel power plants, energy production of wind and photovoltaic (PV) energy is fluctuating. Although predictions have significantly improved, an outage of multi-MW offshore wind farms poses a challenging problem. One solution could be the integration of storage systems in the grid. After a short overview, this paper focuses on two exemplary battery storage systems, including the required power electronics. The grid integration, as well as the optimal usage of volatile energy reserves, is presented for a 5- kW PV system for home application, as well as for a 100- MW medium-voltage system, intended for wind farm usage. The efficiency and cost of topologies are investigated as a key parameter for large-scale integration of renewable power at medium- and low-voltage.
This paper presents the latest prototype of the integrated emitter turn-off thyristor concept, which potentially ranks among thyristor high-power devices like the gate turn-off thyristor and the integrated gate-commutated thyristor (IGCT). Due to modifications of the external driver stage and mechanical press-pack design optimization, this prototype allows for full device characterization. The turn-off capability was increased to 1600 A with an active silicon area of 823mm2 . This leads to a transient peak power of 672.1kW/cm² . Within this paper, measurements and concept assessment are presented and a comparison to state-of-the-art IGCT devices is provided.
Physical layer specification of the L-band Digital Aeronautical Communications System (L-DACS1)
(2009)
The fourth industrial revolution introduces disruptive technologies to production environments. One of these technologies are multi-agent systems (MASs), where agents virtualize machines. However, the agent's actual performances in production environments can hardly be estimated as most research has been focusing on isolated projects and specific scenarios. We address this gap by implementing a highly connected and configurable reference model with quantifiable key performance indicators (KPIs) for production scheduling and routing in single-piece workflows. Furthermore, we propose an algorithm to optimize the search of extrema in highly connected distributed systems. The benefits, limits, and drawbacks of MASs and their performances are evaluated extensively by event-based simulations against the introduced model, which acts as a benchmark. Even though the performance of the proposed MAS is, on average, slightly lower than the reference system, the increased flexibility allows it to find new solutions and deliver improved factory-planning outcomes. Our MAS shows an emerging behavior by using flexible production techniques to correct errors and compensate for bottlenecks. This increased flexibility offers substantial improvement potential. The general model in this paper allows the transfer of the results to estimate real systems or other models.
Next Generation Manufacturing promises significant improvements in performance, productivity, and value creation. In addition to the desired and projected improvements regarding the planning, production, and usage cycles of products, this digital transformation will have a huge impact on work, workers, and workplace design. Given the high uncertainty in the likelihood of occurrence and the technical, economic, and societal impacts of these changes, we conducted a technology foresight study, in the form of a real-time Delphi analysis, to derive reliable future scenarios featuring the next generation of manufacturing systems. This chapter presents the organization dimension and describes each projection in detail, offering current case study examples and discussing related research, as well as implications for policy makers and firms. Specifically, we highlight seven areas in which the digital transformation of production will change how we work, how we organize the work within a company, how we evaluate these changes, and how employment and labor rights will be affected across company boundaries. The experts are unsure whether the use of collaborative robots in factories will replace traditional robots by 2030. They believe that the use of hybrid intelligence will supplement human decision-making processes in production environments. Furthermore, they predict that artificial intelligence will lead to changes in management processes, leadership, and the elimination of hierarchies. However, to ensure that social and normative aspects are incorporated into the AI algorithms, restricting measurement of individual performance will be necessary. Additionally, AI-based decision support can significantly contribute toward new, socially accepted modes of leadership. Finally, the experts believe that there will be a reduction in the workforce by the year 2030.