OWL2Vec*: embedding of OWL ontologies

Machine Learning - Semantic embedding of knowledge graphs has been widely studied and used for prediction and statistical analysis tasks across various domains such as Natural Language Processing...     

A note on the min-max formulation of stiffness optimization including non-zero prescribed displacements

The present theoretical note shows how a natural objective function in stiffness optimization, including both prescribed forces and non-zero prescribed displacements, is the equilibrium potential energy. It also shows how the resulting problem has a saddle point character that may be utilized when calculating sensitivities.     

Near-Surface Deformation in an Alumina–Silicon Carbide-Whisker Composite due to Surface Machining

Deformation due to two different surface-machining conditions—grinding (126 μm diamond) and polishing (3 μm diamond)—in an uniaxial hot-pressed Al₂O₃–30%-SiC-whisker composite has been investigated. A Warren–Averbach analysis of grazing incidence X-ray diffractometry data shows that the deformation is localized to the very top surface zone. The cell size and the root mean square of the strain show a gradient in the deformed layer. Transmission electron microscopy studies, in cross-sectional view, also show a near-surface deformation zone containing dislocations, twins, and cracks. This is seen for both machining procedures, but the depth of the zone and the degree of deformation, in terms of dislocation density and number of cracks, is much higher in the roughly ground specimen than in the polished one. For comparison, a monolithic Al₂O₃ sample also has been studied after grinding. The deformation zone is very similar to the Al₂O₃–SiC sample with the same grinding condition, but cracks and dislocations are present at a slightly larger depth. The deformation depth for the polished Al₂O₃–SiC sample is ∼50 nm. In the ground Al₂O₃–SiC sample, the deformation depth is 1–1.5 μm and corresponds to the grain size. The deformation zone in the ground monolithic Al₂O₃ sample is 1.5–2 μm deep. The observed grain-boundary cracks are almost parallel to the surface and may originate from nonaccommodated plastic flow between grains.     

Manipulability of leader–follower networks with the rigid-link approximation

This paper introduces the notion of manipulability to mobile, multi-agent networks as a tool to analyze the instantaneous effectiveness of injecting control inputs at certain, so-called leader nodes in the network. Effectiveness is interpreted to characterize how the movements of the leader nodes translate into responses among the remaining follower nodes. This notion of effectiveness is a function of the interaction topologies, the agent configurations, and the particular choice of inputs used to influence the network. In fact, classic manipulability is an index used in robotics to analyze the singularity and efficiency of configurations of robot-arm manipulators. To define similar notions for leader–follower networks, we use a rigid-link approximation of the follower dynamics and, under this assumption, we prove that the instantaneous follower velocities can be uniquely determined from that of the leaders’, which allows us to define a meaningful and computable manipulability index for the leader–follower networks. This paper examines the property of the proposed index in simulation and with real mobile robots, and demonstrates how the index can be used to find effective interaction topologies.     

Energieinformatik

Due to the increasing importance of producing and consuming energy more sustainably, Energy Informatics (EI) has evolved into a thriving research area within the CS/IS community. The article attempts to characterize this young and highly dynamic field of research by describing current EI research topics and methods and provides an outlook of how the field might evolve in the future. It is shown that two general research questions have received the most attention so far and are likely to dominate the EI research agenda in the coming years: How to leverage information and communication technology (ICT) to (1) improve energy efficiency, and (2) to integrate decentralized renewable energy sources into the power grid. Selected EI streams are reviewed, highlighting how the respective research questions are broken down into specific research projects and how EI researchers have made contributions based on their individual academic background.     

Influence of the type of reducing agent (H2, CO,C3H6 and C3H8) on the reduction of stored NO X in a Pt/BaO/Al2O3 model catalyst

In this investigation, a comparative study for a NO _X storage catalytic system was performed focusing on the parameters that affect the reduction by using different reductants (H₂, CO, C₃H₆ and C₃H₈) and different temperatures (350, 250 and 150 °C), for a Pt/BaO/Al₂O₃ catalyst. Transient experiments show that H₂ and CO are highly efficient reductants compared to C₃H₆ which is somewhat less efficient. H₂ shows a significant reduction effect at relatively low temperature (150 °C) but with a low storage capacity. We find that C₃H₈ does not show any NO _X reduction ability for NO _X stored in Pt/BaO/Al₂O₃ at any of the temperatures. The formation of ammonia and nitrous oxide is also discussed.

     

Sulfur deactivation and regeneration of Pt/BaO/Al2O3 and Pt/SrO/Al2O3 NO x storage catalysts

Transient experiments were performed to study sulfur deactivation and regeneration of Pt/BaO/Al₂O₃ and Pt/SrO/Al₂O₃ NO _x storage catalysts. It was found that the strontium-based catalysts are more easily regenerated than the barium-based catalysts and that a higher fraction of the NO _x storage sites are regenerated when H₂ is used in combination with CO₂ compared to H₂ only.     

Sequencing of multi‑robot behaviors using reinforcement learning

Given a collection of parameterized multi-robot controllers associated with individual behaviors designed for particular tasks, this paper considers the problem of how to sequence and instantiate the behaviors for the purpose of completing a more complex, overarching mission. In addition, uncertainties about the environment or even the mission specifications may require the robots to learn, in a cooperative manner, how best to sequence the behaviors. In this paper, we approach this problem by using reinforcement learning to approximate the solution to the computationally intractable sequencing problem, combined with an online gradient descent approach to selecting the individual behavior parameters, while the transitions among behaviors are triggered automatically when the behaviors have reached a desired performance level relative to a task performance cost. To illustrate the effectiveness of the proposed method, it is implemented on a team of differential-drive robots for solving two different missions, namely, convoy protection and object manipulation.     

Effect of artificial aging on intergranular corrosion of extruded AlMgSi alloy with small Cu content

The effect of artificial aging parameters on the corrosion performance of air cooled AlMgSi(Cu) model alloy extrusions was investigated. Accelerated corrosion test revealed that the extrusions were highly susceptible to intergranular corrosion (IGC) in the naturally aged condition. However, IGC susceptibility was reduced, and finally eliminated, by artificial aging. Overaging introduced slight pitting susceptibility. EDS X-ray mapping in FE-TEM revealed Mg₂Si and Q-phase (Al₄Cu₂Mg₈Si₇) grain boundary precipitates and a continuous Cu-enriched grain boundary film. IGC susceptibility was related to the Cu-enriched grain boundary film. Increased IGC resistance was caused by coarsening of the grain boundary film by aging. Pitting susceptibility by over aging evolved due to coarsening of the Q-phase particles in the grain bodies.