Statistical relational learning of trust

The learning of trust and distrust is a crucial aspect of social interaction among autonomous, mentally-opaque agents. In this work, we address the learning of trust based on past observations and context information. We argue that from the truster’s point of view trust is best expressed as one of several relations that exist between the agent to be trusted (trustee) and the state of the environment. Besides attributes expressing trustworthiness, additional relations might describe commitments made by the trustee with regard to the current situation, like: a seller offers a certain price for a specific product. We show how to implement and learn context-sensitive trust using statistical relational learning in form of a Dirichlet process mixture model called Infinite Hidden Relational Trust Model (IHRTM). The practicability and effectiveness of our approach is evaluated empirically on user-ratings gathered from eBay. Our results suggest that (i) the inherent clustering achieved in the algorithm allows the truster to characterize the structure of a trust-situation and provides meaningful trust assessments; (ii) utilizing the collaborative filtering effect associated with relational data does improve trust assessment performance; (iii) by learning faster and transferring knowledge more effectively we improve cold start performance and can cope better with dynamic behavior in open multiagent systems. The later is demonstrated with interactions recorded from a strategic two-player negotiation scenario.     

Thermodynamic modeling of the C–Pu–U system

The ternary C–Pu–U system is thermodynamically assessed to pursue the development of a thermodynamic database for future nuclear fuels. The substitution model was used for the liquid phase, and a two-sublattice model for the PuC–UC monocarbide, PuC₂–UC₂ dicarbide and Pu₂C₃–U₂C₃ sesquicarbide phases. Ternary interaction parameters were adjusted on the experimental information for the phase relationships. Isoplethal and isothermal ternary sections, as well as some liquidus temperatures are calculated and compared with the experimental data. The overall agreement is discussed, and shows that experimental uncertainties still remain.     

A short and versatile finite element multiscale code for homogenization problems

We describe a multiscale finite element (FE) solver for elliptic or parabolic problems with highly oscillating coefficients. Based on recent developments of the so-called heterogeneous multiscale method (HMM), the algorithm relies on coupled macro- and microsolvers. The framework of the HMM allows to design a code whose structure follows the classical finite elements implementation at the macro level. To account for the fine scales of the problem, elementwise numerical integration is replaced by micro FE methods on sampling domains. We discuss a short and flexible FE implementation of the multiscale algorithm, which can accommodate simplicial or quadrilateral FE and various coupling conditions for the constrained micro simulations. Extensive numerical examples including three dimensional and time dependent problems are presented illustrating the efficiency and the versatility of the computational strategy.     

Efficient moving horizon state and parameter estimation for SMB processes

In this paper, a moving horizon state and parameter estimation scheme for chromatographic simulated moving bed SMB processes is proposed. The simultaneous state and parameter estimation is based on a high-order nonlinear SMB model which incorporates rigorous models of the chromatographic columns and the discrete shiftings of the inlet and outlet ports. The estimation is performed using sparse measurement information: the concentrations of the components are only measured at the two outlet ports (which are periodically switched from one column to the next) and at one fixed location between two columns. The goal is to reconstruct the full state of the system, i.e. the concentration profiles along all columns, and to identify critical model parameters reliably such that the estimated model can be used in the context of online optimizing control. The state estimation scheme is based upon a deterministic model within the prediction horizon, state noise is only present in the state and the parameters prior to and at the beginning of the horizon. By solving the optimization problem with a multiple-shooting method and applying a real-time iteration scheme, the computation times are such that the scheme can be applied online. Numerical simulations of a validated model for a separation problem with nonlinear isotherms of the Langmuir type demonstrate the efficiency of the algorithm.     

Daily impaired detachment and short-term effects of impaired sleep quality on next-day commuting near-accidents – an ambulatory diary study

This study investigated the short-term effects of daily recovery, that is, impaired psychological detachment from work and various actigraphical indicators of sleep quality, on near-accidents when commuting to work the next morning. Furthermore, the mediating effect of actigraphically assessed sleep quality on the relationship between impaired psychological detachment from work and near-accidents when commuting to work was analysed. Fifty-six full-time employees of a Swiss assurance company participated in the one-week study. Multilevel analyses revealed that impaired detachment was highly related to a decrease in sleep duration. Furthermore, impaired daily recovery processes, such as impaired psychological detachment from work and disturbed sleep quality, were related to commuting near-accidents. Impaired sleep quality mediated the effect of impaired psychological detachment from work on these near-accidents. Our results show that occupational safety interventions should address both impaired psychological detachment from work and sleep quality in order to prevent near accidents when commuting to work.

Practitioner Summary: Commuting accidents occur frequently and have detrimental effects on employees, organisations and society. This study shows that daily lack of recovery, that is, impaired psychological detachment and impaired sleep quality, is related to near-accidents when commuting to work the next morning. Primary prevention of commuting accidents should therefore address daily lack of recovery.     

Study on TSV isolation liners for a Via Last approach with the use in 3D-WLP for MEMS

This paper discusses approaches for the isolation of deep high aspect ratio through silicon vias (TSV) with respect to a Via Last approach for micro-electro-mechanical systems (MEMS). Selected TSV samples have depths in the range of 170…270 µm and a diameter of 50 µm. The investigations comprise the deposition of different layer stacks by means of subatmospheric and plasma enhanced chemical vapour deposition (PECVD) of tetraethyl orthosilicate; Si(OC₂H₅)₄ (TEOS). Moreover, an etch-back approach and the selective deposition on SiN were also included in the investigations. With respect to the Via Last approach, the contact opening at the TSV bottom by means of a specific spacer-etching method have been addressed within this paper. Step coverage values of up to 74 % were achieved for the best of those approaches. As an alternative to the SiO₂-isolation liners a polymer coating based on the CVD of Parylene F was investigated, which yields even higher step coverage in the range of 80 % at the lower TSV sidewall for a surface film thickness of about 1000 nm. Leakage current measurements were performed and values below 0.1 nA/cm² at 10 kV/cm were determined for the Parylene F films which represents a promising result for the aspired application to Via Last MEMS-TSV.     

A complete strategy for efficient and accurate multibody dynamics of flexible structures with large lap joints considering contact and friction

This paper deals with the dynamics of jointed flexible structures in multibody simulations. Joints are areas where the surfaces of substructures come into contact, for example, screwed or bolted joints. Depending on the spatial distribution of the joint, the overall dynamic behavior can be influenced significantly. Therefore, it is essential to consider the nonlinear contact and friction phenomena over the entire joint. In multibody dynamics, flexible bodies are often treated by the use of reduction methods, such as component mode synthesis (CMS). For jointed flexible structures, it is important to accurately compute the local deformations inside the joint in order to get a realistic representation of the nonlinear contact and friction forces. CMS alone is not suitable for the capture of these local nonlinearities and therefore is extended in this paper with problem-oriented trial vectors. The computation of these trial vectors is based on trial vector derivatives of the CMS reduction base. This paper describes the application of this extended reduction method to general multibody systems, under consideration of the contact and friction forces in the vector of generalized forces and the Jacobian. To ensure accuracy and numerical efficiency, different contact and friction models are investigated and evaluated. The complete strategy is applied to a multibody system containing a multilayered flexible structure. The numerical results confirm that the method leads to accurate results with low computational effort.     

Optimal design of a three tape-spring hinge deployable space structure using an experimentally validated physics-based model

An optimal design approach is developed for a self-driven, self-locking tape-spring under a pure bending load in deployable space structures. A novel hinge with three tape springs is investigated and designed via an optimization process. Firstly, we investigate the steady-state moment and maximum stress of the hinge during deploying and folding processes using physics-based simulations. Experimental analyses are then conducted to verify the physics-based simulation results. Secondly, a parametric analysis is carried out to prove that both the tape spring thickness and subtended angle have significant effect on steady-state moment. A Response Surface Methodology (RSM) is employed to define an optimal surrogate model aimed at maximizing the steady-state moment, subjected to allowable stress. Finally, the Large Scale Generalized Reduced Gradient (LSGRG) optimization algorithm is used to solve the optimal design problem. Optimization results show that steady-state moment is increased by 19.5% while satisfying a maximum stress constraint. The proposed method is promising for designing novel deployable structures with high stability and reliability.