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QC 20221219

In this paper, we aim towards providing a practical framework for learning to satisfy signal temporal logic (STL) task specifications for systems with partially unknown dynamics. We consider STL tasks whose satisfaction can be guaranteed by enforcing a priori known temporal specifications imposed on the atomic propositions that compose them. First, a neural network is trained offline as a control policy to satisfy such temporal specifications while also minimizing a target cost, such as the input energy of the system. The obtained controller then serves as a guide that aids exploration while learning to satisfy any specific STL task optimally using policy improvement, greatly increasing the sample efficiency of the procedure. The promise of the approach towards a versatile STL learning framework is demonstrated through simulations.  QC 20201125

We present an online API to access a number of Natural Language Processing services developed at KTH. The services work on Swedish text. They include tokenization, part-of-speech tagging, shallow parsing, compound word analysis, word inflection, lemmatization, spelling error detection and correction, grammar checking, and more. The services can be accessed in several ways, including a RESTful interface, direct socket communication, and premade Web forms. The services are open to anyone. The source code is also freely available making it possible to set up another server or run the tools locally. We have also evaluated the performance of several of the services and compared them to other available systems. Both the precision and the recall for the Granska grammar checker are higher than for both Microsoft Word and Google Docs. The evaluation also shows that the recall is greatly improved when combining all the grammar checking services in the API, compared to any one method, and combining services is made easy by the API.

This paper provides a study of a workshop which invited composers, musicians, and sound designers to explore instruments from the history of electronic sound in Sweden. The workshop participants applied media archaeology methods towards analyzing one particular instrument from the past, the Dataton System 3000. They then applied design fiction methods towards imagining several speculative instruments of the future. Each stage of the workshop revealed very specific utopian ideas surrounding the design of sound instruments. After introducing the background and methods of the workshop, the authors present an overview and thematic analysis of the workshop's outcomes. The paper concludes with some reflections on the use of this method-in-progress for investigating the ethics and affordances of historical electronic sound instruments. It also suggests the significance of ethics and affordances for the design of contemporary instruments. QC 20210804

The design of optimal energy management strategies that trade-off consumers' privacy and expected energy cost by using an energy storage is studied. The Kullback-Leibler divergence rate is used to assess the privacy risk of the unauthorized testing on consumers' behavior. We further show how this design problem can be formulated as a belief state Markov decision process problem so that standard tools of the Markov decision process framework can be utilized, and the optimal solution can be obtained by using Bellman dynamic programming. Finally, we illustrate the privacy-enhancement and cost-saving by numerical examples.  Part of proceedings ISBN 978-1-5386-1571-3QC 20220923

The conducting polymer poly(3,4-ethylenedioxythiophene), or PEDOT, is an attractive material for flexible electronics. We present combined molecular dynamics and quantum chemical calculations, based on density functional theory, of EDOT oligomers and isoelectronic selenium and tellurium derivatives (EDOS and EDOTe) to address the effect of temperature on the geometrical and electronic properties of these systems. With finite size scaling, we also extrapolate our results to the infinite polymers, i.e., PEDOT, PEDOS, and PEDOTe. Our computations indicate that the most favourable oligomer conformations at finite temperature are conformations around the flat trans-conformation and a non-flat conformation around 45° from the cis-conformation. Also, the dihedral stiffness increases with the atomic number of the heteroatom. We find excellent agreement with experimentally measured gaps for PEDOT and PEDOS. For PEDOT, the gap does not increase with temperature, whereas this is the case for its derivatives. The conformational disorder and the choice of the basis set both significantly affect the calculated gaps.

Ohmic CoSi2 contacts to n-type 4H-SiC showing low contact resistance have been made by sputter depositing sequential layers of Si and Co on 4H-SiC substrates followed by a two-step rapid thermal anneal at 600 °C and 950 °C. The contacts formed have been characterized at temperatures ranging from-40 °C to 500 °C with a specific contact resistance of 3.80∙10-5 Ωcm2 at 25 °C and a minimum of 6.0∙10-6 Ωcm2 at 500 °C.

Integration of functional materials and structures on the tips of optical fibers has enabled various applications in micro-optics, such as sensing, imaging, and optical trapping. Direct laser writing is a 3D printing technology that holds promise for fabricating advanced micro-optical structures on fiber tips. To date, material selection has been limited to organic polymer-based photoresists because existing methods for 3D direct laser writing of inorganic materials involve high-temperature processing that is not compatible with optical fibers. However, organic polymers do not feature stability and transparency comparable to those of inorganic glasses. Herein, we demonstrate 3D direct laser writing of inorganic glass with a subwavelength resolution on optical fiber tips. We show two distinct printing modes that enable the printing of solid silica glass structures (“Uniform Mode”) and self-organized subwavelength gratings (“Nanograting Mode”), respectively. We illustrate the utility of our approach by printing two functional devices: (1) a refractive index sensor that can measure the indices of binary mixtures of acetone and methanol at near-infrared wavelengths and (2) a compact polarization beam splitter for polarization control and beam steering in an all-in-fiber system. By combining the superior material properties of glass with the plug-and-play nature of optical fibers, this approach enables promising applications in fields such as fiber sensing, optical microelectromechanical systems (MEMS), and quantum photonics. QC 20240425

Group-based control is an advanced traffic signal strategy capable of dynamically generating phase sequences at intersections. Combined with the phasing scheme, vehicle actuated timing is often adopted to respond to the detected traffic. However, the parameters of a signal controller are often predetermined in practice, and the control performance may suffer from deterioration when dealing with highly fluctuating traffic demand. This study proposes a group-based signal control approach capable of making decisions based on its understanding of traffic conditions at the intersection level. In particular, the control problem is formulated using a framework of stochastic optimal control for multi-agent system in which each signal group is modeled as an intelligent agent. The agents learn how to react to traffic environment and make optimal timing decisions according to the perceived system states. Reinforcement learning, enhanced by multiple-step backups, is employed as the kernel of the intelligent control algorithm, where each agent updates its knowledge on-line based on a sequence of states during the process. In addition, the proposed system is designated to be compatible with the prevailing signal system. A case study was carried out in a simulation environment to compare the proposed control approach with a benchmark controller used in practice, group-based vehicle actuated (GBVA) controller, whose parameters were off-line optimized using a genetic algorithm. Simulation results show that the proposed adaptive group-based control system outperforms the optimized GBVA control system mainly because of its real-time adaptive learning capacity in response to the changes in traffic demand. QC 20180514