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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

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

Negative carbon dioxide (CO2)-emissions are prevalent in most global emissions pathways that meet the Paris temperature targets and are a critical component for reaching net-zero emissions in Year 2050. However, economic incentives supporting commercialization and deployment of BioEnergy Carbon Capture and Storage (BECCS) are missing. This Policy and Practice Review discusses five different models for creating incentives and financing for BECCS, using Sweden as an example: (1) governmental guarantees for purchasing BECCS outcomes; (2) quota obligation on selected sectors to acquire BECCS outcomes; (3) allowing BECCS credits to compensate for hard-to-abate emissions within the EU ETS; (4) private entities for voluntary compensation; and (5) other states acting as buyers of BECCS outcomes to meet their mitigation targets under the Paris Agreement. We conclude that successful implementation of BECCS is likely to require a combination of several of the Policy Models, implemented in a sequential manner. The governmental guarantee model (Model 1) is likely to be required in the shorter term, so as to establish BECCS. Policy Models 2 and 3 may become more influential over time once BECCS has been established and accepted. Model 3 links BECCS to a large carbon-pricing regime with opportunities for cost-effectiveness and expanded financing. We conclude that Policy Models 4 and 5 are associated with high levels of uncertainty regarding the timing and volume of negative emissions that can be expected—Thus, they are unlikely to trigger BECCS implementation in the short term, although may have roles in the longer term. Based on this study, we recommend that policymakers carefully consider a policy sequencing approach that is predictable and sustainable over time, for which further analyses are required. It is not obvious how such sequencing can be arranged, as the capacities to implement the different Policy Models are vested in different organizations (national governments, EU, private firms). Furthermore, it is important that a BECCS policy is part of an integrated climate policy framework, in particular one that is in line with policies aimed at the mitigation of greenhouse gas (GHG) emissions and the creation of a circular economy. It will be important to ensure that BECCS and the associated biomass resource are not overexploited. A well-designed policy package should guarantee that BECCS is neither used to postpone the reduction of fossil fuel-based emissions nor overused in the short term as a niche business for “greenwashing” while not addressing fossil fuel emissions.

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

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.

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.

AbstractProbabilistic programming is an approach to reasoning under uncertainty by encoding inference problems as programs. In order to solve these inference problems, probabilistic programming languages (PPLs) employ different inference algorithms, such as sequential Monte Carlo (SMC), Markov chain Monte Carlo (MCMC), or variational methods. Existing research on such algorithms mainly concerns their implementation and efficiency, rather than the correctness of the algorithms themselves when applied in the context of expressive PPLs. To remedy this, we give a correctness proof for SMC methods in the context of an expressive PPL calculus, representative of popular PPLs such as WebPPL, Anglican, and Birch. Previous work have studied correctness of MCMC using an operational semantics, and correctness of SMC and MCMC in a denotational setting without term recursion. However, for SMC inference—one of the most commonly used algorithms in PPLs as of today—no formal correctness proof exists in an operational setting. In particular, an open question is if the resample locations in a probabilistic program affects the correctness of SMC. We solve this fundamental problem, and make four novel contributions: (i) we extend an untyped PPL lambda calculus and operational semantics to include explicit resample terms, expressing synchronization points in SMC inference; (ii) we prove, for the first time, that subject to mild restrictions, any placement of the explicit resample terms is valid for a generic form of SMC inference; (iii) as a result of (ii), our calculus benefits from classic results from the SMC literature: a law of large numbers and an unbiased estimate of the model evidence; and (iv) we formalize the bootstrap particle filter for the calculus and discuss how our results can be further extended to other SMC algorithms.