Human in the Loop: Interactive Passive Automata Learning via Evidence-Driven State-Merging Algorithms

We present an interactive version of an evidence-driven state-merging (EDSM) algorithm for learning variants of finite state automata. Learning these automata often amounts to recovering or reverse engineering the model generating the data despite noisy, incomplete, or imperfectly sampled data sources rather than optimizing a purely numeric target function. Domain expertise and human knowledge about the target domain can guide this process, and typically is captured in parameter settings. Often, domain expertise is subconscious and not expressed explicitly. Directly interacting with the learning algorithm makes it easier to utilize this knowledge effectively.Comment: 4 pages, presented at the Human in the Loop workshop at ICML 201

Improving Missing Data Imputation with Deep Generative Models

Datasets with missing values are very common on industry applications, and they can have a negative impact on machine learning models. Recent studies introduced solutions to the problem of imputing missing values based on deep generative models. Previous experiments with Generative Adversarial Networks and Variational Autoencoders showed interesting results in this domain, but it is not clear which method is preferable for different use cases. The goal of this work is twofold: we present a comparison between missing data imputation solutions based on deep generative models, and we propose improvements over those methodologies. We run our experiments using known real life datasets with different characteristics, removing values at random and reconstructing them with several imputation techniques. Our results show that the presence or absence of categorical variables can alter the selection of the best model, and that some models are more stable than others after similar runs with different random number generator seeds

Control of fine-structure splitting and excitonic binding energies in selected individual InAs/GaAs quantum dots

A systematic study of the impact of annealing on the electronic properties of single InAs/GaAs quantum dots (QDs) is presented. Single QD cathodoluminescence spectra are recorded to trace the evolution of one and the same QD over several steps of annealing. A substantial reduction of the excitonic fine-structure splitting upon annealing is observed. In addition, the binding energies of different excitonic complexes change dramatically. The results are compared to model calculations within eight-band k.p theory and the configuration interaction method, suggesting a change of electron and hole wave function shape and relative position.Comment: 4 pages, 4 figure

An intercomparison of procedures for the determination of total mercury in seawater and recommendations regarding mercury speciation during GEOTRACES cruises

Author Posting. © Association for the Sciences of Limnology and Oceanography, 2012. This article is posted here by permission of Association for the Sciences of Limnology and Oceanography for personal use, not for redistribution. The definitive version was published in Limnology and Oceanography: Methods 10 (2012): 90-100, doi:10.4319/lom.2012.10.90.We conducted a laboratory intercomparison of total mercury (Hg) determination in seawater collected during U.S. GEOTRACES Intercalibration cruises in 2008 and 2009 to the NW Atlantic and NE Pacific Oceans. Results indicated substantial disagreement between the participating laboratories, which appeared to be affected most strongly by bottle cleanliness and preservation procedures. In addition, we examined the effectiveness of various collection and sample preparation procedures that may be used on future GEOTRACES cruises. The type of sampling system and filtration medium appeared to make little difference to results. Finally, and in light of results from experiments that considered sample bottle material effect and the development of new methods for CH3Hg+ extraction from seawater, we propose a recommended procedure for determining all four of the major Hg species in seawater (elemental, dimethyl-, monomethyl-, and total Hg).This work was supported by the National Science Foundation program in Chemical Oceanography under grants OCE–0825157, –0825108, –0825583 and –0825068

Elemental (im-)miscibility determines phase formation of multinary nanoparticles co-sputtered in ionic liquids

Non-equilibrium synthesis methods allow to alloy bulk-immiscible elements into multinary nanoparticles, which broadens the design space for new materials.Whereas sputtering onto solid substrates can combine immiscible elements into thin film solid solutions, this is not clear for sputtering of nanoparticles in ionicliquids. Thus, the suitability of sputtering in ionic liquids for producing nanoparticles of immiscible elements is investigated by co-sputtering the systems Au-Cu (miscible), Au-Ru and Cu-Ru (both immiscible), and Au-Cu-Ru on the surface of the ionic liquid 1-butyl-3-methylimidazolium bis-trifluoromethylsulfonyl)imide [Bmim][(Tf)2N]. The sputtered nanoparticles were analyzed to obtain (i) knowledge concerning the general formation process ofnanoparticles when sputtering onto ionic liquid surfaces and (ii) information, if alloy nanoparticles of immiscible elements can be synthesized as well as (iii)evidence if the Hume-Rothery rules for solid solubility are valid for sputtered nanoparticles. Accompanying atomistic simulations using density-functional theoryfor clusters of different size and ordering confirm that the miscibility of Au-Cu and the immiscibility of Au-Ru and Cu-Ru govern the thermodynamic stabilityof the nanoparticles. Based on the matching experimental and theoretical results for the NP/IL-systems concerning NP stability, a formation model of multinaryNPs in ILs was developed