Discovering interacting artifacts from ERP systems (extended version)

The omnipresence of using Enterprise Resource Planning (ERP) systems to support business processes has enabled recording a great amount of (relational) data which contains information about the behaviors of these processes. Various process mining techniques have been proposed to analyze recorded information about process executions. However, classic process mining techniques generally require a linear event log as input and not a multi-dimensional relational database used by ERP systems. Much research has been conducted into converting a relational data source into an event log. Most conversion approaches found in literature usually assume a clear notion of a case and a unique case identifier in an isolated process. This assumption does not hold in ERP systems where processes comprise the life-cycles of various interrelated data objects, instead of a single process. In this paper, a new semi-automatic approach is presented to discover from the plain database of an ERP system the various objects supporting the system. More precisely, we identify an artifact-centric process model describing the system’s objects, their life-cycles, and detailed information about how the various objects synchronize along their life-cycles, called interactions. In addition, our artifact-centric approach helps to eliminate ambiguous dependencies in discovered models caused by the data divergence and convergence problems and to identify the exact "abnormal flows". The presented approach is implemented and evaluated on two processes of ERP systems through case studies

De relatie tussen stikstofopname en gewasreflectie bij vijf buitenbloemen

Bij buitenbloemen is er een grote variatie aan gewassen. Het is daarom niet mogelijk om voor ieder gewas afzonderlijk bemestingsonderzoek uit te voeren. Een N -opnamecurve is een belangrijk hulpmiddel bij het ontwikkelen van bijmestsystemen. Onderzoek is gedaan naar de mogelijkheid om met non-destructieve middelen, o.a. refelectiemetingen, iets te zeggen over de vorm van de N-opnamecurve bij een vijftal gewassen, die representatief zijn voor een groot deel van het sortimen

Calculating flux to predict future cave radon concentrations

Cave radon concentration measurements reflect the outcome of a perpetual competition which pitches flux against ventilation and radioactive decay. The mass balance equations used to model changes in radon concentration through time routinely treat flux as a constant. This mathematical simplification is acceptable as a first order approximation despite the fact that it sidesteps an intrinsic geological problem: the majority of radon entering a cavity is exhaled as a result of advection along crustal discontinuities whose motions are inhomogeneous in both time and space. In this paper the dynamic nature of flux is investigated and the results are used to predict cave radon concentration for successive iterations. The first part of our numerical modelling procedure focuses on calculating cave air flow velocity while the second part isolates flux in a mass balance equation to simulate real time dependence among the variables. It is then possible to use this information to deliver an expression for computing cave radon concentration for successive iterations. The dynamic variables in the numerical model are represented by the outer temperature, the inner temperature, and the radon concentration while the static variables are represented by the radioactive decay constant and a range of parameters related to geometry of the cavity. Input data were recorded at Driny Cave in the Little Carpathians Mountains of western Slovakia. Here the cave passages have developed along splays of the NE–SW striking Smolenice Fault and a series of transverse faults striking NW–SE. Independent experimental observations of fault slip are provided by three permanently installed mechanical extensometers. Our numerical modelling has revealed four important flux anomalies between January 2010 and August 2011. Each of these flux anomalies was preceded by conspicuous fault slip anomalies. The mathematical procedure outlined in this paper will help to improve our understanding of radon migration along crustal discontinuities and its subsequent exhalation into the atmosphere. Furthermore, as it is possible to supply the model with continuous data, future research will focus on establishing a series of underground monitoring sites with the aim of generating the first real time global radon flux maps.The authors would like to thank Peter Zvonár, Sara Argerich-Bergada, Amanda Keen-Zebert, Lenka Thinová, and Petr Otáhal as well as the reviewers whose constructive comments have helped to improve the clarity of the manuscript. This study was conducted with support from the long term conceptual development research organisation RVO: 67985891. It is published in the framework of CzechGeo-EPOS “Distributed system of permanent observatory measurements and temporary monitoring of geophysical fields in the Czech Republic” (MŠMT Project: LM2010008).Peer reviewe

Josephson supercurrent in a topological insulator without a bulk shunt

A Josephson supercurrent has been induced into the three-dimensional topological insulator Bi1.5Sb0.5Te1.7Se1.3. We show that the transport in Bi1.5Sb0.5Te1.7Se1.3 exfoliated flakes is dominated by surface states and that the bulk conductivity can be neglected at the temperatures where we study the proximity induced superconductivity. We prepared Josephson junctions with widths in the order of 40 nm and lengths in the order of 50 to 80 nm on several Bi1.5Sb0.5Te1.7Se1.3 flakes and measured down to 30 mK. The Fraunhofer patterns unequivocally reveal that the supercurrent is a Josephson supercurrent. The measured critical currents are reproducibly observed on different devices and upon multiple cooldowns, and the critical current dependence on temperature as well as magnetic field can be well explained by diffusive transport models and geometric effects

Singlet-triplet transition in a single-electron transistor at zero magnetic field

We report sharp peaks in the differential conductance of a single-electron transistor (SET) at low temperature, for gate voltages at which charge fluctuations are suppressed. For odd numbers of electrons we observe the expected Kondo peak at zero bias. For even numbers of electrons we generally observe Kondo-like features corresponding to excited states. For the latter, the excitation energy often decreases with gate voltage until a new zero-bias Kondo peak results. We ascribe this behavior to a singlet-triplet transition in zero magnetic field driven by the change of shape of the potential that confines the electrons in the SET.Comment: 4 p., 4 fig., 5 new ref. Rewrote 1st paragr. on p. 4. Revised author list. More detailed fit results on page 3. A plotting error in the horizontal axis of Fig. 1b and 3 was corrected, and so were the numbers in the text read from those fig. Fig. 4 was modified with a better temperature calibration (changes are a few percent). The inset of this fig. was removed as it is unnecessary here. Added remarks in the conclusion. Typos are correcte

The JCMT Spectral Legacy Survey: physical structure of the molecular envelope of the high-mass protostar AFGL2591

The understanding of the formation process of massive stars (>8 Msun) is limited, due to theoretical complications and observational challenges. We investigate the physical structure of the large-scale (~10^4-10^5 AU) molecular envelope of the high-mass protostar AFGL2591 using spectral imaging in the 330-373 GHz regime from the JCMT Spectral Legacy Survey. Out of ~160 spectral features, this paper uses the 35 that are spatially resolved. The observed spatial distributions of a selection of six species are compared with radiative transfer models based on a static spherically symmetric structure, a dynamic spherical structure, and a static flattened structure. The maps of CO and its isotopic variations exhibit elongated geometries on scales of ~100", and smaller scale substructure is found in maps of N2H+, o-H2CO, CS, SO2, CCH, and methanol lines. A velocity gradient is apparent in maps of all molecular lines presented here, except SO, SO2, and H2CO. We find two emission peaks in warm (Eup~200K) methanol separated by 12", indicative of a secondary heating source in the envelope. The spherical models are able to explain the distribution of emission for the optically thin H13CO+ and C34S, but not for the optically thick HCN, HCO+, and CS, nor for the optically thin C17O. The introduction of velocity structure mitigates the optical depth effects, but does not fully explain the observations, especially in the spectral dimension. A static flattened envelope viewed at a small inclination angle does slightly better. We conclude that a geometry of the envelope other than an isotropic static sphere is needed to circumvent line optical depth effects. We propose that this could be achieved in envelope models with an outflow cavity and/or inhomogeneous structure at scales smaller than ~10^4 AU. The picture of inhomogeneity is supported by observed substructure in at least six species.Comment: 17 pages; accepted for publication in A&

Semi-parametric Expected Shortfall Forecasting

Intra-day sources of data have proven effective for dynamic volatility and tail risk estimation. Expected shortfall is a tail risk measure, that is now recommended by the Basel Committee, involving a conditional expectation that can be semi-parametrically estimated via an asymmetric sum of squares function. The conditional autoregressive expectile class of model, used to indirectly model expected shortfall, is generalised to incorporate information on the intra-day range. An asymmetric Gaussian density model error formulation allows a likelihood to be developed that leads to semiparametric estimation and forecasts of expectiles, and subsequently of expected shortfall. Adaptive Markov chain Monte Carlo sampling schemes are employed for estimation, while their performance is assessed via a simulation study. The proposed models compare favourably with a large range of competitors in an empirical study forecasting seven financial return series over a ten year period