Detecting Branching Condition Changes in Process Models

Business processes are continuously evolving in order to adapt to changes due to various factors. One important process drift perspective yet to be investigated is the detection of branching condition changes in the process model. None of the existing process drift detection methods focus on detecting changes of branching conditions in process models. Existing branching condition detection methods do not take changes within the process into account, hence results are inadequate to represent the changes of decision criteria of the process. In this paper, we present a method which can detect branching condition changes in process models. The method takes both process models and event logs as input, and translates event logs into decision sequences for change points detection. The proposed method is evaluated by simulated event logs.

Benchmark tests for separating n time components of runoff with one stable isotope tracer

A validation of the recently introduced iterative extension of the standard two-component hydrograph separation method is presented. The data for testing this method are retrieved from a random rainfall generator and a rainfall-runoff model composed of linear reservoirs. The results show that it is possible to reconstruct the simulated event water response of a given random model input by applying the iterative separation model and using a single stable isotope tracer. The benchmark model also covers the partially delayed response of event water so that a situation can be simulated in which pre-event water is rapidly mobilized. It is demonstrated how mathematical constraints, such as an ill-conditioned linear equation system, may influence the separation of the event water response. In addition, it is discussed how the volume weighted separated event water response can serve as an estimator for a time-varying backward travel time distribution.

Validation of a Physics Based Three Phonon Scattering Algorithm Implemented in the Statistical Phonon Transport Model

Three phonon scattering is the primary mechanism by which phonon transport is impeded in insulating and semiconducting bulk materials. Accurate computational modeling of this scattering mechanism is required for high fidelity simulations of thermal transport across the ballistic (quantum mechanics) to Fourier (continuum mechanics) range of behavior. Traditional Monte Carlo simulations of phonon transport use a scaling factor such that each scattering event is considered representative of a large number of phonons, often on the order of 104 physical phonons per simulated event. The ability to account for every phonon scattering event is desirable to enhance model fidelity. A physics-based model using time dependent perturbation theory (Fermi’s Golden Rule) is implemented to compute three phonon scattering rates for each permissible phonon interaction subject to selection rules. The strength of the interaction is based on use of a Gruneisen-like parameter. Both Type I and Type II scattering rates are computed for the allowable interactions that conserve energy and momentum (up to the addition of a reciprocal lattice vector) on a given discretization of momentum space. All of the phonons in the computational domain are represented and phonon populations are updated in momentum space and real space based on the computed number of phonons involved in given scattering events. The computational algorithm is tested in an adiabatic single cell of silicon of dimension 100 × 100 × 100 nm at a nominal temperature of 500 Kelvin containing approximately 108 fully anisotropic phonons. The results indicate that phonon populations return to equilibrium if artificially displaced from that condition. Two approaches are introduced to model the relaxation time of phonon states: the single mode relaxation time (SMRT) which is consistent with the underlying assumptions for previously reported theoretical estimates, and the multi model relaxation time (MMRT) which is more consistent with in-situ conditions. The trends meet physical expectations and are comparable to other literature results. In addition, an estimate of error associated with the relaxation times is presented using the statistical nature of the model. The three phonon scattering model presented provides a high fidelity representation of this physical process that improves the computational prediction of anisotropic phonon transport in the statistical phonon transport model.

Assessing crowd management strategies for the 2010 Love Parade disaster using computer simulations and virtual reality

Dense crowds in public spaces have often caused serious security issues at large events. In this paper, we study the 2010 Love Parade disaster, for which a large amount of data (e.g. research papers, professional reports and video footage) exist. We reproduce the Love Parade disaster in a three-dimensional computer simulation calibrated with data from the actual event and using the social force model for pedestrian behaviour. Moreover, we simulate several crowd management strategies and investigate their ability to prevent the disaster. We evaluate these strategies in virtual reality (VR) by measuring the response and arousal of participants while experiencing the simulated event from a festival attendee’s perspective. Overall, we find that opening an additional exit and removing the police cordons could have significantly reduced the number of casualties. We also find that this strategy affects the physiological responses of the participants in VR.

Evaluation of two automated inundation-mapping methods

<p>Flash Floods cause significant material and human damage worldwide. In France, they frequently hit small rivers of the Mediterranean area, often inducing catastrophic consequences.</p><p>Considering the large number of possibly affected small watercourses, the use of automated flood-mapping methods may be of great help for the identification of the possibly affected areas and the prediction of the potential consequences of this type of floods.</p><p>In 2019, a first evaluation of three automated inundation-mapping methods, directly implemented on high-resolution Digital Terrain Models (DTM) was presented (https://meetingorganizer.copernicus.org/EGU2019/EGU2019-15710-1.pdf). The automatically retrieved flood extent maps were compared with simulated reference maps from local expert studies.        </p><p>As a continuation of this work, an application of the two best performing of these methods (1D caRtino approach and 2D Floodos approach), is presented here for the simulation of  three recent flash flood events:</p><ul><li>The 15<sup>th</sup> of June 2010 flood on the Argens watershed: 25 deaths, more than 1 billion € of economic damage, 585 km of affected and simulated rivers.</li> <li>The 3<sup>rd </sup>– 4<sup>th,</sup> of october 2015 floods in the French Riviera: 20 deaths, and 600 million € of economic damage, 131 km of affected and simulated rivers.</li> <li>The 15<sup>th </sup>- 16<sup>th</sup> of October 2018 flood on the Aude watershed: 15 deaths, approximatively 300 million € of economic damage, 569 km of affected and simulated rivers.</li> </ul><p>At first, the peak discharges for each reach of the stream network are estimated with a hydrological model (CINECAR), calibrated against discharge values based on extensive post-event surveys. The hydraulic simulations with the two methods are then run for each reach separately in steady-state regime, based on estimated peak discharges, to obtain simulated flood maps at the reach scale that are then combined to obtain a flood extent map for the simulated event. The computation times are calculated for the two methods and compared.</p><p>The simulation results are compared with observed flood extent maps and high water marks. The flood extent maps are compared based on a critical success index criterion (CSI), showing an overall very good correspondence. The simulated water levels show a difference of less than 50 cm with high water marks in most cases.</p><p>Finally, a sensitivity analysis to the quality of DTM input information and roughness coefficients is presented.</p>

Evaluating Preschool Visual Attentional Selective-Set: Preliminary ERP Modeling and Simulation of Target Enhancement Homology

We reanalyzed, modeled and simulated Event-Related Potential (ERP) data from 13 healthy children (Mean age = 5.12, Standard Deviation = 0.75) during a computerized visual sustained target detection task. Extending an ERP-based ACT–R (Adaptive Control of Thought–Rational) neurocognitive modeling approach, we tested whether visual sustained selective-set attention in preschool children involves the enhancement of neural response to targets, and it shows key adult-like features (neurofunctional homology). Blinded automatic peaks analysis was conducted on vincentized binned grand ERP averages. Time-course and distribution of scalp activity were detailed through topographic mapping and paths analysis. Reaction times and accuracy were also measured. Adult Magnetic Resonance Imaging-based mapping using ACT–R dipole source modeling and electric-field spiking simulation provided very good fit with the actual ERP data (R2 > 0.70). In most electrodes, between 50 and 400 ms, ERPs concurrent with target presentation were enhanced relative to distractor, without manual response confounds. Triangulation of peak analysis, ACT–R modeling and simulation for the entire ERP epochs up to the moment of manual response (~700 ms, on average) suggested converging evidence of distinct but interacting processes of enhancement and planning for response release/inhibition, respectively. The latter involved functions and structures consistent with adult ERP activity which might correspond to a large-scale network, implicating Dorsal and Ventral Attentional Networks, corticostriatal loops, and subcortical hubs connected to prefrontal cortex top-down working memory executive control. Although preliminary, the present approach suggests novel directions for further tests and falsifiable hypotheses on the origins and development of visual selective attention and their ERP correlates.

Belle2VR: An Interactive Virtual Reality Visualization of GEANT4 Event Histories

Belle2VR is a novel interactive virtual reality visualization of the Belle II detector at KEK and the animation therein of GEANT4-simulated event histories. The user, wearing a VR headset, manipulates a gamepad or hand controller(s) to interact with and interrogate the detailed GEANT4 event history over time, to adjust the visibility and transparency of the particles and detector subsystems, to translate freely in 3D, to zoom in or out, and to control the event-history timeline. In this way, the user explores the world of subatomic physics via electron-positron collision events in the Belle II experiment at the SuperKEKB colliding-beam facility at KEK in Japan. Developed at Virginia Tech by an interdisciplinary team of researchers in physics, education, and virtual environments, the simulation is intended to be integrated into the undergraduate physics curriculum.

Cycle-by-cycle analysis of neural oscillations

Neural oscillations are widely studied using methods based on the Fourier transform, which models data as sums of sinusoids. This has successfully uncovered numerous links between oscillations and cognition or disease. However, neural data are nonsinusoidal, and these nonsinusoidal features are increasingly linked to a variety of behavioral and cognitive states, pathophysiology, and underlying neuronal circuit properties. We present a new analysis framework, one that is complementary to existing Fourier and Hilbert transform-based approaches, that quantifies oscillatory features in the time domain on a cycle-by-cycle basis. We have released this cycle-by-cycle analysis suite as “bycycle,” a fully documented, open-source Python package with detailed tutorials and troubleshooting cases. This approach performs tests to assess whether an oscillation is present at any given moment and, if so, quantifies each oscillatory cycle by its amplitude, period, and waveform symmetry, the latter of which is missed with the use of conventional approaches. In a series of simulated event-related studies, we show how conventional Fourier and Hilbert transform approaches can conflate event-related changes in oscillation burst duration as increased oscillatory amplitude and as a change in the oscillation frequency, even though those features were unchanged in simulation. Our approach avoids these errors. Furthermore, we validate this approach in simulation and against experimental recordings of patients with Parkinson’s disease, who are known to have nonsinusoidal beta (12–30 Hz) oscillations. NEW & NOTEWORTHY We introduce a fully documented, open-source Python package, bycycle, for analyzing neural oscillations on a cycle-by-cycle basis. This approach is complementary to traditional Fourier and Hilbert transform-based approaches but avoids specific pitfalls. First, bycycle confirms an oscillation is present, to avoid analyzing aperiodic, nonoscillatory data as oscillations. Next, it quantifies nonsinusoidal aspects of oscillations, increasingly linked to neural circuit physiology, behavioral states, and diseases. This approach is tested against simulated and real data.