Simple Process Model Research Articles

Male rutting calls synchronize reproduction in Serengeti wildebeest

Tightly synchronized reproduction in vast wildebeest herds underpins the keystone role this iconic species plays in the Serengeti. However, despite decades of study, the proximate synchronizing mechanism remains unknown. Combining a season-long field experiment with simple stochastic process models, we show that females exposed to playback of male rutting vocalizations are over three times more synchronous in their expected time to mating than a control group isolated from all male stimuli. Additionally, predictions of both mating and calving synchrony based on the playback group were highly consistent with independent data on wildebeest mating and calving synchrony, while control-based predictions were inconsistent with the data. Taken together, our results provide the first experimental evidence that male rutting vocalizations alone could account for the highly synchronized reproduction observed in Serengeti wildebeest. Given anthropogenically driven losses in many areas, a mechanistic understanding of synchrony can highlight additional risks declining wildebeest populations may face.

Bayesian Metropolis methods for source localization in an urban environment

We apply Bayesian techniques to determine the location and intensity of a gamma radiation source in an urban environment using count rates taken from a distributed detector network. A simplified model of the radiation transport process is used to construct a statistical model for the detector count rates in the presence of a randomly varying background. Markov Chain Monte Carlo is used to generate samples from the Bayesian posterior density, which can be used to inform search and interdiction efforts. We also present a modification of the traditional Metropolis sampling algorithm that allows us to incorporate fixed parameter uncertainties in building macroscopic cross sections and account for their effects on the posterior distribution. This method is then applied to a test problem based on a real urban geometry with different levels of uncertainty in the building cross sections. The results show that the uncertainty in the estimated source location is modest, even with a large degree of uncertainty in the building cross sections.

Non-equilibrium Thermodynamics of Fast Traveling Waves in a Catalytic Fixed Bed. Emergence of Near-equilibrium Spatiotemporal Dissipative Structure

AbstractThis work presents the results of the mathematical modeling of the fast traveling wave propagation phenomenon in the fixed-bed catalytic reactors according to a simple (basic) mathematical model with a reversible reaction. Qualitative and quantitative research is used to study the behavior of separatrices’ trajectories of the system’s non-linear ordinary differential equations. Special attention has been paid to the non-equilibrium thermodynamic methods. The entropy balance equation is constructed and analyzed under the assumption of the simple mathematical model of physical and chemical processes. The influence of key physical and chemical parameters on the fast traveling wave properties is studied. The phenomenon of fast traveling wave propagation in the fixed-bed catalytic reactors provides a vivid example of a spatiotemporal dissipative structure in active heterogeneous medium. These dissipative structures are shown to exist near the thermodynamic equilibrium.

Split miner: automated discovery of accurate and simple business process models from event logs

The problem of automated discovery of process models from event logs has been intensively researched in the past two decades. Despite a rich field of proposals, state-of-the-art automated process discovery methods suffer from two recurrent deficiencies when applied to real-life logs: (i) they produce large and spaghetti-like models; and (ii) they produce models that either poorly fit the event log (low fitness) or over-generalize it (low precision). Striking a trade-off between these quality dimensions in a robust and scalable manner has proved elusive. This paper presents an automated process discovery method, namely Split Miner, which produces simple process models with low branching complexity and consistently high and balanced fitness and precision, while achieving considerably faster execution times than state-of-the-art methods, measured on a benchmark covering twelve real-life event logs. Split Miner combines a novel approach to filter the directly-follows graph induced by an event log, with an approach to identify combinations of split gateways that accurately capture the concurrency, conflict and causal relations between neighbors in the directly-follows graph. Split Miner is also the first automated process discovery method that is guaranteed to produce deadlock-free process models with concurrency, while not being restricted to producing block-structured process models.

Multivariate spatial meta kriging

This work extends earlier work on spatial meta kriging for the analysis of large multivariate spatial datasets as commonly encountered in environmental and climate sciences. Spatial meta-kriging partitions the data into subsets, analyzes each subset using a Bayesian spatial process model and then obtains approximate posterior inference for the entire dataset by optimally combining the individual posterior distributions from each subset. Importantly, as is often desired in spatial analysis, spatial meta kriging offers posterior predictive inference at arbitrary locations for the outcome as well as the residual spatial surface after accounting for spatially oriented predictors. Our current work explores spatial meta kriging idea to enhance scalability of multivariate spatial Gaussian process model that uses linear model co-regionalization (LMC) to account for the correlation between multiple components. The approach is simple, intuitive and scales multivariate spatial process models to big data effortlessly. A simulation study reveals inferential and predictive accuracy offered by spatial meta kriging on multivariate observations.

A Simplified Dynamic Thermokinetic-Based Model of Wood Gasification Process

Gasification has been one of the most attractive and common biomass conversion processes for recent years. The existence of an accurate and dynamic model frees us from carrying out time-consuming and expensive tests. In this study, to eliminate the complexity of dynamic models, a hybrid model is used for modeling the process of wood-fixed bed gasification. Firstly, an equilibrium model is developed to obtain the mole fractions of product flow and the equilibrium temperature of the flaming pyrolysis zone. The equilibrium model is applied as the initial condition of the unsteady one-dimensional kinetic model for the reduction zone. The couple of heat and mass equations in the gas phase are solved by considering the kinetic of main reactions in the reduction zone using MATLAB software. Oxygen is considered gasifying agent instead of air. The results indicate a good agreement with previous relevant researches. In the equivalence ratio of 0.35, the maximum mole fraction of hydrogen as the most valuable syngas has obtained. In this optimum ER, the equilibrium temperature of flaming pyrolysis zone has been calculated to be 1012 K, and the gasifier outlet temperature at gas-phase velocity within 0.1–1 m/s is 890–952 K. The final mole fractions of CO and H2 as the main products of the process are 0.46 and 0.36, respectively. The heating value of produced syngas equals 10.8 MJ/m3 that is 120% higher than the average heating value when the air is utilized as the gasifier agent.

Dynamics of impulse response of streaming electrification current in swinging cylinder system insulation

The paper presents results of measurements and analysis of the flow electrification process in the Swinging Cylinder System. This system is similar to the Couette system. The proposed system has the ability to perform different movement function of the internal electrode. The identification of the electrification process was made based on small step movements of the electrode in both directions. The battery powered measurement device was mounted inside the movable inner cylinder. In addition, it allows for the wireless transmission of the measured data. A series of the electrification current measurements were made in response to the impulse changes of the speed of the measuring electrode. The identification of simple process models of first and second order was made on the basis of the results.

Optical bandgap energy of CH3NH3PbI3 perovskite studied by photoconductivity and reflectance spectroscopy

Organic-inorganic hybrid perovskite materials have been receiving considerable attention due to their promising applications in many optoelectronic fields. However, the optical bandgap of CH3NH3PbI3 perovskite is still disputed. In order to comprehend the intrinsic characteristics of these materials, we study the near-band-edge optical responses of the solution-processed CH3NH3PbI3 perovskite crystals by photoconductivity and reflectance spectroscopy at room temperature. All these spectra of the CH3NH3PbI3 polycrystals show only one significant absorption edge at 1.58 eV. However, we observe an extra absorption edge at 1.47 eV in CH3NH3PbI3 single crystal. We establish a simple kinetic model of charge annihilation processes to explain why the low-energy structure of the photoconductivity and diffuse reflectance spectra of CH3NH3PbI3 polycrystals disappear, which provides another possibility for understanding the difference in absorption edge. It is noteworthy that this low-energy absorption edge of CH3NH3PbI3 single crystal has, to the best of our knowledge, seldom been reported on organic-inorganic hybrid perovskites. Therefore, the CH3NH3PbI3 single crystal exhibits a relatively wide absorption which makes it a promising candidate for photoelectric applications.

Sliding Mode Control of Underground Coal Gasification Energy Conversion Process

The control of highly complex and nonlinear underground coal gasification (UCG) energy conversion process is a challenging job. As the process occurs under the surface of the earth, so it is either impossible or very expensive to measure all the important parameters, which further complicates the control design. The input of the UCG process is the flow rate of the injected air and the heating value of the product gas is the output. In this paper, a sliding mode control (SMC) algorithm is designed for a simplified model of an actual UCG process in order to maintain a desired constant heating value. The relative degree of the sliding variable is zero, because the input is readily available in it. As the heating value is the only measurement available, the trivial control design is not possible. Therefore, the time derivative of the control is selected as the system input, and then the relative degree becomes one and the conventional SMC may be implemented. This approach let us maintain the output at the desired level and provides insensitivity with respect to different types of uncertainties. The stability of the zero dynamics is proved, which ensures that the overall system is stable. The simulation results demonstrate the robustness of the SMC design against the input disturbance and the modeling inaccuracies.

Dissociative recombination by frame transformation to Siegert pseudostates: A comparison with a numerically solvable model

We present a simple two-dimensional model of the indirect dissociative recombination process. The model has one electronic and one nuclear degree of freedom and it can be solved to high precision, without making any physically motivated approximations, by employing the exterior complex scaling method together with the finite-elements method and discrete variable representation. The approach is applied to solve a model for dissociative recombination of H$_2^+$ and the results serve as a benchmark to test validity of several physical approximations commonly used in the computational modeling of dissociative recombination for real molecular targets. The second, approximate, set of calculations employs a combination of multi-channel quantum defect theory and frame transformation into a basis of Siegert pseudostates. The cross sections computed with the two methods are compared in detail for collision energies from 0 to 2 eV.

Model Predictive Control of Simulated Moving Bed Chromatography for Binary and Pseudo-binary Separations: Simulation Study

Simulated moving bed (SMB) processes have been applied to petrochemical, pharmaceutical, and fine chemical industries to separate products in high purity and yield since it was introduced in 1960s. Owing to process complexity and operational sensitivity, the control and dynamic optimization of the SMB process are still challenging issues. In this work, a simplified process model with linear isotherms was introduced to estimate process states of conventional four-zone SMB chromatography. In a simulation study, a controller can estimate current process states and find the optimal operating conditions ‘switch by switch’ up to moderately nonlinear ranges of the competitive Langmuir isotherms. Furthermore, the controller works for the process with system void volumes and delayed feedback information.

CONTSID: a Matlab toolbox for standard and advanced identification of black-box continuous-time models

The CONtinuous-Time System IDentification (CONTSID) toolbox provides Matlab functions for estimating continuous-time black-box models of dynamical systems from measured data without having to fully characterize the mathematics governing the system behavior. The toolbox includes tools for standard identification of linear continuous-time models such as simple process, transfer functions and state-space models. The toolbox also provides algorithms for more advanced identification such as errors-in-variable (EIV) and closed-loop model estimation or to capture nonlinear system dynamics. This paper presents an overview of the main features of the latest release of the CONTSID toolbox and outlines some recent developments for on-line parameter and time-delay system estimation.

Dead-Time Compensator for State-delay Stable Systems

This paper deals with the control of simple process models with state-delays. A pre-compensator is used to cancel the delay. Due to the cancellation of some terms, the process as well as its undelayed part should be stable. Although the approach is general, in order to simplify the notation, second order systems are considered to describe the procedure. The proposed methodology is applied to compensate the delay in a recycled reactor as well as to control a pure state-delayed academic example.

Probing resonant energy transfer in collisions of ammonia with Rydberg helium atoms by microwave spectroscopy.

We present the results of experiments demonstrating the spectroscopic detection of Förster resonance energy transfer from NH3 in the X1A1 ground electronic state to helium atoms in 1sns 3S1 Rydberg levels, where n = 37 and n = 40. For these values of n, the 1sns 3S1 → 1snp 3PJ transitions in helium lie close to resonance with the ground-state inversion transitions in NH3 and can be tuned through resonance using electric fields of less than 10 V/cm. In the experiments, energy transfer was detected by direct state-selective electric field ionization of the 3S1 and 3PJ Rydberg levels and by monitoring the population of the 3DJ levels following pulsed microwave transfer from the 3PJ levels. Detection by microwave spectroscopic methods represents a highly state selective, low-background approach to probing the collisional energy transfer process and the environment in which the atom-molecule interactions occur. The experimentally observed electric-field dependence of the resonant energy transfer process, probed both by direct electric field ionization and by microwave transfer, agrees well with the results of calculations performed using a simple theoretical model of the energy transfer process. For measurements performed in zero electric field with atoms prepared in the 1s40s 3S1 level, the transition from a regime in which a single energy transfer channel can be isolated for detection to one in which multiple collision channels begin to play a role has been identified as the NH3 density was increased.

DNA interaction with platinum-based cytostatics revealed by DNA sequencing

The main mechanism of action of platinum-based cytostatic drugs – cisplatin, oxaliplatin and carboplatin – is the formation of DNA cross-links, which restricts the transcription due to the disability of DNA to enter the active site of the polymerase. The polymerase chain reaction (PCR) was employed as a simplified model of the amplification process in the cell nucleus. PCR with fluorescently labelled dideoxynucleotides commonly employed for DNA sequencing was used to monitor the effect of platinum-based cytostatics on DNA in terms of decrease in labeling efficiency dependent on a presence of the DNA-drug cross-link. It was found that significantly different amounts of the drugs - cisplatin (0.21 μg/mL), oxaliplatin (5.23 μg/mL), and carboplatin (71.11 μg/mL) - were required to cause the same quenching effect (50%) on the fluorescent labelling of 50 μg/mL of DNA. Moreover, it was found that even though the amounts of the drugs was applied to the reaction mixture differing by several orders of magnitude, the amount of incorporated platinum, quantified by inductively coupled plasma mass spectrometry, was in all cases at the level of tenths of μg per 5 μg of DNA.

Isothermal and CW laser crystallization of amorphous Ge2Sb2Te5 thin films

Transmission electron microscopy results are presented for as-deposited amorphous Ge2Sb2Te5 thin films after theirs isothermal annealing and CW laser illumination. Obtained microphotographs suggested that the crystallization process was driven solely by heterogeneous nucleation on the film boundary. The simplified model of steady-state crystallization process was developed for the case of heterogeneous nucleation mechanism. The values of nucleation rate and growth rate for isothermal and CW laser crystallization are calculated. The calculated values are in reasonable agreement with both our experimental data and with results previously published by the other authors.

On the Use of the Terms Verification and Validation

AbstractWhile the concepts of verification and validation are commonplace, in practice the terms are often used interchangeably and the context of their use is not made clear, resulting in the meaning of the concepts frequently being misunderstood. This paper addresses the use of the terms verification and validation and identifies their various meanings in terms of the context in which they are used, particularly as defined in the relevant standards and literature, as well as everyday usage. In particular, it is identified that both terms are ambiguous unless a modifier is included in front of the word, clearly indicating to which context the term is referring. This paper illustrates that failing to use a modifier—thus assuming the reader understands the context in which the terms are used—is the most common reason for ambiguity and misunderstanding. The paper presents a simple model of the system design process to allow the nature of verification and validation to be understood better within a given context. Definitions are then proposed in order to disambiguate the various uses of the terms.

Availability estimation of navigation aids

Ground network of waypoints has been commonly used for different navigation tasks. Detection and positioning of aircraft location line in 3D airspace are the most important of them. Aircraft location determination by signals from ground-based waypoints is a part of alternative positioning algorithms in flight management system. A new method of radio navigation aids availability in particular airspace volume has been represented in paper. It includes cylindrical model of NAVAIDS service volume according to three basic types: Terminal, Low altitude and High Altitude. Proposed method uses digital elevation model of terrain data for detection of radio sight line and availability estimation in 3D space of NAVAIDS. The simple model of diffraction process was considered to increase accuracy of the method. However, diffraction model has been used only for peaks of relief. Represented method has been used for availability areas estimation of VOR and DME waypoints network for Ukrainian airspace. Availability areas of waypoints were highlighted in contour lines according to data in Aeronautical Information Publication. Also, the total number of NAVAIDS combination was estimated and indicated in contour graph for region.

Inverse Gaussian process models for bivariate degradation analysis: A Bayesian perspective

ABSTRACTThis article conducts a Bayesian analysis for bivariate degradation models based on the inverse Gaussian (IG) process. Assume that a product has two quality characteristics (QCs) and each of the QCs is governed by an IG process. The dependence of the QCs is described by a copula function. A bivariate simple IG process model and three bivariate IG process models with random effects are investigated by using Bayesian method. In addition, a simulation example is given to illustrate the effectiveness of the proposed methods. Finally, an example about heavy machine tools is presented to validate the proposed models.

A neuro-dynamic programming approach to the optimal stand management problem

Some ideas of neuro-dynamic programming (NDP) are illustrated by considering the problem of optimally managing a forest stand under uncertainty. Because reasonable growth models require state information such as height (or age), basal area, and stand diameter, as well as an indicator variable for treatments that have been performed on the stand, they can easily lead to very large state spaces that include continuous variables. Realistic stand management policies include silvicultural options such as pre-commercial and commercial thinning as well as post-harvest treatments. We are interested in problems that are stochastic in their basic growth dynamics, in market prices, and in disturbances, ranging from insects to fire to hurricanes. NDP algorithms are appropriate for problems with large dimensions that may lack a simple model of dynamics and stochastic processes. This paper looks at applying these ideas in the context of a multispecies model. Results show that policies obtained using NDP are optimal within a 95% confidence interval or better. The set of states and controls incorporated into our NDP model allows us to develop optimal policies with a level of detail not typically seen in the forestry literature.