The electrical resistance of the amorphous phase gradually increases slowly with time, after switching from the crystalline state in phase‐change random‐access memory (PCRAM), which is known as the ...resistance drift (R‐drift). Although several interpretations of R‐drift have been proposed, the mechanisms are still not fully understood. The models are examined quantitatively by investigating the changes in the optical dielectric function and the resistance in the amorphous phase of Ge2Sb2Te5. The results suggest that R‐drift is an intrinsic phenomenon in nonequilibrium systems—the mechanical stress induced in the amorphous state relaxes into a more stable nonequilibrium state (order in disorder). Hence, R‐drift is not attributed to purely electronic processes.
Carbonate environments inhabit the realm of the surface, intermediate and deep currents of the ocean circulation where they produce and continuously deliver material which is potentially deposited ...into contourite drifts. In the tropical realm, fine‐grained particles produced in shallow water and transported off‐bank by tidal, wind‐driven, and cascading density currents are a major source for transport and deposition by currents. Sediment production is especially high during interglacial times when sea level is high and is greatly reduced during glacial times of sea‐level lowstands. Reduced sedimentation on carbonate contourite drifts leads to early marine cementation and hardened surfaces, which are often reworked when current strength increases. As a result, reworked lithoclasts are a common component in carbonate drifts. In areas of temperate and cool water carbonates, currents are able to flow across carbonate producing areas and incorporate sediment directly to the current. The entrained skeletal carbonate particles have variable bulk density and shapes that lower the prediction of transport rates in energy‐based transport models, as well as prediction of current velocity based on grain size. All types of contourite drifts known in clastic environments are found in carbonate environments, but three additional drift types occur in carbonates because of local sources and current flow diversion in the complicated topography inherent to carbonate systems. The periplatform drift is a carbonate‐specific plastered drift that is nearly exclusively made of periplatform ooze. Its geometry is built by the interaction of along‐slope currents and downslope currents, which deliver sediment from the adjacent shallow‐water carbonate realm to the contour current via a line source. Because the periplatform drift is plastered on the slopes of the platforms it is also subject to mass gravity flow and large slope failures. At platform edges, a special type of patch drift develops. These hemiconal platform‐edge drifts also contain exclusively periplatform ooze but their geometry is controlled by the current around the corner of the platform. At the north‐western end of Little and Great Bahama Bank are platform‐edge drifts that are over 100 km long and up to 600 m thick. A special type of channel‐related drift forms when passages between carbonate buildups or channels within a platform open into deeper water. A current flowing in these channels will entrain material shed from the sediment producing areas. At the channel mouth, the sediment‐charged current deposits its sediment load into the deeper basin. With continuous flow, a submarine delta drift is built that progrades into the deep water. The strongly focused current forming the delta drift, is able to rework coarse skeletal grains and clasts, making this type of carbonate drift the coarsest drift type.
In a simulation study, Stafford et al. (Behavior Research Methods, 52, 2142–2155, 2020) explored the effect of sample size on detecting group differences in ability in the presence of speed–accuracy ...trade-offs using the Drift Diffusion Model (DDM) and introduced an online tool to perform a power analysis. They found that the DDM approach was superior to analyzing the observed response times and response accuracies alone. In their simulation, they applied the EZ method to estimate the model parameters. In this article, we demonstrate that the EZ method, which cannot estimate the response bias parameter of the DDM, causes severe estimation bias for all parameters if the true response bias is not 0.5. Moreover, the bias patterns differ between EZ and the equivalent maximum likelihood estimation with z fixed at 0.5. This should be taken into consideration when using the otherwise excellent power analysis tool for experimental designs, in which z≠ 0.5 cannot be ruled out or even stipulate it.
A Survey on Concept Drift in Process Mining Sato, Denise Maria Vecino; De Freitas, Sheila Cristiana; Barddal, Jean Paul ...
ACM computing surveys,
12/2022, Letnik:
54, Številka:
9
Journal Article
Recenzirano
Odprti dostop
Concept drift in process mining (PM) is a challenge as classical methods assume processes are in a steady-state, i.e., events share the same process version. We conducted a systematic literature ...review on the intersection of these areas, and thus, we review concept drift in PM and bring forward a taxonomy of existing techniques for drift detection and online PM for evolving environments. Existing works depict that (i) PM still primarily focuses on offline analysis, and (ii) the assessment of concept drift techniques in processes is cumbersome due to the lack of common evaluation protocol, datasets, and metrics.
We have assessed the use of satellite derived currents to calculate oceanic surface drift, as an alternative to using currents from ocean models. Predicted trajectories are compared to observed ...trajectories of two types of drifting buoys, which are subject to different degree of wind and wave forcing, in addition to the ocean surface current. This variable degree of ocean-, wind- and wave forcing is highly relevant for the practical problem of predicting the drift of e.g. oil to aid cleanup operations, and the drift of floating objects to aid search and rescue operations. The calculated trajectories are evaluated in terms of separation distance, and a calculated skill score. For the submerged drifters (CODE/DAVIS), we find that a high resolution non-assimilated ocean model gives the best results, whereas a coarser scale assimilated model performs similarly to satellite derived surface currents from the GlobCurrent project (geostrophic + Ekman components). For the wind-exposed drifters (iSphere), the wind-drift contribution is found to be dominating, and there is only a small impact of using any of the available information about ocean currents. The wind drift contribution to the iSphere drift is estimated to be 3% of the wind if Stokes drift is included in the calculations, and 4% if the Stokes drift is not included. Including Stokes drift in the calculations gives improvement for the submerged drifters, but shows no improvement for the wind exposed drifters.
•Satellite derived currents are found to be useful for ocean trajectory forecasting.•Ocean currents represent the largest uncertainty in ocean trajectory forecasting.•Ocean surface drift may be fairly well predicted from wind only.
In this article, we study the Schrödinger bridge problem (SBP) with nonlinear prior dynamics. In control-theoretic language, this is a problem of minimum effort steering of a given joint state ...probability density function (PDF) to another over a finite-time horizon, subject to a controlled stochastic differential evolution of the state vector. As such, it can be seen as a stochastic optimal control problem in continuous time with endpoint density constraints-A topic that originated in the physics literature in 1930s, and in the recent years, has garnered burgeoning interest in the systems-control community. For generic nonlinear drift, we reduce the SBP to solving a system of forward and backward Kolmogorov partial differential equations (PDEs) that are coupled through the boundary conditions, with unknowns being the "Schrödinger factors"-so named since their product at any time yields the optimal controlled joint state PDF at that time. We show that if the drift is a gradient vector field, or is of mixed conservative-dissipative nature, then it is possible to transform these PDEs into a pair of initial value problems (IVPs) involving the same forward Kolmogorov operator. Combined with a recently proposed fixed point recursion that is contractive in the Hilbert metric, this opens up the possibility to numerically solve the SBPs in these cases by computing the Schrödinger factors via a single IVP solver for the corresponding (uncontrolled) forward Kolmogorov PDE. The flows generated by such forward Kolmogorov PDEs, for the two aforementioned types of drift, in turn, enjoy gradient descent structures on the manifold of joint PDFs with respect to suitable distance functionals. We employ a proximal algorithm developed in our prior work that exploits this geometric viewpoint, to solve these IVPs and compute the Schrödinger factors via weighted scattered point cloud evolution in the state space. We provide the algorithmic details and illustrate the proposed framework of solving the SBPs with nonlinear prior dynamics by numerical examples.
Previous studies suggested that sudden stratospheric warmings (SSW) change the global atmosphere from troposphere to thermosphere/ionosphere. We report the low‐latitude O+ and H+ composition at ...840‐km altitude during the 2009 SSW, with the DMSP satellite morning measurements. Our results indicate that the stratospheric variation around 30‐km altitude modulates the ion exchange between the ionosphere and protonosphere via the vertical and field‐aligned plasma drifts due to the enhanced lunar semidiurnal tides. The upward disturbance drift uplifts the ionospheric O+ into the protonosphere, and most O+ is changed to H+ via chemical coupling, while the O+/H+ transition height does not change under combined effects of the southward and upward disturbance drifts on 24–29 January. The disturbance drift turns downward, lowers the O+/H+ transition height, depletes the O+ density in the protonosphere, and the H+ at higher altitudes moves downward to supply the H+ at 840 km from 30 January to 5 February.
Plain Language Summary
The stratosphere is a layer of the atmosphere from ∼10–50 km altitudes. Roughly every 2 years, the Northern Hemisphere winter polar stratosphere suddenly warms over a course of few days, and the winds decelerate dramatically, even reversal to easterly winds, which is known as sudden stratospheric warmings (SSW). SSW causes large changes in global atmosphere including the troposphere, mesosphere, and thermosphere via the dynamic coupling. Studies in the last decade revealed that SSW can also lead to the remarkable changes in the ionospheric electron density around the 300–400 km F2 region. A question is whether or not the SSW effects can reach higher altitude. The main ions are O+ around the F2 peak, while change to light ions as the altitude increases. We use the DMSP satellite observations in the morning to present the O+ and H+ distributions at 840 km altitude during the 2009 SSW. The ion composition distributions provide us a channel to study the coupling between the protonosphere and ionosphere. The results illustrate that the SSW occurred at ∼30 km altitude can impact the protonospheric plasma environment in low latitudes that has been not presented previously.
Key Points
The sudden stratospheric warmings modulates the ion exchange between the ionosphere and protonosphere
The O+/H+ transition height does not change under the combined effects of the upward and southward disturbance plasma drifts
The enhanced semidiurnal lunar tides may contribute to the ion exchange between two layers
•This method not only makes a preliminary division of concept drift, but also gives a more detailed classification.•It can provide more accurate guidance for rapid model updating after a concept ...drift occurs.
Concept drift is a common and important issue in streaming data analysis and mining. Thus far, many concept drift detection methods have been proposed but may not be able to identify the type of concept drift, which will result in some difficulties, such as extracting the wrong key information, inadequate model learning and poor detection efficiency. To solve these problems, a concept drift type identification method is proposed based on multi-sliding windows (CDT_MSW). This method consists of three processes. During the first detection process, the drift position is detected by sliding the basic window forward. Then, in the growth process, the drift length is detected using the growth of the adjoint window, and the drift category is identified according to the drift length. Finally, during tracking process, the drift subcategory can be accurately identified according to the different tracking flow ratio curves generated during window tracking. Experimental results show that the proposed method can effectively identify the type of concept drift, accurately analyze the key information during online learning and improve the efficiency and generalization performance of streaming data analysis and mining.
We introduce ∂PV, an end-to-end differentiable photovoltaic (PV) cell simulator based on the drift-diffusion model and Beer–Lambert law for optical absorption. ∂PV is programmed in Python using JAX, ...an automatic differentiation (AD) library for scientific computing. Using AD coupled with the implicit function theorem, ∂PV computes the power conversion efficiency (PCE) of an input PV design as well as the derivative of the PCE with respect to any input parameters, all within comparable time of solving the forward problem. We show an example of perovskite solar-cell optimization and multi-parameter discovery, and compare results with random search and finite differences. The simulator can be integrated with optimization algorithms and neural networks, opening up possibilities for data-efficient optimization and parameter discovery.
Program Title:∂PV
CPC Library link to program files:https://doi.org/10.17632/7w7r8mtx3d.1
Developer's repository link:https://github.com/romanodev/deltapv.git
Code Ocean capsule:https://codeocean.com/capsule/0851990
Licensing provisions: MIT
Programming language: Python
Nature of problem: Photovoltaic cell optimization has been traditionally difficult due to the lack of gradients from numerical drift-diffusion solvers. This results in the need to treat the problem as a case of black-box optimization, which incurs high computational costs and low data efficiency.
Solution method: An end-to-end differentiable photovoltaic simulator via the drift-diffusion model was developed using JAX, a growing scientific computation and automatic-differentiation library. To enhance computational speed, the implicit function theorem was used to bypass the need for directly differentiating through iterative solvers.
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