In this paper, we use the C/NOFS and ROCSAT‐1 satellites observations to analyze the storm time evolution of the disturbance plasma drifts in a 24 h local time scale during three magnetic storms ...driven by long‐lasting southward IMF Bz. The disturbance plasma drifts during the three storms present some common features in the periods dominated by the disturbance dynamo. The newly formed disturbance plasma drifts are upward and westward at night, and downward and eastward during daytime. Further, the disturbance plasma drifts are gradually evolved to present significant local time shifts. The westward disturbance plasma drifts gradually migrate from nightside to dayside. Meanwhile, the dayside downward disturbance plasma drifts become enhanced and shift to later local time. The local time shifts in disturbance plasma drifts are suggested to be mainly attributed to the evolution of the disturbance winds. The strong disturbance winds arisen around midnight can constantly corotate to later local time. At dayside the westward and equatorward disturbance winds can drive the F region dynamo to produce the poleward and westward polarization electric fields (or the westward and downward disturbance drifts). The present results indicate that the disturbance winds corotated to later local time can affect the local time features of the disturbance dynamo electric field.
Key Points
The 24 h local time variations of the disturbance plasma drifts are observed continuously
The downward and westward disturbance plasma drifts shift to later local time
The local time shifts in the disturbance plasma drifts are mainly attributed to the evolution of the disturbance winds
RDDM: Reactive drift detection method Barros, Roberto S.M.; Cabral, Danilo R.L.; Gonçalves, Paulo M. ...
Expert systems with applications,
12/2017, Letnik:
90
Journal Article
Recenzirano
•RDDM: a new concept drift detection method inspired on DDM.•Tackles the lack of sensitivity problem of DDM when concepts are very large.•Tested against DDM, ECDD and STEPD using Naive Bayes as base ...learner.•RDDM was significantly superior to the other three methods in accuracy.•RDDM presented the best balance of false negative and false positive detections.
Concept drift detectors are online learning software that mostly attempt to estimate the drift positions in data streams in order to modify the base classifier after these changes and improve accuracy. This is very important in applications such as the detection of anomalies in TCP/IP traffic and/or frauds in financial transactions. Drift Detection Method (DDM) is a simple, efficient, well-known method whose performance is often impaired when the concepts are very long. This article proposes the Reactive Drift Detection Method (RDDM), which is based on DDM and, among other modifications, discards older instances of very long concepts aiming to detect drifts earlier, improving the final accuracy. Experiments run in MOA, using abrupt and gradual concept drift versions of different dataset generators and sizes (48 artificial datasets in total), as well as three real-world datasets, suggest RDDM beats the accuracy results of DDM, ECDD, and STEPD in most scenarios.
We present the first direct evidence of an in situ excitation of drift‐compressional waves driven by drift resonance with ring current protons in the magnetosphere. Compressional Pc4–5 waves with ...frequencies of 4–12 mHz were observed by the Arase satellite near the magnetic equator at L ∼ 6 in the evening sector on 19 November 2018. Estimated azimuthal wave numbers (m) ranged from −100 to −130. The observed frequency was consistent with that calculated using the drift‐compressional mode theory, whereas the plasma anisotropy was too small to excite the drift‐mirror mode. We discovered that the energy source of the wave was a drift resonance instability, which was generated by the negative radial gradient in a proton phase space density at 20–25 keV. This proton distribution is attributed to a temporal variation of the electric field, which formed the observed multiple‐nose structures of ring current protons.
Plain Language Summary
During magnetic storms and substorms, energetic ions are sporadically injected into the geospace, which distorts the stable population and velocity distributions of ions in space. At these moments, various plasma instabilities lead to ultra‐low frequency (ULF) wave excitations. The lowest‐frequency waves in the ULF range have a wavelength comparable to the size of the Earth and are typically analyzed using magnetohydrodynamic principles. This approach considers the plasma environment using macroscale parameters such as pressure and density. In this paper, we report a spacecraft observation of a broadband compressional ULF wave that cannot be interpreted using magnetohydrodynamics. Such waves have rarely been reported and analyzed; however, their interaction with energetic ions is important to understand magnetospheric energy dynamics. The plasma conditions were described using the kinetic theory, which involves particle velocity distributions. We observed that a drift resonance occurred between the energetic protons and waves, while the gradient instability condition was satisfied for a part of time. Therefore, we concluded that the wave was in a drift‐compressional mode excited through drift resonance and gradient instability. The interpretation of compressional waves via satellite observations of energetic ions has been receiving increasing attention to understand their excitation mechanism.
Key Points
Pc4–5 compressional ultra‐low frequency waves with an azimuthal wave number of −130 were observed in the nose structure on duskside
Theoretically predicted values of drift‐compressional mode frequency match the observed wave frequency
Both radial ion temperature gradient and drift resonance of 20–25 keV protons serve as energy sources of the wave
Among the difficulties being considered in data stream processing, a particularly interesting one is the phenomenon of concept drift. Methods of concept drift detection are frequently used to ...eliminate the negative impact on the quality of classification in the environment of evolving concepts. This article proposes Statistical Drift Detection Ensemble (sdde), a novel method of concept drift detection. The method uses drift magnitude and conditioned marginal covariate drift measures, analyzed by an ensemble of detectors, whose members focus on random subspaces of the stream’s features. The proposed detector was compared with state-of-the-art methods on both synthetic data streams and the semi-synthetic streams generated based on the real-world concepts. A series of computer experiments and a statistical analysis of the results, both for the classification accuracy and Drift Detection errors were carried out and confirmed the effectiveness of the proposed method.
Abstract
Tungsten (W) is used as the plasma-facing material in the divertor region of future fusion reactors, such as ITER; however, its concentration in the core plasma must be maintained at an ...extremely low level. W transport in the scrape-off layer (SOL), which is related to the source of core W contamination, has been extensively studied. In this study, the influence of
E
×
B
drift on the transport of W impurity in the SOL is studied via numerical simulations of a model case based on EAST upper single-null configuration with high recycling divertor plasma. W transport is simulated using DIVIMP on the background plasma obtained from scape-off layer plasma simulation-ITER simulation including drifts. The
E
×
B
drift of W ions is introduced based on the background electric field. Therefore, both the direct
E
×
B
drift effect of W ion and the indirect effect via background plasma on W transport in the SOL are studied. The influence on the flux of W impurities entering confined plasma across the last closed flux surface
Γ
enter
is focused on, which is expected to be proportional to the core W concentration. Results reveal that
Γ
enter
is mainly from the outer (inner) target under a favorable (unfavorable) toroidal field
B
T
and can be increased by more than one order of magnitude compared with the case without drifts; this reflects the significant effect of
E
×
B
drift. The effects due to the background plasma and the poloidal and radial
E
×
B
drift of W ion, as well as the related mechanisms, are analyzed in detail for three stages of W transport in the SOL: effective sputtering from the target, leakage from the divertor, and entry into the confined plasma.
The objective of this study was to evaluate and to compare spray drift potential and field spray drift from pesticide application in citrus orchards carried out mainly comparing standard nozzles with ...drift reducing nozzles. Two different standard nozzles (hollow cone and full cone) and one Venturi drift reducing nozzle (hollow cone) were tested. Spray drift potential was measured by means of wind tunnel experiments (ISO 22856:2008 method). To estimate field airborne and sedimenting spray drift, two trials with 5 replicates each were carried out (ISO 22866:2005 method) in two different commercial orchards of Clementine mandarins. Results showed that Venturi nozzles significantly reduced drift with the two methodologies. Moreover, the wind tunnel method showed the same trend as the field results. Additionally, spray drift deposition variability was lower for the Venturi nozzles. Therefore, it could be concluded that Venturi nozzles can be recommended to be used in citrus orchards to prevent human and environmental risks and their use could be appropriate for different scenarios where spray drift risk must be mitigated.
•Drift reducing nozzles diminish better the airborne than sedimenting drift.•Drift reducing nozzles decrease airborne spray drift variability.•Drift reducing nozzles can be recommended for chemical applications in citrus crops.
The asymmetric instability of drift kinetic Alfvén waves (DKAWs) is analyzed to study the interplay between the density inhomogeneity and the temperature anisotropy, including the wave‐particle ...interaction and finite ion Larmor radius effects. The asymmetric behavior arises due to the opposite diamagnetic drifts of electrons and ions and quantifies the contribution of electron drift waves and ion drift waves in altering the dispersion characteristic of DKAWs. It is shown that the coupling of drift waves with kinetic Alfvén waves leads to the generation of three different frequency (i.e., higher, intermediate, and lower) modes of DKAWs. The comparison of their propagation characteristics and stability mechanisms applicable to a wide range of plasma parameters is provided. The analytical dispersion relation can be used as an improved theoretical tool for identifying the existence of DKAWs and their source region in the multisatellite observations, especially near the reconnection X‐line.
Key Points
The wave propagation parallel and antiparallel to the diamagnetic drift leads to the asymmetric behavior in the dispersion characteristics
Theoretical prediction of asymmetric behavior is useful to identify the DKAWs and their source region in the multisatellite observations
A new asymmetric drift instability scenario has the potential to advance our understanding of wave properties during magnetic reconnection
The dynamicity of real-world systems poses a significant challenge to deployed predictive machine learning (ML) models. Changes in the system on which the ML model has been trained may lead to ...performance degradation during the system’s life cycle. Recent advances that study non-stationary environments have mainly focused on identifying and addressing such changes caused by a phenomenon called concept drift. Different terms have been used in the literature to refer to the same type of concept drift and the same term for various types. This lack of unified terminology is set out to create confusion on distinguishing between different concept drift variants. In this paper, we start by grouping concept drift types by their mathematical definitions and survey the different terms used in the literature to build a consolidated taxonomy of the field. We also review and classify performance-based concept drift detection methods proposed in the last decade. These methods utilize the predictive model’s performance degradation to signal substantial changes in the systems. The classification is outlined in a hierarchical diagram to provide an orderly navigation between the methods. We present a comprehensive analysis of the main attributes and strategies for tracking and evaluating the model’s performance in the predictive system. The paper concludes by discussing open research challenges and possible research directions.
•A new taxonomical classification of concept drift types.•Providing a classification hierarchy of performance-based detection methods.•Identifying research gaps and trends in performance-based detection methods.•Suggesting future research directions in concept drift detection based on the findings.
To address the issue of costly computational expenditure related to high‐fidelity numerical models, surrogate models have been widely used in various engineering tasks, including design optimization. ...Despite the successful application of the existing surrogate models, physics‐based models depend largely on simplifications and assumptions, which render parameter calibration challenging; whereas data‐driven models require substantial data to reach their full potential, with their performance often being constrained in tasks when obtaining massive data is difficult. In this study, a hybrid surrogate model is proposed combining physics‐based and data‐driven models to rapidly estimate building seismic responses. The application of this model is exemplified through effective estimation of inter‐story drift ratios (IDRs), being a critical factor in shear‐wall structure design. Initially, a data augmentation technique and a parametric modeling procedure are introduced to significantly enhance the dataset diversity. Subsequently, a task decomposition strategy is proposed to effectively integrate a data‐driven graph neural network (GNN) and a physics‐based flexural‐shear model. Additionally, the output layer and the loss function of the GNN are modified to enhance the estimation accuracy by eliminating fundamental errors. Results of numerical experiments indicate that the proposed hybrid model can complete IDR estimations in an average time of 0.56 s, with a mean absolute percentage error of 12.7%. This performance significantly surpasses that of existing purely data‐driven and physics‐based models. A case study shows that the efficiency of the proposed hybrid model is approximately 100 times greater than that of conventional finite element software. This enables an accurate assessment of the design compliance with code requirements. The results of this study can be applied to the design optimization of seismic‐resistant building structures.
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