A Statistical Measurement of Randomness Based on Pattern Vectors

International Journal of Circuits, Systems and Signal Processing ◽

10.46300/9106.2020.14.50 ◽

2020 ◽

Vol 14 ◽

Keyword(s):

Data Assimilation ◽

Failure Rate ◽

Kalman Filters ◽

Binary Sequence ◽

Statistical Testing ◽

New Approach ◽

New Device ◽

Statistical Measurement ◽

Pattern Vector

Randomness of data or signals has been applied and studied in various theoretical and industrial fields. There are many ways to define and measure randomness. The most popular one probably is the statistical testing for randomness. Among the approaches adopted, Runs Test is a highly used technique in testing the randomness. In this article, we demonstrate the inefficient aspects of Runs Test and put forward a new approach, or pattern-vector-based statistic, based on pattern vectors that could effectively enhance the precision of testing randomness. A random binary sequence is supposedly to have less or no patterns. Based on this, we put forward our randomness-testing statistic. We also run an experiment to demonstrate how to apply this statistic and compare the efficiency or failure rate with Runs Test in dealing with a set of randomly generated input sequences. Moreover, we devise a statistically-justifiable measure of randomness for any given binary sequence. In the end, we demonstrate a way to combine this new device with Kalman filters to enhance the data assimilation.

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A New Approach for Estimating the Observation Impact in Ensemble–Variational Data Assimilation

Monthly Weather Review ◽

10.1175/mwr-d-17-0252.1 ◽

2018 ◽

Vol 146 (2) ◽

pp. 447-465 ◽

Cited By ~ 12

Author(s):

Mark Buehner ◽

Ping Du ◽

Joël Bédard

Keyword(s):

Data Assimilation ◽

Forecast Error ◽

Forecast Model ◽

Variational Data Assimilation ◽

Observation Error ◽

New Approach ◽

Regional Prediction ◽

Observation Impact ◽

Adjoint Approach ◽

The Impact

Abstract Two types of approaches are commonly used for estimating the impact of arbitrary subsets of observations on short-range forecast error. The first was developed for variational data assimilation systems and requires the adjoint of the forecast model. Comparable approaches were developed for use with the ensemble Kalman filter and rely on ensembles of forecasts. In this study, a new approach for computing observation impact is proposed for ensemble–variational data assimilation (EnVar). Like standard adjoint approaches, the adjoint of the data assimilation procedure is implemented through the iterative minimization of a modified cost function. However, like ensemble approaches, the adjoint of the forecast step is obtained by using an ensemble of forecasts. Numerical experiments were performed to compare the new approach with the standard adjoint approach in the context of operational deterministic NWP. Generally similar results are obtained with both approaches, especially when the new approach uses covariance localization that is horizontally advected between analysis and forecast times. However, large differences in estimated impacts are obtained for some surface observations. Vertical propagation of the observation impact is noticeably restricted with the new approach because of vertical covariance localization. The new approach is used to evaluate changes in observation impact as a result of the use of interchannel observation error correlations for radiance observations. The estimated observation impact in similarly configured global and regional prediction systems is also compared. Overall, the new approach should provide useful estimates of observation impact for data assimilation systems based on EnVar when an adjoint model is not available.

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Analysis of lithofacies cyclicity in the Miocene Coal Complex of the Bełchatów lignite deposit, south-central Poland

Geologos ◽

10.1515/logos-2015-0021 ◽

2015 ◽

Vol 21 (4) ◽

pp. 285-302 ◽

Cited By ~ 2

Author(s):

Wojciech Mastej ◽

Tomasz Bartuś ◽

Jerzy Rydlewski

Keyword(s):

Statistical Tests ◽

Surface Flow ◽

Alluvial Fan ◽

Statistical Testing ◽

New Approach ◽

Sedimentary Environments ◽

Carbonate Sedimentation ◽

South Central ◽

Sedimentation Model ◽

Almost All

Abstract Markov chain analysis was applied to studies of cyclic sedimentation in the Coal Complex of the Bełchatów mining field (part of the Bełchatów lignite deposit). The majority of ambiguous results of statistical testing that were caused by weak, statistically undetectable advantage of either cyclicity over environmental barriers or vice versa, could be explained if only the above-mentioned advantages appeared in the neighbourhood. Therefore, in order to enhance the credibility of statistical tests, a new approach is proposed here in that matrices of observed transition numbers from different boreholes should be added to increase statistical reliability if they originated in a homogeneous area. A second new approach, which consists of revealing statistically undetectable cyclicity of lithofacies alternations, is proposed as well. All data were derived from the mining data base in which differentiation between lithology and sedimentary environments was rather weak. For this reason, the methodological proposals are much more important than details of the sedimentation model in the present paper. Nevertheless, they did reveal some interesting phenomena which may prove important in the reconstruction of peat/lignite environmental conditions. First of all, the presence of cyclicity in the sedimentation model, i.e., cyclic alternation of channel and overbank deposits, represents a fluvial environment. It was also confirmed that the lacustrine subenvironment was cut off from a supply of clastic material by various types of mire barriers. Additionally, our analysis revealed new facts: (i) these barriers also existed between lakes in which either carbonate or clay sedimentation predominated; (ii) there was no barrier between rivers and lakes in which clay sedimentation predominated; (iii) barriers were less efficient in alluvial fan areas but were perfectly tight in regions of phytogenic or carbonate sedimentation; (iv) groundwater, rather than surface flow, was the main source of CaCO3 in lakes in which carbonate sedimentation predominated; (v) a lack of cyclic alternation between abandoned channels and pools with clayey sedimentation; (vi) strong evidence for autocyclic alternation of phytogenic subenvironments and lakes in which carbonate sedimentation predominated was found in almost all areas studied.

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Sensor and Actuator Intrusion Detection for Cyber-Physical Systems via Adaptive Estimation Algorithm

Volume 2: Intelligent Transportation/Vehicles; Manufacturing; Mechatronics; Engine/After-Treatment Systems; Soft Actuators/Manipulators; Modeling/Validation; Motion/Vibration Control Applications; Multi-Agent/Networked Systems; Path Planning/Motion Control; Renewable/Smart Energy Systems; Security/Privacy of Cyber-Physical Systems; Sensors/Actuators; Tracking Control Systems; Unmanned Ground/Aerial Vehicles; Vehicle Dynamics, Estimation, Control; Vibration/Control Systems; Vibrations ◽

10.1115/dscc2020-3245 ◽

2020 ◽

Author(s):

Jiayi Su ◽

Yuqin Weng ◽

Susan C. Schneider ◽

Edwin E. Yaz

Keyword(s):

Kalman Filters ◽

Adaptive Estimation ◽

Estimation Algorithm ◽

Cyber Physical Systems ◽

Motor Speed ◽

New Approach ◽

Physical Systems ◽

Unknown Type ◽

Different Types ◽

Conditional State

Abstract In this work, a new approach to detect sensor and actuator intrusion for Cyber-Physical Systems using a bank of Kalman filters is presented. The case where the unknown type of the intrusion signal is considered first, using two Kalman filters in a bank to provide the conditional state estimates, then the unknown type of intrusion signal can be detected properly via the adaptive estimation algorithm. The case where the target (either sensor or actuator) of the intrusion signal is unknown is also considered, using four Kalman filters in a bank designed to detect if the intrusion signal is about to affect healthy sensor or actuator signal. To test these methods, a DC motor speed control system subject to attack by different types of sensor and actuator signals is simulated. Simulations show that different types of sensor and actuator intrusion signals can be detected properly without the knowledge of the nature and the type of these signals.

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A new device to select carriers for biomass immobilization and application in an aerobic/anaerobic fixed-bed sequencing batch biofilm reactor for nitrogen removal

Water Science & Technology ◽

10.2166/wst.2016.410 ◽

2016 ◽

Vol 74 (11) ◽

pp. 2666-2674 ◽

Cited By ~ 2

Author(s):

A. Sarti ◽

A. W. Lamon ◽

A. Ono ◽

E. Foresti

Keyword(s):

Nitrogen Removal ◽

Fixed Bed ◽

Ammonia Concentration ◽

Nitrogen Loading ◽

Biofilm Reactor ◽

New Approach ◽

New Device ◽

Sequencing Batch Biofilm Reactor ◽

Biofilm Carrier ◽

Aerobic And Anaerobic

This study proposes a new approach to selecting a biofilm carrier for immobilization using dissolved oxygen (DO) microsensors to measure the thickness of aerobic and anaerobic layers in biofilm. The biofilm carriers tested were polyurethane foam, mineral coal (MC), basaltic gravel, and low-density polyethylene. Development of layers in the biofilm carrier surface was evaluated using a flow cell device, and DO profiles were conducted to determine the size of the layers (aerobic and anaerobic). MC was the biofilm carrier selected due to allowing the development of larger aerobic and anaerobic layers in the biofilm (896 and 1,058 μm, respectively). This ability is supposed to improve simultaneous nitrogen removal by nitrification and denitrification biological processes. Thus, as a biofilm carrier, MC was used in a fixed-bed sequencing batch biofilm reactor (FB-SBBR) for treatment of wastewater with a high ammonia concentration (100–400 mgNH4+-N L−1). The FB-SBBR (15.0 L) was filled with matrices of the carrier and operated under alternating aeration and non-aeration periods of 6 h each. At a mean nitrogen loading rate of 0.55 ± 0.10 kgNH4+-N m−3 d−1, the reactor attained a mean nitrification efficiency of 95 ± 9% with nitrite as the main product (aerobic period). Mean denitrification efficiency during the anoxic period was 72 ± 13%.

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An Examination of Background Error Correlations between Mass and Rotational Wind over Precipitation Regions

Monthly Weather Review ◽

10.1175/2009mwr2998.1 ◽

2010 ◽

Vol 138 (2) ◽

pp. 563-578 ◽

Cited By ~ 18

Author(s):

Jean-François Caron ◽

Luc Fillion

Keyword(s):

Linear Regression ◽

Data Assimilation ◽

Traditional Approach ◽

Forecast Error ◽

Lower Atmosphere ◽

Forecast Errors ◽

Background Error ◽

New Approach ◽

Geostrophic Balance ◽

Analysis System

Abstract The differences in the balance characteristics between dry and precipitation areas in estimated short-term forecast error fields are investigated. The motivation is to see if dry and precipitation areas need to be treated differently in atmospheric data assimilation systems. Using an ensemble of lagged forecast differences, it is shown that perturbations are, on average, farther away from geostrophic balance over precipitation areas than over dry areas and that the deviation from geostrophic balance is proportional to the intensity of precipitation. Following these results, the authors investigate whether some improvements in the coupling between mass and rotational wind increments over precipitation areas can be achieved by using only the precipitation points within an ensemble of estimated forecast errors to construct a so-called diabatic balance operator by linear regression. Comparisons with a traditional approach to construct balance operators by linear regression show that the new approach leads to a gradually significant improvement (related to the intensity of the diabatic processes) of the accuracy of the coupling over precipitation areas as judged from an ensemble of lagged forecast differences. Results from a series of simplified data assimilation experiments show that the new balance operators can produce analysis increments that are substantially different from those associated with the traditional balance operator, particularly for observations located in the lower atmosphere. Issues concerning the implementation of this new approach in a full-fledged analysis system are briefly discussed but their investigations are left for a following study.

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