Modeling of temporal groundwater level variations based on a Kalman filter adaptation algorithm with exogenous inputs

Reliable temporal modelling of groundwater level is significant for efficient water resources management in hydrological basins and for the prevention of possible desertification effects. In this work we propose a stochastic method of temporal monitoring and prediction that can incorporate auxiliary information. More specifically, we model the temporal (mean annual and biannual) variation of groundwater level by means of a discrete time autoregressive exogenous variable (ARX) model. The ARX model parameters and its predictions are estimated by means of the Kalman filter adaptation algorithm (KFAA) which, to our knowledge, is applied for the first time in hydrology. KFAA is suitable for sparsely monitored basins that do not allow for an independent estimation of the ARX model parameters. We apply KFAA to time series of groundwater level values from the Mires basin in the island of Crete. In addition to precipitation measurements, we use pumping data as exogenous variables. We calibrate the ARX model based on the groundwater level for the years 1981 to 2006 and use it to predict the mean annual and biannual groundwater level for recent years (2007–2010). The predictions are validated with the available annual averages reported by the local authorities.

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Neutrosophic ratio-type estimators for estimating the population mean

Complex & Intelligent Systems ◽

10.1007/s40747-021-00439-1 ◽

2021 ◽

Author(s):

Zaigham Tahir ◽

Hina Khan ◽

Muhammad Aslam ◽

Javid Shabbir ◽

Yasar Mahmood ◽

...

Keyword(s):

Minimum Mean Square Error ◽

Auxiliary Information ◽

Population Parameter ◽

Uncertain Information ◽

Population Mean ◽

Classical Statistics ◽

Neutrosophic Statistics ◽

The Mean ◽

Type Data ◽

First Time

AbstractAll researches, under classical statistics, are based on determinate, crisp data to estimate the mean of the population when auxiliary information is available. Such estimates often are biased. The goal is to find the best estimates for the unknown value of the population mean with minimum mean square error (MSE). The neutrosophic statistics, generalization of classical statistics tackles vague, indeterminate, uncertain information. Thus, for the first time under neutrosophic statistics, to overcome the issues of estimation of the population mean of neutrosophic data, we have developed the neutrosophic ratio-type estimators for estimating the mean of the finite population utilizing auxiliary information. The neutrosophic observation is of the form $${Z}_{N}={Z}_{L}+{Z}_{U}{I}_{N}\, {\rm where}\, {I}_{N}\in \left[{I}_{L}, {I}_{U}\right], {Z}_{N}\in [{Z}_{l}, {Z}_{u}]$$ Z N = Z L + Z U I N where I N ∈ I L , I U , Z N ∈ [ Z l , Z u ] . The proposed estimators are very helpful to compute results when dealing with ambiguous, vague, and neutrosophic-type data. The results of these estimators are not single-valued but provide an interval form in which our population parameter may have more chance to lie. It increases the efficiency of the estimators, since we have an estimated interval that contains the unknown value of the population mean provided a minimum MSE. The efficiency of the proposed neutrosophic ratio-type estimators is also discussed using neutrosophic data of temperature and also by using simulation. A comparison is also conducted to illustrate the usefulness of Neutrosophic Ratio-type estimators over the classical estimators.

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RESULTS OF INTRALESIONAL TRIAMCINOLONE ACETONIDE FOR CHALAZION TREATMENT

Journal of Medicine and Pharmacy ◽

10.34071/jmp.2011.5.13 ◽

2011 ◽

pp. 100-104

Author(s):

Thi Thu Nguyen ◽

Viet Hien Vo ◽

Thi Em Do

Keyword(s):

Success Rate ◽

Key Words ◽

Triamcinolone Acetonide ◽

Lower Eyelid ◽

Upper Eyelid ◽

Interventional Trial ◽

The Mean ◽

First Time

The study use intralesional triamcinolone acetonide injection proceduce for chalazion treatment.1. Objectives: To evaluate results of intralesional triamcinolone acetonide injection for chalazion treatment. 2. Method: This noncomparative prospective interventional trial included 72 chalazions of 61 patients. 3. Results: 61 patients (72 chalazions) with 19 males (31.1%) và 42 females (68.9%), the mean age was 24 ± 9,78 years. 31.1% patients was the first time chalazion and 68.9% patients was more than one times chalazion including 78.6% patients was recurrent at the first position and 21.4% patients occur at new position. 72 chalazions with 16 (22.2%) chalazions was treated before and 56 (77.8%) chalazions wasn’t done that. 72 chalazions with 49 chalazions (68.1%) are local in upper eyelid and 23 chalazions (31.9%) are local in lower eyelid. The mean of chalazion diameter is 6.99 ± 3.03mm. Intralesional triamcinolone acetonide is injected to treat 72 chalazions with 16 (22.2%) chalazions are injected through the route of skin and 56 (77.8%) chalazions are injected through the route of conjunctiva. After 2 weeks follow-up, the success rate was 93.1% and 6.9% failed. 4. Conclusion: intralesional triamcinolone acetonide injection for chalazion treatment is really effective. Key words: chalazion, intralesional triamcinolone acetonide.

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Synthesis of a silymarin-gold nanoparticle conjugate and analysis of its liver-protecting activity

Current Pharmaceutical Biotechnology ◽

10.2174/1389201022666210101163734 ◽

2021 ◽

Vol 22 ◽

Author(s):

Sergey Staroverov ◽

Sergey Kozlov ◽

Alexander Fomin ◽

Konstantib Gabalov ◽

Alexey Volkov ◽

...

Keyword(s):

Gold Nanoparticles ◽

Liver Disease ◽

Carbon Tetrachloride ◽

Glutathione Depletion ◽

Laboratory Animals ◽

Experimental Hepatitis ◽

Acute Liver Disease ◽

The Mean ◽

Extent Of Damage ◽

First Time

Background: The liver disease problem prompts investigators to search for new methods of liver treatment. Introduction: Silymarin (Sil) protects the liver by reducing the concentration of free radicals and the extent of damage to the cell membranes. A particularly interesting method to increase the bioavailability of Sil is to use synthesized gold nanoparticles (AuNPs) as reagents. The study considered whether it was possible to use the silymarin-AuNP conjugate as a potential liver-protecting drug. Method: AuNPs were conjugated to Sil and examine the liver-protecting activity of the conjugate. Experimental hepatitis and hepatocyte cytolysis after carbon tetrachloride actionwere used as a model system, and the experiments were conducted on laboratory animals. Result: For the first time, silymarin was conjugated to colloidal gold nanoparticles (AuNPs). Electron microscopy showed that the resultant preparations were monodisperse and that the mean conjugate diameter was 18–30 nm ± 0.5 nm (mean diameter of the native nanoparticles, 15 ± 0.5 nm). In experimental hepatitis in mice, conjugate administration interfered with glutathione depletion in hepatocytes in response to carbon tetrachloride was conducive to an increase in energy metabolism, and stimulated the monocyte–macrophage function of the liver. The results were confirmed by the high respiratory activity of the hepatocytes in cell culture. Conclusion: We conclude that the silymarin-AuNP conjugate holds promise as a liver-protecting agent in acute liver disease caused by carbon tetrachloride poisoning.

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Attitude and Heading Estimation for Indoor Positioning Based on the Adaptive Cubature Kalman Filter

Micromachines ◽

10.3390/mi12010079 ◽

2021 ◽

Vol 12 (1) ◽

pp. 79

Author(s):

Jijun Geng ◽

Linyuan Xia ◽

Dongjin Wu

Keyword(s):

Kalman Filter ◽

Angular Rate ◽

Indoor Positioning ◽

Location Based Services ◽

Statistical Characteristics ◽

Fading Memory ◽

Limited Memory ◽

Cubature Kalman Filter ◽

The Mean ◽

Heading Estimation

The demands for indoor positioning in location-based services (LBS) and applications grow rapidly. It is beneficial for indoor positioning to combine attitude and heading information. Accurate attitude and heading estimation based on magnetic, angular rate, and gravity (MARG) sensors of micro-electro-mechanical systems (MEMS) has received increasing attention due to its high availability and independence. This paper proposes a quaternion-based adaptive cubature Kalman filter (ACKF) algorithm to estimate the attitude and heading based on smart phone-embedded MARG sensors. In this algorithm, the fading memory weighted method and the limited memory weighted method are used to adaptively correct the statistical characteristics of the nonlinear system and reduce the estimation bias of the filter. The latest step data is used as the memory window data of the limited memory weighted method. Moreover, for restraining the divergence, the filter innovation sequence is used to rectify the noise covariance measurements and system. Besides, an adaptive factor based on prediction residual construction is used to overcome the filter model error and the influence of abnormal disturbance. In the static test, compared with the Sage-Husa cubature Kalman filter (SHCKF), cubature Kalman filter (CKF), and extended Kalman filter (EKF), the mean absolute errors (MAE) of the heading pitch and roll calculated by the proposed algorithm decreased by 4–18%, 14–29%, and 61–77% respectively. In the dynamic test, compared with the above three filters, the MAE of the heading reduced by 1–8%, 2–18%, and 2–21%, and the mean of location errors decreased by 9–22%, 19–31%, and 32–54% respectively by using the proposed algorithm for three participants. Generally, the proposed algorithm can effectively improve the accuracy of heading. Moreover, it can also improve the accuracy of attitude under quasistatic conditions.

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The Relationship between Inflammation Markers (CRP, IL-6, sCD40L) and Colorectal Cancer Stage, Grade, Size and Location

Diagnostics ◽

10.3390/diagnostics11081382 ◽

2021 ◽

Vol 11 (8) ◽

pp. 1382

Author(s):

Olga Martyna Koper-Lenkiewicz ◽

Violetta Dymicka-Piekarska ◽

Anna Justyna Milewska ◽

Justyna Zińczuk ◽

Joanna Kamińska

Keyword(s):

Colorectal Cancer ◽

Linear Regression ◽

Tumor Size ◽

Distal Colon ◽

Proximal Colon ◽

Model Parameters ◽

Grade Group ◽

Who Grade ◽

The Mean ◽

Mean Concentration

The aim of the study was the evaluation whether in primary colorectal cancer (CRC) patients (n = 55): age, sex, TNM classification results, WHO grade, tumor location (proximal colon, distal colon, rectum), tumor size, platelet count (PLT), mean platelet volume (MPV), mean platelet component (MCP), levels of carcinoembryonic antigen (CEA), cancer antigen (CA 19-9), as well as soluble lectin adhesion molecules (L-, E-, and P-selectins) may influence circulating inflammatory biomarkers: IL-6, CRP, and sCD40L. We found that CRP concentration evaluation in routine clinical practice may have an advantage as a prognostic biomarker in CRC patients, as this protein the most comprehensively reflects clinicopathological features of the tumor. Univariate linear regression analysis revealed that in CRC patients: (1) with an increase in PLT by 10 × 103/μL, the mean concentration of CRP increases by 3.4%; (2) with an increase in CA 19-9 of 1 U/mL, the mean concentration of CRP increases by 0.7%; (3) with the WHO 2 grade, the mean CRP concentration increases 3.631 times relative to the WHO 1 grade group; (4) with the WHO 3 grade, the mean CRP concentration increases by 4.916 times relative to the WHO 1 grade group; (5) with metastases (T1-4N+M+) the mean CRP concentration increases 4.183 times compared to non-metastatic patients (T1-4N0M0); (6) with a tumor located in the proximal colon, the mean concentration of CRP increases 2.175 times compared to a tumor located in the distal colon; (7) in patients with tumor size > 3 cm, the CRP concentration is about 2 times higher than in patients with tumor size ≤ 3 cm. In the multivariate linear regression model, the variables that influence the mean CRP value in CRC patients included: WHO grade and tumor localization. R2 for the created model equals 0.50, which indicates that this model explains 50% of the variance in the dependent variable. In CRC subjects: (1) with the WHO 2 grade, the mean CRP concentration rises 3.924 times relative to the WHO 1 grade; (2) with the WHO 3 grade, the mean CRP concentration increases 4.721 times in relation to the WHO 1 grade; (3) with a tumor located in the rectum, the mean CRP concentration rises 2.139 times compared to a tumor located in the distal colon; (4) with a tumor located in the proximal colon, the mean concentration of CRP increases 1.998 times compared to the tumor located in the distal colon; if other model parameters are fixed.

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Explanation Plus Prediction—The Logical Focus of Project Management Research

Project Management Journal ◽

10.1177/8756972821999945 ◽

2021 ◽

pp. 875697282199994

Author(s):

Joseph F. Hair ◽

Marko Sarstedt

Keyword(s):

Project Management ◽

Statistical Models ◽

Predictive Power ◽

Mean Absolute Error ◽

Explanatory Power ◽

Absolute Error ◽

Model Parameters ◽

Mean Square ◽

Management Research ◽

The Mean

Most project management research focuses almost exclusively on explanatory analyses. Evaluation of the explanatory power of statistical models is generally based on F-type statistics and the R 2 metric, followed by an assessment of the model parameters (e.g., beta coefficients) in terms of their significance, size, and direction. However, these measures are not indicative of a model’s predictive power, which is central for deriving managerial recommendations. We recommend that project management researchers routinely use additional metrics, such as the mean absolute error or the root mean square error, to accurately quantify their statistical models’ predictive power.

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Assimilation of Dynamic Combined Finite Discrete Element Methods Using the Ensemble Kalman Filter

Applied Sciences ◽

10.3390/app11072898 ◽

2021 ◽

Vol 11 (7) ◽

pp. 2898

Author(s):

Humberto C. Godinez ◽

Esteban Rougier

Keyword(s):

Kalman Filter ◽

Ensemble Kalman Filter ◽

Failure Modes ◽

Split Hopkinson Pressure Bar ◽

Peak Stress ◽

Discrete Element ◽

Material Behavior ◽

Model Parameters ◽

Hopkinson Pressure Bar ◽

Parameter Values

Simulation of fracture initiation, propagation, and arrest is a problem of interest for many applications in the scientific community. There are a number of numerical methods used for this purpose, and among the most widely accepted is the combined finite-discrete element method (FDEM). To model fracture with FDEM, material behavior is described by specifying a combination of elastic properties, strengths (in the normal and tangential directions), and energy dissipated in failure modes I and II, which are modeled by incorporating a parameterized softening curve defining a post-peak stress-displacement relationship unique to each material. In this work, we implement a data assimilation method to estimate key model parameter values with the objective of improving the calibration processes for FDEM fracture simulations. Specifically, we implement the ensemble Kalman filter assimilation method to the Hybrid Optimization Software Suite (HOSS), a FDEM-based code which was developed for the simulation of fracture and fragmentation behavior. We present a set of assimilation experiments to match the numerical results obtained for a Split Hopkinson Pressure Bar (SHPB) model with experimental observations for granite. We achieved this by calibrating a subset of model parameters. The results show a steady convergence of the assimilated parameter values towards observed time/stress curves from the SHPB observations. In particular, both tensile and shear strengths seem to be converging faster than the other parameters considered.

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P1398 Echocardiographic continuous monitoring of exercise stress test using probe fixation device

European Heart Journal - Cardiovascular Imaging ◽

10.1093/ehjci/jez319.831 ◽

2020 ◽

Vol 21 (Supplement_1) ◽

Author(s):

K Wdowiak-Okrojek ◽

P Wejner-Mik ◽

Z Bednarkiewicz ◽

P Lipiec ◽

J D Kasprzak

Keyword(s):

Image Quality ◽

Physical Exercise ◽

Stress Test ◽

Exercise Stress Test ◽

Bicycle Ergometer ◽

Exercise Stress ◽

Fixation Device ◽

The Mean ◽

First Time

Abstract Background Stress echocardiography (SE) plays an important role among methods of noninvasive diagnosis of ischemic disease. Despite the advantages of physical exercise as the most physiologic stressor, it is difficult (bicycle ergometer) or impossible (treadmill) to obtain and maintain the acoustic window during the exercise. Recently, an innovative probe fixation device was introduced and a research plan was developed to assess the feasibility of external probe fixation during exercise echocardiography on a supine bicycle and upright treadmill exercise for the first time. Methods 37 subjects (36 men, mean age 39 ± 16 years, 21 healthy volunteers, 16 patients with suspected coronary artery disease) were included in this study. This preliminary testing stage included mostly men due to more problematic probe fixation in women. All subjects underwent a submaximal exercise stress test on a treadmill (17/37) or bicycle ergometer (11/37). Both sector and matrix probes were used. We assessed semi-quantitatively the quality of acquired apical views at each stage – the four-point grading system was used (0-no view, 1-suboptimal quality, 2-optimal quality, 3-very good quality), 2-3 sufficient for diagnosis. Results The mean time required for careful positioning of the probe and image optimization was 12 ± 3 min and shortened from 13,7 to 11,1 minutes (mean) in first vs second half of the cohort documenting learning curve. At baseline, 9 patients had at least one apical view of quality precluding reliable analysis. Those patients were excluded from further assessment. During stress, 17 patients maintained the optimal or very good quality of all apical views, whereas in 11 patients the quality significantly decreased during the stress test and required probe repositioning. The mean image quality score at baseline was 2,61 ± 0,48 and 2,25 ± 0,6 after exercise. Expectedly, good image quality was easier to obtain and maintain in the supine position (score 2,74 ± 0,44) points as compared with upright position (score 2,25 ± 0,57). Conclusion This preliminary, unique experience with external probe fixation device indicates that continuous acquisition and monitoring of echocardiographic images is feasible during physical exercise, and for the first time ever - also on the treadmill. This feasibility data stem from almost exclusively male patients and the estimated rate of sufficient image quality throughout the entire test is currently around 60%. We are hoping, that gaining more experience with the product could increase the success rate on exercise tests. Abstract P1398 Figure. Treadmill and ergometer stress test

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Parameter Identification and State-of-Charge Estimation for Lithium-Ion Batteries Using Separated Time Scales and Extended Kalman Filter

Energies ◽

10.3390/en14041054 ◽

2021 ◽

Vol 14 (4) ◽

pp. 1054

Author(s):

Kuo Yang ◽

Yugui Tang ◽

Zhen Zhang

Keyword(s):

Kalman Filter ◽

Parameter Identification ◽

Open Circuit Voltage ◽

Lithium Ion ◽

Open Circuit ◽

State Of Charge ◽

Recursive Least Squares ◽

Model Parameters ◽

Soc Estimation ◽

Battery Model

With the development of new energy vehicle technology, battery management systems used to monitor the state of the battery have been widely researched. The accuracy of the battery status assessment to a great extent depends on the accuracy of the battery model parameters. This paper proposes an improved method for parameter identification and state-of-charge (SOC) estimation for lithium-ion batteries. Using a two-order equivalent circuit model, the battery model is divided into two parts based on fast dynamics and slow dynamics. The recursive least squares method is used to identify parameters of the battery, and then the SOC and the open-circuit voltage of the model is estimated with the extended Kalman filter. The two-module voltages are calculated using estimated open circuit voltage and initial parameters, and model parameters are constantly updated during iteration. The proposed method can be used to estimate the parameters and the SOC in real time, which does not need to know the state of SOC and the value of open circuit voltage in advance. The method is tested using data from dynamic stress tests, the root means squared error of the accuracy of the prediction model is about 0.01 V, and the average SOC estimation error is 0.0139. Results indicate that the method has higher accuracy in offline parameter identification and online state estimation than traditional recursive least squares methods.

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Robustness and Sensitivity Tuning of the Kalman Filter for Speech Enhancement

Signals ◽

10.3390/signals2030027 ◽

2021 ◽

Vol 2 (3) ◽

pp. 434-455

Author(s):

Sujan Kumar Roy ◽

Kuldip K. Paliwal

Keyword(s):

Kalman Filter ◽

Speech Enhancement ◽

Linear Prediction ◽

Real Life ◽

Model Parameters ◽

Noise Variance ◽

Noisy Speech ◽

Kalman Gain ◽

Whitening Filter ◽

Prediction Coefficient

Inaccurate estimates of the linear prediction coefficient (LPC) and noise variance introduce bias in Kalman filter (KF) gain and degrade speech enhancement performance. The existing methods propose a tuning of the biased Kalman gain, particularly in stationary noise conditions. This paper introduces a tuning of the KF gain for speech enhancement in real-life noise conditions. First, we estimate noise from each noisy speech frame using a speech presence probability (SPP) method to compute the noise variance. Then, we construct a whitening filter (with its coefficients computed from the estimated noise) to pre-whiten each noisy speech frame prior to computing the speech LPC parameters. We then construct the KF with the estimated parameters, where the robustness metric offsets the bias in KF gain during speech absence of noisy speech to that of the sensitivity metric during speech presence to achieve better noise reduction. The noise variance and the speech model parameters are adopted as a speech activity detector. The reduced-biased Kalman gain enables the KF to minimize the noise effect significantly, yielding the enhanced speech. Objective and subjective scores on the NOIZEUS corpus demonstrate that the enhanced speech produced by the proposed method exhibits higher quality and intelligibility than some benchmark methods.

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