Time-varying parameters estimation with adaptive neural network EKF for missile-dual control system

In this paper, a filtering method is presented to estimate time-varying parameters of a missile dual control system with tail fins and reaction jets as control variables. In this method, the long-short-term memory(LSTM) neural network is nested into the extended Kalman filter(EKF) to modify the Kalman gain such that the filtering performance is improved in the presence of large model uncertainties. To avoid the unstable network output caused by the abrupt changes of system states,an adaptive correction factor is introduced to correct the network output online. In the process of training the network, a multi-gradient descent learning mode is proposed to better fit the internal state of the system, and a rolling training is used to implement an online prediction logic. Based on the Lyapunov second method, we discuss the stability of the system, the result shows that when the training error of neural network is sufficiently small, the system is asymptotically stable. With its application to the estimation of time-varying parameters of a missile dual control system, the LSTM-EKF shows better filtering performance than the EKF and adaptive EKF(AEKF) when there exist large uncertainties in the system model.

Adaptive Containment Control for Fractional-Order Nonlinear Multi-Agent Systems With Time-Varying Parameters

This paper investigates adaptive containment control for a class of fractional-order multi-agent systems(FOMASs)with time-varying parameters and disturbances.By using the bounded estimation method,the difficulty generated by the timevarying parameters and disturbances is overcome.The command filter is introduced to solve the complexity problem inherent in adaptive backstepping control.Meanwhile,in order to eliminate the effect of filter errors,a novel distributed error compensating scheme is constructed,in which only the local information from the neighbor agents is utilized.Then,a distributed adaptive containment control scheme for FOMASs is developed based on backstepping to guarantee that the outputs of all the followers are steered to the convex hull spanned by the leaders.Based on the extension of Barbalat's lemma to fractional-order integrals,it can be proven that the containment errors and the compensating signals have asymptotic convergence.Finally,three simulation examples are given to show the feasibility and effectiveness of the proposed control method.

A Novel PF-LSSVR-based Framework for Failure Prognosis of Nonlinear Systems with Time-varying Parameters

Particle filtering （PF） is being applied successfully in nonlinear and/or non-Gaussian system failure prognosis. However, for failure prediction of many complex systems whose dynamic state evolution models involve time-varying parameters, the tradi- tional PF-based prognosis framework will probably generate serious deviations in results since it implements prediction through iterative calculation using the state models. To address the problem, this paper develops a novel integrated PF-LSSVR frame- work based on PF and least squares support vector regression （LSSVR） for nonlinear system failure prognosis. This approach employs LSSVR for long-term observation series prediction and applies PF-based dual estimation to collaboratively estimate the values of system states and parameters of the corresponding future time instances. Meantime, the propagation of prediction un- certainty is emphatically taken into account. Therefore, PF-LSSVR avoids over-dependency on system state models in prediction phase. With a two-sided failure definition, the probability distribution of system remaining useful life （RUL） is accessed and the corresponding methods of calculating performance evaluation metrics are put forward. The PF-LSSVR framework is applied to a three-vessel water tank system failure prognosis and it has much higher prediction accuracy and confidence level than traditional PF-based framework.

Interaction between systemic iron parameters and left ventricular structure and function in the preserved ejection fraction population:a two-sample bidirectional Mendelian randomization study

BACKGROUND Left ventricular(LV)remodeling and diastolic function in people with heart failure(HF)are correlated with iron status;however,the causality is uncertain.This Mendelian randomization(MR)study investigated the bidirectional causal relationship between systemic iron parameters and LV structure and function in a preserved ejection fraction population.METHODS Transferrin saturation(TSAT),total iron binding capacity(TIBC),and serum iron and ferritin levels were extracted as instrumental variables for iron parameters from meta-analyses of public genome-wide association studies.Individuals without myocardial infarction history,HF,or LV ejection fraction(LVEF)<50%(n=16,923)in the UK Biobank Cardiovascular Magnetic Resonance Imaging Study constituted the outcome dataset.The dataset included LV end-diastolic volume,LV endsystolic volume,LV mass(LVM),and LVM-to-end-diastolic volume ratio(LVMVR).We used a two-sample bidirectional MR study with inverse variance weighting(IVW)as the primary analysis method and estimation methods using different algorithms to improve the robustness of the results.RESULTS In the IVW analysis,one standard deviation(SD)increased in TSAT significantly correlated with decreased LVMVR(β=-0.1365;95%confidence interval[CI]:-0.2092 to-0.0638;P=0.0002)after Bonferroni adjustment.Conversely,no significant relationships were observed between other iron and LV parameters.After Bonferroni correction,reverse MR analysis showed that one SD increase in LVEF significantly correlated with decreased TSAT(β=-0.0699;95%CI:-0.1087 to-0.0311;P=0.0004).No heterogeneity or pleiotropic effects evidence was observed in the analysis.CONCLUSIONS We demonstrated a causal relationship between TSAT and LV remodeling and function in a preserved ejection fraction population.

A Novel On-Site-Real-Time Method for Identifying Characteristic Parameters Using Ultrasonic Echo Groups and Neural Network

On-site and real-time non-destructive measurement of elastic constants for materials of a component in a in-service structure is a challenge due to structural complexities,such as ambiguous boundary,variable thickness,nonuniform material properties.This work develops for the first time a method that uses ultrasound echo groups and artificial neural network(ANN)for reliable on-site real-time identification of material parameters.The use of echo groups allows the use of lower frequencies,and hence more accommodative to structural complexity.To train the ANNs,a numerical model is established that is capable of computing the waveform of ultrasonic echo groups for any given set of material properties of a given structure.The waveform of an ultrasonic echo groups at an interest location on the surface the structure with material parameters varying in a predefined range are then computed using the numerical model.This results in a set of dataset for training the ANN model.Once the ANN is trained,the material parameters can be identified simultaneously using the actual measured echo waveform as input to the ANN.Intensive tests have been conducted both numerically and experimentally to evaluate the effectiveness and accuracy of the currently proposed method.The results show that the maximum identification error of numerical example is less than 2%,and the maximum identification error of experimental test is less than 7%.Compared with currently prevailing methods and equipment,the proposefy the density and thickness,in addition to the elastic constants.Moreover,the reliability and accuracy of inverse prediction is significantly improved.Thus,it has broad applications and enables real-time field measurements,which has not been fulfilled by any other available methods or equipment.

IDENTIFICATION OF TIME-VARYING MODAL PARAMETERS USING LINEAR TIME-FREQUENCY REPRESENTATION

A new method of parameter identification based on linear time-frequencyrepresentation and Hubert transform is proposed to identity modal parameters of linear time-varyingsystems from measured vibration responses. Using Gabor expansion and synthesis theory, measuredresponses are represented in the time-frequency domain and modal components are reconstructed bytime-frequency filtering. The Hilbert transform is applied to obtain time histories of the amplitudeand phase angle of each modal component, from which time-varying frequencies and damping ratios areidentified. The proposed method has been demonstrated with a numerical example in which a lineartime-varying system of two degrees of freedom is used to validate the identification scheme based ontime-frequency representation. Simulation results have indicated that time-frequency representationpresents an effective tool for modal parameter identification of time-varying systems.

State estimation for neural neutral-type networks with mixed time-varying delays and Markovian jumping parameters

This paper is concerned with a delay-dependent state estimator for neutral-type neural networks with mixed timevarying delays and Markovian jumping parameters.The addressed neural networks have a finite number of modes,and the modes may jump from one to another according to a Markov process.By construction of a suitable Lyapunov-Krasovskii functional,a delay-dependent condition is developed to estimate the neuron states through available output measurements such that the estimation error system is globally asymptotically stable in a mean square.The criterion is formulated in terms of a set of linear matrix inequalities（LMIs）,which can be checked efficiently by use of some standard numerical packages.

Chronic Hepatitis B Virus Infection: Biological Parameters in Patients Treated with Tenofovir Disoproxil Fumarate

Chronic hepatitis B causes a liver disease characterized by inflammation of the liver parenchyma. The aim of this study was to investigate the evolution of biological parameters in patients treated with Tenofovir for chronic B infection at the Commune V referral health center in Bamako. We obtained a prevalence of 14.15%. The most represented age group was 31 - 40 years, with 36.8%. The sex ratio was 1.44 in favour of men. Viral load was undetectable after 18 months of treatment in 25 patients (42.37%). Tenofovir, the 1st-line drug in Mali, is effective on the biological parameters monitored in patients.

Study on the clogging mechanism of punching screen in sand control by the punching structure parameters

As an independent sand control unit or a common protective shell of a high-quality screen,the punching screen is the outermost sand retaining unit of the sand control pipe which is used in geothermal well or oil and gas well.However,most screens only consider the influence of the internal sand retaining medium parameters in the sand control performance design while ignoring the influence of the plugging of the punching screen on the overall sand retaining performance of the screen.To explore the clogging mechanism of the punching screen,this paper established the clogging mechanism calculation model of a single punching screen sand control unit by using the computational fluid mechanics-discrete element method(CFD-DEM)combined method.According to the combined motion of particles and fluids,the influence of the internal flow state on particle motion and accumulation was analyzed.The results showed that(1)the clogging process of the punching sand control unit is divided into three stages:initial clogging,aggravation of clogging and stability of clogging.In the initial stage of blockage,coarse particles form a loose bridge structure,and blockage often occurs preferentially at the streamline gathering place below chamfering inside the sand control unit.In the stage of blockage intensification,the particle mass develops into a relatively complete sand bridge,which develops from both ends of the opening to the center of the opening.In the stable plugging stage,the sand deposits show a“fan shape”and form a“V-shaped”gully inside the punching slot element.(2)Under a certain reservoir particle-size distribution,The slit length and opening height have a large influence on the permeability and blockage rate,while the slit width size has little influence on the permeability and blockage rate.The microscopic clogging mechanism and its law of the punching screen prevention unit are proposed in this study,which has some field guidance significance for the design of punching screen and sand prevention selection.

A Physical Security Technology Based upon Doubly Multiple Parameters Weighted Fractional Fourier Transform

Enhancing the security of the wireless communication is necessary to guarantee the reliable of the data transmission, due to the broadcast nature of wireless channels. In this paper, we provide a novel technology referred to as doubly multiple parameters weighted fractional Fourier transform(DMWFRFT), which can strengthen the physical layer security of wireless communication. This paper introduces the concept of DM-WFRFT based on multiple parameters WFRFT(MP-WFRFT), and then presents its four properties. Based on these properties, the parameters decryption probability is analyzed in terms of the number of parameters. The number of parameters for DM-WFRFT is more than that of the MP-WFRFT,which indicates that the proposed scheme can further strengthen the the physical layer security. Lastly, some numerical simulations are carried out to illustrate that the efficiency of proposed DM-WFRFT is related to preventing eavesdropping, and the effect of parameters variety on the system performance is associated with the bit error ratio(BER).

Exponential synchronization of complex dynamical networks with Markovian jumping parameters using sampled-data and mode-dependent probabilistic time-varying delays

In this paper, the problem of exponential synchronization of complex dynamical networks with Markovian jumping parameters using sampled-data and Mode-dependent probabilistic time-varying coupling delays is investigated. The sam- pling period is assumed to be time-varying and bounded. The information of probability distribution of the time-varying delay is considered and transformed into parameter matrices of the transferred complex dynamical network model. Based on the condition, the design method of the desired sampled data controller is proposed. By constructing a new Lyapunov functional with triple integral terms, delay-distribution-dependent exponential synchronization criteria are derived in the form of linear matrix inequalities. Finally, two numerical examples are given to illustrate the effectiveness of the proposed methods.

Quaternion-Based Adaptive Trajectory Tracking Control of a Rotor-Missile with Unknown Parameters Identification

This paper investigates the adaptive trajectory tracking control problem and the unknown parameter identification problem of a class of rotor-missiles with parametric system uncertainties.First,considering the uncertainty of structural and aerodynamic parameters,the six-degree-of-freedom(6Do F) nonlinear equations describing the position and attitude dynamics of the rotor-missile are established,respectively,in the inertial and body-fixed reference frames.Next,a hierarchical adaptive trajectory tracking controller that can guarantee closed-loop stability is proposed according to the cascade characteristics of the 6Do F dynamics.Then,a memory-augmented update rule of unknown parameters is proposed by integrating all historical data of the regression matrix.As long as the finitely excited condition is satisfied,the precise identification of unknown parameters can be achieved.Finally,the validity of the proposed trajectory tracking controller and the parameter identification method is proved through Lyapunov stability theory and numerical simulations.

Comparison of ocular biometric parameters between two swept-source optical coherence tomography devices and Scheimpflug tomography in patients with cataract

AIM:To assess and compare the variations and agreements across different ocular biometric parameters using swept-source optical coherence tomography(SS-OCT)and Scheimpflug tomography in patients diagnosed with cataract.METHODS:This prospective case series was conducted at Tianjin Medical University Eye Hospital.In total,212 eyes from 212 patients scheduled for phacoemulsification were included.Eyes were evaluated preoperatively using two SSOCT devices(IOLMaster700 and CASIA2)and Scheimpflug tomography(Pentacam).Central corneal thickness(CCT),anterior chamber depth(ACD),aqueous depth(AQD),white-to-white distance(WTW),flat simulated keratometry(Kf),steep simulated keratometry(Ks),mean keratometry(Km),and total corneal keratometry(TKm)were measured.Intraclass correlation coefficient(ICC),95%confidence intervals(CI)and limits of agreement(LoA)widths were conducted to assess differences and correlations between devices.RESULTS:All parameters,except for Ks,were significantly different.Pairwise comparison revealed no significant differences between keratometry obtained by IOLMaster 700 and Pentacam.LoA widths of all paired comparisons for Ks were>0.80 D.Except for WTW between IOLMaster 700 and CASIA2 and between CASIA2 and Pentacam,other Pearson’s coefficients between devices showed a strong correlation(all r>0.95).The ICC of WTW(ICC=0.438,95%CI 0.167-0.625)showed poor reliability.The reliability of CCT,ACD,and AQD was excellent(all ICC>0.95),whereas that of TKm was good(ICC=0.827,95%CI 0.221-0.939).A significant linear correlation was also observed among devices.CONCLUSION:The ocular parameters derived from the use of IOLMaster700,CASIA2,and Pentacam exhibit significant discrepancies;as such,measurements from these devices should not be deemed as interchangeable.

Digital measuring the ocular morphological parameters of guinea pig eye in vivo with Python

AIM:To quantitatively measure ocular morphological parameters of guinea pig with Python technology.METHODS:Thirty-six eyeballs of eighteen 3-weekold guinea pigs were measured with keratometer and photographed to obtain the horizontal,coronal,and sagittal planes respectively.The corresponding photo pixels-actual length ratio was acquired by a proportional scale.The edge coordinates were identified artificially by ginput function.Circle and conic curve fitting were applied to fit the contour of the eyeball in the sagittal,coronal and horizontal view.The curvature,curvature radius,eccentricity,tilt angle,corneal diameter,and binocular separation angle were calculated according to the geometric principles.Next,the eyeballs were removed,canny edge detection was applied to identify the contour of eyeball in vitro.The results were compared between in vivo and in vitro.RESULTS:Regarding the corneal curvature and curvature radius on the horizontal and sagittal planes,no significant differences were observed among results in vivo,in vitro,and the keratometer.The horizontal and vertical binocular separation angles were 130.6°±6.39°and 129.8°±9.58°respectively.For the corneal curvature radius and eccentricity in vivo,significant differences were observed between horizontal and vertical planes.CONCLUSION:The Graphical interface window of Python makes up the deficiency of edge detection,which requires too much definition in Matlab.There are significant differences between guinea pig and human beings,such as exotropic eye position,oblique oval eyeball,and obvious discrepancy of binoculus.This study helps evaluate objectively the ocular morphological parameters of small experimental animals in emmetropization research.

Analysis and comparison of retinal vascular parameters under different glucose metabolic status based on deep learning

AIM:To develop a deep learning-based model for automatic retinal vascular segmentation,analyzing and comparing parameters under diverse glucose metabolic status(normal,prediabetes,diabetes)and to assess the potential of artificial intelligence(AI)in image segmentation and retinal vascular parameters for predicting prediabetes and diabetes.METHODS:Retinal fundus photos from 200 normal individuals,200 prediabetic patients,and 200 diabetic patients(600 eyes in total)were used.The U-Net network served as the foundational architecture for retinal arteryvein segmentation.An automatic segmentation and evaluation system for retinal vascular parameters was trained,encompassing 26 parameters.RESULTS:Significant differences were found in retinal vascular parameters across normal,prediabetes,and diabetes groups,including artery diameter(P=0.008),fractal dimension(P=0.000),vein curvature(P=0.003),C-zone artery branching vessel count(P=0.049),C-zone vein branching vessel count(P=0.041),artery branching angle(P=0.005),vein branching angle(P=0.001),artery angle asymmetry degree(P=0.003),vessel length density(P=0.000),and vessel area density(P=0.000),totaling 10 parameters.CONCLUSION:The deep learning-based model facilitates retinal vascular parameter identification and quantification,revealing significant differences.These parameters exhibit potential as biomarkers for prediabetes and diabetes.

Effects of Fresh Cupressus sempervirens Leaves Infusion on Growth Performance, Intestinal Microbiota and Haemato-Biochemical Parameters in Broilers

The accumulation of growth-promoting antibiotic residues in animal products and the resistance developed by bacteria in poultry farms has led to a search for natural compounds derived from plants. This study was designed to promote the production performance of broiler chickens using fresh Cupressus sempervirens leaves infusion. Fresh Cupressus sempervirens leaves were harvested, washed, chopped and ground to a paste using a blender and fermented for three days in a closed container at a rate of 500 g/L of water. The solution obtained was filtered and added at the rate of 2, 4, 6, 8 and 10 ml/L of drinking water. The chickens fed on the graded level of the solution were compared to a control ration without an additive and positive control group supplemented with 1 g antibiotic/kg feed. At the finisher phase and throughout the study period, water intake increased significantly (P < 0.05) with increasing levels of infusion. Feed intake decreased significantly (P < 0.05) with 2 and 4 ml of infusion/L drinking water. Live weight and weight gain were significantly (P < 0.05) higher with 6 ml/L, while feed conversion significantly (P < 0.05) decreased with the same treatment compared with the control treatment without additives (T0). Carcass characteristics were not significantly (P > 0.05) affected by the inclusion of Cupressus sempervirens infusion. Haematological parameters significantly (P < 0.05) increase independently of the rate of incorporation of the infusion into the drinking water, with the exception of RBCs, MCHT and PCT. Serum content in total protein, globulins, LDL cholesterol and triglycerides were significantly (P < 0.05) high with 8 and 10 ml Cupressus sempervirens infusion/litre drinking water as compared to all other treatments. AST, ALT, urea, creatine, albumin, total cholesterol and HDL-cholesterol were not significantly affected. The lactic acid bacteria load increased significantly (P E. coli and salmonella counts decreased significantly (P < 0.05) with infusion compared to the control without additive. In conclusion, 6 ml of Cupressus sempervirens infusion can be used as an alternative to antibiotic feed additives to promote growth performance in broilers.

Determination of uncertainties of geomechanical parameters of metamorphic rocks using petrographic analyses

Geomechanical parameters of intact metamorphic rocks determined from laboratory testing remain highly uncertain because of the great intrinsic variability associated with the degrees of metamorphism.The aim of this paper is to develop a proper methodology to analyze the uncertainties of geomechanical characteristics by focusing on three domains,i.e.data treatment process,schistosity angle,and mineralogy.First,the variabilities of the geomechanical laboratory data of Westwood Mine(Quebec,Canada)were examined statistically by applying different data treatment techniques,through which the most suitable outlier methods were selected for each parameter using multiple decision-making criteria and engineering judgment.Results indicated that some methods exhibited better performance in identifying the possible outliers,although several others were unsuccessful because of their limitation in large sample size.The well-known boxplot method might not be the best outlier method for most geomechanical parameters because its calculated confidence range was not acceptable according to engineering judgment.However,several approaches,including adjusted boxplot,2MADe,and 2SD,worked very well in the detection of true outliers.Also,the statistical tests indicate that the best-fitting probability distribution function for geomechanical intact parameters might not be the normal distribution,unlike what is assumed in most geomechanical studies.Moreover,the negative effects of schistosity angle on the uniaxial compressive strength(UCS)variabilities were reduced by excluding the samples within a specific angle range where the UCS data present the highest variation.Finally,a petrographic analysis was conducted to assess the associated uncertainties such that a logical link was found between the dispersion and the variabilities of hard and soft minerals.

Surface Water Quality Profiling Using Physicochemical Parameters in Open Defecation Free and Non-Open Defecation Free Local Government Areas in Benue State, Nigeria

Physicochemical parameters of surface water sources in the study of local government areas (LGAs) were assessed using standard procedures. The mean physicochemical parameters for pH (5.49), NO2 (0.23 mg/L), SO4 (0.77 mg/L), Na (28.72 mg/L), Ca (28.94 mg/L), Mg (17.50 mg/L), Cl (11.65 mg/L), TSS (6.27 mg/L), TDS (104.23 mg/L), BOD (2.83 mg/L) and F (0.87 mg/L) were below WHO standards irrespective of their defecation status. The values for electrical conductivity (EC) (2770.50 µs/cm, turbidity (481.24 NTU), dissolved oxygen (DO) (5.32 mg/L), chemical oxygen demand (COD) (445.50 mg/L), K (125.06 mg/L), PO4 (0.78 mg/L) and Fe (0.57 mg/L) were above the WHO limits for safe water. Higher EC and COD values obtained in the study is evidence of pollution of the water sources by organic matter.

Effects of processing parameters on fabrication defects,microstructure and mechanical properties of additive manufactured Mg–Nd–Zn–Zr alloy by selective laser melting process

Mg–3Nd–0.2Zn–0.4Zr(NZ30K,wt.%)alloy is a new kind of high-performance metallic biomaterial.The combination of the NZ30K Magnesium(Mg)alloy and selective laser melting(SLM)process seems to be an ideal solution to produce porous Mg degradable implants.However,the microstructure evolution and mechanical properties of the SLMed NZ30K Mg alloy were not yet studied systematically.Therefore,the fabrication defects,microstructure,and mechanical properties of the SLMed NZ30K alloy under different processing parameters were investigated.The results show that there are two types of fabrication defects in the SLMed NZ30K alloy,gas pores and unfused defects.With the increase of the laser energy density,the porosity sharply decreases to the minimum first and then slightly increases.The minimum porosity is 0.49±0.18%.While the microstructure varies from the large grains with lamellar structure inside under low laser energy density,to the large grains with lamellar structure inside&the equiaxed grains&the columnar grains under middle laser energy density,and further to the fine equiaxed grains&the columnar grains under high laser energy density.The lamellar structure in the large grain is a newly observed microstructure for the NZ30K Mg alloy.Higher laser energy density leads to finer grains,which enhance all the yield strength(YS),ultimate tensile strength(UTS)and elongation,and the best comprehensive mechanical properties obtained are YS of 266±2.1 MPa,UTS of 296±5.2 MPa,with an elongation of 4.9±0.68%.The SLMed NZ30K Mg alloy with a bimodal-grained structure consisting of fine equiaxed grains and coarser columnar grains has better elongation and a yield drop phenomenon.

Changes of the peripapillary vascular parameters inpremature infants without retinopathy of prematurityusing U-net segmentation

AIM:To quantitatively assess the changes in mean vascular tortuosity(mVT)and mean vascular width(mVW)around the optic disc and their correlation with gestational age(GA)and birth weight(BW)in premature infants without retinopathy of prematurity(ROP).METHODS:A single-center retrospective study included a total of 133(133 eyes)premature infants[mean corrected gestational age(CGA)43.6wk]without ROP as the premature group and 130(130 eyes)CGA-matched fullterm infants as the control group.The peripapillary mVT and mVW were quantitatively measured using computerassisted techniques.RESULTS:Premature infants had significantly higher mVT(P=0.0032)and lower mVW(P=0.0086)by 2.68(10^(4) cm^(-3))and 1.85μm,respectively.Subgroup analysis with GA showed significant differences(P=0.0244)in mVT between the early preterm and middle to late preterm groups,but the differences between mVW were not significant(P=0.6652).The results of the multiple linear regression model showed a significant negative correlation between GA and BW with mVT after adjusting sex and CGA(P=0.0211 and P=0.0006,respectively).For each day increase in GA at birth,mVT decreased by 0.1281(10^(4) cm^(-3))and for each 1 g increase in BW,mVT decreased by 0.006(10^(4) cm^(-3)).However,GA(P=0.9402)and BW(P=0.7275)were not significantly correlated with mVW.CONCLUSION:Preterm birth significantly affects the peripapillary vascular parameters that indicate higher mVT and narrower mVW in premature infants without ROP.Alterations in these parameters may provide new insights into the pathogenesis of ocular vascular disease.