Robustness Study and Superior Method Development and Validation for Analytical Assay Method of Atropine Sulfate in Pharmaceutical Ophthalmic Solution

Background: The robustness is a measurement of an analytical chemical method and its ability to contain unaffected by little with deliberate variation of analytical chemical method parameters. The analytical chemical method variation parameters are based on pH variability of buffer solution of mobile phase, organic ratio composition changes, stationary phase (column) manufacture, brand name and lot number variation;flow rate variation and temperature variation of chromatographic system. The analytical chemical method for assay of Atropine Sulfate conducted for robustness evaluation. The typical variation considered for mobile phase organic ratio change, change of pH, change of temperature, change of flow rate, change of column etc. Purpose: The aim of this study is to develop a cost effective, short run time and robust analytical chemical method for the assay quantification of Atropine in Pharmaceutical Ophthalmic Solution. This will help to make analytical decisions quickly for research and development scientists as well as will help with quality control product release for patient consumption. This analytical method will help to meet the market demand through quick quality control test of Atropine Ophthalmic Solution and it is very easy for maintaining (GDP) good documentation practices within the shortest period of time. Method: HPLC method has been selected for developing superior method to Compendial method. Both the compendial HPLC method and developed HPLC method was run into the same HPLC system to prove the superiority of developed method. Sensitivity, precision, reproducibility, accuracy parameters were considered for superiority of method. Mobile phase ratio change, pH of buffer solution, change of stationary phase temperature, change of flow rate and change of column were taken into consideration for robustness study of the developed method. Results: The limit of quantitation (LOQ) of developed method was much low than the compendial method. The % RSD for the six sample assay of developed method was 0.4% where the % RSD of the compendial method was 1.2%. The reproducibility between two analysts was 100.4% for developed method on the contrary the compendial method was 98.4%.

A robust triaxial localization method of AE source using refraction path

Acoustic emission(AE)localization algorithms based on homogeneous media or single-velocity are less accurate when applied to the triaxial localization experiments.To the end,a robust triaxial localization method of AE source using refraction path is proposed.Firstly,the control equation of the refraction path is established according to the sensor coordinates and arrival times.Secondly,considering the influence of time-difference-of-arrival(TDOA)errors,the residual of the governing equation is calculated to estimate the equation weight.Thirdly,the refraction points in different directions are solved using Snell’s law and orthogonal constraints.Finally,the source coordinates are iteratively solved by weighted correction terms.The feasibility and accuracy of the proposed method are verified by pencil-lead breaking experiments.The simulation results show that the new method is almost unaffected by the refraction ratio,and always holds more stable and accurate positioning performance than the traditional method under different ratios and scales of TDOA outliers.

Research on Regulation Method of Energy Storage System Based on Multi-Stage Robust Optimization

To address the scheduling problem involving energy storage systems and uncertain energy,we propose a method based on multi-stage robust optimization.This approach aims to regulate the energy storage system by using a multi-stage robust optimal control method,which helps overcome the limitations of traditional methods in terms of time scale.The goal is to effectively utilize the energy storage power station system to address issues caused by unpredictable variations in environmental energy and fluctuating load throughout the day.To achieve this,a mathematical model is constructed to represent uncertain energy sources such as photovoltaic and wind power.The generalized Benders Decomposition method is then employed to solve the multi-stage objective optimization problem.By decomposing the problem into a series of sub-objectives,the system scale is effectively reduced,and the algorithm’s convergence ability is improved.Compared with other algorithms,the multi-stage robust optimization model has better economy and convergence ability and can be used to guide the power dispatching of uncertain energy and energy storage systems.

One-step spraying method to construct superhydrophobic magnesium surface with extraordinary robustness and multi-functions

The robust magnesium surfaces with multi-functions are highly desirable,and the simple and scalable methods to construct such surfaces are urgently indispensable.Herein,we conducted a one-step spraying method to facilely fabricate the robust coating with multi-functions on magnesium alloys.The as-sprayed magnesium alloys surface is superhydrophobic with a static water contact angle(WCA)of 157.0°and a roll-off angle of 6.0°.Such surface has excellent mechanical,chemical and thermal stabilities,even undergoing various physical and chemical damages,including sand impact(10 gmin^(-1),≥20 min),water impact(2 impacts s^(-1),≥180 min),abrasion(1.00 kPa,≥25 cycles),peeling(≥2.15 kPa),high temperature(200°C,≥24 h),strong acidic/salty/basic media(p H=113)and organic-solvent immersion(ethanol and n-hexane,≥24 h),demonstrating brilliant robustness.Notably,the surface displays multi-functions of corrosion protection,anti-fouling and heat insulation,which will undoubtedly promote the much wider applications of magnesium alloys.

A New Method to Solve Robust Data Reconciliation in Nonlinear Process

Data reconciliation is an effective technique for providing accurate and consistent value for chemical process. However, the presence of gross errors can severely bias the reconciled results. Robust estimators can significantly reduce the effect of gross errors and yield less-biased results. In this article, a new method is proposed to solve the robust data reconciliation problem of nonlinear chemical process. By using several technologies including linearization method, penalty function, virtual observation equation, and equivalent weights method, the robust data reconciliation problem can be transformed into least squares estimator problem which leads to the convenience in computation. Simulation results in a nonlinear chemical process demonstrate the efficiency of the proposed method.

Robust design of natural laminar flow supercritical airfoil by multi-objective evolution method

Abstract A transonic, high Reynolds number natural laminar flow airfoil is designed and studied. The γ-θ transition model is combined with the shear stress transport （SST） k-w turbulence model to predict the transition region for a laminar-turbulent boundary layer. The non-uniform free-form deformation （NFFD） method based on the non-uniform rational B-spline （NURBS） basis function is introduced to the airfoil parameterization. The non-dominated sorting genetic algorithm-II （NSGA-II） is used as the search algo- rithm, and the surrogate model based on the Kriging models is introduced to improve the efficiency of the optimization system. The optimization system is set up based on the above technologies, and the robust design about the uncertainty of the Mach number is carried out for NASA0412 airfoil. The optimized airfoil is analyzed and compared with the original airfoil. The results show that natural laminar flow can be achieved on a supercritical airfoil to improve the aerodynamic characteristic of airfoils.

ROBUSTNESS OF THE SUBSPACE METHOD FOR BLIND SIGNATURE WAVEFORM ESTIMATION WITH RESPECT TO CHANNEL ORDER IN ASYNCHRONOUS DS-CDMA SYSTEMS

The robustness of the subspace method for blind signature waveform estimation with respect to channel order is analyzed in asynchronous DS-CDMA systems theoretically. Theoretical analysis and simulation results show that the overestimating of the channel order will lead to the degradation of the quality of the estimated signature waveform. So we should adopt the channel order as small as possible.

Robust airfoil optimization based on improved particle swarm optimization method

A robust airfoil optimization platform is constructed based on the modified particle swarm optimization method （i.e., the second-order oscillating particle swarm method）, which consists of an efficient optimization algorithm, a precise aerodynamic analysis program, a high accuracy surrogate model, and a classical airfoil parametric method. There are two improvements for the modified particle swarm method compared with the standard particle swarm method. First, the particle velocity is represented by the combination of the particle position and the variation of position, which makes the particle swarm algorithm a second-order precision method with respect to the particle po- sition. Second, for the sake of adding diversity to the swarm and enlarging the parameter searching domain to improve the global convergence performance of the algorithm, an oscillating term is introduced to the update formula of the particle velocity. At last, tak- ing two airfoils as examples, the aerodynamic shapes are optimized on this optimization platform. It is shown from the optimization results that the aerodynamic characteristic of the airfoils is greatly improved in a broad design range.

The Method for Optimum Design of Water Rocket Flight Stability Performance Conditions Using CAE with T Method and Robust Parameter Design

A water rocket is a rocket system that obtains thrust by injecting water with compressed air of up to about 8 atmospheres. It is usually manufactured using a pressure-resistant PET bottle. The mechanical elements and principles contained in the water rocket have much in common with the actual small rocket system, and are suitable as educational and research teaching materials in the field of mechanics. Especially in the field of disaster prevention and mitigation, the use of water rockets is being researched and developed as a rescue tool in the event of a flood or earthquake as a disaster countermeasure. However, since the water rocket is a flying object based on the mechanical principle, it is important to ensure the accuracy and stability of the flight path. In this paper, a mechanical simulator is developed with a numerical calculation program based on the mechanical consideration of water rocket flight performance. In addition, the correlation between the flight distance obtained in the simulation and the estimated flight distance is analyzed by applying a multivariate analysis method and verifying the validity of the flight distance calculated from the result. Based on the verification results, we will apply a statistical optimization method to approach the optimization of flight stability performance conditions for water rockets.

Research on robust control strategy of single DOF supporting system of MLDSB based on H∞ mixed-sensitivity Method

Because of hydraulic-electromagnetic double supporting forms,the supporting capacity and stiffness of magnetic-liquid double suspension bearing(MLDSB)can be improved sharply and then it is more suitable for medium speed,heavy load and frequent-starting occasions.Due to the multiple uncertainty,such as the coupling,the unmodeled dynamics,the parameter perturbation and the external disturbance perturbation,the robust stability and stiffness of control system of MLDSB are hard to meet the design requirements.Firstly,the structural features and the regulation mechanisms of MLDSB are presented and the radial 4-DOF kinetic equations are established.Secondly,the influence factors of the control system's coupling on unbalanced vibration caused by the deviation of the rotor center of mass are revealed,and then the weighting function of suppressing the unbalanced vibration can be obtained.Finally,H∞ controller of MLDSB is designed with H∞ mixed-sensitivity method,and the control performances of H∞ controller is compared with the state feedback controller.The simulation results show that single degree of freedom(DOF)supporting system of MLDSB with H∞ controller has good robust stability,stiffness and the ability to suppress unbalanced external disturbances.This study can provide the theoretical reference for stabilized suspension and control of MLDSB.

A robust method for performance evaluation of the vapor cell for magnetometry

A robust performance evaluation method for vapor cells used in magnetometers is proposed in this work.The performance of the vapor cell determines the sensitivity of the magnetic measurement,which is the core parameter of a magnetometer.After establishing the relationship between intrinsic sensitivity and the total relaxation rate,the total relaxation rate of the vapor cell can be obtained to represent the intrinsic sensitivity of the magnetometer by fitting the parameters of the magnetic resonance experiments.The method for measurement of the total relaxation rate based on the magnetic resonance experiment proposed in this work is robust and insensitive to ambient noise.Experiments show that,compared with conventional sensitivity measurement,the total relaxation rate affected by magnetic noise below 0.9 n T,pump light frequency noise below 1.5 GHz,pump light power noise below 9%,probe light power noise below 3%and temperature fluctuation of 150±3℃deviates by less than 2%from the noise-free situation.This robust performance evaluation method for vapor cells is conducive to the construction of a multi-channel high-spatial-resolution cardio-encephalography system.

Investigation and Optimization of Sn/Gr Lubricants Effects on Cold Extrudability of Fe-TiC Nanocomposite Using Taguchi Robust Design Method

The present study deals with the effects of both tin (Sn) and graphite (Gr) powders on the cold extrudability of Fe-TiC nanocomposites as lubricant. The production process includes low-energy ball milling, powder metallurgy and cold direct Extrusion. Due to various factors influencing the extrudability of the Fe-TiC nanocomposites, such as milling time, rate of extrusion, type and content of lubricant and etc, Taguchi robust design method of system optimization was used to determine the approximate contribution percent (% &#961) of each factor. In order to investigation of Fe-TiC properties, samples with best quality of extrusion were analyzed by XRD and SEM investigations. The results indicate that, sitting the atomic layers of Sn lubricant between Fe and TiC particles leads to decreasing the friction. In this case sliding the particles on each other is easier and a part of the load is applied on lubricant. The results of extrusion of samples indicate that using 2% Sn admixed and die wall graphite lubrication can improve cold extrudability of Fe-TiC nanocomposites.

Robust Variance Components Estimation in the PERG Mixed Distributions of Empirical Variances—PEROBVC Method

A mixed distribution of empirical variances, composed of two distributions the basic and contaminating ones, and referred to as PERG mixed distribution of empirical variances, is considered. In the paper a robust inverse problem solution is given, namely a (new) robust method for estimation of variances of both distributions—PEROBVC Method, as well as the estimates for the numbers of observations for both distributions and, in this way also the estimate of contamination degree.

A Robust Design Method in Product Quality Applications

In order to express information on the quality grade of product designed, thetarget value of product quality design was described with a fuzzy number in this paper. Analternative to Taguchi's, the robustness application design method has been recently presented.However, neither Taguchi's method nor the alternative method is capable of dealing satisfactorilywith the frequently encountered situations in which all the noise variables cannot be studiedsimultaneously. Based on the ideas from response surface modeling, linear models theory, and randomeffects models, we provide a method for estimation in the robustness application design method inproduct quality applications. With this new method used, the high-quality ratio of the productdesigned could be increased, and the ability to resist the influence of various disturbing factorsand noise factors could be enhanced.

Upper and Lower Bounds of the α-Universal Triple I Method for Unified Interval Implications

Theα-universal triple I(α-UTI)method is a recognized scheme in the field of fuzzy reasoning,whichwas proposed by our research group previously.The robustness of fuzzy reasoning determines the quality of reasoning algorithms to a large extent,which is quantified by calculating the disparity between the output of fuzzy reasoning with interference and the output without interference.Therefore,in this study,the interval robustness(embodied as the interval stability)of theα-UTI method is explored in the interval-valued fuzzy environment.To begin with,the stability of theα-UTI method is explored for the case of an individual rule,and the upper and lower bounds of its results are estimated,using four kinds of unified interval implications(including the R-interval implication,the S-interval implication,the QL-interval implication and the interval t-norm implication).Through analysis,it is found that theα-UTI method exhibits good interval stability for an individual rule.Moreover,the stability of theα-UTI method is revealed in the case of multiple rules,and the upper and lower bounds of its outcomes are estimated.The results show that theα-UTI method is stable for multiple rules when four kinds of unified interval implications are used,respectively.Lastly,theα-UTI reasoning chain method is presented,which contains a chain structure with multiple layers.The corresponding solutions and their interval perturbations are investigated.It is found that theα-UTI reasoning chain method is stable in the case of chain reasoning.Two application examples in affective computing are given to verify the stability of theα-UTImethod.In summary,through theoretical proof and example verification,it is found that theα-UTImethod has good interval robustness with four kinds of unified interval implications aiming at the situations of an individual rule,multi-rule and reasoning chain.

Robust Estimation of the Normal-Distribution Parameters by Use of Structural Partitioning-Perobls D Method

Quite many authors have dealt with the estimation of the parameters of normal distribution on the basis of non-homogeneous sets: Hald A. 1949 [1], Arango-Castillo L. and Takahara G. 2018 [2]. All the robust methods are based on the assumption that the results affected by gross errors can be found to the left and/or to the right of censoring, or truncated, points. However, as a rule, the (intrinsic) distribution of observations is complex (mixed) consisting of two or more distributions. Then the existing methods, such as ML, Huber’s, etc., yield enlarged estimates for the normal-distribution variance. By studying better estimates the present author has invented new method, called PEROBLS D, based on the Tukeyan mixed-distribution model in which both the contamination rate (percentage) and the parameters of both distributions, forming the mixed one, are estimated, and for the parameters of the basic normal distribution better estimates are obtained than by the existing methods.

A Study of EM Algorithm as an Imputation Method: A Model-Based Simulation Study with Application to a Synthetic Compositional Data

Compositional data, such as relative information, is a crucial aspect of machine learning and other related fields. It is typically recorded as closed data or sums to a constant, like 100%. The statistical linear model is the most used technique for identifying hidden relationships between underlying random variables of interest. However, data quality is a significant challenge in machine learning, especially when missing data is present. The linear regression model is a commonly used statistical modeling technique used in various applications to find relationships between variables of interest. When estimating linear regression parameters which are useful for things like future prediction and partial effects analysis of independent variables, maximum likelihood estimation (MLE) is the method of choice. However, many datasets contain missing observations, which can lead to costly and time-consuming data recovery. To address this issue, the expectation-maximization (EM) algorithm has been suggested as a solution for situations including missing data. The EM algorithm repeatedly finds the best estimates of parameters in statistical models that depend on variables or data that have not been observed. This is called maximum likelihood or maximum a posteriori (MAP). Using the present estimate as input, the expectation (E) step constructs a log-likelihood function. Finding the parameters that maximize the anticipated log-likelihood, as determined in the E step, is the job of the maximization (M) phase. This study looked at how well the EM algorithm worked on a made-up compositional dataset with missing observations. It used both the robust least square version and ordinary least square regression techniques. The efficacy of the EM algorithm was compared with two alternative imputation techniques, k-Nearest Neighbor (k-NN) and mean imputation (), in terms of Aitchison distances and covariance.

实验室间比对试验结果的评价——Robust法

概述了Robust评价法的特点,总结了该法的评价步骤,并通过举例进一步介绍了该法在评价实验室间比对试验结果的具体应用。

基于Robust的AMT阻抗张量估计算法参数影响研究

针对云南省澜沧多金属矿区AMT实测数据开展Robust阻抗估算的参数影响研究,挑选两个实测点数据进行相干因子估算和电阻率离差估算,得到其视电阻率和相位曲线图,分别对其进行讨论。经过Robust阻抗估算法处理过后的数据可以明显看出,只进行相干因子估算处理后数据其视电阻率高频段部分有明显的缓和,走势更平滑,在相位低频段部分跳点减少,数据得到改善;而当数据低频段跳点较多时只进行电阻率离差估算处理的效果更好,其相位曲线圆滑程度改善,中低频段数据离差小,数据稳定,飞点减少。研究结果表明,Robust阻抗估算法可以有效抑制非高斯噪声的AMT实测数据,平滑曲线,使高频段更接近实际地质情况。