New scale factor correction scheme for CORDIC algorithm

To overcome the drawbacks such as irregular circuit construction and low system throughput that exist in conventional methods, a new factor correction scheme for coordinate rotation digital computer（ CORDIC） algorithm is proposed. Based on the relationship between the iteration formulae, a new iteration formula is introduced, which leads the correction operation to be several simple shifting and adding operations. As one key part, the effects caused by rounding error are analyzed mathematically and it is concluded that the effects can be degraded by an appropriate selection of coefficients in the iteration formula. The model is then set up in Matlab and coded in Verilog HDL language. The proposed algorithm is also synthesized and verified in field-programmable gate array （FPGA）. The results show that this new scheme requires only one additional clock cycle and there is no change in the elementary iteration for the same precision compared with the conventional algorithm. In addition, the circuit realization is regular and the change in system throughput is very minimal.

An Improved DV-Hop Localization Algorithm Based on Hop Distances Correction

DV-Hop localization algorithm has greater localization error which estimates distance from an unknown node to the different anchor nodes by using estimated average size of a hop to achieve the location of the unknown node.So an improved DV-Hop localization algorithm based on correctional average size of a hop,HDCDV-Hop algorithm,is proposed.The improved algorithm corrects the estimated distance between the unknown node and different anchor nodes based on fractional hop count information and relatively accurate coordinates of the anchor nodes information,and it uses the improved Differential Evolution algorithm to get the estimate location of unknown nodes so as to further reduce the localization error.Simulation results show that our proposed algorithm have lower localization error and higher localization accuracy compared with the original DV-Hop algorithm and other classical improved algorithms.

Real-time model correction using Kalman filter for Raman-controlled cell culture processes

Raman spectroscopy has found extensive use in monitoring and controlling cell culture processes.In this context,the prediction accuracy of Raman-based models is of paramount importance.However,models established with data from manually fed-batch cultures often exhibit poor performance in Raman-controlled cultures.Thus,there is a need for effective methods to rectify these models.The objective of this paper is to investigate the efficacy of Kalman filter(KF)algorithm in correcting Raman-based models during cell culture.Initially,partial least squares(PLS)models for different components were constructed using data from manually fed-batch cultures,and the predictive performance of these models was compared.Subsequently,various correction methods including the PLS-KF-KF method proposed in this study were employed to refine the PLS models.Finally,a case study involving the auto-control of glucose concentration demonstrated the application of optimal model correction method.The results indicated that the original PLS models exhibited differential performance between manually fed-batch cultures and Raman-controlled cultures.For glucose,the root mean square error of prediction(RMSEP)of manually fed-batch culture and Raman-controlled culture was 0.23 and 0.40 g·L^(-1).With the implementation of model correction methods,there was a significant improvement in model performance within Raman-controlled cultures.The RMSEP for glucose from updating-PLS,KF-PLS,and PLS-KF-KF was 0.38,0.36 and 0.17 g·L^(-1),respectively.Notably,the proposed PLS-KF-KF model correction method was found to be more effective and stable,playing a vital role in the automated nutrient feeding of cell cultures.

OPTIMIZED STRAPDOWN CONING CORRECTION ALGORITHM

Traditional coning algorithms are based on the first-order coning correction reference model.Usually they reduce the algorithm error of coning axis(z)by increasing the sample numbers in one iteration interval.But the increase of sample numbers requires the faster output rates of sensors.Therefore,the algorithms are often limited in practical use.Moreover,the noncommutivity error of rotation usually exists on all three axes and the increase of sample numbers has little positive effect on reducing the algorithm errors of orthogonal axes(x,y).Considering the errors of orthogonal axes cannot be neglected in the high-precision applications,a coning algorithm with an additional second-order coning correction term is developed to further improve the performance of coning algorithm.Compared with the traditional algorithms,the new second-order coning algorithm can effectively reduce the algorithm error without increasing the sample numbers.Theoretical analyses validate that in a coning environment with low frequency,the new algorithm has the better performance than the traditional time-series and frequency-series coning algorithms,while in a maneuver environment the new algorithm has the same order accuracy as the traditional time-series and frequency-series algorithms.Finally,the practical feasibility of the new coning algorithm is demonstrated by digital simulations and practical turntable tests.

Comparison of QT Correction Methods in the Pediatric Population of a Community Hospital: A Retrospective Study

Objective:Accurate measurement of QT interval,the ventricular action potential from depolarization to repolarization,is important for the early detection of Long QT syndrome.The most effective QT correction(QTc)formula has yet to be determined in the pediatric population,although it has intrinsically greater extremes in heart rate(HR)and is more susceptible to errors in measurement.The authors of this study compare six dif-ferent QTc methods(Bazett,Fridericia,Framingham,Hodges,Rautaharju,and a computer algorithm utilizing the Bazett formula)for consistency against variations in HR and RR interval.Methods:Descriptive Retrospective Study.We included participants from a pediatric cardiology practice of a community hospital who had an ECG performed in 2017.All participants were healthy patients with no past medical history and no regular med-ications.Results:ECGs from 95 participants from one month to 21 years of age(mean 9.7 years)were included with a mean HR of 91 beats per minute(bpm).The two-sample paired t-test or Wilcoxon signed-rank test assessed for any difference between QTc methods.A statistically significant difference was observed between every combination of two QTc formulae.The Spearman’s rank correlation analysis explored the QTc/HR and QTc/RR relationships for each formula.Fridericia method was most independent of HR and RR with the lowest absolute value of correlation coefficients.Bazett and Computer had moderate correlations,while Framingham and Rautaharju exhibited strong correlations.Correlations were positive for Bazett and Computer,reflecting results from prior studies demonstrating an over-correction of Bazett at higher HRs.In the linear QTc/HR regression analysis,Bazett had the slope closest to zero,although Computer,Hodges,and Fridericia had comparable values.Alternatively,Fridericia had the linear QTc/RR regression coefficient closest to zero.The Bland-Altman method assessed for bias and the limits of agreement between correction formulae.Bazett and Computer exhibited good agreement with minimal bias along with Framingham and Rautaharju.To account for a possible skewed distri-bution of QT,all the above analyses were also performed excluding the top and bottom 2%of data as sorted by heart rate ranges(N=90).Results from this data set were consistent with those derived from all participants(N=95).Conclusions:Overall,the Fridericia correction method provided the best rate correction in our pedia-tric study cohort.

Dispersed Wind Power Planning Method Considering Network Loss Correction with Cold Weather

In order to play a positive role of decentralised wind power on-grid for voltage stability improvement and loss reduction of distribution network,a multi-objective two-stage decentralised wind power planning method is proposed in the paper,which takes into account the network loss correction for the extreme cold region.Firstly,an electro-thermal model is introduced to reflect the effect of temperature on conductor resistance and to correct the results of active network loss calculation;secondly,a two-stage multi-objective two-stage decentralised wind power siting and capacity allocation and reactive voltage optimisation control model is constructed to take account of the network loss correction,and the multi-objective multi-planning model is established in the first stage to consider the whole-life cycle investment cost of WTGs,the system operating cost and the voltage quality of power supply,and the multi-objective planning model is established in the second stage.planning model,and the second stage further develops the reactive voltage control strategy of WTGs on this basis,and obtains the distribution network loss reduction method based on WTG siting and capacity allocation and reactive power control strategy.Finally,the optimal configuration scheme is solved by the manta ray foraging optimisation(MRFO)algorithm,and the loss of each branch line and bus loss of the distribution network before and after the adoption of this loss reduction method is calculated by taking the IEEE33 distribution system as an example,which verifies the practicability and validity of the proposed method,and provides a reference introduction for decision-making for the distributed energy planning of the distribution network.

Evaluation of Correction Algorithm for the Reflectance Measured with Optical Glass

The proposed algorithm for reflectance measured with optical glass has been verified with materials of various forms. The reflectances measured with optical glass ( raw), without glass (true) and corrected by the algorithm are compared. The results show that the corrected reflectance agrees very well with true one and their color differences fall below the acceptable limit, which indicates the validity of the correction algorithm. The algorithm could be used not only for fiber-forming materials, but also for powder-forming, granulate-forming, etc.

PARALLEL ALGORITHMS OF ONE-LEG METHOD AND ITERATED DEFECT CORRECTION METHODS

The parallel algorithms of iterated defect correction methods (PIDeCM’s) are constructed, which are of efficiency and high order B-convergence for general nonlinear stiff systems in ODE’S. As the basis of constructing and discussing PIDeCM’s. a class of parallel one-leg methods is also investigated, which are of particular efficiency for linear systems.

Coordinate correction algorithm for WLAN indoor positioning

In the fingerprint matching-based wireless local area network(WLAN) indoor positioning system,Kalman filter(KF) is usually applied after fingerprint matching algorithms to make positioning results more accurate and consecutive.But this method,like most methods in WLAN indoor positioning field,fails to consider and make use of users' moving speed information.In order to make the positioning results more accurate through using the users' moving speed information,a coordinate correction algorithm(CCA) is proposed in this paper.It predicts a reasonable range for positioning coordinates by using the moving speed information.If the real positioning coordinates are not in the predicted range,it means that the positioning coordinates are not reasonable to a moving user in indoor environment,so the proposed CCA is used to correct this kind of positioning coordinates.The simulation results prove that the positioning results by the CCA are more accurate than those calculated by the KF and the CCA is effective to improve the positioning performance.

Evaluation of Atmospheric Correction Algorithms for Landsat-8 OLI and MODIS-Aqua to Study Sediment Dynamics in the Northern Gulf of Mexico

Suspended particulate matter (SPM) is regarded as an energy source and a water quality indicator in coastal and marine ecosystems. To estimate SPM from ocean color sensors and land observing satellites, an accurate and robust atmospheric correction must be done. We evaluated the capabilities of ocean color and land observing satellite for estimation of SPM concentrations over Louisiana continental shelf in the northern Gulf of Mexico, using the Operational Land Imager (OLI) on Landsat-8, and Moderate Resolution Imaging Spectroradiometer (MODIS) on Aqua. In high turbidity waters, the traditional atmospheric correction algorithms based on near-infrared (NIR) bands underestimate SPM concentrations due to the inaccurate removal of the aerosol contribution to the top of atmosphere signals. Therefore, atmospheric correction in high turbidity waters is a challenge. Four atmospheric correction algorithms were implemented on remote sensing reflectance (Rrs) values to select suitable atmospheric correction algorithms for each sensor in our study area. We evaluated short-wave infrared (SWIR) and NIR atmospheric correction algorithms on Rrs products from Landsat-8 OLI and Management Unit of the North Sea Mathematical Models (MUMM) and SWIR.NIR atmospheric correction algorithms on Rrs products from MODIS-Aqua. SPM was retrieved from a band-ratio SPM-retrieval algorithm for each sensor. Our results indicated that SWIR atmospheric correction algorithm was the suitable algorithm for Landsat-8 OLI and SWIR.NIR atmospheric correction algorithm outperformed MUMM algorithm for MODIS.

AN EXPANSION AND CORRECTION ALGORITHM FOR PHOTOELECTRIC IMAGE WITH GEOMETRIC DISTORTION^1

A creepy photoelectric endoscopy system with good performance is studied, and anexpansion and correction algorithm for a compressed photoelectric image with serious geometricdistortion is presented. The algorithm can not only correct the geometric distortion, but alsorestore the gray-level distribution by means of ternary convolution algorithm. The details andthe outline in the image are very clear. It is proved to be of high performance in practice.

Low/distortion on Exterior Surface of Auto Body and Its Correction Method

Surface low/distortion is one of the most challenging surface deflections that have a great effect on the exterior appearance of automobiles.Most studies on surface distortion/deflection have focused on evaluation and visualization techniques,the research work on correction or prevention of surface low/distortion is limited,and there is no perfect surface low/distortion corrective method that can satisfy the needs of the engineering.A B-spline based geometry morphing algorithm is proposed and then a new program based on UG-NX platform is developed to modify the die face in the surface low/distortion areas.To verify this developed system,the experimental dies that can replicate the surface low/distortion phenomenon successfully is put to use.Five geometric variables are introduced to describe the basic geometry of typical depression features of automotive outer panels.The experimental dies are then designed to reflect various combinations of these geometric parameters.The stamping experiments are conducted on cold rolled grade 5（CR5） sheet steel and various static measurements,such as oil-stoning,laser scanner,etc,are performed to measure and record the surface low/distortions.Three approaches including good bearing,holds in blank and die face morphing that aim to correct low/distortions are tried out and surface low/distortions are observed in the specimen with reverse draw depth of 10 mm.The measurement results show that die morphing is a practical and effective method to correct the surface low/distortion.The correction method proposed can be used to minimize the occurrence of surface low/distortion in die manufacturing,which has certain reference significance to the correction of surface low/distortion.

Tooth surface error correction of hypoid gears machined by duplex helical method

In this work,synchronous cutting of concave and convex surfaces was achieved using the duplex helical method for the hypoid gear,and the problem of tooth surface error correction was studied.First,the mathematical model of the hypoid gears machined by the duplex helical method was established.Second,the coordinates of discrete points on the tooth surface were obtained by measurement center,and the normal errors of the discrete points were calculated.Third,a tooth surface error correction model is established,and the tooth surface error was corrected using the Levenberg-Marquard algorithm with trust region strategy and least square method.Finally,grinding experiments were carried out on the machining parameters obtained by Levenberg-Marquard algorithm with trust region strategy,which had a better effect on tooth surface error correction than the least square method.After the tooth surface error is corrected,the maximum absolute error is reduced from 30.9μm before correction to 6.8μm,the root mean square of the concave error is reduced from 15.1 to 2.1μm,the root mean square of the convex error is reduced from 10.8 to 1.8μm,and the sum of squared errors of the concave and convex surfaces was reduced from 15471 to 358μm^(2).It is verified that the Levenberg-Marquard algorithm with trust region strategy has a good accuracy for the tooth surface error correction of hypoid gear machined by duplex helical method.

Multi-objectives nonlinear structure optimization for actuator in trajectory correction fuze subject to high impact loadings

This paper presents an actuator used for the trajectory correction fuze,which is subject to high impact loadings during launch.A simulation method is carried out to obtain the peak-peak stress value of each component,from which the ball bearings are possible failures according to the results.Subsequently,three schemes against impact loadings,full-element deep groove ball bearing and integrated raceway,needle roller thrust bearing assembly,and gaskets are utilized for redesigning the actuator to effectively reduce the bearings’stress.However,multi-objectives optimization still needs to be conducted for the gaskets to decrease the stress value further to the yield stress.Four gasket’s structure parameters and three bearings’peak-peak stress are served as the four optimization variables and three objectives,respectively.Optimized Latin hypercube design is used for generating sample points,and Kriging model selected according to estimation result can establish the relationship between the variables and objectives,representing the simulation which is time-consuming.Accordingly,two optimization algorithms work out the Pareto solutions,from which the best solutions are selected,and verified by the simulation to determine the gaskets optimized structure parameters.It can be concluded that the simulation and optimization method based on these components is effective and efficient.

Nonlinear Correction of Pressure Sensor Based on Depth Neural Network

With the global climate change,the high-altitude detection is more and more important in the climate prediction,and the input-output characteristic curve of the air pressure sensor is offset due to the interference of the tested object and the environment under test,and the nonlinear error is generated.Aiming at the difficulty of nonlinear correction of pressure sensor and the low accuracy of correction results,depth neural network model was established based on wavelet function,and Levenberg-Marquardt algorithm is used to update network parameters to realize the nonlinear correction of pressure sensor.The experimental results show that compared with the traditional neural network model,the improved depth neural network not only accelerates the convergence rate,but also improves the correction accuracy,meets the error requirements of upper-air detection,and has a good generalization ability,which can be extended to the nonlinear correction of similar sensors.

Analysis of an improved trajectory correction scheme based on mass blocks

In conventional technical trajectory correction schemes,continuous attitude adjusting mechanisms, such as canards, are inferior in terms of response time and efficiency of executing instructions. Discontinuous attitude adjusting mechanisms, such as the lateral pulse jet, have complex impact on the airflow layer of the projectile surface caused by the thrust vector jet flow. An improved two-dimensional trajectory correction mechanism is designed based on the principle of firing mass blocks by a tailor-made propellant. The mechanical properties of the thrust force(namely the correction force) is analyzed. The trajectory correction model is established to analyze the effects of correction starting moment and correction phase angle of a thrust force on the projectile's trajectory. According to the trajectory correction scheme, an improved genetic algorithm is employed to this work. The scheme is tested in the simulation. The results show that the correction scheme is effective to reduce target dispersion and increase the precision of the impact point.

PPA BASED PREDICTION-CORRECTION METHODS FOR MONOTONE VARIATIONAL INEQUALITIES

In this paper we study the proximal point algorithm (PPA) based predictioncorrection (PC) methods for monotone variational inequalities. Each iteration of these methods consists of a prediction and a correction. The predictors are produced by inexact PPA steps. The new iterates are then updated by a correction using the PPA formula. We present two profit functions which serve two purposes: First we show that the profit functions are tight lower bounds of the improvements obtained in each iteration. Based on this conclusion we obtain the convergence inexactness restrictions for the prediction step. Second we show that the profit functions are quadratically dependent upon the step lengths, thus the optimal step lengths are obtained in the correction step. In the last part of the paper we compare the strengths of different methods based on their inexactness restrictions.

Study on Health Monitoring Systems Based on Correction Mode

Current health monitoring systems often do not concern about the needs of the elderly,leading to inaccurate health status monitoring and delayed treatment for emergency health conditions.Similarly,they do not consider the variable factors affecting each patient,resulting in discrepancies between the measured values and real health status.To solve the problems,we propose a new health monitoring system with physiological parameter measurement,correction,and feedback.The study collects clinical samples of the elderly to formulate regression equations and statistical models for analyzing the relationship between gender,age,measurement time,and physical signs.After multiple adjustments to measurements of physical signs,the correction algorithm compares the data with a standard value.The process significantly reduces the risk of misjudgment while matching users’health status more accurately.The application case of this paper proves the validity of the method for measuring and correcting heart rate results in the elderly and presents a specific correction procedure.Additionally,the correction algorithm provides a scientific basis for eliminating or modifying other influencing factors in future health monitoring studies.

Predictor-corrector interior-point algorithm for linearly constrained convex programming

Active set method and gradient projection method are curre nt ly the main approaches for linearly constrained convex programming. Interior-po int method is one of the most effective choices for linear programming. In the p aper a predictor-corrector interior-point algorithm for linearly constrained c onvex programming under the predictor-corrector motivation was proposed. In eac h iteration, the algorithm first performs a predictor-step to reduce the dualit y gap and then a corrector-step to keep the points close to the central traject ory. Computations in the algorithm only require that the initial iterate be nonn egative while feasibility or strict feasibility is not required. It is proved th at the algorithm is equivalent to a level-1 perturbed composite Newton method. Numerical experiments on twenty-six standard test problems are made. The result s show that the proposed algorithm is stable and robust.