Aircraft Optimal Separation Allocation Based on Global Optimization Algorithm

A dynamic programming-sequential quadratic programming(DP-SQP)combined algorithm is proposed to address the problem that the traditional continuous control method has high computational complexity and is easy to fall into local optimal solution.To solve the globally optimal control law sequence,we use the dynamic programming algorithm to discretize the separation control decision-making process into a series of sub-stages based on the time characteristics of the separation allocation model,and recursion from the end stage to the initial stage.The sequential quadratic programming algorithm is then used to solve the optimal return function and the optimal control law for each sub-stage.Comparative simulations of the combined algorithm and the traditional algorithm are designed to validate the superiority of the combined algorithm.Aircraft-following and cross-conflict simulation examples are created to demonstrate the combined algorithm’s adaptability to various conflict scenarios.The simulation results demonstrate the separation deploy strategy’s effectiveness,efficiency,and adaptability.

Adaptive Particle Swarm Optimization Data Hiding for High Security Secret Image Sharing

The main aim of this work is to improve the security of data hiding forsecret image sharing. The privacy and security of digital information have becomea primary concern nowadays due to the enormous usage of digital technology.The security and the privacy of users’ images are ensured through reversible datahiding techniques. The efficiency of the existing data hiding techniques did notprovide optimum performance with multiple end nodes. These issues are solvedby using Separable Data Hiding and Adaptive Particle Swarm Optimization(SDHAPSO) algorithm to attain optimal performance. Image encryption, dataembedding, data extraction/image recovery are the main phases of the proposedapproach. DFT is generally used to extract the transform coefficient matrix fromthe original image. DFT coefficients are in float format, which assists in transforming the image to integral format using the round function. After obtainingthe encrypted image by data-hider, additional data embedding is formulated intohigh-frequency coefficients. The proposed SDHAPSO is mainly utilized for performance improvement through optimal pixel location selection within the imagefor secret bits concealment. In addition, the secret data embedding capacityenhancement is focused on image visual quality maintenance. Hence, it isobserved from the simulation results that the proposed SDHAPSO techniqueoffers high-level security outcomes with respect to higher PSNR, security level,lesser MSE and higher correlation than existing techniques. Hence, enhancedsensitive information protection is attained, which improves the overall systemperformance.

Novel computer-assisted approach to quick prediction and optimization of gradient separation for online enrichment-reversed phase liquid chromatography tandem system

An algorithm capable of predicting and optimizing the gradient separation of LC×LC system was developed in this paper.Two groups of structural analogues,five ginsenosides as well as eight bisphenols,which were difficult to discriminate in routine analysis,were used to verify the effectiveness of the proposed algorithm in fast separation optimization.Average errors of retention times below 1%were found in the retention prediction for all types of gradient programs,implying that the theory could lead to high quality in prediction of the retention times under gradients elution.Meanwhile,84%of relative average deviations(RADs)between the predicted peak width and the measured ones were less than 20%.The larger deviation occurred at the time when the peak appeared while the gradient of the mobile phase changed,which led the deviations increased to 20%–42%.In all,method development and optimization for LC×LC tandem system was realized by the homemade user-friendly software.The present protocol may turn on great opportunities for the convenient method development in analysis of trace structural analogues in environmental,food and biological samples.

Accuracy analysis of the optimal separable approximation method of one-way wave migration

An approximation for the one-way wave operator takes the form of separated space and wave-number variables and makes it possible to use the FFT, which results in a great improvement in the computational efficiency. From the function approximation perspective, the OSA method shares the same separable approximation format to the one-way wave operator as other separable approximation methods but it is the only global function approximation among these methods. This leads to a difference in the phase error curve, impulse response, and migration result from other separable approximation methods. The difference is that the OSA method has higher accuracy, and the sensitivity to the velocity variation declines with increasing order.

Investigation on a vertical radial flow adsorber designed by a novel parallel connection method

Due to the increasing global demand for industrial gas, the development of large-scale cryogenic air separation systems has attracted considerable attention in recent years. Increasing the height of the adsorption bed in a vertical radial flow adsorber used in cryogenic air separation systems may efficiently increase the treatment capacity of the air in the adsorber. However, uniformity of the flow distribution of the air inside the adsorber would be deteriorated using the height-increasing method. In order to reduce the non-uniformity of the flow distribution caused by the excessive height of adsorption bed in a vertical radial flow adsorber, a novel parallel connection method is proposed in the present work. The experimental apparatus is designed and constructed; the Computational Fluid Dynamics(CFD) technique is used to develop a CFD-based model, which is used to analyze the flow distribution, the static pressure drop and the radial velocity in the newly designed adsorber. In addition, the geometric parameters of annular flow channels and the adsorption bed thickness of the upper unit in the parallelconnected vertical radial flow adsorber are optimized, so that the upper and lower adsorption units could be penetrated by air simultaneously. Comparisons are made between the height-increasing method and the parallel connection method with the same adsorber height. It is shown that using the parallel connection method could reduce the difference between the maximum and minimum radial static pressure drop by 86.2% and improve the uniformity by 80% compared with those of using the height-increasing method. The optimal thickness ratio of the upper and lower adsorption units is obtained as 0.966, in which case the upper and lower adsorption units could be penetrated by air simultaneously, so that the adsorbents in adsorption space could be used more efficiently.

3D wavefield extrapolation with optimal separable approximation

An accurate and wide-angle one-way propagator for wavefield extrapolation is an important topic for research on wave-equation prestack depth migration in the presence of large and rapid velocity variations. Based on the optimal separable approximation presented in this paper, the mixed domain algorithm with forward and inverse Fourier transforms is used to construct the 3D one-way wavefield extrapolation operator. This operator separates variables in the wavenumber and spatial domains. The phase shift operation is implemented in the wavenumber domain while the time delay for lateral velocity variation is corrected in the spatial domain. The impulse responses of the one-way wave operator show that the numeric computation is consistent with the theoretical value for each velocity, revealing that the operator constructed with the optimal separable approximation can be applied to lateral velocity variations for the case of small steps. Imaging results of the SEG/EAGE model and field data indicate that the new method can be used to image complex structure.

The Offset-Domain Prestack Depth Migration with Optimal Separable Approximation

The offset-domain prestack depth migration with optimal separable approximation, based on the double square root equation, is used to image complex media with large and rapid velocity variations. The method downward continues the source and the receiver wavefields simultaneously. The mixed domain algorithm with forward Fourier and inverse Fourier transform is used to construct the double square root equation wavefield extrapolation operator. This operator separates variables in the wave number domain and variables in the space domain. The phase operation is implemented in the wave number domain, whereas the time delay for lateral velocity variation is corrected in the space domain. The migration algorithm is efficient since the seismic data are not computed shot by shot. The data set test of the Marmousi model indicates that the offset-domain migration provides a satisfied seismic migration section on which complex geologic structures are imaged in media with large and rapid lateral velocity variations.

Inertial Proximal ADMM for Separable Multi-Block Convex Optimizations and Compressive Affine Phase Retrieval

Separable multi-block convex optimization problem appears in many mathematical and engineering fields.In the first part of this paper,we propose an inertial proximal ADMM to solve a linearly constrained separable multi-block convex optimization problem,and we show that the proposed inertial proximal ADMM has global convergence under mild assumptions on the regularization matrices.Affine phase retrieval arises in holography,data separation and phaseless sampling,and it is also considered as a nonhomogeneous version of phase retrieval,which has received considerable attention in recent years.Inspired by convex relaxation of vector sparsity and matrix rank in compressive sensing and by phase lifting in phase retrieval,in the second part of this paper,we introduce a compressive affine phase retrieval via lifting approach to connect affine phase retrieval with multi-block convex optimization,and then based on the proposed inertial proximal ADMM for 3-block convex optimization,we propose an algorithm to recover sparse real signals from their(noisy)affine quadratic measurements.Our numerical simulations show that the proposed algorithm has satisfactory performance for affine phase retrieval of sparse real signals.

Optimization of the separation of a mixture of unknown composition by reversed-phase HPLC

A method is presented for the computer-assisted optimization of mobile phase selection for the separation of a synthetic intermediate of unknown composition by reversed- phase HPLC.The method is based on recognition of the order of the peaks by comparison of peak area ratio and followed by the BSOS-L(Binary Solvent Optimization System for HPLC)method.Excellent agreement was obtained between predicted data and experimental results.

A Homotopy Alternating Direction Method of Multipliers for Linearly Constrained Separable Convex Optimization

Linearly constrained separable convex minimization problems have been raised widely in many real-world applications.In this paper,we propose a homotopy-based alternating direction method of multipliers for solving this kind of problems.The proposed method owns some advantages of the classical proximal alternating direction method of multipliers and homotopy method.Under some suitable condi-tions,we prove global convergence and the worst-case O(k/1)convergence rate in a nonergodic sense.Preliminary numerical results indicate effectiveness and efficiency of the proposed method compared with some state-of-the-art methods.

A HOMOTOPY-BASED ALTERNATING DIRECTION METHOD OF MULTIPLIERS FOR STRUCTURED CONVEX OPTIMIZATION

The alternating direction method of multipliers （ADMM for short） is efficient for linearly constrained convex optimization problem. The practicM computationM cost of ADMM depends on the sub-problem solvers. The proximal point algorithm is a common sub-problem-solver. However, the proximal parameter is sensitive in the proximM ADMM. In this paper, we propose a homotopy-based proximal linearized ADMM, in which a homotopy method is used to soNe the sub-problems at each iteration. Under some suitable conditions, the global convergence and the convergence rate of O（1/k） in the worst case of the proposed method are proven. Some preliminary numerical results indicate the validity of the proposed method.

Optimal mode of capillary electrophoresis for the impurity analysis of β-lactam antibiotics

In order to determine the optimal mode of capillary electrophoresis for the impurity control of β-lactam antibiotics, different modes and various electrophoresis conditions for the separation of impurities were compared.The results showed that micellar electrokinetic capillary chromatography（MEKC） was the optimal separation mode for the impurity profiling of β-lactam antibiotics.In MEKC,not only the common R and S isomers,Δ-2 andΔ-3 isomers,and Z and E isomers,but also the impurities of β-lactam antibiotics could be well separated compared with the capillary zone electrophoresis.Therefore,MECK is the first choice for the separation of impurities of β-lactam antibiotics with capillary electrophoresis（CE）.The optimal separation could be achieved in MEKC by optimizing the pH and the concentrations of buffered saline,micelles and organic solvent（methanol） in running buffer.

A Fast Symmetric Alternating Direction Method of Multipliers

In recent years,alternating direction method of multipliers(ADMM)and its variants are popular for the extensive use in image processing and statistical learning.A variant of ADMM:symmetric ADMM,which updates the Lagrange mul-tiplier twice in one iteration,is always faster whenever it converges.In this paper,combined with Nesterov’s accelerating strategy,an accelerated symmetric ADMM is proposed.We prove its O(1/k^(2))convergence rate under strongly convex condition.For the general situation,an accelerated method with a restart rule is proposed.Some preliminary numerical experiments show the efficiency of our algorithms.