Phase-Based Optical Flow Method with Optimized Parameter Settings for Enhancing Displacement Measurement Adaptability

To enhance the applicability and measurement accuracy of phase-based optical flow method using complex steerable pyramids in structural displacement measurement engineering applications, an improved method of optimizing parameter settings is proposed. The optimized parameters include the best measurement points of the Region of Interest (ROI) and the levels of pyramid filters. Additionally, to address the issue of updating reference frames in practical applications due to the difficulty in estimating the maximum effective measurement value, a mechanism for dynamically updating reference frames is introduced. Experimental results demonstrate that compared to representative image gradient-based displacement measurement methods, the proposed method exhibits higher measurement accuracy in engineering applications. This provides reliable data support for structural damage identification research based on vibration signals and is expected to broaden the engineering application prospects for structural health monitoring.

DSAS:A new macromolecular substructure solution program based on the modified phase-retrieval algorithm

Considering the pivotal role of single-wavelength anomalous diffraction(SAD) in macromolecular crystallography,our objective was to introduce DSAS,a novel program designed for efficient anomalous scattering substructure determination.DSAS stands out with its core components:a modified phase-retrieval algorithm and automated parameter tuning.The software boasts an intuitive graphical user interface(GUI),facilitating seamless input of essential data and real-time monitoring.Extensive testing on DSAS has involved diverse datasets,encompassing proteins,nucleic acids,and various anomalous scatters such as sulfur(S),selenium(Se),metals,and halogens.The results confirm DSAS’s exceptional performance in accurately determining heavy atom positions,making it a highly effective tool in the field.

Application of MPSO technique to find optimal location and parameter setting of TCSC

A new mothod was presented to find the optimal location and parameter setting of Thyristor Controlled Series Compensator (TCSC) to maxmize the transfer capability.Firstly the sensitivity of the transfer capability with respect was described to the line's reactance was described to find the more sensitive lines for installing TCSC,however,the line which has the most sesitivity value is always not the best line for installing TCSC.For solving this problem,the more sensitive m lines were selected as the alternative line group of installing TCSC,and then modified particle swarm optimization (MPSO) was used to find out the optimal location and the optimal parameter settings of TCSC.Particle swarm optimization (PSO) algorithm can results premature convergence.For solving this problem,population entropy and cellular automata were introduced to it.Simulation results of IEEE 30-bus system proved the effectiveness of the method and its application values.

An approach to optimize the settings of actuated signals

Traffic-actuated signal employs relatively complex control logic to regulate traffic flow. Introduction of control variables into the traffic-actuated system contributes to system operational flexibility and complexity, and also complicates the system with uncertainties. The paper proposes two tentative methods to optimize the actuated signal parameters： basic requirements of controller parameters and analytical model, and macroscopic computer simulation. It is concluded that when the actuated signal operates within the volume/capacity range of 0.4 to 0.6, it will create the most significant benefits; the research suggests that minimum green time in the main street shall be set long enough to meet the required demand, preferably at the 60% of the main street capacity. In order to ensure less control delay in a semi-actuated intersection, relatively small values of vehicle extension （e.g., 2.5 s） and maximum green time are recommended to be assigned to the less important street.

Dynamic Setting Method of Assessment Indicators for Power Curves of Renewable Energy Sources Considering Scarcity of Reserve Resources

With the increasing proportion of renewable energy sources(RESs)in power grid,the reserve resource(RR)scarcity for correcting power deviation of RESs has become a potential issue.Consequently,the power curve of RES needs to be more rigorously assessed.The RR scarcity varies during different time periods,so the values of assessment indicators should be dynamically adjusted.The assessment indicators in this paper include two aspects,i.e.,deviation exemption ratio and penalty price.Firstly,this paper proposes a method for dynamically calculating the supply capacity and RR cost,primarily taking into account the operating status of thermal units,forecast information of RES,and load curve.Secondly,after clarifying the logical relationship between the degree of RR scarcity and the values of assessment indicators,this paper establishes a mapping function between them.Based on this mapping function,a dynamic setting method for assessment indicators is proposed.In the future,RES will generally be equipped with battery energy storage systems(BESSs).Reasonably utilizing BESSs to reduce the power deviation of RESs can increase the expected income of RESs.Therefore,this paper proposes a power curve optimization strategy for RESs considering self-owned BESSs.The case study demonstrates that the dynamic setting method of assessment indicators can increase the revenue of RESs while ensuring that the penalty fees paid by RESs to the grid are sufficient to cover the RR costs.Additionally,the power curve optimization strategy can help RESs further increase income and fully utilize BESSs to reduce power deviation.

Investigations on Nuclei near Z = 82 in Relativistic Mean Field Theory with FSUGold

In this work, the ground-state properties of Pt, Hg, Pb, and Po isotopes have been systematically investigated in the deformed relativistic mean field （RMF） theory with the new parameter set FSUGold. The calculated results show that FSUGold is as successful as NL3 in reproducing the ground-state binding energies of the nuclei in this region. The calculated two- neutron separation energies, quadrupole deformations, and root-mean-square charge radii are in agreement with the experimental data. The parameter set FSUGold can successfully describe the shell effect of the neutron magic number N = 126 and give smaller neutron skin thicknesses than NL3 for all the nuclei considered.

Starting Control of Free Piston Stirling Linear Generator System Based on FOC

Aiming at the problem of poor system dynamic performance caused by low parameter matching in the coordinated control of Stirling engine and linear generator in the starting stage control of free piston Stirling linear generator system,a joint control method of free piston Stirling permanent magnet synchronous linear generator system based on field orientation control is proposed,based on the theoretical derivation of the mathematical model of the system and the principle of controller parameters setting,the simulation experiments of the system starting stage under several Stirling engine working conditions are carried out under simulation.The experimental results show that the stability and rapidity of the system are improved,and the dynamic response speed of generator parameters under different working conditions is accelerated,what fully verifies the correctness and effectiveness of the method.It provides an effective way to improve the control performance of the system and stabilize the power generation operation.

TRAPEZOIDAL PLATE BENDING ELEMENT WITH DOUBLE SET PARAMETERS

Using double set parameter method, a 12-parameter trapezoidal plate bending element is presented. The first set of degrees of freedom, which make the element convergent, are the values at the four vertices and the middle points of the four sides together with the mean values of the outer normal derivatives along four sides. The second set of degree of freedom, which make the number of unknowns in the resulting discrete system small and computation convenient are values and the first derivatives at the four vertices of the element. The convergence of the element is proved.

A systematic method of smooth switching LPV controllers design for a morphing aircraft

This paper is concerned with a systematic method of smooth switching linear parameter- varying （LPV） controllers design for a morphing aircraft with a variable wing sweep angle. The morphing aircraft is modeled as an LPV system, whose scheduling parameter is the variation rate of the wing sweep angle. By dividing the scheduling parameter set into subsets with overlaps, output feedback controllers which consider smooth switching are designed and the controllers in over- lapped subsets are interpolated from two adjacent subsets. A switching law without constraint on the average dwell time is obtained which makes the conclusion less conservative. Furthermore, a systematic algorithm is developed to improve the efficiency of the controllers design process. The parameter set is divided into the fewest subsets on the premise that the closed-loop system has a desired performance. Simulation results demonstrate the effectiveness of this approach.

Parameter Control of Genetic Algorithms by Learning and Simulation of Bayesian Networks——A Case Study for the Optimal Ordering of Tables

Parameter setting for evolutionary algorithms is still an important issue in evolutionary computation. There are two main approaches to parameter setting： parameter tuning and parameter control. In this paper, we introduce self-adaptive parameter control of a genetic algorithm based on Bayesian network learning and simulation. The nodes of this Bayesian network are genetic algorithm parameters to be controlled. Its structure captures probabilistie conditional （in）dependence relationships between the parameters. They are learned from the best individuals, i.e., the best configurations of the genetic algorithm. Individuals are evaluated by running the genetic algorithm for the respective parameter configuration. Since all these runs are time-consuming tasks, each genetic algorithm uses a small-sized population and is stopped before convergence. In this way promising individuals should not be lost. Experiments with an optimal search problem for simultaneous row and column orderings yield the same optima as state-of-the-art methods but with a sharp reduction in computational time. Moreover, our approach can cope with as yet unsolved high-dimensional problems.

A Model of Spray Tool and a Parameter Optimization Method for Spraying Path Planning

The digital camouflage spraying of special vehicles carried out by robots can greatly improve the spraying efficiency, spraying quality, and rapid adaptability to personalized patterns. The selection of spray tool and the accuracy of the adopted mathematical spray tool model has a great impact on the effectiveness of spray path planning and spraying quality. Since traditional conical spray tool models are not suitable for spraying rectangular digital camouflage, according to the characteristics of digital camouflage, the coating thickness cumulative distribution model of strip nozzle spray tool for 2 D plane spraying and 3 D surface spraying is derived, and its validity is verified by simulation. Based on the accumulation velocity model of the coating thickness(AVCT) on the curved surface and aiming at spraying path planning within the same surface and different surfaces, a path parameter optimization method based on coating uniformity evaluation of adjacent path overlapping area is proposed. Combined with the vehicle surface model, parameters such as path interval, spray tool angle and spray tool motion velocity can be calculated in real-time to ensure uniform coating. Based on the known local three-dimensional model of vehicle surface and the comprehensive spraying simulation, the validity of the purposed models: the coating thickness on the adjacent path area(CTAPA), the coating thickness on the intersection of two surfaces(CTITS), the coating thickness on the intersection of a plane and a surface(CTIPS), and the optimization method of path parameters are verified. The results show that compared with the traditional spray tool, the strip nozzle can better ensure the uniformity of the coating thickness of digital camouflage spray. Finally, according to a practical spraying experiment, the results prove that the proposed models not only are effective but also meet the practical industrial requirements and are of great practical value.

Parameter Ecology for Feedback Vertex Set

This paper deals with the FEEDBACK VERTEX SET problem on undirected graphs, which asks for the existence of a vertex set of bounded size that intersects all cycles. Due it is theoretical and practical importance,the problem has been the subject of intensive study. Motivated by the parameter ecology program we attempt to classify the parameterized and kernelization complexity of FEEDBACK VERTEX SET for a wide range of parameters.We survey known results and present several new complexity classifications. For example, we prove that FEEDBACK VERTEX SET is fixed-parameter tractable parameterized by the vertex-deletion distance to a chordal graph. We also prove that the problem admits a polynomial kernel when parameterized by the vertex-deletion distance to a pseudo forest, a graph in which every connected component has at most one cycle. In contrast, we prove that a slightly smaller parameterization does not allow for a polynomial kernel unless NP coNP=poly and the polynomial-time hierarchy collapses.