Optimal deadlock avoidance Petri net supervisors for automated manufacturing systems

Deadlock avoidance problems are investigated for automated manufacturing systems with flexible routings. Based on the Petri net models of the systems, this paper proposes, for the first time, the concept of perfect maximal resourcetransition circuits and their saturated states. The concept facilitates the development of system liveness characterization and deadlock avoidance Petri net supervisors. Deadlock is characterized as some perfect maximal resource-transition circuits reaching their saturated states. For a large class of manufacturing systems, which do not contain center resources, the optimal deadlock avoidance Petri net supervisors are presented. For a general manufacturing system, a method is proposed for reducing the system Petri net model so that the reduced model does not contain center resources and, hence, has optimal deadlock avoidance Petri net supervisor. The controlled reduced Petri net model can then be used as the liveness supervisor of the system.

Stochastic bounded consensus of second-order multi-agent systems in noisy environment

This paper investigates the stochastic bounded consensus of leader-following second-order multi-agent systems in a noisy environment. It is assumed that each agent received the information of its neighbors corrupted by noises and time delays. Based on the graph theory, stochastic tools, and the Lyapunov function method, we derive the sufficient conditions under which the systems would reach stochastic bounded consensus in mean square with the protocol we designed. Finally, a numerical simulation is illustrated to check the effectiveness of the proposed algorithms.

Delay-dependent exponential stability of impulsive stochastic systems with time-varying delay

The problem of delay-dependent exponential stability is investigated for impulsive stochastic systems with time-varying delay. Although the exponential stability of impulsive stochastic delay systems has been discussed by several authors, few works have been done on delay-dependent exponential stability of impulsive stochastic delay systems. Firstly, the Lyapunov-Krasovskii functional method combing the free-weighting matrix approach is applied to investigate this problem. Some delay-dependent mean square exponential stability criteria are derived in terms of linear matrix inequalities. In particular, the estimate of the exponential convergence rate is also provided, which depends on system parameters and impulsive effects. The obtained results show that the system will stable if the impulses＇ frequency and amplitude are suitably related to the increase or decrease of the continuous flows, and impulses may be used as controllers to stabilize the underlying stochastic system. Numerical examples are given to show the effectiveness of the results.

The metabolic profiling of Chinese yam fermented by Saccharomyces boulardii and the biological activities of its ethanol extract in vitro

Chinese yam(Dioscorea opposita Thunb.),as one of the medicinal and edible homologous plants,is rich in various nutrients and functional factors.In this study,Chinese yam fermented by Saccharomyces boulardii was performed to investigate its bioactive components and metabolic profile.And then,the main bioactive components and biological activities of fermented Chinese yam ethanol extract(FCYE)were evaluated.Results showed that there were 49 up-regulated metabolites and 52 down-regulated metabolites in fermented Chinese yam compared to unfermented Chinese yam.Besides,corresponding metabolic pathways analysis initially revealed that the distribution of bioactive substances was concentrated on alcoholsoluble small molecular substances.Ulteriorly,the total polyphenol content and the total flavonoid content in FCYE were significantly increased,and the corresponding antioxidant and immunomodulatory activities in vitro were also significantly enhanced.Our study provided a new reference for the comprehensive utilization of Chinese yam and laid a theoretical foundation for the development and application of natural probiotic-fermented products.

Modifiers of the Effects of Vitamin D Supplementation on Cardiometabolic Risk Factors:A Systematic Review and Meta-Analysis

The inconsistent findings concerning the effects of vitamin D supplementation on cardiometabolic risk factors and the large heterogeneity in the published literature call for further research to identify sources of heterogeneity and potential effect modifiers.We performed a meta-analysis of randomized controlled trials(RCTs)published until March 2024 that reported estimates for the effects of vitamin D supplementation on cardiometabolic factors and relevant baseline covariates of RCT participants.A total of 17656 participants from 99 RCTs were analyzed,and weighted mean differences(95%confidence intervals(CI))for the intervention status were derived using random-effects modeling.Overall,compared with the placebo,vitamin D supplementation(median dose:3320 international unit(IU)·day^(-1);range 40-120000 IU·day^(-1))had favorable effects on systolic blood pressure(SBP;-2.04(95%CI,-3.50,-0.59)mmHg;1 mmHg=0.133 kPa),diastolic blood pressure(DBP;-3.00(95%CI,-3.61,-2.39)mmHg),total cholesterol(TC;-0.12(95%CI,-0.21,-0.03)mmol·L^(-1)),fasting blood glucose(FBG;-0.13(95%CI,-0.20,-0.05)mmol·L^(-1)),hemoglobin A1C(A1C;-0.09%(95%CI,-0.13%,-0.05%)),and fasting blood insulin(FBI:-7.61(95%CI,-11.93,-3.30)pmol·L^(-1)).The benefits of vitamin D were most evident in trials performed in non-Westerners,participants with baseline 25-hydroxyvitamin D(25[OH]D)lower than 15.0 ng·mL^(-1),non-obese(body mass index(BMI)<30 kg·m^(-2)),and older(age-50 years).The findings of this study underscore the need for personalized vitamin D intervention strategies that comprehensively account for individual patient characteristics(such as ethnocultural background,age,BMI,and circulating 25[OH]D level),intervention dosage,and intervention duration to optimize cardiometabolic health outcomes.

High-order Bragg forward scattering and frequency shift of low-frequency underwater acoustic field by moving rough sea surface

Acoustic scattering modulation caused by an undulating sea surface on the space-time dimension seriously affects underwater detection and target recognition.Herein,underwater acoustic scattering modulation from a moving rough sea surface is studied based on integral equation and parabolic equation.And with the principles of grating and constructive interference,the mechanism of this acoustic scattering modulation is explained.The periodicity of the interference of moving rough sea surface will lead to the interference of the scattering field at a series of discrete angles,which will form comb-like and frequency-shift characteristics on the intensity and the frequency spectrum of the acoustic scattering field,respectively,which is a high-order Bragg scattering phenomenon.Unlike the conventional Doppler effect,the frequency shifts of the Bragg scattering phenomenon are multiples of the undulating sea surface frequency and are independent of the incident sound wave frequency.Therefore,even if a low-frequency underwater acoustic field is incident,it will produce obvious frequency shifts.Moreover,under the action of ideal sinusoidal waves,swells,fully grown wind waves,unsteady wind waves,or mixed waves,different moving rough sea surfaces create different acoustic scattering processes and possess different frequency shift characteristics.For the swell wave,which tends to be a single harmonic wave,the moving rough sea surface produces more obvious high-order scattering and frequency shifts.The same phenomena are observed on the sea surface under fully grown wind waves,however,the frequency shift slightly offsets the multiple peak frequencies of the wind wave spectrum.Comparing with the swell and fully-grown wind waves,the acoustic scattering and frequency shift are not obvious for the sea surface under unsteady wind waves.

Enhancing Renewable Energy Integration:A Gaussian-Bare-Bones Levy Cheetah Optimization Approach to Optimal Power Flow in Electrical Networks

In the contemporary era,the global expansion of electrical grids is propelled by various renewable energy sources(RESs).Efficient integration of stochastic RESs and optimal power flow(OPF)management are critical for network optimization.This study introduces an innovative solution,the Gaussian Bare-Bones Levy Cheetah Optimizer(GBBLCO),addressing OPF challenges in power generation systems with stochastic RESs.The primary objective is to minimize the total operating costs of RESs,considering four functions:overall operating costs,voltage deviation management,emissions reduction,voltage stability index(VSI)and power loss mitigation.Additionally,a carbon tax is included in the objective function to reduce carbon emissions.Thorough scrutiny,using modified IEEE 30-bus and IEEE 118-bus systems,validates GBBLCO’s superior performance in achieving optimal solutions.Simulation results demonstrate GBBLCO’s efficacy in six optimization scenarios:total cost with valve point effects,total cost with emission and carbon tax,total cost with prohibited operating zones,active power loss optimization,voltage deviation optimization and enhancing voltage stability index(VSI).GBBLCO outperforms conventional techniques in each scenario,showcasing rapid convergence and superior solution quality.Notably,GBBLCO navigates complexities introduced by valve point effects,adapts to environmental constraints,optimizes costs while considering prohibited operating zones,minimizes active power losses,and optimizes voltage deviation by enhancing the voltage stability index(VSI)effectively.This research significantly contributes to advancing OPF,emphasizing GBBLCO’s improved global search capabilities and ability to address challenges related to local minima.GBBLCO emerges as a versatile and robust optimization tool for diverse challenges in power systems,offering a promising solution for the evolving needs of renewable energy-integrated power grids.

Radar-Based Multi-Target Localization and Vital Sign Monitoring

The frequency-modulated continuous wave (FMCW) radar, known for its high range resolution, has garnered significant attention in the field of non-contact vital sign monitoring. However, accurately locating multiple targets and separating their vital sign signals remains a challenging research topic. This paper proposes a scene-differentiated method for multi-target localization and vital sign monitoring. The approach identifies the relative positions of multiple targets using Range FFT and determines the directions of targets via the multiple signal classification (MUSIC) algorithm. Phase signals within the range bins corresponding to the targets are separated using bandpass filtering. If multiple targets reside in the same range bin, the variational mode decomposition (VMD) algorithm is employed to decompose their breathing or heartbeat signals. Experimental results demonstrate that the proposed method accurately localizes targets. When multiple targets occupy the same range bin, the mean absolute error (MAE) for respiratory signals is 3 bpm, and the MAE for heartbeat signals is 5 bpm.

Non-Invasive Cerebral Hemorrhage Size Determination by Microwave Signal Based on RSSD

Aiming at the prediction of the size of human cerebral hemorrhage point, a signal processing method based on Resonance Sparse Decomposition (RSSD) algorithm is proposed to decompose and analyze the microwave echo signal. According to the organizational structure of the human brain, a complete human brain model was established, and bleeding points of different sizes were placed at the same position, and 5 antennas were placed around the model (front, back, left, right, and top). RSSD is performed on the obtained echo signal, and Hilbert envelope analysis is performed on the low resonance component obtained by the decomposition, and then the size of the bleeding point is judged. Using CST and MATLAB to conduct simulation analysis and experiments, it is verified that the proposed method can successfully determine the size of the bleeding point, and the effectiveness and feasibility of the method are proved.

电化学法快速测定茶多酚含量的研究

基于电化学循环伏安法,讨论了3种低成本自制工作电极——银电极、碳糊电极和玻碳电极在茶多酚含量测定应用上的可行性。通过分析茶多酚在电极表面的氧化还原行为,发现所制银电极不适宜检测茶多酚,碳糊电极、玻碳电极的氧化电流峰值与茶多酚含量有良好的线性关系。所制玻碳电极测定绿茶茶样中的茶多酚含量的重复性和准确性较碳糊电极好。与国标方法相比,碳糊电极、玻碳电极检测茶多酚所需时间大大缩短。结果表明,电化学方法可应用于茶多酚含量的快速测定,从而为快速、低价、便捷检测茶多酚提供一条新思路。

Robust Deadlock Avoidance Policy for Automated Manufacturing System With Multiple Unreliable Resources

This work studies the robust deadlock control of automated manufacturing systems with multiple unreliable resources. Our goal is to ensure the continuous production of the jobs that only require reliable resources. To reach this goal, we propose a new modified Banker's algorithm(MBA) to ensure that all resources required by these jobs can be freed. Moreover,a Petri net based deadlock avoidance policy(DAP) is introduced to ensure that all jobs remaining in the system after executing the new MBA can complete their processing smoothly when their required unreliable resources are operational. The new MBA together with the DAP forms a new DAP that is robust to the failures of unreliable resources. Owing to the high permissiveness of the new MBA and the optimality of the DAP, it is tested to be more permissive than state-of-the-art control policies.

Wavelet neural network aerodynamic modeling from flight data based on pso algorithm with information sharing and velocity disturbance

For the accurate description of aerodynamic characteristics for aircraft,a wavelet neural network (WNN) aerodynamic modeling method from flight data,based on improved particle swarm optimization (PSO) algorithm with information sharing strategy and velocity disturbance operator,is proposed.In improved PSO algorithm,an information sharing strategy is used to avoid the premature convergence as much as possible;the velocity disturbance operator is adopted to jump out of this position once falling into the premature convergence.Simulations on lateral and longitudinal aerodynamic modeling for ATTAS (advanced technologies testing aircraft system) indicate that the proposed method can achieve the accuracy improvement of an order of magnitude compared with SPSO-WNN,and can converge to a satisfactory precision by only 60 120 iterations in contrast to SPSO-WNN with 6 times precocities in 200 times repetitive experiments using Morlet and Mexican hat wavelet functions.Furthermore,it is proved that the proposed method is feasible and effective for aerodynamic modeling from flight data.

Adaptive WNN aerodynamic modeling based on subset KPCA feature extraction

In order to accurately describe the dynamic characteristics of flight vehicles through aerodynamic modeling, an adaptive wavelet neural network (AWNN) aerodynamic modeling method is proposed, based on subset kernel principal components analysis (SKPCA) feature extraction. Firstly, by fuzzy C-means clustering, some samples are selected from the training sample set to constitute a sample subset. Then, the obtained samples subset is used to execute SKPCA for extracting basic features of the training samples. Finally, using the extracted basic features, the AWNN aerodynamic model is established. The experimental results show that, in 50 times repetitive modeling, the modeling ability of the method proposed is better than that of other six methods. It only needs about half the modeling time of KPCA-AWNN under a close prediction accuracy, and can easily determine the model parameters. This enables it to be effective and feasible to construct the aerodynamic modeling for flight vehicles.

Effect of WS_2 particle size on mechanical properties and tribological behaviors of Cu-WS_2 composites sintered by SPS

The mechanical properties and tribological behaviors of Cu-WS2 composites fabricated by spark plasma sintering（SPS） using two different WS2 particle sizes of 0.6 and 5.0 μm and Cu powders as raw materials were investigated. The results indicate that the bending strength and tribological behavior of Cu-WS2 composites are greatly affected by the size of WS2 particles. The bending strength of Cu-WS2 composites with the WS2 particle size of 5.0 μm is 292.2 MPa. As the size of WS2 particle decreases to 0.6 μm, the bending strength also decreases to 181.5 MPa. Moreover, as the WS2 particle size decreases from 5.0 to 0.6 μm, the wear rate of Cu-WS2 composite sharply increases from 2.99×10^-14 to 6.13×10^-14 m^3/（N·m） and its friction coefficient increases from 0.158 to 0.172. The size of WS2 particle（5.0 μm） plays an important role in forming transfer film formed on the counter-face. The sample with 5.0 μm WS2 particle forms smoother and more continuous transfer film, which results in a low wear rate and friction coefficient of the Cu-WS2 composites.

SRV constraint based FIB design for wideband linear array

Frequency-invariant beamformer （FIB） design is a key issue in wideband array signal processing. To use commonly wideband linear array with tapped delay line （TDL） structure and complex weights, the FIB design is provided according to the rule of minimizing the sidelobe level of the beampattern at the reference frequency while keeping the distortionless response constraint in the mainlobe direction at the reference frequency, the norm constraint of the weight vector and the amplitude constraint of the averaged spatial response variation （SRV）. This kind of beamformer design problem can be solved with the interior-point method after being converted to the form of standard second order cone programming （SOCP）. The computer simulations are presented which illustrate the effectiveness of our FIB design method for the wideband linear array with TDL structure and complex weights.

Optimization and Mechanical Accuracy Reliability of a New Type of Forging Manipulator

Researches on forging manipulator have enormous influence on the development of the forging industry and national economy.Clamp device and lifting mechanism are the core parts of forging manipulator,and have been studied for longer time.However,the optimization and mechanical accuracy reliability of them are less analyzed.Based on General Function（G_F）set and parallel mechanism theory,proper configuration of 10t forging manipulator is selected firstly.A new type of forging manipulator driven by cylinders is proposed.After solved mechanical analysis of manipulator＇s core mechanisms,expressions of force of cylinders are carried out.In order to achieve smaller force afforded by cylinders and better mechanical characteristics,some particular sizes of core mechanisms are optimized intuitively through the combined use of the genetic algorithms（GA）and GUI interface in MATLAB.Comparing with the original mechanisms,optimized clamp saves at least 8 percent efforts and optimized lifting mechanism 20 percent under maximum working condition.Finally,considering the existed manufacture error of components,mechanical accuracy reliability of optimized clamp,lifting mechanism and whole manipulator are demonstrated respectively based on fuzzy reliability theory.Obtained results show that the accuracy reliability of optimized clamp is bigger than 0.991 and that of optimized lifting mechanism is 0.995.To the whole manipulator under maximum working condition,that value exceeds 0.986 4,which means that optimized manipulator has high motion accuracy and is reliable.A new intuitive method is created to optimize forging manipulator sizes efficiently and more practical theory is utilized to analyze mechanical accuracy reliability of forging manipulator precisely.

Study of Direction Probability and Algorithm of Improved Marriage in Honey Bees Optimization for Weapon Network System

To solve the weapon network system optimization problem against small raid objects with low attitude,the concept of direction probability and a new evaluation index system are proposed.By calculating the whole damaging probability that changes with the defending angle,the efficiency of the whole weapon network system can be subtly described.With such method,we can avoid the inconformity of the description obtained from the traditional index systems.Three new indexes are also proposed,i.e.join index,overlap index and cover index,which help manage the relationship among several sub-weapon-networks.By normalizing the computation results with the Sigmoid function,the matching problem between the optimization algorithm and indexes is well settled.Also,the algorithm of improved marriage in honey bees optimization that proposed in our previous work is applied to optimize the embattlement problem.Simulation is carried out to show the efficiency of the proposed indexes and the optimization algorithm.

VFT PHASE VOLTAGE MEASUREMENT IN THREE-PHASE ENCLOSED GIS

The measuring of VFT phase voltage in three-phase enclosed GIS is more complex and difficult than in single-phase ones. There are 3 capacitive sensors in the measuring system, the outputs of which are with a linear relation to the three phase voltages. This linear relation is presented with a factorial matrix. Because each capacitive sensor is coupled with the electric field of three phases (A, B, and C), the electric coupling coefficients are introduced. In order to determine the matrix of electric coupling coefficients, the numerical calculation method can be used. From the discussion on two types of three-phase enclosed GIS bus, i.e. standard arrangement and biased arrangement, the dominant electric coupling coefficients are named, which can be simply and approximately calculated by an analytic expression. Finally, as an example, the waveforms of VFT phase voltage generated on a three-phase enclosed GIS bus model are displayed. When a capacitive sensor is located at the ’shortest point’ of phase A (or B, or C), the VFT phase voltage V A (or V B, or V C) can almost be measured by that capacitive sensor alone.

Influence of warm eddies on sound propagation in the Gulf of Mexico

An automatic detection method is employed to identify and track eddies in the Gulf of Mexico. The physical parameters of the eddies, such as lifespan, radius, and distribution position are first examined and used to determine the spatio–temporal evolution of a strong warm eddy separated from the Mexico current. Then, the influence of this strong warm eddy on sound propagation during its lifespan are comprehensively analyzed with the parabolic equation and explained by using the normal mode and ray theories. Additionally, the influence of mesoscale eddies on the redistribution of total depth-integrated energy among the normal modes in the deep water is also discussed. The variation of arrival angle is investigated to explain the spreading acoustic energy caused by eddies. Overall, the results show that warm eddies can change the propagation paths and cause the convergence zone to broaden and approach the sound source. Moreover,the warm eddy can disperse sound energy and cause the total depth-integrated energy to incline to a lower normal mode.Throughout the whole of these three periods(eddy generating, eddy maturing, and eddy terminating), the fluctuation in the transmission loss is up to 30 dB(depending on the relative location of eddy center to the source).