Enhanced UAV Pursuit-Evasion Using Boids Modelling:A Synergistic Integration of Bird Swarm Intelligence and DRL

TheUAV pursuit-evasion problem focuses on the efficient tracking and capture of evading targets using unmanned aerial vehicles(UAVs),which is pivotal in public safety applications,particularly in scenarios involving intrusion monitoring and interception.To address the challenges of data acquisition,real-world deployment,and the limited intelligence of existing algorithms in UAV pursuit-evasion tasks,we propose an innovative swarm intelligencebased UAV pursuit-evasion control framework,namely“Boids Model-based DRL Approach for Pursuit and Escape”(Boids-PE),which synergizes the strengths of swarm intelligence from bio-inspired algorithms and deep reinforcement learning(DRL).The Boids model,which simulates collective behavior through three fundamental rules,separation,alignment,and cohesion,is adopted in our work.By integrating Boids model with the Apollonian Circles algorithm,significant improvements are achieved in capturing UAVs against simple evasion strategies.To further enhance decision-making precision,we incorporate a DRL algorithm to facilitate more accurate strategic planning.We also leverage self-play training to continuously optimize the performance of pursuit UAVs.During experimental evaluation,we meticulously designed both one-on-one and multi-to-one pursuit-evasion scenarios,customizing the state space,action space,and reward function models for each scenario.Extensive simulations,supported by the PyBullet physics engine,validate the effectiveness of our proposed method.The overall results demonstrate that Boids-PE significantly enhance the efficiency and reliability of UAV pursuit-evasion tasks,providing a practical and robust solution for the real-world application of UAV pursuit-evasion missions.

Teaching Reform and Practice of Embedded System Design Based on Outcome-Based Education

Embedded system design is the core course of the telecommunication major in engineering universities,which combines software and hardware through embedded development boards.Aiming at the problems existing in traditional teaching,this paper proposes curriculum teaching reform based on the outcome-based education(OBE)concept,including determining course objectives,reforming teaching modes and methods,and improving the curriculum assessment and evaluation system.After two semesters of practice,this method not only enhances students’learning initiative but also improves teaching quality.

Retinal layer segmentation using gradient feature calculation in OCT

Retinal diseases pose significant challenges to global healthcare systems,necessitating accurate and e±cient diagnostic methods.Optical Coherence Tomography(OCT)has emerged as a valuable tool for diagnosing and monitoring retinal conditions due to its noncontact and noninvasive nature.This paper presents a novel retinal layering method based on OCT images,aimed at enhancing the accuracy of retinal lesion diagnosis.The method utilizes gradient analysis to effectively identify and segment retinal layers.By selecting a column of pixels as a segmentation line and utilizing gradient information from adjacent pixels,the method initiates and proceeds with the layering process.This approach addresses potential issues arising from partial layer overlapping,minimizing deviations in layer segmentation.Experimental results demonstrate the e±cacy of the proposed method in accurately segmenting eight retinal boundaries,with an average absolute position deviation of 1.75 pixels.By providing accurate segmentation of retinal layers,this approach contributes to the early detection and management of ocular conditions,ultimately improving patient outcomes and reducing the global burden of vision-related ailments.

A Survey of Output Feedback Robust MPC for Linear Parameter Varying Systems

For constrained linear parameter varying(LPV)systems,this survey comprehensively reviews the literatures on output feedback robust model predictive control(OFRMPC)over the past two decades from the aspects on motivations,main contributions,and the related techniques.According to the types of state observer systems and scheduling parameters of LPV systems,different kinds of OFRMPC approaches are summarized and compared.The extensions of OFRMPC for LPV systems to other related uncertain systems are also investigated.The methods of dealing with system uncertainties and constraints in different kinds of OFRMPC optimizations are given.Key issues on OFRMPC optimizations for LPV systems are discussed.Furthermore,the future research directions on OFRMPC for LPV systems are suggested.

Effects of pulse energy ratios on plasma characteristics of dual-pulse fiber-optic laser-induced breakdown spectroscopy

Laser-induced plasmas of dual-pulse fiber-optic laser-induced breakdown spectroscopy with different pulse energy ratios are studied by using the optical emission spectroscopy(OES)and fast imaging.The energy of the two laser pulses is independently adjusted within 0–30 m J with the total energy fixed at 30 m J.The inter-pulse delay remains 450 ns constantly.As the energy share of the first pulse increases,a similar bimodal variation trend of line intensities is observed.The two peaks are obtained at the point where the first pulse is half or twice of the second one,and the maximum spectral enhancement is at the first peak.The bimodal variation trend is induced by the change in the dominated mechanism of dual-pulse excitation with the trough between the two peaks caused by the weak coupling between the two mechanisms.By increasing the first pulse energy,there is a transition from the ablation enhancement dominance near the first peak to the plasma reheating dominance near the second peak.The calculations of plasma temperature and electron number density are consistent with the bimodal trend,which have the values of 17024.47 K,2.75×10^(17)cm;and 12215.93 K,1.17×10^(17)cm;at a time delay of 550 ns.In addition,the difference between the two peaks decreases with time delay.With the increase in the first pulse energy share,the plasma morphology undergoes a transformation from hemispherical to shiny-dot and to oblate-cylinder structure during the second laser irradiation from the recorded images by using an intensified charge-coupled device(ICCD)camera.Correspondingly,the peak expansion distance of the plasma front first decreases significantly from 1.99 mm in the single-pulse case to 1.34 mm at 12/18(dominated by ablation enhancement)and then increases slightly with increasing the plasma reheating effect.The variations in plasma dynamics verify that the change of pulse energy ratios leads to a transformation in the dual-pulse excitation mechanism.

An improved method for internal multiple elimination using the theory of virtual events

Compared with first-order surface-related multiples from marine data,the onshore internal multiples are weaker and are always combined with a hazy and occasionally strong interference pattern.It is usually difficult to discriminate these events from complex targets and highly scattering overburdens,especially when the primary energy from deep layers is weaker than that from shallow layers.The internal multiple elimination is even more challenging due to the fact that the velocity and energy difference between primary reflections and internal multiples is tiny.In this study,we propose an improved method which formulates the elimination of the internal multiples as an optimization problem and develops a convolution factor T.The generated internal multiples at all interfaces are obtained using the convolution factor T through iterative inversion of the initial multiple model.The predicted internal multiples are removed from seismic data through subtraction.Finally,several synthetic experiments are conducted to validate the effectiveness of our approach.The results of our study indicate that compared with the traditional virtual events method,the improved method simplifies the multiple prediction process in which internal multiples generated from each interface are built through iterative inversion,thus reducing the calculation cost,improving the accuracy,and enhancing the adaptability of field data.

Research on the Prediction of Load Regulation Capacity for Supercritical Thermal Power Unit

Both the modeling and the load regulation capacity prediction of a supercritical power plant are investigated in this paper. Firstly, an indirect identification method based on subspace identification method is proposed. The obtained identification model is verified by the actual operation data and the dynamic characteristics of the system are well reproduced. Secondly, the model is used to predict the load regulation capacity of thermal power unit. The power, main steam pressure, main steam temperature and other parameters are simulated respectively when the unit load is going up and down. Under the actual constraints, the load regulation capacity of thermal power unit can be predicted quickly.

Exploring plasmons weakly coupling to perovskite excitons with tunable emission by energy transfer

Localized surface plasmon resonance(LSPR) has caused extensive concern and achieved widespread applications in optoelectronics. However, the weak coupling of plasmons and excitons in a nanometal/semiconductor system remains to be investigated via energy transfer. Herein, bandgap tunable perovskite films were synthesized to adjust the emission peaks,for further coupling with stable localized surface plasmons from gold nanoparticles. The degree of mismatch, using steadystate and transient photoluminescence(PL), was investigated systematically in two different cases of gold nanoparticles that were in direct contacting and insulated. The results demonstrated the process of tuning emission coupled to LSPR via wavelength-dependent photoluminescence intensity in the samples with an insulating spacer. In the direct contact case,the decreased radiative decay rate involves rapid plasmon resonance energy transfer to the perovskite semiconductor and non-radiative energy transfer to metal nanoparticles in the near-field range.

Privacy Preserving Demand Side Management Method via Multi-Agent Reinforcement Learning

The smart grid utilizes the demand side management technology to motivate energy users towards cutting demand during peak power consumption periods, which greatly improves the operation efficiency of the power grid. However, as the number of energy users participating in the smart grid continues to increase, the demand side management strategy of individual agent is greatly affected by the dynamic strategies of other agents. In addition, the existing demand side management methods, which need to obtain users’ power consumption information,seriously threaten the users’ privacy. To address the dynamic issue in the multi-microgrid demand side management model, a novel multi-agent reinforcement learning method based on centralized training and decentralized execution paradigm is presented to mitigate the damage of training performance caused by the instability of training experience. In order to protect users’ privacy, we design a neural network with fixed parameters as the encryptor to transform the users’ energy consumption information from low-dimensional to high-dimensional and theoretically prove that the proposed encryptor-based privacy preserving method will not affect the convergence property of the reinforcement learning algorithm. We verify the effectiveness of the proposed demand side management scheme with the real-world energy consumption data of Xi’an, Shaanxi, China. Simulation results show that the proposed method can effectively improve users’ satisfaction while reducing the bill payment compared with traditional reinforcement learning(RL) methods(i.e., deep Q learning(DQN), deep deterministic policy gradient(DDPG),QMIX and multi-agent deep deterministic policy gradient(MADDPG)). The results also demonstrate that the proposed privacy protection scheme can effectively protect users’ privacy while ensuring the performance of the algorithm.

Design,simulation,and testing of a tunable MEMS multi-threshold inertial switch

This paper presents a tunable multi-threshold micro-electromechanical inertial switch with adjustable threshold capability.The demonstrated device combines the advantages of accelerometers in providing quantitative acceleration measurements and g-threshold switches in saving power when in the inactive state upon experiencing acceleration below the thresholds.The designed proof-of-concept device with two thresholds consists of a cantilever microbeam and two stationary electrodes placed at different positions in the sensing direction.The adjustable threshold capability and the effect of the shock duration on the threshold acceleration are analytically investigated using a nonlinear beam model.Results are shown for the relationships among the applied bias voltage,the duration of shock impact,and the tunable threshold.The fabricated prototypes are tested using a shock-table system.The analytical results agree with the experimental results.The designed device concept is very promising for the classification of the shock and impact loads in transportation and healthcare applications.

Practical fixed-time adaptive fuzzy control of uncertain nonlinear systems with time-varying asymmetric constraints: a unified barrier function based approach

A practical fixed-time adaptive fuzzy control strategy is investigated for uncertain nonlinear systems with time-varying asymmetric constraints and input quantization. To overcome the difficulties of designing controllers under the state constraints, a unified barrier function approach is employed to construct a coordinate transformation that maps the original constrained system to an equivalent unconstrained one, thus relaxing the time-varying asymmetric constraints upon system states and avoiding the feasibility check condition typically required in the traditional barrier Lyapunov function based control approach. Meanwhile, the “explosion of complexity” problem in the traditional backstepping approach arising from repeatedly derivatives of virtual controllers is solved by using the command filter method. It is verified via the fixed-time Lyapunov stability criterion that the system output can track a desired signal within a small error range in a predetermined time, and that all system states remain in the constraint range. Finally, two simulation examples are offered to demonstrate the effectiveness of the proposed strategy.

Tailoring chaotic motion of microcavity photons in ray and wave dynamics by tuning the curvature of space

Microcavity photon dynamics in curved space is an emerging interesting area at the crossing point of nanophotonics,chaotic science,and non-Euclidean geometry.We report the sharp difference between the regular and chaotic motions of cavity photons subjected to the varying space curvature.While the island modes of regular motion rise in the phase diagram in the curved space,the chaotic modes show special mechanisms to adapt to the space curvature,including the fast diffusion of ray dynamics,and the localization and hybridization of the Husimi wavepackets among different periodic orbits.These observations are unique effects enabled by the combination of the chaotic trajectory,the wave nature of light,and the non-Euclidean orbital motion,and therefore make the system a versatile optical simulator for chaotic science under quantum mechanics in curved space-time.

Data Augmentation Technology Driven By Image Style Transfer in Self-Driving Car Based on End-to-End Learning

With the advent of deep learning,self-driving schemes based on deep learning are becoming more and more popular.Robust perception-action models should learn from data with different scenarios and real behaviors,while current end-to-end model learning is generally limited to training of massive data,innovation of deep network architecture,and learning in-situ model in a simulation environment.Therefore,we introduce a new image style transfer method into data augmentation,and improve the diversity of limited data by changing the texture,contrast ratio and color of the image,and then it is extended to the scenarios that the model has been unobserved before.Inspired by rapid style transfer and artistic style neural algorithms,we propose an arbitrary style generation network architecture,including style transfer network,style learning network,style loss network and multivariate Gaussian distribution function.The style embedding vector is randomly sampled from the multivariate Gaussian distribution and linearly interpolated with the embedded vector predicted by the input image on the style learning network,which provides a set of normalization constants for the style transfer network,and finally realizes the diversity of the image style.In order to verify the effectiveness of the method,image classification and simulation experiments were performed separately.Finally,we built a small-sized smart car experiment platform,and apply the data augmentation technology based on image style transfer drive to the experiment of automatic driving for the first time.The experimental results show that:(1)The proposed scheme can improve the prediction accuracy of the end-to-end model and reduce the model’s error accumulation;(2)the method based on image style transfer provides a new scheme for data augmentation technology,and also provides a solution for the high cost that many deep models rely heavily on a large number of label data.

A Fully Homomorphic Encryption Scheme with Better Key Size

Fully homomorphic encryption is faced with two problems now. One is candidate fully homomorphic encryption schemes are few. Another is that the efficiency of fully homomorphic encryption is a big question. In this paper, we propose a fully homomorphic encryption scheme based on LWE, which has better key size. Our main contributions are： （1） According to the binary-LWE recently, we choose secret key from binary set and modify the basic encryption scheme proposed in Linder and Peikert in 2010. We propose a fully homomorphic encryption scheme based on the new basic encryption scheme. We analyze the correctness and give the proof of the security of our scheme. The public key, evaluation keys and tensored ciphertext have better size in our scheme. （2） Estimating parameters for fully homomorphic encryption scheme is an important work. We estimate the concert parameters for our scheme. We compare these parameters between our scheme and Bral2 scheme. Our scheme have public key and private key that smaller by a factor of about logq than in Bral2 scheme. Tensored ciphertext in our scheme is smaller by a factor of about log2q than in Bral2 scheme. Key switching matrix in our scheme is smaller by a factor of about log3q than in Bra12 scheme.

Non-Hermitian control of confined optical skyrmions in microcavities formed by photonic spin-orbit coupling

Optical skyrmions formed by photonic spin–orbit(SO)coupling are of significant interest in high-dimensional optical information processing.We report the formation mechanism and non-Hermitian properties of skyrmionlike states in a circular confinement potential with photonic SO coupling,which is preferably realized in a concave-planar microcavity system.We show that the effective photonic gauge field leads to two split manifolds of degenerate skyrmions whose spin textures can be controlled via the non-Hermitian properties by introducing circularly polarized gain and loss,exhibiting dramatically discrepant evolutions at the two sides of the exceptional point(EP).Furthermore,the lifetime degeneracy can be lifted by spatially inhomogeneous pumping according to the non-Hermitian mechanism,enabling the possibility for the skyrmion laser.By introducing shape asymmetry of the confinement potential,a double EP evolution can be achieved,which allows non-Hermitian control of the SO coupled states with higher degrees of freedom.These results open the way for the non-Hermitian control of photonic spin in confined systems,which would be of great significance for the fundamentals of advanced optical information processing.

Systematic study on size and temporal dependence of micro-LED arrays for display applications

Micro-LEDs are one of the most promising candidates for next-generation displays,yet they are inconvenienced by the efficiency reduction induced by the sidewall defects when pursuing further scaled-down device dimensions.We have systematically investigated both the size and temporal dependence of micro-LEDs.Micro-LED arrays with a mesa size ranging from 7 to 100μm were prepared for display purposes.The luminance and external quantum efficiency(EQE)were measured and discussed.Surprisingly,micro-LED arrays with a smaller mesa size exhibit a higher EQE under 100 ns pulse duration operation when compared with longer pulse duration operations.Under certain short-pulsed excitation,a 7×7μm^(2)micro-LED array even exhibits a>20%higher EQE as compared to the direct current(DC)or the long duration pulse operation condition.We thus concluded that the notorious efficiency reduction induced by sidewall defects in small-sized micro-LED arrays could be significantly reduced by applying short-pulse voltages.

Sintering characteristics, phase transitions, and microwave dielectric properties of low-firing [(Na_(0.5)Bi_(0.5))_(x)Bi_(1-x)](W_(x)V_(1-x))O_(4) solid solutionceramics

A series of high-k[(Na_(0.5)Bi_(0.5))_(x)Bi_(1-x)](W_(x)V_(1-x))O_(4)(abbreviated as NBWV(x value))solid solution ceramics with a scheelite-like structure are synthesized by a modified solid-state reaction method at the temperature range of 680-760 C.A monoclinic(0≤x<0.09)to tetragonal scheelite(0.09≤x≤1.0)structural phase transition is confirmed by X-ray difraction(XRD),Raman,and infrared(IR)analyses.The effect of structural deformation and order-disorder caused by Na^(+)/Bi^(3+)/W^(6+) complex substitution on microwave dielectric properties is investigated in deail.The compositional series possess a wide range of variable relative permittivity(er=24.8-80)and temperature coefficient of resonant frequency(TCF value,-271.9-188.9 ppm/℃).The maximum permittivity of 80 and a high Qxf value of~10,000 GHz are obtained near the phase boundary at x=0.09.Furthermore,the temperature-stable dielectric ceramics sintered at 680 C with excellent microwave dielectric properties of ε_(r)=80.7,Qxf=9400 GHz(at 4.1 GHz),and TCF value=-3.8 ppm/℃ are designed by mixing the components of x=0.07 and 0.08.In summary,similar sinterability and structural compatibility of scheelite-like solid solution systems make it potential for low-temperature co-fired ceramic(LTCC)applications.

Electromagnetically induced transparency-like effect in a lithium niobate resonator via electronic control

In this study,we theoretically proposed a method to achieve an electromagnetically induced transparency(EIT)-like effect in a whispering gallery mode resonator(WGMR)and experimentally validated the method in a lithium niobate(LN)device.Benefitting from the electro-optic and inverse piezoelectric effects of the LN material,two modes of the LN WGMR that are close in frequency can be tuned at different tuning rates,resulting in EIT-like resonance lineshapes.By varying the electric field applied to the LN WGMR,the full dynamic of the EIT-like phenomenon can be precisely controlled.The experimental results agreed well with the calculations based on the coupled mode theory.Moreover,we observed a hysteresis resulting from the photorefractive effect of LN.We believe our proposed method and demonstrated devices offer a way to control an EIT-like effect,which could have potential applications in light storage,quantum information processing,and enhanced sensing techniques.

The effect of lateral growth of self-assembled GaN microdisks on UV lasing action

There are significant differences in the extent of impurity incorporation on different crystallographic directions of GaN microstructures,and the impurity-related deep energy level behavior will have a significant impact on device performance.However,a comprehensive understanding of the effect of lateral growth on device performance has not been achieved due to the lack of comprehensive spatial distribution characterization of the optical behavior and impurity incorporation in GaN microstructures.We present a comprehensive study of the optical behavior and growth mechanism of self-assembled GaN microdisks using nanoscale spatially resolved cathodoluminescence(CL)mapping.We have found a clear growth orientation-dependent optical behavior of the lateral and vertical growth sectors of self-assembled GaN microcrystals.The lateral growth sector,i.e.,the{101¯1}-growth sector,forms six side facets of the microdisk and shows significant near-bandgap emission(NBE)and weak deep energy level luminescence.Cavity effect enhanced emission was found for the first time in such a truncated hexagonal Na-flux GaN microdisk system with an ultra-smooth surface(Ra<0.7 nm)and low stress.The self-assembled microdisk shows significant ultraviolet(UV)lasing action(main lasing peak wavelength 370.9 nm,quality factor 1278,threshold 6×10^(4)μJ/cm^(2))under pulsed optical pumping.We believe that the appearance of UV lasing action may be related to the light limitation on the six side facets of the lateral growth of the GaN microdisk,the high structural quality,the low content of deep energy level defects,the low surface roughness,and the low stress.

NextPolish2:A Repeat-aware Polishing Tool for Genomes Assembled Using HiFi Long Reads

The high-fidelity(HiFi)long-read sequencing technology developed by PacBio has greatly improved the base-level accuracy of genome assemblies.However,these assemblies still contain base-level errors,particularly within the error-prone regions of HiFi long reads.Existing genome polishing tools usually introduce overcorrections and haplotype switch errors when correcting errors in genomes assembled from HiFi long reads.Here,we describe an upgraded genome polishing tool-NextPolish2,which can fix base errors remaining in those“highly accurate”genomes assembled from HiFi long reads without introducing excessive overcorrections and haplotype switch errors.We believe that NextPolish2 has a great significance to further improve the accuracy of telomere-to-telomere(T2T)genomes.NextPolish2 is freely available at https://github.com/Nextomics/NextPolish2.