Real Path Research Articles

Accurate estimation of dynamical quantities for nonequilibrium nanoscale systems.

Fluctuations of dynamical quantities are fundamental and inevitable. For the booming research in nanotechnology, huge relative fluctuation comes with the reduction of system size, leading to large uncertainty for the estimates of dynamical quantities. Thus, increasing statistical efficiency, i.e., reducing the number of samples required to achieve a given accuracy, is of great significance for accurate estimation. Here we propose a theory as a fundamental solution for such problem by constructing auxiliary path for each real path. The states on auxiliary paths constitute canonical ensemble and share the same macroscopic properties (NVT) with the initial states of the real path. By implementing the theory in molecular dynamics simulations, we obtain a nanoscale Couette flow field with an accuracy of 0.2μm/s with relative standard error <0.1. The required number of samples is reduced by 12 orders compared to conventional method. The predicted thermolubric behavior of water sliding on a self-assembled surface is directly validated by experiment under the same velocity. This theory only assumes the system is initially in thermal equilibrium, then driven from that equilibrium by an external perturbation. It could serve as a general approach for extracting the accurate estimate of dynamical quantities from large fluctuations to provide insights on atomic level under experimental conditions, and benefit the studies on mass transport through (biological) nanochannels and fluid film lubrication of nanometer thickness.

Метод обобщенного импеданса для расчета отражения и прохождения волны через многослойную структуру. Часть 2. Падение волны на прямоугольный барьер

On the basis of generalized impedance method the propagation of single-dimension wave in multi-layer structure which contains the rectangular-type barrier is investigated. The concept of single barrier as a slide which parameters are different from the parameters of all other slides of structure is introduced. It is investigated the variation of position of real negative single barrier along the length of structure. It is found that the entrance impedance along the length of structure is varied by periodic manner. It is found the analytical formulas which simulate the dependencies of real and imaginary parts of entrance media impedances from coordinate along the structure. It is found three basis regimes which correspond to different character of oscillations: regime №1 – precise periodicity, regime №2 – break periodicity, regime №3 – monotonous increasing. It is investigated the coefficient of reflection for all mentioned above cases. It is found that the reflection coefficient from barrier displacement is not depended. It is found the periodic character of changing of amplitude and phase of reflected wave and also reflection coefficient when the height of barrier is varied. For interpretation of observed dependencies it is proposed the model of resonance inside of barrier. It is investigated the special feature of wave propagation when the barrier has complex character. It is investigated the case when the real path of wave number of barrier medium is established constant but imaginary path of the same number is varied in wide boundaries. It is established that reflection coefficient started by zero when the imaginary part of wave number is equal to zero. When imaginary part of wave number increases the reflection coefficient smooth increases in limit goes to unit. The passing coefficient also smooth decreases but more quickly then reflection coefficient and in limit goes to zero. The absorb coefficient started by zero at first smooth increases and after reaching of maximum smooth decreases in limit goes to zero. It is investigated the case when real and imaginary paths of barrier medium wave number simultaneous increase in equally proportion. It is found that in this case on the smooth curves for coefficients ob reflection, passing and absorb it is putted the oscillations. The character of oscillations is explained in the frames of resonance model.

The Real Dilemma and Cracking Path of the Supply-Side Reform of Voluntary Universal Prekindergarten in Guangdong Province

In view of the characteristics of the development of voluntary universal prekindergarten in Guangdong Province at this stage, we analyze and refine the development of voluntary universal prekindergarten from 2010 to 2021 based on the supply-side reform perspective in terms of preschool education supply main body, financial supply, teacher supply and institutional supply respectively, and find that there are problems such as imbalance in the structure of supply main body, weak awareness of government main body, insufficient structural supply of funds, lack of stable Based on this, we propose to ensure the supply attributes, improve the system to guarantee the supply system, increase the supply motivation, improve the mechanism to guarantee the supply of funds, optimize the supply efficiency, improve the quality of the supply of teachers, improve the supply mechanism, and increase the supervision and accountability.

The motif of the way in the work of the poets of Finland in the 20th century

The path motif is one of the major dominants in the works of prominent 20thcentury poetsof Finland, both Finnish and Swedishnative speakers. Understanding life as a road is what Eino Leino shares in common with Uuno Kailas, Paavo Haavikko, Risto Ahti, Heli Laaksonen, Edith Södergran, and Ralf Nordgren. Their position coincides with the creative concepts of Alexander Blok and the ideas of pilgrimage in European literature and in Kalevalian poetry. 20th-century Finnish poetry falls into all- European line. But in Finnish poetry, the path motif has existed since the epic songs: Lemminkäinen’s escape, folklore heroes’ journey in search of a bride, and Kalevalians’ quest to recover the Sampo. Furthermore, travelers’ purposes ranged from noble and holy to everyday and mundane. In the early 20th century, Finnish neo-Romanticists, referring to the history of national culture, travelled frequently to Finnish and Russian Karelia. Since the 1920s, poets have been referring to the road image as the “holy road of calling” (Uuno Kailas) a singer has no right to turn away from. In post-World War II poetry, moving in a circle or “back and forth” (Risto Ahti) is, in any case, moving forward. The important thing is not to get stranded, not to run into a wall. The path dominant becomes deeply intertwined with the image of a home, as the path motif does with the image of time, life cycle, and biography. A real, geographical, biographical, and spiritual path become one, and on that path high is combined with low or even vile. In modern Finnish poetry, the path theme found a new life with different, sometimes not matching nuances, while still remaining relevant and arguably primary.

Scan path resolved thermal modelling of LPBF

• Laser powder bed fusion product quality depends on process and on the scan strategy. The accuracy by which a feature outline is printed defines the surface finish, workpiece fatigue behavior and the extent of post processing needed to achieve surface quality specifications. In this paper we develop a semi-analytic thermal model allowing the resolution of the scan strategy in detail while solving the energy equation to predict the thermal history of the printed component and its features. Experiments are performed using process parameters that have been shown to achieve an IN718 relative density larger than 99.5%. We study the influence of scan strategies on different features’ surface quality while keeping the process parameters unchanged. The model is driven by the build file provided to the 3D printer or using the more accurate in-situ process data describing the laser path and status. The model is verified using high-fidelity modes as well as experimental results. We demonstrate both experimentally and numerically how the printer controller changes the build strategy, slightly affecting the quality of fine features. Taking the real scan path into account, different scan strategies are studied. Laser powder bed fusion product quality depends on process parameters (e.g. laser power, scan speed, etc.) and on the scan strategy. The accuracy by which a feature outline is printed defines the surface finish, workpiece fatigue behavior and the extent of post processing needed to achieve surface quality specifications. In this paper we develop a semi-analytic thermal model allowing the resolution of the scan strategy in detail while solving the energy equation to predict the thermal history of the printed component and its features. Experiments are performed using process parameters that have been shown to achieve an IN718 relative density larger than 99.5%. We study the influence of scan strategies on different features’ surface quality while keeping the process parameters unchanged. The model is driven by the build file provided to the 3D printer or using the more accurate in-situ process data describing the laser path and status. The model is verified using high-fidelity models as well as experimental results. We demonstrate both experimentally and numerically how the printer controller changes the build strategy, slightly affecting the quality of fine features. Laser scan dynamics and timing, particularly sky-writing, was shown to have a critical effect on the melt pool morphology and necessary to include in the models.

Improving Path Accuracy of Mobile Robots in Uncertain Environments by Adapted Bézier Curves

An algorithm that presents the best possible approximation for the theoretical Bézier curve and the real path on which a mobile robot moves in a dynamic environment with mobile obstacles and boundaries is introduced in this paper. The algorithm is tested on a set of scenarios that comprehensively cover critical situations of obstacle avoidance. The selection of scenarios is made by deploying robot navigation performances into constraints and further into descriptive characteristics of the scenarios. Computer-simulated environments are created with dedicated tools (i.e., Gazebo) and modeling and programming technologies (i.e., Robot Operating System (ROS) and Python). It is shown that the proposed algorithm improves the performance of the path for robot navigation in a highly dynamic environment, with dense mobile obstacles.

An efficient blockchain‐based privacy‐preserving scheme with attribute and homomorphic encryption

As a distributed ledger technology, blockchain has excellent openness and transparency, which can provide data security management services for distributed intelligent systems and establish effective security guarantee mechanisms. However, precisely due to the open nature of blockchain, malicious users can trace the real transaction transfer path with high probability and even obtain the real identity of users by collecting transaction information on the blockchain and performing data analysis. Besides, existing intelligent systems lack effective encryption or desensitization measures, and attackers are able to access data in intelligent systems through identity forgery and other means, posing a huge potential risk to user privacy. To alleviate the above security issues, this paper proposes an efficient blockchain-based privacy-preserving scheme with attribute and homomorphic encryption, which can not only achieve user-level fine-grained secure access control but also supports the transmission and verification of blockchain data in the form of ciphertext. The access control method based on attribute-based encryption and the data transmission method based on homomorphic encryption are proposed, and the blockchain-based access whitelist mechanism is designed to reduce the resource loss due to repeated authentication. Simulation calculations and blockchain performance experiments show that this scheme can develop flexible access policies according to the attributes of users, has good performance in computational efficiency, and the blockchain performance test results are stable with errors in milliseconds for all operations. It has certain application potential in the field of distributed intelligent systems and blockchain.

Dynamic cognitive maps for robot route planning in complex workplaces represented by abstract mazes

Adaptive path planning and optimization for robots are a persistent challenge due to the lack of a cognitive map of the complex and dynamic environments. This paper presents a cognitive-map-based method for dynamic robot path planning by a formal maze model for workplace layouts representation. The maze model and global path trees provide a cognitive map for the robot to aware the environment. A theory of dynamic Paths Finding and Optimization (PFO) is developed. Powered by the PFO algorithm, a robot is able to autonomously explore the optimal path in a complex workplace by a single sight-read of its layout. The maze based PFO methodology provides robot for an efficient real time path cognition and optimization algorithm for dealing with dynamic workplaces. A set of experiments demonstrates the efficiency of the method, which extends traditional stepwise robot vision technologies to cognitive-map-driven global path optimization.

An interpretable knowledge-based decision support method for ship collision avoidance using AIS data

AIS data include ship spatial-temporal and motion parameters which can be used to excavate the deep-seated information. In this article, an interpretable knowledge-based decision support method is established to guide the ship to make collision avoidance decisions with good seamanship and ordinary practice of seamen using AIS data. First, AIS data is preprocessed and trajectory reconstructed to restore the ship historical navigation state, and a ship encounter identification model is constructed according to the encounter characteristics; Second, a two-stage collision avoidance behavior extraction algorithm is formed to build a behavior knowledge base, and the scenario similarity model is constructed to measure and match similar scenarios based on ship position, motion tendency and collision risk. Then, the Delaunay Triangulation Network is used to fuse ship trajectories of similar scenario to form the collision avoidance path. Finally, a case study is performed using the real AIS data outside Ningbo-Zhoushan Port waters, China, and the effectiveness of the planned path is verified by setting the head-on and crossing situations and comparison between the planned and real paths. Results indicate that the proposed model can extract the ship collision avoidance behavior accurately, and the planned path can ensure navigation safety.

An improved fault model of wind turbine gear drive under multi-stage cracks

Considering the real crack propagation paths using the fracture mechanics theory, a novel simulation dynamic model for the two-stage cracked gear drive of the wind turbine is established. The mesh characteristics (time-varying mesh stiffness, contact stress) are obtained with the finite element method. The mesh stiffness under the single-stage and multi-stage cracks is imported into the two-stage cracked gear drive dynamic model to solve the dynamics. The results of the simulation and experiment are performed to verify the proposed dynamic model. The dynamic characteristics and statistical indicators under different cracks are discussed. The results reveal that the crack has a significant influence on the mesh stiffness of the single-tooth contact zone. A rotating periodic impact is found on the time-domain response for the cracked gear drive. Under the single-stage crack, the components of rotating sideband frequencies also appear in the other-stage healthy gear drive. The gear acceleration amplitudes under the multi-cracks are larger than that under the single-stage crack. Therefore, the single-stage crack has an influence on the other-stage gear in the coupling system. This developed result can be applied well to vibration measurement and fault diagnosis.

A Hypothetical Modelling and Experimental Design for Measuring Foraging Strategies of Animals.

Based on animal long-term and short-term memory radial foraging techniques (or LMRFT and SMRFT), we devise a modelling approach that could capture the foraging behaviours of animals. In this modelling, LMRFT-based optimal foraging paths and SMRFT-based ones are constructed with respect to different levels of foraging strategies. Then, by a devised structural metric, we calculate the structural distance between these modelled optimal paths and the hypothetical real foraging paths taken by agents. We sample 20 foods positions via a chosen bivariate normal distribution for three agents. Then, we calculate their Euclidean distance matrix and their ranked matrix. Using LMRFT-based or SMRFT-based optimal foraging strategies, the optimal foraging paths are created. Then, foraging strategies are identified using optimal parameter learning techniques. Our results, based on the simulated foraging data, show that LMRFT-based foraging strategies for agent 1,2 and 3 are 3, 2 and 5, i.e., agent 3 is the most intelligent one among the three in terms of radial level. However, from the SMRFT-based perspective of strategies, their optimal foraging strategies are 5,5 and 2, respectively, i.e., agent 1 is as intelligent as agent 2 and both of them have better SMRFT-based foraging strategies than agent 3.

RNN-Based Demodulation Framework for Spectrum Narrowing in Ultra-Dense WDM Networks

To cope with the continuous traffic growth, spectral efficiency needs to be enhanced. Ultra-dense WDM systems, where narrower guard-bands are inserted between wavelength-division-multiplexed (WDM) signals than those used in conventional dense WDM (DWDM) systems, are expected to offer higher spectral efficiency. However, such systems are hindered by the spectrum narrowing induced by wavelength selective switches (WSSs) at nodes. As a result, intersymbol interference (ISI) can be excessive. Linear digital filters widely used in typical digital coherent receivers can equalize the ISI. However, ISI equalization yields noise enhancement due to the interaction between ISI and amplifier noise. Sequence estimation can alleviate the impact of this interaction; however, to introduce sequence estimation into real systems, an ISI-imposing filter is needed because the adaptive filter used for polarization recovery automatically equalizes the ISI. Although the optimum ISI-imposing filter can be created with the proper spectrum model, its characteristics change frequently in real optical path networks. Therefore, we need to develop a demodulation framework that does not necessitate any spectrum models. In this letter, we propose a novel demodulation framework that uses a recurrent neural network (RNN) to simultaneously realize the ISI-imposing filter and sequence estimator. Extensive computer simulations show that our proposal increases the transmission distance in ultra-dense WDM networks.

Machine learning the real discriminant locus

Parameterized systems of polynomial equations arise in many applications in science and engineering with the real solutions describing, for example, equilibria of a dynamical system, linkages satisfying design constraints, and scene reconstruction in computer vision. Since different parameter values can have a different number of real solutions, the parameter space is decomposed into regions whose boundary forms the real discriminant locus. This article views locating the real discriminant locus as a supervised classification problem in machine learning where the goal is to determine classification boundaries over the parameter space, with the classes being the number of real solutions. This article presents a novel sampling method which carefully samples a multidimensional parameter space. At each sample point, homotopy continuation is used to obtain the number of real solutions to the corresponding polynomial system. Machine learning techniques including nearest neighbors, support vector classifiers, and neural networks are used to efficiently approximate the real discriminant locus. One application of having learned the real discriminant locus is to develop a real homotopy method that only tracks real solution paths unlike traditional methods which track all complex solution paths. Examples show that the proposed approach can efficiently approximate complicated solution boundaries such as those arising from the equilibria of the N=4 Kuramoto model which was previously intractable using traditional methods.

Directions of high cycle fatigue cracks emanating from circular notches studied by optical profilometry

Current models for predicting the fatigue endurance of notched solids use the stresses along a straight line, beginning at the notch root, as a simplification of the real crack propagation path. In this work, the experimental crack paths for hollow notched samples were analysed through different microscopy techniques, with the objective of establishing high cycle fatigue crack growth directions in a mild steel. Fully reversed tension–compression fatigue tests (R=−1) of thin-walled tube specimens with a passing-through hole were carried out. The crack paths observed in the outer cylindrical surface were studied in each case, with special attention to the crack initiation point and the crack direction along the first grains. Moreover, the analysis of the fracture surfaces allowed the same analysis to be performed to determine the internal crack paths. It was observed that the crack initiation point was close to the maximum principal stress point at the hole contour as obtained from linear elastic finite element analysis, and the crack direction in its initiation was generally close to Mode I direction, contrary to the conventionally accepted 45∘ crack growth direction.

Reshaping Local Path Planner

This letter proposes a path planner that reshapes a global path locally in response to sensor-based observations of obstacles in the environment. Two fundamental concepts enable the resultant algorithm (a) a path-following <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">synthetic vehicle</i> whose steering actions are non-myopically optimized to result in a smooth traversible path that meets path curvature constraints, and (b) a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">path-aware</i> turning moment-field that enables obstacle avoidance while eluding the typical local-minimum-induced stagnation associated with potential field methods. The use of the combination of the two concepts results in a reduced action space over which optimization needs to be performed towards minimizing the path deviation subject to obstacle avoidance, and thus results in an efficient algorithm that can be implemented online. We demonstrate the algorithm in simulations as well as in field experiments, performing real time local path planning and obstacle avoidance on two different vehicle platforms (an ackerman steering vehicle two-axled vehicle, and a differential-steering 4-axled vehicle) in an unstructured off-road terrain.

Paso a paso se va muy lejos: Traveling the Path with AFS

<i>Paso a paso se va muy lejos</i>: Traveling the Path with AFS

Finite Difference Pre-Stack Depth Migration of One-Way Wave Equation in Isotropic Visco-Acoustic Media of a Ray-Centered Coordinate System

In seismic exploration, obtaining accurate bandwidth of the reflected signal is essential for determining seismic resolution. A portion of the stored energy is attenuated during signal propagation, narrowing the received seismic signal bandwidth. Therefore, compensating the energy attenuation is important for improving the seismic resolution. The current method of compensating absorption and attenuation based on a single channel can only compensate the post-stack data (self-exciting and self-receiving), whereas in practice, seismic waves do not propagate along the self-exciting and self-receiving seismic wave path; the propagation path is complex. The absorption and attenuation depend on the propagation path. The primary methods used for Q-compensation along the propagation paths are one-way wave extrapolation in the Cartesian coordinate system and Gaussian beam Q-compensation migration in the ray-centered coordinate system. However, the large angle limits the one-way wave method, and the Gaussian beam method refers to the high-frequency approximation solution of the two-way wave equation. Therefore, a 15-degree equation in the ray-centered coordinate system is proposed. Seismic waves extrapolate along the ray, which compensates the absorption and attenuation along the real propagation path. The 15-degree equation in the ray-centered coordinate system does not perform high-frequency approximation in the ray beam and has no large angle limit, facilitating the accurate description of local wavefields in the ray beam.

Improved JPS Path Optimization for Mobile Robots Based on Angle-Propagation Theta* Algorithm

The Jump Point Search (JPS) algorithm ignores the possibility of any-angle walking, so the paths found by the JPS algorithm under the discrete grid map still have a gap with the real paths. To address the above problems, this paper improves the path optimization strategy of the JPS algorithm by combining the viewable angle of the Angle-Propagation Theta* (AP Theta*) algorithm, and it proposes the AP-JPS algorithm based on an any-angle pathfinding strategy. First, based on the JPS algorithm, this paper proposes a vision triangle judgment method to optimize the generated path by selecting the successor search point. Secondly, the idea of the node viewable angle in the AP Theta* algorithm is introduced to modify the line of sight (LOS) reachability detection between two nodes. Finally, the paths are optimized using a seventh-order polynomial based on minimum snap, so that the AP-JPS algorithm generates paths that better match the actual robot motion. The feasibility and effectiveness of this method are proved by simulation experiments and comparison with other algorithms. The results show that the path planning algorithm in this paper obtains paths with good smoothness in environments with different obstacle densities and different map sizes. In the algorithm comparison experiments, it can be seen that the AP-JPS algorithm reduces the path by 1.61–4.68% and the total turning angle of the path by 58.71–84.67% compared with the JPS algorithm. The AP-JPS algorithm reduces the computing time by 98.59–99.22% compared with the AP-Theta* algorithm.

ANN-based LoRaWAN Channel Propagation Model

LoRaWAN wireless communication channels are often impacted by noise and interference over long-range causing loss of a received signal. One of the main drawbacks of using existing propagation models is less accurate as these models in designing the communication link are tailored to simplify the estimation. In this paper, an artificial intelligent real time path loss model is proposed. It is capable of processing complex variables over a short period of time. Providing it with enough data, the model is able to learn channel behavior and predict the path loss accurately. Results of the model are benchmarked against classical statistical curve fitting models where RMSE values are also compared and indicating that the artificial intelligent model has better accurate prediction.

Investigation of the fatigue crack growth behavior of S355 steel weldments of motor hangers of high-speed trains

The behavior of fatigue cracks in welded details of motor hangers is investigated through crack growth numerical simulation under constant amplitude loading. The fatigue crack growth rate (FCGR) parameters of S355J2W steel are measured. FCGR tests are conducted on compact tension (CT) specimens. FCGR increases as the stress ratio increasing. Test data are compared with the reference curve of standards IIW and BS7910. Crack growth calculating results under mode I and mixed-modes conditions are compared. The crack growth path by simulation is in good agreement with the real crack path. The results also revealed that, even though fatigue cracks in the motor hanger are usually caused by mixed-modes conditions, mode I still governs the propagation.