浅谈小学语文学科渗透法制教育策略

国家《中小学法制教育指导纲要》明确提出要充分发挥课堂主渠道作用,将学科教学渗透法制教育作为对学生实施法制教 育的主要途径,要求法制教育要有机渗透在学校教育的各门学科、各个教学环节之中。现行小学语文教材中涉及法制教育的素材很多 , 是渗透法制教育的最佳途径。小学语文教师要充分、合理、科学地挖掘语文课程中的法制教育资源,在识字写字、阅读、口语交际、 写作等教学环节中有效进行法制教育和德育渗透,提高学生的法制观念和明辨是非能力,使他们成为学法、知法、守法的合格小公民。

谈谈在我国中小学推行校本管理的几点策略

在我国中小学校 ,逐步试验、推广校本管理模式 ,能从根本上促进教育生产力的向前发展 ,能普遍提高学校管理的效率。本文试从法制、社会、民主三个方面的策略上 。

农村“三产融合”视阈下数字经济发展的法制思考

数字技术能促使信息迅速的在一二三产业中传递和交换,其带来的经济效应有效地贯通了农村一二三产业的分界,对推动农村一二三产业融合大有裨益,是未来必然的发展趋势。通过对杭州、广州、珠海、重庆四市农村“三产融合”中的数字经济实践比较考察发现,当前在农村“三产融合”中数字经济仍主要体现为电商经济,少部分则以科技赋能,发展以人工智能为主线的多要素产业园经济,然而目前关于农村产业数字经济的法律讨论暂且较少,故而应当从法律层面健全完善农村“三产融合”中发展数字经济的相关制度保障。

Dynamic modelling of 2-DOF luffing mechanism with serial closed kinematic chains

Luffing mechanism is a key component of the construction machinery.This paper proposes a two degree of freedom(2-DOF)luffing mechanism,which has one more pair of driving cylinders than the single DOF luffing mechanism,to improve the performance of the machinery.To establish the dynamic model of the 2-DOF luffing mechanism,firstly,we develop a hierarchical method to deduce the Jacobian matrix and Hessian matrix for obtaining the kinematics equations.Subsequently,we divide the luffing mechanism into six bodies considering actuators,and deduce the kinetic equations of each body by the Newton-Euler method.Based on the dynamic model,we simulate the luffing process.Finally,a prototype is built on a pile driver to validate the model.Simulations and experiments show that the dynamic model can reflect the dynamic properties of the proposed luffing mechanism.And the control strategy that the front cylinders retract first shows better mechanical behavior than the other two control strategies.This research provides a reference for the design and application of 2-DOF luffing mechanism on construction machinery.The modeling approach can also be applied to similar mechanism with serial closed kinematic chains,which allows to calculate the dynamic parameters easily and exactly.

Active Control of Structurally Radiated Sound from an Elastic Cylindrical Shell

A numerical and experimental study was presented on active control of structurally radiated sound from an elastic cylindrical shell.An analytical model was developed for the active structural acoustic control (ASAC) of the cylindrical shell.Both global and local control strategies were considered.The optimal control forces corresponding to each control strategy were obtained by using the linear quadratic optimal control theory.Numerical simulations were performed to examine and analyze the control performance under different control strategies.The results show that global sound attenuation of the cylindrical shell at resonance frequencies can be achieved by using point force as the control input of the ASAC system.Better control performance can be obtained under the control strategy of minimization of the radiated sound power.However,control spillover may occur at off-resonance frequencies with the control strategy of structural kinetic energy minimization in terms of the radiated sound power.Considerable levels of global sound attenuation can also be achieved in the on-resonance cases with the local control strategy,i.e.,minimization of the mean-square velocity of finite discrete locations.An ASAC experiment using an FXLMS algorithm was implemented,agreement was observed between the numerical and experimental results,and successful attenuation of structural vibration and radiated sound was achieved.

Leg compliance control of a hexapod robot based on improved adaptive control in different environments

Considering the compliance control problem of a hexapod robot under different environments, a control strategy based on the improved adaptive control algorithm is proposed. The model of robot structure and impedance control is established. Then, the indirect adaptive control algorithm is derived. Through the analysis of its parameters, it can be noticed that the algorithm does not meet the requirements of the robot compliance control in a complex environment. Therefore, the fuzzy control algorithm is used to adjust the adaptive control parameters. The satisfied system response can be obtained based on the adjustment in real time according to the error between input and output. Comparative experiments and analysis of traditional adaptive control and the improved adaptive control algorithm are presented. It can be verified that not only desired contact force can be reached quickly in different environments, but also smaller contact impact and sliding avoidance are guaranteed, which means that the control strategy has great significance to enhance the adaptability of the hexapod robot.

Diagrams Produced by Secondary Students in Multiplicative Comparison Word Problems

We investigated the use of diagrams in multiplicative comparison word problems. The diagrams have been considered as one of the effective heuristic strategies or solving math problems. However, how students use during their school and the degree development that shows in their performance when applied to specific fields of knowledge is a task to be elucidated. We place our study in the school stage in which it makes the transition from arithmetic to algebra and arithmetic problems we focus on in the underlying multiplicative comparison scheme. In this paper, we analyzed the responses of high school students to the translation of multiplicative comparison word problems to representation graphs. We have used the responses of 12 -14 year old students （freshman year of secondary school） to represent multiplicative comparison word problems to identify and categorize the students responses, which allowed us identify categories for each type of representation and hypothesize priority order and subordination between the categories. Results show that students are not familiar with building diagrams that integrate existing relations in word problems. Most of the students do not use all the quantitative information contained in the word problem, therefore draw diagrams referring to the subject or context of the problem without relating to the data in it. We describe in detail the quantitative diagram types produced by these students. We have identified four kinds of quantitative diagrams that the students used to represent the multiplicative comparison problems with inconsistent statements, and these diagrams correspond to the four strategies for tackling the construction of the diagram.

Decoupling control and zero dynamics stabilization for shunt hybrid active power filter

An inverse system method based optimal control strategy was proposed for the shunt hybrid active power filter （SHAPF） to enhance its harmonic elimination performance. Based on the inverse system method, the d-axis and q-axis current dynamics of the SHAPF system were decoupled and linearized into two pseudolinear subsystems. Then, an optimal feedback controUer was designed for the pseudolinear system, and the stability condition of the resulting zero dynamics was presented. Under the control strategy, the current dynamics can asymptotically converge to their reference states and the zero dynamics can be bounded. Simulation results show that the proposed control strategy is robust against load variations and system parameter mismatches, its steady-state performance is better than that of the traditional linear control strategy.

OpenMP-based parallel transient stability simulation for large-scale power systems

This paper provides an OpenMP-based parallel Very Dishonest Newton(VDHN) algorithm with variable step size,running transient stability simulations(TSA) on multi-core computers.Under the framework of simultaneous solution method of TSA,the step-size control strategy is used according to the local truncation error theory firstly.Then,computation of the generation units,which is the most time-consuming part of the simulation,is dynamically dispatched to several cores using an α dynamic scheduling scheme to obtain workload balancing based on OpenMP.Due to the convergence of Newton-type iterations,an adaptive Jacobian update control strategy is applied to reduce the sequential part of the simulation and the overhead generated by OpenMP.Several large scale test cases verify the validity and practicability of the proposed parallel algorithm,showing that the proposed approach achieves high speed-up and a considerable reduction in parallel overheads.

Theoretical research on reservoir closed-loop production management

Closed-loop production management combines the process of history matching and production optimization together to peri-odically updates the reservoir model and determine the optimal control strategy for production development to realize the goal of decreasing the knowledge of model uncertainty as well as maximize the economic benefits for the expected reservoir life. The adjoint-gradient-based methods seem to be the most efficient algorithms for closed-loop management. Due to complicated calculation and limited availability of adjoint-gradient in commercial reservoir simulators, the application of this method is still prohibited for real fields. In this paper, a simultaneous perturbation stochastic approximation (SPSA) algorithm is proposed for reservoir closed-loop production management with the combination of a parameterization way for history matching and a co-variance matrix to smooth well controls for production optimization. By using a set of unconditional realizations, the proposed parameterization method can transform the minimization of the objective function in history matching from a higher dimension to a lower dimension, which is quite useful for large scale history matching problem. Then the SPSA algorithm minimizes the objective function iteratively to get an optimal estimate reservoir model. Based on a prior covariance matrix for production op-timization, the SPSA algorithm generates a smooth stochastic search direction which is always uphill and has a certain time correlation for well controls. The example application shows that the SPSA algorithm for closed-loop production management can decrease the geological uncertainty and provide a reasonable estimate reservoir model without the calculation of the ad-joint-gradient. Meanwhile, the well controls optimized by the alternative SPSA algorithm are fairly smooth and significantly improve the effect of waterflooding with a higher NPV and a better sweep efficiency than the reactive control strategy.

GLOBALLY ASYMPTOTICALLY STABLE FORMATION CONTROL OF THREE AGENTS

This paper considers the formatiomshape control of three agents in the plane. By adding an adaptive perturbation to any agent＇s movement direction, a novel control strategy is proposed. It is shown that the proposed novel control law can not only guarantee the global asymptotical stability of the desired formation shape, but also ensure the collision avoidance of agents between each other. Simulation results are provided to illustrate the effectiveness of the control algorithm.

Fuzzy energy management strategy for parallel HEV based on pigeon-inspired optimization algorithm

Improvements in fuel consumption and emissions of hybrid electric vehicle(HEV)heavily depend upon an efficient energy management strategy(EMS).This paper presents an optimizing fuzzy control strategy of parallel hybrid electric vehicle em-

A novel policy iteration based deterministic Q-learning for discrete-time nonlinear systems

In this paper, a novel iterative Q-learning algorithm, called "policy iteration based deterministic Qlearning algorithm", is developed to solve the optimal control problems for discrete-time deterministic nonlinear systems. The idea is to use an iterative adaptive dynamic programming(ADP) technique to construct the iterative control law which optimizes the iterative Q function. When the optimal Q function is obtained, the optimal control law can be achieved by directly minimizing the optimal Q function, where the mathematical model of the system is not necessary. Convergence property is analyzed to show that the iterative Q function is monotonically non-increasing and converges to the solution of the optimality equation. It is also proven that any of the iterative control laws is a stable control law. Neural networks are employed to implement the policy iteration based deterministic Q-learning algorithm, by approximating the iterative Q function and the iterative control law, respectively. Finally, two simulation examples are presented to illustrate the performance of the developed algorithm.

New strategy for virus discovery:viruses identified in human feces in the last decade

Emerging and re-emerging viruses continue to surface all over the world.Some of these viruses have the potential for rapid and global spread with high morbidity and mortality,such as the SARS coronavirus outbreak.It is extremely urgent and important to identify a novel virus near-instantaneously to develop an active preventive and/or control strategy.As a cultureindependent approach,viral metagenomics has been widely used to investigate highly divergent and completely new viruses in humans,animals,and even environmental samples in the past decade.A new model of Koch's postulates,named the metagenomic Koch's postulates,has provided guidance for the study of the pathogenicity of novel viruses.This review explains the viral metagenomics strategy for virus discovery and describes viruses discovered in human feces in the past 10 years using this approach.This review also addresses issues related to the metagenomic Koch's postulates and the challenges for virus discovery in the future.

Optimal Design for a Retrial Queueing System with State-Dependent Service Rate

This paper considers a single server retrial queue in which a state-dependent service policy is adopted to control the service rate. Customers arrive in the system according to a Poisson process and the service times and inter-retrial times are all exponentially distributed. If the number of customers in orbit is equal to or less than a certain threshold, the service rate is set in a low value and it also can be switched to a high value once this number exceeds the threshold. The stationary distribution and two performance measures are obtained through the partial generating functions. It is shown that this state-dependent service policy degenerates into a classic retrial queueing system without control policy under some conditions. In order to achieve the social optimal strategies, a new reward-cost function is established and the global numerical solutions, obtained by Canonical Particle Swarm Optimization algorithm, demonstrate that the managers can get more benefits if applying this state-dependent service policy compared with the classic model.