Taking science education beyond schooling

Abstract

The shape and content of science education has always been articulated from the scientist's perspective. Recently, an increasing number of science educators have recognized the serious limitations of this perspective and have proposed to define scientific literacy from societal or citizenship perspectives. In this article, I argue that these alternatives will remain as limited as their predecessors unless the very structures of schooling are called into question. Furthermore, I argue that alternatives cannot be designed at the drawing board by theoreticians, but have to be grounded in praxis, thereby providing concrete trajectories along which science education can actually change.     

What Constitutes Effective Mathematics Instruction: A Comparison of Chinese Expert and Novice Teachers’ Views

Abstract

In this study, we examined the views of 10 experts and 10 novices on effective mathematics instruction in China. We found that all the participants valued students’ mastering of mathematical knowledge and skills and their development in mathematical thinking methods and abilities. Compared with novice teachers, expert teachers emphasized the development of students’ mathematical thinking and higher order thinking abilities and properly dealing with important and difficult content points. In contrast, novice teachers were particularly concerned about the effectiveness of teachers' guidance.     

Stabilization of One‐Dimensional Schrödinger Equation with Variable Coefficient under Delayed Boundary Output Feedback

This article considers stabilization of a one‐dimensional Schrödinger equation with variable coefficient and boundary observation which suffers from an arbitrary given time delay. We design an observer and predictor to stabilize the system. The state is estimated in the time span where the observation is available, and also predicted in the time interval where the observation is not available. It is shown that the estimated state feedback stabilizes the system exponentially. A numerical simulation is presented to illustrate the effect of the stabilizing controller.     

Stability Analysis for Delayed Neural Networks with Discontinuous Neuron Activations

This paper considers a class of delayed neural networks with discontinuous neuron activations. Based on the theory of differential equations with discontinuous right‐hand sides, some novel sufficient conditions are derived that ensure the existence and global exponential stability of the equilibrium point. Moreover, by adopting the concept of convergence in measure, convergence behavior for the output is discussed. The obtained results are independent of the delay parameter and can be thought of as a generalization of previous results established for delayed neural networks with Lipschtz continuous neuron activations to the discontinuous case. Finally, we give a numerical example to illustrate the effectiveness and novelty of our results by comparing our results with those in the early literature.     

Sliding Mode Control for Swing‐Up and Stabilization of the Cart‐Pole Underactuated System

This paper uses sliding mode control to accomplish the objectives of swing‐up and stabilization of the cart‐pole underactuated system. The features of underactuated systems prohibit direct application of conventional sliding mode control for fully‐actuated systems. In this paper, we design a novel sliding mode control for the cart‐pole underactuated system so that the control goals can be achieved. In addition, by simply changing the parameters of the sliding surface, we use only one sliding mode control scheme to swing up and to stabilize the cart‐pole system. Using the sliding mode dynamics and the internal dynamics, we show that the proposed sliding mode control can swing up the cart‐pole system from the stable equilibrium and can stabilize the system to the unstable equilibrium. Our simulation results on a cart‐pole system demonstrate the feasibility of the proposed sliding mode control. The proposed control schemes, the stability analysis, and the numerical simulation provide a useful guideline for designing the sliding mode control for the cart‐pole underactuated system.     

Variable Structure Control with Chattering Reduction of a Generalized T‐S Model

In this paper, a fuzzy logic controller (FLC) based variable structure control (VSC) is presented. The main objective is to obtain an improved performance of highly non‐linear unstable systems. New functions for chattering reduction and error convergence without sacrificing invariant properties are proposed. The main feature of the proposed method is that the switching function is added as an additional fuzzy variable and will be introduced in the premise part of the fuzzy rules; together with the state variables. In this work, a tuning of the well known weighting parameters approach is proposed to optimize local and global approximation and modelling capability of the Takagi‐Sugeno (T‐S) fuzzy model to improve the choice of the performance index and minimize it. The main problem encountered is that the T‐S identification method can not be applied when the membership functions are overlapped by pairs. This in turn restricts the application of the T‐S method because this type of membership function has been widely used in control applications. The approach developed here can be considered as a generalized version of the T‐S method. An inverted pendulum mounted on a cart is chosen to evaluate the robustness, effectiveness, accuracy and remarkable performance of the proposed estimation approach in comparison with the original T‐S model. Simulation results indicate the potential, simplicity and generality of the estimation method and the robustness of the chattering reduction algorithm. In this paper, we prove that the proposed estimation algorithm converge the very fast, thereby making it very practical to use. The application of the proposed FLC‐VSC shows that both alleviation of chattering and robust performance are achieved.     

A novel artificial bee colony algorithm with Powell's method

Artificial bee colony (ABC) algorithm is a relatively new optimization technique which has been shown to be competitive to other population-based algorithms. However, there is still an insufficiency in ABC regarding its solution search equation, which is good at exploration but poor at exploitation. To address this concerning issue, we first propose a modified search equation which is applied to generate a candidate solution in the onlookers phase to improve the search ability of ABC. Further, we use the Powell's method as a local search tool to enhance the exploitation of the algorithm. The new algorithm is tested on 22 unconstrained benchmark functions and 13 constrained benchmark functions, and are compared with some other ABCs and several state-of-the-art algorithms. The comparisons show that the proposed algorithm offers the highest solution quality, fastest global convergence, and strongest robustness among all the contenders on almost all test functions.     

Stabilization of a memristor-based chaotic system by intermittent control and fuzzy processing

This paper further investigates the problem of intermittent control of a memristor-based Chua’s oscillator and presents the oscillator as the T-S fuzzy model system. Based on Lyapunov stability theory, we design an intermittent controller to guarantee the stability of the chaotic system. Simulation results are presented to verify the effectiveness of the method.     

企业数据中心规划设计

为了满足企业生产经营,IT基础设施保障核心应用系统高效可靠运行成为本企业信息化建设的重点。从企业信息化建设的未来发展需求及结合现状,分析IT基础设施规划设计目标与原则、软硬件基础设施的设计内容及使用的技术架构。