“手绘+故事化+情境化+问题化”手绘式微课设计与创作

手绘是一种平民化的、简明高效的微课制作技术,非常适合一线教师使用。目前部分手绘式微课作品存在平铺直叙、逻辑结构不清晰、忽视问题引导、缺少吸引力等问题。针对这些问题,文章提出了"手绘+故事化+情境化+问题化"的手绘式微课设计模式,在阐述其内涵和制作要点的基础上,提出了四条提升手绘式微课创作质量的对策:明确手绘式微课的适用范围,掌握手绘SVG图片素材获取途径,注重逻辑与呈现,选择合适的制作工具和软件。

问题化教学设计与学生高级思维技能的培养

随着时代的发展,教育教学改革的不断深化,社会亟需全面发展的高素质人才,而具有高级思维技能是高素质人才的一个重要体现。培养学习者的高级思维技能已经越来越受到教育工作者的重视。在阐述高级思维技能的基础上,介绍了几种以发展学生高级思维技能为目标的问题化教学设计方式。

浅谈问题化教学设计在生物学探究课上的应用——以绿色植物通过光合作用制造有机物为例

本文以＂绿色植物通过光合作用制造有机物＂为例,探讨如何将问题化教学设计应用于生物学探究课上。阐述了教师如何设计有效问题来引导学生高效并自主的学习、探究,以达到变被动为主动学习、开发智力、活跃思维的目的,以激发学生的学习兴趣。

网络课程中“问”的设计及运用——以《广府新探》为例

"问"是一种方式方法,是一种策略,更是一种态度。《广府新探》网络课程借鉴并运用问题化教学设计的理念进行课程设计,在"问"的设计思路上把握了两个方面,一是把握"问"的原则,包括:目标性原则、支架性原则、启发性原则和动态性原则等;二是在"问"的形式、结构和内涵上把握"问"的策略。"问"在网络课程中运用于互动关系的构建,也运用于课程内容的动态发展。

Intel未来教育理念下的《现代教育技术学》课程教学探索——以洛阳师范学院为例

《现代教育技术》课程是对师范类学生培养教学技能的重要课程之一,一直以来都被列为师范学生的必选课程.本文以洛阳师范学院为例,视野聚焦在师范生教育平台课程中的《现代教育技术》课程.分析了该课程目前的教学现状,存在的不足,在Intel未来教育理念下尝试探索解决问题的办法.通过对INTEL未来教育项目的介绍和特点分析,对现代教育技术课程和INTEL未来教育进行结合的优势以及可行性进行了阐述.并通过在实际教学环节中的实践对二者结合以后的教学效果进行了检验,整理出教学效果的变化对比和存在的不足以及如何进一步完善教学的合理化建议.

A hybrid cuckoo search algorithm with feasibility-based rule for constrained structural optimization

Constrained optimization problems are very important as they are encountered in many science and engineering applications.As a novel evolutionary computation technique,cuckoo search(CS) algorithm has attracted much attention and wide applications,owing to its easy implementation and quick convergence.A hybrid cuckoo pattern search algorithm(HCPS) with feasibility-based rule is proposed for solving constrained numerical and engineering design optimization problems.This algorithm can combine the stochastic exploration of the cuckoo search algorithm and the exploitation capability of the pattern search method.Simulation and comparisons based on several well-known benchmark test functions and structural design optimization problems demonstrate the effectiveness,efficiency and robustness of the proposed HCPS algorithm.

Hybridizing artificial bee colony with biogeography-based optimization for constrained mechanical design problems

A novel hybrid algorithm named ABC-BBO, which integrates artificial bee colony(ABC) algorithm with biogeography-based optimization(BBO) algorithm, is proposed to solve constrained mechanical design problems. ABC-BBO combined the exploration of ABC algorithm with the exploitation of BBO algorithm effectively, and hence it can generate the promising candidate individuals. The proposed hybrid algorithm speeds up the convergence and improves the algorithm's performance. Several benchmark test functions and mechanical design problems are applied to verifying the effects of these improvements and it is demonstrated that the performance of this proposed ABC-BBO is superior to or at least highly competitive with other population-based optimization approaches.

The Design and Control of Distillation Column with Side Reactors for Chlorobenzene Production

The distillation column with side reactors (SRC) can overcome the temperature/pressure mismatch in the traditional reactive distillation, the column operates at temperature/pressure favorable for vapor-liquid separation, while the reactors operate at temperatures/pressures favorable for reaction kinetics. According to the smooth operation and automatic control problem of the distillation column with side reactors (SRC), the design, simulation calculation and dynamic control of the SCR process for chlorobenzene production are discussed in the paper. Firstly, the mechanism models, the integrated structure optimal design and process simulation systems are established, respectively. And then multivariable control schemes are designed, the controllability of SRC process based on the optimal steady-state integrated structure is explored. The dynamic response performances of closed-loop system against several disturbances are discussed to verify the effectiveness of control schemes for the SRC process. The simulating results show that the control structure using conventional control strategies can effectively overcome feeding disturbances in a specific range.

Optimization design of deep lean-ore mining and safety evaluation

In order to settle the mining optimization design and safety problem of the above 1 150 m pillar of No.1 ore-body in No.H Mining Jinchuan, the lean-ore above 1 250 m, the 1 150 m horizontal pillar and the ore-body below 1 100 m regarded as research objects based on the original design project, and nine calculation schemes on different mining sequence and different fill body strength were put forward based on cement-sand ratio of 1 ： 4, 1： 12 and 1 ： 24. Calculation parameters were got by the back analysis method of field monitoring data, and the FLAC2D program was applied to compute for these schemes, stress and displacement of ground settlement, shaft and stope roof were analyzed, and some conclusions were got. Results show that the intensity of filling body and the mining technique have very important effect on controlling settlement and stability of surrounding rock; Developing of lean ore have some influences to the 16th return air filling shaft, especially for 1 500--1 400 m of the shaft; The best project is the first project. This research supply some technique references and safety appraisals for the mining of lean-ore of No.II Mining Jinchuan.

Optimal Seat Suspension Design Using Genetic Algorithms

The linear seat suspension is considered due to the low cost consideration therefore, the optimal linear seat suspension design method can be used for this purpose. In this paper, the design of a passive vehicle seat suspension system was handled in the framework of linear optimization. The variance of the dynamic load resulting from the vibrating vehicle operating at a constant speed was used as the performance measure of a suspension system. Using 4-DOF human body model developed by Abbas et al., with linear seat suspension and coupled with half car model. A genetic algorithm is applied to solve the linear optimization problem. The optimal design parameters of the seat suspension systems obtained are kse = 3 012.5 N/m and cse = 1 210.4 N.s/m, respectively.

Simultaneous optimization of transit network and public bicycle station network

The traditional manner to design public transportation system is to sequentially design the transit network and public bicycle network. A new public transportation system design problem that simultaneously considers both bus network design and public bicycle network design is proposed. The chemical reaction optimization(CRO) is designed to solve the problem. A shortcoming of CRO is that, when the two-molecule collisions take place, the molecules are randomly picked from the container.Hence, we improve CRO by employing different mating strategies. The computational results confirm the benefits of the mating strategies. Numerical experiments are conducted on the Sioux-Falls network. A comparison with the traditional sequential modeling framework indicates that the proposed approach has a better performance and is more robust. The practical applicability of the approach is proved by employing a real size network.

Optimum Determination of Partial Transmission Ratios of Three-Step Helical Gearboxes for Getting Minimum Cross Section Dimension

This paper presents a new study on optimum calculation of partial ratios of three-step helical gearboxes. The chosen objective function is the cross section dimension of the gearbox. In solving the optimization problem, the design equation for pitting resistance of a gear set was investigated and equations on moment equilibrium condition of a mechanic system including three gear units and their regular resistance condition are analyses. From the results of the study, effective formula for determination of the partial ratios of three-step helical gearboxes is introduced. As the formulas are explicit, the partial ratios can be calculated accurately and simply.

An Integrated Approach for Decision Support through Multi-objective Optimization with Application to an Ill-posed Design Problem

In the current scenario of global competition and short product life cycles, customer-defined satisfaction has attracted interest in artifact design. Accordingly, intelligent decision-making through multi-objective optimization has been proposed as an efficient method for human-centered manufacturing. However, previous vast researches on optimization have been mainly focused on optimization theory and optimization techniques and paid little interests on the process of problem formulation itself. In this paper, therefore, the authors present a total framework for supporting multi-objective decision making. Then, the authors try to solve the formulated multi-objective optimization problem that involves both qualitative and quantitative performance measures as a general consequence from the above procedure. Taking especially quality as a qualitative measure, the authors gave a new idea to evaluate the quality quantitatively. Additionally, to facilitate the portability of the proposed method in multidisciplinary decision-making environments, the authors implement the proposal algorithm in an Excel spreadsheet and validate the effectiveness of the approach through a case study.

Enhancements of Genetic Algorithm for Minimum Cost Design of Steel Frames Considering Fabrication Cost

A discrete optimization problem for minimizing the sum of fabrication cost and steel material cost of sf^el frames under constraints based on Japanese seismic code is set up. Enhancements of the genetic algorithm for the above-mentioned problem are proposed, which are combined with a 1D （one-dimensional） search or a 2D （two-dimensional） search. After the proposed methods are described, they are applied to a five-story frame. A comparison with an exact solution obtained by a revised enumeration algorithm demonstrates the effectiveness of the proposed methods.

Integration of axiomatic design and theory of inventive problem solving for conceptual design

Axiomatic design (AD) and theory of inventive problem solving (TRIZ) are widely used in conceptual design. Both of them have limitations, however. We presented an integrated model of these two methods to increase the efficiency and quality of the problem solving process for conceptual design. AD is used for systematically defining and structuring a problem into a hierarchy. Sometimes, the design matrix is coupled in AD which indicates the functional requirements are coupled. TRIZ separation principles can be used to separate non-independent design parameters, which provide innovative solutions at each hierarchical level. We applied the integrated model to the heating and drying equipment of bitumen reproduction device. The result verifies that the integrated model can work very well in conceptual design.

Suboptimal State Feedback H2/H∞ Controller Design with Spectrum Constraint for Discrete-time Stochastic Systems

With the aid of the spectnnn techique, a new concept named-α-stabilizability （0≤α≤1） is intnxhged and its suffident and necessary canditions are also prvposed. Especially, it is identical with the asymptotically mean square stabilizability when α = 1. As an application, the suboptimal state feedback H2/H∞ controller that satisfies the additional Spectrum canstmint via solving a convex optimization problem is delt with.

Study on Spatial Characteristics of Commercial Stores

the issues on space design of commercial stores are the main social problems that people put forward to enjoy life after the development of the national market economy in recent period. Because of the restriction of space structure and brand culture, the design rules of commercial stores＇ space have made changes of times. Taking consumers as the main body, the space of commercial stores has gradually focused on humanization and characterization.

Williams-Otto Plant Control Based on Production Planning Associated to Coordinated Decentralized Optimization and Plantwide Control Techniques

Manufacturing plants are increasingly complex and integrated, requiring control systems able to identify the interactions between the various operating units. Production planning and control design of a process are tools that, if combined, bring many economic benefits to the processes since they aim to identify and maintain optimal decision operations to a system. This work uses such integration between production planning and plantwide control to propose a control system for the Williams-Otto plant from the definition of the operating optimal point for coordinated decentralized optimization, in which the original optimization problem decomposition into smaller coordinated problems ensure that the found local optimum also meets the requirements of the global system. The results for decentralized optimization are satisfactory and very similar to the global optimum problem and to the control system response proposed based on the optimal obtained. It is effective taking smooth actions, working with （economic） optimal set points （economically） of operation. The unification of production planning techniques and plantwide control techniques is an effective tool for the control system design for entire plants.

Design and optimization of low-energy transfer orbit to Mars with multi-body environment

This paper discusses the problem of design and optimization of low-energy transfer orbit with multi-body environment. A new integrative method is proposed to effectively solve the problem, in which the parameterized patched manifolds in CR3BP(circular restricted three-body problems), the shape-based method with multi-body environment, the homotopic method with multi-body environment, and the low-thrust capturing and descending algorithm with multi-body environment are all included. Firstly, the parameters describing the patched manifolds in CR3 BP are optimized until the least total absolute velocity increment has been got, including the employment of the shape-based method with multi-body environment. Secondly, the low-thrust control laws of the transfer orbit are optimized employing the homotopic method with multi-body environment that transfers the fuel optimization problem to an easier energy optimization problem. Thirdly, the low-thrust descending orbit around Mars is computed using the laws proposed in this paper. As a typical example, the Earth-Mars transfer orbit design is discussed. The results showed that the parameters describing the patched manifolds could be optimized by the DE(differential evolution) algorithm effectively; the homotopic method with multi-body environment could get the optimal value that meets the first order optimality conditions; and the low-thrust descending orbit could effectively be captured by Mars and finally become a circular parking orbit around it by the hypothesis control laws proposed in this paper. It shows that the final fuel cost is much less than the optimal transfer in the patched two-body problems. In conclusion, the method proposed in this paper could effectively solve the low-energy low-thrust optimal control problem in multi-body environment for the future deep space explorations.

A surrogate-based optimization algorithm for network design problems

Network design problems （NDPs） have long been regarded as one of the most challenging problems in the field of transportation planning due to the intrinsic non-convexity of their bi-level programming form. Furthermore, a mixture of continuous/discrete decision variables makes the mixed network design problem （MNDP） more complicated and difficult to solve. We adopt a surrogate-based optimization （SBO） framework to solve three featured categories of NDPs （continuous, discrete, and mixed-integer）. We prove that the method is asymptotically completely convergent when solving continuous NDPs, guaranteeing a global optimum with probability one through an indefinitely long run. To demonstrate the practical performance of the proposed framework, numerical examples are provided to compare SBO with some existing solving algorithms and other heuristics in the literature for NDP. The results show that SBO is one of the best algorithms in terms of both accuracy and efficiency, and it is efficient for solving large-scale problems with more than 20 decision variables. The SBO approach presented in this paper is a general algorithm of solving other optimization problems in the transportation field.