“翻转课堂”中国化:微课程问题系统化脚本设计

教学是教师基于学生问题的系统指导学生学习的实践活动,微课程的"小"精""深""透"的特点决定了其无系统性的缺点。微课程作为"翻转课堂"课前知识的学习与问题情景的铺设或激发,设计开发人员必须有意把学习目标与学习内容有机结合,利用云计算服务技术打造微课程的运行平台,将微课程承载的一个个小问题系统化、序列化、多样化、多元化、个性化,让师生能够根据自己的实际情况有选择的权利。

Application of a Derivative-Free Method with Projection Skill to Solve an Optimization Problem

Improving numerical forecasting skill in the atmospheric and oceanic sciences by solving optimization problems is an important issue. One such method is to compute the conditional nonlinear optimal perturbation(CNOP), which has been applied widely in predictability studies. In this study, the Differential Evolution(DE) algorithm, which is a derivative-free algorithm and has been applied to obtain CNOPs for exploring the uncertainty of terrestrial ecosystem processes, was employed to obtain the CNOPs for finite-dimensional optimization problems with ball constraint conditions using Burgers' equation. The aim was first to test if the CNOP calculated by the DE algorithm is similar to that computed by traditional optimization algorithms, such as the Spectral Projected Gradient(SPG2) algorithm. The second motive was to supply a possible route through which the CNOP approach can be applied in predictability studies in the atmospheric and oceanic sciences without obtaining a model adjoint system, or for optimization problems with non-differentiable cost functions. A projection skill was first explanted to the DE algorithm to calculate the CNOPs. To validate the algorithm, the SPG2 algorithm was also applied to obtain the CNOPs for the same optimization problems. The results showed that the CNOPs obtained by the DE algorithm were nearly the same as those obtained by the SPG2 algorithm in terms of their spatial distributions and nonlinear evolutions. The implication is that the DE algorithm could be employed to calculate the optimal values of optimization problems, especially for non-differentiable and nonlinear optimization problems associated with the atmospheric and oceanic sciences.

Dynamical Correction of Control Laws for Marine Ships’ Accurate Steering

The objective of this work is the analytical synthesis problem for marine vehicles autopilots design. Despite numerous known methods for a solution, the mentioned problem is very complicated due to the presence of an extensive population of certain dynamical conditions, requirements and restrictions, which must be satisfied by the appropriate choice of a steering control law. The aim of this paper is to simplify the procedure of the synthesis, providing accurate steering with desirable dynamics of the control system. The approach proposed here is based on the usage of a special unified multipurpose control law structure that allows decoupling a synthesis into simpler particular optimization problems. In particular, this structure includes a dynamical corrector to support the desirable features for the vehicle＇s motion under the action of sea wave disturbances. As a result, a specialized new method for the corrector design is proposed to provide an accurate steering or a trade-off between accurate steering and economical steering of the ship. This method guaranties a certain flexibility of the control law with respect to an actual environment of the sailing;its corresponding turning can be realized in real time onboard.

A discrete multi-swarm optimizer for radio frequency identification network scheduling

Due to the effectiveness, simple deployment and low cost, radio frequency identification （RFID） systems are used in a variety of applications to uniquely identify physical objects. The operation of RFID systems often involves a situation in which multiple readers physically located near one another may interfere with one another＇s operation. Such reader collision must be minimized to avoid the faulty or miss reads. Specifically, scheduling the colliding RFID readers to reduce the total system transaction time or response time is the challenging problem for large-scale RFID network deployment. Therefore, the aim of this work is to use a successful multi-swarm cooperative optimizer called pseo to minimize both the reader-to-reader interference and total system transaction time in RFID reader networks. The main idea of pS20 is to extend the single population PSO to the interacting multi-swarm model by constructing hierarchical interaction topology and enhanced dynamical update equations. As the RFID network scheduling model formulated in this work is a discrete problem, a binary version of PS20 algorithm is proposed. With seven discrete benchmark functions, PS20 is proved to have significantly better performance than the original PSO and a binary genetic algorithm, pS20 is then used for solving the real-world RFID network scheduling problem. Numerical results for four test cases with different scales, ranging from 30 to 200 readers, demonstrate the performance of the proposed methodology.

Hybrid Differential Evolution for Estimation of Kinetic Parameters for Biochemical Systems

Determination of the optimal model parameters for biochemical systems is a time consuming iterative process. In this study, a novel hybrid differential evolution （DE） algorithm based on the differential evolution technique and a local search strategy is developed for solving kinetic parameter estimation problems. By combining the merits of DE with Gauss-Newton method, the proposed hybrid approach employs a DE algorithm for identifying promising regions of the solution space followed by use of Gauss-Newton method to determine the optimum in the identified regions. Some well-known benchmark estimation problems are utilized to test the efficiency and the robustness of the proposed algorithm compared to other methods in literature. The comparison indicates that the present hybrid algorithm outperforms other estimation techniques in terms of the global searching ability and the con- vergence speed. Additionally, the estimation of kinetic model parameters for a feed batch fermentor is carried out to test the applicability of the proposed algorithm. The result suggests that the method can be used to estimate suitable values of model oarameters for a comolex mathematical model.

A hybrid discrete particle swarm optimization-genetic algorithm for multi-task scheduling problem in service oriented manufacturing systems

To cope with the task scheduling problem under multi-task and transportation consideration in large-scale service oriented manufacturing systems(SOMS), a service allocation optimization mathematical model was established, and then a hybrid discrete particle swarm optimization-genetic algorithm(HDPSOGA) was proposed. In SOMS, each resource involved in the whole life cycle of a product, whether it is provided by a piece of software or a hardware device, is encapsulated into a service. So, the transportation during production of a task should be taken into account because the hard-services selected are possibly provided by various providers in different areas. In the service allocation optimization mathematical model, multi-task and transportation were considered simultaneously. In the proposed HDPSOGA algorithm, integer coding method was applied to establish the mapping between the particle location matrix and the service allocation scheme. The position updating process was performed according to the cognition part, the social part, and the previous velocity and position while introducing the crossover and mutation idea of genetic algorithm to fit the discrete space. Finally, related simulation experiments were carried out to compare with other two previous algorithms. The results indicate the effectiveness and efficiency of the proposed hybrid algorithm.

A decision tree based decomposition method for oil refinery scheduling

Refinery scheduling attracts increasing concerns in both academic and industrial communities in recent years.However, due to the complexity of refinery processes, little has been reported for success use in real world refineries. In academic studies, refinery scheduling is usually treated as an integrated, large-scale optimization problem,though such complex optimization problems are extremely difficult to solve. In this paper, we proposed a way to exploit the prior knowledge existing in refineries, and developed a decision making system to guide the scheduling process. For a real world fuel oil oriented refinery, ten adjusting process scales are predetermined. A C4.5 decision tree works based on the finished oil demand plan to classify the corresponding category(i.e. adjusting scale). Then,a specific sub-scheduling problem with respect to the determined adjusting scale is solved. The proposed strategy is demonstrated with a scheduling case originated from a real world refinery.

A Probe Method of Gradient Projection Type

In this paper,a probe method for nonlinear programming wiht equality and inequality is given. Its iterative directions at an arbitrary point x can be obtained through solving a liear system. The terminate conditions and choices of the parameters are given. The global convergence of the method is proved. Further more,some well known gradient projection type algorithms [1-15] and new gradient projection type algorithms from the linear system are given in this paper.

Symmetry Reduction of Initial-Value Problems for a Class of Third-order Evolution Equations

Symmetry reduction of a class of third-order evolution equations that admit certain generalized conditionalsymmetries (GCSs) is implemented.The reducibility of the initial-value problem for an evolution equation to a Cauchyproblem for a system of ordinary differential equations (ODEs) is characterized via the GCS and its Lie symmetry.Complete classification theorems are obtained and some examples are taken to show the main reduction procedure.

Transceiver Optimization for Multi-Antenna Device-to-Device Communications

It has been shown that the deployment of device-to-device(D2D) communication in cellular systems can provide better support for local services. However, improper design of the hybrid system may cause severe interference between cellular and D2D links. In this paper, we consider transceiver design for the system employing multiple antennas to mitigate the interference. The precoder and decoder matrices are optimized in terms of sum mean squared error(MSE) and capacity, respectively. For the MSE minimization problem, we present an alternative transceiver optimization algorithm. While for the non-convex capacity maximization problem, we decompose the primal problem into a sequence of standard convex quadratic programs for efficient optimization. The evaluation of our proposed algorithms for performance enhancement of the entire D2D integrated cellular system is carried out through simulations.

NSGA Ⅱ based multi-objective homing trajectory planning of parafoil system

Homing trajectory planning is a core task of autonomous homing of parafoil system.This work analyzes and establishes a simplified kinematic mathematical model,and regards the homing trajectory planning problem as a kind of multi-objective optimization problem.Being different from traditional ways of transforming the multi-objective optimization into a single objective optimization by weighting factors,this work applies an improved non-dominated sorting genetic algorithm Ⅱ(NSGA Ⅱ) to solve it directly by means of optimizing multi-objective functions simultaneously.In the improved NSGA Ⅱ,the chaos initialization and a crowding distance based population trimming method were introduced to overcome the prematurity of population,the penalty function was used in handling constraints,and the optimal solution was selected according to the method of fuzzy set theory.Simulation results of three different schemes designed according to various practical engineering requirements show that the improved NSGA Ⅱ can effectively obtain the Pareto optimal solution set under different weighting with outstanding convergence and stability,and provide a new train of thoughts to design homing trajectory of parafoil system.

The Influence of Enterprise Culture on Enterprise Internal Control

Only if an enterprise establishes a good internal control can it survive and develop in a long-term way, and because of the closely relationship between corporate culture and internal control, the corporate culture has important significance on the impact of internal control. From the perspective of cultural problems in enterprise internal control and the innovation enterprise culture, this paper improves the method of construction honesty cultural and harmonious culture, so as to improve the internal control system. Through this study, people hope to provide effective reference to optimize the enterprise internal control system, which will inject new vitality for the construction of enterprises internal control.

A New Optimization Approach for Transmission Usage Allocation in Deregulated Power System

Deregulation of power system industry is a very large complex exercise based on respective national energy strategies and policies. A lot of matters and knowledge need to be studied before the idea of deregulation can be implemented. Theoretically, it is said that deregulation can make a large impact to increase efficiency and encourage the competitiveness among related parties. However, to implement the concept of deregulation to electric power supply is very tough challenge. In deregulation environment, regardless of market structure, to know the transmission usage allocation is vital and very a complex problem. Thus, a lot of algorithms have been proposed to overcome it. This paper intends to solve the transmission usage allocation problem using optimization approach. The optimization tool that will be utilized is Genetic Algorithm （GA）. GA is probabilistic search technique that has its roots in the principle of genetics and strives for survival. In addition, GA is very robust. Since the nonlinear nature of power flow, it is expected that GA can give optimize results that equitable and acceptable. In this paper, 4-bus and Klos-Kerner 11-bus systems are used for analysis studies. Comparison with other method is also given in this paper.

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.

Optimization Framework for Conceptual Powertrain Design

With an increasing number of vehicles with alternative powertrains, the choice of the most appropriate powertrain system for a vehicle class or a load cycle is challenging. This paper introduces a method to design an optimal alternative powertrain based on a longitudinal dynamic simulation. The objective function of the minimization problem describes the characteristic map of the traction system. The goal of the optimization is to minimize fuel consumption respectively energy demand. Different types of propulsion systems are investigated. The results show that the proposed method delivers useful alternative powertrains by applying an optimization with reasonable restrictions.

On Simultaneous Exact Controllability

We consider a mixed problem for a system describing the evolution of sound in a compressible fluid. We describe how to treat a simultaneous exact boundary controllability problem in the sense proposed by J.L. Lions as well as D. Russell. By using convenient modified multipliers we obtain an observability inequality provided suitable geometric condition on the domain is valid and the speed velocity of the models are related.

Optimized Operation of a Solar-Driven Thermoelectric Dehumidification System for Fresh Water Production

The work presents a parametric analysis of the performance of a solar-driven thermoelectric system to dehumidify air and produce fresh water. The system is combined with a solar distiller humidifying ambient air to enhance distillate output to meet the specified fresh water needs for a residential application. The presented system is a totally renewable energy-based system taking advantage of the clean solar energy. A model is developed to simulate the air dehumidification process using TEC （thermoelectrically cooled） channels. An optimization problem for setting system operational parameters is formulated to meet the fresh water requirement of 10 liters per day for a typical residential application in the Lebanese coastal humid climate. Using five TEC channels of length of 1.2 m and area of 0.07 - 0.05 m^2 integrated with 1.2 m^2 solar distiller is capable of meeting the water demand, where the air mass flow rate introduced to each TEC channel is optimally set at 0.0155 kg/s. The optimal electrical current input to the TEC modules from the photovoltaic solar panels varied depending on the month and is set at 2.2 A in June, 2.1 A in July and 2.0 A in August, September and October per each TEC module.

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.

A Decision Support System for Energy Trading and Portfolio Optimization

In the new competitive environment of the electricity market, risk analysis is a powerful tool to guide investors under both contract uncertainties and energy prices of the spot market. Moreover, simulation of spot price scenarios and evaluation of energy contracts performance, are also necessary to the decision maker, and in particular to the trader to foresee opportunities and possible threats in the trading activity. In this context, computational systems that allow what-if analysis, involving simulation of spot price, contract portfolio optimization and risk evaluation are rather important. This paper proposes a decision support system not only for solving the problem of contracts portfolio optimization, by using linear programming, but also to execute risks analysis of the contracts portfolio performance, with VaR and CVaR metrics. Realistic tests have demonstrated the efficiency of this system.

GLOBAL CLASSICAL SOLUTIONS TO QUASILINEAR HYPERBOLIC SYSTEMS WITH WEAK LINEAR DEGENERACY

Consider the following Cauchy problem for the first order quasilinear strictly hy- perbolic system ?u ?u + A(u) = 0, ?t ?x t = 0 : u = f(x). We let M = sup |f (x)| < +∞. x∈R The main result of this paper is that under the assumption that the system is weakly linearly degenerated, there exists a positive constant ε independent of M, such that the above Cauchy problem admits a unique global C1 solution u = u(t,x) for all t ∈ R, provided that +∞ |f (x)|dx ≤ ε, ?∞ +∞ ε |f(x)|dx ≤ . M∞