基于“问题”的高校政治理论课教学探微

问题意识是思想政治理论课教学改革与创新的原动力。把教材的理论体系问题化,社会热点问题讨论化,专业背景问题专题化,实践问题行动化,是改善高校思想政治理论课教学的有效尝试。

基于问题导向的小学数学深度学习思考

在新课改的背景下,小学数学教学是非常重要的,主要是能够培养小学生的数学能力以及数学综合素养,小学数学老师可以运用科学的有效的方法,如,“问题导向”学习法来提升小学生的数学学习能力,进而提高数学学习实效性。针对此教学方法,本文作者论述分析了“问题导向”教学法对小学数学深度学习的重要作用。

Heterogeneous Quality of Experience Guarantees Over Wireless Networks

Quality of experience(Qo E), which is very critical for the experience of users in wireless networks, has been extensively studied. However, due to different human perceptions, quantifying the effective capacity of wireless network subject to diverse Qo E is very difficult, which leads to many new challenges regarding Qo E guarantees in wireless networks. In this paper, we formulate the Qo E guarantees model for cellular wireless networks. Based on the model, we convert the effective capacity maximization problem into the equivalent convex optimization problem. Then, we develop the optimal Qo E-driven power allocation scheme, which can maximize the effective capacity. The obtained simulation results verified our proposed power allocation scheme, showing that the effective capacity can be significantly increased compared with that of traditional Qo E guarantees based schemes.

The Use of PBL （Problem-Based Learning） in Improving the Student Performance in Navigation 3 （Terrestrial and Coastal Navigation）

This quasi-experimental study aimed at looking into the effectiveness of PBL （problem-based learning） in improving the performance in Navigation 3 （terrestrial and coastal navigation） of BSMT （Bachelor of Science in Marine Transportation） second year students at JBLFMU-Arevalo during the first semester of school year 2016-2017. The respondents of this research were the two sections comparable with each other who was enrolled in the subject Navigation 3. There were 60 student respondents composed of 30 in the experimental group and 30 in the control group. A validated three item teacher-made problem solving test with 10 points for each correct answer was used as an instrument. The dependent variable was the scores in Navigation 3 and independent variable was the PBL approach. The statistical tools used were mean, standard deviation, Mann-Whitney test, and Wilcoxon-Signed ranks test set at 0.05 level of significance. The effect size was computed to determine the effectiveness of the PBL approach in terms of students＇ performance in Navigation 3. Results showed that in the pretest, though the experimental group had a higher mean than the control group, the Mann-Whitney test showed that the mean scores of the two groups were comparable because the significant value was greater than 0.05. When the treatment was introduced, findings showed that there were significant differences in the Navigation 3 performance in the pretest and posttest of experimental and control groups as well as in the posttests of both groups. It could be inferred that the better performance of the experimental group could be attributed to the intervention where the students were actively involved in the learning process.

On ε-Constraint Based Methods for the Generation of Pareto Frontiers

Over the years, a number of methods have been proposed for the generation of uniform and globally optimal Pareto frontiers in multi-objective optimization problems. This has been the case irrespective of the problem definition. The most commonly applied methods are the normal constraint method and the normal boundary intersection method. The former suffers from the deficiency of an uneven Pareto set distribution in the case of vertical （or horizontal） sections in the Pareto frontier, whereas the latter suffers from a sparsely populated Pareto frontier when the optimization problem is numerically demanding （ill-conditioned）. The method proposed in this paper, coupled with a simple Pareto filter, addresses these two deficiencies to generate a uniform, globally optimal, well-populated Pareto frontier for any feasible bi-objective optimization problem. A number of examples are provided to demonstrate the performance of the algorithm.

基于UKF的雷达和机载ESM扩维跟踪

为有效提高异类传感器融合跟踪的效果,提出了一种基于UKF的雷达和机载ESM扩维跟踪算法。首先将目标和机载ESM的状态信息组合起来,形成一个高维的状态向量,从而有效抑制滤波中GPS定位误差所带来的影响;接着在此基础上采用UKF来实现目标的定位跟踪,以求进一步减小扩维后线性化误差加大等问题的影响。仿真结果表明,该算法可更好地实现对目标的定位跟踪。

Multi-Objective Cooperative Salvo Attack Against Group Target

This paper proposes a solution for the problem of cooperative salvo attack of multiple cruise missiles against targets in a group. Synchronization of the arrival time of missiles to hit their common target, minimizing the time consumption of attack and maximizing the expected damage to group targets are taken into consideration simultaneously. These operational objectives result in a hierarchical mixed-variable optimization problem which includes two types of subproblems, namely the multi-objective missile-target assignment（MOMTA） problem at the upper level and the time-optimal coordinated path planning（TOCPP） problems at the lower level. In order to solve the challenging problem, a recently proposed coordinated path planning method is employed to solve the TOCPP problems to achieve the soonest salvo attack against each target. With the aim of finding a more competent solver for MOMTA, three state-of-the-art multi-objective optimization methods（MOMs）,namely NSGA-II, MOEA/D and DMOEA-εC, are adopted. Finally, a typical example is used to demonstrate the advantage of the proposed method. A simple rule-based method is also employed for comparison. Comparative results show that DMOEA-εC is the best choice among the three MOMs for solving the MOMTA problem. The combination of DMOEA-εC for MOMTA and the coordinated path planning method for TOCPP can generate obviously better salvo attack schemes than the rule-based method.

Problem-Based L2 Learning: Self-Negotiated Linguistic Cognition

The existing literature has revealed that Problem-based Learning （PBL） can improve the cognitive competence of learners, but few studies focus on L2 learning from the perspective of students, or on the relationship between PBL and linguistic cognition. Based on students＇ reflective journals, the researcher＇s observation notes, and interviews with teachers and students, this case study describes the individual and collective self-negotiations during a Problem-Based L2 Learning （PBLL） practice of 157 non-English majors at three universities in Beijing. The current study makes a distinction between surface and deep self-negotiations, and confirms the conception of the self-negotiated L2 cognition of PBLL learners. The research results show （1） that the self-negotiation is a consistent feature of PBLL because the whole PBLL process comprises the cyclic intertwining of individual and collective self-negotiations, （2） that L2 learners manage to achieve individual and collective self-negotiations through cognitive mechanisms of linking, riffling and converging, and （3） that deep self-negotiations in PBLL are more dynamic, interactive, and generative. Pedagogical implications, research limitations, and future directions are also discussed.

On the optimization problem of model-based monitoring

Today there is a big interest in reducing the maintenance costs and in increasing the reliability of machines in continuous operation. Therefore, maintenance on condition is used. State-of-the-art is a trend analysis and a fault prediction made only based on sensor signals and stochastic methods. The identification possibilities of this technique are limited. A new concept for model-based monitoring has been developed for more detailed fault identification. The developed concept determines the condition of a machine after the occurrence of a fault. The concept is based on a simulation including various faults and an optimization tool. The development of a cost function and the optimization is one of the challenges of such a concept. Using an AMB rotor system with an auxiliary bearing, the new concept of model-based monitoring is investigated using experiments and the optimization is discussed in this paper.