Adaptive retrieval practice with multiple-choice questions in the university classroom

Retrieval practice promotes retention more than restudying (i.e., the testing effect) and is applied to many educational settings. However, little research has investigated means to enhance this effect in educational settings. Theoretical accounts assume retrieval practice to be the most effective whenever retrieval is difficult but successful. Therefore, we developed a novel retrieval practice procedure, which adapts to learners' abilities and can be applied irrespective of learning content. This adaptive procedure aims to make retrieval gradually easier whenever students provide an incorrect answer. In a field experiment, students read book chapters as part of a weekly university course. In three consecutive weeks, they then practiced reading assignments by (a) adaptive testing, (b) non-adaptive testing and (c) restudy. In Week 4, a surprise criterial test took place. Restudy outperformed both testing conditions, whereas adaptive testing performed equally well as non-adaptive testing. However, exploratory analyses revealed that with increasing retention intervals, the superiority of restudy disappeared. Furthermore, whenever participants fully read the assignments and retention intervals increased, adaptive testing outperformed non-adaptive testing. In sum, adaptive retrieval practice did not prove to be generally superior, but retention interval and students' preparation for class might be conditions rendering adaptive retrieval useful in educational settings.     

Geometry optimization and pressure analysis of a proton exchange membrane fuel cell stack

For proton exchange membrane fuel cells (PEMFCs), the distribution of reactant streams in the reactor is critical to their efficiency. This study aims to investigate the optimal design of the inlet/outlet flow channel in the fuel cell stack with different geometric dimensions of the tube and intermediate zones (IZ). The tube-to-IZ length ratio, the IZ width, and the tube diameter are adjusted to optimize the geometric dimensions for the highest pressure uniformity. Four different methods, including the Taguchi method, analysis of variance (ANOVA), neural network (NN), and multiple adaptive regression splines (MARS), are used in the analyses. The results indicate the tube diameter is the most impactive one among the three factors to improve the pressure uniformity. The analysis suggests that the optimal geometric design is the tube-to-IZ length ratio of 9, the IZ width of 14 mm, and the tube diameter of 9 mm with the pressure uniformity of 0.529. The relative errors of the predicted pressure uniformity values by NN and MARS under the optimal design are 1.62% and 3.89%, respectively. This reveals that NN and MARS can accurately predict the pressure uniformity, and are promising tools for the design of PEMFCs.     

Combination of dynamic features with a new mask to optimize neural network speech enhancement

Concerning the problem that the Neural Network speech enhancement algorithm cannot fully represent the nonlinear structure of speech due to feature selection,which leads to speech distortion.This paper proposes the combination of dynamic features with a new mask to optimize neural network speech enhancement.First,three features of noisy speech are extracted and spliced to obtain static features.Then,the first and second difference derivatives are obtained to capture the instantaneous signals of speech and fuse them into dynamic features.The combination of dynamic and static features completes internal complementarity of features and reduced speech distortion.Second,in order to enhance the intelligibility and clarity of speech at the same time,an adaptive mask is proposed,which can adjust the energy ratio of speech and noise as well as the ratio of the traditional mask and the square root mask.The Gammatone channel weight is used to modify the mask value in each channel to simulate the human auditory system and further improve the speech intelligibility.Finally,the simulation of multiple voices under different noise backgrounds shows that compared with different literature algorithms,the algorithm has a higher SNR,subjective speech quality and short-term objective intelligibility,which verifies the effectiveness of the algorithm.     

An efficient method for estimating time-dependent failure possibility by combining adaptive Kriging with adaptive truncated fuzzy simulation

Time-dependent failure possibility (TDFP) can measure the structural safety level for a time interval of interest under fuzzy uncertainty, but its calculational cost is unaffordable by using fuzzy simulation (FS) due to a required large size of FS candidate sampling pool (CSP). Although time-dependent adaptive Kriging model (T-AK) combined with FS (T-AK-FS) was presented to reduce the number of calling performance function, a large FS CSP still makes training T-AK time-consuming. To improve its efficiency, an adaptive truncated FS (ATFS) with T-AK (T-AK-ATFS) is proposed by CSP size reduction approach. By T-AK-ATFS, the largest safety hypercube in fuzzy standard space is adaptively searched, in which the samples are in safety states and can be removed from the FS CSP. Moreover, T-AK is adaptively trained to search the largest safety hypercube and estimate TDFP simultaneously. In adaptively searching process, the FS CSP is divided into several sub-CSPs, on which training T-AK is more time-saving. Overall, strategies of T-AK-ATFS include proposing ATFS to reduce the FS CSP, adaptively searching the largest safety hypercube, estimating the TDFP with the same T-AK and training T-AK in the sub-CSPs sequentially. Verified by examples, these strategies make T-AK-ATFS more efficient than existing FS and T-AK-FS.     

火电机组一次调频性能实时监测系统

为了实时监测和评价火电机组一次调频性能，开发了火电机组一次调频性能实测监测系统。该系统具有一次调频参数异动感知、一次调频性能量化预测及自适应校正等关键功能。某机组的实际应用表明，该系统能够实现火电机组一次调频关键参数的实时监测和调频性能的准确预测。     

冰下单载波水声通信试验研究

北极地区战略地位的提高促进了极区各种应用的快速发展，冰下水声通信成为其中一个热点问题。为了研究冰下单载波水声通信性能，在黄海冰区开展冰下试验。重点分析了内嵌锁相环的多通道判决反馈均衡(Multi-channelDecision Feedback Equalization, M-DFE)技术在冰下水声通信中抗多途时延的能力，研究比较了改进比例归一化最小均方(Improved Proportional normalized Least Mean Square, IPNLMS)算法和递归最小二乘(Recursive Least Squares,RLS)算法的均衡性能。试验结果表明IPNLMS和RLS都能克服信道多途效应带来的影响。在牺牲计算复杂度的前提下，RLS具有更好的均衡效果，M-DFE在冰下环境中能够有效消除码间干扰。     

采用分级模糊滑模控制器实现二级倒立摆的解耦控制

针对二级倒立摆系统的非线性强耦合的特点,提出和采用了一种新型分级模糊滑模(HFSM)控制器的思想,实现了对二级倒立摆系统的解耦控制。基于李亚普诺夫函数采用自适应规则来调节分级模糊滑模控制器参数,保证系统可靠稳定性。通过系统仿真实验,也验证了该方法的可行性和优于采用常规模糊滑模解耦控制的解耦性能。     

一种适用于井下通信的自适应滤波器研究

针对煤矿井下严重的环境噪声影响，文章论述了一种受话音频谱控制的自适应动态滤波器。它可以有效地减小井下环境噪声对话音信号的影响，达到改善通信质量，增加通信距离的效果。     

铜精炼过程能耗模糊自适应变权重组合预测模型及其应用

基于已有的铜精炼过程的能耗数据,引入了各预测方法的预测相对误差、预测对象的变化趋势、灰色基本权重和自适应调节系数等概念,建立了铜精炼过程的能耗模糊自适应变权重组合预测模型。结果表明,此模糊自适应变权重组合预测模型的精度较高,并且平均误差和预测平方根误差均较小。该组合预测模型为铜精炼过程的能源需求决策提供了有力支持。     

铝带坯铸轧板形检测信号的参数递推辨识与滤波并行除噪

基于参数递推辨识与信号滤波同时并行处理 ,建立通用板形检测信号除噪方法 ,编制RPEM -KF自适应滤波算法程序。仿真结果表明该法除噪效果明显 ,滤波前后信号的标准差比值 Ve/Vn =4 63 % ,最大误差比值Me/Mn =4 13 %。能满足实时控制要求