Enhancement of process modelling and simulation evaluation by deploying a test for assessment and feedback individualisation

This paper demonstrates a novel approach for a computer-based course assessment. A test is introduced in which computers are deployed. This significantly contributes to the enhancement of the marking consistency, individual performance distinction and feedbacks, and widen the questions range for computer-based modules. The proposed test method, for the first time, uses the simulation files marking for individualised evaluation purposes. The methodology has successfully been implemented in practice for three modules including Process Simulation (CE2105), Advanced Process Simulation (CE4023), and Process Computation (CE3021) at Aston University (UK) over three academic years, from 2016 to 2019. The effectiveness of the proposed approach has been evaluated using several factors, including final marks, consistency multiple academic years, and mark distribution. In contrast to the common teamwork assessments, individualised feedback became possible. While ASPEN has been used for CE4023 and CE2105 tests, MATLAB has been applied as the computation platform for CE3021 module. This reveals the applicability of different software in proposed methodology. The number of students in the cohorts studied was from 52 to 204, demonstrating the applicability of the method for various cohort sizes. Even though the methodology has been demonstrated based on the chemical engineering discipline modules, it allows digitalising the delivery and assessment of a wide range of simulation techniques in many disciplines.     

PSO优化多核RVM的模拟电路故障预测

针对模拟电路健康管理的特点，提出了一种基于PSO优化多核RVM的模拟电路故障预测方法。利用参数分析得到电路的输出频域响应作为特征，计算其与电路无故障标准响应的欧氏距离来表征电路元件健康值，将多个核函数线性组合，并用PSO优化多核RVM参数后的模型实现对各个时间点元件的健康值变化轨迹进行预测。仿真结果表明，该方法在小样本情况下，预测效果优于单一核函数的RVM模型，适用于健康管理中实时预测，具有较好的实用性。     

Active disturbance rejection based trajectory linearization control for hypersonic reentry vehicle with bounded uncertainties

This paper investigates a novel compound control scheme combined with the advantages of trajectory linearization control (TLC) and alternative active disturbance rejection control (ADRC) for hypersonic reentry vehicle (HRV) attitude tracking system with bounded uncertainties. Firstly, in order to overcome actuator saturation problem, nonlinear tracking differentiator (TD) is applied in the attitude loop to achieve fewer control consumption. Then, linear extended state observers (LESO) are constructed to estimate the uncertainties acting on the LTV system in the attitude and angular rate loop. In addition, feedback linearization (FL) based controllers are designed using estimates of uncertainties generated by LESO in each loop, which enable the tracking error for closed-loop system in the presence of large uncertainties to converge to the residual set of the origin asymptotically. Finally, the compound controllers are derived by integrating with the nominal controller for open-loop nonlinear system and FL based controller. Also, comparisons and simulation results are presented to illustrate the effectiveness of the control strategy.     

Creating formative feedback spaces in large lectures

Large lectures are the predominant way of teaching first-year students at universities in Norway. However, this forum for education is seldom discussed as a context for a formative feedback practice. The purpose of this sequential mixed methods study was to address whether and how a student-response system can open for a formative feedback practice in lectures and thereby support students' ability to monitor their own learning, as well as supply insight into how students engage with the feedback in their course work. The context for the study was large lectures (150–200 students) in a qualitative method course for first-year psychology students. Findings from the survey (n = 149) showed a positive correlation between the extent to which students report that they use clickers to monitor their own learning, and the extent to which they report that they used the feedback in their own course work. However, findings indicate that students valued the process of monitoring their own learning during the lectures to a greater extent than they actually used the feedback in their course work. Findings from interviews (n = 6) illustrated various ways students applied feedback in their course work.     

Semantic content-based image retrieval: A comprehensive study

The complexity of multimedia contents is significantly increasing in the current digital world. This yields an exigent demand for developing highly effective retrieval systems to satisfy human needs. Recently, extensive research efforts have been presented and conducted in the field of content-based image retrieval (CBIR). The majority of these efforts have been concentrated on reducing the semantic gap that exists between low-level image features represented by digital machines and the profusion of high-level human perception used to perceive images. Based on the growing research in the recent years, this paper provides a comprehensive review on the state-of-the-art in the field of CBIR. Additionally, this study presents a detailed overview of the CBIR framework and improvements achieved; including image preprocessing, feature extraction and indexing, system learning, benchmarking datasets, similarity matching, relevance feedback, performance evaluation, and visualization. Finally, promising research trends, challenges, and our insights are provided to inspire further research efforts.     

Effects of multiple-try feedback and question type during mathematics problem solving on performance in similar problems

In a study of mathematics problem solving, the effect of providing multiple-try feedback on later success in solving similar problems was examined. Participants solved mathematics problems that were presented as either multiple-choice or open-ended questions, and were provided with one of four types of feedback: no feedback (NF), immediate knowledge of the correct response (KCR), multiple-try feedback with knowledge of the correct response (MTC), or multiple-try feedback with hints after an initial incorrect response (MTH). Results showed that gains in performance were larger in the open-ended than multiple-choice condition. Furthermore, gains under NF and KCR were similar, gains were larger under MTC than KCR, and gains were larger under MTH than MTC. The implications of these results for the design of assessments for learning are discussed.     

Understand Students Feedback Using Bi-Integrated CRF Model Based Target Extraction

Educational institutions showing interest to find the opinion of the students about their course and the instructors to enhance the teaching-learning process. For this, most research uses sentiment analysis to track students’ behavior. Traditional sentence-level sentiment analysis focuses on the whole sentence sentiment. Previous studies show that the sentiments alone are not enough to observe the feeling of the students because different words express different sentiments in a sentence. There is a need to extract the targets in a given sentence which helps to find the sentiment towards those targets. Target extraction is the subtask of targeted sentiment analysis. In this paper, we proposed the innovative model to find the targets of the given sentence using Bi-Integrated Conditional Random Fields (CRF). A Parallel fusion neural network model is designed to perform this task. We evaluate the model using the Michigan dataset and we build a dataset for target extraction from student reviews. The experimental results show that our proposed fusion model achieves better results compared to baseline models.     

Unity direct chain with feedback series impedance based innovative negative group delay circuit

An innovative negative group delay (NGD) circuit theory on unity direct chain (UDC) topology is developed in this paper. The NGD UDC cells are based on the operational amplifier adder with feedback series impedance. Innovative topologies of high-pass NGD UDC cell composed of RL-series network, all-pass RC-parallel network and low-pass RC-series network are identified. It is a first time that all-pass NGD original topologies are defined. NGD analyses and synthesis methods of each NGD UDC cells are provided. The UDC cell based NGD functions are validated with SPICE simulations. The proofs-of-concept (POC) of UDCs behave as all-pass and low-pass NGD functions with group delay equal to −1 ms at very low frequencies. The low-pass NGD cut-off frequency is 424 Hz. The high pass NGD circuit generates −1 µs at the optimal NGD frequency of about 5.15 kHz. Further analysis of the operational amplifier gain and bandwidth effects is performed. The operational amplifier gain affects significantly the NGD level and bandwidth for the all considered UDC cells. Nevertheless, only the RC-parallel feedback based UDC cell is particularly sensitive to the operational bandwidth.     

Modellbasierte Regelung der Partikelgrößenverteilung in der kontinuierlichen Wirbelschicht‐Sprühgranulation

Recycling of milled product particles in continuous fluidised bed spray granulation can lead to sustained oscillations in the particle size distribution. In this contribution, a model‐predictive feedback control scheme is presented that allows for stabilisation of unstable steady‐states. The feedback law is designed based on a population balance model, which describes the temporal evolution of the particle size distribution due to the particulate processes, and is compared with traditional design methods (PI, LQR).