Learning Processes in Interactive CALL Systems: Linking Automatic Feedback, System Logs, and Learning Outcomes

Interactive digital tools increasingly used for language learning can provide detailed system logs (e.g., number of attempts, responses submitted), and thereby a window into the user’s learning processes. To date, SLA researchers have made little use of such data to understand the relationships between learning conditions, processes, and outcomes. To fill this gap, we analyzed and interpreted detailed logs from an ICALL system used in a randomized controlled field study where 205 German learners of English in secondary school received either general or specific corrective feedback on grammar exercises. In addition to explicit pre-/post-test results, we derived 19 learning process variables from the system log. Exploratory factor analysis revealed three latent factors underlying these process variables: effort,accuracy focus, and time on task. Accuracy focus and finish time (a process variable that did not load well on any factors) significantly predicted pre-/post-test gain scores with a medium effect size. We then clustered learners based on their process patterns and found that the specific feedback group tended to demonstrate particular learning processes and that these patterns moderate the advantage of specific feedback. We discuss the implications of analyzing system logs for SLA, CALL, and education researchers and call for more collaboration.

Statistics Decomposition and Monitoring in Original Variable Space

The traditional process monitoring method first projects the measured process data into the principle component subspace (PCS) and the residual subspace (RS), then calculates $$\mathrm T^2$$ T 2 and $$\mathrm SPE$$ S P E statistics to detect the abnormality. However, the abnormality by these two statistics are detected from the principle components of the process. Principle components actually have no specific physical meaning, and do not contribute directly to identify the fault variable and its root cause. Researchers have proposed many methods to identify the fault variable accurately based on the projection space. The most popular is contribution plot which measures the contribution of each process variable to the principal element (Wang et al. 2017; Luo et al. 2017; Liu and Chen 2014). Moreover, in order to determine the control limits of the two statistics, their probability distributions should be estimated or assumed as specific one. The fault identification by statistics is not intuitive enough to directly reflect the role and trend of each variable when the process changes.

Towards an Efficient Generalization of the Online Dosage of Hydrogen Peroxide in Photo-Fenton Process to Treat Industrial Wastewater

This work addresses the dosage of H2O2 in photo-Fenton processes and the monitoring of Dissolved oxygen (DO) that can be used to drive the dosage of H2O2. The objective of this work is to show that a smarter monitoring of a process variable such as DO (for which on-line measurement can be inexpensively obtained) enables the proposal and implementation of efficient dosage strategies. The work explores the application of a recent proposed strategy consisting of: (i) initial H2O2 addition, (ii) continuous H2O2 addition until a DO set up is reached, and (iii) automatic H2O2 addition by an on-off control system based on DO slope monitoring, and applies it to the treatment of different individual contaminants and their mixtures (paracetamol and sulfamethazine). The assays performed following this dosage strategy showed improved values of TOC removed per H2O2 consumed. For the case of sulfamethazine, this improvement increased up to 25–35% with respect to the efficiency obtained without dosage. Furthermore, a deeper analysis of the results allowed detecting and assessing the opportunity to redesign the dosage scheme and reduce its complexity and the number of control parameters. The promising results obtained are discussed in regard of future research into further increasing the simplicity and robustness of this generalized control strategy that improves the applicability of the photo-Fenton process by reducing its operating costs and increasing automation.

Advanced Control to Improve the Ramp-Rate of a Gas Turbine: Optimization of Control Schedule

As the proportion of power generation using renewable energy increases, it is important to improve the operational flexibility of gas turbines (GTs) for the stability of power grids. Increasing the ramp-rate of GTs is a general solution. However, a higher ramp-rate increases the turbine inlet temperature (TIT), its rate of change, and the fluctuation of the frequency of produced electricity, which are negative side effects. This study proposes a method to optimize the set-point schedule for a PID controller to improve the ramp-rate while decreasing the negative impacts. The set-point schedule was optimized for a 170-MW class GT using a genetic algorithm to minimize the difference between the value of the process variable and the set-point value of the conventional control. The advanced control reduced the fluctuation of the rotation speed by 20% at the reference ramp-rates (12 MW/min and 15 MW/min). The maximum TIT decreased by 6.3 °C, and its maximum rate of change decreased from 0.7 °C/s to 0.4 °C/s. The advantage of the advanced control becomes more marked as the ramp-rate increases. Even at a much higher ramp-rate (50 MW/min), the advanced control decreased the rotation speed fluctuation by 40% in comparison to the conventional control at the reference ramp-rate.

The Implementation of Anti-Corruption Character Education Through Bali Local Wisdom in Junior High Schools

This study aims to evaluate anti-corruption character education through Balinese local wisdom in junior high schools and formulate strategies to strengthen its implementation. The research samples were determined purposively. The evaluation model used was the CIPPO model (Context, Input, Process, Output, Outcome), modified from the CIPP model. Data were collected by interview, observation, and documentation methods. Data analysis was carried out using quantitative descriptive methods and SWOT analysis. The results showed that the implementation of anti-corruption character education was considered effective with an achievement of 76.06%. The highest achievement is on the input variable of 81.75% (very effective), and the lowest is on the process variable of 61.75% (less effective). The process of implementing anti-corruption education through learning, habituation, and civilizing is still dominant at the theoretical level, not involving students actively and critically in real life. The SWOT analysis resulted in five strategy formulations, namely: (1) establishment of a character education development unit (anti-corruption), (2) transformation of anti-corruption education learning, (3) exemplary, habituation and civilizing, (4) strengthening extracurricular programs, and (5) building cooperation network.

Multi-criteria performance assessment based on closed-loop system identification

<div>A method to assess the performance of closed loop control loops, based on closed-loop system identification. This method allows to take into account the trade-off between process variable and manipulated variable energy, thus overcoming one of the most important criticisms to Harris' index. </div>

Multi-criteria performance assessment based on closed-loop system identification

<div>A method to assess the performance of closed loop control loops, based on closed-loop system identification. This method allows to take into account the trade-off between process variable and manipulated variable energy, thus overcoming one of the most important criticisms to Harris' index. </div>

Enhanced keratin extraction from wool waste using a deep eutectic solvent

In this study, the solubilisation of waste coarse wool as a precursory step for the large scale valorisation of keratin was investigated using a green deep eutectic solvent (DES) based on L-cysteine and lactic acid. The investigation was undertaken via the response surface methodology and based on the Box-Behnken design for four process variables of temperature (70-110 °C), dissolution time (2-10 h), the mass of L-cysteine (0.5-2.5 g) in 20 mL of lactic acid, and wool load in the DES (0.2-0.6 g). The effect of variations in temperature was established to be the most significant process variable influencing keratin yield from waste coarse wool in the current work. An optimum keratin yield (93.77 wt.%) was obtained at the temperature of 105 °C, 8 h dissolution time, with 1.6 g L-cysteine in 20 mL of lactic acid using 0.5 g of wool. This study suggests L-cysteine and lactic acid as a green solvent with the potential to scale up keratin recovery from waste wool without significant destruction in the structure of the recovered keratin.HighlightsKeratin recovery from wool using deep eutectic solvent was assessedThe basis for the use of the new deep eutectic solvent was discussedThe effects of the process variables on keratin yield were exploredKeratin recovered was optimised and characterised.

Evaluation of sonication on stability-indicating properties of optimized pilocarpine hydrochloride-loaded niosomes in ocular drug delivery

Niosomes are increasingly explored for enhancing drug penetration and retention in ocular tissues for both posterior and anterior eye delivery. They have been employed in encapsulating both hydrophilic and hydrophobic drugs, but their use is still plagued with challenges of stability and poor entrapment efficiency particularly with hydrophilic drugs. As a result, focus is on understanding the parameters that affect their stability and their optimization for improved results. Pilocarpine hydrochloride (HCl), a hydrophilic drug is used in the management of intraocular pressure in glaucoma. We aimed at optimizing pilocarpine HCl niosomes and evaluating the effect of sonication on its stability-indicating properties such as particle size, polydispersity index (PDI), zeta potential and entrapment efficiency. Pilocarpine niosomes were prepared by ether injection method. Composition concentrations were varied and the effects of these variations on niosomal properties were evaluated. The effects of sonication on niosomes were determined by sonicating optimized drug-loaded formulations for 30 min and 60 min. Tween 60 was confirmed to be more suitable over Span 60 for encapsulating hydrophilic drugs, resulting in the highest entrapment efficiency (EE) and better polydispersity and particle size indices. Optimum sonication duration as a process variable was determined to be 30 min which increased EE from 24.5% to 42% and zeta potential from (−)14.39 ± 8.55 mV to (−)18.92 ± 7.53 mV. In addition to selecting the appropriate surfactants and varying product composition concentrations, optimizing sonication parameters can be used to fine-tune niosomal properties to those most desirable for extended eye retainment and maintenance of long term stability.