Chinese Students’ Ambivalent Perceptions of Grammar Correction in L2 Writing

The efficacy of Grammar Correction (GC) in second language (L2) writing classes has been the subject of much controversy and the field seems to take Ferris’ (1999) generalization that students believe in GC and want to receive it for granted. To test Ferris’ generalization, this study examines Chinese students’ perceptions of GC in their English writing. The results of a questionnaire administered to six groups of three proficiency levels of university students majoring in or not in English show ambivalent perceptions towards GC. On the one hand, all learners believe GC has obvious effects and can improve their accuracy in L2 writing. On the other hand, they all agree that GC is not enough for improving learners’ writing ability and that the time spent on GC should be allocated on training other writing abilities. All groups of participants gave a negative to uncertain answer to GC, though different perception patterns figure in whether or not majoring in English: English-major groups’ mean expectation scores of GC increase while those of non-English-major groups decrease in keeping with their English levels. These results provide strong evidence for Truscott’s (1996) view that GC should be abandoned. We believe that the different perceptions of GC shown by English and non-English major students stem from the fact that the former receives a more systematic grammar instruction than the latter. The ambivalent perceptions of GC originate in the fact that grammar accuracy occupies an important proportion in various writing evaluation systems

A Finite Element Method for the Multiterm Time-Space Riesz Fractional Advection-Diffusion Equations in Finite Domain

We present an effective finite element method (FEM) for the multiterm time-space Riesz fractional advection-diffusion equations (MT-TS-RFADEs). We obtain the weak formulation of MT-TS-RFADEs and prove the existence and uniqueness of weak solution by the Lax-Milgram theorem. For multiterm time discretization, we use the Diethelm fractional backward finite difference method based on quadrature. For spatial discretization, we show the details of an FEM for such MT-TS-RFADEs. Then, stability and convergence of such numerical method are proved, and some numerical examples are given to match well with the main conclusions

Symphony No. 1

Abstract Symphony No.1, created on December 10, 2017. It was finally completed on February 1, 2018. This is a music representation of the environment using music. The composer of this symphony believes that at present it is a world of diversity, many different environmental factors and many different music senses and imagination are different. We can’t just stick to traditional music research and modern music research. The author of this music thinks that should complement each other and merge them totally different music materials, representing the three different styles of music materials, representing the three different styles of modern, national and classical. This work is inspired by the winter, and it is divided into three movements. Each movement describes the feeling of the environment, things and the abstract feeling of a certain time period. About Symphony No.1, the melody uses the national color factor. The harmony is divided into dissonance intervals and consonants intervals. According to the study of modern music and classical music, the composer also makes a static comparison in the rhythm in his music work. The first movement, the theme and motivation of the first movement in this symphony is paramount. The beginning of the music is fluency by the flute. First of all, on the design and layout of the motif flute part, I divided it into time values and voice. Subsequently, the other parts of the woodwind began to gradually motivate the theme. With regard to strings, in the first half, in the light background, the overall feeling of music is like the kind of scene before dawn. A piece of land, a mountain, they are so quiet and peace. The second movement, the strong sound started the movement, and as a grouping arrangement, the flute and clarinet were a group, the oboe and the bassoon were a group. This design is to highlight their tone, but also to make a contrast between the tone. In this movement, brass appears to strengthen the overall momentum. It\u27s like a powerful force moving forward. In addition, strings have also changed a great deal in strength and tempo. Through the overall cooperation, this movement expresses the struggling picture of people in the cold air and is a strong manifestation of the feeling of the soul. The third movement, there was a whole new theme motivation in the last movement. The overall feeling is very flexible, beating big. It is also from the cautious, worried to the release and show the feeling of dance. Importantly, percussion plays the single most important role in this movement. Therefore, the weather is very cold, but people\u27s heart is very hot. That cheerful mood defeated the cold

Enhanced independent pole control of hybrid MMC-HVDC system

This paper presents an enhanced independent pole control scheme for hybrid modular multilevel converter (MMC) based on full bridge sub-module (FBSM) and half bridge sub-module (HBSM). A detailed analysis of power distribution between upper and lower arms under asymmetrical DC pole voltages is presented. It is found that the fundamental AC currents in the upper and lower arms are asymmetrical. To enable operation under asymmetrical DC pole voltages, an enhanced independent pole control scheme is proposed. The controller is composed of two DC control loops, two AC control loops and circulating current suppression control based on current injection. Six modulation indices are presented to independently control the upper and lower arms. With this controller, the DC voltage operating region is significantly extended. To ride through pole to ground DC fault without bringing DC bias at the neutral point of interface transformer, a pole to ground DC fault ride through strategy is proposed. Feasibility and effectiveness of the proposed control scheme are verified by simulation results using PSCAD/EMTDC

Automated Scoring of Clinical Patient Notes using Advanced NLP and Pseudo Labeling

Clinical patient notes are critical for documenting patient interactions, diagnoses, and treatment plans in medical practice. Ensuring accurate evaluation of these notes is essential for medical education and certification. However, manual evaluation is complex and time-consuming, often resulting in variability and resource-intensive assessments. To tackle these challenges, this research introduces an approach leveraging state-of-the-art Natural Language Processing (NLP) techniques, specifically Masked Language Modeling (MLM) pretraining, and pseudo labeling. Our methodology enhances efficiency and effectiveness, significantly reducing training time without compromising performance. Experimental results showcase improved model performance, indicating a potential transformation in clinical note assessment

The Fusion of Deep Reinforcement Learning and Edge Computing for Real-time Monitoring and Control Optimization in IoT Environments

In response to the demand for real-time performance and control quality in industrial Internet of Things (IoT) environments, this paper proposes an optimization control system based on deep reinforcement learning and edge computing. The system leverages cloud-edge collaboration, deploys lightweight policy networks at the edge, predicts system states, and outputs controls at a high frequency, enabling monitoring and optimization of industrial objectives. Additionally, a dynamic resource allocation mechanism is designed to ensure rational scheduling of edge computing resources, achieving global optimization. Results demonstrate that this approach reduces cloud-edge communication latency, accelerates response to abnormal situations, reduces system failure rates, extends average equipment operating time, and saves costs for manual maintenance and replacement. This ensures real-time and stable control

Improved YOLOv5 Based on Attention Mechanism and FasterNet for Foreign Object Detection on Railway and Airway tracks

In recent years, there have been frequent incidents of foreign objects intruding into railway and Airport runways. These objects can include pedestrians, vehicles, animals, and debris. This paper introduces an improved YOLOv5 architecture incorporating FasterNet and attention mechanisms to enhance the detection of foreign objects on railways and Airport runways. This study proposes a new dataset, AARFOD (Aero and Rail Foreign Object Detection), which combines two public datasets for detecting foreign objects in aviation and railway systems.The dataset aims to improve the recognition capabilities of foreign object targets. Experimental results on this large dataset have demonstrated significant performance improvements of the proposed model over the baseline YOLOv5 model, reducing computational requirements.Improved YOLO model shows a significant improvement in precision by 1.2%, recall rate by 1.0%, and [email protected] by 0.6%, while [email protected] remained unchanged. The parameters were reduced by approximately 25.12%, and GFLOPs were reduced by about 10.63%. In the ablation experiment, it is found that the FasterNet module can significantly reduce the number of parameters of the model, and the reference of the attention mechanism can slow down the performance loss caused by lightweight