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An English Teaching Information-assisted Platform Design Based on Process-oriented Management

JOURNAL OF INFORMATION & KNOWLEDGE MANAGEMENT 2025年第2期24卷

作者： Tan, Xiaochuang Jilin Normal Univ Siping Jilin Peoples R China

With the development of global education informatisation, the application of knowledge management system in teaching is more and more extensive, which promotes the progress of intelligent education and personalised teaching. Although the existing English teaching platform realises resource sharing and network teaching, there are still shortcomings in real-time feedback and personalised support. To solve this problem, this study proposes an English teaching assistance platform based on process management and Deep Knowledge Tracking (DKT) model. By introducing formative evaluation systems and dynamic learning data analysis, the platform provides teachers with real-time feedback to optimise teaching strategies. At the same time, the personalised practice recommendation function based on the knowledge graph can effectively improve students' learning efficiency and knowledge mastery. The experimental results show that the Area Under Curve (AUC) value of the DKT model on six data sets is 0.83 to 0.93, which is superior to other knowledge tracking models. Moreover, the average score of students in the experimental group is 10.6 points higher than that in the blank group and 6.2 points higher than that in the control group, and the review time is reduced by 3 and 2 h. The mean square error of the platform is 0.202, and the F1 value is 0.93, which outperforms the traditional teaching model and significantly improves the learning effect and experience of students. Through the integration of the knowledge graph and DKT model, the platform realises the functions of dynamic learning data analysis, personalised recommendation and real-time feedback, which improves learning efficiency and optimises teaching effect. By optimizing information flow and knowledge-sharing mechanisms, in the field of public services, knowledge management helps to improve government transparency and response speed, and promote scientific and precise policy making. In addition, knowledge management also p

关键词： Process management English teaching supporting platform learning detection personalised recommendation SDG

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Application of Stochastic Approximation in the Hilbert Space to Solving the Problem of Detecting the Instant of Arrival of an Object in a Sequence of Noisy Images

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OPTOELECTRONICS INSTRUMENTATION AND DATA PROCESSING 2011年第3期47卷 215-219页

作者： Pyatkin, V. P. Salov, G. I. Russian Acad Sci Inst Computat Math & Math Geophys Siberian Branch Pr Akad Lavrenteva 6 Novosibirsk 630090 Russia

Application of stochastic approximation in an infinite-dimensional Hilbert space to the problem of object detection on one observed image distorted by noise and to the problem of fast detection of object arrival in a sequence of noisy images is considered. No a priori information is assumed to be available. The observer is supposed to have two stochastically independent sequences of independent "exact" noisy images, one containing and one not containing the object that has to be (repeatedly) detected by the observer in the nearest time.

关键词： noisy image sequence of images detection of objects learning detection

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“FOLO”: A Vision-Based Human-Following Robot

“FOLO”: A Vision-Based Human-Following Robot

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2018 3rd International Conference on Automation,Mechanical Control and Computational Engineering(AMCCE 2018)

作者： Evan Chen Department of Information Art ＆ Design Tsinghua University

The main challenge in following robot is solving the real-time user localization problem. In this paper we introduce our solution for it together with our whole robot system called "FOLO". Using extra-tool（such as Bluetooth） may cause inconvenience in interaction;3 D detector plus tracker ID approaches are at risks of computing consume and ROI flash;Approaches based on 2 D appearance have challenges on appearance change, re-detecting and complex background. We present a 2 D-appearance approach on "FOLO" which can work overcome above issues. Our approach utilizes consensus of corresponding method to track, and then, updates features by supervised learning into classifier cascade to against challenges of re-detecting and complex background. Moreover, we give pre-processing procedure on each frame to sharpen edges on image to enhance quality of tracking and use adaptive background to overcome challenge of complex background. This paper illustrates that our tracking approach can work against common challenges of tracking in our own designed experiments, has a rapid speed over 25 fps and can achieve state-of-the-art results. We use two-layer-PID method to control "FOLO" for a long-term task which allows "FOLO" succeeding to follow user in office environment.

关键词： Human-following learning detection Autonomous navigation

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