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    An efficient algorithm for solving time-dependent Gross-Pitaevskii equation
    Lisha SHU, Guangjiong DONG
    Journal of East China Normal University(Natural Science)    2024, 2024 (3): 84-90.   DOI: 10.3969/j.issn.1000-5641.2024.03.009
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    The Gross-Pitaevskii equation is widely applied in Bose-Einstein condensate research, yet is rarely analytically determined; thus, it is important to develop a numerical method with high precision to resolve this. Accordingly, a numerical method was developed in this work, considering the splitting step method, Crank-Nicolson algorithm, and Numerov algorithm with four-order accuracy. The corresponding test shows that compared with the finite difference method using five points, the proposed algorithm is more efficient and costs less memory.

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    A case study on the application of the automatic labelling of the subject knowledge graph of Chinese large language models: Take morality and law and mathematics as examples
    Sijia KOU, Fengyun YAN, Jing MA
    Journal of East China Normal University(Natural Science)    2024, 2024 (5): 81-92.   DOI: 10.3969/j.issn.1000-5641.2024.05.008
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    With the rapid development of artificial intelligence technology, large language models (LLMs) have demonstrated strong abilities in natural language processing and various knowledge applications. This study examined the application of Chinese large language models in the automatic labelling of knowledge graphs for primary and secondary school subjects in particular compulsory education stage morality and law and high school mathematics. In education, the construction of knowledge graphs is crucial for organizing systemic knowledge . However, traditional knowledge graph methods have problems such as low efficiency and labor-cost consumption in data labelling. This study aimed to solve these problems using LLMs, thereby improving the level of automation and intelligence in the construction of knowledge graphs. Based on the status quo of domestic LLMs, this paper discusses their application in the automatic labelling of subject knowledge graphs. Taking morality and rule of law and mathematics as examples, the relevant methods and experimental results are explained. First, the research background and significance are discussed. Second, the development status of the domestic large language model and automatic labelling technology of the subject knowledge graph are then presented. In the methods and model section, an automatic labelling method based on LLMs is explored to improve its application in a subject knowledge graph. This study also explored the subject knowledge graph model to compare and evaluate the actual effect of the automatic labelling method. In the experiment and analysis section, through the automatic labelling experiments and results analysis of the subjects of morality and law and mathematics, the knowledge graphs of the two disciplines are automatically labeled to achieve high accuracy and efficiency. A series of valuable conclusions are obtained, and the effectiveness and accuracy of the proposed methods are verified. Finally, future research directions are discussed. In general, this study provides a new concept and method for the automatic labelling of subject knowledge graphs, which is expected to promote further developments in related fields.

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    A formal verification method for embedded operating systems
    Yang WANG, Jingcheng FANG, Xiong CAI, Zhipeng ZHANG, Yong CAI, Weikai MIAO
    Journal of East China Normal University(Natural Science)    2024, 2024 (4): 1-17.   DOI: 10.3969/j.issn.1000-5641.2024.04.001
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    The operating system is the core and foundation of the entire computer system. Its reliability and safety are vital because faults or vulnerabilities in the operating system can lead to system crashes, data loss, privacy breaches, and security attacks. In safety-critical systems, any errors in the operating system can result in significant loss of life and property. Ensuring the safety and reliability of the operating system has always been a major challenge in industry and academia. Currently, methods for verifying the operating system’s safety include software testing, static analysis, and formal methods. Formal methods are the most promising in ensuring the operating system’s safety and trustworthiness. Mathematical models can be established using formal methods, and the system can be formally analyzed and verified to discover potential errors and vulnerabilities. In the operating system, formal methods can be used to verify the correctness and completeness of the operating system’s functions and system safety. A formal scheme for embedded operating systems is proposed herein on the basis of existing formal verification achievements for operating systems. This scheme uses VCC (verified C compiler), CBMC (C bounded model checker), and PAT (process analysis toolkit) tools to verify the operating system at the unit, module, and system levels, respectively. The schema, upon being successfully applied to a task scheduling architecture case of a certain operating system, exhibits a certain universality for analyzing and verifying embedded operating systems.

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    OpenRank contribution evaluation method and empirical study in open-source course
    Jie WANG, Wenrui HUANG, Shengyu ZHAO, Xiaoya XIA, Fanyu HAN, Wei WANG, Yanbin ZHANG
    Journal of East China Normal University(Natural Science)    2024, 2024 (5): 11-19.   DOI: 10.3969/j.issn.1000-5641.2024.05.002
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    This study presents an OpenRank-based method for evaluating open-source contributions, designed to address the challenge of quantifying student contributions in open-source projects. Taking the “Open-Source Software Design and Development” course as a case study, we developed a method to assess student contributions in open-source practice. The OpenRank algorithm, which is based on developer collaboration networks, evaluates student contributions in discussions, problem-solving, and coding. Experimental results indicate that OpenRank not only aligns with traditional grading methods but also provides a more comprehensive view of student contributions. Combining OpenRank with traditional grading offers a more scientific and thorough evaluation of student contributions and skills in open-source projects.

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    Knowledge graph empowered object-oriented programming C++ teaching reform and practice
    Zhuang PEI, Xiuxia TIAN, Bingxue LI
    Journal of East China Normal University(Natural Science)    2024, 2024 (5): 104-113.   DOI: 10.3969/j.issn.1000-5641.2024.05.010
    Abstract302)   HTML4)    PDF(pc) (3157KB)(282)       Save

    Against the backdrop of the national new engineering education initiative, early C++ teaching has failed to meet the requirements of high-level sophistication, innovation, and challenges. Furthermore, issues such as fragmented knowledge points, difficulty in integrating theory with practice, and single-perspective bias are prevalent in this field. To address these problems, we propose an innovative teaching model that effectively integrates QT(Qt Toolkit) and C++ by merging the two courses. This model facilitates the teaching process via a course knowledge graph deployed on the Zhihuishu platform. The breadth of teaching is expanded by effectively linking course knowledge points, integrating and sharing multimodal teaching resources, enhancing multiperspective learning, showcasing the course’s innovative nature, and avoiding single-perspective bias. Simultaneously, the depth of teaching is increased through the construction of a knowledge graph that integrates QT and object-oriented programming (C++), organically combining the knowledge points of both courses. This approach bridges the gap between theory and practice by enhancing the course’s sophistication and level of challenge. Consequently, this study pioneers the reform of C++ teaching by providing valuable references and insights for programming courses under the new engineering education framework.