通过传授知识来培养学生解决问题的能力是课程教学乃至教育永恒不变宗旨。在人工智能技术浪潮下,知识传播手段的变革、知识体系结构的更新成为了新时期我国教育发展尤其是课程教学改革需要面对的机遇与挑战。为应对上述挑战,教师需要合...通过传授知识来培养学生解决问题的能力是课程教学乃至教育永恒不变宗旨。在人工智能技术浪潮下,知识传播手段的变革、知识体系结构的更新成为了新时期我国教育发展尤其是课程教学改革需要面对的机遇与挑战。为应对上述挑战,教师需要合理使用人工智能工具,在课程教学设计上以“促进融合、加强理解”为指导原则,不断提升课程内容的广度和深度。一方面,通过跨学科交叉融合的教学方式培养学生跨学科的视野和融会贯通的思维方式,从而具备从不同学科的角度看待和解决问题的能力。另一方面,教师的核心职责从信息层次的知识传授转变为理解层次的启发式探讨,重点在于培养学生的批判性思维和创新能力。The enduring goal of curriculum teaching and education is to cultivate students’ problem-solving abilities through the dissemination of knowledge. In the wave of artificial intelligence technology, the transformation of knowledge dissemination methods and the updating of knowledge system structures present both opportunities and challenges for the development of education in China, particularly in the context of curriculum reform. To address these challenges, teachers need to effectively utilize artificial intelligence tools, guided by the principles of “promoting integration and enhancing understanding” in curriculum design, in order to continually broaden and deepen the course content. On one hand, interdisciplinary teaching methods should be employed to foster students’ cross-disciplinary perspectives and integrative thinking, enabling them to view and solve problems from various academic angles. On the other hand, the core responsibility of teachers is shifting from the transmission of knowledge at the information level to heuristic discussions at the understanding level, with a focus on cultivating students’ critical thinking and innovative capabilities.展开更多
密集场景下群株生菜的有效分割与参数获取是植物工厂生长监测中的关键环节。针对群株生菜中个体生菜鲜质量提取问题,该研究提出一种利用实例分割模型提取个体生菜点云,再以深度学习点云算法预测个体鲜质量的方法。该方法以群株生菜为研...密集场景下群株生菜的有效分割与参数获取是植物工厂生长监测中的关键环节。针对群株生菜中个体生菜鲜质量提取问题,该研究提出一种利用实例分割模型提取个体生菜点云,再以深度学习点云算法预测个体鲜质量的方法。该方法以群株生菜为研究对象,利用深度相机采集群株生菜俯视点云,将预处理后的点云数据输入实例分割模型Mask3D中训练,实现背景与生菜个体的实例分割,之后使用鲜质量预测网络预测个体生菜鲜质量。试验结果表明,该模型实现了个体生菜点云的分割提取,无多检和漏检的情况。当交并比(intersection over union,IoU)阈值为0.75时,群株生菜点云实例分割的精确度为0.924,高于其他实例分割模型;鲜质量预测网络实现了直接通过深度学习处理点云数据,预测个体生菜鲜质量的目的,预测结果的决定系数R2值为0.90,均方根误差值为12.42 g,优于从点云中提取特征量,再回归预测鲜质量的传统方法。研究结果表明该研究预测生菜鲜质量的精度较高,为利用俯视单面点云提取群株生菜中个体生菜表型参数提供了一种思路。展开更多
工程实践限定了信号的因果性,物理可实现性要求系统满足因果性,因此系统分析通常隐含遵循因果律。同时,系统起初绝对静止是系统分析的另一个基本假设。基于这两个条件,结合具体案例,阐明初始条件的物理意义,揭示零状态响应概念的本质,...工程实践限定了信号的因果性,物理可实现性要求系统满足因果性,因此系统分析通常隐含遵循因果律。同时,系统起初绝对静止是系统分析的另一个基本假设。基于这两个条件,结合具体案例,阐明初始条件的物理意义,揭示零状态响应概念的本质,并推导卷积分解方法的合理性。研究结果不仅丰富了相关理论内容,为教材编写提供了参考和补充,也对研究方法优化、课程思政设计和教学方法创新具有重要启示。Engineering practice constrains signals to causality, and physical realizability requires systems to adhere to causality, making causality an implicit assumption in system analysis. Additionally, the assumption of an initially quiescent system serves as another fundamental premise for system analysis. Based on these two conditions, this study, through specific cases, elucidates the physical significance of initial conditions, reveals the essence of the zero-state response, and derives the rationality of the convolution decomposition approach. The findings not only enrich relevant theoretical content and provide references and supplements for textbook development but also offer valuable insights for optimizing research methods, designing curriculum ideologies, and innovating teaching approaches.展开更多
叠加性和均匀性是《信号与系统》课程中的核心概念,是理解线性特性和判断线性系统的基础。然而,现有教材中普遍缺乏具备叠加性但不具备均匀性,以及具备均匀性但不具备叠加性的具体实例。教学实验结果显示,学生对这两个概念的理解普遍存...叠加性和均匀性是《信号与系统》课程中的核心概念,是理解线性特性和判断线性系统的基础。然而,现有教材中普遍缺乏具备叠加性但不具备均匀性,以及具备均匀性但不具备叠加性的具体实例。教学实验结果显示,学生对这两个概念的理解普遍存在不足。对叠加性和均匀性的关系进行了研究,证明了实数域内叠加性蕴含均匀性的结论,并构造了两类非线性系统实例。研究结果丰富了现有教材内容,提示教学过程中有必要加强探究性与启发式的讨论。Superposition and homogeneity are core concepts in the “Signals and Systems” course, forming the foundation for understanding linear properties and identifying linear systems. However, current textbooks generally lack specific examples that demonstrate systems possessing superposition but not homogeneity, or vice versa. Teaching experiments reveal a widespread deficiency in students’ comprehension of these two concepts. This study explores the relationship between superposition and homogeneity, proving that superposition implies homogeneity in the real domain, and presents two types of nonlinear system examples. The findings supplement existing textbook content and highlight the need for inquiry-based, heuristic discussions in the teaching process.展开更多
文摘通过传授知识来培养学生解决问题的能力是课程教学乃至教育永恒不变宗旨。在人工智能技术浪潮下,知识传播手段的变革、知识体系结构的更新成为了新时期我国教育发展尤其是课程教学改革需要面对的机遇与挑战。为应对上述挑战,教师需要合理使用人工智能工具,在课程教学设计上以“促进融合、加强理解”为指导原则,不断提升课程内容的广度和深度。一方面,通过跨学科交叉融合的教学方式培养学生跨学科的视野和融会贯通的思维方式,从而具备从不同学科的角度看待和解决问题的能力。另一方面,教师的核心职责从信息层次的知识传授转变为理解层次的启发式探讨,重点在于培养学生的批判性思维和创新能力。The enduring goal of curriculum teaching and education is to cultivate students’ problem-solving abilities through the dissemination of knowledge. In the wave of artificial intelligence technology, the transformation of knowledge dissemination methods and the updating of knowledge system structures present both opportunities and challenges for the development of education in China, particularly in the context of curriculum reform. To address these challenges, teachers need to effectively utilize artificial intelligence tools, guided by the principles of “promoting integration and enhancing understanding” in curriculum design, in order to continually broaden and deepen the course content. On one hand, interdisciplinary teaching methods should be employed to foster students’ cross-disciplinary perspectives and integrative thinking, enabling them to view and solve problems from various academic angles. On the other hand, the core responsibility of teachers is shifting from the transmission of knowledge at the information level to heuristic discussions at the understanding level, with a focus on cultivating students’ critical thinking and innovative capabilities.
文摘密集场景下群株生菜的有效分割与参数获取是植物工厂生长监测中的关键环节。针对群株生菜中个体生菜鲜质量提取问题,该研究提出一种利用实例分割模型提取个体生菜点云,再以深度学习点云算法预测个体鲜质量的方法。该方法以群株生菜为研究对象,利用深度相机采集群株生菜俯视点云,将预处理后的点云数据输入实例分割模型Mask3D中训练,实现背景与生菜个体的实例分割,之后使用鲜质量预测网络预测个体生菜鲜质量。试验结果表明,该模型实现了个体生菜点云的分割提取,无多检和漏检的情况。当交并比(intersection over union,IoU)阈值为0.75时,群株生菜点云实例分割的精确度为0.924,高于其他实例分割模型;鲜质量预测网络实现了直接通过深度学习处理点云数据,预测个体生菜鲜质量的目的,预测结果的决定系数R2值为0.90,均方根误差值为12.42 g,优于从点云中提取特征量,再回归预测鲜质量的传统方法。研究结果表明该研究预测生菜鲜质量的精度较高,为利用俯视单面点云提取群株生菜中个体生菜表型参数提供了一种思路。
文摘工程实践限定了信号的因果性,物理可实现性要求系统满足因果性,因此系统分析通常隐含遵循因果律。同时,系统起初绝对静止是系统分析的另一个基本假设。基于这两个条件,结合具体案例,阐明初始条件的物理意义,揭示零状态响应概念的本质,并推导卷积分解方法的合理性。研究结果不仅丰富了相关理论内容,为教材编写提供了参考和补充,也对研究方法优化、课程思政设计和教学方法创新具有重要启示。Engineering practice constrains signals to causality, and physical realizability requires systems to adhere to causality, making causality an implicit assumption in system analysis. Additionally, the assumption of an initially quiescent system serves as another fundamental premise for system analysis. Based on these two conditions, this study, through specific cases, elucidates the physical significance of initial conditions, reveals the essence of the zero-state response, and derives the rationality of the convolution decomposition approach. The findings not only enrich relevant theoretical content and provide references and supplements for textbook development but also offer valuable insights for optimizing research methods, designing curriculum ideologies, and innovating teaching approaches.
文摘叠加性和均匀性是《信号与系统》课程中的核心概念,是理解线性特性和判断线性系统的基础。然而,现有教材中普遍缺乏具备叠加性但不具备均匀性,以及具备均匀性但不具备叠加性的具体实例。教学实验结果显示,学生对这两个概念的理解普遍存在不足。对叠加性和均匀性的关系进行了研究,证明了实数域内叠加性蕴含均匀性的结论,并构造了两类非线性系统实例。研究结果丰富了现有教材内容,提示教学过程中有必要加强探究性与启发式的讨论。Superposition and homogeneity are core concepts in the “Signals and Systems” course, forming the foundation for understanding linear properties and identifying linear systems. However, current textbooks generally lack specific examples that demonstrate systems possessing superposition but not homogeneity, or vice versa. Teaching experiments reveal a widespread deficiency in students’ comprehension of these two concepts. This study explores the relationship between superposition and homogeneity, proving that superposition implies homogeneity in the real domain, and presents two types of nonlinear system examples. The findings supplement existing textbook content and highlight the need for inquiry-based, heuristic discussions in the teaching process.
