基于支持向量机的铁谱磨粒自动识别

为了实现支持向量机对磨损磨粒的自动识别,首先对彩色磨粒图像进行图像处理,运用 K －均值聚类、区域生长法和数学形态学将磨粒成功地从图像中分割出来;其次根据各类磨粒形貌特征确定磨粒的形状尺寸、纹理特征和颜色特征参数,并采用相应的方法提取这三方面的参数;由于支持向量机参数的选取对其分类效果影响很大,所以采用遗传算法对其参数做进一步的优化;最后以提取的特征参数为基础,运用优化的支持向量机成功地识别了严重滑动磨粒、球形磨粒、切削磨粒、疲劳磨粒和红色氧化物五类特征磨粒,其识别准确率达90％。结果表明该方法切实可行。     

数控机床定位精度补偿技术(英文)

通过分析多体系统中典型体的基本变换关系,引入相邻体的位置变换和位移变换误差矩阵,运用多体系统运动学提出数控机床定位误差的通用模型,利用８０３１单片机系统开发了智能误差补偿控制器．在ＸＨ７１４加工中进行的一系列实验表明,机床的定位精度提高５０％以上．     

材料试验仪器设备的安全保护

通过试验教学和科学研究的几点认识,提出试验仪器的安全保护值得引起重视的问题,并阐述对仪器设备完好率的提高和教学科研的顺利开展有很大作用     

From substitution to redefinition: A framework of machine learning-based science assessment

This study develops a framework to conceptualize the use and evolution of machine learning (ML) in science assessment. We systematically reviewed 47 studies that applied ML in science assessment and classified them into five categories: (a) constructed response, (b) essay, (c) simulation, (d) educational game, and (e) inter-discipline. We compared the ML-based and conventional science assessments and extracted 12 critical characteristics to map three variables in a three-dimensional framework: construct, functionality, and automaticity. The 12 characteristics used to construct a profile for ML-based science assessments for each article were further analyzed by a two-step cluster analysis. The clusters identified for each variable were summarized into four levels to illustrate the evolution of each. We further conducted cluster analysis to identify four classes of assessment across the three variables. Based on the analysis, we conclude that ML has transformed—but not yet redefined—conventional science assessment practice in terms of fundamental purpose, the nature of the science assessment, and the relevant assessment challenges. Along with the three-dimensional framework, we propose five anticipated trends for incorporating ML in science assessment practice for future studies: addressing developmental cognition, changing the process of educational decision making, personalized science learning, borrowing 'good' to advance 'good', and integrating knowledge from other disciplines into science assessment.     

Utilizing statistical physics and machine learning to discover collective behavior on temporal social networks

Computational social science has become a branch of social science that uses computationally intensive ways to investigate and model social phenomena. Exploitation on mathematics, physics, and computer sciences, and analytic approaches like Social Network Analysis (SNA), Machine Learning (ML), etc, develops and tests the theories of complex social phenomena. In the emerging environment of social media, the new characteristics of social collective behavior and its extensive phenomena have become the hot spot of common concern across many disciplines. In this paper, we propose a general quantitative framework to discover the social collective behavior in temporal social networks. The general framework incorporates the Time-Correlation Function (T.C.F.) in statistical physics and evolutionary approach in Machine Learning, and provides the quantitative evidence of the existence of social collective behavior. Results show collective behaviors are observed and there exists a tiny fraction of users whose behavior are constantly replicated by public, disregard of the behavior itself. Our method is assumption-independent and has the potential to be applied to various temporal systems.     

一种基于参数污点分析的软件行为模型

基于细粒度二进制动态分析平台,提出通过系统调用参数的污点分析构建软件行为模型的方法。该方法主要在指令级别监控应用程序运行,跟踪系统调用参数的污点传播获取参数与参数、局部变量和外部数据之间的关联关系,进而抽取出参数的污点传播链。其次,基于参数污点传播链和系统调用序列构造能够同时反映控制流和数据流特性的软件动态行为模型。最后,分析和验证该模型具备检测隐秘的非控制流数据攻击的能力。     

机械原理课程双语教学的研究与探索

本文分析了双语教学的必要性和重要性,并结合机械原理课程双语教学的教学实践,就双语教学的定位、教学模式、教材选用、教学内容、教学方法和多媒体课件制作等方面进行了研究与探索,为进一步提高双语教学的质量提供了实践经验和有益的参考。     

关于支持向量回归机的模型选择

支持向量机是在统计学习理论基础上发展起来的一种新型的机器学习方法。模型选择是设计支持向量机的重要内容之一。本文在分析用于回归的支持向量机原理的基础上,分别从核函数的选择、模型参数的作用、模型参数的调整方法等模型选择方面进行了综述,并讨论了模型选择的优缺点,最后指出在实际应用中常见的核函数和模型参数调整方法。     

基于稀疏RAM的N-tuple神经网络的足球机器人识别法

提出了一种采用稀疏RAM的N-tuple神经网络(SN-tuple)的方法,用在足球机器人比赛时,根据图像快速识别队员。通过大量实验证明,该方法有效地解决了传统BP神经网络收敛速度慢、易陷入局部最小值的问题,对机器人队员和足球位置的识别稳定可靠。     

S7-300在红外热风回流焊机温控系统中的应用

本文介绍了红外热风回流焊机的应用情况及系统结构,以及用西门子S7-300PLC作主控制器、TP270触摸屏作人机界面系统的温度控制的软硬件设计方法。