步进电机细分技术在经济型数控机床中的应用

本文叙述了步进电机细分原理及微机控制系统，并将其应用于经济型数控铣床的横向进给伺服系统，有效提高了开环数控系统的定位精度。     

链式输送竹片软化机研究

简述了链式输送竹片软化机的设计指导思想和设计方案，重点介绍软化机的构成，参数的确定以及它的优点。     

加工硬质合金端铣刀刀槽时的工艺调整计算

硬质合金端铣刀刀体上的刀槽，通常将设计为槽底与铣刀轴线倾斜δ角，槽侧壁与铣刀轴线倾角为ω且偏移一个距离为ｅ，以使刀齿装夹在刀体上后获得端铣刀所需的几何角度。本文主要论述在万能铣床上铣削铣刀体上具有δ、ω、ｅ的刀槽时必要的工艺调整，利用矢量及座标转换推导了加工刀槽时必要的参数计算公式，为高效率、高质量地进行铣刀体刀槽的加工提供了一种精确可行的参数计算方法。     

虚拟机在操作系统开发中的应用研究

虚拟机是使用软件模拟的方法在电脑上模拟出来的计算机，利用它来开发OS软件能显著地缩短开发周期，降低开发难度。本文从实战出发，介绍了将虚拟机应用在OS开发实战中的应用方法。     

图G_i~(S*)(P,2(sum form j=1 to n)mj)的伴随多项式因式分解的图论方法及应用

通过研究图的伴随多项式的因式分解 ,给出了证明非色唯一图的一种新方法 ,并且得到了若干图簇的色等价图的结构性质     

统计模式识别的研究

模式识别的基本目标就是在有监督和无监督的情况下进行分类,在模式识别的各种模型中,基于统计的方法已经被广泛的研究并应用于实际.一些新的技术和方法的引入（神经网络和支持向量机方法）也促进了该领域发展,文章研究了基于统计的模式识别的进展情况,给出了模式识别的概念、原理、方法并对各种方法进行了相关的评述.     

基于CTV100平台的DPTV系统的研究与实现

从硬件和软件两方面详细阐述了基于CTV100平台的DPTV系统,并给出了总体设计框图和设计流程图。本项目采用意法半导体公司(ST)的CTV100解决方案,实现了对传统模拟电视信号的高效数字域处理,显著提高了电视画面的图像质量;并通过采用基于32bitCPU的OS20嵌入式操作系统,实现了多种传统模拟电视无法实现的功能。     

Distributed and Parallel Component Library

Software component library is the essential part of reuse-based software development. It is shown that making use of a single component library to store all kinds of components and from which components are searched is very inefficient. We construct multi-libraries to support software reuse and use PVM as development environments to imitate Iargescale computer, which is expected to fulfill distributed storage and parallel search of components efficiently and improve software reuse.     

提高西德MNPJ型毛圈圆纬机压针三角与舌针使用寿命的研究

本文通过西德MNPJ型毛圈圆纬机编织过程的受力分析和机械润滑试验,提出了提高三角和舌针使用寿命的途径;同时又对该机三角系统的材料进行了研究,提出了自制三角系统的看法。     

Learning attention-based strategies to cooperate for multi-agent path finding

Multi-agent path finding (MAPF) is a challenging multi-agent systems problem where all agents are required to effectively reach their goals concurrently with not colliding with each other and avoiding obstacles. In MAPF, it is a challenge to effectively express the observation of agents, utilize historical information, and effectively communicate with neighbor agents. To tackle these issues, in this work, we proposed a well-designed model that utilizes the local states of nearby agents and outputs an optimal action for each agent to execute. We build the local observation encoder by using residual attention CNN to extract local observations and use the Transformer architecture to build an interaction layer to combine local observations of agents. With the purpose of overcoming the deficiency of success rate, we also designed a new evaluation index, namely extra time rate (ETR). The experimental results show that our model is superior to most previous models in terms of success rate and ETR. In addition, we also completed the ablation study on the model, and the effectiveness of each component of the model was proved.