2.M1T专业工具

说明：  计算器小程序 简易的计算器代码 自学练习 python 代码程序(Self-learning Calculator Small Program Learning)

信息化是将来管理系统改进的主要方向 虽然电子化档案是重要的发展方向，但是实物档案也是重要的资产，特别是涉及保密内容时，两者同样重要 采用自动识别手段，提高操作效率是发展方向 实现档案在位监管，提高资产保全率是重要方向 减少实物档案的遗失等问题发生 从而避免财产损失，杜绝涉密事件的发生(Informatization is the main direction of the improvement of management system in the future. Although electronic archives are an important development direction, physical archives are also important assets, especially when it comes to confidentiality. Using automatic identification method to improve operational efficiency is the direction of development. It is an important direction to realize the supervision of archives in place and improve the asset preservation rate. Reduce the loss of physical files and other problems. So as to avoid property losses and eliminate secret incidents.)

说明：  UDDS工况下的电流数据，可以带入MATLAB中进行仿真。(Current data under UDDS conditions can be brought into MATLAB for simulation.)

说明：  超好用的网络抓包框架（Windivert） 主要有以下功能： 1、捕获网络数据包 2、筛选/丢弃网络数据包 3、嗅探网络数据包 4、(重新) 注入网络数据包 5、修改网络数据包 主要有以下特点：可抓包，修改包(Windivert The main functions are as follows: 1. Capturing Network Packets 2. Screening/Dropping Network Packets 3. Sniffing Network Packets 4. (Re) Injection of Network Packets 5. Modifying Network Packets The main features are as follows: can grab the package, modify the package)

各种公司小程序，优化办公，非常有用，让办公时间节省很多(Company Website Small Procedures)

说明：  使用卷积神经网络进行高光谱遥感数据分类，使用的数据源为Pavia University高光谱数据 文件夹log--日志文件夹，存放TensorBorad日志、网络参数文件、混淆矩阵图 文件夹Patch--存放数据处理的切片结果 文件夹PaviaU--高光谱数据下载存放位置 文件夹predicted--CNN对原始影像的分类结果 data.py--对原始高光谱影像进行数据处理，生成切片 net.py--神经网络模型 train.py--训练神经网络 utils.py--需要用到的函数 show.py--使用训练好的神经网络模型对原始数据进行分类(Using convolution neural network to classify hyperspectral remote sensing data, the data source is Pavia University hyperspectral data. Folder log -- Log folder, store TensorBorad logs, network parameter files, obfuscation matrix diagrams Folder Patch -- Stores slice results of data processing Folder PaviaU -- Place for Hyperspectral Data Download and Storage Folder predicted -- CNN classification results of original images Data.py -- Data processing of original hyperspectral images to generate slices Net.py--Neural Network Model Train.py--Training Neural Network Utils. py -- Functions to be used Show.py -- Classification of raw data using trained neural network model)

说明：  试验是结束后，计算上升曲线与下降曲线之间的偏差，并将计算结果显示出来(At the end of the test, the deviation between the ascending curve and the descending curve is calculated and the results are shown.)

说明：  网上书店SQL文件，里面以及包含数据以及两个视图，支持的数据库为mysql5.0及以上(SQL file of online bookstore, including data and two views. The supported database is mysql5.0 and above)

说明：  oculus usb adb driver 2.0