手册是 Rockwell 关于PackML应用指导，前面介绍了运动控制的设计，接线，编程等必要信息，附录具体介绍了PackML编程应用。 State model programming provides a way to execute processing procedures based on machine conditions, but independent of the direct equipment control logic. This is an essential component to modular programming. The PackML 3.0 state model, a recognized standard in the packaging segment, is implemented in this example using an Add-On Instruction (AOI) that manages from 1…32 modes, each having its associated instance of the state model. The states may be enabled and disabled as required depending on the needs of the mode.

一个全 Java J2EE 家庭气象站和网站项目。 当前基于 Davis Weather Monitor II，但将发展为支持其他设备、服务器和数据库。 该项目已发展为完全开发的 Runy on Rails 解决方案。

prophesee公司在CVPR2019 workshop（第二届国际事件相机讨论会）中介绍的公司事件相机的相关资料。

对于理解渲染的各个部分，构建渲染器很有用，特别是在体渲染方面，提供了很详细的介绍。

干扰观测器论文

【中文版】architectural styles and the design of network-based software architectures

_一款基于网页游戏的游戏，使用网页浏览器、iPhone 和安卓手机在互联网上播放。 _这是一款大型多人即时战略网页游戏，背景设定在公元前 111 年至公元前 602 年的越南战争中。玩家在僻静的土地上扮演将军或国王的角色，并建立自己的资源，建立军队并攻击城堡、村庄的另一名球员。 _本游戏有2个版本：iOS和Android

生物识别技术是一个新兴的技术领域，它使用独特且可测量的物理、生物或行为特征，可以对其进行处理以识别一个人。 人类的生物特征是指纹、虹膜、面部和声音。 生物识别技术的简明定义是“使用不同特征自动识别人”。 语音是生物特征之一，它是作为声音序列产生的。 声带的振动，以及各种咬合器（如舌头、嘴唇和牙齿）的位置、形状和大小都会产生所产生的声音。声音的特征因人而异，可以用于识别个人。 虽然通常认为不如其他类型的生物识别系统准确，但语音识别系统可以与其他生物识别系统结合使用，以创建更强大的识别系统说话人识别主要涉及特征提取和特征匹配两个模块。 特征提取是从说话者的语音信号中提取少量数据的过程，这些数据稍后可以用来代表该说话者。 特征匹配涉及通过将从他/她的语音输入中提取的特征与已经存储在我们的语音数据库中的特征进行比较来识别未知说话者的实际过程。 在特征提取中，我们找到梅尔频率倒谱系数 (MFCC)，

The advent of widespread fast computing has enabled us to work on more complex problems and to build and analyze more complex models. This book provides an introduction to one of the primary methodologies for research in this new field of knowledge. Agent-based modeling (ABM) offers a new way of doing science: by conducting computer-based experiments. ABM is applicable to complex systems embedded in natural, social, and engineered contexts, across domains that range from engineering to ecology. An Introduction to Agent-Based Modeling offers a comprehensive description of the core concepts, methods, and applications of ABM. Its hands-on approach -- with hundreds of examples and exercises using NetLogo -- enables readers to begin constructing models immediately, regardless of experience or discipline. The book first describes the nature and rationale of agent-based modeling, then presents the methodology for designing and building ABMs, and finally discusses how to utilize ABMs to answer complex questions. Features in each chapter include step-by-step guides to developing models in the main text; text boxes with additional information and concepts; end-of-chapter explorations; and references and lists of relevant reading. There is also an accompanying website with all the models and code. Table of Contents Chapter 0 Why Agent-Based Modeling? Chapter 1 What Is Agent-Based Modeling? Chapter 2 Creating Simple Agent-Based Models Chapter 3 Exploring and Extending Agent-Based Models Chapter 4 Creating Agent-Based Models Chapter 5 The Components of Agent-Based Modeling Chapter 6 Analyzing Agent-Based Models Chapter 7 Verification, Validation, and Replication Chapter 8 Advanced Topics and Applications Appendix: The Computational Roots of Agent-Based Modeling

这篇论文是Breunig于2000年发表在Proc. ACM SIGMOD 2000 Int. Conf. On Management of Data的关于LOF算法的经典论文，需要了解该算法的同学可以详细读一读。