The .NET Design Pattern Framework 4.5 is actually 10 products in one -- each filled with .NET code and information you will not find anywhere else -- and each working together, ready to give your apps, your projects, and your career a boost. They are: 69 Comprehensive .NET 4.5 GoF Design Pattern Projects 23 Valuable UML Diagrams in Visio format 3-Tier / N-Tier Pattern and Practices based Architectures Reference Application: ASP.NET MVC Patterns Reference Application: ASP.NET Web Forms Patterns Reference Application: Windows Forms Patterns Reference Application: WPF Patterns NEW Art Shop -- A fully functional, real-world e-commerce Web App NEW SparkTM -- A rapid application development (RAD) platform & more... Printable PDF documents for all Projects & Patterns Our most recent release, Design Pattern Framework 4.5, has been enhanced with the latest insights into building apps using modern architectures, patterns, and best practices. These include MVC 4, SimpleMembership, OAuth with Facebook, REST, Active Record Pattern, CQRS Pattern, Repository and Unit-of-Work Patterns, and more. We're particularly excited about the addition of our new SparkTM technology. Spark is a RAD (rapid application development) platform that helps you deliver .NET applications faster and better than ever before. Continue reading to learn more.

Spring 5 Design Patterns. PDF format. Spring 5 Design Patterns is for all Java developers who want to learn Spring for the enterprise application. Therefore, enterprise Java developers will find it particularly useful in the understanding of design patterns used by the Spring Framework and how it solves common design problems in the enterprise application, and they will fully appreciate the examples presented in this book. Before reading this book, readers should have basic knowledge of Core Java, JSP, Servlet, and XML.

High-quality 3D shape measurement using saturated fringe patterns

一般的加权顺序模式挖掘算法会忽略或没有充分利用时间和数据元素的时间间隔信息。 除了某些算法需要扫描数据库外时间或建立临时数据库。 为了解决这些问题，我们提出了一种基于内存的算法MITWCSpan（用于时间间隔加权封闭式顺序模式挖掘的内存索引），用于区间加权封闭顺序模式挖掘。 该算法充分考虑了重要性数据元素的时间间隔。 此外，基于时间间隔p-tidx的改进索引集是定义。 在挖掘过程中，该算法递归采用“查找-然后-索引”技术来查找可以构成时间间隔加权顺序模式并构造p-tidx的项目可能的顺序模式。 最后，算法使用闭合检测得到整个时间间隔加权封闭顺序模式。 实验结果表明，该算法更加有效。 寻找更重要的顺序模式。