Quartz is a full-featured, open source job scheduling system that can be integrated with, or used along side virtually any J2EE or J2SE application - from the smallest stand-alone application to the largest e-commerce system. Quartz can be used to create simple or complex schedules for executing tens, hundreds, or even tens-of-thousands of jobs jobs whose tasks are defined as standard Java components or EJBs. The Quartz Scheduler includes many enterprise-Class features, such as JTA transactions and clustering. Quartz is freely usable, licensed under the Apache 2.0 license.
Class="tags">标签： full-featured integrated scheduling Quartz
Class="time">上传时间： 2017-08-07
Class="username">上传用户：来茴
Libsvm is a simple, easy-to-use, and efficient software for SVM Classification and regression. It solves C-SVM Classification, nu-SVM Classification, one-Class-SVM, epsilon-SVM regression, and nu-SVM regression. It also provides an automatic model selection tool for C-SVM Classification. This document explains the use of libsvm.
Class="tags">标签： Classification easy-to-use regression and
Class="time">上传时间： 2013-12-21
Class="username">上传用户：zuozuo1215
Abstract—Stable direct and indirect decentralized adaptive radial basis neural network controllers are presented for a Class of interconnected nonlinear systems. The feedback and adaptation mechanisms for each subsystem depend only upon local measurements to provide asymptotic tracking of a reference trajectory. Due to the functional approximation capabilities of radial basis neural networks, the dynamics for each subsystem are not required to be linear in a set of unknown coeffi cients as is typically required in decentralized adaptive schemes. In addition, each subsystem is able to adaptively compensate for disturbances and interconnections with unknown bounds.
Class="tags">标签： decentralized controllers Abstract adaptive
Class="time">上传时间： 2017-08-17
Class="username">上传用户：gdgzhym
SVM 软件包，可以解决分类问题（包括C- SVC、n - SVC ）、回归问题（包括e - SVR、n - SVR ）以及分布估计（one-Class-SVM ）等问题
Class="time">上传时间： 2014-01-05
Class="username">上传用户：shizhanincc
NetGUI v0.4.1 INSTALL Instructions Pedro de las Heras Quiros pheras@gmail.com 1. Install netkit (www.netkit.org) 2. Compile src/*java 3. mv src/*Class bin 4. Edit and adapt bin/netgui.sh 5. Run bin/netgui.sh
Class="tags">标签： Instructions INSTALL NetGUI Pedro
Class="time">上传时间： 2013-12-20
Class="username">上传用户：虫虫虫虫虫虫
何使用? 工厂模式是我们最常用的模式了,著名的Jive论坛 ,就大量使用了工厂模式，工厂模式在Java程序系统可以说是随处可见。 为什么工厂模式是如此常用？因为工厂模式就相当于创建实例对象的new，我们经常要根据类Class生成实例对象，如A a=new A() 工厂模式也是用来创建实例对象的，所以以后new时就要多个心眼，是否可以考虑实用工厂模式，虽然这样做，可能多做一些工作，但会给你系统带来更大的可扩展性和尽量少的修改量。
Class="tags">标签： Jive 模式 工厂 论坛
Class="time">上传时间： 2014-12-06
Class="username">上传用户：qoovoop
A generic widestring list for use in all versions of Delphi. It has all the capabilities you find in the TStrings Class, can be sorted etc. Suitable for persistent storage.
Class="tags">标签： capabilities widestring all versions
Class="time">上传时间： 2013-12-26
Class="username">上传用户：hn891122
│ .Classpath │ .project │ 404.html │ index.html │ welcome.html │ ├─bin │ └─com │ └─accp │ └─demo │ └─socket │ Client.Class │ HttpServer.Class │ Server.Class │ └─src └─com └─accp └─demo └─socket Client.java HttpServer.java Server.java
Class="tags">标签： html Classpath project welcome
Class="time">上传时间： 2013-12-19
Class="username">上传用户：csgcd001
library for SVMClassification and regression. It solves C-SVM Classification, nu-SVM Classification, one-Class-SVM, epsilon-SVM regression, and nu-SVM regression. It also provides an automatic model selection tool for C-SVM Classification.
Class="tags">标签： Classification SVMClassification regression library
Class="time">上传时间： 2013-12-21
Class="username">上传用户：thuyenvinh
The object detector described below has been initially proposed by P.F. Felzenszwalb in [Felzenszwalb2010]. It is based on a Dalal-Triggs detector that uses a single filter on histogram of oriented gradients (HOG) features to represent an object category. This detector uses a sliding window approach, where a filter is applied at all positions and scales of an image. The first innovation is enriching the Dalal-Triggs model using a star-structured part-based model defined by a “root” filter (analogous to the Dalal-Triggs filter) plus a set of parts filters and associated deformation models. The score of one of star models at a particular position and scale within an image is the score of the root filter at the given location plus the sum over parts of the maximum, over placements of that part, of the part filter score on its location minus a deformation cost easuring the deviation of the part from its ideal location relative to the root. Both root and part filter scores are defined by the dot product between a filter (a set of weights) and a subwindow of a feature pyramid computed from the input image. Another improvement is a representation of the Class of models by a mixture of star models. The score of a mixture model at a particular position and scale is the maximum over components, of the score of that component model at the given location.
Class="tags">标签： 计算机视觉
Class="time">上传时间： 2015-03-15
Class="username">上传用户：sb_zhang
