RTX51 TINY Version 2 has been completly restructured to gain flexiblity,
accelarate performance, and reduce code/data space Requirements. Also
several new features are added to this popular Real-Time Kernal.
Quality control of production has always been a necessity
in stainless steel mills. The users of stainless
steel set ever-increasing Requirements on product
quality. Many material properties can still only be
measured in laboratory but more and more measurements
are now made on-line during the production.
Especially surface defects have to be detected on-line
with a surface inspection system because of their random
appearance.
The FM24C256/C256L/C256LZ devices are 256 Kbits CMOS
nonvolatile electrically erasable memory. These devices offer the
designer different low voltage and low power options. They
conform to all Requirements in the Extended IIC 2-wire protocol.
Furthermore, they are designed to minimize device pin count and
simplify PC board layout Requirements.
The XC226x derivatives are high-performance members of the Infineon XC2000 Family
of full-feature single-chip CMOS microcontrollers. These devices extend the functionality
and performance of the C166 Family in terms of instructions (MAC unit), peripherals, and
speed. They combine high CPU performance (up to 80 million instructions per second)
with extended peripheral functionality and enhanced IO capabilities. Optimized
peripherals can be adapted flexibly to meet the application Requirements. These
derivatives utilize clock generation via PLL and internal or external clock sources. Onchip
memory modules include program Flash, program RAM, and data RAM.
The Linux GPIB Package is a support package for GPIB (IEEE 488) hardware. The package contains kernel driver modules, and a C user-space library with Guile, Perl, PHP, Python and TCL bindings. The API of the C library is intended to be compatible with National Instrument s GPIB library. The Linux GPIB Package is licensed under the GNU General Public License .
Requirements:
Linux kernel version 2.4.x (use Linux-GPIB version 3.1.x). Earlier kernel versions are not supported.
The purpose of this document is to define the format of the messages and data being
communicated between microprocessors used in heavy-duty vehicle applications. It is meant to serve as a
guide toward a standard practice to promote software compatibility among microcomputer based modules.
This document is to be used with SAE J1708. SAE J1708 defines the Requirements for the hardware and
basic protocol that is needed to implement this document.
isual Chat 1.91 Developer Edition
- Customize the Visual Chat code regarding your own Requirements
- Use customchatdev.html for developing / testing
- Create .jar and .cab-files containing client-specific .class-files and the images-folder (use zip and cabarc compressing tools)
- Adapt the customchat.html file
- Upload all the files to your webserver
- Start the ChatServer by invoking java at.ac.uni_linz.tk.vchat.ChatServer [port [server-key]] from your commandline
- I kindly ask you to leave copyright and credit information in the InfoPanel.class as it is - but you are invited to add your own text. In case of violations I will consider excluding this class from the source in the future.
利用java實現文件的AES加密功能
This Java AES Crypt package contains the Java class es.vocali.util.AESCrypt, which provides file encryption and decryption using aescrypt file format.
Requirements
The Java AES Crypt package only works in Java 6, but can be easily adapted to Java 5 by replacing the call to NetworkInterface.getHardwareAddress() with something else.
In order to use 256 bit AES keys, you must download and install "Java Cryptography Extension (JCE) Unlimited Strength Jurisdiction Policy Files" from http://java.sun.com/javase/downloads/index.jsp
In this paper, we describe the development of a rapidly reconfigurable system in which the users’ tacit knowledge and Requirements are
elicited via a process of Interactive Evolution, finding the image processing parameters to achieve the required goals without any need for
specialised knowledge of the machine vision system. We show that the resulting segmentation can be quickly and easily evolved from
scratch, and achieves detection rates comparable to those of a hand-tuned system on a hot-rolled steel defect recognition problem.
