Download software tagged by free activex draw component

This data acquisition software component makes data acquisition and data collection easy! Automate data collection with devices like barcode readers, scanners, gauges and scales. For Visual Basic, C/C++, .NET, Excel, Access, Word, Delphi, IE and more

EDraw Flowchart ActiveX Control - Build flowchart applications with minimum time loss! Lets you quickly build basic flowcharts, organizational charts, business charts, hr diagram, work flowchart, programming flowchart and network design diagrams.

SkICMP ActiveX Control is a lightweight and powerful ICMP (Ping and Traceroute) ActiveX control that can be used for network diagnosing, troubleshooting, and monitoring. It can be used from any 32-bit Windows development environment.

The ActiveX Barcode Control and DLL is a component that generates graphic linear barcodes like Code 39, Code 128, GS1-128, UPC-A, UPC-E, EAN-8, EAN-13, Intelligent Mail and others, in any application that supports COM or ActiveX components.

Create professional quality bar codes with BarCodeWiz ActiveX.Insert it into your Word document, Access report, or Excel spreadsheet. Type your data into the Barcode field, and click Print

X360 Tiff Image & Fax Viewer ActiveX used to view and save image as Bmp, Emf, Gif, Jpeg, Png, multipaged Tiff, Wmf.Major functions include crop, flip, rotate, resize, scroll, zoom, draw text, print, grayscaled, blackwhite, clipboard, get tiff tags, hand & select tool

PDF Viewer Component is a light weight ActiveX Control which enables your application to display and interact with PDF files. It is identical to Adobe Reader program and adds high speed viewing of PDF documents to your applications easily.

Genetic System can be used to solve optimization problems. This component can be used to construct binary genetic system, it provides user with appropriate functionality to control the generation.

Artificial Neural System Component is designed for researchers in the fields of machine learning, it can be used to construct Back Propagation Neural Network and to train it with provided samples, then finally recall it with appropriate data.