Review of automatic data processing developments in the Federal Government.

Mode of access: Internet.

Management information systems : user's guide for indentifying automatic data processing equipment (ADPE) requirements.

Issued Feb. 23, 1976.

Digest [of] automatic data processing; selected seminar presentations, interagency training programs.

Cover title.

Training and education programs in automatic data processing (ADP).

Mode of access: Internet.

Installing and using an automatic data processing system; a case study for management.

Mode of access: Internet.

Company investigations of automatic data processing.

Mode of access: Internet.

Automatic data-processing systems;

Mode of access: Internet.

Considerations in the selection of security measures for automatic data processing systems /

"Contributed to the Federal Information Processing Standards Task Group 15 - Computer Systems Security" -t.p.

An architecture of internet based data processing based on multicast and anycast protocols

Most of the current web-based application systems suffer from poor performance and costly heterogeneous accessing. Distributed or replicated strategies can alleviate the problem in some degree, but there are still some problems of the distributed or replicated model, such as data synchronization, load balance, and so on.  In this paper, we propose a novel architecture for Internet-based data processing system based on multicast and anycast protocols. The proposed architecture breaks the functionalities of existing data processing system, in particular, the database functionality, into several agents. These agents communicate with each other using multicast and anycast mechanisms. We show that the proposed architecture provides better scalability, robustness, automatic load balance, and performance than the current distributed architecture of Internet-based data
processing.

Automatic Data Normalization and Parameterization for Optical Motion Tracking

Methods for optical motion capture often require timeconsuming manual processing before the data can be used for subsequent tasks such as retargeting or character animation. These processing steps restrict the applicability of motion capturing especially for dynamic VR-environments with real time requirements. To solve these problems, we present two additional, fast and automatic processing stages based on our motion capture pipeline presented in [HSK05]. A normalization step aligns the recorded coordinate systems with the skeleton structure to yield a common and intuitive data basis across different recording sessions. A second step computes a parameterization based on automatically extracted main movement axes to generate a compact motion description. Our method does not restrict the placement of marker bodies nor the recording setup, and only requires a short calibration phase.