Artificial Intelligence

1204 Submissions

[3] viXra:1204.0081 [pdf] submitted on 2012-04-18 13:14:24

Erasure Techniques in MRD Codes

Authors: W. B. Vasantha Kandasamy, Florentin Smarandache, R. Sujatha, R. S. Raja Duray
Comments: 162 Pages.

In this book the notions of erasure techniques to MRD codes and concatenated MRD codes are introduced. Special type of concatenated supercodes using linear codes are given, which may find its application in networking.
Category: Artificial Intelligence

[2] viXra:1204.0080 [pdf] submitted on 2012-04-18 13:24:29

The Fifth Function of University: “Neutrosophic e-Function” of Communication-Collaboration-Integration of University in the Information Age

Authors: Florentin Smarandache, Stefan Vladutescu
Comments: 18 Pages.

The study is based on the following hypothesis with practical foundation: - Premise 1 - if two members of university on two continents meet on the Internet and initiate interdisciplinary scientific communication; - Premise 2 - subsequently, if within the curricular interests they develop an academic scientific collaboration; - Premise 3 - if the so-called collaboration integrates the interests of other members of the university; - Premise 4 - finally, if the university allows, accepts, validates and promotes such an approach; - Conclusion: then it means the university as a system (the global academic system) has, and it is, exerting a potential function to provide communication, collaboration and integration of research and of academic scientific experience.
Category: Artificial Intelligence

[1] viXra:1204.0002 [pdf] replaced on 2012-12-18 22:39:33

Correction of Inertial Navigation System's Errors by the Help of Video-Based Navigator Based on Digital Terrarium Map

Authors: Kupervasser O. Yu., Voronov V.V.

This paper deals with the error analysis of a novel navigation algorithm that uses as input the sequence of images acquired from a moving camera and a Digital Terrain (or Elevation) Map (DTM/DEM). More specifically, it has been shown that the optical flow derived from two consecutive camera frames can be used in combination with a DTM to estimate the position, orientation and ego-motion parameters of the moving camera. As opposed to previous works, the proposed approach does not require an intermediate explicit reconstruction of the 3D world. In the present work the sensitivity of the algorithm outlined above is studied. The main sources for errors are identified to be the optical-flow evaluation and computation, the quality of the information about the terrain, the structure of the observed terrain and the trajectory of the camera. By assuming appropriate characterization of these error sources, a closed form expression for the uncertainty of the pose and motion of the camera is first developed and then the influence of these factors is confirmed using extensive numerical simulations. The main conclusion of this paper is to establish that the proposed navigation algorithm generates accurate estimates for reasonable scenarios and error sources, and thus can be effectively used as part of a navigation system of autonomous vehicles.
Category: Artificial Intelligence