Theory and Algorithms Commons^™

Motion Characterization By Temporal Slices Analysis, Chong-Wah Ngo, Ting-Chuen Pong, Hong-Jiang Zhang, Roland T. Chin

Research Collection School Of Computing and Information Systems

This paper describes an approach to characterize camera and object motions based on the analysis of spatio temporal image volumes. In the spatio-temporal slices of image volumes, motion is depicted as oriented patterns. We propose a tensor histogram computation algorithm to represent these oriented patterns. The motion trajectories in a histogram are tracked to describe both the camera and object motions. In addition, we exploit the similarity of the temporal slices in a volume to reliably partition a volume into motion tractable units.

Predictive Adaptive Resonance Theory And Knowledge Discovery In Databases, Ah-Hwee Tan, Hui-Shin Vivien Soon

Research Collection School Of Computing and Information Systems

This paper investigates the scalability of predictive Adaptive Resonance Theory (ART) networks for knowledge discovery in very large databases. Although predictive ART performs fast and incremental learning, the number of recognition categories or rules that it creates during learning may become substantially large and cause the learning speed to slow down. To tackle this problem, we introduce an on-line algorithm for evaluating and pruning categories during learning. Benchmark experiments on a large scale data set show that on-line pruning has been effective in reducing the number of the recognition categories and the time for convergence. Interestingly, the pruned networks also …

Personalizing The Gams Cross-Index, Saverio Perugini, Priya Lakshminarayanan, Naren Ramakrishnan

Computer Science Faculty Publications

The NIST Guide to Available Mathematical Software (GAMS) system at http://gams.nist .gov serves as the gateway to thousands of scientific codes and modules for numerical computation. We describe the PIPE personalization facility for GAMS, whereby content from the cross-index is specialized for a user desiring software recommendations for a specific problem instance. The key idea is to (i) mine structure, and (ii) exploit it in a programmatic manner to generate personalized web pages. Our approach supports both content-based and collaborative personalization and enables information integration from multiple (and complementary) web resources. We present case studies for the domain of linear, …

Monte Carlo Simulations Of Photoemission Characteristics From Gaas And Diamond, Abhishek Srivastava

Electrical & Computer Engineering Theses & Dissertations

Monte Carlo based numerical simulations were performed to study photoemission from GaAs and diamond. The central goal was to assess the potential for NEA photoemission from diamond, and to predict its characteristics. The GaAs material system was also included in the simulation study to provide: (i) calibration and validation of the numerical model developed by carefully matching the simulation results with available experimental data, and (ii) quantitative comparisons between the response characteristics of diamond and the better known GaAs system.

Predictions of the energy distribution, temporal response and angular distribution of emitted electrons were obtained. Effects of various parameters, such …

Gnarly Rantings About The Hacker And The Ants, Rudy Rucker

SWITCH

The article is an excerpt from Rucker’s book “The Happy Mutant”. It begins with his reflection of his career with GoMotion. He discusses the relation that he saw between design and cyberspace. Later he discusses his experience with a game a colleague found on the net: a virtual world where player is an ant. He talks about the struggles he goes through in this virtual world because of game difficulty and poor visuals. He ties it all in with how the Silicon Valley works in a similar way, and is filled with hackers and programers all needing each other to …

Multiple Learner Systems Using Resampling Methods, Binyun Xie

Computer Science Theses & Dissertations

The N-Learners Problem deals with combining a number of learners such that the resultant system is "better", under some criterion, than the best of the individual learners. We consider a system of probably approximately correct concept learners. Depending on the available information, there are several methods to make the composite system better than the best of the individual learners. If a sample and an oracle that generates data points (but, not their classification) is available, then we show that we can achieve arbitrary levels of the normalized confidence of the composite system if (a) a robust learning algorithm is available, …

A Direct Formulation And Computer-Implementation Of A Symbolic Network Analysis Algorithm, Timothy James Knerr

Electrical & Computer Engineering Theses & Dissertations

An algorithm for the symbolic analysis of linear, time-invariant, active or passive networks is presented. The algorithm incorporates the best features of earlier numerical and topological methods of symbolic analysis. A hybrid set of equations is formulated for a closed linear graph and arranged in matrix form. A numerical evalu­ation procedure for the determinant of this hybrid matrix results in an efficient method of symbolic analysis. A proof of the algorithm based on determinant evaluation by a permutation product expansion provides insight into relationships with other methods of symbolic analysis. A computer program implementation of the algorithm is described and …