An investigation into graph isomorphism based zero-knowledge proofs. (open access)

An investigation into graph isomorphism based zero-knowledge proofs.

Zero-knowledge proofs protocols are effective interactive methods to prove a node's identity without disclosing any additional information other than the veracity of the proof. They are implementable in several ways. In this thesis, I investigate the graph isomorphism based zero-knowledge proofs protocol. My experiments and analyses suggest that graph isomorphism can easily be solved for many types of graphs and hence is not an ideal solution for implementing ZKP.
Date: December 2009
Creator: Ayeh, Eric
System: The UNT Digital Library
Trajectories As a Unifying Cross Domain Feature for Surveillance Systems (open access)

Trajectories As a Unifying Cross Domain Feature for Surveillance Systems

Manual video analysis is apparently a tedious task. An efficient solution is of highly importance to automate the process and to assist operators. A major goal of video analysis is understanding and recognizing human activities captured by surveillance cameras, a very challenging problem; the activities can be either individual or interactional among multiple objects. It involves extraction of relevant spatial and temporal information from visual images. Most video analytics systems are constrained by specific environmental situations. Different domains may require different specific knowledge to express characteristics of interesting events. Spatial-temporal trajectories have been utilized to capture motion characteristics of activities. The focus of this dissertation is on how trajectories are utilized in assist in developing video analytic system in the context of surveillance. The research as reported in this dissertation begins real-time highway traffic monitoring and dynamic traffic pattern analysis and in the end generalize the knowledge to event and activity analysis in a broader context. The main contributions are: the use of the graph-theoretic dominant set approach to the classification of traffic trajectories; the ability to first partition the trajectory clusters using entry and exit point awareness to significantly improve the clustering effectiveness and to reduce the computational time …
Date: December 2014
Creator: Wan, Yiwen
System: The UNT Digital Library
Tesla Turbine Torque Modeling for Construction of a Dynamometer and Turbine (open access)

Tesla Turbine Torque Modeling for Construction of a Dynamometer and Turbine

While conventional turbines have been extensively researched and tested, Tesla and boundary layer type turbines have not. In order to construct a dynamometer, thermodynamic flow apparatus and future turbines, we modeled the Tesla turbine using theoretical calculations and preliminary experiments. Thus a series of experiments were run to determine stall torque and maximum run speed for a known pressure range. This data was then applied to modeling formulas to estimate stall torque over an extended range of variables. The data were then used to design an appropriate dynamometer and airflow experiment. The model data also served to estimate various specifications and power output of the future turbine. An Obi Laser SSTG‐001 Tesla turbine was used in the experiments described. Experimental stall torque measurements were conducted in two stages. Shaft speed measurements were taken with an optical laser tachometer and Tesla turbine stall torque was measured using a spring force gauge. Two methods were chosen to model Tesla turbine stall torque: 1) flow over flat plate and 2) free vortex with a sink. A functional dynamometer and thermodynamic apparatus were constructed once the model was confirmed to be within the experimental uncertainty. Results of the experiments show that the experimental turbine …
Date: May 2011
Creator: Emran, Tamir Ali
System: The UNT Digital Library