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Dartmouth College

Dartmouth College Master’s Theses

2010

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Full-Text Articles in Physical Sciences and Mathematics

Out Of The Depths: Image Statistics Of Space, Water, And The Minuscule World, Nimit S. Dhulekar Sep 2010

Out Of The Depths: Image Statistics Of Space, Water, And The Minuscule World, Nimit S. Dhulekar

Dartmouth College Master’s Theses

In images of natural scenes, a consistent relationship exists between spectral power and spatial frequency. The power spectrum falls off with a form 1/f^p as spatial frequency f increases, with values of p approximately equal to 2. To quantify the extent to which this statistical characteristic is exhibited by other classes of images, we examined astronomical, underwater, and microscale images. It was found that this property holds for all three categories of images, although the value of p varies in the range 1.76 to 2.37. The second statistical characteristic computed was the angular spread of the power spectrum. This metric …


Numerical Methods For Fmri Data Analysis, Geethmala Sridaran Aug 2010

Numerical Methods For Fmri Data Analysis, Geethmala Sridaran

Dartmouth College Master’s Theses

Brain imaging data are increasingly analyzed via a range of machine-learning methods. In this thesis, we discuss three specific contributions to the field of neuroimaging analysis methods: 1. To apply a recently-developed technique for identifying and viewing similarity structure in neuroimaging data, in which candidate representational structures are ranked; 2. Provide side-by-side analyses of neuroimaging data by a typical non-hierarchical (SVM) versus hierarchical (Decision Tree) machine-learning classification methods; and 3. To develop a novel programming environment for PyMVPA, a current popular analysis toolbox, such that users will be able to type a small number of packaged commands to carry out …


Predictive Yasir: High Security With Lower Latency In Legacy Scada, Rouslan V. Solomakhin Jun 2010

Predictive Yasir: High Security With Lower Latency In Legacy Scada, Rouslan V. Solomakhin

Dartmouth College Master’s Theses

Message authentication with low latency is necessary to ensure secure operations in legacy industrial control networks, such as power grid networks. Previous authentication solutions by our lab and others looked at single messages and incurred noticeable latency. To reduce this latency, we develop Predictive YASIR, a bump-in-the-wire device that looks at broader patterns of messages. The device (1) predicts the incoming plaintext based on previous observations; (2) compresses, encrypts, and authenticates data online; and (3) pre-sends a part of ciphertext before receiving the whole plaintext. I demonstrate the performance properties of this approach by implementing it in the Scalable Simulation …