Thesis (M.Eng.). / Written for the Dept. of Mechanical Engineering. Title from title page of PDF (viewed 2008/03/12 ). Includes bibliographical references.

Thesis (M.S.)--Montana State University--Bozeman, 2005. / Typescript. Chairperson, Graduate Committee: David M. Klumpar. Includes bibliographical references (leaves 220-221).

No description available.

published_or_final_version / abstract / Mechanical Engineering / Master / Master of Philosophy

The objective of this research is to determine the possibility of an alternative for government-developed satellites which produce high resolution imagery. This study focuses on the concept of the U.S. government purchasing proven and successful commercial satellites with minimal non-recurring engineering costs to help augment current national systems. The benefit with this alternative is the reliability and affordability of a system that is currently used in space and therefore reduces a significant amount of risk as well as production time. A constellation of commercial satellites that are reconstituted on a monthly or quarterly cycle could also invigorate the commercial satellite work force and better produce future systems. A disadvantage with an architecture of commercial satellites are potential limitations with geolocation accuracy and data rate downlink transmission capability. This thesis evaluates constellation design factors such as orbit types, number of satellites, life-cycle and ground segment implementation. A coverage capability evaluation is provided to determine how a commercial system would be able to fulfill national imagery collection requirements. Eight different constellation types were created, ranging from one to 12 satellites in size. Orbit analysis settled on a sun-synchronous polar elliptical orbit at 185 km x 700 km, using an existing commercial satellite with a 0.6m optic. This provided imaging with a resolution range between 10-37 inches. The largest constellation of 12 satellites would provide a daily area collection of 43,000 km2 and 150 point images for a region the size of Iraq and would have an estimated $1-2B cost for an annual life cycle cost. Revisit time for mid-latitude targets was approximately one day at 10 inch resolution.

Clustering is a fundamental data mining tool that aims to divide data into groups of similar items. Intuition about clustering reflects the ideal case -- exact data sets endowed with flawless dissimilarity between individual instances. In practice however, these cases are in the minority, and clustering applications are typically characterized by noisy data sets with approximate pairwise dissimilarities. As such, the efficacy of clustering methods necessitates robustness to perturbations. In this paper, we address foundational questions on perturbation robustness, studying to what extent can clustering techniques exhibit this desirable characteristic. Our results also demonstrate the type of cluster structures required for robustness of popular clustering paradigms. / A Thesis submitted to the Department of Computer Science in partial fulfillment of the requirements for the degree of Master of Science. / Summer Semester 2017. / May 4, 2017. / Includes bibliographical references. / Margareta Ackerman, Professor Co-Directing Thesis; Gary Tyson, Professor Co-Directing Thesis; Sonia Haiduc, Committee Member; Peixiang Zhao, Committee Member.

Typescript (photocopy). / Digitized by Kansas Correctional Industries

abstract: Rapid growth of internet and connected devices ranging from cloud systems to internet of things have raised critical concerns for securing these systems. In the recent past, security attacks on different kinds of devices have evolved in terms of complexity and diversity. One of the challenges is establishing secure communication in the network among various devices and systems. Despite being protected with authentication and encryption, the network still needs to be protected against cyber-attacks. For this, the network traffic has to be closely monitored and should detect anomalies and intrusions. Intrusion detection can be categorized as a network traffic classification problem in machine learning. Existing network traffic classification methods require a lot of training and data preprocessing, and this problem is more serious if the dataset size is huge. In addition, the machine learning and deep learning methods that have been used so far were trained on datasets that contain obsolete attacks. In this thesis, these problems are addressed by using ensemble methods applied on an up to date network attacks dataset. Ensemble methods use multiple learning algorithms to get better classification accuracy that could be obtained when the corresponding learning algorithm is applied alone. This dataset for network traffic classification has recent attack scenarios and contains over fifteen attacks. This approach shows that ensemble methods can be used to classify network traffic and detect intrusions with less training times of the model, and lesser pre-processing without feature selection. In addition, this thesis also shows that only with less than ten percent of the total features of input dataset will lead to similar accuracy that is achieved on whole dataset. This can heavily reduce the training times and classification duration in real-time scenarios. / Dissertation/Thesis / Masters Thesis Computer Science 2019

Thesis (M Dent(Operative Dentistry))-- University of Limpopo, 2012. / The importance and demand for aesthetics has resulted in an increase in tooth-coloured restorations in dental practice. Composite undergoes polymerization using a curing device, after which it gains its physical and aesthetic properties. An improperly cured composite restoration is weak and prone to discolouration and secondary decay. The aim of this study was to determine and compare the effect that composite shade and curing distance would have on the depth of cure (DOC) of composite Filtek Silorane, Filtek Supreme XT and Z100. The scrape and penetrometer techniques were used to determine the DOC of the 450 specimens prepared. The DOC decreased with an increase in the curing distance and the darker shade had a lower DOC than the lighter shade for each of the composites tested. Both the scrape and penetrometer techniques yielded similar results in the DOC. Z100 had the highest DOC followed by Supreme XT and lastly Silorane. Thus a lighter composite shade in posterior teeth (non-aesthetic zone) and in deep Class II cavities will ensure an optimal depth of cure. The curing distance should be minimal and as close as possible to the composite surface to achieve an optimal depth of cure.

Thesis (Ph. D.)--University of Texas at Austin, 2000. / Vita. Includes bibliographical references (leaves 97-105). Available also in a digital version from Dissertation Abstracts.