Defense Notices

Rapid development in technologies and database systems result in producing and storing large amounts of data. With such an enormous increase in data over the last few decades, data mining became a useful tool to discover the knowledge hidden in large data. Domain experts often use machine learning algorithms for finding theories that would explain their data. 
In this project we compare Weka implementation of CART and C4.5 with their original implementation on different datasets from University of California Irvine (UCI). Comparisons of these implementations has been carried in terms of accuracy, decision tree complexity and area under ROC curve (AUC). Results from our experiments show that the decision tree complexity of C4.5 is much higher than CART and that the original implementation of these algorithms perform slightly better than their corresponding Weka implementation in terms of accuracy and AUC. 

Logging system information and its metrics provides us with a valuable resource to monitor the system for unusual activity and understand the various factors affecting its performance. Though there are several tools that are available to log and analyze the system locally, it is inefficient to individually analyze every system and is seldom effective in case of hardware failure. Having centralized access to this information aids the system administrators in performing their operational tasks. Here we present a centralized logging solution for system logs and metrics by using Time Series Databases (TSDB). We provide reliable storage and efficient access to system information by storing the parsed system logs and metrics in a TSDB. In this project, we develop a solution to store the system’s default log storage - syslog as well as the system metrics like CPU load, disk load, and network traffic load into a TSDB. We further extend our ability to monitor and analyze the data in our TSDB by using an open source graphing tool. 

Property-directed verification of functional programs tends to take one of two paths. 
First, is the traditional testing approach, where properties are expressed in the original programming language and checked with a collection of test data. 
Alternatively, for those desiring a more rigorous approach, properties can be written and checked with a formal tool; typically, an external proof system. 
This dissertation details a hybrid approach that captures the best of both worlds: the formality of a proof system paired with the native integration of an embedded, domain specific language (EDSL) for testing. 

At the heart of this hybridization is the titular concept -- \emph{a theorem prover as a library}. 
The verification capabilities of this prover, HaskHOL, are introduced to a Haskell development environment as a GHC compiler plugin. 
Operating at the compiler level provides for a comparatively simpler integration and allows verification to co-exist with the numerous other passes that stand between source code and program. 

The logical connection between language and proof library is formalized, and the open problems related to this connection are documented. 
Additionally, the resultant, novel verification workflow is applied to two major classes of problems, type class laws and polymorphic test cases, to judge the real-world feasibility of compiler-directed verification. 
These applications and formalization serve to position this work relative to existing work and to highlight potential, future extensions.

Ice shelves are sensitive indicators of climate change and play a critical role in the stability of ice sheets and oceanic currents. Basal melting of ice shelves plays an important role in both the mass balance of the ice sheet and the global climate system. Airborne- and satellite based remote sensing systems can perform thickness measurements of ice shelves. Time separated repeat flight tracks over ice shelves of interest generate data sets that can be used to derive basal melt rates using traditional glaciological techniques. Many previous melt rate studies have relied on surface elevation data gathered by airborne- and satellite based altimeters. These systems infer melt rates by assuming hydrostatic equilibrium, an assumption that may not be accurate, especially near an ice shelf’s grounding line. Moderate bandwidth, VHF, ice penetrating radar has been used to measure ice shelf profiles with relatively coarse resolution. This study presents the application of an ultra wide bandwidth (UWB), UHF, ice penetrating radar to obtain finer resolution data on the ice shelves. These data reveal significant details about the basal interface, including the locations and depth of bottom crevasses and deviations from hydrostatic equilibrium. While our single channel radar provides new insight into ice shelf structure, it only images a small swatch of the shelf, which is assumed to be an average of the total shelf behavior. This study takes an additional step by investigating the application of a 3 D imaging technique to a data set collected using a ground based multi channel version of the UWB radar. The intent is to show that the UWB radar could be capable of providing a wider swath 3 D image of an ice shelf. The 3 D images can then be used to obtain a more complete estimate of bottom melt rates of ice shelves.

A mobile ad-hoc network (MANET) routing algorithm defines the path packets take to reach their destination using measurements of attributes such as adjacency and distance. Graph theory is increasingly applied in many fields of research today to model the properties of data on a graph plane. Graph theory is applied to in networking to form structures from patterns of nodes. Conventional MANET protocols are often based on path measurements from wired network algorithms and do not implement mechanisms to mitigate route entropy, defined as the procession of a converged path to a path loss state as a result of increasing random movement. Graph isomorphism measures equality beginning in the individual node and in sets of nodes and edges. The measurement of isomorphism is applied in this research to form paths from an aggregate set of route inputs, such as adjacency, cardinality to impending nodes in a path, and network width. A routing protocol based on the presence of isomorphism in a MANET topology is then tested to measure the performance of the proposed routing protocol.

The problem of outdoor positioning has been largely solved via the use of GPS. This thesis addresses the problem of determining position in areas where GPS is unavailable. No clear solution exists for indoor localization and all approximation methods offer unique drawbacks. To mitigate the drawbacks, robust systems combine multiple complementary approaches. In this thesis, fusion of wireless internet access points and inertial sensors was used to allow indoor positioning without the need for prior information regarding surroundings. Implementation of the algorithm involved development of three separate systems. The first system simply combines inertial sensors on the Android Nexus 7 to form a step counter capable of providing marginally accurate initial measurements. Having achieved reliable initial measurements, the second system receives signal strength from nearby wireless internet access points, augmenting the sensor data in order to generate half-planes. The half-planes partition the available space and bound the possible region in which each access point can exist. Lastly, the third system addresses the tendency of the step counter to lose accuracy over time by using the recently established positions of the access points to correct flawed values. The resulting process forms a simple feedback loop.

It is difficult to write programs which are both correct and fast. A promising approach, functional programming, is based on the idea of using pure, mathematical functions to construct programs. With effort, it is possible to establish a connection between a specification written in a functional language, which has been proven correct, and a fast implementation, via program transformation. 

When practiced in the functional programming community, this style of reasoning is still typically performed by hand, by either modifying the source code or using pen-and-paper. Unfortunately, performing such semi-formal reasoning by directly modifying the source code often obfuscates the program, and pen-and-paper reasoning becomes outdated as the program changes over time. Even so, this semi-formal reasoning prevails because formal reasoning is time-consuming, and requires considerable expertise. Formal reasoning tools often only work for a subset of the target language, or require programs to be implemented in a custom language for reasoning. 

This dissertation investigates a solution, called HERMIT, which mechanizes reasoning during compilation. HERMIT can be used to prove properties about programs written in the Haskell functional programming language, or transform them to improve their performance. 
Reasoning in HERMIT proceeds in a style familiar to practitioners of pen-and-paper reasoning, and mechanization allows these techniques to be applied to real-world programs with greater confidence. HERMIT can also re-check recorded reasoning steps on subsequent compilations, enforcing a connection with the program as the program is developed. 

HERMIT is the first system capable of directly reasoning about the full Haskell language. The design and implementation of HERMIT, motivated both by typical reasoning tasks and HERMIT's place in the Haskell ecosystem, is presented in detail. Three case studies investigate HERMIT's capability to reason in practice. These case studies demonstrate that semi-formal reasoning with HERMIT lowers the barrier to writing programs which are both correct and fast. 

To meet the demand for additional snow characterization from the Intergovernmental Panel on Climate Change (IPCC), a new “Airborne” Multichannel, Quad-Polarized 2-18GHz Snow Radar has been proposed. With tight size and weight constraints from the airborne platforms deploying with the Navy Research Laboratory (NRL), the need for integrated and miniaturized receivers for cost and size reduction is crucial for future deployments. 

A set of heterodyne microwave receivers were developed to enable snow thickness measurements from a survey altitude of 500 feet to 5000 feet while nadir looking, and estimation of SWE from polarimetric backscattered signals at low elevation 30 degree off nadir. The individual receiver has undergone a five times size reduction with respect to initial prototype design, while achieving a sensitivity of -125 dBm on average across the 2-18 GHz bandwidth, enabling measurements with a vertical range resolution of 1.64 cm in snow. The design of a compact enclosure was defined to accommodate up to 18 individual receiver modules allowing for multichannel quad-polarized measurements over the entire 16 GHz bandwidth. The receiver bank was tested individually and with the entire system in a full multichannel loop-back measurement, using a 2.95 μs optical delay line, resulting in a beat frequency of 200 MHz with 20 dB range side lobes. Due to the multi-angle, multi-polarization, and multi-frequency content from the data , the number of free parameters in the SWE estimation can thus be significantly reduced. 

Design equations have been derived and a new method for modeling Suspended Substrate Stripline (SSS) filters in ADS for rapid-prototyping has been accomplished. Two SSS filters were designed which include an Optimized Chebyshev SSS Low Pass Filter (LPF) with an 18 GHz cutoff frequency and a Broadside Coupled SSS High Pass Filter (HPF) with a 2 GHz cutoff frequency. Also, a 2-18 GHz three-port Transverse Electromagnetic (TEM) Mode Hybrid 8:1 power combiner was designed and modeled at CReSIS. This design will be integrated into the Vivaldi Dual Polarized antenna array with 8 active dual-polarized elements to implement a lightweight and compact array structure, eliminating cable and connector cost and losses. 

FET resistive mixers play a key role in providing high linearity and low noise figure levels. HEMT technology with low threshold voltage has popularized mobile phone market and milli-meter wave technologies. The project analyzes working of a down-conversion VHF FET resistive mixer model designed using ultra-low noise ATF -38143 P-HEMT. Its widely used in KNG-P150 portable mobile radios manufactured by RELM Wireless Corporation. The mixer is designed to function within RF frequency range from 136Mhz -174Mhz at an IF frequency of 51.50Mhz. Statz model has been used to simulate the working of P-HEMT under normal conditions. Transfer function of matching circuits at each port have been obtained using simulink modelling. Effect of change in Q factor at the RF port and IF port have been considered. Analytical modelling of the mixer is performed and simulated results are compared with experimental data obtained at constant 5dbm LO power. IF transfer function has been modelled to closely match the practical circuits by applying adequate amplitude damping to the response of LC circuits at the RF port, in order to provide the required IF bandwidth and conversion gain. Effect of stray capacitances and inductances have been neglected during the modelling, and changes in series resistance of inductors at RF port and IF port have been made to match experimental results.

Computer networks are getting more involved in providing services for most of our daily life activities related to education, business, health care, social life, and government. Publicly available computer networks are prone to targeted attacks and natural disasters that could disrupt normal operation and services. Building highly resilient networks is an important aspect of their design and implementation. For existing networks, resilience against such challenges can be improved by adding more links. In fact, adding links to form a full mesh yields the most resilient network but it incurs an unfeasible high cost. In this research, we investigate the resilience improvement of real-world networks via adding a cost-efficient set of links. Adding a set of links to obtain optimal solution using an exhaustive search is impracticable for large networks. Using a greedy algorithm, a feasible solution is obtained by adding a set of links to improve network connectivity by increasing a graph robustness metric such as algebraic connectivity or total path diversity. We use a graph metric called flow robustness as a measure for network resilience. To evaluate the improved networks, we apply three centrality-based attacks and study their resilience. The flow robustness results of the attacks show that the improved networks are more resilient than the non-improved networks.