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Electrical Engineering and Computer Science

Defense Notices

EECS MS and PhD Defense Notices for

All students and faculty are welcome to attend the final defense of EECS graduate students completing their M.S. or Ph.D. degrees. Defense notices for M.S./Ph.D. presentations for this year and several previous years are listed below in reverse chronological order.

Students who are nearing the completion of their M.S./Ph.D. research should schedule their final defenses through the EECS graduate office at least THREE WEEKS PRIOR to their presentation date so that there is time to complete the degree requirements check, and post the presentation announcement online.




Upcoming Defense Notices


JONATHAN LYLE - A Digital Approach to Bistatic Radar Synchronization via GPS PPS

MS Project Defense (CoE)

When & Where:
March 16, 2017
10:30 am
246 Nichols Hall
Committee Members:
Carl Leuschen, Chair
Chris Allen
Jilu Li

Abstract: [ Show / Hide ]
Bistatic Radar systems utilize physically separate transmit and receive systems to collect information that monostatic systems cannot. One issue with developing bisatic systems is guaranteeing synchronization between the transmitters and receivers. This project presents a purely digital method for improving synchronization of a bistatic system based on the GPS PPS signal, and using step-time for both transmitter and receiver timing. The issue of bistatic synchronization is simulated in Matlab and then modified to utilize the proposed step-time adjustment to show that the method works in theory. This method is then implemented in hardware on the digital system of CReSIS’s ‘HF Sounder’ radar system, and then tested to verify that the proposed method can be implemented in hardware and that it improves performance.



TYLER WADE - AOT Vs. JIT: Impact of Profile Data on Code Quality

MS Thesis Defense (CS)

When & Where:
March 3, 2017
1:00 pm
246 Nichols Hall
Committee Members:
Prasad Kulkarni, Chair
Perry Alexander
Heechul Yun

Abstract: [ Show / Hide ]
Just-in-time (JIT) compilation during program execution and
ahead-of-time (AOT) compilation during software installation are
alternate techniques used by managed language virtual machines
(VM) to generate optimized native code while simultaneously
achieving binary code portability and high execution performance.
JIT compilers typically collect profile information at run-time to
enable profile-guided optimizations (PGO) to customize the gener-
ated native code to different program inputs/behaviors. AOT com-
pilation removes the speed and energy overhead of online profile
collection and dynamic compilation, but may not be able to achieve
the quality and performance of customized native code. The goal
of this work is to investigate and quantify the implications of the
AOT compilation model on the quality of the generated native code
for current VMs.
First, we quantify the quality of native code generated by the
two compilation models for a state-of-the-art (HotSpot) Java VM.
Second, we determine how the amount of profile data collected af-
fects the quality of generated code. Third, we develop a mechanism
to determine the accuracy or similarity of different profile data for a
given program run, and investigate how the accuracy of profile data
affects its ability to effectively guide PGOs. Finally, we categorize
the profile data types in our VM and explore the contribution of
each such category to performance.





Past Defense Notices


LOHITH NANUVALA - An Implementation of the MLEM2 Algorithm

MS Project Defense (CS)

When & Where:
February 24, 2017
1:00 pm
1 Eaton Hall
Committee Members:
Jerzy Grzymala-Busse, Chair
Prasad Kulkarni
Richard Wang

Abstract: [ Show / Hide ]
Data mining is the process of finding meaningful information from data. Data mining can be used in several areas like business, medicine, education etc. It allows us to find patterns in the data and make predictions for the future. One form of data mining is to extract rules from data sets. In this project we discuss an implementation of one of the data mining algorithms called MLEM2 (Modified Learning from Examples Module, version 2). This algorithm uses the concept of blocks of attribute-value pairs. It is also robust and generates rules for both complete and incomplete data sets with numeric and symbolic attributes. A rule checker has been developed which is used to evaluate the rule sets produced by MLEM2. The accuracy of the rules is measured by computing the error rate which is the ratio of the number of incorrectly classified cases to the total number of all cases. Experiments are conducted on different kinds of data sets (complete, incomplete, numeric and symbolic) using 10-fold cross validation method.



ASHWINI BALACHANDRA - Implementation of Truncated Lévy Walk Mobility Model in ns-3

MS Project Defense (EE)

When & Where:
January 31, 2017
1:30 pm
246 Nichols Hall
Committee Members:
James Sterbenz, Chair
Victor Frost
Fengjun Li

Abstract: [ Show / Hide ]
Mobility models generate the mobility patterns of the nodes in a given system. Mobility models help us to analyze and study the characteristic of new and existing systems. Various mobility models implemented in network simulation tools like ns-3 does not model the patterns of human mobility. The main idea of this project is to implement the truncated Lévy walk mobility model in ns-3. The model has two variations, in the first variation, the flight length and pause time of the nodes are determined from the truncated Pareto distribution and in the second variation, Lévy distribution models the flight length and pause time distributions and the values are obtained by Lévy α-stable random number generator. The mobility patterns of the nodes are generated and analyzed for the model by changing various model attributes. Further studies can be done to understand the behavior of these models for different ad hoc networking protocols.



PAVAN KUMAR MOTURU - Image Processing Techniques in Matlab GUI

MS Project Defense (CS)

When & Where:
January 31, 2017
9:00 am
246 Nichols Hall
Committee Members:
Carl Leuschen, Chair
Chris Allen
Fernando Rodriguez-Morales

Abstract: [ Show / Hide ]
Identifying missing bed in radar data is very important in sea level changes. Increase in sea level is a problem of global importance because of its impact on infrastructure. Ice sheets in the Greenland and Antarctic are melting and increasing their contribution to sea level change over the last decade. Measuring ice sheets thickness is required to estimate sea level rise. We need to use several algorithms, pre-defined functions to extract the weak bed echoes, but we don’t have a tool in Matlab which contains some important algorithms like ImageJ. We can’t process all the data in ImageJ as Matlab produces better results compared to ImageJ as some of the functions like window and symmetric selection around center in FFT domain are not implemented in ImageJ.
In this project, we will investigate the application of some image processing techniques using a GUI developed for analyzing ice sounding radargrams. One key advantage of the tool is that the image processing techniques are applied in a single GUI instead of doing separately. We apply these techniques on the data which came after applying extensive signal processing techniques. After performing these techniques, we compare the processed data with the original data.




MOHSEN ALEENEJAD - New Modulation Methods and Control Strategies for Power Converters

PhD Comprehensive Defense (EE)

When & Where:
January 30, 2017
3:00 pm
1 Eaton Hall
Committee Members:
Reza Ahmadi, Chair
Glenn Prescott
Alessandro Salandrino
Jim Stiles
Huazhen Fang*

Abstract: [ Show / Hide ]
The DC to AC power Inverters (so-called Inverters) are widely used in industrial applications. The multilevel Inverters are becoming increasingly popular in industrial apparatus aimed at medium to high power conversion applications. In comparison to the conventional inverters, they feature superior characteristics such as lower total harmonic distortion (THD), higher efficiency, and lower switching voltage stress{Malinowski, 2010 #9}{Malinowski, 2010 #9}. Nevertheless, the superior characteristics come at the price of a more complex topology with an increased number of power electronic switches. As a general rule in a Inverter topology, as the number of power electronic switches increases, the chances of fault occurrence on of the switches increases, and thus the Inverter’s reliability decreases. Due to the extreme monetary ramifications of the interruption of operation in commercial and industrial applications, high reliability for power Inverters utilized in these sectors is critical. As a result, developing fault-tolerant operation schemes for multilevel Inverters has always been an interesting topic for researchers in related areas. The purpose of this proposal is to develop new control and fault-tolerant strategies for the multilevel power Inverter. In the event of a fault, the line voltages of the faulty Inverters are unbalanced and cannot be applied to the three phase loads. This fault-tolerant strategy generates balanced line voltages without bypassing any healthy and operative Inverter element, makes better use of the Inverter capacity and generates higher output voltage. This strategy exploits the advantages of the Selective Harmonic Elimination (SHE) method in conjunction with a slightly modified Fundamental Phase Shift Compensation technique to generate balanced voltages and manipulate voltage harmonics at the same time. However, due to the distinctive requirement of the strategy to manipulate both amplitude and angle of the harmonics, the conventional SHE technique is not the suitable basis for the proposed strategy. Therefore, in this project a modified Unbalanced SHE technique which can be used as the basis for the fault-tolerant strategy is developed. The proposed strategy is applicable to several classes of multilevel Inverters with three or more voltage levels.




SIVA RAM DATTA BOBBA - Rule Induction For Numerical Data using PRISM

MS Project Defense (CS)

When & Where:
January 30, 2017
1:00 pm
2001B Eaton Hall
Committee Members:
Jerzy Grzymala-Busse, Chair
Bo Luo
James Miller

Abstract: [ Show / Hide ]
Rule induction is one of the basic and important techniques of data mining. Inducing a rule set for symbolic data is simple and straightforward, but it becomes complex when the attributes are numerical. There are several algorithms available that do the task of rule induction for symbolic data. One such algorithm is PRISM which uses conditional probability for attribute-value selection to induce a rule.
In the real world scenario, data may comprise of either symbolic or numerical attributes. It becomes difficult to induce a discriminant ruleset on the data with numerical attributes. This project provides an implementation of PRISM to handle numerical data. First, it takes as input, a dataset with numerical attributes and converts them into discrete values using the multiple scanning approach which identifies the cut-points for intervals using minimum conditional entropy. Once discretization completes, PRISM uses these discrete values to induce ruleset for each decision. Thus, this project helps to induce modular rulesets over a numerical dataset.



NILISHA MANE - Tools to Explore Run-time Program Properties

MS Project Defense (CS)

When & Where:
January 30, 2017
11:30 am
246 Nichols Hall
Committee Members:
Prasad Kulkarni,Chair
Perry Alexander
Gary Minden

Abstract: [ Show / Hide ]
The advancement in the field of embedded technology has resulted in its extensive use in almost all the modern electronic devices. Hence, unlike in the past, there is a very crucial need to develop system security tools for these devices. So far most of the research has been concentrated either on security for general computer systems or on static analysis of embedded systems. In this project, we develop tools that explore and monitor the run-time properties of programs/applications as well as the inter-process communication. We also present a case studies in which these tools are be used on a Gumstix (an embedded system) running Poky Linux system to monitor a particular program as well as print out a graph of all inter-process communication on the system.



BRIAN MACHARIA - UWB Microwave Filters on Multilayer LCP Substrates: A Feasibility Study

MS Project Defense (EE)

When & Where:
January 30, 2017
11:00 am
317 Nichols Hall
Committee Members:
Carl Leuschen, Chair
Fernando Rodriguez-Morales-Co-Chair
Chris Allen

Abstract: [ Show / Hide ]
Having stable dielectric properties extending to frequencies over 110 GHz, Liquid Crystal Polymer (LCP) materials are a new and promising substrate alternative for low-cost production of planar microwave circuits. This project focused on the design of several microwave filter structures using multiple layers for operation in the 2-18 GHz and 10-14 GHz bands. Circuits were simulated and optimized using EDA tools, obtaining good results over the bands of interest. The results show that it is feasible to fabricate these structures on dielectric substrates compatible with off-site manufacturing facilities. It is likewise shown that LCP technology can yield a 3-5x area reduction as compared to cavity-type filters, making them much easier to integrate in a planar circuit.



Md. MOSHFEQUR RAHMAN - OpenFlow based Multipath Communication for Resilience

MS Thesis Defense (EE)

When & Where:
January 30, 2017
9:00 am
246 Nichols Hall
Committee Members:
James Sterbenz, Chair
Victor Frost
Fengjun Li

Abstract: [ Show / Hide ]
A cross-layer framework in the Software Defined Networking domain is pro- posed to study the resilience in OpenFlow-based multipath communication. A testbed has been built, using Brocade OpenFlow switches and Dell Poweredge servers. The framework is evaluated against regional challenges. By using differ- ent adjacency matrices, various topologies are built. The behavior of OpenFlow multipath-based communication is studied in case of a single path failure, splitting of traffic and also with multipath TCP enabled traffic. The behavior of different coupled congestion algorithms for MPTCP is also studied. A Web framework is presented to demonstrate the OpenFlow experiment by importing the network topologies and then executing and analyzing user defined regional attacks.



RAGAPRABHA CHINNASWAMY - A Comparison of Maximal Consistent Blocks and Characteristics Sets for Incomplete Data Sets

MS Project Defense (CS)

When & Where:
January 25, 2017
10:00 am
2001B Eaton Hall
Committee Members:
Jerzy Grzymala-Busse, Chair
Prasad Kulkarni
Bo Luo

Abstract: [ Show / Hide ]
One of the main applications of rough set theory is rule induction. If the input data set contains inconsistencies, using rough set theory leads to inducing certain and possible rule sets.
In this project, the concept of a maximal consistent block is applied to formulate a new approximation to a concept in the incomplete data set with a higher level of accuracy. This method does not require change in the size of the original incomplete data set. Two interpretations of missing attribute values are discussed: lost values and “do not care” conditions. The main objective is to compare maximal consistent blocks and characteristics sets in terms of cardinality of lower and upper approximations. Four incomplete data sets are used for experiments with varying levels of missing information. The next objective is to compare the decision rules induced and cases covered by both techniques. The experiments show that the both techniques provide the same lower approximations for all the datasets with “do not care” conditions. The best results are achieved by maximal consistent blocks for upper approximations for three datasets and there is a tie for the other data set.



PRAVEEN YARLAGADDA - A Comparison of Rule Sets Generated by Algorithms: AQ, C4.5, and CART

MS Project Defense (CS)

When & Where:
January 24, 2017
2:00 pm
2001B Eaton Hall
Committee Members:
Jerzy Grzymala-Busse, Chair
Bo Luo
Jim Miller

Abstract: [ Show / Hide ]
In data mining, rules are the most popular symbolic representation of knowledge. Classification of data and extracting of classification rules from the data is a difficult process, and there are different approaches to this process. One such approach is inductive learning. Inductive learning involves the process of learning from examples - where a system tries to induce a set of rules from a set of observed examples. Inductive learning methods produce distinct concept descriptions when given identical training data and there are questions about the quality of the different rule sets produced. This project work is aimed at comparing and analyzing the rule sets induced by different inductive learning systems. In this project, three different algorithms AQ, CART and C4.5 are used to induce rule sets from different data sets. An analysis is carried out in terms of the total number of rules and the total number of conditions present in the rules. These space complexity measures such as rule count and condition count show that AQ tends to produce more complex rule sets than C4.5 and CART. AQ algorithm has been implemented as a part of project and is used to induce the rule sets.



DIVYA GUPTA - Investigation of a License Plate Recognition Algorithm

MS Project Defense (EE)

When & Where:
January 24, 2017
8:00 am
250 Nichols Hall
Committee Members:
Glenn Prescott, Chair
Erik Perrins
Jim Stiles

Abstract: [ Show / Hide ]
License plate Recognition method is a technique to detect license plate numbers from the vehicle images. This method has become an important part of our life with an increase in traffic and crime every now and then. It uses computer vision and pattern recognition technologies. Various techniques have been proposed so far and they work best within boundaries.This detection technique helps in finding the accurate location of license plates and extracting characters of the plates. The license plate detection is a three-stage process that includes license plate detection, character segmentation and character recognition. The first stage is the extraction of the number plate as it occupies a small portion of the whole image. After tracking down the license plate, localizing of the characters is done. The character recognition is the last stage of the detection and template matching is the most common method used for it. The results achieved by the above experiment were quite accurate which showed the robustness of the investigated algorithm.



NAZMA KOTCHERLA - Hybrid Mobile and Responsive Web Application - KU Quick Quiz

MS Project Defense (CoE)

When & Where:
January 23, 2017
2:00 pm
2001B Eaton Hall
Committee Members:
Prasad Kulkarni, Chair
Perry Alexander
Jerzy Grzymala-Busse

Abstract: [ Show / Hide ]
The objective of this project is to leverage the open source Angular JS, Node JS, and Ionic Framework along with Cordova to develop “A Hybrid Mobile Application” for students and “A Responsive Web Application” for professor to conduct classroom centered “Dynamic Tests”. Dynamic Tests are the test taking environments where questions can be posted to students in the form of quizzes during a classroom setup. Guided by the specifications set by the professor, students answer and submit the quiz from their mobile devices. The results are generated instantaneously after the completion of the test session and can be viewed by the professor. The web application performs statistical analysis of the responses by considering the factors that the professor had set to measure the students’ performance. This advanced methodology of test taking is highly beneficial as it gives a clear picture to the professor the level of understanding of all the students in any chosen topic immediately after the test. It helps to improvise the teaching methods. This is also very advantageous to students since it helps them to come out of their hesitation to clarify their doubts as their marks become the measure of their understanding which is directly uncovered before the professor. This application overall improves the classroom experience to help students gain higher standards.



JYOTHI PRASAD PANGLURI SREEHARINAIDU - Implementation of ChiMerge Algorithm for Discretization of Numerical Attributes

MS Project Defense (CS)

When & Where:
January 23, 2017
10:00 am
2001B Eaton Hall
Committee Members:
Jerzy Grzymala-Busse, Chair
Perry Alexander
Prasad Kulkarni

Abstract: [ Show / Hide ]
Most of the present classification algorithms require the input data with discretized attributes. If the input data contains numerical attributes, we need to convert such attributes into discrete values (intervals) before performing classification. Discretization algorithms for real value attributes are very important for applications such as artificial intelligence and machine learning. In this project we discuss an implementation of the ChiMerge algorithm for discretization of numerical attributes, a robust algorithm, which uses X2 statistic to determine interval similarity as it constructs intervals in a bottom-up merging process. ChiMerge provides a reliable summarization of numerical attributes and determines the number of intervals.




MOHAN KRISHNA VEERAMACHINENI - A Graphical User Interface System for Rule Visualization

MS Project Defense (CS)

When & Where:
January 20, 2017
1:00 pm
2001B Eaton Hall
Committee Members:
Jerzy Grzymala-Busse, Chair
Bo Luo
Prasad Kulkarni

Abstract: [ Show / Hide ]
The primary goal of data visualization is to communicate information clearly and efficiently via statistical graphs, plots and information graphics. It makes complex data more accessible, understandable and usable. The goal of this project is to build a graphical user interface called RULEVIZ to visualize the rules, induced by LERS (Learning from Examples using Rough Set Theory) data mining system in the form of directed graphs. LERS is a technique used to induce a set of rules from examples given in the form of a decision table. Such rules are used to classify unseen data. The RULEVIZ is developed as a web application where the user uploads the rule set and the data set from which the rule set is visualized in the graphical format and is rendered on the web browser. Every rule is taken sequentially, and all the conditions of that rule are visualized as nodes connected by undirected edges. The last condition is connected to the concept by a directed edge. The RULEVIZ offers custom filtering options for the user to filter the rules based on factors like the number of conditions and conditional probability or strength. The RULEVIZ also has interactive capabilities to filter out rule sets and manipulate the generated graph for a better look and feel.



HARA MADHAV TALASILA - Modular Frequency Multiplier and Filters for the Global Hawk Snow Radar

MS Thesis Defense (EE)

When & Where:
January 20, 2017
12:00 pm
317 Nichols Hall
Committee Members:
John Paden, Chair
Chris Allen
Carl Leuschen
Fernando Rodriguez-Morales

Abstract: [ Show / Hide ]
Remote sensing with radar systems on airborne platforms is key for wide-area data collection to estimate the impact of ice and snow masses on rising sea levels. NASA P-3B and DC-8, as well as other platforms, successfully flew with multiple versions of the Snow Radar developed at CReSIS. Compared to these manned missions, the Global Hawk UAV can support flights with long endurance, complex flight paths and flexible altitude operation up to 70,000 ft. This thesis documents the process of adapting the 2-18 GHz Snow radar to meet the requirements for operation on manned and unmanned platforms from 700 ft to 70,000 ft. The primary focus of this work is the development of an improved microwave chirp generator implemented with frequency multipliers. The x16 frequency multiplier is composed of a series of x2 frequency multiplication stages, overcoming some of the limitations encountered in previous designs. At each stage, undesired harmonics are kept out of the band and filtered. The miniaturized design presented here reduces reflections in the chain, overall size, and weight as compared to the earlier large and heavy connectorized chain. Each stage is implemented by a drop-in type modular design operating at microwaves and millimeter waves; and realized with commercial surface-mount ICs, wire-bondable chips, and custom filters. DC circuits for power regulation and sequencing are developed as well. Another focus of this thesis is the development of band-pass filters using different distributed element filter technologies. Multiple edge-coupled band pass filters are fabricated on alumina substrate based on the design and optimization in computer-aided design (CAD) tools. Interdigital cavity filter models developed in-house are validated by full-wave EM simulation and measurements. Overall, the measured results of the modular frequency multiplier and filters match with the expected responses from original design and co-simulation outputs. The design files, test setups, and simulation models are generalized to use with any similar or new designs in the future.




SOUMYAROOP NANDI - Robust Object Tracking and Adaptive Detection for Autonavigation of Unmanned Aerial Vehicle

MS Thesis Defense (EE)

When & Where:
January 9, 2017
9:00 am
246 Nichols Hall
Committee Members:
Richard Wang, Chair
Jim Rowland
Jim Stiles

Abstract: [ Show / Hide ]
Object detection and tracking is an important research topic in the computer vision field with numerous practical applications. Although great progress has been made, both in object detection and tracking over the last decade, it is still a big challenge in real-time applications like automated navigation of an unmanned aerial vehicle and collision avoidance with a forward looking camera. An automated and robust object tracking approach is proposed by integrating a kernelized correlation filter framework with an adaptive object detection technique based on minimum barrier distance transform. The proposed tracker is automatically initialized with salient object detection and the detected object is localized in the image frame with a rectangular bounding box. An adaptive object redetection strategy is proposed to refine the location and boundary of the object, when the tracking correlation response drops below a certain threshold. In addition, reliable pre-processing and post-processing methods are applied on the image frames to accurately localize the object. Extensive quantitative and qualitative experimentation on challenging datasets have been performed to verify the proposed approach. Furthermore, the proposed approach is comprehensively examined with six other recent state-of-the-art¬ trackers, demonstrating that the proposed approach greatly outperforms these trackers, both in terms of tracking speed and accuracy.




TRUC ANH NGUYEN - ResTP: A Configurable and Adaptable Multipath Transport Protocol for Future Internet Resilience

PhD Comprehensive Defense (CS)

When & Where:
January 6, 2017
8:00 am
246 Nichols Hall
Committee Members:
James Sterbenz, Chair
Victor Frost
Bo Luo
Gary Minden
Justin Rohrer
Michael Welzl
Hyunjin Seo*

Abstract: [ Show / Hide ]
With the motivation to develop a resilient and survivable networking system that can cope with challenges posed by the rapid growth in networking technologies and use paradigms and the impairments of TCP and UDP, we propose a general-purpose, configurable and adaptable multipath-capable transport-layer protocol called ResTP. By supporting cross- layering, ResTP allows service tuning by the upper application layer while promptly reacting to the underlying network dynamics by using the feedback from the lower layer. Our composable ResTP not only has the flexibility to provide services to different application classes operating across various network environments, its selection of mechanisms also increases the resilience level of the system in which it is deployed since the design of ResTP is guided by a set of principles derived from the ResiliNets framework. Moreover, the implementation of ResTP employs modular programming to minimize the complexity while increasing its extensibility. Hence, the addition of any new algorithms to ResTP would require only some small changes to the existing code. Last but not least, many ResTP components, including its header, are optimized to reduce unnecessary overhead. In this proposal, we introduce ResTP’s key functionalities, present some preliminary simulation results of ResTP in comparison with TCP and UDP in ns-3, and discuss our plan towards the completion and analysis of the protocol. The results show that ResTP is a promising transport-layer protocol for Future Internet (FI) resilience.