Computer Sciences Commons^™

Online Diagnosis Of Diabetes With Twitter Data, Farheen Ali

Masters Theses

"Innovation in technology enables people to communicate, share information and look for their needs by just sitting in rooms and going through some clicks. While social media has played a very important role in connecting people worldwide, its potential has stretched beyond the innovative idea of connecting people through their social networks. While many thought there was no meeting point for the healthcare sector and social media, it was a surprise when research and innovations have shown that social media could lay a very significant role in the health care sector.

Research has been done in developing models that could …

Sensor Authentication In Collaborating Sensor Networks, Jake Uriah Bielefeldt

Masters Theses

"In this thesis, we address a new security problem in the realm of collaborating sensor networks. By collaborating sensor networks, we refer to the networks of sensor networks collaborating on a mission, with each sensor network is independently owned and operated by separate entities. Such networks are practical where a number of independent entities can deploy their own sensor networks in multi-national, commercial, and environmental scenarios, and some of these networks will integrate complementary functionalities for a mission. In the scenario, we address an authentication problem wherein the goal is for the Operator Oⁱ of Sensor Network S^{i …}

Argumentation Based Collaborative Software Architecture Design And Intelligent Analysis Of Software Architecture Rationale, Nagaprashanth Chanda

Masters Theses

"A growing model for software architecture defines it as a set of principle design decisions which drive system architects to design the architecture satisfying software requirements and architectural constraints. The design decision making process involves a group of stakeholders exchanging their viewpoints to address various concerns and to reach a consensus collaboratively. These architecture design decisions are usually made based on experiences since there aren't defined methods and models for architecture design. Each design decision yields a set of outcomes which impacts both the system architecture and the final product. As software product systems, tend to be large in size, …

Energy Disaggregation In Nialm Using Hidden Markov Models, Anusha Sankara

Masters Theses

"This work presents an appliance disaggregation technique to handle the fundamental goal of the Non-Intrusive Appliance Load Monitoring (NIALM) problem i.e., a simple breakdown of an appliance level energy consumption of a house. It also presents the modeling of individual appliances as load models using hidden Markov models and combined appliances as a single load model using factorial hidden Markov models. Granularity of the power readings of the disaggregated appliances matches with that of the readings collected at the service entrance. Accuracy of the proposed algorithm is evaluated using publicly released Tracebase data sets and UK-DALE data sets at various …

Fuzzy Adaptive Resonance Theory: Applications And Extensions, Clayton Parker Smith

Masters Theses

"Adaptive Resonance Theory, ART, is a powerful clustering tool for learning arbitrary patterns in a self-organizing manner. In this research, two papers are presented that examine the extensibility and applications of ART. The first paper examines a means to boost ART performance by assigning each cluster a vigilance value, instead of a single value for the whole ART module. A Particle Swarm Optimization technique is used to search for desirable vigilance values. In the second paper, it is shown how ART, and clustering in general, can be a useful tool in preprocessing time series data. Clustering quantization attempts to meaningfully …

Rote-Lcs Learning Classifier System For Classification And Prediction, Benjamin Daniels

Masters Theses

"Machine Learning (ML) involves the use of computer algorithms to solve for approximate solutions to problems with large, complex search spaces. Such problems have no known solution method, and search spaces too large to allow brute force search to be feasible. Evolutionary algorithms (EA) are a subset of machine learning algorithms which simulate fundamental concepts of evolution. EAs do not guarantee a perfect solution, but rather facilitate convergence to a solution of which the accuracy depends on a given EA's learning architecture and the dynamics of the problem.

Learning classifier systems (LCS) are algorithms comprising a subset of EAs. The …

Hyper-Heuristics For The Automated Design Of Black-Box Search Algorithms, Matthew Allen Martin

Masters Theses

"Within the field of Black-Box Search Algorithms (BBSAs), there is a focus on improving algorithm performance over increasingly diversified problem classes. However, these general purpose problem solvers have no guarantee to perform well on an arbitrary problem class that a practitioner needs to solve. The problem classes that the research in this thesis most applies to are difficult problems that are going to be solved multiple times. BBSAs tailored to one of these problem class can be expected to significantly outperform the more general purpose problem solvers, including canonical Evolutionary Algorithms (EAs). The first paper in this thesis explores a …

Design And Implementation Of A Broker For Cloud Additive Manufacturing Services, Venkata Prashant Modekurthy

Masters Theses

"The growing number of cloud Additive Manufacturing (AM) services, offered by different providers over the Internet, makes it challenging for consumers to compare these cloud AM services to select a service of their choice. In addition, it is even more challenging for consumers to compare these cloud AM services against their personal preferences. This is because, consumers personal preferences on multiple service attributes such as price, material, accuracy, and schedule, should be considered for cloud AM service selection. The decentralized nature of these cloud AM services coupled by the need to consider consumers personal preferences during cloud AM service selection, …

Cyber Security Research Frameworks For Coevolutionary Network Defense, George Daniel Rush

Masters Theses

"Cyber security is increasingly a challenge for organizations everywhere. Defense systems that require less expert knowledge and can adapt quickly to threats are strongly needed to combat the rise of cyber attacks. Computational intelligence techniques can be used to rapidly explore potential solutions while searching in a way that is unaffected by human bias.

Several architectures have been created for developing and testing systems used in network security, but most are meant to provide a platform for running cyber security experiments as opposed to automating experiment processes. In the first paper, we propose a framework termed Distributed Cyber Security Automation …

Aerial Vehicle Trajectory Design For Spatio-Temporal Task Satisfaction And Aggregation Based On Utility Metric, Amarender Reddy Mekala

Masters Theses

"Flight trajectories are mainly designed in order to make sure that the aerial vehicle reaches the destination point from the start point. In addition to that, the flight path is designed in such a way that the flight avoids dangerous zones and the maneuvers required for the path are practically feasible for the flight.

This thesis focuses on the aerial vehicle trajectory generation passing through a set of pre-defined way points while satisfying the task points sent by the ground base station in between the way points. Each specified waypoint is reached exactly at the specified location and time. Intermediate …

A Gaussian Mixture Model For Automated Vesicle Fusion Detection And Classification, Haohan Li

Masters Theses

"Accurately detecting and classifying vesicle-plasma membrane fusion events in fluorescence microscopy, is of primary interest for studying biological activities in a close proximity to the plasma membrane. In this paper, we present a novel Gaussian mixture model for automated identification of vesicle-plasma membrane fusion and partial fusion events in total internal reflection fluorescence microscopy image sequences. Image patches of fusion event candidates are detected in individual images and linked over consecutive frames. A Gaussian mixture model is fit on each image patch of the patch sequence with outliers rejected for robust Gaussian fitting. The estimated parameters of Gaussian functions over …

Quantitative Modeling Of The Equilibration Of Two-Phase Solid-Liquid Fe By Atomistic Simulations On Diffusive Time Scales, Ebrahim Asadi, Mohsen Asle Zaeem, Sasan Nouranian, Michael I. Baskes

Materials Science and Engineering Faculty Research & Creative Works

In this paper, molecular dynamics (MD) simulations based on the modified-embedded atom method (MEAM) and a phase-field crystal (PFC) model are utilized to quantitatively investigate the solid-liquid properties of Fe. A set of second nearest-neighbor MEAM parameters for higherature applications are developed for Fe, and the solid-liquid coexisting approach is utilized in MD simulations to accurately calculate the melting point, expansion in melting, latent heat, and solid-liquid interface free energy, and surface anisotropy. The required input properties to determine the PFC model parameters, such as liquid structure factor and fluctuations of atoms in the solid, are also calculated from MD …

Detection And Recognition Of R/F Devices Based On Their Unintended Electromagnetic Emissions Using Stochastic And Computational Intelligence Methods, Shikhar Prasad Acharya

Doctoral Dissertations

"Radio Frequency (RF) devices produce some amount of Unintended Electromagnetic Emissions (UEEs). UEEs are generally unique to a device and can be thought of as a signature of the device. This property of uniqueness of UEEs can be used to detect and identify the device producing the emission. The problem with UEEs is that they are very low in power and are often buried deep inside the noise band which makes them difficult to detect. There are two types of UEE detection methods. The first one is called stimulated detection method where the UEEs of a device are enhanced using …

Vrcc-3d+: Qualitative Spatial And Temporal Reasoning In 3 Dimensions, Nathan Eloe

Doctoral Dissertations

"Qualitative Spatial Reasoning (QSR) has varying applications in Geographic Information Systems (GIS), visual programming language semantics, and digital image analysis. Systems for spatial reasoning over a set of objects have evolved in both expressive power and complexity, but implementations or usages of these systems are not common. This is partially due to the computational complexity of the operations required by the reasoner to make informed decisions about its surroundings. These theoretical systems are designed to focus on certain criteria, including efficiency of computation, ease of human comprehension, and expressive power. Sadly, the implementation of these systems is frequently left as …

Enabling Near-Term Prediction Of Status For Intelligent Transportation Systems: Management Techniques For Data On Mobile Objects, Lasanthi Nilmini Heendaliya

Doctoral Dissertations

"Location Dependent Queries (LDQs) benefit from the rapid advances in communication and Global Positioning System (GPS) technologies to track moving objects' locations, and improve the quality-of-life by providing location relevant services and information to end users. The enormity of the underlying data maintained by LDQ applications - a large quantity of mobile objects and their frequent mobility - is, however, a major obstacle in providing effective and efficient services. Motivated by this obstacle, this thesis sets out in the quest to find improved methods to efficiently index, access, retrieve, and update volatile LDQ related mobile object data and information. …

Computational Intelligence Based Complex Adaptive System-Of-Systems Architecture Evolution Strategy, Siddharth Agarwal

Doctoral Dissertations

The dynamic planning for a system-of-systems (SoS) is a challenging endeavor. Large scale organizations and operations constantly face challenges to incorporate new systems and upgrade existing systems over a period of time under threats, constrained budget and uncertainty. It is therefore necessary for the program managers to be able to look at the future scenarios and critically assess the impact of technology and stakeholder changes. Managers and engineers are always looking for options that signify affordable acquisition selections and lessen the cycle time for early acquisition and new technology addition. This research helps in analyzing sequential decisions in an evolving …

Privacy-Preserving Query Processing Over Encrypted Data In Cloud, Yousef M. Elmehdwi

Doctoral Dissertations

"The query processing of relational data has been studied extensively throughout the past decade. A number of theoretical and practical solutions to query processing have been proposed under various scenarios. With the recent popularity of cloud computing, data owners now have the opportunity to outsource not only their data but also data processing functionalities to the cloud. Because of data security and personal privacy concerns, sensitive data (e.g., medical records) should be encrypted before being outsourced to a cloud, and the cloud should perform query processing tasks on the encrypted data only. These tasks are termed as Privacy-Preserving Query Processing …

Quantification Of Information Flow In Cyber Physical Systems, Li Feng

Doctoral Dissertations

"In Cyber Physical Systems (CPSs), traditional security mechanisms such as cryptography and access control are not enough to ensure the security of the system since complex interactions between the cyber portion and physical portion happen frequently. In particular, the physical infrastructure is inherently observable; aggregated physical observations can lead to unintended cyber information leakage. Information flow analysis, which aims to control the way information flows among different entities, is better suited for CPSs than the access control security mechanism. However, quantifying information leakage in CPSs can be challenging due to the flow of implicit information between the cyber portion, the …

Methods And Algorithms For Service Selection And Recommendation (Preference And Aggregation Based), Kenneth Kofi Fletcher

Doctoral Dissertations

"In order for service users to get the best service that meets their requirements, they prefer to personalize their non-functional attributes, such as reliability and price. However, the personalization makes it challenging because service providers have to deal with conflicting non-functional attributes when selecting services for users. In addition, users may sometimes want to explicitly specify their trade-offs among non-functional attributes to make their preferences known to service providers. Typically, users' service search requests with conflicting non-functional attributes may result in a ranked list of services that partially meet their needs. When this happens, it is natural for users to …

Distributed State Verification In The Smart Grid Using Physical Attestation, Thomas Patrick Roth

Doctoral Dissertations

"A cyber process in a distributed system can fabricate its internal state in its communications with its peers. These state fabrications can cause other processes in the distributed system to make incorrect control decisions. Cyber-physical systems have a unique advantage in the detection of falsified states because processes typically have observable effects on a shared physical infrastructure. This physical infrastructure acts as a high-integrity message channel that broadcasts changes in individual process states. The objective of this research is to demonstrate that there are cases where physical feedback from the shared infrastructure can be used to detect state fabrications. To …

Quantum Inspired Algorithms For Learning And Control Of Stochastic Systems, Karthikeyan Rajagopal

Doctoral Dissertations

"Motivated by the limitations of the current reinforcement learning and optimal control techniques, this dissertation proposes quantum theory inspired algorithms for learning and control of both single-agent and multi-agent stochastic systems.

A common problem encountered in traditional reinforcement learning techniques is the exploration-exploitation trade-off. To address the above issue an action selection procedure inspired by a quantum search algorithm called Grover's iteration is developed. This procedure does not require an explicit design parameter to specify the relative frequency of explorative/exploitative actions.

The second part of this dissertation extends the powerful adaptive critic design methodology to solve finite horizon stochastic optimal …

Efficient Cryptographic Primitives: Secure Comparison, Binary Decomposition And Proxy Re-Encryption, Feng Li

Doctoral Dissertations

”Data outsourcing becomes an essential paradigm for an organization to reduce operation costs on supporting and managing its IT infrastructure. When sensitive data are outsourced to a remote server, the data generally need to be encrypted before outsourcing. To preserve the confidentiality of the data, any computations performed by the server should only be on the encrypted data. In other words, the encrypted data should not be decrypted during any stage of the computation. This kind of task is commonly termed as query processing over encrypted data (QPED).

One natural solution to solve the QPED problem is to utilize fully …

Stochastic Adaptive Event-Triggered Control And Network Scheduling Protocol Co-Design For Distributed Networked Systems, Hao Xu, Avimanyu Sahoo, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

In a distributed 'networked control system' (NCS), multiple physical systems or agents are connected to their corresponding controllers through a shared packet-switched communication network. For such distributed NCS, periodic sampled controller design is unsuitable to handle packet-switched closed-loop control systems, and a novel stochastic optimal adaptive event-sampled controller scheme is proposed in the application layer for each physical system or agent expressed as an uncertain linear dynamic system. Lyapunov stability analysis will be utilized to derive the event trigger condition. In addition, a network scheduling protocol is also required for such NCS. Traditional network scheduling protocols are unsuitable for such …

Vehicle Base Station, Emad William Saad, John L. Vian, Matthew A. Vavrina, Jared A. Nisbett, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

A system to load and unload material from a vehicle comprises a vehicle base station and an assembly to autonomously load and unload material from the vehicle.

Efficient Integrity Verification Of Replicated Data In Cloud Using Homomorphic Encryption, Raghul Mukundan, Sanjay Madria, Mark Linderman

Computer Science Faculty Research & Creative Works

The cloud computing is an emerging model in which computing infrastructure resources are provided as a service over the internet. Data owners can outsource their data by remotely storing them in the cloud and enjoy on-demand high quality services from a shared pool of configurable computing resources. However, since data owners and the cloud servers are not in the same trusted domain, the outsourced data may be at risk as the cloud server may no longer be fully trusted. Therefore, data confidentiality, availability and integrity are of critical importance in such a scenario. The data owner encrypts data before storing …

X-Ray Emission Produced In Charge-Exchange Collisions Between Highly Charged Ions And Argon: Role Of The Multiple Electron Capture, Sebastian Otranto, N. D. Cariatore, Ronald E. Olson

Physics Faculty Research & Creative Works

In this work we use the classical trajectory Monte Carlo method within an eight-electron scheme to theoretically study photonic spectra that follow charge-exchange processes between highly charged ions of charge states 10+, 17+, 18+, and 36+ with neutral argon. The energy range considered is 18 eV/amu to 4 keV/amu, covering typical electron beam ion traps and solar wind energies. The role played by multiple electron capture processes for the different collision systems under consideration is explicitly analyzed and its contribution separated as arising from radiative decay and autoionizing multiple capture. For the present collision systems we find that multiple electron …

Theoretical And Experimental (E, 2e) Study Of Electron-Impact Ionization Of Laser-Aligned Mg Atoms, Sadek Amami, Andrew J. Murray, Al Stauffer, Kate Nixon, Gregory Armstrong, James Colgan, Don H. Madison

Physics Faculty Research & Creative Works

We have performed calculations of the fully differential cross sections for electron-impact ionization of magnesium atoms. Three theoretical approximations, the time-dependent close coupling, the three-body distorted wave, and the distorted wave Born approximation, are compared with experiment in this article. Results will be shown for ionization of the 3s ground state of Mg for both asymmetric and symmetric coplanar geometries. Results will also be shown for ionization of the 3p state which has been excited by a linearly polarized laser which produces a charge cloud aligned perpendicular to the laser beam direction and parallel to the linear polarization. Theoretical and …

Neural Network Dynamic Progamming Constrained Control Of Distributed Parameter Systems Governed By Parabolic Partial Differential Equations With Application To Diffusion-Reaction Processes, Behzad Talaei, Hao Xu, S. Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a novel neural network (NN) adaptive dynamic programming (ADP) control scheme for distributed parameter systems (DPS) governed by parabolic partial differential equations (PDE) is introduced in the presence of control constraints and unknown system dynamics. First, Galerkin method is utilized to develop a relevant reduced order system which captures the dominant dynamics of the DPS. Subsequently, a novel control scheme is proposed over finite horizon by using NN ADP. To relax the requirement of system dynamics, a novel NN identifier is developed. More-over, a second NN is proposed to estimate online the time-varying non-quadratic value function from …

Large-Scale Mechanical Buckle Fold Development And The Initiation Of Tensile Fractures, Andreas Eckert, Peter Connolly, Xiaolong Liu

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Tensile failure associated with buckle folding is commonly associated to the distribution of outer arc extension but has also been observed on fold limbs. This study investigates whether tensile stresses and associated failure can be explained by the process of buckling under realistic in situ stress conditions. A 2-D plane strain finite element modeling approach is used to study single-layer buckle folds with a Maxwell viscoelastic rheology. A variety of material parameters are considered and their influence on the initiation of tensile stresses during the various stages of deformation is analyzed. It is concluded that the buckling process determines the …

Localization Of Near-Field Radio Controlled Unintended Emitting Sources In The Presence Of Multipath Fading, Nurbanu Guzey, Hao Xu, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

Localization of near-field unintended emitting radio controlled (RC) devices under a multipath environment is considered in this paper using a uniform linear array (ULA). Since received signals are dependent on both angle of arrival (AoA) and distance from the RC devices to the ULA in the near-field scenario, traditional localization schemes based on received signal strength indicator, time difference in arrival, which only estimate either AoA or distance, are unsuitable. Therefore, a novel smooth 2-D multiple signal classification (MUSIC) near-field localization scheme is developed to locate RC devices under a multipath environment with a possible location error of 0.5 m. …