Physical Sciences and Mathematics Commons^™

Microstructural Analysis Of Thermoelastic Response, Nonlinear Creep, And Pervasive Cracking In Heterogeneous Materials, Alden C. Cook

Electronic Theses and Dissertations

This dissertation is concerned with the development of robust numerical solution procedures for the generalized micromechanical analysis of linear and nonlinear constitutive behavior in heterogeneous materials. Although the methods developed are applicable in many engineering, geological, and materials science fields, three main areas are explored in this work. First, a numerical methodology is presented for the thermomechanical analysis of heterogeneous materials with a special focus on real polycrystalline microstructures obtained using electron backscatter diffraction techniques. Asymptotic expansion homogenization and finite element analysis are employed for micromechanical analysis of polycrystalline materials. Effective thermoelastic properties of polycrystalline materials are determined and compared …

Investigating High Speed Localization Microscopy Through Experimental Methods, Data Processing Methods, And Applications Of Localization Microscopy To Biological Questions, Andrew J. Nelson

Electronic Theses and Dissertations

Fluorescence Photoactivation Localization Microscopy(FPALM) and other super resolution localization microscopy techniques can resolve structures with nanoscale resolution. Unlike techniques of electron microscopy, they are also compatible with live cell and live animal studies, making FPALM and related techniques ideal for answering questions about the dynamic nature of molecular biology in living systems. Many processes in biology occur on rapid sub second time scales requiring the imaging technique to be capable of resolving these processes not just with a high enough spatial resolution, but with an appropriate temporal resolution. To that end, this Dissertation in part investigates high speed FPALM as …

A Reduced Labeled Samples (Rls) Framework For Classification Of Imbalanced Concept-Drifting Streaming Data., Elaheh Arabmakki

Electronic Theses and Dissertations

Stream processing frameworks are designed to process the streaming data that arrives in time. An example of such data is stream of emails that a user receives every day. Most of the real world data streams are also imbalanced as is in the stream of emails, which contains few spam emails compared to a lot of legitimate emails. The classification of the imbalanced data stream is challenging due to the several reasons: First of all, data streams are huge and they can not be stored in the memory for one time processing. Second, if the data is imbalanced, the accuracy …

Improving The Performance Of Ice Sheet Modeling Through Embedded Simulation, Christopher G. Dufour

Electronic Theses and Dissertations

Understanding the impact of global climate change is a critical concern for society at large. One important piece of the climate puzzle is how large-scale ice sheets, such as those covering Greenland and Antarctica, respond to a warming climate. Given such ice sheets are under constant change, developing models that can accurately capture their dynamics represents a significant challenge to researchers. The problem, however, is properly capturing the dynamics of an ice sheet model requires a high model resolution and simulating these models is intractable even for state-of-the-art supercomputers.

This thesis presents a revolutionary approach to accurately capture ice sheet …

An Algorithm For The Machine Calculation Of Minimal Paths, Robert Whitinger

Electronic Theses and Dissertations

Problems involving the minimization of functionals date back to antiquity. The mathematics of the calculus of variations has provided a framework for the analytical solution of a limited class of such problems. This paper describes a numerical approximation technique for obtaining machine solutions to minimal path problems. It is shown that this technique is applicable not only to the common case of finding geodesics on parameterized surfaces in R³, but also to the general case of finding minimal functionals on hypersurfaces in Rⁿ associated with an arbitrary metric.

Sparse Feature Learning For Image Analysis In Segmentation, Classification, And Disease Diagnosis., Ehsan Hosseini-Asl

Electronic Theses and Dissertations

The success of machine learning algorithms generally depends on intermediate data representation, called features that disentangle the hidden factors of variation in data. Moreover, machine learning models are required to be generalized, in order to reduce the specificity or bias toward the training dataset. Unsupervised feature learning is useful in taking advantage of large amount of unlabeled data, which is available to capture these variations. However, learned features are required to capture variational patterns in data space. In this dissertation, unsupervised feature learning with sparsity is investigated for sparse and local feature extraction with application to lung segmentation, interpretable deep …

Transcriptional And Post-Transcriptional Regulation Of Gene Expression, Jun Ding

Electronic Theses and Dissertations

Regulation of gene expression includes a variety of mechanisms to increase or decrease specific gene products. Gene expression can be regulated at any stage from transcription to post-transcription and it's essential to almost all living organisms, as it increases the versatility and adaptability by allowing the cell to express the needed proteins. In this dissertation, we comprehensively studied the gene regulation from both transcriptional and post-transcriptional points of view. Transcriptional regulation is by which cells regulate the transcription from DNA to RNA, thereby directing gene activity. Transcriptional factors (TFs) play a very important role in transcriptional regulation and they are …

A Comparison Of Concurrent Correctness Criteria For Shared Memory Based Data Structure, Dipanjan Bhattacharya

Electronic Theses and Dissertations

Developing concurrent algorithms requires safety and liveness to be defined in order to understand their proper behavior. Safety refers to the correctness criteria while liveness is the progress guarantee. Nowadays there are a variety of correctness conditions for concurrent objects. The way these correctness conditions differ and the various trade-offs they present with respect to performance, usability, and progress guarantees is poorly understood. This presents a daunting task for the developers and users of such concurrent algorithms who are trying to better understand the correctness of their code and the various trade-offs associated with their design choices and use. The …

Analysis Of Commutativity With State-Chart Graph Representation Of Concurrent Programs., Kishore Debnath

Electronic Theses and Dissertations

We present a new approach to check for Commutativity in concurrent programs from their run-time state-chart graphs. Two operations are said to be commutative if changing the order of their execution do not change the resultant effect on the working object. Commutative property is capable of boosting performance in concurrent transactions such that transactional concurrency is comparable to a non-blocking linearizable version of a similar data structure type. Transactional concurrency is a technique that analyses object semantics, as object states, to determine conflicts and recovery between conflicting operations. Processes that commute at object level can be executed concurrently at transaction …

Techniques For Automated Parameter Estimation In Computational Models Of Probabilistic Systems, Faraz Hussain

Electronic Theses and Dissertations

The main contribution of this dissertation is the design of two new algorithms for automatically synthesizing values of numerical parameters of computational models of complex stochastic systems such that the resultant model meets user-specified behavioral specifications. These algorithms are designed to operate on probabilistic systems – systems that, in general, behave differently under identical conditions. The algorithms work using an approach that combines formal verification and mathematical optimization to explore a model's parameter space. The problem of determining whether a model instantiated with a given set of parameter values satisfies the desired specification is first defined using formal verification terminology, …

Spatiotemporal Graphs For Object Segmentation And Human Pose Estimation In Videos, Dong Zhang

Electronic Theses and Dissertations

Images and videos can be naturally represented by graphs, with spatial graphs for images and spatiotemporal graphs for videos. However, for different applications, there are usually different formulations of the graphs, and algorithms for each formulation have different complexities. Therefore, wisely formulating the problem to ensure an accurate and efficient solution is one of the core issues in Computer Vision research. We explore three problems in this domain to demonstrate how to formulate all of these problems in terms of spatiotemporal graphs and obtain good and efficient solutions. The first problem we explore is video object segmentation. The goal is …

Computational Approaches For Binning Metagenomic Reads, Ying Wang

Electronic Theses and Dissertations

Metagenomics uses sequencing technologies to study genetic sequences from whole microbial communities. Binning metagenomic reads is the most fundamental step in metagenomic studies, which is essential for the understanding of microbial functions, compositions, and interactions in environmental samples. Various taxonomy-dependent and taxonomy-independent approaches have been developed based on information such as sequence similarity, sequence composition, or k-mer frequency. However, there is still room for improvement, and it is still challenging to bin reads from species with similar or low abundance or to bin reads from unknown species. In this dissertation, we introduce one taxonomy-independent and three taxonomy-dependent approaches to improve …

Similarity Measurement Of Breast Cancer Mammographic Images Using Combination Of Mesh Distance Fourier Transform And Global Features, Ravi Kasaudhan

Electronic Theses and Dissertations

Similarity measurement in breast cancer is an important aspect of determining the vulnerability of detected masses based on the previous cases. It is used to retrieve the most similar image for a given mammographic query image from a collection of previously archived images. By analyzing these results, doctors and radiologists can more accurately diagnose early-stage breast cancer and determine the best treatment. The direct result is better prognoses for breast cancer patients. Similarity measurement in images has always been a challenging task in the field of pattern recognition. A widely-adopted strategy in Content-Based Image Retrieval (CBIR) is comparison of local …

Product Authentication Using Hash Chains And Printed Qr Codes, Harshith R. Keni

Electronic Theses and Dissertations

This thesis explores the usage of simple printed tags for authenticating products. Printed tags are a cheap alternative to RFID and other tag based systems and do not require specialized equipment. Due to the simplistic nature of such printed codes, many security issues like tag impersonation, server impersonation, reader impersonation, replay attacks and denial of service present in RFID based solutions need to be handled differently. An algorithm that utilizes hash chains to secure such simple tags while still keeping cost low is discussed. The security characteristics of this scheme as well as other product authentication schemes that use RFID …

The Woz Recognizer: A Tool For Understanding User Perceptions Of Sketch-Based Interfaces, Jared Bott

Electronic Theses and Dissertations

Sketch recognition has the potential to be an important input method for computers in the coming years; however, designing and building an accurate and sophisticated sketch recognition system is a time consuming and daunting task. Since sketch recognition is still at a level where mistakes are common, it is important to understand how users perceive and tolerate recognition errors and other user interface elements with these imperfect systems. A problem in performing this type of research is that we cannot easily control aspects of recognition in order to rigorously study the systems. We performed a study examining user perceptions of …

A Study Of Holistic Strategies For The Recognition Of Characters In Natural Scene Images, Muhammad Ali

Electronic Theses and Dissertations

Recognition and understanding of text in scene images is an important and challenging task. The importance can be seen in the context of tasks such as assisted navigation for the blind, providing directions to driverless cars, e.g. Google car, etc. Other applications include automated document archival services, mining text from images, and so on. The challenge comes from a variety of factors, like variable typefaces, uncontrolled imaging conditions, and various sources of noise corrupting the captured images. In this work, we study and address the fundamental problem of recognition of characters extracted from natural scene images, and contribute three holistic …

Gesture Assessment Of Teachers In An Immersive Rehearsal Environment, Roghayeh Barmaki

Electronic Theses and Dissertations

Interactive training environments typically include feedback mechanisms designed to help trainees improve their performance through either guided- or self-reflection. When the training system deals with human-to-human communications, as one would find in a teacher, counselor, enterprise culture or cross-cultural trainer, such feedback needs to focus on all aspects of human communication. This means that, in addition to verbal communication, nonverbal messages must be captured and analyzed for semantic meaning. The goal of this dissertation is to employ machine-learning algorithms that semi-automate and, where supported, automate event tagging in training systems developed to improve human-to-human interaction. The specific context in which …

Spatial And Temporal Modeling For Human Activity Recognition From Multimodal Sequential Data, Jun Ye

Electronic Theses and Dissertations

Human Activity Recognition (HAR) has been an intense research area for more than a decade. Different sensors, ranging from 2D and 3D cameras to accelerometers, gyroscopes, and magnetometers, have been employed to generate multimodal signals to detect various human activities. With the advancement of sensing technology and the popularity of mobile devices, depth cameras and wearable devices, such as Microsoft Kinect and smart wristbands, open a unprecedented opportunity to solve the challenging HAR problem by learning expressive representations from the multimodal signals recording huge amounts of daily activities which comprise a rich set of categories. Although competitive performance has been …

Quantitative Framework For Social Cultural Interactions, Taranjeet Singh Bhatia

Electronic Theses and Dissertations

For an autonomous robot or software agent to participate in the social life of humans, it must have a way to perform a calculus of social behavior. Such a calculus must have explanatory power (it must provide a coherent theory for why the humans act the way they do), and predictive power (it must provide some plausible events from the predicted future actions of the humans). This dissertation describes a series of contributions that would allow agents observing or interacting with humans to perform a calculus of social behavior taking into account cultural conventions and socially acceptable behavior models. We …

Tryopenjml - A Verily Based Web Application For Learning About The Java Modeling Language, Tushar Deshpande

Electronic Theses and Dissertations

This thesis has a two-fold purpose. On the one hand, the web applications are an important part of life. On a day to day basis, from managing our heath care choices to banking, to connecting to a friend, almost everything is done through a web application. Development of these applications is also a very trend-driven domain. Numerous web frameworks are available today, but almost none has been created taking reliability into consideration. With the combination of application construction recipes and static analysis, the Verily framework was created to build more reliable web applications. On the other hand, the goal of …

Breast Cancer Classification Of Mammographic Masses Using Circularity Max Metric, A New Method, Tae Keun Heo

Electronic Theses and Dissertations

Breast cancer classification can be divided into two categories. The first category is a benign tumor, and the other is a malignant tumor. The main purpose of breast cancer classification is to classify abnormalities into benign or malignant classes and thus help physicians with further analysis by minimizing potential errors that can be made by fatigued or inexperienced physicians. This paper proposes a new shape metric based on the area ratio of a circle to classify mammographic images into benign and malignant class. Support Vector Machine is used as a machine learning tool for training and classification purposes. The improved …

Optimizing Vehicle Usage Using Csp, Sat And Max-Sat, Raheem T. Al Rammahi

Electronic Theses and Dissertations

Most of the companies in Iraq spend significant amounts of time and money when transferring employees between home and work. In this thesis, we model the problem of the Dhi Qar Oil company (DQOC) transportations using three modeling languages from AI: Constraint Programing (CP), Boolean Satisfiability (SAT), and Maximum Satisfiability (MAX-SAT). We then use solvers to find optimal solutions to this problem.

We show which of these solvers is more efficient when finding optimal solutions. For this purpose, we create a test suite of 360 problems to test these solvers. All solvers are applied to these problems and the final …

Greenc5: An Adaptive, Energy-Aware Collection For Green Software Development, Junya Michanan

Electronic Theses and Dissertations

Dynamic data structures in software applications have been shown to have a large impact on system performance. In this paper, we explore energy saving opportunities of interface-based dynamic data structures. Our results suggest that savings opportunities exist in the C5 Collection between 16.95% and 97.50%. We propose a prototype and architecture for creating adaptive green data structures by applying machine learning tools to build a model for predicting energy efficient data structures based on the dynamic workload. Our neural network model can classify energy efficient data structures based on features such as the number of elements, frequency of operations, interface …

Implementing Agile Development At Scale: An Industry Case Study, Nikita Kataria

Electronic Theses and Dissertations

Agile software development methodologies are extremely popular. Their dynamic restructuring of the development process has been seen as the silver bullet for increasing the productivity of software development. A significant number of studies have analyzed the impact of implementing agile techniques. However these are mostly evaluated only in smaller team settings. There is very little reporting done on how agile development methods can be implemented at the team level and scaled up at the program/portfolio level in large software organizations.

We present the results of an empirical study conducted at Pearson Education. The study focuses on the penetration of agile …

A Near-To-Far Learning Framework For Terrain Characterization Using An Aerial/Ground-Vehicle Team, Ashkan Hajjam

Electronic Theses and Dissertations

In this thesis, a novel framework for adaptive terrain characterization of untraversed far terrain in a natural outdoor setting is presented. The system learns the association between visual appearance of different terrain and the proprioceptive characteristics of that terrain in a self-supervised framework. The proprioceptive characteristics of the terrain are acquired by inertial sensors recording measurements of one second traversals that are mapped into the frequency domain and later through a clustering technique classified into discrete proprioceptive classes. Later, these labels are used as training inputs to the adaptive visual classifier. The visual classifier uses images captured by an aerial …

Model Based Security Testing For Autonomous Vehicles, Seana Lisa Hagerman

Electronic Theses and Dissertations

The purpose of this dissertation is to introduce a novel approach to generate a security test suite to mitigate malicious attacks on an autonomous system. Our method uses model based testing (MBT) methods to model system behavior, attacks and mitigations as independent threads in an execution stream. The threads intersect at a rendezvous or attack point. We build a security test suite from a behavioral model, an attack type and a mitigation model using communicating extended finite state machine (CEFSM) models. We also define an applicability matrix to determine which attacks are possible with which states. Our method then builds …

Leveraging Client Processing For Location Privacy In Mobile Local Search, Wisam Mohamed Eltarjaman

Electronic Theses and Dissertations

Usage of mobile services is growing rapidly. Most Internet-based services targeted for PC based browsers now have mobile counterparts. These mobile counterparts often are enhanced when they use user's location as one of the inputs. Even some PC-based services such as point of interest Search, Mapping, Airline tickets, and software download mirrors now use user's location in order to enhance their services. Location-based services are exactly these, that take the user's location as an input and enhance the experience based on that. With increased use of these services comes the increased risk to location privacy. The location is considered an …

Reducing Cache Contention On Gpus, Kyoshin Choo

Electronic Theses and Dissertations

The usage of Graphics Processing Units (GPUs) as an application accelerator has become increasingly popular because, compared to traditional CPUs, they are more cost-effective, their highly parallel nature complements a CPU, and they are more energy efficient. With the popularity of GPUs, many GPU-based compute-intensive applications (a.k.a., GPGPUs) present significant performance improvement over traditional CPU-based implementations. Caches, which significantly improve CPU performance, are introduced to GPUs to further enhance application performance. However, the effect of caches is not significant for many cases in GPUs and even detrimental for some cases. The massive parallelism of the GPU execution model and the …

Peccit: An Omniscient Debugger For Web Development, Zachary Ryan Azar

Electronic Theses and Dissertations

Debugging can be an extremely expensive and time-consuming task for a software developer. To find a bug, the developer typically needs to navigate backwards through infected states and symptoms of the bug to find the initial defect. Modern debugging tools are not designed for navigating back-in-time and typically require the user to jump through hoops by setting breakpoints, re-executing, and guessing where errors occur. Omniscient debuggers offer back-in-time debugging capabilities to make this task easier. These debuggers trace the program allowing the user to navigate forwards and backwards through the execution, examine variable histories, and visualize program data and control …

Obstacle-Aware Wireless Video Sensor Network Deployment For 3d Indoor Space Monitoring, Zhonghui Wang

Electronic Theses and Dissertations

In recent years wireless video sensors networks (WVSNs) have emerged as a leading technology for monitoring 3D indoor space in campus, industrial and medical areas as well as other types of environments. In contrast to traditional sensors such as heat or light sensors often considered with omnidirectional sensing range, the sensing range of a video sensor is directional and can be deemed as a pyramid-shape in 3D. Moreover, in an indoor environment, there are often obstacles such as lamp stands or furniture, which introduce additional challenges and further render the deployment solutions for traditional sensors and 2D sensing field inapplicable …