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Articles 1 - 30 of 37
Full-Text Articles in Physical Sciences and Mathematics
Constructing And Validating Feature Models Using Relational, Document, And Graph Databases, Hazim Shatnawi
Constructing And Validating Feature Models Using Relational, Document, And Graph Databases, Hazim Shatnawi
Electronic Theses and Dissertations
Building a software product line (SPL) is a systematic strategy for reusing software within a family of related systems from some application domain. To define an SPL, a domain analyst must identify the common and variable aspects of a family of systems and capture them for later use in construction of specific products. To do so, Feature-Oriented Domain Analysis (FODA) introduced the feature model as an abstraction to represent the common and variable aspects, using a feature diagram to depict the model visually. However, this abstraction is often difficult for developers to use because most tools rely on specialized theories, …
Dependency-Based Reactive Change Propagation Design Pattern Applied To Environments With High Unpredictability, João Paulo Oliveira Marum
Dependency-Based Reactive Change Propagation Design Pattern Applied To Environments With High Unpredictability, João Paulo Oliveira Marum
Electronic Theses and Dissertations
Transitional turbulence is a period of chaotic or unreliable variation in the state of a software system that results from changes in the system’s interconnected components. During these periods of instability, an external observer of the system’s state may “see” erroneous results. This is a problem that can affect visual user interfaces such as those in virtual and augmented reality applications and desktop or Web GUIs. In this research, we study two different reactive applications developed in C# on .NET. We reduce the transitional turbulence by augmenting the base applications with a dependency-graph-based event scheduling approach. The first study investigates …
Building An Automated Q-A System Using Online Forums As Knowledge Bases, Kyle Moore
Building An Automated Q-A System Using Online Forums As Knowledge Bases, Kyle Moore
Electronic Theses and Dissertations
Question-Answer systems traditionally use expensive and difficult to produce structured knowledge bases. Recent systems have used unstructured natural language sources as their datasets, but most of those sources have been overly broad or difficult to extend. Online forums are a largely untapped source of information that can provide both depth and breadth when limited to a specific domain, as well as being adaptive to the introduction of new information. In this paper, I conjecture that online forums can be similarly and effectively used as an unstructured knowledge base for Question-Answer systems. I use a relatively simple summarization-based approach to analyze …
Towards Misleading Connection Mining, Md Main Uddin Rony
Towards Misleading Connection Mining, Md Main Uddin Rony
Electronic Theses and Dissertations
This study introduces a new Natural Language Generation (NLG) task – Unit Claim Identification. The task aims to extract every piece of verifiable information from a headline. The Unit Claim identification has applications in other domains; such as fact-checking where the identification of each verifiable information from a check-worthy statement can lead to an effective fact-check. Moreover, the extracting of the unit claims from headlines can identify a misleading news article, by mapping evidence from contents. For addressing the unit claim identification problem, we outlined a set of guidelines for data annotation, arranged in-house training for the annotators and obtained …
Optimizing The Performance Of Complex Engineering Systems Aided By Artificial Neural Networks, Khalil Qatu
Optimizing The Performance Of Complex Engineering Systems Aided By Artificial Neural Networks, Khalil Qatu
Electronic Theses and Dissertations
In the first problem Polyetherimide graphene nanoplatelets papers (PEIGNP) were tested with different graphene loadings varying from 0-97 weight percent (WT%). The resulting stress-strain curves were utilized to develop two ANN models. Stress-controlled and strain-controlled models. Both models shoan excellent correlation to the experimental. Several Mechanical properties were calculated from the predicted stress-strain curves namely; toughness maximum strength maximum strain and maximum tangent modulus. Both models captured the same overall behavior of the PEIGNP composite. However the strain-controlled model was found to predict lower stress than the stress-controlled model. Finally a Graphical User Interface (GUI) was developed to aid in …
Performance Evaluation Of Blocking And Non-Blocking Concurrent Queues On Gpus, Hossein Pourmeidani
Performance Evaluation Of Blocking And Non-Blocking Concurrent Queues On Gpus, Hossein Pourmeidani
Electronic Theses and Dissertations
The efficiency of concurrent data structures is crucial to the performance of multi-threaded programs in shared-memory systems. The arbitrary execution of concurrent threads, however, can result in an incorrect behavior of these data structures. Graphics Processing Units (GPUs) have appeared as a powerful platform for high-performance computing. As regular data-parallel computations are straightforward to implement on traditional CPU architectures, it is challenging to implement them in a SIMD environment in the presence of thousands of active threads on GPU architectures. In this thesis, we implement a concurrent queue data structure and evaluate its performance on GPUs to understand how it …
An Approach To Semi-Autonomous Indoor Drone System: Software Architecture And Integration Testing, Shobhan Singh
An Approach To Semi-Autonomous Indoor Drone System: Software Architecture And Integration Testing, Shobhan Singh
Electronic Theses and Dissertations
To address these problems, we establish a semi-autonomous functionality by removing the RC transmitter, and remotely connecting the Drone System to track status and executing user-based input commands. In order to resolve the limitation in hardware connections on the Flight Controller, we integrated the sonar sensor into a companion computer, from where the data is continuously fed to an embedded system through MAVLink (Micro Aerial Vehicle Link) network communication protocol. In this study, we also implemented a modular architecture which enables scalable integration of sensor modules into the Drone System to streamline the process of development, deployment, testing and debugging.
Utilizing Various Neural Network Architectures To Play A Game Developed For Human Players, Michael Blake Arender
Utilizing Various Neural Network Architectures To Play A Game Developed For Human Players, Michael Blake Arender
Electronic Theses and Dissertations
Neural Networks have received an explosive amount of attention and interest in recent years. Despite the fact that Neural Network algorithms having existed for many decades, it was not until recent advances in computer hardware that they saw widespread use. This is in no small part due to the success these algorithms have had in tasks ranging from image classification, voice recognition, game theory, and many other applications. Thanks to recent strides in hardware development, most importantly in the advancements in Graphics Processor Units including the capabilities of modern GPU Computing, Neural Networks are now capable of solving tasks at …
Scheduling Irregular Workloads On Gpus, David Arthur Troendle
Scheduling Irregular Workloads On Gpus, David Arthur Troendle
Electronic Theses and Dissertations
This doctoral research aims at understanding the nature of the overhead for data irregular GPU workloads, proposing a solution, and examining the consequences of the result. We propose a novel, retry-free GPU workload scheduler for irregular workloads. When used in a Breadth First Search (BFS) algorithm, the proposed simple, monolithic concurrent queue scales to within 10% of ideal scalability on AMD’s Fiji GPU with 14,336 active threads. The dissertation presents an important finding that the retry overhead associated with Compare and Swap (CAS) operations is the principle reason why concurrent queues do not scale well as the number of clients …
Improving Random Forests By Feature Dependence Analysis, Silu Zhang
Improving Random Forests By Feature Dependence Analysis, Silu Zhang
Electronic Theses and Dissertations
Random forests (RFs) have been widely used for supervised learning tasks because of their high prediction accuracy good model interpretability and fast training process. However they are not able to learn from local structures as convolutional neural networks (CNNs) do when there exists high dependency among features. They also cannot utilize features that are jointly dependent on the label but marginally independent of it. In this dissertation we present two approaches to address these two problems respectively by dependence analysis. First a local feature sampling (LFS) approach is proposed to learn and use the locality information of features to group …
Building An Autonomous Indoor Drone System, Hunter Gossett
Building An Autonomous Indoor Drone System, Hunter Gossett
Electronic Theses and Dissertations
This thesis presents an indoor autonomous drone system using a self assembled drone which uses a companion computer as well as external sensors for autonomous flight. While autonomous drone systems have been around for some time, originating with the military, the vast majority of them are designed for outdoor use, because of their heavy reliance on GPS for their positioning systems. In order to achieve autonomous flight indoors we choose to use simultaneous localization and mapping (slam) as our positioning system. The contributions of this thesis is an in depth guide to the hardware and assembly of a drone system, …
A Study Of Computational Problems In Computational Biology And Social Networks: Cancer Informatics And Cascade Modelling, Christopher Ma
A Study Of Computational Problems In Computational Biology And Social Networks: Cancer Informatics And Cascade Modelling, Christopher Ma
Electronic Theses and Dissertations
It is undoubtedly that everything in this world is related and nothing independently exists. Entities interact together to form groups, resulting in many complex networks. Examples involve functional regulation models of proteins in biology, communities of people within social network. Since complex networks are ubiquitous in daily life, network learning had been gaining momentum in a variety of discipline like computer science, economics and biology. This call for new technique in exploring the structure as well as the interactions of network since it provides insight in understanding how the network works and deepening our knowledge of the subject in hand. …
Machine Learning And Natural Language Methods For Detecting Psychopathy In Textual Data, Andrew Stephen Henning
Machine Learning And Natural Language Methods For Detecting Psychopathy In Textual Data, Andrew Stephen Henning
Electronic Theses and Dissertations
Among the myriad of mental conditions permeating through society, psychopathy is perhaps the most elusive to diagnose and treat. With the advent of natural language processing and machine learning, however, we have ushered in a new age of technology that provides a fresh toolkit for analyzing text and context. Because text remains the medium of choice for most personal and professional interactions, it may be possible to use textual samples from psychopaths as a means for understanding and ultimately classifying similar individuals based on the content of their language usage. This paper aims to investigate natural language processing and supervised …
Deployment, Coverage And Network Optimization In Wireless Video Sensor Networks For 3d Indoor Monitoring, Tisha Lafaye Brown
Deployment, Coverage And Network Optimization In Wireless Video Sensor Networks For 3d Indoor Monitoring, Tisha Lafaye Brown
Electronic Theses and Dissertations
As a result of extensive research over the past decade or so, wireless sensor networks (wsns) have evolved into a well established technology for industry, environmental and medical applications. However, traditional wsns employ such sensors as thermal or photo light resistors that are often modeled with simple omni-directional sensing ranges, which focus only on scalar data within the sensing environment. In contrast, the sensing range of a wireless video sensor is directional and capable of providing more detailed video information about the sensing field. Additionally, with the introduction of modern features in non-fixed focus cameras such as the pan, tilt …
A Work-Stealing For Dynamic Workload Balancing On Cpu-Gpu Heterogeneous Computing Platforms, Esraa A. Gad
A Work-Stealing For Dynamic Workload Balancing On Cpu-Gpu Heterogeneous Computing Platforms, Esraa A. Gad
Electronic Theses and Dissertations
Although many general purpose workloads have been accelerated on graphical processing units (gpus) over the last decade, other applications whose runtime behaviors are dynamic and irregular such as ones based on trees and graphs have suffered from serious workload imbalance problem caused by architectural differences between cpu and gpu processors. In this thesis, we propose a work-stealing framework to overcome such problems. Our proposed framework allows cpu and gpu threads to steal tasks from each other as well as within the same device by leveraging fine-grained data sharing and thread communication feature available on modern cpu-gpu heterogeneous systems. The implementation …
Blockchains For Publicizing Available Scientific Datasets, Shirish Patel
Blockchains For Publicizing Available Scientific Datasets, Shirish Patel
Electronic Theses and Dissertations
This thesis explores the effectiveness of blockchain technology for advertisement of scientific data. Recently the advancement in hardware and software for data processing increases the supply and demand for huge data sets. Such data may be widely distributed, and not immediately available to the scientists who need it. We need a method of advertising available datasets to interested parties. Blockchains are a recent innovation developed by the cryptocurrency community, but are increasingly applied to other problem domains. Due to their currency heritage, however, the properties of blockchains do not always lend themselves to new applications. We have developed a prototype …
A Probabilistic Approach To Multiple-Instance Learning, Silu Zhang
A Probabilistic Approach To Multiple-Instance Learning, Silu Zhang
Electronic Theses and Dissertations
This study introduced a probabilistic approach to the multiple-instance learning (mil) problem. In particular, two bayes classication algorithms were proposed where posterior probabilities were estimated under dierent assumptions. The rst algorithm, named instance-vote, assumes that the probability of a bag being positive or negative depends upon the percentage of its instances being positive or negative. This probability is estimated using a k-nn classication of instances. In the second approach, embedded kernel density estimation (ekde), bags are represented in an instance induced (very high dimensional) space. A parametric stochastic neighbor embedding method is applied to learn a mapping that projects bags …
Accelerating The Discontinuous Galerkin Cell-Vertex Scheme (Dg-Cvs) Solver On Cpu-Gpu Heterogeneous Systems, Xiaoqi Hu
Electronic Theses and Dissertations
Dg-Cvs (Discontinuous Galerkin Cell-Vertex Scheme) is an efficient, accurate and robust numerical solver for general hyperbolic conservation laws. It can solve a broad range of conservation laws such as the shallow water equation and Magnetohydrodynamics equations. Dg-Cvs is a Riemann-Solver-free high order space-time method for arbitrary space conservation laws. It fuses the discontinuous Galerkin (dg) method and the conservation element/solution element (ce/se) method to take advantage of the best features of both methods. Thanks to the ce/se method, the time derivative of the solution is treated as an independent unknown, which is amendable to gpu's parallel execution. In this thesis, …
Genetic Algorithm For University Course Timetabling Problem, Achini Kumari Herath
Genetic Algorithm For University Course Timetabling Problem, Achini Kumari Herath
Electronic Theses and Dissertations
Creating timetables for institutes which deal with transport, sport, workforce, courses, examination schedules, and healthcare scheduling is a complex problem. It is difficult and time consuming to solve due to many constraints. Depending on whether the constraints are essential or desirable they are categorized as ‘hard’ and ‘soft’, respectively. Two types of timetables, namely, course and examination are designed for academic institutes. A feasible course timetable could be described as a plan for the movement of students and staff from one classroom to another, without conflicts. Being an NP-complete problem, many attempts have been made using varying computational methods to …
Reducing Cache Contention On Gpus, Kyoshin Choo
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 …
Obstacle-Aware Wireless Video Sensor Network Deployment For 3d Indoor Space Monitoring, Zhonghui Wang
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 …
The Effect Of Hyperparameters In The Activation Layers Of Deep Neural Networks, Clay Lafayette Mcleod
The Effect Of Hyperparameters In The Activation Layers Of Deep Neural Networks, Clay Lafayette Mcleod
Electronic Theses and Dissertations
Deep neural networks (DNNs), and artificial neural networks (ANNs) in general, have recently received a great amount of attention from both the media and the machine learning community at large. DNNs have been used to produce world-class results in a variety of domains, including image recognition, speech recognition, sequence modeling, and natural language processing. Many of most exciting recent deep neural network studies have made improvements by hardcoding less about the network and giving the neural network more control over its own parameters, allowing flexibility and control within the network. Although much research has been done to introduce trainable hyperparameters …
Power And Hotspot Modeling For Modern Gpus, Md Mainul Hassan
Power And Hotspot Modeling For Modern Gpus, Md Mainul Hassan
Electronic Theses and Dissertations
As General Purpose GPUs (GPGPU) are increasingly becoming a prominent component of high performance computing platforms, power and thermal dissipation are getting more attention. The trade-offs among performance, power, and heat must be well modeled and evaluated from the early stage of GPU design. This necessitates a tool that allows GPU architects to quickly and accurately evaluate their design. There are a few models for GPU power but most of them estimate power at a higher level than architecture, which are therefore missing hardware reconfigurability. In this thesis, we propose a framework that models power and heat dissipation at the …
Specification And Mechanical Verification Of Performance Profiles Of Software Components, Nighat Yasmin
Specification And Mechanical Verification Of Performance Profiles Of Software Components, Nighat Yasmin
Electronic Theses and Dissertations
Software performance predictability is vital to a system design and unpredictable performance is a leading cause of software failure. The emphasis of this dissertation is on verification that component-based software performs as specified. Performance profiles (specifications) depend on functional specifications and are necessary for all components for modular verification. Modular verification process is scalable because it uses profiles as contracts and allows verification of a single component in isolation with the assumption that any underlying component would have already been verified or will be verified to meet its specifications independently. This dissertation presents an integration of performance specification (profiles) with …
Design And Implementation Of Fast Motion Estimation In Modern Video Compression On Gpu, Zhaohua Yi
Design And Implementation Of Fast Motion Estimation In Modern Video Compression On Gpu, Zhaohua Yi
Electronic Theses and Dissertations
Motion estimation is the most compute expensive part of high definition video compression. It accounts for more than 50\% of overall execution. Therefore, improving the performance of motion estimation can make significant impact on the overall performance of video compression. The performance of motion estimation can be improved in two aspects: algorithm and implementation. This thesis touches both aspects. We first propose an innovative motion estimation algorithm by replacing the traditional block matching method which comparing blocks pixel by pixel with a brand new method which based on lbp (local binary pattern) code. Our new method first encodes the original …
Functional Reactive Programming For Games, Peter Adewunmi Salu
Functional Reactive Programming For Games, Peter Adewunmi Salu
Electronic Theses and Dissertations
We investigate the effectiveness of functional reactive programming for games. To accomplish this, we clone aa, an existing game, in Elm, a purely functional programming language. We find that functional reactive programming offers an excellent alternative to event driven programming in purely functional languages. Elm still needs more work if it aims to compete with JavaScript libraries. Games, which typically need several inputs at the same time, benefit from the first class status of Signals, which allow them to be combined.
Impact Of Thread Scheduling On Modern Gpus, Orevaoghene Addoh
Impact Of Thread Scheduling On Modern Gpus, Orevaoghene Addoh
Electronic Theses and Dissertations
The Graphics Processing Unit (GPU) has become a more important component in high-performance computing systems as it accelerates data and compute intensive applications significantly with less cost and power. The GPU achieves high performance by executing massive number of threads in parallel in a SPMD (Single Program Multiple Data) fashion. Threads are grouped into workgroups by programmer and workgroups are then assigned to each compute core on the GPU by hardware. Once assigned, a workgroup is further subgrouped into wavefronts of the fixed number of threads by hardware when executed in a SIMD (Single Instruction Multiple Data) fashion. In this …
Segmentation And Spatial Depth Ridge Detection Of Unorganized Point Cloud Data, James Clark Church
Segmentation And Spatial Depth Ridge Detection Of Unorganized Point Cloud Data, James Clark Church
Electronic Theses and Dissertations
Visual 3D data are of interest to a number of fields: medical professionals, game designers, graphic designers, and (in the interest of this paper) ichthyologists interested in the taxonomy of fish. Since the release of the Kinect for the Microsoft XBox, game designers have been interested in using the 3D data returned by the device to understand human movement and translate that movement into an interface with which to interact with game systems. In the medical field, researchers must use computer vision tools to navigate through the data found in CT scans and MRI scans. These tools must segment images …
Exploration Into The Performance Of Asymmetric D-Ary Heap-Based Algorithms For The Hsa Architecture, Stephen Adams
Exploration Into The Performance Of Asymmetric D-Ary Heap-Based Algorithms For The Hsa Architecture, Stephen Adams
Electronic Theses and Dissertations
No abstract provided.
An Efficient Storage And Retrieval Mechanism For Large Unstructured Grids, Oyindamola Akande
An Efficient Storage And Retrieval Mechanism For Large Unstructured Grids, Oyindamola Akande
Electronic Theses and Dissertations
The size of spatial scientific datasets is steadily increasing due to improvements in instruments and availability of computational resources. Scientific datasets today are often far too large to fit into a single machine's memory or even a single disk. However, much of the research on efficient storage and access to spatial datasets has focused on large multidimensional arrays. In contrast, unstructured grids consisting of collections of implices (e.g. triangles or tetrahedra) present special challenges that have received less attention. Data values found at the vertices of the simplices may be dispersed throughout a datafile, producing especially poor disk locality. Partitioning …