Computer Sciences Commons^™

Fault Tolerance: Validating A Mathematical Model Via A Case Study Of Raxml, An Hpc Community Code, Bidisha Chakraborty

Open Access Theses & Dissertations

Researchers have mentioned that the three most difficult and growing problems in the future of high-performance computing will be avoiding, coping and recovering from failures. As the scale of computing increases, the Mean Time to Failure (MTTF) of the entire system decreases and, therefore, system resilience and fault tolerance techniques become mandatory. One of the most commonly used fault tolerance schemes is checkpoint/restart, however, it has been predicted that the current checkpoint/restart approach is not scalable. Thus, current research seeks to find scalable fault tolerance techniques as well as to extend the scalability of checkpoint/restart.

The periodicity of the checkpointing …

Stereo Matching - Improving Image Quality, Aritra Dattagupta

Open Access Theses & Dissertations

Stereo vision or stereopsis is a biological process in which the impression of the depth of a scene viewed by the two eyes is perceived. Stereo vision helps us to see where objects are in relation to our bodies. Computational stereo describes the process of synthesizing the mechanics of binocular vision; and stereo matching is an important process in the problem of computational stereo.

Stereo matching is used for Digital Elevation Modeling (DEM), which is the method of extracting 3D information from digital images obtained by cameras and, therefore, is a crucial process for representing a 3D view of surfaces …

Decision Rule Induction For Service Sector Using Data Mining- A Rough Set Theory Approach, Zhonghua Hu

Open Access Theses & Dissertations

Nowadays, data mining is more widely used than ever before; not only by the academic area, but also in the industry and business area. Apart from execution of business processes, the creation of knowledge base and its utilization for the benefit of the organization is becoming a strategy tool to compete. Despite of having ever growing data bases, the problem is that the finance company fails to fully capitalize the true benefits which can be gained from this great wealth of information. The data mining technology instead of classic statistical analysis is developed to help the people to discover the …

A Robust Real Time Eye Tracking And Gaze Estimation System Using Particle Filters, Tariq Iqbal

Open Access Theses & Dissertations

Eye tracking and gaze estimation techniques have been extensively investigated by researchers in the computer vision and the psychology community for the last few decades. Still it remains a challenging task due to the individuality of the eyes, variability in shape, scale, location, and lighting conditions. Eye tracking has many applications in neuroscience, psychology, and human-computer interaction. Gaze estimation plays a vital role in the field of human attention analysis, human factors in industrial engineering, marketing and advertising, human cognitive state analysis, gaze-based interactive user interfaces, and monitoring driver vigilance systems.

Eye-tracking technology was originally a pioneer method in reading …

Algorithmic Aspects Of Analysis, Prediction, And Control In Science And Engineering: Symmetry-Based Approach, Jaime Nava

Open Access Theses & Dissertations

Algorithms are extremely important in science and engineering. One of the main objectives of science is to predict future events; this usually requires sophisticated algorithms. Once we are able to predict future events, a natural next step is to influence these events, i.e., to control the corresponding systems; control also usually requires complex algorithms. To be able to predict and control a system, we need to have a good description of this system, so that we can use this description to analyze the system's behavior and extract the desired prediction and control algorithms from this analysis. A typical prediction is …

Propagation Of Interval And Probabilistic Uncertainty In Cyberinfrastructure-Related Data Processing And Data Fusion, Christian Servin

Open Access Theses & Dissertations

Data uncertainty affects the results of data processing. So, it is necessary to find out how the data uncertainty propagates into the uncertainty of the results of data processing.

This problem is especially important when cyberinfrastructure enables us to process large amounts of heterogeneous data.

In the ideal world, we should have an accurate description of data

uncertainty, and well-justified efficient algorithms to propagate this uncertainty. In practice, we are often not yet in this ideal situation:

the description of uncertainty is often only approximate, and the algorithms for uncertainty propagation are often not well-justified and not very computationally efficient. …

Partial Orders For Representing Uncertainty, Causality And Decision Making: General Properties, Operations, And Algorithms, Francisco Adolfo Zapata

Open Access Theses & Dissertations

One of the main objectives of science and engineering is to help people select the most beneficial decisions. To make these decisions, we must know people's preferences, we must have the information about different possible consequences of different decisions. Since information is never absolutely accurate and precise, we must also have information about the degree of certainty of different parts on information. All these types of information naturally lead to partial orders:

- For preferences, a <= b means that b is preferable to a. This relation is used in decision theory.

- For events, a <= b means that a can influence b. This causality relation is one of the fundamental notions of physics, especially of physics of space-time.

* For uncertain statements, a <= b means that a is less certain than b. This relation is used in logics describing uncertainty, such as fuzzy logic.

In each of these areas, there is abundant research about studying the corresponding partial orders. …

Fusion Of Visual And Thermal Images Using Genetic Algorithms, Sertan Erkanli, Jiang Li, Ender Oguslu, Shangce Gao (Ed.)

Electrical & Computer Engineering Faculty Publications

No abstract provided.

An Investigation Into A Hybrid Genetic Programming And Ant Colony Optimization Method For Credit Scoring, Rojin Aliehyaei

Theses and Dissertations

This thesis proposes and investigates a new hybrid technique based on Genetic Programming (GP) and Ant Colony Optimization (ACO) techniques for inducing data classification rules. The proposed hybrid approach aims to improve on the accuracy of data classification rules produced by the original GP technique, which uses randomly generated initial populations. This hybrid technique relies on the ACO technique to produce the initial populations for the GP technique. To evaluate and compare their effectiveness in producing good data classification rules, GP, ACO, and hybrid techniques were implemented in the C programming language. The data classification rules were created and evaluated …

Procedurally Generating Everything, Micah Caunter

Senior Independent Study Theses

This paper investigates using Perlin Noise in a three-dimensional environment. Perlin Noise has been previously used to simulate clouds, marble, wood, and other natural phenomena as well as to model virtual landscapes. The simulation created for the I.S. procedurally generates both static and animated textures and models virtual landscapes to create a virtual world. In order to keep up with the rapidly advancing graphics industry, the OpenGL API is utilized to generate the textures in real-time and to display the final product.

Developing A Semantic Web Crawler To Locate Owl Documents, Ronald Dean Koron

Browse all Theses and Dissertations

The terms Semantic Web and OWL are relatively new and growing concepts in the World Wide Web. Because these concepts are so new there are relatively few applications and/or tools for utilizing the potential power of this new concept. Although there are many components to the Semantic Web, this thesis will focus on the research question, "How do we go about developing a web crawler for the Semantic Web that locates and retrieves OWL documents." Specifically for this thesis, we hypothesize that by giving URIs to OWL documents, including all URIs from within these OWL documents, priority over other types …

Human Action Recognition By Principal Component Analysis Of Motion Curves, Daniel Stephen Chivers

Browse all Theses and Dissertations

Human action recognition is used to automatically detect and recognize actions per- formed by humans in a video. Applications include visual surveillance, human-computer interaction, and robot intelligence, to name a few. An example of a surveillance application is a system that monitors a large public area, such as an airport, for suspicious activity. In human-machine interaction, computers may be controlled by simple human actions. For example, the motion of an arm may instruct the computer to rotate a 3-D model that is being displayed. Human action recognition is also an important capability of intelligent robots that interact with humans.

General …

A New Semantic Similarity Join Method Using Diffusion Maps And Long String Table Attributes, Bilal Hani Hawashin

Wayne State University Dissertations

With the rapid increase of the distributed data sources, and in order to make information integration, there is a need to combine the information that refers to the same entity from different sources. However, there are no global conventions that control the format of the data, and it is impractical to impose such global conventions. Also, there could be some spelling errors in the data as it is entered manually in most of the cases. For such reasons, the need to find and join similar records instead of exact records is important in order to integrate the data. Most of …

Querying And Managing Opm-Compliant Scientific Workflow Provenance, Chunhyeok Lim

Wayne State University Dissertations

Provenance, the metadata that records the derivation history of scientific results, is important in scientific workflows to interpret, validate, and analyze the result of scientific computing. Recently,

to promote and facilitate interoperability among heterogeneous provenance systems, the Open Provenance Model (OPM) has been proposed and has played an important role in the community.

In this dissertation, to efficiently query and manage OPM-compliant provenance, we first propose a provenance collection framework that collects both prospective provenance, which captures

an abstract workflow specification as a recipe for future data derivation and retrospective provenance, which captures past workflow execution and data derivation information. …

Effective Semantic-Based Keyword Search Over Relational Databases For Knowledge Discovery, Sina Fakhraee

Wayne State University Dissertations

Keyword-based search has been popularized by Internet web search engines such as Google which is the most commonly used search engine to locate the information on the web. On the other hand while traditional database management systems offer powerful query languages such as SQL, they do not provide keyword-based search similar to the one provided by web search engines. The current amount of text data in relational databases is massive and is growing fast. This increases the importance and need for non-technical users to be able to search for such information using simple keyword search just as how they would …

Systems Support For Genomics Computing In Cloud Environments, Tung Thanh Nguyen

Wayne State University Dissertations

Genomics research has enormous applications in many areas such as health care, forensic, agriculture, etc. Most recent achievements in this field come from the availability of the unprecedented genomic data. However, new sequencing technologies in genomics keep producing data at a faster pace resulting a very huge amount of data. This poses great challenges on how to store, manage, process and analyze the data efficiently. To deal with these, genomics research groups often equip themselves with a small scale server room composed of high storage capacity and computing ability machines. This solution is not only costly, unscalable but also inefficient. …

Differential Modeling For Cancer Microarray Data, Omar Odibat

Wayne State University Dissertations

Capturing the changes between two biological phenotypes is a crucial task in understanding the mechanisms of various diseases. Most of the existing computational approaches depend on testing the changes in the expression levels of each single gene individually. In this work, we proposed novel computational approaches to identify the differential genes between two phenotypes. These approaches aim to quantitatively characterize the differences between two phenotypes and can provide better insights and understanding of various diseases. The purpose of this thesis is three-fold. Firstly, we review the state-of-the-art approaches for differential analysis of gene expression data.

Secondly, we propose a novel …

Rethinking The Design And Implementation Of The I/O Software Stack For High-Performance Computing, Xuechen Zhang

Wayne State University Dissertations

Current I/O stack for high-performance computing is composed of multiple software layers in order to hide users from complexity of I/O performance optimization. However, the design and implementation of a specific layer is usually carried out separately with limited consideration of its impact on other layers, which could result in suboptimal I/O performance because data access locality is weakened, if not lost, on hard disk, a widely used storage medium in high-end storage systems.

In this dissertation, we experimentally demonstrated such issues in four different layers, including operating system process management layer and MPI-IO middleware layer on compute server side, …

Bringing To Life An Ancient Urban Center At Monte Albán, Mexico: Exploiting The Synergy Between The Micro, Meso, And Macro Levels In A Complex System, Thaer W. Jayyousi

Wayne State University Dissertations

In this dissertation, agent-based models of emergent ancient urban centers were constructed through the use of techniques from computational intelligence, agent-based modeling, complex systems, and data-mining of existing archaeological data from the prehistoric urban center, Monte Albán. This real world application was selected because of its importance in understanding the emergence of modern economic and political systems. Specifically, Cultural Algorithms was used to evolve models of early Monte Alban, models that can then be compared with existing models of ancient and modern urban centers.

Features of a complex system were used to help interpret the archaeological data. The analysis went …

Location Privacy In Emerging Network-Based Applications, Yong Xi

Wayne State University Dissertations

With the wide spread of computer systems and networks, privacy has become an issue that increasingly attracts attention. In wireless sensor networks, the location of an event source may be subject to unintentional disclosure through traffic analysis by the attacker. In vehicular networks, authentication leaves a trail to tie a driver to a sequence of time and space coordinates. In a cloud-based navigation system, the location information of a sensitive itinerary is disclosed. Those scenarios have shown that privacy protection is a far-reaching problem that could span many different aspects of a computer/network system, especially on a diversified landscape of …

An Ssvep Brain-Computer Interface: A Machine Learning Approach, Fei Teng

Electronic Theses and Dissertations

A Brain-Computer Interface (BCI) provides a bidirectional communication path for a human to control an external device using brain signals. Among neurophysiological features in BCI systems, steady state visually evoked potentials (SSVEP), natural responses to visual stimulation at specific frequencies, has increasingly drawn attentions because of its high temporal resolution and minimal user training, which are two important parameters in evaluating a BCI system. The performance of a BCI can be improved by a properly selected neurophysiological signal, or by the introduction of machine learning techniques. With the help of machine learning methods, a BCI system can adapt to the …

An Investigation Into Feature Selection For Oncological Survival Prediction, Dmitry Strunkin, Brian Mac Namee, John D. Kelleher

Conference papers

In machine learning based clinical decision support (CDS) systems the features used to train prediction models are of paramount importance. Strong features will lead to accurate models, whereas as weak features will have the opposite effect. Feature sets can either be designed by domain experts, or automatically extracted for unstructured data that happens to be available from some process other than a CDS system. This paper compares the usefulness of structured expert-designed features to features extracted from unstructured data sources in an oncological survival prediction application scenario.

Formalising Human Mental Workload As Non-Montonic Concept For Adaptive And Personalised Web-Design, Luca Longo

Books/Book Chapters

Web Design has been evolving with Web-based systems becoming more complex and structured due to the delivery of personalised information adapted to end-users. Although information presented can be useful and well formatted, people have little mental workload available for dealing with unusable systems. Subjective mental workload assessments tools are usually adopted to measure the impact of Web-tasks upon end-users thanks to their ease of use and are aimed at supporting design practices. The Nasa Task Load Index subjective procedure has been taken as a reference technique for measuring mental workload, but it has a background in aircraft cockpits, supervisory and …

Developing A Promo Video In Premiere Elements: A Day In Dublin, Jerome Casey

Instructional Guides

No abstract provided.

Characterizing Conflict In Wikipedia, Nathaniel Miller

Mathematics, Statistics, and Computer Science Honors Projects

Wikipedia serves as the Internet's most widely viewed reference. In order to ensure its success, editors who create and maintain articles must resolve conflicts over appropriate article content. Previous research has measured Wikipedia conflict at two levels: single articles and categories of pages. I observe conflicts within small groups of articles, identifying their frequency, size, and intensity. Additionally, I identify individual conflicts spanning multiple articles and effects of conflict upon users' editing habits. I analyze cross-article conflict in three stages. First, I cluster a group of 1.4 million Wikipedia articles. Next, I find individual user conflicts within each article cluster …

Behavioral Signature-Based Framework For Identifying Unsatisfiable Variable Mappings Between Digital Designs, Vaibhav Uday Tendulkar

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Throughout its design process (from specification to implementation) a digital circuit goes through a variety of structural changes. These changes are introduced primarily due to the use of automated tools in the design process. Checking whether the Boolean functions representing the two designs are equivalent is thus necessary to verify if a design implementation adheres to its specification. Combinational Equivalence Checking (CEC) - a process of determining whether two combinational design functions are equiv-alent, has been one of the most researched Boolean matching problems. The well-known CEC techniques that have been proposed adopt some kind of a formal approach such …

Smart Card Based User Authentication, Brandon James

Browse all Theses and Dissertations

User authentication plays a very important role in building a secure computing system. In this thesis, we first studied and investigated existing user authentication schemes and some basic concepts of smart cards. We then proposed and implemented an improved user authentication scheme based on the smart card, specifically, Java card. We simulated a web server, and implemented the user authentication scheme with the Java card by programming a Java card applet and a Java program to send commands and receive responses from the card.

The proposed user authentication scheme has two phases: the registration phase and the user authentication phase. …

Knn-R: Building Secure And Efficient Outsourced Knn Query Service With The Rasp Encryption, Huiqi Xu

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With the wide deployment of public cloud computing infrastructures, outsourcing database services to the cloud has become an appealing solution to save operating expense. However, some databases might be so sensitive or precious that the data owner does not want to move to the cloud unless the security is guaranteed. On the other hand, a secure outsourced service should still provide efficient query processing and significantly reduce the inhouse workload to fully realize the benefits of outsourcing. We summarize these key features for an outsourced service as the CPEL criteria: data Confidentiality, query Privacy, Efficient query processing, and Low inhouse …

Direct Optimization Of Ranking Measures For Learning To Rank Models, Li Li Guo

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The main challenge in learning-to-rank for information retrieval is the difficulty to di- rectly optimize ranking measures to automatically construct a ranking model from training data. It is mainly due to the fact that the ranking measures are determined by the order of ranked documents rather than the specific values of ranking model scores, thus they are non-convex, nondifferentiable and discontinuous. To address this issue, listwise approaches have been proposed where loss functions are defined either by exploiting a probabilistic model or by optimizing upper bounds or smoothed approximations of ranking measures. Even though very promising results have been achieved, …

Linked Open Data Alignment & Querying, Prateek Jain

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The recent emergence of the "Linked Data" approach for publishing data represents a major step forward in realizing the original vision of a web that can "understand and satisfy the requests of people and machines to use the web content" i.e. the Semantic Web. This new approach has resulted in the Linked Open Data (LOD) Cloud, which includes more than 295 large datasets contributed by experts belonging to diverse communities such as geography, entertainment, and life sciences. However, the current interlinks between datasets in the LOD Cloud, as we will illustrate,are too shallow to realize much of the benefits promised. …